xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

40290e453dc415a935e77faf36f362c1b48c02aa

176

py

Python

digits/model/tasks/__init__.py

ZeusNightBolt/DIGITS

3450cc683143415418af5ecdb1b17b02da3e2c79

[ "BSD-3-Clause" ]

2

2017-04-24T10:16:15.000Z

2019-02-26T09:36:27.000Z

digits/model/tasks/__init__.py

ZeusNightBolt/DIGITS

3450cc683143415418af5ecdb1b17b02da3e2c79

[ "BSD-3-Clause" ]

1

2016-08-30T23:48:17.000Z

digits/model/tasks/__init__.py

ZeusNightBolt/DIGITS

3450cc683143415418af5ecdb1b17b02da3e2c79

[ "BSD-3-Clause" ]

3

2017-04-24T10:16:15.000Z

2019-02-26T09:36:49.000Z

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py

Python

credentials/providers/passport/exceptions.py

ad-m/h1-credentials-helper-python

2c3e0d9c57ea4a37349debbbe7bc640bc326e5e3

[ "MIT" ]

null

credentials/providers/passport/exceptions.py

ad-m/h1-credentials-helper-python

2c3e0d9c57ea4a37349debbbe7bc640bc326e5e3

[ "MIT" ]

null

credentials/providers/passport/exceptions.py

ad-m/h1-credentials-helper-python

2c3e0d9c57ea4a37349debbbe7bc640bc326e5e3

[ "MIT" ]

null

from credentials.exceptions import CredentialsException class InvalidPassportException(CredentialsException): pass

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py

Python

dfval/tests/tests_dfcheck.py

ashendrickson/dfval

99e758edfb76e4069ef0c4fe1085f1fa76b4cd23

[ "Apache-2.0" ]

5

2020-10-12T23:24:47.000Z

2022-02-18T20:20:58.000Z

dfval/tests/tests_dfcheck.py

ashendrickson/dfval

99e758edfb76e4069ef0c4fe1085f1fa76b4cd23

[ "Apache-2.0" ]

null

dfval/tests/tests_dfcheck.py

ashendrickson/dfval

99e758edfb76e4069ef0c4fe1085f1fa76b4cd23

[ "Apache-2.0" ]

1

2020-09-28T15:04:16.000Z

import unittest from dfval import dups_check from dfval import column_names_check import pandas as pd class TestCheck(unittest.TestCase): def setUp(self): self.d_dups = [[3, '2019-12-15'], [3, '2019-12-15'], [3, '2019-12-15'], [3, '2019-12-08']] self.df_dups = pd.DataFrame(self.d_dups, columns = ['co_loc_ref_i', 'wk_beg_d']) self.d_no_dups = [[3, '2019-12-15'], [3, '2019-12-22'], [3, '2019-12-29'], [3, '2019-12-08']] self.df_no_dups = pd.DataFrame(self.d_no_dups, columns = ['co_loc_ref_i', 'wk_beg_d']) self.k = ['co_loc_ref_i', 'wk_beg_d'] self.d_column_names = [[3, '2019-12-15'], [3, '2019-12-15'], [3, '2019-12-15'], [3, '2019-12-08']] self.df_column_names = pd.DataFrame(self.d_dups, columns = ['co_loc_ref_i', 'wk_beg_d']) self.expected_column_names_match = ['co_loc_ref_i', 'wk_beg_d'] self.expected_column_names_diff = ['co_loc_i', 'wk_beg_d'] def test_dups(self): dups = dups_check(self.df_dups, self.k) self.assertEqual(len(dups.index), 2) def test_no_dups(self): dups = dups_check(self.df_no_dups, self.k) self.assertEqual(len(dups.index), 0) def test_column_names_match(self): column_names_result = column_names_check(self.df_column_names, self.expected_column_names_match) self.assertEqual(len(column_names_result[column_names_result['column_check_pass'] == 'True'].index), 2) self.assertEqual(len(column_names_result[column_names_result['column_check_pass'] == 'False'].index), 0) def test_column_names_diff(self): column_names_result = column_names_check(self.df_column_names, self.expected_column_names_diff) self.assertEqual(len(column_names_result[column_names_result['column_check_pass'] == 'True'].index), 1) self.assertEqual(len(column_names_result[column_names_result['column_check_pass'] == 'False'].index), 1) if __name__ == '__main__': unittest.main()

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py

Python

medialog/googlefonts/vocabularies.py

collective/medialog.googlefonts

4ea2fd2a71241af4b712295a2d240d89e4cc1e52

[ "BSD-Source-Code" ]

null

medialog/googlefonts/vocabularies.py

collective/medialog.googlefonts

4ea2fd2a71241af4b712295a2d240d89e4cc1e52

[ "BSD-Source-Code" ]

null

medialog/googlefonts/vocabularies.py

collective/medialog.googlefonts

4ea2fd2a71241af4b712295a2d240d89e4cc1e52

[ "BSD-Source-Code" ]

null

from zope.schema.vocabulary import SimpleVocabulary, SimpleTerm from zope.schema.interfaces import IVocabularyFactory from zope.interface import directlyProvides from medialog.googlefonts import messageFactory as _ FONTS = [ "Abel", "Abril Fatface", "Aclonica", "Allan", "Allerta Stencil", "Allerta", "Amaranth", "Annie Use Your Telescope", "Anonymous Pro", "Anton", "Architects Daughter", "Arimo", "Arvo", "Astloch", "Bangers", "Bentham", "Bevan", "Buda", "Cabin", "Calligraffitti", "Candal", "Cantarell", "Cardo", "Cherry Cream Soda", "Chewy", "Coda", "Coming Soon", "Copse", "Corben", "Cousine", "Covered By Your Grace", "Crafty Girls", "Crimson Text", "Crushed", "Cuprum", "Damion", "Dancing Script", "Dawning of a New Day", "Droid Sans Mono", "Droid Sans", "Droid Serif", "EB Garamond", "Expletus Sans", "Fontdiner Swanky", "Geo", "Goudy Bookletter 1911", "Gruppo", "Homemade Apple", "IM Fell", "Inconsolata", "Indie Flower", "Irish Grover", "Josefin Sans", "Josefin Slab", "Just Another Hand", "Just Me Again Down Here", "Kenia", "Kranky", "Kreon", "Kristi", "Lato", "League Script", "Lekton", "Lobster", "Luckiest Guy", "Maiden Orange", "Meddon", "MedievalSharp", "Merriweather", "Michroma", "Miltonian", "Molengo", "Montserrat", "Neucha", "News Cycle", "Nobile", "Nova Round", "OFL Sorts Mill Goudy TT", "Old Standard TT", "Orbitron", "Oswald", "Over the Rainbow", "Pacifico by Vernon Adams ", "Pacifico", "Permanent Marker", "Philosopher", "PT Sans", "PT Serif", "Puritan", "Quattrocento Sans", "Quattrocento", "Radley by Vernon Adams", "Radley", "Raleway", "Reenie Beanie", "Rock Salt", "Schoolbell", "Six Caps", "Slackey", "Smythe", "Sniglet", "Special Elite", "Sue Ellen Francisco", "Sunshiney", "Swanky and Moo Moo", "Syncopate", "Tangerine", "Terminal Dosis Light", "The Girl Next Door", "Tinos", "Ubuntu", "UnifrakturMaguntia", "Unkempt", "Vibur", "Vollkorn", "VT323", "Waiting for the Sunrise", "Yanone Kaffeesatz", "** ----- more fonts ----- **", "ABeeZee", "Acme", "Actor", "Adamina", "Advent Pro", "Aguafina Script", "Akronim", "Aladin", "Aldrich", "Alef", "Alegreya Sans SC", "Alegreya Sans", "Alegreya SC", "Alegreya", "Alex Brush", "Alfa Slab One", "Alice", "Alike Angular", "Alike", "Allura", "Almendra Display", "Almendra SC", "Almendra", "Amarante", "Amatic SC", "Amethysta", "Anaheim", "Andada", "Andika", "Antic Didone", "Antic Slab", "Antic", "Arapey", "Arbutus Slab", "Arbutus", "Archivo Black", "Archivo Narrow", "Arizonia", "Armata", "Artifika", "Asap", "Asset", "Asul", "Atomic Age", "Aubrey", "Audiowide", "Autour One", "Average Sans", "Average", "Averia Gruesa Libre", "Averia Libre", "Averia Sans Libre", "Averia Serif Libre", "Bad Script", "Balthazar", "Basic", "Baumans", "Belgrano", "Belleza", "BenchNine", "Berkshire Swash", "Bigelow Rules", "Bigshot One", "Bilbo Swash Caps", "Bilbo", "Bitter", "Black Ops One", "Bonbon", "Boogaloo", "Bowlby One SC", "Bowlby One", "Brawler", "Bree Serif", "Bubblegum Sans", "Bubbler One", "Buenard", "Butcherman", "Butterfly Kids", "Cabin Condensed", "Cabin Sketch", "Caesar Dressing", "Cagliostro", "Cambo", "Cantata One", "Cantora One", "Capriola", "Carme", "Carrois Gothic SC", "Carrois Gothic", "Carter One", "Caudex", "Cedarville Cursive", "Ceviche One", "Changa One", "Chango", "Chau Philomene One", "Chela One", "Chelsea Market", "Cherry Swash", "Chicle", "Chivo", "Cinzel Decorative", "Cinzel", "Clicker Script", "Coda Caption", "Codystar", "Combo", "Comfortaa", "Concert One", "Condiment", "Contrail One", "Convergence", "Cookie", "Courgette", "Coustard", "Creepster", "Crete Round", "Croissant One", "Cutive Mono", "Cutive", "Days One", "Delius Swash Caps", "Delius Unicase", "Delius", "Della Respira", "Denk One", "Devonshire", "Didact Gothic", "Diplomata SC", "Diplomata", "Domine", "Donegal One", "Doppio One", "Dorsa", "Dosis", "Dr Sugiyama", "Duru Sans", "Dynalight", "Eagle Lake", "Eater", "Economica", "Electrolize", "Elsie Swash Caps", "Elsie", "Emblema One", "Emilys Candy", "Engagement", "Englebert", "Enriqueta", "Erica One", "Esteban", "Euphoria Script", "Ewert", "Exo 2", "Exo", "Fanwood Text", "Fascinate Inline", "Fascinate", "Faster One", "Fauna One", "Federant", "Federo", "Felipa", "Fenix", "Finger Paint", "Fjalla One", "Fjord One", "Flamenco", "Flavors", "Fondamento", "Forum", "Francois One", "Freckle Face", "Fredericka the Great", "Fredoka One", "Fresca", "Frijole", "Fruktur", "Fugaz One", "Gabriela", "Gafata", "Galdeano", "Galindo", "Gentium Basic", "Gentium Book Basic", "Geostar Fill", "Geostar", "Germania One", "Gilda Display", "Give You Glory", "Glass Antiqua", "Glegoo", "Gloria Hallelujah", "Goblin One", "Gochi Hand", "Gorditas", "Graduate", "Grand Hotel", "Gravitas One", "Great Vibes", "Griffy", "Gudea", "Habibi", "Hammersmith One", "Hanalei Fill", "Hanalei", "Handlee", "Happy Monkey", "Headland One", "Henny Penny", "Herr Von Muellerhoff", "Holtwood One SC", "Homenaje", "Iceberg", "Iceland", "IM Fell Double Pica SC", "IM Fell Double Pica", "IM Fell DW Pica SC", "IM Fell DW Pica", "IM Fell English SC", "IM Fell English", "IM Fell French Canon SC", "IM Fell French Canon", "IM Fell Great Primer SC", "IM Fell Great Primer", "Imprima", "Inder", "Inika", "Istok Web", "Italiana", "Italianno", "Jacques Francois Shadow", "Jacques Francois", "Jim Nightshade", "Jockey One", "Jolly Lodger", "Joti One", "Judson", "Julee", "Julius Sans One", "Junge", "Jura", "Kameron", "Karla", "Kaushan Script", "Kavoon", "Keania One", "Kelly Slab", "Kite One", "Knewave", "Kotta One", "Krona One", "La Belle Aurore", "Lancelot", "Leckerli One", "Ledger", "Lemon", "Libre Baskerville", "Life Savers", "Lilita One", "Lily Script One", "Limelight", "Linden Hill", "Lobster Two", "Londrina Outline", "Londrina Shadow", "Londrina Sketch", "Londrina Solid", "Lora", "Love Ya Like A Sister", "Loved by the King", "Lovers Quarrel", "Lusitana", "Lustria", "Macondo Swash Caps", "Macondo", "Magra", "Mako", "Marcellus SC", "Marcellus", "Marck Script", "Margarine", "Marko One", "Marmelad", "Marvel", "Mate SC", "Mate", "Maven Pro", "McLaren", "Medula One", "Megrim", "Meie Script", "Merienda One", "Merienda", "Merriweather Sans", "Metal Mania", "Metamorphous", "Metrophobic", "Milonga", "Miltonian Tattoo", "Miniver", "Miss Fajardose", "Modern Antiqua", "Molle", "Monda", "Monofett", "Monoton", "Monsieur La Doulaise", "Montez", "Montserrat Alternates", "Montserrat Subrayada", "Mountains of Christmas", "Mouse Memoirs", "Mr Bedfort", "Mr Dafoe", "Mr De Haviland", "Mrs Saint Delafield", "Mrs Sheppards", "Muli", "Mystery Quest", "Neuton", "New Rocker", "Niconne", "Nixie One", "Norican", "Nosifer", "Nothing You Could Do", "Noticia Text", "Noto Sans", "Noto Serif", "Nova Cut", "Nova Flat", "Nova Mono", "Nova Oval", "Nova Script", "Nova Slim", "Nova Square", "Numans", "Nunito", "Offside", "Oldenburg", "Oleo Script Swash Caps", "Oleo Script", "Open Sans Condensed", "Open Sans", "Oranienbaum", "Oregano", "Orienta", "Original Surfer", "Overlock SC", "Overlock", "Ovo", "Oxygen Mono", "Paprika", "Parisienne", "Passero One", "Passion One", "Pathway Gothic One", "Patrick Hand SC", "Patrick Hand", "Patua One", "Paytone One", "Peralta", "Petit Formal Script", "Petrona", "Piedra", "Pinyon Script", "Pirata One", "Plaster", "Play", "Playball", "Playfair Display SC", "Playfair Display", "Podkova", "Poiret One", "Poller One", "Poly", "Pompiere", "Pontano Sans", "Port Lligat Sans", "Port Lligat Slab", "Prata", "Press Start 2P", "Princess Sofia", "Prociono", "Prosto One", "PT Mono", "PT Sans Caption", "PT Sans Narrow", "PT Serif Caption", "Purple Purse", "Quando", "Quantico", "Questrial", "Quicksand", "Quintessential", "Qwigley", "Racing Sans One", "Raleway Dots", "Rambla", "Rammetto One", "Ranchers", "Rancho", "Rationale", "Redressed", "Revalia", "Ribeye Marrow", "Ribeye", "Righteous", "Risque", "Roboto Condensed", "Roboto Slab", "Roboto", "Rochester", "Rokkitt", "Romanesco", "Ropa Sans", "Rosario", "Rosarivo", "Rouge Script", "Ruda", "Rufina", "Ruge Boogie", "Ruluko", "Rum Raisin", "Ruslan Display", "Russo One", "Ruthie", "Rye", "Sacramento", "Sail", "Salsa", "Sanchez", "Sancreek", "Sansita One", "Sarina", "Satisfy", "Scada", "Seaweed Script", "Sevillana", "Seymour One", "Shadows Into Light Two", "Shadows Into Light", "Shanti", "Share Tech Mono", "Share Tech", "Share", "Shojumaru", "Short Stack", "Sigmar One", "Signika Negative", "Signika", "Simonetta", "Sintony", "Sirin Stencil", "Skranji", "Smokum", "Snippet", "Snowburst One", "Sofadi One", "Sofia", "Sonsie One", "Sorts Mill Goudy", "Source Code Pro", "Source Sans Pro", "Spicy Rice", "Spinnaker", "Spirax", "Squada One", "Stalemate", "Stalinist One", "Stardos Stencil", "Stint Ultra Condensed", "Stint Ultra Expanded", "Stoke", "Strait", "Supermercado One", "Tauri", "Telex", "Tenor Sans", "Text Me One", "Tienne", "Titan One", "Titillium Web", "Trade Winds", "Trocchi", "Trochut", "Trykker", "Tulpen One", "Ubuntu Condensed", "Ubuntu Mono", "Ultra", "Uncial Antiqua", "Underdog", "Unica One", "UnifrakturCook", "Unlock", "Unna", "Vampiro One", "Varela Round", "Varela", "Vast Shadow", "Vidaloka", "Viga", "Voces", "Volkhov", "Voltaire", "Wallpoet", "Walter Turncoat", "Warnes", "Wellfleet", "Wendy One", "Wire One", "Yellowtail", "Yeseva One", "Yesteryear", "Zeyada", ] def fonts(self): return FONTS def format_font(font): return font.replace(" ", "+") def FontsVocabulary(context): terms = [SimpleTerm(value=format_font(pair), token=format_font(pair), title=pair) for pair in FONTS] return SimpleVocabulary(terms) directlyProvides(FontsVocabulary, IVocabularyFactory)

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py

Python

tests/test_problem_testset.py

feimeng93/probabilistic-bvp-solver

d6b38d4ff7b3ab6cf3003de30eb2f6eeb42c0beb

[ "MIT" ]

null

tests/test_problem_testset.py

feimeng93/probabilistic-bvp-solver

d6b38d4ff7b3ab6cf3003de30eb2f6eeb42c0beb

[ "MIT" ]

null

tests/test_problem_testset.py

feimeng93/probabilistic-bvp-solver

d6b38d4ff7b3ab6cf3003de30eb2f6eeb42c0beb

[ "MIT" ]

null

"""Assert that the jacobians are implemented correctly.""" import sys sys.path.append("..") import numpy as np import pytest from bvps.problem_testset import testset_firstorder @pytest.fixture def dt(): return 1e-6 @pytest.fixture def rtol(): return 1e-6 @pytest.fixture def bvp1st(): return testset_firstorder() @all_first_order_bvps def test_jacobians_1st(bvp1st, dt, rtol): bvp_dim = len(bvp1st.R.T) random_direction = 1 + 0.1 * np.random.rand(bvp_dim) random_point = 1 + np.random.rand(bvp_dim) f1 = bvp1st.f(bvp1st.t0, random_point + dt * random_direction) f2 = bvp1st.f(bvp1st.t0, random_point - dt * random_direction) fd_approx = (f1 - f2) / (2 * dt) true_df = bvp1st.df(bvp1st.t0, random_point) assert f1.ndim == 1 assert f2.ndim == 1 assert true_df.ndim == 2 np.testing.assert_allclose( true_df @ random_direction, fd_approx, rtol=rtol, ) @all_second_order_bvps def test_jacobians_2nd_dy(bvp2nd, dt, rtol): bvp_dim = len(bvp2nd.R.T) // 2 random_direction = 1 + 0.1 * np.random.rand(bvp_dim) random_point = 1 + np.random.rand(bvp_dim) f1 = bvp2nd.f(bvp2nd.t0, random_point + dt * random_direction, random_point) f2 = bvp2nd.f(bvp2nd.t0, random_point - dt * random_direction, random_point) fd_approx = (f1 - f2) / (2 * dt) true_df = bvp2nd.df_dy(bvp2nd.t0, random_point, random_point) assert f1.ndim == 1 assert f2.ndim == 1 assert true_df.ndim == 2 np.testing.assert_allclose( true_df @ random_direction, fd_approx, rtol=rtol, ) @all_second_order_bvps def test_jacobians_2nd_ddy(bvp2nd, dt, rtol): bvp_dim = len(bvp2nd.R.T) // 2 random_direction = 1 + 0.1 * np.random.rand(bvp_dim) random_point = 1 + np.random.rand(bvp_dim) f1 = bvp2nd.f(bvp2nd.t0, random_point, random_point + dt * random_direction) f2 = bvp2nd.f(bvp2nd.t0, random_point, random_point - dt * random_direction) fd_approx = (f1 - f2) / (2 * dt) true_df = bvp2nd.df_ddy(bvp2nd.t0, random_point, random_point) assert f1.ndim == 1 assert f2.ndim == 1 assert true_df.ndim == 2 np.testing.assert_allclose( true_df @ random_direction, fd_approx, rtol=rtol, )

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py

Python

backend/src/pox/ext/gini/core/openflow_keepalive.py

anrl/gini4

d26649c8c02a1737159e48732cf1ee15ba2a604d

[ "MIT" ]

11

2019-03-02T20:39:34.000Z

2021-09-02T19:47:38.000Z

backend/src/pox/ext/gini/core/openflow_keepalive.py

anrl/gini4

d26649c8c02a1737159e48732cf1ee15ba2a604d

[ "MIT" ]

29

2019-01-17T15:44:48.000Z

2021-06-02T00:19:40.000Z

backend/src/pox/ext/gini/core/openflow_keepalive.py

anrl/gini4

d26649c8c02a1737159e48732cf1ee15ba2a604d

[ "MIT" ]

11

2019-01-28T05:00:55.000Z

2021-11-12T03:08:32.000Z

#!/usr/bin/python2 from openflow import keepalive def launch(): keepalive.launch()

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81

py

Python

juno/server/http/handler/base/html_handler.py

DSciLab/juno

1d572c8d3fd06a6c1fcc51b42a6539dd3ae0927e

[ "MIT" ]

null

juno/server/http/handler/base/html_handler.py

DSciLab/juno

1d572c8d3fd06a6c1fcc51b42a6539dd3ae0927e

[ "MIT" ]

null

juno/server/http/handler/base/html_handler.py

DSciLab/juno

1d572c8d3fd06a6c1fcc51b42a6539dd3ae0927e

[ "MIT" ]

null

import tornado.web class HTMLBaseHandler(tornado.web.RequestHandler): pass

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1

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null

0

1

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6

4644c5e162ff3a683854049f6be8b74fc72d0421

228

py

Python

generate_tfrecord.py

xiekai301/211011-CropGAN

6ea23b14fb8e5687313b65f98c42cc74cb9b5097

[ "Apache-2.0" ]

null

generate_tfrecord.py

xiekai301/211011-CropGAN

6ea23b14fb8e5687313b65f98c42cc74cb9b5097

[ "Apache-2.0" ]

null

generate_tfrecord.py

xiekai301/211011-CropGAN

6ea23b14fb8e5687313b65f98c42cc74cb9b5097

[ "Apache-2.0" ]

null

from TFRecord_utils import create_tfrdataset # import tensorflow as tf create_tfrdataset(PATH='dataset/train', tfrecord_file='dataset/train.tfrecord') create_tfrdataset(PATH='dataset/test', tfrecord_file='dataset/test.tfrecord')

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null

0

1

0

1

0

6

d3b5b6b6c0c3358b29f7c54fd0b70e0e340aad92

154

py

Python

enumfields/__init__.py

druids/django-enumfields

0afc244666f7b6ca4dd0f915f6ec2e8ab21220c1

[ "MIT" ]

2

2019-05-21T12:30:02.000Z

2020-02-18T15:13:26.000Z

enumfields/__init__.py

druids/django-enumfields

0afc244666f7b6ca4dd0f915f6ec2e8ab21220c1

[ "MIT" ]

2

2019-05-24T07:34:41.000Z

2020-06-29T14:30:18.000Z

enumfields/__init__.py

druids/django-enumfields

0afc244666f7b6ca4dd0f915f6ec2e8ab21220c1

[ "MIT" ]

3

2019-05-21T12:30:06.000Z

2021-11-08T19:54:30.000Z

from .enums import IntegerChoicesEnum, TextChoicesEnum, Choice from .fields import CharEnumField, CharEnumSubField, IntegerEnumField, IntegerEnumSubField

51.333333

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0.87013

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154

10.307692

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1

0

1

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1

0

6

d3ca77f418be45140135f96542be48477643b573

60

py

Python

mkdocsthemebootstrap4/__init__.py

LukeCarrier/mkdocs-bootstrap4

19354c9d5516d56342ecfb7f18b6b59ca85ec935

[ "MIT" ]

3

2019-11-04T13:39:31.000Z

2020-11-28T05:42:22.000Z

mkdocsthemebootstrap4/__init__.py

LukeCarrier/mkdocs-bootstrap4

19354c9d5516d56342ecfb7f18b6b59ca85ec935

[ "MIT" ]

8

2019-12-22T13:33:38.000Z

2021-07-15T03:12:38.000Z

mkdocsthemebootstrap4/__init__.py

LukeCarrier/mkdocs-theme-bootstrap4

19354c9d5516d56342ecfb7f18b6b59ca85ec935

[ "MIT" ]

null

from .plugin import Bootstrap4Blockquotes, Bootstrap4Tables

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null

0

1

0

1

0

1

0

6

d3e7d66280cfebfb75607cb4f2fd3d873e12486a

229

py

Python

diameter/node/AVP_FailedAVP.py

tj8000rpm/PythonDiameter-0.7

539c4fb7658fc880ddb4ba175cdcce852d1e604d

[ "Zlib" ]

null

diameter/node/AVP_FailedAVP.py

tj8000rpm/PythonDiameter-0.7

539c4fb7658fc880ddb4ba175cdcce852d1e604d

[ "Zlib" ]

null

diameter/node/AVP_FailedAVP.py

tj8000rpm/PythonDiameter-0.7

539c4fb7658fc880ddb4ba175cdcce852d1e604d

[ "Zlib" ]

null

from diameter.AVP_Grouped import AVP_Grouped import diameter.ProtocolConstants class AVP_FailedAVP(AVP_Grouped): def __init__(self,a,vendor_id=0): AVP_Grouped.__init__(self,[a],vendor_id) def _unittest(): pass

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0

null

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1

0

1

0

1

0

6

31070dc2621413c13a281bb6d25f983595110ba6

217

py

Python

djangopj/geo/admin.py

hikarine3/docker-django

ddcb15fa741993c3098a4f6bebbdaa498c27ac20

[ "MIT" ]

25

2019-11-19T07:16:20.000Z

2021-11-09T11:04:15.000Z

djangopj/geo/admin.py

hikarine3/docker-django

ddcb15fa741993c3098a4f6bebbdaa498c27ac20

[ "MIT" ]

6

2020-05-16T10:51:09.000Z

2021-09-22T19:01:51.000Z

djangopj/geo/admin.py

hikarine3/docker-django

ddcb15fa741993c3098a4f6bebbdaa498c27ac20

[ "MIT" ]

1

2019-03-26T05:33:01.000Z

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

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null

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1

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1

0

6

312de341942ad2a8115d0c49f1bbeaa787705ac1

43

py

Python

bin/__init__.py

MFSJMenger/pysurf

99c6a94d4cb5046f16a0961b907061d989ffb6dc

[ "Apache-2.0" ]

7

2020-10-28T13:46:08.000Z

2021-05-27T06:41:56.000Z

bin/__init__.py

MFSJMenger/pysurf

99c6a94d4cb5046f16a0961b907061d989ffb6dc

[ "Apache-2.0" ]

2

2020-10-27T19:15:12.000Z

2020-10-27T19:15:25.000Z

bin/__init__.py

MFSJMenger/pysurf

99c6a94d4cb5046f16a0961b907061d989ffb6dc

[ "Apache-2.0" ]

2

2021-04-15T05:54:30.000Z

2022-02-08T00:10:10.000Z

from sp_calc import SinglePointCalculation

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1

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6

315261c9e9bb0262caaa014f65570cfc6becbdce

38

py

Python

obs/clis/__init__.py

meongbego/neo-obs

23c85642d3533e16855a1158fb939cd4b47fc7d6

[ "MIT" ]

1

2018-09-08T12:59:11.000Z

obs/clis/__init__.py

meongbego/neo-obs

23c85642d3533e16855a1158fb939cd4b47fc7d6

[ "MIT" ]

null

obs/clis/__init__.py

meongbego/neo-obs

23c85642d3533e16855a1158fb939cd4b47fc7d6

[ "MIT" ]

null

from .login import * from .ls import *

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1

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6

3161c9f50918b093b69569a65a18627f0eb7a8ea

45,276

py

Python

animal/arenas/utils/create_arenas.py

compsciencelab/ppo_D

1870c908f498ceb29295e5625ff5598bed82cbb3

[ "MIT" ]

4

2021-08-18T07:47:38.000Z

2022-01-06T17:27:21.000Z

animal/arenas/utils/create_arenas.py

compsciencelab/ppo_D

1870c908f498ceb29295e5625ff5598bed82cbb3

[ "MIT" ]

null

animal/arenas/utils/create_arenas.py

compsciencelab/ppo_D

1870c908f498ceb29295e5625ff5598bed82cbb3

[ "MIT" ]

1

2022-02-16T11:03:12.000Z

""" Create sets C1 to C10 of test arenas with known max reward for testing. """ import random import numpy as np from .edit_arenas import (add_object, write_arena, create_wall) from .sample_features import (random_size, random_pos, random_rotation) from .edit_arenas import (add_ramp_scenario, add_walled, add_choice, cross_test, ramp_test_1, ramp_test_2, ramp_test_3, tunnel_test_1, tunnel_test_2, push_test_1, push_test_2, narrow_spaces_1, narrow_spaces_2, preference_test_1, blackout_test_1, reasoning_step_1, reasoning_step_2, reasoning_step_3) objects_dict = { 'reward_objects': [ 'GoodGoal', 'GoodGoalBounce', 'BadGoal', 'BadGoalBounce', 'GoodGoalMulti', 'GoodGoalMultiBounce' ], 'immovable_objects': [ 'Wall', 'Ramp', 'CylinderTunnel', 'WallTransparent', 'CylinderTunnelTransparent'], 'movable_objects': [ 'Cardbox1', 'Cardbox2', 'UObject', 'LObject', 'LObject2' ], 'zone_objects': [ 'DeathZone', 'HotZone' ], } def create_c1_arena(target_path, arena_name, max_reward=5, time=250, max_num_good_goals=1, is_train=False): """ Create .yaml file for C1-type arena. - Only goals. - Fixed random size for all goals. - At least one green ball. Parameters: target_path (str): save dir path. arena_name (str): save name arena. max_reward (float): set max reward for arena. Relates to arena complexity. time (int): episode length. max_num_good_goals: goal limit. """ allowed_objects = objects_dict['reward_objects'] size_goal = ( np.clip(random_size('GoodGoal')[0], 1.0, max_reward), 0.0, 0.0) position_goal = random_pos() if not is_train else None reward = float(max_reward) arena = add_object('', 'GoodGoal', size=size_goal, pos=position_goal) num_goals = 1 worst_goal = 0.0 min_reward = 0.0 best_goal = size_goal[0] while reward - best_goal > size_goal[0]: category = allowed_objects[np.random.randint(0, len(allowed_objects))] position_goal = random_pos() if not is_train else None if category in ['GoodGoalMulti', 'GoodGoalMultiBounce']: reward -= size_goal[0] if category in ['BadGoal', 'BadGoalBounce']: worst_goal = min(worst_goal, size_goal[0]) if category in ['GoodGoal', 'GoodGoalBounce']: best_goal = max(best_goal, size_goal[0]) if num_goals >= max_num_good_goals: continue num_goals += 1 arena = add_object(arena, category, size=size_goal, pos=position_goal) min_reward -= worst_goal position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'c1', position_agent, rotation_agent def create_c1_arena_weird(target_path, arena_name, time=250, is_train=False): """ Create .yaml file for C1-type arena. - Only goals. - Fixed random size for all goals. - At least one green ball. Parameters: target_path (str): save dir path. arena_name (str): save name arena. max_reward (float): set max reward for arena. Relates to arena complexity. time (int): episode length. max_num_good_goals: goal limit. """ position_goal = random_pos() if not is_train else None arena = add_object('', 'BadGoal', size=(0.5, 0.5, 0.5), pos=position_goal) position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'c1_weird', position_agent, rotation_agent def create_c2_arena(target_path, arena_name, max_reward=5, time=250, max_num_good_goals=1, is_train=False): """ Create .yaml file for C2-type arena. - Only goals. - Different random size for all goals. - At least one green and one red ball. Parameters: target_path (str): save dir path. arena_name (str): save name arena. max_reward (float): set max reward for arena. Relates to arena complexity. time (int): episode length. max_num_good_goals: goal limit. """ allowed_objects = objects_dict['reward_objects'] reward = float(max_reward) size_goal = ( np.clip(random_size('GoodGoal')[0], 1.0, max_reward), 0.0, 0.0) position_goal = random_pos() if not is_train else None arena = add_object('', 'GoodGoal', size=size_goal, pos=position_goal) best_goal = size_goal[0] size_goal = random_size('BadGoal') position_goal = random_pos() if not is_train else None arena = add_object(arena, 'BadGoal', size=size_goal, pos=position_goal) worst_goal = size_goal[0] num_goals = 1 min_reward = 0.0 while reward - best_goal > size_goal[0]: category = allowed_objects[np.random.randint(0, len(allowed_objects))] size_goal = random_size(category) position_goal = random_pos() if not is_train else None if category in ['GoodGoalMulti', 'GoodGoalMultiBounce']: reward -= size_goal[0] if category in ['BadGoal', 'BadGoalBounce']: worst_goal = min(worst_goal, size_goal[0]) if category in ['GoodGoal', 'GoodGoalBounce']: if num_goals >= max_num_good_goals: continue best_goal = max(best_goal, size_goal[0]) num_goals += 1 arena = add_object(arena, category, size=size_goal, pos=position_goal) min_reward -= worst_goal position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'c2', position_agent, rotation_agent def create_c3_arena_basic(target_path, arena_name, time=250, num_walls=1, is_train=False): """ include explanation """ category = random.choice( ['GoodGoal', 'GoodGoalBounce', 'GoodGoalMulti', 'GoodGoalMultiBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object('', category, size=size_goal, pos=position_goal) arena = add_walled(arena, num_walls=num_walls) position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'c3', position_agent, rotation_agent def create_c3_arena(target_path, arena_name, time=250, max_movable=3, max_immovable=3, is_train=False): """ Create .yaml file for C3-type arena. - One random positive reward ball, random sized - With probability 0.5 add red ball, random sized - Create a wall maze by randomly spawning between 1 and 10 walls - If specified randomly add multiple movable and immovable objects Parameters: target_path (str): save dir path. arena_name (str): save name arena. max_reward (float): set max reward for arena. Relates to arena complexity. time (int): episode length. max_movable (int): set a limit to number of movable objects. max_immovable (int): set a limit to number of immovable. """ category = random.choice( ['GoodGoal', 'GoodGoalBounce', 'GoodGoalMulti', 'GoodGoalMultiBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object('', category, size=size_goal, pos=position_goal) if random.random() > 0.5: category = random.choice(['BadGoal', 'BadGoalBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object(arena, category, size=size_goal, pos=position_goal) for _ in range(max_movable): if random.random() > 0.1: category = random.choice(objects_dict['movable_objects']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) for _ in range(max_immovable): if random.random() > 0.1: category = random.choice(objects_dict['immovable_objects']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'c3', position_agent, rotation_agent def create_c4_arena(target_path, arena_name, time=250, num_red_zones=2, max_orange_zones=1, max_movable=1, max_immovable=1, is_train=False): """ Create .yaml file for C4-type arena. - 1 green food (stationary) and some red zones - add orange ball with probability 0.5 - add orange zone with probability 0.5 - add immobable object with probability 0.1 - add movable object with probability 0.1 Parameters: target_path (str): save dir path. arena_name (str): save name arena. time (int): episode length. num_red_zones (int): fixed number of red zones. max_orange_zones (int): set a limit to number of orange zones. max_movable (int): set a limit to number of movable objects. max_immovable (int): set a limit to number of immovable. """ size_goal = random_size('GoodGoal') position_goal = random_pos() if not is_train else None arena = add_object('', 'GoodGoal', size=size_goal, pos=position_goal) if random.random() > 0.5: size_goal = random_size('GoodGoalMulti') position_goal = random_pos() if not is_train else None arena = add_object(arena, 'GoodGoalMulti', size=size_goal, pos=position_goal) for _ in range(num_red_zones): size_object = random_size('DeathZone') pos_object = random_pos() if not is_train else None arena = add_object(arena, 'DeathZone', size=size_object, pos=pos_object) for _ in range(max_orange_zones): if random.random() > 0.5: size_object = random_size('HotZone') pos_object = random_pos() if not is_train else None arena = add_object(arena, 'HotZone', size=size_object, pos=pos_object) for _ in range(max_movable): if random.random() > 0.8: category = random.choice(objects_dict['movable_objects']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) for _ in range(max_immovable): if random.random() > 0.8: category = random.choice(objects_dict['immovable_objects']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'c4', position_agent, rotation_agent def create_c5_arena(target_path, arena_name, time=250, max_movable=1, max_immovable=1, is_train=False): """ Create .yaml file for C5-type arena. - from 1 to 2 platforms accessible by ramps with a goal on top. - if specified, add multiple movable and immovable objects. Parameters: target_path (str): save dir path. arena_name (str): save name arena. time (int): episode length. max_movable (int): set a limit to number of movable objects. max_immovable (int): set a limit to number of immovable. """ arena = add_ramp_scenario('') arena = add_ramp_scenario(arena) for _ in range(max_movable): if random.random() < 0.8: category = random.choice(objects_dict['movable_objects']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) for _ in range(max_immovable): if random.random() < 0.8: category = random.choice(['Wall', 'Ramp', 'CylinderTunnel']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'c5', position_agent, rotation_agent def create_c6_arena_basic(target_path, arena_name, time=250, num_walls=1, is_train=False): """ include explanation """ category = random.choice( ['GoodGoal', 'GoodGoalBounce', 'GoodGoalMulti', 'GoodGoalMultiBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object('', category, size=size_goal, pos=position_goal) arena = add_walled(arena, num_walls=num_walls, random_rgb=True) position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'c6', position_agent, rotation_agent def create_c6_arena(target_path, arena_name, time=250, max_movable=3, max_immovable=3, is_train=False): """ Create .yaml file for C6-type arena. - One random positive reward ball, random sized - add a second positive reward , with probability 0.5 - add up to 2 red balls , with probability 0.5 each - Add multiple (1 to 10) walls with random color. - If specifiedm add also extra multiple movable and immovable objects (with random color) Parameters: target_path (str): save dir path. arena_name (str): save name arena. time (int): episode length. max_movable (int): set a limit to number of movable objects. max_immovable (int): set a limit to number of immovable. """ category = random.choice( ['GoodGoal', 'GoodGoalBounce', 'GoodGoalMulti', 'GoodGoalMultiBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object('', category, size=size_goal, pos=position_goal) if random.random() > 0.5: category = random.choice( ['GoodGoal', 'GoodGoalBounce', 'GoodGoalMulti', 'GoodGoalMultiBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object(arena, category, size=size_goal, pos=position_goal) for _ in range(2): if random.random() > 0.5: category = random.choice(['BadGoal', 'BadGoalBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object(arena, category, size=size_goal, pos=position_goal) for _ in range(max_movable): if random.random() < 0.8: category = random.choice(objects_dict['movable_objects']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) for _ in range(max_immovable): if random.random() < 0.8: category = random.choice(['Wall', 'Ramp', 'CylinderTunnel']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'c6', position_agent, rotation_agent def create_c7_arena(target_path, arena_name, time=250, max_movable=3, max_immovable=3, is_train=False): """ Create .yaml file for C7-type arena. - One random positive reward ball, random sized - add a second positive rewards , with probability 0.5 - add up to 2 red balls , with probability 0.5 each - With probability 0.5 add red balls, random sized - Add multiple movable and immovable objects - random blackouts Parameters: target_path (str): save dir path. arena_name (str): save name arena. time (int): episode length. max_movable (int): set a limit to number of movable objects. max_immovable (int): set a limit to number of immovable. """ blackout_options = [[-20], [-40], [-60], [25, 30, 50, 55, 75], [50, 55, 75, 80, 100, 105, 125]] category = random.choice( ['GoodGoal', 'GoodGoalBounce', 'GoodGoalMulti', 'GoodGoalMultiBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object('', category, size=size_goal, pos=position_goal) if random.random() > 0.5: category = random.choice( ['GoodGoal', 'GoodGoalBounce', 'GoodGoalMulti', 'GoodGoalMultiBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object(arena, category, size=size_goal, pos=position_goal) for _ in range(2): if random.random() > 0.5: category = random.choice(['BadGoal', 'BadGoalBounce']) size_goal = random_size(category) position_goal = random_pos() if not is_train else None arena = add_object(arena, category, size=size_goal, pos=position_goal) for _ in range(max_movable): if random.random() < 0.8: category = random.choice(objects_dict['movable_objects']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) for _ in range(max_immovable): if random.random() < 0.8: category = random.choice(objects_dict['immovable_objects']) size_object = random_size(category) if not is_train else None pos_object = random_pos() if not is_train else None arena = add_object(arena, category, size=size_object, pos=pos_object) position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena, blackouts=random.choice(blackout_options)) return 'c7', position_agent, rotation_agent def create_maze(target_path, arena_name, time=250, num_cells=3, obj=None, is_train=False): """ include explanation """ wall_type = random.choice(['Wall', 'WallTransparent']) arena = '' if obj == 'CylinderTunnel': gap = 3 else: gap = 2 num_cells_x = num_cells num_cells_y = num_cells side_wall_len_x = int(40 / num_cells_x) side_wall_len_y = int(40 / num_cells_y) location_pillars_x = list(range(0, 40, side_wall_len_x))[1:] location_pillars_y = list(range(0, 40, side_wall_len_y))[1:] walls_loc_x = location_pillars_x walls_loc_x.append(40) walls_loc_y = location_pillars_y walls_loc_y.append(40) prev_y = 0 prev_x = 0 z_size = random.choice([0.5, 10]) for y in walls_loc_y: for x in walls_loc_x: size_1, pos_1, size_2, pos_2 = create_wall( (prev_x, y), (x, y), z_size, obj='door', gap=gap) arena = add_object(arena, wall_type, size=size_1, pos=pos_1, rot=0) arena = add_object(arena, wall_type, size=size_2, pos=pos_2, rot=0) if obj != 'door': size, pos = create_wall( (prev_x, y), (x, y), z_size, obj=obj, gap=gap) arena = add_object(arena, obj, size=size, pos=pos, rot=0) size_1, pos_1, size_2, pos_2 = create_wall( (x, prev_y), (x, y), z_size, obj='door', gap=gap) arena = add_object(arena, wall_type, size=size_1, pos=pos_1, rot=0) arena = add_object(arena, wall_type, size=size_2, pos=pos_2, rot=0) if obj != 'door': size, pos = create_wall( (x, prev_y), (x, y), z_size, obj=obj, gap=gap) arena = add_object(arena, obj, size=size, pos=pos, rot=90) prev_x = x prev_x = 0 prev_y = y size_goal = random_size('GoodGoal') position_goal = random_pos() if not is_train else None arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) position_agent = random_pos() if not is_train else None rotation_agent = random_rotation() if not is_train else None arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'maze', position_agent, rotation_agent def create_arena_choice(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena = add_choice('') size_goal = random_size('GoodGoal') position_goal = random_pos() if not is_train else None arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size_goal = random_size('GoodGoalMulti') position_goal = random_pos() if not is_train else None arena = add_object(arena, 'GoodGoalMulti', size=size_goal, pos=position_goal) save_name = '{}/{}'.format(target_path, arena_name, is_train=is_train) write_arena(save_name, time, arena) return 'choice', (20, 0, 20), 0 def create_arena_cross(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = cross_test("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'cross', pos_agent, rot_agent def create_arena_push1(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = push_test_1("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'push1', pos_agent, rot_agent def create_arena_push2(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = push_test_2("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'push2', pos_agent, rot_agent def create_arena_tunnel1(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = tunnel_test_1("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'tunnel1', pos_agent, rot_agent def create_arena_tunnel2(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = tunnel_test_2("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'tunnel2', pos_agent, rot_agent def create_arena_ramp1(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = ramp_test_1("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'ramp1', pos_agent, rot_agent def create_arena_ramp2(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = ramp_test_2("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'ramp2', pos_agent, rot_agent def create_arena_ramp3(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = ramp_test_3("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'ramp3', pos_agent, rot_agent def create_arena_narrow_spaces_1(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = narrow_spaces_1("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'narrow1', pos_agent, rot_agent def create_arena_narrow_spaces_2(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = narrow_spaces_2("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'narrow2', pos_agent, rot_agent def create_arena_pref1(target_path, arena_name, time=250, is_train=False): """ include explanation """ arena, pos_agent, rot_agent = preference_test_1("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'pref', pos_agent, rot_agent def create_blackout_test_1(target_path, arena_name, time=250, is_train=False): arena, pos_agent, rot_agent = blackout_test_1("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena, blackouts=[10, 1000]) return 'blackout', pos_agent, rot_agent def create_reasoning_step_1(target_path, arena_name, time=250, is_train=False): arena, pos_agent, rot_agent = reasoning_step_1("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'reasoning1', pos_agent, rot_agent def create_reasoning_step_2(target_path, arena_name, time=250, is_train=False): arena, pos_agent, rot_agent = reasoning_step_2("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'reasoning2', pos_agent, rot_agent def create_reasoning_step_3(target_path, arena_name, time=250, is_train=False): arena, pos_agent, rot_agent = reasoning_step_3("", is_train=is_train) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'reasoning3', pos_agent, rot_agent def create_front_back(target_path, arena_name, time=1000, is_train=False, rew_range=[0.5, 5]): """ include explanation """ arena = '' range_list = list(np.linspace(rew_range[0], rew_range[1], (rew_range[1] - rew_range[0]) / 0.1 + 1)) range_list = [round(elem, 2) for elem in range_list] list_siz = random.sample(range_list, 2) size = list_siz[0] size_goal = (size, size, size) position_goal = (20, 0, 30) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[1] size_goal = (size, size, size) position_goal = (20, 0, 10) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) pos_agent = (20, 0, 20) arena = add_object(arena, "Agent", pos=pos_agent, rot=0) save_name = '{}/{}'.format(target_path, arena_name) blackout_options_2 = [[-10], [1000, 1000]] write_arena(save_name, time, arena, blackouts=random.choice(blackout_options_2)) return 'front_back', (20, 0, 20), 0 def create_left_right(target_path, arena_name, time=1000, is_train=False, rew_range=[0.5, 5]): """ include explanation """ arena = '' range_list = list(np.linspace(rew_range[0], rew_range[1], (rew_range[1] - rew_range[0]) / 0.1 + 1)) range_list = [round(elem, 2) for elem in range_list] list_siz = random.sample(range_list, 2) size = list_siz[0] size_goal = (size, size, size) position_goal = (10, 0, 20) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[1] size_goal = (size, size, size) position_goal = (30, 0, 20) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) pos_agent = (20, 0, 20) arena = add_object(arena, "Agent", pos=pos_agent, rot=0) save_name = '{}/{}'.format(target_path, arena_name) blackout_options_2 = [[-10], [1000, 1000]] write_arena(save_name, time, arena, blackouts=random.choice(blackout_options_2)) return 'left_right', (20, 0, 20), 0 def create_corners_green(target_path, arena_name, time=1000, is_train=False, rew_range=[0.5, 5]): """ include explanation """ arena = '' range_list = list(np.linspace(rew_range[0], rew_range[1], (rew_range[1] - rew_range[0]) / 0.1 + 1)) range_list = [round(elem, 2) for elem in range_list] list_siz = random.sample(range_list, 4) size = list_siz[0] size_goal = (size, size, size) position_goal = (37, 0, 37) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[1] size_goal = (size, size, size) position_goal = (3, 0, 37) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[2] size_goal = (size, size, size) position_goal = (37, 0, 3) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[3] size_goal = (size, size, size) position_goal = (3, 0, 3) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) pos_agent = (20, 0, 20) arena = add_object(arena, "Agent", pos=pos_agent) save_name = '{}/{}'.format(target_path, arena_name) blackout_options_2 = [[-10], [1000, 1000]] write_arena(save_name, time, arena, blackouts=random.choice(blackout_options_2)) return 'corners_green', (20, 0, 20), 0 def create_cross_green(target_path, arena_name, time=1000, is_train=False, rew_range=[0.5, 5]): """ include explanation """ arena = '' range_list = list(np.linspace(rew_range[0], rew_range[1], (rew_range[1] - rew_range[0]) / 0.1 + 1)) range_list = [round(elem, 2) for elem in range_list] list_siz = random.sample(range_list, 4) size = list_siz[0] size_goal = (size, size, size) position_goal = (30, 0, 20) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[1] size_goal = (size, size, size) position_goal = (10, 0, 20) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[2] size_goal = (size, size, size) position_goal = (20, 0, 10) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[3] size_goal = (size, size, size) position_goal = (20, 0, 30) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) pos_agent = (20, 0, 20) arena = add_object(arena, "Agent", pos=pos_agent) save_name = '{}/{}'.format(target_path, arena_name) blackout_options_2 = [[-10], [1000, 1000]] write_arena(save_name, time, arena, blackouts=random.choice(blackout_options_2)) return 'cross_green', (20, 0, 20), 0 def create_in_front(target_path, arena_name, time=1000, is_train=False, rew_range=[0.5, 5]): """ include explanation """ arena = '' range_list = list(np.linspace(rew_range[0], rew_range[1], (rew_range[1] - rew_range[0]) / 0.1 + 1)) range_list = [round(elem, 2) for elem in range_list] list_siz = random.sample(range_list, 2) size = list_siz[0] size_goal = (size, size, size) position_goal = (30, 0, 35) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[1] size_goal = (size, size, size) position_goal = (10, 0, 35) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) pos_agent = (20, 0, 3) arena = add_object(arena, "Agent", pos=pos_agent, rot=0) save_name = '{}/{}'.format(target_path, arena_name) blackout_options_2 = [[-10], [1000, 1000]] write_arena(save_name, time, arena, blackouts=random.choice(blackout_options_2)) return 'in_front', (20, 0, 20), 0 def create_make_fall_1(target_path, arena_name, time=1000, is_train=False, rew_range=[5, 50]): """ The reward is on top of a box. Agent must push the box to make reward fall down. """ arena = '' height = random.randint(2, 7) pos_box = (random.randint(5, 35), 0, random.randint(5, 35)) siz_box = (random.randint(2, 4), height, random.randint(2, 4)) category = random.choice(['Cardbox1', 'Cardbox2']) arena = add_object(arena, category, size=siz_box, pos=pos_box, rot=0) rew_size = random.randint(1, 5) rew_pos = (pos_box[0], siz_box[1] + rew_size / 2, pos_box[2]) arena = add_object(arena, random.choice(["GoodGoal", "GoodGoalMulti"]), size=(rew_size, rew_size, rew_size), pos=rew_pos) rotation_agent = random_rotation() position_agent = random_pos() arena = add_object(arena, "Agent", pos=position_agent, rot=rotation_agent) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'make_fall', position_agent, rotation_agent def create_arena_choice_2(target_path, arena_name, time=250, is_train=False, rew_range=[0.5, 5]): """ include explanation """ arena = add_choice('') range_list = list(np.linspace(rew_range[0], rew_range[1], (rew_range[1] - rew_range[0]) / 0.1 + 1)) range_list = [round(elem, 2) for elem in range_list] list_siz = random.sample(range_list, 4) size = list_siz[0] size_goal = (size, size, size) position_goal = (30, 0, 30) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[1] size_goal = (size, size, size) position_goal = (10, 0, 30) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = list_siz[2] size_goal = (size, size, size) position_goal = (10, 0, 10) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) size = size = list_siz[3] size_goal = (size, size, size) position_goal = (30, 0, 10) arena = add_object(arena, 'GoodGoal', size=size_goal, pos=position_goal) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'choice2', (20, 0, 20), 0 def create_box_reasoning(target_path, arena_name, time=1000, is_train=True): """ The reward is on top of a box. agent must push box in the right position to be able to acces the reward platform.""" arena = '' arena = add_object(arena, 'WallTransparent', size=(4, 2, 4), pos=(13.5, 0, 20), rot=90) arena = add_object(arena, 'WallTransparent', size=(4, 2, 4), pos=(22, 0, 20), rot=90) arena = add_object(arena, 'Cardbox1', size=(4, 2, 4), pos=(17.75, 0, 9), rot=90) arena = add_object(arena, 'Ramp', size=(8, 2, 8), pos=(28, 0, 20), rot=90) arena = add_object(arena, 'GoodGoal', size=(3, 3, 3), pos=(13.5, 2.25, 20), rot=0) agent_rotation = random_rotation() while True: agent_pos = random_pos() if pos_on_obj(agent_pos,(13.5, 0, 20),(4, 2, 4)) == False: if pos_on_obj(agent_pos,(22, 0, 20),(4, 2, 4)) == False: if pos_on_obj(agent_pos,(17.75, 0, 9),(4, 2, 4)) == False: if pos_on_obj(agent_pos,(28, 0, 20),(8, 2, 8)) == False: break arena = add_object(arena, "Agent", pos= agent_pos, rot=agent_rotation) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'box_reasoning', (20, 0, 3), 0 def create_box_reasoning_hard(target_path, arena_name, time=1000, is_train=True): """ The reward is on top of a box. agent must push box in the right position to be able to acces the reward platform.""" pos_box_ = [(10, 0, 10),(10, 0, 30),(30, 0, 10),(30, 0, 30)] pos_box = random.choice(pos_box_) arena = '' arena = add_object(arena, 'WallTransparent', size=(4, 2, 4), pos=(13.5, 0, 20), rot=90) arena = add_object(arena, 'WallTransparent', size=(4, 2, 4), pos=(22, 0, 20), rot=90) arena = add_object(arena, 'Cardbox1', size=(4, 2, 4), pos=pos_box, rot=90) arena = add_object(arena, 'Ramp', size=(8, 2, 8), pos=(28, 0, 20), rot=90) arena = add_object(arena, 'GoodGoal', size=(3, 3, 3), pos=(13.5, 2.25, 20), rot=0) agent_rotation = random_rotation() while True: agent_pos = random_pos() if pos_on_obj(agent_pos,(13.5, 0, 20),(4, 2, 4)) == False: if pos_on_obj(agent_pos,(22, 0, 20),(4, 2, 4)) == False: if pos_on_obj(agent_pos, pos_box,(4, 2, 4)) == False: if pos_on_obj(agent_pos,(28, 0, 20),(8, 2, 8)) == False: break arena = add_object(arena, "Agent", pos= agent_pos, rot=agent_rotation) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'box_reasoning', (20, 0, 3), 0 def create_box_reasoning_2(target_path, arena_name, time=1000, is_train=True): """ The reward is on top of a box. agent must push box in the right position to be able to acces the reward platform.""" pos_box_ = [(10, 0, 10),(10, 0, 30),(30, 0, 10),(30, 0, 30)] pos_box1, pos_box2 = random.sample(pos_box_, k=2) arena = '' arena = add_object(arena, 'WallTransparent', size=(4, 2, 4), pos=(7.5, 0, 20), rot=90) arena = add_object(arena, 'WallTransparent', size=(4, 2, 4), pos=(22, 0, 20), rot=90) arena = add_object(arena, 'Cardbox1', size=(4, 2, 4), pos=pos_box1, rot=90) arena = add_object(arena, 'Cardbox1', size=(4, 2, 4), pos=pos_box2, rot=90) arena = add_object(arena, 'Ramp', size=(8, 2, 8), pos=(28, 0, 20), rot=90) arena = add_object(arena, 'GoodGoal', size=(3, 3, 3), pos=(7.5, 2.25, 20), rot=0) agent_rotation = random_rotation() while True: agent_pos = random_pos() if pos_on_obj(agent_pos,(7.5, 0, 20),(4, 2, 4)) == False: if pos_on_obj(agent_pos,(22, 0, 20),(4, 2, 4)) == False: if pos_on_obj(agent_pos, pos_box1,(4, 2, 4)) == False: if pos_on_obj(agent_pos, pos_box2,(4, 2, 4)) == False: if pos_on_obj(agent_pos,(28, 0, 20),(8, 2, 8)) == False: break arena = add_object(arena, "Agent", pos= agent_pos, rot=agent_rotation) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'box_reasoning', (20, 0, 3), 0 def create_push_down(target_path, arena_name, time=1000, is_train=True): """ The reward is on top of a box. agent must push box in the right position to be able to acces the reward platform.""" coin = random.choice([0,1]) if coin == 1: box_pos = (random.randint(25, 140) / 10., 1., random.randint(25, 200) / 10.) fake_box_pos = (random.randint(260, 380) / 10., 1., random.randint(25, 200) / 10.) else: fake_box_pos = (random.randint(25, 140) / 10., 1., random.randint(25, 200) / 10.) box_pos = (random.randint(260, 380) / 10., 1., random.randint(25, 200) / 10.) pos_goal = (random.randint(10, 390) / 10., 1., random.randint(250, 390) / 10.) goal_wal_pos = (pos_goal[0], 0, pos_goal[2]) arena = '' arena = add_object(arena, 'Wall', size=(0.3, 1, 0.3), pos=goal_wal_pos, rot=0, RGB= (153, 153, 153)) arena = add_object(arena, 'Wall', size=(40, 1, 20), pos=(20, 0, 10), rot=0, RGB= (0, 0, 255)) arena = add_object(arena, 'Wall', size=(11, 2, 5), pos=(20, 1, 2.5), rot=0, RGB= (0, 0, 255)) arena = add_object(arena, 'Wall', size=(1, .5, 15), pos=(20, 1, 12.5), rot=0, RGB=(153, 153, 153)) arena = add_object(arena, 'Cardbox2', size=(1.5, 1.5, 1.5), pos=box_pos, rot=0) arena = add_object(arena, 'Wall', size=(1.5, 1.5, 1.5), pos=fake_box_pos, rot=0, RGB=(153, 153, 153)) arena = add_object(arena, 'GoodGoal', size=(1,1,1), pos=pos_goal, rot=0) arena = add_object(arena, "Agent", pos= (20, 3, 2.5), rot=2) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'push_down_decieve', (20, 0, 3), 0 def create_push_red(target_path, arena_name, time=1000, is_train=True): """ The reward is on top of a box. agent must push box in the right position to be able to acces the reward platform.""" arena = '' arena = add_object(arena, 'DeathZone', size=(10, 0, 10), pos=(20, 0, 20), rot=45) arena = add_object(arena, 'GoodGoal', size=(1, 1, 1), pos=(20, 0, 20), rot=0) while True: agent_pos = random_pos() pos_box1 = (random.randint(65, 335) / 10., 0., random.randint(65, 335) / 10.) if pos_on_obj(pos_box1,(20, 0, 20),(15, 0, 15)) == False: if pos_on_obj(agent_pos,(20, 0, 20),(15, 0, 15)) == False: if pos_on_obj(agent_pos, pos_box1,(6, .2, 2)) == False: break agent_rotation = random_rotation() box_rotation = random_rotation() arena = add_object(arena, "Agent", pos= agent_pos, rot=agent_rotation) arena = add_object(arena, 'Cardbox2', size=(6, .2, 2), pos=pos_box1, rot=box_rotation) save_name = '{}/{}'.format(target_path, arena_name) write_arena(save_name, time, arena) return 'push_red', (20, 0, 3), 0 def pos_on_obj(agent_pos, obj_pos, obs_size): x_lim1 = obj_pos[0] - obs_size[0]/2 x_lim2 = obj_pos[0] + obs_size[0]/2 y_lim1 = obj_pos[2] - obs_size[2]/2 y_lim2 = obj_pos[2] + obs_size[2]/2 if (agent_pos[0] < x_lim1) or (agent_pos[0]> x_lim2): if (agent_pos[2] < y_lim1) or (agent_pos[2]> y_lim2): return False else: return True else: return True

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null

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null

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6

3173549b78f25e85fad530fb2464104ba94a5011

86

py

Python

Level1/Lessons12903/wowo0709.py

StudyForCoding/ProgrammersLevel

dc957b1c02cc4383a93b8cbf3d739e6c4d88aa25

[ "MIT" ]

null

Level1/Lessons12903/wowo0709.py

StudyForCoding/ProgrammersLevel

dc957b1c02cc4383a93b8cbf3d739e6c4d88aa25

[ "MIT" ]

null

Level1/Lessons12903/wowo0709.py

StudyForCoding/ProgrammersLevel

dc957b1c02cc4383a93b8cbf3d739e6c4d88aa25

[ "MIT" ]

1

2021-04-05T07:35:59.000Z

def solution(s): N = len(s) return s[N//2] if N % 2 == 1 else s[N//2-1:N//2+1]

28.666667

54

0.488372

22

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1.909091

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null

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1

0

6

3185b8f83ea18b9e532fcc72f94a943c356cf5dc

43

py

Python

init_db.py

notnamed/social-graph

1120889bcf72901c69a07797fdbf689b36853e6f

[ "MIT" ]

null

init_db.py

notnamed/social-graph

1120889bcf72901c69a07797fdbf689b36853e6f

[ "MIT" ]

null

init_db.py

notnamed/social-graph

1120889bcf72901c69a07797fdbf689b36853e6f

[ "MIT" ]

null

import social_graph social_graph.init_db()

14.333333

22

0.860465

7

43

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0.069767

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0

null

0

1

0

1

0

6

319b781e5814130abde4cc96fd6e91ef3e46db80

49

py

Python

src/compgen2/gov/__init__.py

CorrelAid/compgen-ii-cgv

810a044d6bbe1ce058a359115e3e5fc71a358549

[ "MIT" ]

1

2022-02-02T12:41:06.000Z

src/compgen2/gov/__init__.py

CorrelAid/compgen-ii-cgv

810a044d6bbe1ce058a359115e3e5fc71a358549

[ "MIT" ]

null

src/compgen2/gov/__init__.py

CorrelAid/compgen-ii-cgv

810a044d6bbe1ce058a359115e3e5fc71a358549

[ "MIT" ]

null

from .gov import Gov from .matcher import Matcher

24.5

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0.5

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6

31a22c249c33ef768a09aa92564829e135db5a00

229

py

Python

msc/tests/test_WNVJungle.py

WNVJungle/git-github-travis-lab

f8127748ee7a31be457d428a09fe7b66c88c54b2

[ "Apache-2.0" ]

null

msc/tests/test_WNVJungle.py

WNVJungle/git-github-travis-lab

f8127748ee7a31be457d428a09fe7b66c88c54b2

[ "Apache-2.0" ]

3

2019-10-23T10:40:14.000Z

2019-10-23T10:54:11.000Z

msc/tests/test_WNVJungle.py

WNVJungle/git-github-travis-lab

f8127748ee7a31be457d428a09fe7b66c88c54b2

[ "Apache-2.0" ]

11

2019-10-23T09:50:57.000Z

2019-10-23T10:24:18.000Z

from msc.rot13 import rot13 from msc.rot13 import rot13_char def test_rot13_char_a(): assert "n" == rot13_char("a"), "Unexpected character" def test_rot13_abcdef(): assert "abcdef" == rot13("nopqrs"), "Unexpected character"

22.9

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4.939394

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229

9

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null

0

1

0

1

0

1

0

6

730e223c864123dc0dc8d6f805e3f412e178069a

197

py

Python

web_elements/content.py

tronze/PythonCustomCalendar

bd7ffbbf28616ccf65e545605ede5f3dda251c9a

[ "BSD-3-Clause" ]

8

2019-03-05T12:23:07.000Z

2021-01-10T09:49:27.000Z

web_elements/content.py

tronze/PythonCustomCalendar

bd7ffbbf28616ccf65e545605ede5f3dda251c9a

[ "BSD-3-Clause" ]

null

web_elements/content.py

tronze/PythonCustomCalendar

bd7ffbbf28616ccf65e545605ede5f3dda251c9a

[ "BSD-3-Clause" ]

2

2019-02-18T06:34:34.000Z

2019-03-05T12:17:22.000Z

from .node import Node class Content(Node): def __init__(self, content): super().__init__() self.content = content def create_element(self): return self.content

16.416667

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197

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0

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197

11

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0

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null

1

0

null

0

1

0

1

0

6

733a0470c3524cff14b8d3a54298cb7055db5599

44

py

Python

tests/test_suite.py

kasium/alembic

af7963889abffe2ab8dc640d4fdcb8cea6d53942

[ "MIT" ]

1,324

2018-11-27T05:44:41.000Z

2022-03-30T19:49:20.000Z

tests/test_suite.py

kasium/alembic

af7963889abffe2ab8dc640d4fdcb8cea6d53942

[ "MIT" ]

452

2018-11-27T22:43:38.000Z

2022-03-28T04:33:43.000Z

tests/test_suite.py

kasium/alembic

af7963889abffe2ab8dc640d4fdcb8cea6d53942

[ "MIT" ]

159

2018-11-29T18:46:15.000Z

2022-03-28T16:34:19.000Z

from alembic.testing.suite import * # noqa

22

43

0.75

6

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5.5

1

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44

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0.891892

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6

b410a1c2a7ffaab5e3100a670f9684254bc4b69c

2,990

py

Python

src/mutator/test_uoi_strategy.py

AAU-PSix/canary

93b07d23cd9380adc03a6aa1291a13eaa3b3008c

[ "MIT" ]

null

src/mutator/test_uoi_strategy.py

AAU-PSix/canary

93b07d23cd9380adc03a6aa1291a13eaa3b3008c

[ "MIT" ]

null

src/mutator/test_uoi_strategy.py

AAU-PSix/canary

93b07d23cd9380adc03a6aa1291a13eaa3b3008c

[ "MIT" ]

null

from unittest import TestCase from .uoi_strategy import UoiStrategy from ts import ( LanguageLibrary, Parser, CSyntax, ) class TestAbsStrategu(TestCase): def setUp(self) -> None: LanguageLibrary.build() self._language = LanguageLibrary.c() self._parser = Parser.create_with_language(self._language) self._syntax = CSyntax() def test_capture_update_expression(self) -> None: program = "--a;" tree = self._parser.parse(program) stategy = UoiStrategy(self._parser) candidates = stategy.capture(tree.root) self.assertEqual(len(candidates), 1) def test_mutations_update_expression(self) -> None: program = "--a;" tree = self._parser.parse(program) stategy = UoiStrategy(self._parser) mutations = stategy.mutations( self._parser, tree, tree.root ) self.assertEqual(len(mutations), 1) def test_mutate_update_expression(self) -> None: program = "--a;" tree = self._parser.parse(program) stategy = UoiStrategy(self._parser) mutation = stategy.mutate( tree, tree.root ) self.assertEqual(mutation.text, "++a;") def test_capture_arithmetic_unary_expression(self) -> None: program = "-a;" tree = self._parser.parse(program) stategy = UoiStrategy(self._parser) candidates = stategy.capture(tree.root) self.assertEqual(len(candidates), 1) def test_mutations_arithmetic_unary_expression(self) -> None: program = "-a;" tree = self._parser.parse(program) stategy = UoiStrategy(self._parser) mutations = stategy.mutations( self._parser, tree, tree.root ) self.assertEqual(len(mutations), 1) def test_mutate_arithmetic_unary_expression(self) -> None: program = "-a;" tree = self._parser.parse(program) stategy = UoiStrategy(self._parser) mutation = stategy.mutate( tree, tree.root ) self.assertEqual(mutation.text, "+a;") def test_capture_logical_unary_expression(self) -> None: program = "!a;" tree = self._parser.parse(program) stategy = UoiStrategy(self._parser) candidates = stategy.capture(tree.root) self.assertEqual(len(candidates), 1) def test_mutations_logical_unary_expression(self) -> None: program = "!a;" tree = self._parser.parse(program) stategy = UoiStrategy(self._parser) mutations = stategy.mutations( self._parser, tree, tree.root ) self.assertEqual(len(mutations), 1) def test_mutate_logical_unary_expression(self) -> None: program = "!a;" tree = self._parser.parse(program) stategy = UoiStrategy(self._parser) mutation = stategy.mutate( tree, tree.root ) self.assertEqual(mutation.text, "a;")

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0.177215

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null

0

1

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null

0

6

b479ea6f9d3acc9f01d13fa6538cc476a4e77ace

124

py

Python

python/testData/hierarchy/call/Static/ArgumentList/main.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/hierarchy/call/Static/ArgumentList/main.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/hierarchy/call/Static/ArgumentList/main.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

from file_1 import * target_<caret>func() func1(target_func) func1(target_func()) func2(target_func) func2(target_func())

13.777778

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124

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0.444444

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124

8

21

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0

1

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6

b48a5e0433c477b5bbc3ef3fba7800faa2b49177

32

py

Python

lim/genetics/heritability/__init__.py

glimix/glimix

22c9b94732918bce31f64cb33ce368ea85ead478

[ "MIT" ]

2

2016-12-16T14:14:59.000Z

2017-01-31T16:50:08.000Z

lim/genetics/heritability/__init__.py

glimix/glimix

22c9b94732918bce31f64cb33ce368ea85ead478

[ "MIT" ]

null

lim/genetics/heritability/__init__.py

glimix/glimix

22c9b94732918bce31f64cb33ce368ea85ead478

[ "MIT" ]

2

2017-02-13T14:34:37.000Z

2017-02-15T14:27:32.000Z

from ._estimate import estimate

16

31

0.84375

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6.5

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1

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1

0

6

81fd37ba1f5605285358f7bfabbd32206b6341ee

7,284

py

Python

tests/test_path_zip.py

jhermann/dephell_archive

582e7e38d7dd702a267b6436da42bc372c8e4d44

[ "MIT" ]

null

tests/test_path_zip.py

jhermann/dephell_archive

582e7e38d7dd702a267b6436da42bc372c8e4d44

[ "MIT" ]

19

2019-12-17T12:29:36.000Z

2020-06-03T07:56:22.000Z

tests/test_path_zip.py

jhermann/dephell_archive

582e7e38d7dd702a267b6436da42bc372c8e4d44

[ "MIT" ]

6

2019-09-04T05:30:51.000Z

2021-09-28T02:43:22.000Z

# built-in from pathlib import Path # project from dephell_archive import ArchivePath wheel_path = Path(__file__).parent / 'requirements' / 'wheel.whl' def test_open_zip(tmpdir): path = ArchivePath( archive_path=wheel_path, cache_path=Path(str(tmpdir)), ) subpath = path / 'dephell' / '__init__.py' with subpath.open() as stream: content = stream.read() assert 'from .controllers' in content def test_glob_zip(tmpdir): path = ArchivePath( archive_path=wheel_path, cache_path=Path(str(tmpdir)), ) paths = list(path.glob('*/__init__.py')) assert len(paths) == 1 assert paths[0].member_path.as_posix() == 'dephell/__init__.py' def test_exists(tmpdir): path = ArchivePath( archive_path=wheel_path, cache_path=Path(str(tmpdir)), ) subpath = path / 'dephell' / '__init__.py' assert subpath.exists() is True subpath = path / 'dephell' / 'some_junk.py' assert subpath.exists() is False def test_is_file(tmpdir): path = ArchivePath( archive_path=wheel_path, cache_path=Path(str(tmpdir)), ) subpath = path / 'dephell' / '__init__.py' assert subpath.is_file() is True subpath = path / 'dephell' assert subpath.is_file() is False def test_is_dir(tmpdir): path = ArchivePath( archive_path=wheel_path, cache_path=Path(str(tmpdir)), ) subpath = path / 'dephell' / '__init__.py' assert subpath.is_dir() is False subpath = path / 'dephell' assert subpath.exists() is True assert subpath.is_dir() is True def test_is_dir_explicit_entry(tmpdir): path = ArchivePath( archive_path=Path('tests', 'requirements', 'graphviz-0.13.2.zip'), cache_path=Path(str(tmpdir)), ) subpath = path / 'graphviz-0.13.2' assert subpath.is_dir() is True subpath = subpath / 'graphviz' assert subpath.exists() is True assert subpath.is_dir() is True subpath = subpath / '__init__.py' assert subpath.is_dir() is False def test_iterdir_non_recursive(tmpdir): path = ArchivePath( archive_path=Path('tests', 'requirements', 'dnspython-1.16.0.zip'), cache_path=Path(str(tmpdir)), ) paths = [str(subpath) for subpath in path.iterdir(_recursive=False)] assert paths == ['dnspython-1.16.0'] def test_iterdir_recursive(tmpdir): path = ArchivePath( archive_path=Path('tests', 'requirements', 'dnspython-1.16.0.zip'), cache_path=Path(str(tmpdir)), ) paths = [str(subpath) for subpath in path.iterdir(_recursive=True)] assert 'dnspython-1.16.0' in paths assert str(Path('dnspython-1.16.0', 'setup.py')) in paths assert str(Path('dnspython-1.16.0', 'dns', '__init__.py')) in paths assert str(Path('dnspython-1.16.0', 'dns', 'rdtypes')) in paths assert str(Path('dnspython-1.16.0', 'dns', 'rdtypes', 'ANY')) in paths for path in paths: assert paths.count(path) == 1, 'duplicate dir: ' + path def test_iterdir_subpath_non_recursive(tmpdir): path = ArchivePath( archive_path=Path('tests', 'requirements', 'dnspython-1.16.0.zip'), cache_path=Path(str(tmpdir)), ) subpath = path / 'dnspython-1.16.0' paths = [str(item) for item in subpath.iterdir(_recursive=False)] for path in paths: assert paths.count(path) == 1, 'duplicate dir: ' + path assert 'dns' in paths assert 'dnspython.egg-info' in paths assert 'setup.py' in paths subpath = subpath / 'dns' paths = [str(item) for item in subpath.iterdir(_recursive=False)] assert 'rdtypes' in paths for path in paths: assert paths.count(path) == 1, 'duplicate dir: ' + path def test_iterdir_subpath_recursive(tmpdir): path = ArchivePath( archive_path=Path('tests', 'requirements', 'dnspython-1.16.0.zip'), cache_path=Path(str(tmpdir)), ) subpath = path / 'dnspython-1.16.0' paths = [str(item) for item in subpath.iterdir(_recursive=True)] assert 'setup.py' in paths assert Path('dnspython-1.16.0', 'dns') not in paths assert 'dns' in paths assert str(Path('dns', '__init__.py')) in paths for path in paths: assert paths.count(path) == 1, 'duplicate dir: ' + path def test_iterdir_non_recursive_with_dirs(tmpdir): path = ArchivePath( archive_path=Path('tests', 'requirements', 'graphviz-0.13.2.zip'), cache_path=Path(str(tmpdir)), ) paths = [str(subpath) for subpath in path.iterdir(_recursive=False)] assert paths == ['graphviz-0.13.2'] def test_iterdir_recursive_with_dirs(tmpdir): path = ArchivePath( archive_path=Path('tests', 'requirements', 'graphviz-0.13.2.zip'), cache_path=Path(str(tmpdir)), ) paths = [str(subpath) for subpath in path.iterdir(_recursive=True)] assert 'graphviz-0.13.2' in paths assert str(Path('graphviz-0.13.2', 'setup.py')) in paths assert str(Path('graphviz-0.13.2', 'graphviz', '__init__.py')) in paths for path in paths: assert paths.count(path) == 1, 'duplicate dir: ' + path def test_iterdir_subpath_non_recursive_with_dirs(tmpdir): path = ArchivePath( archive_path=Path('tests', 'requirements', 'graphviz-0.13.2.zip'), cache_path=Path(str(tmpdir)), ) subpath = path / 'graphviz-0.13.2' paths = [str(item) for item in subpath.iterdir(_recursive=False)] assert 'graphviz' in paths assert 'graphviz.egg-info' in paths assert 'setup.py' in paths for path in paths: assert paths.count(path) == 1, 'duplicate dir: ' + path subpath = subpath / 'graphviz.egg-info' paths = [str(item) for item in subpath.iterdir(_recursive=False)] for path in paths: assert paths.count(path) == 1, 'duplicate dir: ' + path assert set(paths) == { 'dependency_links.txt', 'PKG-INFO', 'requires.txt', 'SOURCES.txt', 'top_level.txt', } def test_iterdir_subpath_recursive_with_dirs(tmpdir): path = ArchivePath( archive_path=Path('tests', 'requirements', 'graphviz-0.13.2.zip'), cache_path=Path(str(tmpdir)), ) subpath = path / 'graphviz-0.13.2' paths = [str(item) for item in subpath.iterdir(_recursive=True)] assert 'graphviz' in paths assert str(Path('graphviz', '__init__.py')) in paths for path in paths: assert paths.count(path) == 1, 'duplicate dir: ' + path def test_iterdir_non_recursive_wheel(tmpdir): path = ArchivePath( archive_path=wheel_path, cache_path=Path(str(tmpdir)), ) paths = [str(subpath) for subpath in path.iterdir(_recursive=False)] assert len(paths) == 2 assert 'dephell' in paths assert 'dephell-0.2.0.dist-info' in paths def test_iterdir_recursive_wheel(tmpdir): path = ArchivePath( archive_path=wheel_path, cache_path=Path(str(tmpdir)), ) paths = [str(subpath) for subpath in path.iterdir(_recursive=True)] assert 'dephell' in paths assert str(Path('dephell', '__init__.py')) in paths assert 'dephell-0.2.0.dist-info' in paths assert str(Path('dephell-0.2.0.dist-info', 'WHEEL')) in paths for path in paths: assert paths.count(path) == 1, 'duplicate dir: ' + path

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Python

tests/unit/test_nhl_boxscore.py

JosephDErwin/sportsreference

f026366bec91fdf4bebef48e3a4bfd7c5bfab4bd

[ "MIT" ]

null

tests/unit/test_nhl_boxscore.py

JosephDErwin/sportsreference

f026366bec91fdf4bebef48e3a4bfd7c5bfab4bd

[ "MIT" ]

null

tests/unit/test_nhl_boxscore.py

JosephDErwin/sportsreference

f026366bec91fdf4bebef48e3a4bfd7c5bfab4bd

[ "MIT" ]

1

2020-07-08T16:05:25.000Z

from flexmock import flexmock from mock import patch, PropertyMock from pyquery import PyQuery as pq from sportsreference import utils from sportsreference.constants import AWAY, HOME from sportsreference.nhl.boxscore import Boxscore, Boxscores class MockField: def __init__(self, field): self._field = field def text(self): return self._field class MockBoxscoreData: def __init__(self, fields): self._fields = fields def __call__(self, field): return self def items(self): return [self._fields] class MockName: def __init__(self, name): self._name = name def text(self): return self._name def mock_pyquery(url): class MockPQ: def __init__(self, html_contents): self.status_code = 404 self.html_contents = html_contents self.text = html_contents boxscore = read_file('%s.html' % BOXSCORE) return MockPQ(boxscore) class TestNHLBoxscore: @patch('requests.get', side_effect=mock_pyquery) def setup_method(self, *args, **kwargs): flexmock(Boxscore) \ .should_receive('_parse_game_data') \ .and_return(None) self.boxscore = Boxscore(None) def test_away_team_wins(self): fake_away_goals = PropertyMock(return_value=4) fake_home_goals = PropertyMock(return_value=3) type(self.boxscore)._away_goals = fake_away_goals type(self.boxscore)._home_goals = fake_home_goals assert self.boxscore.winner == AWAY def test_home_team_wins(self): fake_away_goals = PropertyMock(return_value=3) fake_home_goals = PropertyMock(return_value=4) type(self.boxscore)._away_goals = fake_away_goals type(self.boxscore)._home_goals = fake_home_goals assert self.boxscore.winner == HOME def test_winning_name_is_home(self): expected_name = 'Home Name' fake_winner = PropertyMock(return_value=HOME) fake_home_name = PropertyMock(return_value=MockName(expected_name)) type(self.boxscore).winner = fake_winner type(self.boxscore)._home_name = fake_home_name assert self.boxscore.winning_name == expected_name def test_winning_name_is_away(self): expected_name = 'Away Name' fake_winner = PropertyMock(return_value=AWAY) fake_away_name = PropertyMock(return_value=MockName(expected_name)) type(self.boxscore).winner = fake_winner type(self.boxscore)._away_name = fake_away_name assert self.boxscore.winning_name == expected_name def test_winning_abbr_is_home(self): expected_name = 'HOME' flexmock(utils) \ .should_receive('_parse_abbreviation') \ .and_return(expected_name) fake_winner = PropertyMock(return_value=HOME) fake_home_abbr = PropertyMock(return_value=MockName(expected_name)) type(self.boxscore).winner = fake_winner type(self.boxscore)._home_abbr = fake_home_abbr assert self.boxscore.winning_abbr == expected_name def test_winning_abbr_is_away(self): expected_name = 'AWAY' flexmock(utils) \ .should_receive('_parse_abbreviation') \ .and_return(expected_name) fake_winner = PropertyMock(return_value=AWAY) fake_away_abbr = PropertyMock(return_value=MockName(expected_name)) type(self.boxscore).winner = fake_winner type(self.boxscore)._away_abbr = fake_away_abbr assert self.boxscore.winning_abbr == expected_name def test_losing_name_is_home(self): expected_name = 'Home Name' fake_winner = PropertyMock(return_value=AWAY) fake_home_name = PropertyMock(return_value=MockName(expected_name)) type(self.boxscore).winner = fake_winner type(self.boxscore)._home_name = fake_home_name assert self.boxscore.losing_name == expected_name def test_losing_name_is_away(self): expected_name = 'Away Name' fake_winner = PropertyMock(return_value=HOME) fake_away_name = PropertyMock(return_value=MockName(expected_name)) type(self.boxscore).winner = fake_winner type(self.boxscore)._away_name = fake_away_name assert self.boxscore.losing_name == expected_name def test_losing_abbr_is_home(self): expected_name = 'HOME' flexmock(utils) \ .should_receive('_parse_abbreviation') \ .and_return(expected_name) fake_winner = PropertyMock(return_value=AWAY) fake_home_abbr = PropertyMock(return_value=MockName(expected_name)) type(self.boxscore).winner = fake_winner type(self.boxscore)._home_abbr = fake_home_abbr assert self.boxscore.losing_abbr == expected_name def test_losing_abbr_is_away(self): expected_name = 'AWAY' flexmock(utils) \ .should_receive('_parse_abbreviation') \ .and_return(expected_name) fake_winner = PropertyMock(return_value=HOME) fake_away_abbr = PropertyMock(return_value=MockName(expected_name)) type(self.boxscore).winner = fake_winner type(self.boxscore)._away_abbr = fake_away_abbr assert self.boxscore.losing_abbr == expected_name def test_invalid_away_game_winning_goals_returns_default(self): goals = ['0', '1', 'bad'] fake_goals = PropertyMock(return_value=goals) fake_num_skaters = PropertyMock(return_value=3) fake_num_goalies = PropertyMock(return_value=0) type(self.boxscore)._away_game_winning_goals = fake_goals type(self.boxscore)._away_skaters = fake_num_skaters type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_game_winning_goals == 1 def test_invalid_away_even_strength_assists_returns_default(self): assists = ['0', '1', 'bad'] fake_assists = PropertyMock(return_value=assists) fake_num_skaters = PropertyMock(return_value=3) fake_num_goalies = PropertyMock(return_value=0) type(self.boxscore)._away_even_strength_assists = fake_assists type(self.boxscore)._away_skaters = fake_num_skaters type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_even_strength_assists == 1 def test_invalid_home_even_strength_assists_returns_default(self): assists = ['0', '1', 'bad'] fake_assists = PropertyMock(return_value=assists) fake_num_skaters = PropertyMock(return_value=0) fake_num_goalies = PropertyMock(return_value=0) type(self.boxscore)._home_even_strength_assists = fake_assists type(self.boxscore)._away_skaters = fake_num_skaters type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.home_even_strength_assists == 1 def test_invalid_away_power_play_assists_returns_default(self): assists = ['0', '1', 'bad'] fake_assists = PropertyMock(return_value=assists) fake_num_skaters = PropertyMock(return_value=3) fake_num_goalies = PropertyMock(return_value=0) type(self.boxscore)._away_power_play_assists = fake_assists type(self.boxscore)._away_skaters = fake_num_skaters type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_power_play_assists == 1 def test_invalid_home_power_play_assits_returns_default(self): assists = ['0', '1', 'bad'] fake_assists = PropertyMock(return_value=assists) fake_num_skaters = PropertyMock(return_value=0) fake_num_goalies = PropertyMock(return_value=0) type(self.boxscore)._home_power_play_assists = fake_assists type(self.boxscore)._away_skaters = fake_num_skaters type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.home_power_play_assists == 1 def test_invalid_away_short_handed_assists_returns_default(self): assists = ['0', '1', 'bad'] fake_assists = PropertyMock(return_value=assists) fake_num_skaters = PropertyMock(return_value=3) fake_num_goalies = PropertyMock(return_value=0) type(self.boxscore)._away_short_handed_assists = fake_assists type(self.boxscore)._away_skaters = fake_num_skaters type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_short_handed_assists == 1 def test_invalid_home_short_handed_assits_returns_default(self): assists = ['0', '1', 'bad'] fake_assists = PropertyMock(return_value=assists) fake_num_skaters = PropertyMock(return_value=0) fake_num_goalies = PropertyMock(return_value=0) type(self.boxscore)._home_short_handed_assists = fake_assists type(self.boxscore)._away_skaters = fake_num_skaters type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.home_short_handed_assists == 1 def test_invalid_url_returns_none(self): result = Boxscore(None)._retrieve_html_page('') assert result is None def test_regular_season_information(self): fields = { 'date': 'October 5, 2017', 'playoff_round': None, 'time': '7:00 PM', 'attendance': 17565, 'arena': 'TD Garden', 'duration': '2:39' } mock_field = """October 5, 2017, 7:00 PM Attendance: 17,565 Arena: TD Garden Game Duration: 2:39 Logos via Sports Logos.net / About logos """ m = MockBoxscoreData(MockField(mock_field)) self.boxscore._parse_game_date_and_location(m) for field, value in fields.items(): assert getattr(self.boxscore, field) == value def test_playoffs_information(self): fields = { 'date': 'June 7, 2018', 'playoff_round': 'Stanley Cup Final', 'time': '8:00 PM', 'attendance': 18529, 'arena': 'T-Mobile Arena', 'duration': '2:45' } mock_field = """June 7, 2018, 8:00 PM Stanley Cup Final Attendance: 18,529 Arena: T-Mobile Arena Game Duration: 2:45 Logos via Sports Logos.net / About logos """ m = MockBoxscoreData(MockField(mock_field)) self.boxscore._parse_game_date_and_location(m) for field, value in fields.items(): assert getattr(self.boxscore, field) == value def test_no_game_information(self): fields = { 'date': '', 'playoff_round': None, 'time': None, 'attendance': None, 'arena': None, 'duration': None } mock_field = '\n' m = MockBoxscoreData(MockField(mock_field)) self.boxscore._parse_game_date_and_location(m) for field, value in fields.items(): assert getattr(self.boxscore, field) == value def test_limited_game_information(self): fields = { 'date': 'June 7, 2018', 'playoff_round': 'Stanley Cup Final', 'time': None, 'attendance': None, 'arena': 'T-Mobile Arena', 'duration': None } mock_field = """June 7, 2018 Stanley Cup Final Arena: T-Mobile Arena Logos via Sports Logos.net / About logos """ m = MockBoxscoreData(MockField(mock_field)) self.boxscore._parse_game_date_and_location(m) for field, value in fields.items(): assert getattr(self.boxscore, field) == value def test_away_shutout_single_goalies(self): shutout = ['1', '0'] fake_shutout = PropertyMock(return_value=shutout) fake_num_goalies = PropertyMock(return_value=1) type(self.boxscore)._away_shutout = fake_shutout type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_shutout == 1 def test_away_shutout_multiple_goalies(self): shutout = ['0', '1', '0'] fake_shutout = PropertyMock(return_value=shutout) fake_num_goalies = PropertyMock(return_value=2) type(self.boxscore)._away_shutout = fake_shutout type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_shutout == 1 def test_away_shutout_multiple_goalies_empty_field(self): shutout = ['', '1', '0'] fake_shutout = PropertyMock(return_value=shutout) fake_num_goalies = PropertyMock(return_value=2) type(self.boxscore)._away_shutout = fake_shutout type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_shutout == 1 def test_home_shutout_single_goalies(self): shutout = ['0', '1'] fake_shutout = PropertyMock(return_value=shutout) fake_num_goalies = PropertyMock(return_value=1) type(self.boxscore)._home_shutout = fake_shutout type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.home_shutout == 1 def test_home_shutout_multiple_goalies(self): shutout = ['0', '0', '1'] fake_shutout = PropertyMock(return_value=shutout) fake_num_goalies = PropertyMock(return_value=1) type(self.boxscore)._home_shutout = fake_shutout type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.home_shutout == 1 def test_home_shutout_multiple_goalies_empty_field(self): shutout = ['0', '', '1'] fake_shutout = PropertyMock(return_value=shutout) fake_num_goalies = PropertyMock(return_value=1) type(self.boxscore)._home_shutout = fake_shutout type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.home_shutout == 1 def test_away_saves_single_goalies(self): saves = ['29', '30'] fake_saves = PropertyMock(return_value=saves) fake_num_goalies = PropertyMock(return_value=1) type(self.boxscore)._away_saves = fake_saves type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_saves == 29 def test_away_saves_multiple_goalies_empty_field(self): saves = ['29', '3', '30'] fake_saves = PropertyMock(return_value=saves) fake_num_goalies = PropertyMock(return_value=2) type(self.boxscore)._away_saves = fake_saves type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_saves == 32 def test_away_saves_multiple_goalies_empty_field(self): saves = ['29', '', '30'] fake_saves = PropertyMock(return_value=saves) fake_num_goalies = PropertyMock(return_value=2) type(self.boxscore)._away_saves = fake_saves type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.away_saves == 29 def test_home_saves_single_goalies(self): saves = ['29', '30'] fake_saves = PropertyMock(return_value=saves) fake_num_goalies = PropertyMock(return_value=1) type(self.boxscore)._home_saves = fake_saves type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.home_saves == 30 def test_home_saves_multiple_goalies_empty_field(self): saves = ['29', '3', '30'] fake_saves = PropertyMock(return_value=saves) fake_num_goalies = PropertyMock(return_value=1) type(self.boxscore)._home_saves = fake_saves type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.home_saves == 33 def test_home_saves_multiple_goalies_empty_field(self): saves = ['29', '30', ''] fake_saves = PropertyMock(return_value=saves) fake_num_goalies = PropertyMock(return_value=1) type(self.boxscore)._home_saves = fake_saves type(self.boxscore)._away_goalies = fake_num_goalies assert self.boxscore.home_saves == 30 def test_away_save_percentage(self): fake_saves = PropertyMock(return_value=30) fake_shots_on_goal = PropertyMock(return_value=33) type(self.boxscore).away_saves = fake_saves type(self.boxscore).home_shots_on_goal = fake_shots_on_goal assert self.boxscore.away_save_percentage == 0.909 def test_away_save_percentage_zero_shots(self): fake_saves = PropertyMock(return_value=0) fake_shots_on_goal = PropertyMock(return_value=0) type(self.boxscore).away_saves = fake_saves type(self.boxscore).home_shots_on_goal = fake_shots_on_goal assert self.boxscore.away_save_percentage == 0.0 def test_home_save_percentage(self): fake_saves = PropertyMock(return_value=30) fake_shots_on_goal = PropertyMock(return_value=33) type(self.boxscore).home_saves = fake_saves type(self.boxscore).away_shots_on_goal = fake_shots_on_goal assert self.boxscore.home_save_percentage == 0.909 def test_home_save_percentage_zero_shots(self): fake_saves = PropertyMock(return_value=0) fake_shots_on_goal = PropertyMock(return_value=0) type(self.boxscore).home_saves = fake_saves type(self.boxscore).away_shots_on_goal = fake_shots_on_goal assert self.boxscore.home_save_percentage == 0.0 def test_no_class_information_returns_dataframe_of_none(self): mock_goals = PropertyMock(return_value=None) type(self.boxscore)._away_goals = mock_goals type(self.boxscore)._home_goals = mock_goals assert self.boxscore.dataframe is None class TestMLBBoxscores: @patch('requests.get', side_effect=mock_pyquery) def setup_method(self, *args, **kwargs): flexmock(Boxscores) \ .should_receive('_get_team_details') \ .and_return((None, None, None, None, None, None)) flexmock(Boxscores) \ .should_receive('_find_games') \ .and_return(None) self.boxscores = Boxscores(None) def test_improper_loser_boxscore_format_skips_game(self): mock_html = pq("""<table class="teams"> <tbody> <tr class="loser"> <td class="right">1</td> <td class="right gamelink"> </td> </tr> <tr class="winner"> <td><a href="/teams/DET/2019.html">Detroit Red Wings</a></td> <td class="right">3</td> <td class="right">  </td> </tr> </tbody> </table>""") games = self.boxscores._extract_game_info([mock_html]) assert len(games) == 0 def test_improper_winner_boxscore_format_skips_game(self): mock_html = pq("""<table class="teams"> <tbody> <tr class="loser"> <td><a href="/teams/LAK/2019.html">Los Angeles Kings</a></td> <td class="right">1</td> <td class="right gamelink"> <a href="/boxscores/201812100DET.html">Final</a> </td> </tr> <tr class="winner"> <td class="right">3</td> <td class="right">  </td> </tr> </tbody> </table>""") games = self.boxscores._extract_game_info([mock_html]) assert len(games) == 0

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c365664b9c836dcf8ce6404c28cf198414c006e5

144

py

Python

jupyterlab_nvdashboard/tests/test_utils.py

vidosits/jupyterlab-nvdashboard

50cf834b22dc3c6a6ce44997cbfd01aae2bed7e2

[ "BSD-3-Clause" ]

368

2019-10-07T15:32:50.000Z

2022-03-27T03:42:29.000Z

jupyterlab_nvdashboard/tests/test_utils.py

vidosits/jupyterlab-nvdashboard

50cf834b22dc3c6a6ce44997cbfd01aae2bed7e2

[ "BSD-3-Clause" ]

82

2019-10-03T02:05:39.000Z

2022-03-17T20:27:16.000Z

jupyterlab_nvdashboard/tests/test_utils.py

vidosits/jupyterlab-nvdashboard

50cf834b22dc3c6a6ce44997cbfd01aae2bed7e2

[ "BSD-3-Clause" ]

42

2019-10-03T09:02:46.000Z

2021-12-08T05:32:24.000Z

import pytest def test_format_bytes(): from jupyterlab_nvdashboard.utils import format_bytes assert format_bytes(1e13) == "10.00 TB"

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1

0

1

0

6

c370c3f931c787eed137e054e44a6d964aaf49e0

13,362

py

Python

src/tests/functional/api/test_api_views.py

s-light/pretalx

5abed452688d8c0b3e44e71b7ce3ab9b6d80bd95

[ "Apache-2.0" ]

null

src/tests/functional/api/test_api_views.py

s-light/pretalx

5abed452688d8c0b3e44e71b7ce3ab9b6d80bd95

[ "Apache-2.0" ]

null

src/tests/functional/api/test_api_views.py

s-light/pretalx

5abed452688d8c0b3e44e71b7ce3ab9b6d80bd95

[ "Apache-2.0" ]

null

import json import pytest @pytest.mark.django_db def test_api_user_endpoint(orga_client, room): response = orga_client.get('/api/me', follow=True) assert response.status_code == 200 content = json.loads(response.content.decode()) assert set(content.keys()) == {'name', 'email', 'locale', 'timezone'} @pytest.mark.django_db def test_can_only_see_public_events(client, event, other_event): other_event.is_public = False other_event.save() assert event.is_public assert not other_event.is_public response = client.get('/api/events', follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert len(content) == 1, content assert content[0]['name']['en'] == event.name @pytest.mark.django_db def test_orga_can_see_nonpublic_events(orga_client, event, other_event): event.is_public = False event.save() assert not event.is_public assert other_event.is_public response = orga_client.get('/api/events', follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert len(content) == 2, content assert content[0]['name']['en'] == event.name @pytest.mark.django_db def test_can_only_see_public_submissions( client, slot, accepted_submission, rejected_submission, submission ): response = client.get(submission.event.api_urls.submissions, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 1 assert content['results'][0]['title'] == slot.submission.title @pytest.mark.django_db def test_can_only_see_public_submissions_if_public_schedule( client, slot, accepted_submission, rejected_submission, submission, answer ): submission.event.settings.set('show_schedule', False) response = client.get(submission.event.api_urls.submissions, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 0 assert all(submission['answers'] == [] for submission in content['results']) @pytest.mark.django_db def test_orga_can_see_all_submissions( orga_client, slot, accepted_submission, rejected_submission, submission, answer ): response = orga_client.get(submission.event.api_urls.submissions, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 4 assert content['results'][0]['title'] == slot.submission.title assert any(submission['answers'] == [] for submission in content['results']) assert any(submission['answers'] != [] for submission in content['results']) @pytest.mark.django_db def test_orga_can_see_all_submissions_even_nonpublic( orga_client, slot, accepted_submission, rejected_submission, submission ): submission.event.settings.set('show_schedule', False) response = orga_client.get(submission.event.api_urls.submissions, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 4 assert content['results'][0]['title'] == slot.submission.title @pytest.mark.django_db def test_only_see_talks_when_a_release_exists( orga_client, confirmed_submission, rejected_submission, submission ): response = orga_client.get(submission.event.api_urls.talks, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 0 @pytest.mark.django_db def test_can_only_see_public_talks( client, slot, accepted_submission, rejected_submission, submission ): response = client.get(submission.event.api_urls.talks, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 1 assert content['results'][0]['title'] == slot.submission.title @pytest.mark.django_db def test_can_only_see_public_talks_if_public_schedule( client, slot, accepted_submission, rejected_submission, submission ): submission.event.settings.set('show_schedule', False) response = client.get(submission.event.api_urls.talks, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 0 @pytest.mark.django_db def test_orga_can_see_all_talks( orga_client, slot, accepted_submission, rejected_submission, submission ): response = orga_client.get(submission.event.api_urls.talks, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 1 assert content['results'][0]['title'] == slot.submission.title @pytest.mark.django_db def test_orga_can_see_all_talks_even_nonpublic( orga_client, slot, accepted_submission, rejected_submission, submission ): submission.event.settings.set('show_schedule', False) response = orga_client.get(submission.event.api_urls.talks, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 1 assert content['results'][0]['title'] == slot.submission.title @pytest.mark.django_db def test_user_can_see_schedule(client, slot): assert slot.submission.event.schedules.count() == 2 response = client.get(slot.submission.event.api_urls.schedules, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 1 @pytest.mark.django_db def test_user_cannot_see_wip_schedule(client, slot): assert slot.submission.event.schedules.count() == 2 response = client.get(slot.submission.event.api_urls.schedules + 'wip', follow=True) json.loads(response.content.decode()) assert response.status_code == 404 @pytest.mark.django_db def test_user_cannot_see_schedule_if_not_public(client, slot): slot.submission.event.settings.set('show_schedule', False) assert slot.submission.event.schedules.count() == 2 response = client.get(slot.submission.event.api_urls.schedules, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 0 @pytest.mark.django_db def test_orga_can_see_schedule(orga_client, slot): assert slot.submission.event.schedules.count() == 2 response = orga_client.get(slot.submission.event.api_urls.schedules, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 2 @pytest.mark.django_db def test_orga_can_see_wip_schedule(orga_client, slot): assert slot.submission.event.schedules.count() == 2 response = orga_client.get( slot.submission.event.api_urls.schedules + 'wip', follow=True ) json.loads(response.content.decode()) assert response.status_code == 200 @pytest.mark.django_db def test_orga_can_see_current_schedule(orga_client, slot): assert slot.submission.event.schedules.count() == 2 response = orga_client.get( slot.submission.event.api_urls.schedules + 'latest', follow=True ) json.loads(response.content.decode()) assert response.status_code == 200 assert slot.submission.title in response.content.decode() @pytest.mark.django_db def test_orga_cannot_see_schedule_even_if_not_public(orga_client, slot): slot.submission.event.settings.set('show_schedule', False) assert slot.submission.event.schedules.count() == 2 response = orga_client.get(slot.submission.event.api_urls.schedules, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 2 @pytest.mark.django_db def test_can_only_see_public_speakers( client, slot, accepted_submission, rejected_submission, submission, impersonal_answer, ): response = client.get(submission.event.api_urls.speakers, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 1 assert content['results'][0]['name'] == accepted_submission.speakers.first().name assert set(content['results'][0].keys()) == { 'name', 'code', 'biography', 'submissions', 'avatar', } @pytest.mark.django_db def test_can_only_see_public_speakerss_if_public_schedule( client, slot, accepted_submission, rejected_submission, submission ): submission.event.settings.set('show_schedule', False) response = client.get(submission.event.api_urls.speakers, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 0 @pytest.mark.django_db def test_orga_can_see_all_speakers( orga_client, slot, accepted_submission, rejected_submission, submission, impersonal_answer, ): response = orga_client.get(submission.event.api_urls.speakers, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 2 assert set(content['results'][0].keys()) == { 'name', 'code', 'email', 'biography', 'submissions', 'answers', 'avatar', } assert set(content['results'][0]['answers'][0].keys()) == { 'answer', 'answer_file', 'person', 'question', 'submission', 'options', 'id', } @pytest.mark.django_db def test_reviewer_cannot_see_speakers( review_client, slot, accepted_submission, rejected_submission, submission, impersonal_answer, ): submission.event.settings.review_hide_speaker_names = True response = review_client.get(submission.event.api_urls.speakers, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 1 # can see the slot's speaker, but not the other submissions' @pytest.mark.django_db def test_orga_can_see_all_speakers_even_nonpublic( orga_client, slot, accepted_submission, rejected_submission, submission ): submission.event.settings.set('show_schedule', False) response = orga_client.get(submission.event.api_urls.speakers, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 2 @pytest.mark.django_db def test_orga_speakers_with_multiple_talks_are_not_duplicated( client, speaker, slot, other_slot, accepted_submission, other_accepted_submission ): other_accepted_submission.speakers.add(accepted_submission.speakers.first()) response = client.get(accepted_submission.event.api_urls.speakers, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert content['count'] == 2 @pytest.mark.django_db def test_anon_cannot_see_reviews(client, event, review): response = client.get(event.api_urls.reviews, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert len(content['results']) == 0, content @pytest.mark.django_db def test_orga_can_see_reviews(orga_client, event, review): response = orga_client.get(event.api_urls.reviews, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert len(content['results']) == 1 @pytest.mark.django_db def test_reviewer_can_see_reviews(review_client, event, review, other_review): response = review_client.get(event.api_urls.reviews, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert len(content['results']) == 2, content @pytest.mark.django_db def test_reviewer_can_filter_by_submission(review_client, event, review, other_review): response = review_client.get( event.api_urls.reviews + f'?submission__code={review.submission.code}', follow=True, ) content = json.loads(response.content.decode()) assert response.status_code == 200 assert len(content['results']) == 1, content @pytest.mark.django_db def test_reviewer_cannot_see_review_to_own_talk( review_user, review_client, event, review, other_review ): other_review.submission.speakers.add(review_user) response = review_client.get(event.api_urls.reviews, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert len(content['results']) == 1, content @pytest.mark.django_db def test_everybody_can_see_rooms(client, room): response = client.get(room.event.api_urls.rooms, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert len(content['results']) == 1, content assert 'speaker_info' not in content['results'][0] @pytest.mark.django_db def test_orga_can_see_room_speaker_info(orga_client, room): response = orga_client.get(room.event.api_urls.rooms, follow=True) content = json.loads(response.content.decode()) assert response.status_code == 200 assert len(content['results']) == 1, content assert 'speaker_info' in content['results'][0]

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6f00237d5ff01654dba32165ed49a88a7a15a299

43,461

py

Python

action-server/tests/actions/test_daily_ci_enroll_form.py

dialoguemd/covidflow

b159b76dc68462f272614db4cbf716844872ebca

[ "MIT" ]

7

2020-05-23T07:07:26.000Z

2021-11-29T05:58:51.000Z

action-server/tests/actions/test_daily_ci_enroll_form.py

dialoguemd/covidflow

b159b76dc68462f272614db4cbf716844872ebca

[ "MIT" ]

210

2020-04-13T17:21:55.000Z

2021-04-20T15:46:26.000Z

action-server/tests/actions/test_daily_ci_enroll_form.py

dialoguemd/covidflow

b159b76dc68462f272614db4cbf716844872ebca

[ "MIT" ]

3

2020-04-09T14:38:09.000Z

2020-07-29T15:06:11.000Z

from unittest.mock import MagicMock, patch import pytest from rasa_sdk.events import Form, SlotSet from rasa_sdk.forms import REQUESTED_SLOT from covidflow.actions.daily_ci_enroll_form import ( CODE_TRY_COUNTER_SLOT, DO_ENROLL_SLOT, FORM_NAME, JUST_SENT_CODE_SLOT, NO_CODE_SOLUTION_SLOT, PHONE_TO_CHANGE_SLOT, PHONE_TRY_COUNTER_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT, VALIDATION_CODE_REFERENCE_SLOT, VALIDATION_CODE_SLOT, WANTS_CANCEL_SLOT, DailyCiEnrollForm, ) from covidflow.constants import ( FIRST_NAME_SLOT, HAS_DIALOGUE_SLOT, PHONE_NUMBER_SLOT, PRECONDITIONS_SLOT, ) from .form_test_helper import FormTestCase FIRST_NAME = "John" PHONE_NUMBER = "15141234567" VALIDATION_CODE = "4567" DOMAIN = { "responses": { "utter_ask_daily_ci_enroll__wants_cancel_error": [{"text": ""}], "utter_ask_daily_ci_enroll__no_code_solution_error": [{"text": ""}], "utter_ask_preconditions_error": [{"text": ""}], "utter_ask_daily_ci_enroll__preconditions_examples_error": [{"text": ""}], } } def AsyncMock(*args, **kwargs): mock = MagicMock(*args, **kwargs) async def mock_coroutine(*args, **kwargs): return mock(*args, **kwargs) mock_coroutine.mock = mock return mock_coroutine class TestDailyCiEnrollForm(FormTestCase): def setUp(self): super().setUp() self.form = DailyCiEnrollForm() def test_validate_first_name(self): slot_mapping = self.form.slot_mappings()[FIRST_NAME_SLOT] self.assertEqual(slot_mapping, self.form.from_text()) self._validate_first_name("john", "john") self._validate_first_name("John", "John") self._validate_first_name("john john", "john john") # At the moment, we can't extract the name self._validate_first_name("it's John!", "it's John!") def _validate_first_name(self, text: str, expected_name: str): slot_values = self.form.validate_first_name(text, self.dispatcher, None, None) self.assertEqual({FIRST_NAME_SLOT: expected_name}, slot_values) @pytest.mark.asyncio async def test_validate_phone_number(self): slot_mapping = self.form.slot_mappings()[PHONE_NUMBER_SLOT] self.assertEqual(slot_mapping[-1], self.form.from_text()) await self._validate_phone_number("5145554567", "15145554567") await self._validate_phone_number("15145554567", "15145554567") await self._validate_phone_number("514-555-4567", "15145554567") await self._validate_phone_number("1 (514)-555-4567", "15145554567") await self._validate_phone_number("it's 514-555-4567!", "15145554567") await self._validate_phone_number("it's 1 514 555 4567", "15145554567") await self._validate_phone_number("145554567", None) await self._validate_phone_number("25145554567", None) async def _validate_phone_number(self, text: str, expected_phone_number: str): tracker = self.create_tracker( slots={VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE} ) slot_values = await self.form.validate_phone_number( text, self.dispatcher, tracker, None ) self.assertEqual( expected_phone_number, slot_values.get(PHONE_NUMBER_SLOT, None) ) @pytest.mark.asyncio async def test_validate_validation_code(self): slot_mapping = self.form.slot_mappings()[VALIDATION_CODE_SLOT][-1] self.assertEqual(slot_mapping, self.form.from_text()) await self._validate_validation_code("its 4567", "4567") await self._validate_validation_code("4567", "4567") await self._validate_validation_code("45678", None) await self._validate_validation_code("514", None) await self._validate_validation_code("4325", None) async def _validate_validation_code(self, text: str, expected_validation_code: str): tracker = self.create_tracker( slots={VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE} ) slot_values = await self.form.validate_daily_ci_enroll__validation_code( text, self.dispatcher, tracker, None ) self.assertEqual( expected_validation_code, slot_values.get(VALIDATION_CODE_SLOT, None) ) def test_form_activation(self): tracker = self.create_tracker(active_form=False) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_WITH_EXAMPLES_SLOT, "N/A"), Form(FORM_NAME), SlotSet(REQUESTED_SLOT, DO_ENROLL_SLOT), ] ) self.assert_templates( [ "utter_daily_ci_enroll__offer_checkin", "utter_daily_ci_enroll__explain_checkin_1", "utter_daily_ci_enroll__explain_checkin_2", "utter_ask_daily_ci_enroll__do_enroll", ] ) def test_provide_do_enroll_checkin_affirm(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: DO_ENROLL_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", }, intent="affirm", ) self.run_form(tracker, DOMAIN) self.assert_events( [SlotSet(DO_ENROLL_SLOT, True), SlotSet(REQUESTED_SLOT, FIRST_NAME_SLOT),], ) self.assert_templates( ["utter_daily_ci_enroll__start_enroll", "utter_ask_first_name",], ) def test_provide_do_enroll_checkin_deny(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: DO_ENROLL_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", }, intent="deny", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(DO_ENROLL_SLOT, False), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates([]) def test_provide_first_name(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: FIRST_NAME_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, }, text=FIRST_NAME, ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(FIRST_NAME_SLOT, FIRST_NAME), SlotSet(REQUESTED_SLOT, PHONE_NUMBER_SLOT), ], ) self.assert_templates( [ "utter_daily_ci_enroll__thanks_first_name", "utter_daily_ci_enroll__text_message_checkin", "utter_ask_phone_number", ], ) def test_provide_invalid_first_name(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: FIRST_NAME_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, }, text=" ", ) self.run_form(tracker, DOMAIN) self.assert_events( [SlotSet(FIRST_NAME_SLOT, None), SlotSet(REQUESTED_SLOT, FIRST_NAME_SLOT),], ) self.assert_templates(["utter_ask_first_name"]) @patch( "covidflow.actions.daily_ci_enroll_form.send_validation_code", new=AsyncMock(return_value=VALIDATION_CODE), ) def test_provide_phone_number(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PHONE_NUMBER_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, }, text=PHONE_NUMBER, ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PHONE_NUMBER_SLOT, PHONE_NUMBER), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(VALIDATION_CODE_REFERENCE_SLOT, VALIDATION_CODE), SlotSet(JUST_SENT_CODE_SLOT, True), SlotSet(REQUESTED_SLOT, VALIDATION_CODE_SLOT), ], ) self.assert_templates( [ "utter_daily_ci_enroll__acknowledge", "utter_ask_daily_ci_enroll__validation_code", ] ) @patch( "covidflow.actions.daily_ci_enroll_form.send_validation_code", new=AsyncMock(return_value=VALIDATION_CODE), ) def test_provide_phone_number_after_change(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PHONE_NUMBER_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", JUST_SENT_CODE_SLOT: True, CODE_TRY_COUNTER_SLOT: 1, DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, }, text=PHONE_NUMBER, ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PHONE_NUMBER_SLOT, PHONE_NUMBER), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(VALIDATION_CODE_REFERENCE_SLOT, VALIDATION_CODE), SlotSet(JUST_SENT_CODE_SLOT, True), SlotSet(REQUESTED_SLOT, VALIDATION_CODE_SLOT), ], ) self.assert_templates( [ "utter_daily_ci_enroll__acknowledge", "utter_ask_daily_ci_enroll__validation_code", ] ) @patch( "covidflow.actions.daily_ci_enroll_form.send_validation_code", new=AsyncMock(return_value=None), ) def test_provide_phone_number_sms_error(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PHONE_NUMBER_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, }, text=PHONE_NUMBER, ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PHONE_NUMBER_SLOT, PHONE_NUMBER), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(DO_ENROLL_SLOT, False), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates( [ "utter_daily_ci_enroll__acknowledge", "utter_daily_ci_enroll__validation_code_not_sent_1", "utter_daily_ci_enroll__validation_code_not_sent_2", "utter_daily_ci_enroll__continue", ] ) def test_provide_first_invalid_phone_number(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PHONE_NUMBER_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, }, text=" ", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PHONE_NUMBER_SLOT, None), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(PHONE_TRY_COUNTER_SLOT, 1), SlotSet(REQUESTED_SLOT, PHONE_NUMBER_SLOT), ], ) self.assert_templates( [ "utter_daily_ci_enroll__invalid_phone_number", "utter_ask_phone_number_error", ] ) def test_provide_second_invalid_phone_number(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PHONE_NUMBER_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_TRY_COUNTER_SLOT: 1, }, text=" ", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PHONE_NUMBER_SLOT, None), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(PHONE_TRY_COUNTER_SLOT, 2), SlotSet(REQUESTED_SLOT, PHONE_NUMBER_SLOT), ], ) self.assert_templates( [ "utter_daily_ci_enroll__invalid_phone_number", "utter_ask_phone_number_error", ] ) def test_provide_third_invalid_phone_number(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PHONE_NUMBER_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_TRY_COUNTER_SLOT: 2, }, text=" ", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PHONE_NUMBER_SLOT, None), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(DO_ENROLL_SLOT, False), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates(["utter_daily_ci_enroll__invalid_phone_no_checkin"]) def test_provide_no_phone_number(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PHONE_NUMBER_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, }, intent="no_phone", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PHONE_NUMBER_SLOT, None), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(DO_ENROLL_SLOT, False), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates( [ "utter_daily_ci_enroll__no_phone_no_checkin", "utter_daily_ci_enroll__continue", ] ) def test_provide_phone_number_cancel(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PHONE_NUMBER_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, }, intent="cancel", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PHONE_NUMBER_SLOT, None), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(WANTS_CANCEL_SLOT, None), SlotSet(REQUESTED_SLOT, WANTS_CANCEL_SLOT), ], ) self.assert_templates(["utter_ask_daily_ci_enroll__wants_cancel"]) def test_provide_wants_cancel_affirm(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: WANTS_CANCEL_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, WANTS_CANCEL_SLOT: None, }, intent="affirm", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(WANTS_CANCEL_SLOT, True), SlotSet(DO_ENROLL_SLOT, False), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates(["utter_daily_ci_enroll__no_problem_continue"]) def test_provide_wants_cancel_deny(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: WANTS_CANCEL_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, WANTS_CANCEL_SLOT: None, }, intent="deny", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(WANTS_CANCEL_SLOT, False), SlotSet(PHONE_TRY_COUNTER_SLOT, 1), SlotSet(REQUESTED_SLOT, PHONE_NUMBER_SLOT), ], ) self.assert_templates( ["utter_daily_ci_enroll__ok_continue", "utter_ask_phone_number_error"] ) def test_provide_wants_cancel_error(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: WANTS_CANCEL_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, WANTS_CANCEL_SLOT: None, }, intent="something_else", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(WANTS_CANCEL_SLOT, None), SlotSet(REQUESTED_SLOT, WANTS_CANCEL_SLOT), ], ) self.assert_templates(["utter_ask_daily_ci_enroll__wants_cancel_error"]) def test_provide_validation_code(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, text=VALIDATION_CODE, ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, VALIDATION_CODE), SlotSet(JUST_SENT_CODE_SLOT, False), SlotSet(REQUESTED_SLOT, PRECONDITIONS_SLOT), ], ) self.assert_templates( ["utter_daily_ci_enroll__thanks", "utter_ask_preconditions"] ) def test_provide_first_invalid_validation_code(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, text=" ", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(CODE_TRY_COUNTER_SLOT, 1), SlotSet(JUST_SENT_CODE_SLOT, False), SlotSet(REQUESTED_SLOT, VALIDATION_CODE_SLOT), ], ) self.assert_templates(["utter_ask_daily_ci_enroll__validation_code_error"]) def test_provide_second_invalid_validation_code(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, CODE_TRY_COUNTER_SLOT: 1, }, text=" ", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(CODE_TRY_COUNTER_SLOT, 2), SlotSet(JUST_SENT_CODE_SLOT, False), SlotSet(REQUESTED_SLOT, VALIDATION_CODE_SLOT), ], ) self.assert_templates(["utter_ask_daily_ci_enroll__validation_code_error"]) def test_provide_third_invalid_validation_code(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, CODE_TRY_COUNTER_SLOT: 2, }, text=" ", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(DO_ENROLL_SLOT, False), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates(["utter_daily_ci_enroll__invalid_phone_no_checkin"]) def test_provide_validation_code_change_phone(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, intent="change_phone", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(PHONE_NUMBER_SLOT, None), SlotSet(PHONE_TO_CHANGE_SLOT, True), SlotSet(REQUESTED_SLOT, PHONE_NUMBER_SLOT), ], ) self.assert_templates(["utter_ask_phone_number_new"]) @patch( "covidflow.actions.daily_ci_enroll_form.send_validation_code", new=AsyncMock(return_value=VALIDATION_CODE), ) def test_provide_validation_code_phone_number(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, text=PHONE_NUMBER, ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(PHONE_NUMBER_SLOT, PHONE_NUMBER), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(VALIDATION_CODE_REFERENCE_SLOT, VALIDATION_CODE), SlotSet(JUST_SENT_CODE_SLOT, True), SlotSet(REQUESTED_SLOT, VALIDATION_CODE_SLOT), ], ) self.assert_templates( [ "utter_daily_ci_enroll__acknowledge_new_phone_number", "utter_ask_daily_ci_enroll__validation_code", ] ) @patch( "covidflow.actions.daily_ci_enroll_form.send_validation_code", new=AsyncMock(return_value=VALIDATION_CODE), ) def test_provide_validation_code_change_phone_with_new(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, intent="change_phone", text=PHONE_NUMBER, ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(PHONE_NUMBER_SLOT, PHONE_NUMBER), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(VALIDATION_CODE_REFERENCE_SLOT, VALIDATION_CODE), SlotSet(JUST_SENT_CODE_SLOT, True), SlotSet(REQUESTED_SLOT, VALIDATION_CODE_SLOT), ], ) self.assert_templates( [ "utter_daily_ci_enroll__acknowledge_new_phone_number", "utter_ask_daily_ci_enroll__validation_code", ] ) @patch( "covidflow.actions.daily_ci_enroll_form.send_validation_code", new=AsyncMock(return_value=None), ) def test_provide_validation_code_phone_number_sms_error(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, text=PHONE_NUMBER, ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(PHONE_NUMBER_SLOT, PHONE_NUMBER), SlotSet(PHONE_TO_CHANGE_SLOT, False), SlotSet(DO_ENROLL_SLOT, False), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates( [ "utter_daily_ci_enroll__acknowledge_new_phone_number", "utter_daily_ci_enroll__validation_code_not_sent_1", "utter_daily_ci_enroll__validation_code_not_sent_2", "utter_daily_ci_enroll__continue", ] ) def test_provide_validation_code_did_not_get_code_first_time(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, intent="did_not_get_code", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(CODE_TRY_COUNTER_SLOT, 1), SlotSet(JUST_SENT_CODE_SLOT, False), SlotSet(NO_CODE_SOLUTION_SLOT, None), SlotSet(REQUESTED_SLOT, NO_CODE_SOLUTION_SLOT), ], ) self.assert_templates( ["utter_ask_daily_ci_enroll__no_code_solution",] ) def test_provide_validation_code_did_not_get_code_second_time(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", CODE_TRY_COUNTER_SLOT: 1, DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, intent="did_not_get_code", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(CODE_TRY_COUNTER_SLOT, 2), SlotSet(JUST_SENT_CODE_SLOT, False), SlotSet(NO_CODE_SOLUTION_SLOT, None), SlotSet(REQUESTED_SLOT, NO_CODE_SOLUTION_SLOT), ], ) self.assert_templates( ["utter_ask_daily_ci_enroll__no_code_solution",] ) def test_provide_validation_code_did_not_get_code_third_time(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: VALIDATION_CODE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", CODE_TRY_COUNTER_SLOT: 2, DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, intent="did_not_get_code", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(VALIDATION_CODE_SLOT, None), SlotSet(DO_ENROLL_SLOT, False), SlotSet(NO_CODE_SOLUTION_SLOT, None), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates( ["utter_daily_ci_enroll__invalid_phone_no_checkin",] ) @patch( "covidflow.actions.daily_ci_enroll_form.send_validation_code", new=AsyncMock(return_value=VALIDATION_CODE), ) def test_provide_no_code_solution_new_code(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: NO_CODE_SOLUTION_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", CODE_TRY_COUNTER_SLOT: 1, # set when received did_not_get_code intent DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, intent="new_code", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(NO_CODE_SOLUTION_SLOT, "new_code"), SlotSet(VALIDATION_CODE_REFERENCE_SLOT, VALIDATION_CODE), SlotSet(JUST_SENT_CODE_SLOT, True), SlotSet(REQUESTED_SLOT, VALIDATION_CODE_SLOT), ], ) self.assert_templates(["utter_ask_daily_ci_enroll__validation_code"]) @patch( "covidflow.actions.daily_ci_enroll_form.send_validation_code", new=AsyncMock(return_value=None), ) def test_provide_no_code_solution_new_code_sms_error(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: NO_CODE_SOLUTION_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", CODE_TRY_COUNTER_SLOT: 1, DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, intent="new_code", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(NO_CODE_SOLUTION_SLOT, "new_code"), SlotSet(DO_ENROLL_SLOT, False), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates( [ "utter_daily_ci_enroll__validation_code_not_sent_1", "utter_daily_ci_enroll__validation_code_not_sent_2", "utter_daily_ci_enroll__continue", ] ) def test_provide_no_code_solution_change_phone(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: NO_CODE_SOLUTION_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, intent="change_phone", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(NO_CODE_SOLUTION_SLOT, "change_phone"), SlotSet(PHONE_NUMBER_SLOT, None), SlotSet(PHONE_TO_CHANGE_SLOT, True), SlotSet(REQUESTED_SLOT, PHONE_NUMBER_SLOT), ], ) self.assert_templates(["utter_ask_phone_number_new"]) def test_provide_no_code_solution_error(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: NO_CODE_SOLUTION_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_REFERENCE_SLOT: VALIDATION_CODE, }, intent="anything", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(NO_CODE_SOLUTION_SLOT, None), SlotSet(REQUESTED_SLOT, NO_CODE_SOLUTION_SLOT), ], ) self.assert_templates(["utter_ask_daily_ci_enroll__no_code_solution_error"]) def test_provide_preconditions_affirm(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PRECONDITIONS_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, }, intent="affirm", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_SLOT, True), SlotSet(REQUESTED_SLOT, HAS_DIALOGUE_SLOT), ], ) self.assert_templates( ["utter_daily_ci_enroll__acknowledge", "utter_ask_has_dialogue"] ) def test_provide_preconditions_deny(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PRECONDITIONS_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, }, intent="deny", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_SLOT, False), SlotSet(REQUESTED_SLOT, HAS_DIALOGUE_SLOT), ], ) self.assert_templates( ["utter_daily_ci_enroll__acknowledge", "utter_ask_has_dialogue"], ) def test_provide_preconditions_error(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PRECONDITIONS_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, }, intent="other", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_SLOT, None), SlotSet(REQUESTED_SLOT, PRECONDITIONS_SLOT), ], ) self.assert_templates(["utter_ask_preconditions_error"],) def test_provide_preconditions_dont_know(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PRECONDITIONS_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, }, intent="dont_know", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_SLOT, None), SlotSet(PRECONDITIONS_WITH_EXAMPLES_SLOT, None), SlotSet(REQUESTED_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT), ], ) self.assert_templates( [ "utter_daily_ci_enroll__explain_preconditions", "utter_ask_daily_ci_enroll__preconditions_examples", ], ) def test_provide_preconditions_help_preconditions(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PRECONDITIONS_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, }, intent="help_preconditions", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_SLOT, None), SlotSet(PRECONDITIONS_WITH_EXAMPLES_SLOT, None), SlotSet(REQUESTED_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT), ], ) self.assert_templates( [ "utter_daily_ci_enroll__explain_preconditions", "utter_ask_daily_ci_enroll__preconditions_examples", ], ) def test_provide_preconditions_with_examples_affirm(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PRECONDITIONS_WITH_EXAMPLES_SLOT, DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, }, intent="affirm", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_WITH_EXAMPLES_SLOT, True), SlotSet(PRECONDITIONS_SLOT, True), SlotSet(REQUESTED_SLOT, HAS_DIALOGUE_SLOT), ], ) self.assert_templates( ["utter_daily_ci_enroll__acknowledge", "utter_ask_has_dialogue"] ) def test_provide_preconditions_with_examples_deny(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PRECONDITIONS_WITH_EXAMPLES_SLOT, DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, }, intent="deny", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_WITH_EXAMPLES_SLOT, False), SlotSet(PRECONDITIONS_SLOT, False), SlotSet(REQUESTED_SLOT, HAS_DIALOGUE_SLOT), ], ) self.assert_templates( ["utter_daily_ci_enroll__acknowledge", "utter_ask_has_dialogue"], ) def test_provide_preconditions_with_examples_dont_know(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PRECONDITIONS_WITH_EXAMPLES_SLOT, DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, }, intent="dont_know", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_WITH_EXAMPLES_SLOT, "dont_know"), SlotSet(PRECONDITIONS_SLOT, True), SlotSet(REQUESTED_SLOT, HAS_DIALOGUE_SLOT), ], ) self.assert_templates( ["utter_daily_ci_enroll__note_preconditions", "utter_ask_has_dialogue"], ) def test_provide_preconditions_with_examples_error(self): tracker = self.create_tracker( slots={ REQUESTED_SLOT: PRECONDITIONS_WITH_EXAMPLES_SLOT, DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, }, intent="other", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(PRECONDITIONS_WITH_EXAMPLES_SLOT, None), SlotSet(REQUESTED_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT), ], ) self.assert_templates( ["utter_ask_daily_ci_enroll__preconditions_examples_error"], ) @patch("covidflow.actions.daily_ci_enroll_form.ci_enroll") def test_provide_has_dialogue_affirm(self, mock_ci_enroll): tracker = self.create_tracker( slots={ REQUESTED_SLOT: HAS_DIALOGUE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, PRECONDITIONS_SLOT: True, }, intent="affirm", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(HAS_DIALOGUE_SLOT, True), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates( [ "utter_daily_ci_enroll__enroll_done_1", "utter_daily_ci_enroll__enroll_done_2", "utter_daily_ci_enroll__enroll_done_3", ] ) @patch("covidflow.actions.daily_ci_enroll_form.ci_enroll") def test_provide_has_dialogue_deny(self, mock_ci_enroll): tracker = self.create_tracker( slots={ REQUESTED_SLOT: HAS_DIALOGUE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, PRECONDITIONS_SLOT: True, }, intent="deny", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(HAS_DIALOGUE_SLOT, False), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates( [ "utter_daily_ci_enroll__enroll_done_1", "utter_daily_ci_enroll__enroll_done_2", "utter_daily_ci_enroll__enroll_done_3", ], ) @patch("covidflow.actions.daily_ci_enroll_form.ci_enroll", side_effect=Exception) def test_provide_has_dialogue_enrollment_failed(self, mock_ci_enroll): tracker = self.create_tracker( slots={ REQUESTED_SLOT: HAS_DIALOGUE_SLOT, PRECONDITIONS_WITH_EXAMPLES_SLOT: "N/A", DO_ENROLL_SLOT: True, FIRST_NAME_SLOT: FIRST_NAME, PHONE_NUMBER_SLOT: PHONE_NUMBER, VALIDATION_CODE_SLOT: VALIDATION_CODE, PRECONDITIONS_SLOT: True, }, intent="affirm", ) self.run_form(tracker, DOMAIN) self.assert_events( [ SlotSet(HAS_DIALOGUE_SLOT, True), Form(None), SlotSet(REQUESTED_SLOT, None), ], ) self.assert_templates( [ "utter_daily_ci_enroll__enroll_fail_1", "utter_daily_ci_enroll__enroll_fail_2", "utter_daily_ci_enroll__enroll_fail_3", ] ) mock_ci_enroll.assert_called()

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6f0921ee7873a4f3165dfb865e16b2ca70b1351a

14,452

py

Python

castoredc_api/tests/test_import/test_async_import/test_import_report_async.py

reiniervlinschoten/castoredc_api

54a71606fa681a05e795e42a37d4b4f58b97e787

[ "MIT" ]

1

2022-02-07T17:49:31.000Z

castoredc_api/tests/test_import/test_async_import/test_import_report_async.py

reiniervlinschoten/castoredc_api

54a71606fa681a05e795e42a37d4b4f58b97e787

[ "MIT" ]

48

2021-08-05T15:20:27.000Z

2022-03-28T14:49:25.000Z

castoredc_api/tests/test_import/test_async_import/test_import_report_async.py

reiniervlinschoten/castoredc_api

54a71606fa681a05e795e42a37d4b4f58b97e787

[ "MIT" ]

1

2021-08-06T07:06:37.000Z

import pytest from castoredc_api import CastorException from castoredc_api.importer.import_data import import_data class TestImportReportAsync: """Tests uploading data to Castor.""" def test_import_report_value_success(self, import_study): """Tests if uploading value data is successful""" imported_data = import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_values.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file.xlsx", study=import_study, label_data=False, target="Report", target_name="Medication", use_async=True, ) assert imported_data == self.report_success def test_import_report_label_success(self, import_study): """Tests if uploading label data is successful""" imported_data = import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_labels.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file.xlsx", study=import_study, label_data=True, target="Report", target_name="Medication", use_async=True, ) assert imported_data == self.report_success def test_import_report_bulk_success(self, import_study): """Tests if uploading label data in bulk is successful""" imported_data = import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_labels_bulk.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file.xlsx", study=import_study, label_data=True, target="Report", target_name="Medication", use_async=True, ) for record in imported_data: for item in imported_data[record]: assert item in self.report_success_bulk[record] def test_import_report_more_than_connections_success(self, import_study): """Tests if uploading label data is successful when uploading more than max_connections""" imported_data = import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_labels_bulk_large.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file.xlsx", study=import_study, label_data=True, target="Report", target_name="Medication", use_async=True, ) assert imported_data == self.report_more_than_connections def test_import_report_value_missing(self, import_study): """Tests if uploading value data with missings is successful""" imported_data = import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_values_missings.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file.xlsx", study=import_study, label_data=False, target="Report", target_name="Medication", use_async=True, ) assert imported_data == self.report_missing def test_import_report_label_missing(self, import_study): """Tests if uploading label data with missings is successful""" imported_data = import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_labels_missings.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file.xlsx", study=import_study, label_data=True, target="Report", target_name="Medication", use_async=True, ) assert imported_data == self.report_missing def test_import_report_value_error(self, import_study): """Tests if uploading value data with errors is successful""" with pytest.raises(CastorException) as e: import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_values_errors.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file.xlsx", study=import_study, label_data=False, target="Report", target_name="Medication", use_async=True, ) assert str(e.value) == self.report_error def test_import_report_label_error(self, import_study): """Tests if uploading label data with errors is successful""" with pytest.raises(CastorException) as e: import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_labels_errors.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file.xlsx", study=import_study, label_data=True, target="Report", target_name="Medication", use_async=True, ) assert str(e.value) == self.report_error def test_import_report_error_during_upload(self, import_study): """Tests if uploading data with an error during the upload process fails properly""" with pytest.raises(CastorException) as e: import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_values_errors_upload.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file.xlsx", study=import_study, label_data=False, target="Report", target_name="Medication", use_async=True, ) assert str(e.value) == self.report_error def test_import_report_error_during_upload_failed_field(self, import_study): """Tests if uploading data with an error during the upload process fails properly""" imported = import_data( data_source_path="tests/test_import/data_files_for_import_tests/data_file_report_medication_labels_nonexistent_field.xlsx", column_link_path="tests/test_import/link_files_for_import_tests/report_link_file_nonexistent_field.xlsx", study=import_study, label_data=True, target="Report", target_name="Medication", use_async=True, ) assert imported == self.report_error_wrong_field report_success = { "110001": [ { "success": { "med_name": "Azathioprine", "med_start": "05-12-2019", "med_stop": "05-12-2020", "med_dose": "0.05", "med_units": "3", }, "failed": {}, } ], "110002": [ { "success": { "med_name": "Vedolizumab", "med_start": "17-08-2018", "med_stop": "17-09-2020", "med_dose": "300", "med_units": "7", "med_other_unit": "mg/4 weeks", }, "failed": {}, } ], "110003": [ { "success": { "med_name": "Ustekinumab", "med_start": "19-12-2017", "med_stop": "03-06-2019", "med_dose": "90", "med_units": "7", "med_other_unit": "mg/8 weeks", }, "failed": {}, } ], "110004": [ { "success": { "med_name": "Thioguanine", "med_start": "25-04-2020", "med_stop": "27-05-2021", "med_dose": "15", "med_units": "2", }, "failed": {}, } ], "110005": [ { "success": { "med_name": "Tofacitinib", "med_start": "01-03-2020", "med_stop": "31-12-2999", "med_dose": "10", "med_units": "2", }, "failed": {}, } ], } report_missing = { "110001": [ { "success": { "med_name": "Azathioprine", "med_start": "05-12-2019", "med_stop": "05-12-2020", "med_dose": "0.05", "med_units": "3", }, "failed": {}, } ], "110002": [{"success": {"med_start": "17-08-2018"}, "failed": {}}], "110003": [ { "success": { "med_start": "19-12-2017", "med_stop": "03-06-2019", "med_dose": "90", "med_units": "7", "med_other_unit": "mg/8 weeks", }, "failed": {}, } ], "110004": [ {"success": {"med_name": "Thioguanine", "med_units": "2"}, "failed": {}} ], "110005": [ { "success": { "med_name": "Tofacitinib", "med_start": "01-03-2020", "med_stop": "31-12-2999", "med_dose": "10", }, "failed": {}, } ], } report_success_bulk = { "110001": [ { "success": { "med_name": "Azathioprine", "med_start": "05-12-2019", "med_stop": "05-12-2020", "med_dose": "0.05", "med_units": "3", }, "failed": {}, }, { "success": { "med_name": "Vedolizumab", "med_start": "17-08-2018", "med_stop": "17-09-2020", "med_dose": "300", "med_units": "7", "med_other_unit": "mg/4 weeks", }, "failed": {}, }, { "success": { "med_name": "Ustekinumab", "med_start": "19-12-2017", "med_stop": "03-06-2019", "med_dose": "90", "med_units": "7", "med_other_unit": "mg/8 weeks", }, "failed": {}, }, ], "110002": [ { "success": { "med_name": "Thioguanine", "med_start": "25-04-2020", "med_stop": "27-05-2021", "med_dose": "15", "med_units": "2", }, "failed": {}, }, { "success": { "med_name": "Tofacitinib", "med_start": "01-03-2020", "med_stop": "31-12-2999", "med_dose": "10", "med_units": "2", }, "failed": {}, }, ], } report_error = ( "Non-viable data found in dataset to be imported. See output folder for details" ) report_error_wrong_field = { "110001": [ { "success": { "med_name": "Azathioprine", "med_start": "05-12-2019", "med_stop": "05-12-2020", "med_dose": "0.05", "med_units": "3", }, "failed": {"pat_sex": ["BAD_REQUEST", "Unsupported field type"]}, } ], "110002": [ { "success": { "med_name": "Vedolizumab", "med_start": "17-08-2018", "med_stop": "17-09-2020", "med_dose": "300", "med_units": "7", "med_other_unit": "mg/4 weeks", }, "failed": {"pat_sex": ["BAD_REQUEST", "Unsupported field type"]}, } ], "110003": [ { "success": { "med_name": "Ustekinumab", "med_start": "19-12-2017", "med_stop": "03-06-2019", "med_dose": "90", "med_units": "7", "med_other_unit": "mg/8 weeks", }, "failed": {"pat_sex": ["BAD_REQUEST", "Unsupported field type"]}, } ], "110004": [ { "success": { "med_name": "Thioguanine", "med_start": "25-04-2020", "med_stop": "27-05-2021", "med_dose": "15", "med_units": "2", }, "failed": {"pat_sex": ["BAD_REQUEST", "Unsupported field type"]}, } ], "110005": [ { "success": { "med_name": "Tofacitinib", "med_start": "01-03-2020", "med_stop": "31-12-2999", "med_dose": "10", "med_units": "2", }, "failed": {"pat_sex": ["BAD_REQUEST", "Unsupported field type"]}, } ], } report_more_than_connections = { "110006": [ { "success": { "med_name": "Azathioprine", "med_start": "05-12-2019", "med_stop": "05-12-2020", "med_dose": "0.05", "med_units": "3", }, "failed": {}, } for i in range(39) ] }

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6f73ef8b45320b7f555fe98e8434d7029128b373

93

py

Python

src/__init__.py

kirbiyik/generate-any-text

7f9d78e439e23f99be34681268c052f7f6df9fdb

[ "MIT" ]

11

2019-07-27T04:42:17.000Z

2020-11-15T21:55:40.000Z

src/__init__.py

kirbiyik/generate-any-text

7f9d78e439e23f99be34681268c052f7f6df9fdb

[ "MIT" ]

null

src/__init__.py

kirbiyik/generate-any-text

7f9d78e439e23f99be34681268c052f7f6df9fdb

[ "MIT" ]

1

2019-07-27T14:02:40.000Z

from .layers import * from .model import * from .optimizer import * from .dataloader import *

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488b0f5283d971475c4ebbcb495d025d65a798f0

178

py

Python

test_inputs/tests.py

gribbg/x7-testing

c062c430ff1c31e943f04f152c9c88c179f5085b

[ "BSD-2-Clause" ]

null

test_inputs/tests.py

gribbg/x7-testing

c062c430ff1c31e943f04f152c9c88c179f5085b

[ "BSD-2-Clause" ]

null

test_inputs/tests.py

gribbg/x7-testing

c062c430ff1c31e943f04f152c9c88c179f5085b

[ "BSD-2-Clause" ]

null

""" This file will generate output that will be in error because the name of this module (tests) clashes with the @tests annotation. """ def this_wont_work(): pass

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6

488bb55325651b61fca0dc5655afb0eda4f622c8

26,437

py

Python

server/tracebin_server/traces/fixture_gen.py

alex/tracebin

cd9717e750718dcb94140f60957c3f543915317f

[ "BSD-3-Clause" ]

3

2015-11-08T12:45:45.000Z

2019-05-09T20:03:57.000Z

server/tracebin_server/traces/fixture_gen.py

alex/tracebin

cd9717e750718dcb94140f60957c3f543915317f

[ "BSD-3-Clause" ]

null

server/tracebin_server/traces/fixture_gen.py

alex/tracebin

cd9717e750718dcb94140f60957c3f543915317f

[ "BSD-3-Clause" ]

null

from textwrap import dedent from fixture_generator import fixture_generator from .models import (Log, RuntimeEnviroment, TimelineEvent, StatCounter, BaseTrace, PythonTrace, RegexTrace, NumPyPyTrace, TraceSection, TraceChunk, PythonChunk, ResOpChunk) @fixture_generator( Log, RuntimeEnviroment, TimelineEvent, StatCounter, BaseTrace, PythonTrace, RegexTrace, NumPyPyTrace, TraceSection, TraceChunk, PythonChunk, ResOpChunk ) def demo_data(): log = Log.objects.create( uploader=None, public=True, command="pypy test.py", runtime=9.8, ) for kind, key, value in [ (RuntimeEnviroment.JIT_OPTION, "trace_limit", "6000"), (RuntimeEnviroment.JIT_OPTION, "loop_longevity", "1000"), (RuntimeEnviroment.JIT_OPTION, "retrace_limit", "5"), (RuntimeEnviroment.JIT_OPTION, "trace_eagerness", "200"), (RuntimeEnviroment.JIT_OPTION, "enable_opts", "all"), (RuntimeEnviroment.JIT_OPTION, "max_retrace_guards", "15"), (RuntimeEnviroment.JIT_OPTION, "treshold", "1039"), (RuntimeEnviroment.JIT_OPTION, "function_threshold", "1619"), (RuntimeEnviroment.JIT_OPTION, "inlining", "1"), (RuntimeEnviroment.GC_OPTION, "PYPY_GC_NURSERY", "4MB"), (RuntimeEnviroment.GC_OPTION, "PYPY_GC_MAJOR_COLLECT", "1.82"), (RuntimeEnviroment.GC_OPTION, "PYPY_GC_GROWTH", "1.4"), (RuntimeEnviroment.BUILD_OPTION, "PyPy Version", "c2d42bf471da"), (RuntimeEnviroment.BUILD_OPTION, "GC root finder", "asmgcc"), (RuntimeEnviroment.BUILD_OPTION, "Garbage collector", "minimark"), ]: log.enviroment_options.create(kind=kind, key=key, value=value) # For now we just care about the percent of total time, so this idiotic # representation is fine, these add up to 100. start_time = 0 for event_type, duration in [ ("jit-running", 65), ("gc-major", 12), ("jit-tracing", 8), ("gc-mior", 8), ("jit-backend-compile", 7), ]: log.timeline_events.create( event_type=event_type, start_time=start_time, end_time=start_time + duration ) start_time += duration for label, value in [ ("traces_compiled", 3), ("traces_aborted", 0), ("gc_major", 12), ("gc_minor", 37), ]: log.counters.create(label=label, count=value) py_trace = PythonTrace.objects.create( log=log, root_file="test.py", root_function="main", ) RegexTrace.objects.create( log=log, pattern=r"\w+", ) NumPyPyTrace.objects.create( log=log, debug_repr="Call1(sin, Call2(multiply, Array, Scalar))", ) entry = py_trace.sections.create(label=TraceSection.ENTRY) ResOpChunk.objects.create( section=entry, ordering=0, raw_source=dedent(""" [p0, p1] p2 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_last_exception 80>) p3 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_pycode 120>) i4 = getfield_gc(p0, descr=<FieldU pypy.interpreter.pyframe.PyFrame.inst_is_being_profiled 150>) p5 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_lastblock 96>) i6 = getfield_gc(p0, descr=<FieldS pypy.interpreter.pyframe.PyFrame.inst_valuestackdepth 128>) i7 = getfield_gc(p0, descr=<FieldS pypy.interpreter.pyframe.PyFrame.inst_last_instr 88>) p8 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_locals_stack_w 104>) p10 = getarrayitem_gc(p8, 0, descr=<ArrayP 8>) p12 = getarrayitem_gc(p8, 1, descr=<ArrayP 8>) p14 = getarrayitem_gc(p8, 2, descr=<ArrayP 8>) p16 = getarrayitem_gc(p8, 3, descr=<ArrayP 8>) p18 = getarrayitem_gc(p8, 4, descr=<ArrayP 8>) p20 = getarrayitem_gc(p8, 5, descr=<ArrayP 8>) p22 = getarrayitem_gc(p8, 6, descr=<ArrayP 8>) p23 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_cells 40>) """), ) preamble = py_trace.sections.create(label=TraceSection.PREAMBLE) ResOpChunk.objects.create( section=preamble, ordering=0, raw_source=dedent(""" label(p0, p1, p2, p3, i4, p5, i6, i7, p10, p12, p14, p16, p18, p20, p22, descr=TargetToken(140048017138976)) """), ) PythonChunk.objects.create( section=preamble, ordering=1, start_line=3, end_line=6, raw_source=dedent(""" def main(): data = [0] * N for i in xrange(N): """), ) ResOpChunk.objects.create( section=preamble, ordering=2, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #26 FOR_ITER') guard_value(i6, 4, descr=<Guard4>) [i6, p1, p0, p2, p3, i4, p5, i7, p10, p12, p14, p16, p18, p20, p22] guard_class(p16, 38449928, descr=<Guard5>) [p1, p0, p16, p2, p3, i4, p5, p10, p12, p14, p18, p20, p22] i26 = getfield_gc(p16, descr=<FieldS pypy.module.__builtin__.functional.W_XRangeIterator.inst_remaining 16>) i28 = int_gt(i26, 0) guard_true(i28, descr=<Guard6>) [p1, p0, p16, p2, p3, i4, p5, p10, p12, p14, p18, p20, p22] i29 = getfield_gc(p16, descr=<FieldS pypy.module.__builtin__.functional.W_XRangeIterator.inst_current 8>) i30 = getfield_gc(p16, descr=<FieldS pypy.module.__builtin__.functional.W_XRangeIterator.inst_step 24>) i31 = int_add(i29, i30) i33 = int_sub(i26, 1) setfield_gc(p16, i31, descr=<FieldS pypy.module.__builtin__.functional.W_XRangeIterator.inst_current 8>) setfield_gc(p16, i33, descr=<FieldS pypy.module.__builtin__.functional.W_XRangeIterator.inst_remaining 16>) guard_value(i4, 0, descr=<Guard7>) [i4, p1, p0, p2, p3, p5, p10, p12, p14, p16, p20, p22, i29] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #29 STORE_FAST') """) ) PythonChunk.objects.create( section=preamble, ordering=3, start_line=6, end_line=7, raw_source=""" x = i ^ 3""" ) ResOpChunk.objects.create( section=preamble, ordering=4, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #32 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #35 LOAD_CONST') guard_value(p3, ConstPtr(ptr35), descr=<Guard8>) [p1, p0, p3, p2, p5, p10, p14, p16, p20, p22, i29] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #38 BINARY_XOR') i37 = int_xor(i29, 3) debug_merge_point(0, '<code object main. file 'test.py'. line 3> #39 STORE_FAST') """), ) PythonChunk.objects.create( section=preamble, ordering=5, start_line=7, end_line=8, raw_source=""" x <<= 2""" ) ResOpChunk.objects.create( section=preamble, ordering=6, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #42 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #45 LOAD_CONST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #48 INPLACE_LSHIFT') i39 = int_lshift(i37, 2) i40 = int_rshift(i39, 2) i41 = int_ne(i40, i37) guard_false(i41, descr=<Guard9>) [p1, p0, i39, p2, p5, p10, p16, p22, i37, i29] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #49 STORE_FAST') """), ) PythonChunk.objects.create( section=preamble, ordering=7, start_line=8, end_line=9, raw_source=""" x *= 7""", ) ResOpChunk.objects.create( section=preamble, ordering=8, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #52 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #55 LOAD_CONST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #58 INPLACE_MULTIPLY') i43 = int_mul_ovf(i39, 7) guard_no_overflow(, descr=<Guard10>) [p1, p0, i43, p2, p5, p10, p16, p22, i39, None, i29] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #59 STORE_FAST') """) ) PythonChunk.objects.create( section=preamble, ordering=9, start_line=9, end_line=10, raw_source=""" x -= 1""", ) ResOpChunk.objects.create( section=preamble, ordering=10, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #62 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #65 LOAD_CONST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #68 INPLACE_SUBTRACT') i46 = int_sub_ovf(i43, 1) guard_no_overflow(, descr=<Guard11>) [p1, p0, i46, p2, p5, p10, p16, p22, i43, None, None, i29] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #69 STORE_FAST') """) ) PythonChunk.objects.create( section=preamble, ordering=11, start_line=10, end_line=11, raw_source=""" data[i] = x""", ) ResOpChunk.objects.create( section=preamble, ordering=12, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #72 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #75 LOAD_FAST') guard_nonnull_class(p10, ConstClass(W_ListObject), descr=<Guard12>) [p1, p0, p10, p2, p5, p16, p22, i46, None, None, None, i29] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #78 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #81 STORE_SUBSCR') p48 = getfield_gc(p10, descr=<FieldP pypy.objspace.std.listobject.W_ListObject.inst_strategy 16>) guard_class(p48, 38554720, descr=<Guard13>) [p1, p0, p10, i29, p48, p2, p5, p16, i46, None, None, None, None] p50 = getfield_gc(p10, descr=<FieldP pypy.objspace.std.listobject.W_ListObject.inst_lstorage 8>) i51 = getfield_gc(p50, descr=<FieldS list.length 8>) i52 = uint_ge(i29, i51) guard_false(i52, descr=<Guard14>) [p1, p0, p10, i51, i46, i29, p50, p2, p5, p16, None, None, None, None, None] p53 = getfield_gc(p50, descr=<FieldP list.items 16>) setarrayitem_gc(p53, i29, i46, descr=<ArrayS 8>) debug_merge_point(0, '<code object main. file 'test.py'. line 3> #82 JUMP_ABSOLUTE') guard_not_invalidated(, descr=<Guard15>) [p1, p0, p2, p5, p10, p16, i46, None, None, None, i29] i55 = getfield_raw(43922552, descr=<FieldS pypysig_long_struct.c_value 0>) i57 = int_lt(i55, 0) guard_false(i57, descr=<Guard16>) [p1, p0, p2, p5, p10, p16, i46, None, None, None, i29] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #26 FOR_ITER') i58 = same_as(i46) i59 = same_as(i31) """) ) loop = py_trace.sections.create(label=TraceSection.LOOP_BODY) ResOpChunk.objects.create( section=loop, ordering=0, raw_source=dedent(""" label(p0, p1, p2, p5, p10, i29, i46, p16, i33, i59, i30, p50, descr=TargetToken(140048017139056)) """) ) PythonChunk.objects.create( section=loop, ordering=1, start_line=3, end_line=6, raw_source=dedent(""" def main(): data = [0] * N for i in xrange(N): """), ) ResOpChunk.objects.create( section=loop, ordering=2, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #26 FOR_ITER') i60 = int_gt(i33, 0) guard_true(i60, descr=<Guard17>) [p1, p0, p16, p2, p5, p10, i29, i46] i61 = int_add(i59, i30) i62 = int_sub(i33, 1) debug_merge_point(0, '<code object main. file 'test.py'. line 3> #29 STORE_FAST') """) ) PythonChunk.objects.create( section=loop, ordering=3, start_line=6, end_line=7, raw_source=""" x = i ^ 3""", ) ResOpChunk.objects.create( section=loop, ordering=4, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #32 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #35 LOAD_CONST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #38 BINARY_XOR') i63 = int_xor(i59, 3) debug_merge_point(0, '<code object main. file 'test.py'. line 3> #39 STORE_FAST') """) ) PythonChunk.objects.create( section=loop, ordering=5, start_line=7, end_line=8, raw_source=""" x <<= 2""", ) ResOpChunk.objects.create( section=loop, ordering=6, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #42 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #45 LOAD_CONST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #48 INPLACE_LSHIFT') i64 = int_lshift(i63, 2) i65 = int_rshift(i64, 2) setfield_gc(p16, i61, descr=<FieldS pypy.module.__builtin__.functional.W_XRangeIterator.inst_current 8>) setfield_gc(p16, i62, descr=<FieldS pypy.module.__builtin__.functional.W_XRangeIterator.inst_remaining 16>) i66 = int_ne(i65, i63) guard_false(i66, descr=<Guard18>) [p1, p0, i64, p2, p5, p10, p16, i63, i59, None, None] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #49 STORE_FAST') """), ) PythonChunk.objects.create( section=loop, ordering=7, start_line=8, end_line=9, raw_source=""" x *= 7""", ) ResOpChunk.objects.create( section=loop, ordering=8, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #52 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #55 LOAD_CONST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #58 INPLACE_MULTIPLY') i67 = int_mul_ovf(i64, 7) guard_no_overflow(, descr=<Guard19>) [p1, p0, i67, p2, p5, p10, p16, i64, None, i59, None, None] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #59 STORE_FAST') """) ) PythonChunk.objects.create( section=loop, ordering=9, start_line=9, end_line=10, raw_source=""" x -= 1""", ) ResOpChunk.objects.create( section=loop, ordering=10, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #62 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #65 LOAD_CONST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #68 INPLACE_SUBTRACT') i68 = int_sub_ovf(i67, 1) guard_no_overflow(, descr=<Guard20>) [p1, p0, i68, p2, p5, p10, p16, i67, None, None, i59, None, None] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #69 STORE_FAST') """), ) PythonChunk.objects.create( section=loop, ordering=11, start_line=10, end_line=11, raw_source=""" data[i] = x""", ) ResOpChunk.objects.create( section=loop, ordering=12, raw_source=dedent(""" debug_merge_point(0, '<code object main. file 'test.py'. line 3> #72 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #75 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #78 LOAD_FAST') debug_merge_point(0, '<code object main. file 'test.py'. line 3> #81 STORE_SUBSCR') i69 = getfield_gc(p50, descr=<FieldS list.length 8>) i70 = uint_ge(i59, i69) guard_false(i70, descr=<Guard21>) [p1, p0, p10, i69, i68, i59, p50, p2, p5, p16, None, None, None, None, None, None] p71 = getfield_gc(p50, descr=<FieldP list.items 16>) setarrayitem_gc(p71, i59, i68, descr=<ArrayS 8>) debug_merge_point(0, '<code object main. file 'test.py'. line 3> #82 JUMP_ABSOLUTE') guard_not_invalidated(, descr=<Guard22>) [p1, p0, p2, p5, p10, p16, i68, None, None, None, i59, None, None] i72 = getfield_raw(43922552, descr=<FieldS pypysig_long_struct.c_value 0>) i73 = int_lt(i72, 0) guard_false(i73, descr=<Guard23>) [p1, p0, p2, p5, p10, p16, i68, None, None, None, i59, None, None] debug_merge_point(0, '<code object main. file 'test.py'. line 3> #26 FOR_ITER') jump(p0, p1, p2, p5, p10, i59, i68, p16, i62, i61, i30, p50, descr=TargetToken(140048017139056)) """) ) py_trace_inline = PythonTrace.objects.create( log=log, root_file="test.py", root_function="main_inline", ) entry = py_trace_inline.sections.create(label=TraceSection.ENTRY) ResOpChunk.objects.create( section=entry, ordering=0, raw_source=dedent(""" [p0, p1] p2 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_last_exception 80>) p3 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_pycode 120>) i4 = getfield_gc(p0, descr=<FieldU pypy.interpreter.pyframe.PyFrame.inst_is_being_profiled 150>) p5 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_lastblock 96>) i6 = getfield_gc(p0, descr=<FieldS pypy.interpreter.pyframe.PyFrame.inst_valuestackdepth 128>) i7 = getfield_gc(p0, descr=<FieldS pypy.interpreter.pyframe.PyFrame.inst_last_instr 88>) p8 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_locals_stack_w 104>) p10 = getarrayitem_gc(p8, 0, descr=<ArrayP 8>) p12 = getarrayitem_gc(p8, 1, descr=<ArrayP 8>) p14 = getarrayitem_gc(p8, 2, descr=<ArrayP 8>) p15 = getfield_gc(p0, descr=<FieldP pypy.interpreter.pyframe.PyFrame.inst_cells 40>) """), ) preamble = py_trace_inline.sections.create(label=TraceSection.PREAMBLE) ResOpChunk.objects.create( section=preamble, ordering=1, raw_source=dedent(""" label(p0, p1, p2, p3, i4, p5, i6, i7, p10, p12, p14, descr=TargetToken(139725302244320)) """), ) PythonChunk.objects.create( section=preamble, ordering=2, start_line=4, end_line=7, raw_source=dedent(""" def main(): i = 0 while i < 10000: """), ) ResOpChunk.objects.create( section=preamble, ordering=3, raw_source=dedent(""" debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #9 LOAD_FAST') guard_value(i6, 1, descr=<Guard4>) [i6, p1, p0, p2, p3, i4, p5, i7, p10, p12, p14] guard_nonnull_class(p10, ConstClass(W_IntObject), descr=<Guard5>) [p1, p0, p10, p2, p3, i4, p5, p12, p14] guard_value(i4, 0, descr=<Guard6>) [i4, p1, p0, p2, p3, p5, p10, p14] debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #12 LOAD_CONST') guard_value(p3, ConstPtr(ptr19), descr=<Guard7>) [p1, p0, p3, p2, p5, p10, p14] debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #15 COMPARE_OP') i20 = getfield_gc_pure(p10, descr=<FieldS pypy.objspace.std.intobject.W_IntObject.inst_intval 8>) i22 = int_lt(i20, 10000) guard_true(i22, descr=<Guard8>) [p1, p0, p10, p2, p5] debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #18 POP_JUMP_IF_FALSE') """), ) PythonChunk.objects.create( section=preamble, ordering=4, start_line=7, end_line=8, raw_source=""" i = f(i)""", ) ResOpChunk.objects.create( section=preamble, ordering=5, raw_source=dedent(""" debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #21 LOAD_GLOBAL') p23 = getfield_gc(p0, descr=<FieldP pypy.interpreter.eval.Frame.inst_w_globals 8>) guard_value(p23, ConstPtr(ptr24), descr=<Guard9>) [p1, p0, p23, p2, p5, p10] p25 = getfield_gc(p23, descr=<FieldP pypy.objspace.std.dictmultiobject.W_DictMultiObject.inst_strategy 16>) guard_value(p25, ConstPtr(ptr26), descr=<Guard10>) [p1, p0, p25, p23, p2, p5, p10] guard_not_invalidated(, descr=<Guard11>) [p1, p0, p23, p2, p5, p10] debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #24 LOAD_FAST') debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #27 CALL_FUNCTION') p28 = call(ConstClass(getexecutioncontext), descr=<Callr 8 EF=1>) p29 = getfield_gc(p28, descr=<FieldP pypy.interpreter.executioncontext.ExecutionContext.inst_topframeref 64>) i30 = force_token() p31 = getfield_gc(p28, descr=<FieldP pypy.interpreter.executioncontext.ExecutionContext.inst_w_tracefunc 80>) guard_isnull(p31, descr=<Guard12>) [p1, p0, p28, p31, p2, p5, p10, i30, p29] i32 = getfield_gc(p28, descr=<FieldU pypy.interpreter.executioncontext.ExecutionContext.inst_profilefunc 40>) i33 = int_is_zero(i32) guard_true(i33, descr=<Guard13>) [p1, p0, p28, p2, p5, p10, i30, p29] """), ) PythonChunk.objects.create( section=preamble, ordering=6, start_line=1, end_line=3, raw_source=dedent(""" def f(i): return i + 1 """), ) ResOpChunk.objects.create( section=preamble, ordering=7, raw_source=dedent(""" debug_merge_point(1, '<code object f. file 'test.py'. line 1> #0 LOAD_FAST') debug_merge_point(1, '<code object f. file 'test.py'. line 1> #3 LOAD_CONST') debug_merge_point(1, '<code object f. file 'test.py'. line 1> #6 BINARY_ADD') i35 = int_add(i20, 1) debug_merge_point(1, '<code object f. file 'test.py'. line 1> #7 RETURN_VALUE') """), ) ResOpChunk.objects.create( section=preamble, ordering=8, raw_source=dedent(""" debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #30 STORE_FAST') debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #33 JUMP_ABSOLUTE') guard_not_invalidated(, descr=<Guard14>) [p1, p0, p2, p5, i35, None, None] i38 = getfield_raw(44216344, descr=<FieldS pypysig_long_struct.c_value 0>) i40 = int_lt(i38, 0) guard_false(i40, descr=<Guard15>) [p1, p0, p2, p5, i35, None, None] debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #9 LOAD_FAST') p41 = same_as(ConstPtr(ptr26)) """), ) loop = py_trace_inline.sections.create(label=TraceSection.LOOP_BODY) ResOpChunk.objects.create( section=loop, ordering=0, raw_source=dedent(""" label(p0, p1, p2, p5, i35, descr=TargetToken(139725302244400)) """), ) PythonChunk.objects.create( section=loop, ordering=1, start_line=4, end_line=7, raw_source=dedent(""" def main(): i = 0 while i < 10000: """), ) ResOpChunk.objects.create( section=loop, ordering=2, raw_source=dedent(""" debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #9 LOAD_FAST') debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #12 LOAD_CONST') debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #15 COMPARE_OP') i42 = int_lt(i35, 10000) guard_true(i42, descr=<Guard16>) [p1, p0, p2, p5, i35] debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #18 POP_JUMP_IF_FALSE') """), ) PythonChunk.objects.create( section=loop, ordering=3, start_line=7, end_line=8, raw_source=""" i = f(i)""", ) ResOpChunk.objects.create( section=loop, ordering=4, raw_source=dedent(""" debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #21 LOAD_GLOBAL') guard_not_invalidated(, descr=<Guard17>) [p1, p0, p2, p5, i35] debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #24 LOAD_FAST') debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #27 CALL_FUNCTION') i43 = force_token() """), ) PythonChunk.objects.create( section=loop, ordering=5, start_line=1, end_line=3, raw_source=dedent(""" def f(i): return i + 1 """), ) ResOpChunk.objects.create( section=loop, ordering=6, raw_source=dedent(""" debug_merge_point(1, '<code object f. file 'test.py'. line 1> #0 LOAD_FAST') debug_merge_point(1, '<code object f. file 'test.py'. line 1> #3 LOAD_CONST') debug_merge_point(1, '<code object f. file 'test.py'. line 1> #6 BINARY_ADD') i44 = int_add(i35, 1) debug_merge_point(1, '<code object f. file 'test.py'. line 1> #7 RETURN_VALUE') """), ) ResOpChunk.objects.create( section=loop, ordering=7, raw_source=dedent(""" debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #30 STORE_FAST') debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #33 JUMP_ABSOLUTE') i45 = getfield_raw(44216344, descr=<FieldS pypysig_long_struct.c_value 0>) i46 = int_lt(i45, 0) guard_false(i46, descr=<Guard18>) [p1, p0, p2, p5, i44, None] debug_merge_point(0, '<code object main_inline. file 'test.py'. line 4> #9 LOAD_FAST') jump(p0, p1, p2, p5, i44, descr=TargetToken(139725302244400)) """), )

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null

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d2c45b1783d1dc87374d177921834282ee656e79

210

py

Python

packages/admin.py

dandeduck/package-tracking-web

f7cb3dffd6f7f6b7ced5b1106a049c79c192dfa5

[ "MIT" ]

1

2021-02-11T22:16:51.000Z

packages/admin.py

dandeduck/package-tracking-web

f7cb3dffd6f7f6b7ced5b1106a049c79c192dfa5

[ "MIT" ]

54

2021-02-11T18:52:11.000Z

2021-06-13T13:45:01.000Z

packages/admin.py

dandeduck/package-tracking-web

f7cb3dffd6f7f6b7ced5b1106a049c79c192dfa5

[ "MIT" ]

null

from django.contrib import admin from .models import Partner, Order, Address, Package admin.site.register(Partner) admin.site.register(Order) admin.site.register(Address) admin.site.register(Package)

23.333333

53

0.780952

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0.414634

0

0.119048

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6

d2d83d452fd30e718546c0eac26fe03bbef59c06

1,647

py

Python

sympy/physics/optics/__init__.py

utkarshdeorah/sympy

dcdf59bbc6b13ddbc329431adf72fcee294b6389

[ "BSD-3-Clause" ]

8,323

2015-01-02T15:51:43.000Z

2022-03-31T13:13:19.000Z

sympy/physics/optics/__init__.py

utkarshdeorah/sympy

dcdf59bbc6b13ddbc329431adf72fcee294b6389

[ "BSD-3-Clause" ]

15,102

2015-01-01T01:33:17.000Z

2022-03-31T22:53:13.000Z

sympy/physics/optics/__init__.py

utkarshdeorah/sympy

dcdf59bbc6b13ddbc329431adf72fcee294b6389

[ "BSD-3-Clause" ]

4,490

2015-01-01T17:48:07.000Z

2022-03-31T17:24:05.000Z

__all__ = [ 'TWave', 'RayTransferMatrix', 'FreeSpace', 'FlatRefraction', 'CurvedRefraction', 'FlatMirror', 'CurvedMirror', 'ThinLens', 'GeometricRay', 'BeamParameter', 'waist2rayleigh', 'rayleigh2waist', 'geometric_conj_ab', 'geometric_conj_af', 'geometric_conj_bf', 'gaussian_conj', 'conjugate_gauss_beams', 'Medium', 'refraction_angle', 'deviation', 'fresnel_coefficients', 'brewster_angle', 'critical_angle', 'lens_makers_formula', 'mirror_formula', 'lens_formula', 'hyperfocal_distance', 'transverse_magnification', 'jones_vector', 'stokes_vector', 'jones_2_stokes', 'linear_polarizer', 'phase_retarder', 'half_wave_retarder', 'quarter_wave_retarder', 'transmissive_filter', 'reflective_filter', 'mueller_matrix', 'polarizing_beam_splitter', ] from .waves import TWave from .gaussopt import (RayTransferMatrix, FreeSpace, FlatRefraction, CurvedRefraction, FlatMirror, CurvedMirror, ThinLens, GeometricRay, BeamParameter, waist2rayleigh, rayleigh2waist, geometric_conj_ab, geometric_conj_af, geometric_conj_bf, gaussian_conj, conjugate_gauss_beams) from .medium import Medium from .utils import (refraction_angle, deviation, fresnel_coefficients, brewster_angle, critical_angle, lens_makers_formula, mirror_formula, lens_formula, hyperfocal_distance, transverse_magnification) from .polarization import (jones_vector, stokes_vector, jones_2_stokes, linear_polarizer, phase_retarder, half_wave_retarder, quarter_wave_retarder, transmissive_filter, reflective_filter, mueller_matrix, polarizing_beam_splitter)

42.230769

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1,647

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1,647

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false

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0.166667

0

null

0

1

0

null

0

6

825b43a19aa2a825d590518292a7f19d23a5c051

21,681

py

Python

micro_admin/migrations/0001_initial.py

lance0145/micro-finance

1ba6339a9d05ff2f20b020b97a233c766b2ee6e0

[ "MIT" ]

72

2015-09-18T07:23:20.000Z

2022-03-23T14:35:46.000Z

micro_admin/migrations/0001_initial.py

mohbadar/micro-finance

00fc9ad1e09cd6658aa5fa0dd991cf18fe2927a6

[ "MIT" ]

68

2015-01-03T13:44:40.000Z

2021-06-10T20:00:23.000Z

micro_admin/migrations/0001_initial.py

mohbadar/micro-finance

00fc9ad1e09cd6658aa5fa0dd991cf18fe2927a6

[ "MIT" ]

73

2015-02-10T07:03:42.000Z

2022-02-24T21:11:01.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.9.7 on 2016-06-07 07:54 from __future__ import unicode_literals from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('auth', '0007_alter_validators_add_error_messages'), ] operations = [ migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('password', models.CharField(max_length=128, verbose_name='password')), ('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')), ('username', models.CharField(max_length=50, unique=True)), ('email', models.EmailField(max_length=255, unique=True)), ('first_name', models.CharField(max_length=100)), ('last_name', models.CharField(max_length=100, null=True)), ('gender', models.CharField(choices=[('M', 'Male'), ('F', 'Female')], max_length=10)), ('user_roles', models.CharField(choices=[('BranchManager', 'BranchManager'), ('LoanOfficer', 'LoanOfficer'), ('Cashier', 'Cashier')], max_length=20)), ('date_of_birth', models.DateField(default='2000-01-01', null=True)), ('is_active', models.BooleanField(default=True)), ('is_staff', models.BooleanField(default=True)), ('is_admin', models.BooleanField(default=False)), ('country', models.CharField(max_length=50, null=True)), ('state', models.CharField(max_length=50, null=True)), ('district', models.CharField(max_length=50, null=True)), ('city', models.CharField(max_length=50, null=True)), ('area', models.CharField(max_length=150, null=True)), ('mobile', models.CharField(default='0', max_length=10, null=True)), ('pincode', models.CharField(default='', max_length=10, null=True)), ], options={ 'permissions': (('branch_manager', 'Can manage all accounts under his/her branch.'),), }, ), migrations.CreateModel( name='Branch', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=100, unique=True)), ('opening_date', models.DateField()), ('country', models.CharField(max_length=50)), ('state', models.CharField(max_length=50)), ('district', models.CharField(max_length=50)), ('city', models.CharField(max_length=50)), ('area', models.CharField(max_length=150)), ('phone_number', models.BigIntegerField()), ('pincode', models.IntegerField()), ('is_active', models.BooleanField(default=True)), ], ), migrations.CreateModel( name='Centers', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=200, unique=True)), ('created_date', models.DateField()), ('is_active', models.BooleanField(default=True)), ('branch', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Branch')), ], ), migrations.CreateModel( name='Client', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('first_name', models.CharField(max_length=200)), ('last_name', models.CharField(max_length=200)), ('email', models.EmailField(max_length=255, null=True)), ('account_number', models.CharField(max_length=50, unique=True)), ('date_of_birth', models.DateField()), ('blood_group', models.CharField(default=True, max_length=10, null=True)), ('gender', models.CharField(choices=[('M', 'Male'), ('F', 'Female')], max_length=10)), ('client_role', models.CharField(choices=[('FirstLeader', 'FirstLeader'), ('SecondLeader', 'SecondLeader'), ('GroupMember', 'GroupMember')], max_length=20)), ('occupation', models.CharField(max_length=200)), ('annual_income', models.BigIntegerField()), ('joined_date', models.DateField()), ('country', models.CharField(max_length=50)), ('state', models.CharField(max_length=50)), ('district', models.CharField(max_length=50)), ('city', models.CharField(max_length=50)), ('area', models.CharField(max_length=150)), ('mobile', models.CharField(default=True, max_length=20, null=True)), ('pincode', models.CharField(default=True, max_length=20, null=True)), ('photo', models.ImageField(null=True, upload_to='static/images/users')), ('signature', models.ImageField(null=True, upload_to='static/images/signatures')), ('is_active', models.BooleanField(default=True)), ('status', models.CharField(default='UnAssigned', max_length=50, null=True)), ('sharecapital_amount', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('entrancefee_amount', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('membershipfee_amount', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('bookfee_amount', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('insurance_amount', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('branch', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Branch')), ('created_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='FixedDeposits', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('deposited_date', models.DateField()), ('status', models.CharField(choices=[('Opened', 'Opened'), ('Closed', 'Closed')], max_length=20)), ('fixed_deposit_number', models.CharField(max_length=50, unique=True)), ('fixed_deposit_amount', models.DecimalField(decimal_places=6, max_digits=19)), ('fixed_deposit_period', models.IntegerField()), ('fixed_deposit_interest_rate', models.DecimalField(decimal_places=2, max_digits=5)), ('nominee_firstname', models.CharField(max_length=50)), ('nominee_lastname', models.CharField(max_length=50)), ('nominee_gender', models.CharField(choices=[('M', 'Male'), ('F', 'Female')], max_length=10)), ('relationship_with_nominee', models.CharField(max_length=50)), ('nominee_date_of_birth', models.DateField()), ('nominee_occupation', models.CharField(max_length=50)), ('nominee_photo', models.ImageField(upload_to='static/images/users')), ('nominee_signature', models.ImageField(upload_to='static/images/signatures')), ('fixed_deposit_interest', models.DecimalField(blank=True, decimal_places=6, max_digits=19, null=True)), ('maturity_amount', models.DecimalField(blank=True, decimal_places=6, max_digits=19, null=True)), ('client', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Client')), ], ), migrations.CreateModel( name='Group', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=200)), ('account_number', models.CharField(max_length=50, unique=True)), ('activation_date', models.DateField()), ('is_active', models.BooleanField(default=True)), ('status', models.CharField(default='UnAssigned', max_length=50)), ('branch', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Branch')), ('clients', models.ManyToManyField(blank=True, to='micro_admin.Client')), ('created_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='group_created_by', to=settings.AUTH_USER_MODEL)), ('staff', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='GroupMeetings', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('meeting_date', models.DateField()), ('meeting_time', models.CharField(max_length=20)), ('group', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Group')), ], ), migrations.CreateModel( name='LoanAccount', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('account_no', models.CharField(max_length=50, unique=True)), ('interest_type', models.CharField(choices=[('Flat', 'Flat'), ('Declining', 'Declining')], max_length=20)), ('status', models.CharField(choices=[('Applied', 'Applied'), ('Withdrawn', 'Withdrawn'), ('Approved', 'Approved'), ('Rejected', 'Rejected'), ('Closed', 'Closed')], max_length=20)), ('opening_date', models.DateField(auto_now_add=True)), ('approved_date', models.DateField(blank=True, null=True)), ('loan_issued_date', models.DateField(blank=True, null=True)), ('closed_date', models.DateField(blank=True, null=True)), ('loan_amount', models.DecimalField(decimal_places=6, max_digits=19)), ('loan_repayment_period', models.IntegerField()), ('loan_repayment_every', models.IntegerField()), ('loan_repayment_amount', models.DecimalField(blank=True, decimal_places=6, max_digits=19, null=True)), ('total_loan_amount_repaid', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('loanpurpose_description', models.TextField()), ('annual_interest_rate', models.DecimalField(decimal_places=2, max_digits=5)), ('interest_charged', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('total_interest_repaid', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('total_loan_paid', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('total_loan_balance', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('loanprocessingfee_amount', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('no_of_repayments_completed', models.IntegerField(default=0)), ('principle_repayment', models.DecimalField(blank=True, decimal_places=6, max_digits=19, null=True)), ('client', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Client')), ('created_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ('group', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Group')), ('loan_issued_by', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='loan_issued_by', to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='Payments', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('date', models.DateField()), ('voucher_number', models.CharField(max_length=50, unique=True)), ('payment_type', models.CharField(choices=[('Loans', 'Loans'), ('TravellingAllowance', 'TravellingAllowance'), ('Paymentofsalary', 'Paymentofsalary'), ('PrintingCharges', 'PrintingCharges'), ('StationaryCharges', 'StationaryCharges'), ('OtherCharges', 'OtherCharges'), ('SavingsWithdrawal', 'SavingsWithdrawal'), ('FixedWithdrawal', 'FixedWithdrawal'), ('RecurringWithdrawal', 'RecurringWithdrawal')], max_length=25)), ('amount', models.DecimalField(decimal_places=6, max_digits=19)), ('interest', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('total_amount', models.DecimalField(decimal_places=6, max_digits=19)), ('totalamount_in_words', models.CharField(max_length=200)), ('branch', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Branch')), ('client', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Client')), ('group', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Group')), ('staff', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='Receipts', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('date', models.DateField()), ('receipt_number', models.CharField(max_length=50, unique=True)), ('sharecapital_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('entrancefee_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('membershipfee_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('bookfee_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('loanprocessingfee_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('savingsdeposit_thrift_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('fixeddeposit_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('recurringdeposit_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('loanprinciple_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('loaninterest_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('insurance_amount', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('savings_balance_atinstant', models.DecimalField(blank=True, decimal_places=6, max_digits=19, null=True)), ('demand_loanprinciple_amount_atinstant', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('demand_loaninterest_amount_atinstant', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('principle_loan_balance_atinstant', models.DecimalField(blank=True, decimal_places=6, default=0, max_digits=19, null=True)), ('branch', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Branch')), ('client', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Client')), ('group', models.ForeignKey(blank=True, default=0, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Group')), ('group_loan_account', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='group_loan_account', to='micro_admin.LoanAccount')), ('member_loan_account', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.LoanAccount')), ('staff', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='RecurringDeposits', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('deposited_date', models.DateField()), ('reccuring_deposit_number', models.CharField(max_length=50, unique=True)), ('status', models.CharField(choices=[('Opened', 'Opened'), ('Closed', 'Closed')], max_length=20)), ('recurring_deposit_amount', models.DecimalField(decimal_places=6, max_digits=19)), ('recurring_deposit_period', models.IntegerField()), ('recurring_deposit_interest_rate', models.DecimalField(decimal_places=2, max_digits=5)), ('nominee_firstname', models.CharField(max_length=50)), ('nominee_lastname', models.CharField(max_length=50)), ('nominee_gender', models.CharField(choices=[('M', 'Male'), ('F', 'Female')], max_length=10)), ('relationship_with_nominee', models.CharField(max_length=50)), ('nominee_date_of_birth', models.DateField()), ('nominee_occupation', models.CharField(max_length=50)), ('nominee_photo', models.ImageField(upload_to='static/images/users')), ('nominee_signature', models.ImageField(upload_to='static/images/signatures')), ('recurring_deposit_interest', models.DecimalField(blank=True, decimal_places=6, max_digits=19, null=True)), ('maturity_amount', models.DecimalField(blank=True, decimal_places=6, max_digits=19, null=True)), ('client', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Client')), ], ), migrations.CreateModel( name='SavingsAccount', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('account_no', models.CharField(max_length=50, unique=True)), ('status', models.CharField(choices=[('Applied', 'Applied'), ('Withdrawn', 'Withdrawn'), ('Approved', 'Approved'), ('Rejected', 'Rejected'), ('Closed', 'Closed')], max_length=20)), ('opening_date', models.DateField()), ('min_required_balance', models.DecimalField(decimal_places=2, max_digits=5)), ('savings_balance', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('annual_interest_rate', models.DecimalField(decimal_places=2, max_digits=5)), ('total_deposits', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('total_withdrawals', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('fixeddeposit_amount', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('fixeddepositperiod', models.IntegerField(blank=True, null=True)), ('recurringdeposit_amount', models.DecimalField(decimal_places=6, default=0, max_digits=19)), ('recurringdepositperiod', models.IntegerField(blank=True, null=True)), ('client', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Client')), ('created_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ('group', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Group')), ], ), migrations.AddField( model_name='centers', name='groups', field=models.ManyToManyField(blank=True, to='micro_admin.Group'), ), migrations.AddField( model_name='user', name='branch', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='micro_admin.Branch'), ), migrations.AddField( model_name='user', name='user_permissions', field=models.ManyToManyField(blank=True, related_name='user_permissions', to='auth.Permission'), ), ]

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0

1

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null

0

6

82639d04709bb7e35e36b9d519f7420e58a05774

67

py

Python

pymusical/__init__.py

jgueting/pymusical

5dfebbe496dd9e2e3aa04fbc9485b8f8ff588eba

[ "MIT" ]

null

pymusical/__init__.py

jgueting/pymusical

5dfebbe496dd9e2e3aa04fbc9485b8f8ff588eba

[ "MIT" ]

null

pymusical/__init__.py

jgueting/pymusical

5dfebbe496dd9e2e3aa04fbc9485b8f8ff588eba

[ "MIT" ]

null

from pymusical.converter import MusicConverter, MusicConverterError

67

0.910448

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67

10.166667

1

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67

1

67

0.968254

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0

null

0

1

0

1

0

1

0

6

82ba72859cc184d9e3af6870d7d31bfe1e648030

113

py

Python

__init__.py

Harryjun/pytorch-vsumm-reinforce

2200d58e855ae3ea42c98107dc059f691d138671

[ "MIT" ]

18

2019-10-17T02:05:40.000Z

2021-05-08T15:39:49.000Z

__init__.py

Harryjun/pytorch-vsumm-reinforce

2200d58e855ae3ea42c98107dc059f691d138671

[ "MIT" ]

null

__init__.py

Harryjun/pytorch-vsumm-reinforce

2200d58e855ae3ea42c98107dc059f691d138671

[ "MIT" ]

1

2020-07-27T20:46:14.000Z

import sys sys.path.append('./utils/') from file_process import * from knapsack import * from vsum_tool import *

18.833333

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0.761062

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4.941176

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1

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1

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6

7d568330ec0526ae317a57d151bb8319e73a140e

4,464

py

Python

project/emccfr_all_games.py

aditya140/rlcard

de203b9b74a653019452aeb0622345f33dd42eda

[ "MIT" ]

null

project/emccfr_all_games.py

aditya140/rlcard

de203b9b74a653019452aeb0622345f33dd42eda

[ "MIT" ]

null

project/emccfr_all_games.py

aditya140/rlcard

de203b9b74a653019452aeb0622345f33dd42eda

[ "MIT" ]

null

''' An example of solve Leduc Hold'em with CFR ''' import torch import os import sys sys.path.append(".") import numpy as np import rlcard from rlcard.agents import EMCCFRAgent, RandomAgent from rlcard import models from rlcard.utils import set_global_seed, tournament from rlcard.utils import Logger def train_leduc(): # Make environment and enable human mode env = rlcard.make('leduc-holdem', config={'seed': 0, 'allow_step_back':True}) eval_env = rlcard.make('leduc-holdem', config={'seed': 0}) # Set the iterations numbers and how frequently we evaluate the performance and save model evaluate_every = 100 save_plot_every = 1000 evaluate_num = 10000 episode_num = 10000 # The paths for saving the logs and learning curves log_dir = './experiments/leduc_holdem_emccfr_result/' # Set a global seed set_global_seed(0) # Initilize CFR Agent model_path = 'models/leduc_holdem_emccfr' agent = EMCCFRAgent(env,model_path = model_path) agent.load() # If we have saved model, we first load the model # Evaluate CFR against pre-trained NFSP eval_env.set_agents([agent, models.load('leduc-holdem-nfsp').agents[0]]) # Init a Logger to plot the learning curve logger = Logger(log_dir) for episode in range(episode_num): agent.train() print('\rIteration {}'.format(episode), end='') # Evaluate the performance. Play with NFSP agents. if episode % evaluate_every == 0: agent.save() # Save model logger.log_performance(env.timestep, tournament(eval_env, evaluate_num)[0]) # Close files in the logger logger.close_files() # Plot the learning curve logger.plot('EMCCFR') def train_uno(): # Make environment and enable human mode env = rlcard.make('uno', config={'seed': 0, 'allow_step_back':True}) eval_env = rlcard.make('uno', config={'seed': 0}) # Set the iterations numbers and how frequently we evaluate the performance and save model evaluate_every = 100 save_plot_every = 1000 evaluate_num = 10000 episode_num = 10000 # The paths for saving the logs and learning curves log_dir = './experiments/uno_emccfr_result/' # Set a global seed set_global_seed(0) # Initilize CFR Agent agent = EMCCFRAgent(env) agent.load() # If we have saved model, we first load the model # Evaluate CFR against pre-trained NFSP eval_env.set_agents([agent, models.load('uno-nfsp').agents[0]]) # Init a Logger to plot the learning curve logger = Logger(log_dir) for episode in range(episode_num): agent.train() print('\rIteration {}'.format(episode), end='') # Evaluate the performance. Play with NFSP agents. if episode % evaluate_every == 0: agent.save() # Save model logger.log_performance(env.timestep, tournament(eval_env, evaluate_num)[0]) # Close files in the logger logger.close_files() # Plot the learning curve logger.plot('EMCCFR') def train_mahjong(): # Make environment and enable human mode env = rlcard.make('mahjong', config={'seed': 0, 'allow_step_back':True}) eval_env = rlcard.make('mahjong', config={'seed': 0}) # Set the iterations numbers and how frequently we evaluate the performance and save model evaluate_every = 100 save_plot_every = 1000 evaluate_num = 10000 episode_num = 10000 # The paths for saving the logs and learning curves log_dir = './experiments/mahjong_emccfr_result/' # Set a global seed set_global_seed(0) # Initilize CFR Agent agent = EMCCFRAgent(env) agent.load() # If we have saved model, we first load the model # Evaluate CFR against pre-trained NFSP eval_env.set_agents([agent, models.load('mahjong-nfsp').agents[0]]) # Init a Logger to plot the learning curve logger = Logger(log_dir) for episode in range(episode_num): agent.train() print('\rIteration {}'.format(episode), end='') # Evaluate the performance. Play with NFSP agents. if episode % evaluate_every == 0: agent.save() # Save model logger.log_performance(env.timestep, tournament(eval_env, evaluate_num)[0]) # Close files in the logger logger.close_files() # Plot the learning curve logger.plot('EMCCFR') if __name__=="__main__": train_leduc() # train_uno() # train_mahjong()

30.162162

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0

null

0

1

0

null

0

6

7d5958e81a3c96be8904d1145d2daff5d82d8b41

1,309

py

Python

Python/libraries/recognizers-date-time/recognizers_date_time/date_time/chinese/__init__.py

ParadoxARG/Recognizers-Text

70c2a368e48fb0694f8a185574d6dd6076b29362

[ "MIT" ]

10

2019-05-11T18:07:14.000Z

2021-08-20T03:02:47.000Z

Python/libraries/recognizers-date-time/recognizers_date_time/date_time/chinese/__init__.py

ParadoxARG/Recognizers-Text

70c2a368e48fb0694f8a185574d6dd6076b29362

[ "MIT" ]

76

2018-11-09T18:19:44.000Z

2019-08-20T20:29:53.000Z

Python/libraries/recognizers-date-time/recognizers_date_time/date_time/chinese/__init__.py

ParadoxARG/Recognizers-Text

70c2a368e48fb0694f8a185574d6dd6076b29362

[ "MIT" ]

18

2019-08-19T12:11:00.000Z

2021-10-12T09:36:27.000Z

from .base_date_time_extractor import * from .duration_extractor_config import * from .duration_extractor import * from .time_extractor import * from .date_extractor_config import * from .date_extractor import * from .timeperiod_extractor import * from .dateperiod_extractor_config import * from .dateperiod_extractor import * from .datetime_extractor_config import * from .datetime_extractor import * from .datetimeperiod_extractor_config import * from .datetimeperiod_extractor import * from .set_extractor_config import * from .set_extractor import * from .holiday_extractor_config import * from .merged_extractor_config import * from .merged_extractor import * from .duration_parser_config import * from .duration_parser import * from .time_parser import * from .date_parser_config import * from .date_parser import * from .timeperiod_parser_config import * from .timeperiod_parser import * from .dateperiod_parser_config import * from .dateperiod_parser import * from .datetime_parser_config import * from .datetime_parser import * from .datetimeperiod_parser_config import * from .datetimeperiod_parser import * from .holiday_parser_config import * from .holiday_parser import * from .set_parser_config import * from .set_parser import * from .merged_parser_config import * from .merged_parser import *

34.447368

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0.830405

167

1,309

6.173653

0.095808

0.349176

0.263822

0.192047

0.068865

0

0.113063

1,309

37

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0

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true

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1

0

null

0

1

0

1

0

1

0

6

7d681fdf8380487d0dbc5b16bbcf61ea66ffdd9e

124

py

Python

tests/conftest.py

nanten2/necst-lib

763477825c24b4307028b2d8ac1d08954512899b

[ "MIT" ]

1

2022-02-04T12:12:46.000Z

tests/conftest.py

nanten2/neclib

763477825c24b4307028b2d8ac1d08954512899b

[ "MIT" ]

14

2022-02-09T06:32:28.000Z

2022-03-27T10:27:20.000Z

tests/conftest.py

nanten2/neclib

763477825c24b4307028b2d8ac1d08954512899b

[ "MIT" ]

null

from pathlib import Path import pytest @pytest.fixture def data_dir() -> Path: return Path(__file__).parent / "_data"

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124

4.941176

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124

7

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null

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null

0

1

0

1

0

6

7d80a2d4612796abfb35f3900633eb4752f47e91

74

py

Python

src/aspire/basis/fpswf_2d.py

janden/ASPIRE-Python

5bcf831881fd0e42630c3b99671c5ed08de260ea

[ "MIT" ]

null

src/aspire/basis/fpswf_2d.py

janden/ASPIRE-Python

5bcf831881fd0e42630c3b99671c5ed08de260ea

[ "MIT" ]

null

src/aspire/basis/fpswf_2d.py

janden/ASPIRE-Python

5bcf831881fd0e42630c3b99671c5ed08de260ea

[ "MIT" ]

null

from aspire.basis.pswf_2d import PSWF2D class FPSWF2D(PSWF2D): pass

12.333333

39

0.756757

11

74

5

0.909091

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0.175676

74

5

40

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0.836066

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1

0

true

0.333333

0

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1

0

null

0

1

0

null

0

1

0

1

0

6

7db55bb2614582e0cb28478e6149e2e228fd34fd

124

py

Python

src/python/zensols/deepnlp/index/__init__.py

plandes/deepnlp

49820084ccf797d59535d5920559ab768bf2ec73

[ "MIT" ]

7

2020-05-11T07:13:56.000Z

2021-09-27T13:03:46.000Z

src/python/zensols/deepnlp/index/__init__.py

plandes/deepnlp

49820084ccf797d59535d5920559ab768bf2ec73

[ "MIT" ]

null

src/python/zensols/deepnlp/index/__init__.py

plandes/deepnlp

49820084ccf797d59535d5920559ab768bf2ec73

[ "MIT" ]

1

2022-02-12T00:22:26.000Z

"""Contains classes for vectorizers for indexing document. """ from .domain import * from .lsi import * from .lda import *

17.714286

58

0.725806

16

124

5.625

0.6875

0.222222

0

0.169355

124

6

59

20.666667

0.873786

0.443548

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

7dd7b8b37b180c758ca299046bc44ee50698a8c1

1,836

py

Python

util.py/bond.py

yomichi/HPhi-samples

040cbf101dbe4c19df90fec22a21107730ba1879

[ "BSL-1.0" ]

null

util.py/bond.py

yomichi/HPhi-samples

040cbf101dbe4c19df90fec22a21107730ba1879

[ "BSL-1.0" ]

null

util.py/bond.py

yomichi/HPhi-samples

040cbf101dbe4c19df90fec22a21107730ba1879

[ "BSL-1.0" ]

null

def bond(output, i,j,Jz,Jx,S2=1): if S2==1: bond_half(output, i,j,Jz,Jx) elif S2==2: bond_one(output, i,j,Jz,Jx) else: error("S2 should be 1 or 2.") def bond_half(output, i,j, Jz,Jx): z = 0.25*Jz x = 0.5*Jx # diagonal output.write('{} 0 {} 0 {} 0 {} 0 {} 0.0 \n'.format(i,i,j,j,z)) output.write('{} 1 {} 1 {} 0 {} 0 {} 0.0 \n'.format(i,i,j,j,-z)) output.write('{} 0 {} 0 {} 1 {} 1 {} 0.0 \n'.format(i,i,j,j,-z)) output.write('{} 1 {} 1 {} 1 {} 1 {} 0.0 \n'.format(i,i,j,j,z)) # off-diagonal # S_i^+ S_j^- output.write('{} 1 {} 0 {} 0 {} 1 {} 0.0 \n'.format(i,i,j,j,x)) # S_j^+ S_i^- output.write('{} 1 {} 0 {} 0 {} 1 {} 0.0 \n'.format(j,j,i,i,x)) def bond_one(output, i,j, Jz,Jx): # diagonal output.write('{} 0 {} 0 {} 0 {} 0 {} 0.0 \n'.format(i,i,j,j,Jz)) output.write('{} 2 {} 2 {} 0 {} 0 {} 0.0 \n'.format(i,i,j,j,-Jz)) output.write('{} 0 {} 0 {} 2 {} 2 {} 0.0 \n'.format(i,i,j,j,-Jz)) output.write('{} 2 {} 2 {} 2 {} 2 {} 0.0 \n'.format(i,i,j,j,Jz)) # off-diagonal # S_i^+ S_j^- output.write('{} 1 {} 0 {} 0 {} 1 {} 0.0 \n'.format(i,i,j,j,Jx)) output.write('{} 2 {} 1 {} 0 {} 1 {} 0.0 \n'.format(i,i,j,j,Jx)) output.write('{} 1 {} 0 {} 1 {} 2 {} 0.0 \n'.format(i,i,j,j,Jx)) output.write('{} 2 {} 1 {} 1 {} 2 {} 0.0 \n'.format(i,i,j,j,Jx)) # S_j^+ S_i^- output.write('{} 1 {} 0 {} 0 {} 1 {} 0.0 \n'.format(j,j,i,i,Jx)) output.write('{} 2 {} 1 {} 0 {} 1 {} 0.0 \n'.format(j,j,i,i,Jx)) output.write('{} 1 {} 0 {} 1 {} 2 {} 0.0 \n'.format(j,j,i,i,Jx)) output.write('{} 2 {} 1 {} 1 {} 2 {} 0.0 \n'.format(j,j,i,i,Jx)) def interall_header(output, L, S2=1): output.write('=== header start\n') output.write('NInterAll {}\n'.format(6*S2*L)) output.write('=== header (reserved)\n') output.write('=== header (reserved)\n') output.write('=== header end\n')

39.06383

67

0.494009

388

1,836

2.304124

0.097938

0.080537

0.060403

0.181208

0.831096

0.817673

0.732662

0.655481

0

0.085078

0.193355

1,836

46

68

39.913043

0.518569

0.049564

0

0.057143

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0

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0.114286

false

0

0.114286

0

null

0

1

0

1

0

null

0

6

81e6f9899791154757eceb01cc41dfcabdf0cfd3

125

py

Python

netkan/tests/__init__.py

Olympic1/NetKAN-Infra

ddad74c4942664e22719930a71ff5cc43f229352

[ "MIT" ]

null

netkan/tests/__init__.py

Olympic1/NetKAN-Infra

ddad74c4942664e22719930a71ff5cc43f229352

[ "MIT" ]

null

netkan/tests/__init__.py

Olympic1/NetKAN-Infra

ddad74c4942664e22719930a71ff5cc43f229352

[ "MIT" ]

null

from .indexer import * from .scheduler import * from .utils import * from .metadata import * from .download_counter import *

20.833333

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0.76

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125

5.875

0.5

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true

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null

1

0

1

0

null

0

1

0

1

0

1

0

6

c4a9ea260ab66eeceef383c04a4dbacd2d5c358e

35,171

py

Python

tests/v2_tests/test_zip.py

HiroakiMikami/pfio

1ac997dcba7babd5d91dd8c4f2793d27a6bab69b

[ "MIT" ]

null

tests/v2_tests/test_zip.py

HiroakiMikami/pfio

1ac997dcba7babd5d91dd8c4f2793d27a6bab69b

[ "MIT" ]

null

tests/v2_tests/test_zip.py

HiroakiMikami/pfio

1ac997dcba7babd5d91dd8c4f2793d27a6bab69b

[ "MIT" ]

null

import io import multiprocessing import os import pickle import shutil import subprocess import sys import tempfile import unittest from datetime import datetime from zipfile import ZipFile import pytest from parameterized import parameterized from pfio.testing import make_random_str, make_zip from pfio.v2 import ZipFileStat, local ZIP_TEST_FILENAME_LIST = { "dir_name1": "testdir1", "dir_name2": "testdir2", "zipped_file_name": "testfile1", "testfile_name": "testfile2", "nested_dir_name": "nested_dir", "nested_zip_file_name": "nested.zip", } NON_EXIST_LIST = ["does_not_exist", "does_not_exist/", "does/not/exist"] class TestZip(unittest.TestCase): def setUp(self): # The following zip layout is created for all the tests # outside.zip # | - testdir1 # | | - nested1.zip # | | - nested_dir # | | - nested # | - testdir2 # | | - testfile1 # | - testfile2 self.test_string = "this is a test string\n" self.nested_test_string = \ "this is a test string for nested zip\n" self.test_string_b = self.test_string.encode("utf-8") self.nested_test_string_b = \ self.nested_test_string.encode("utf-8") # the most outside zip self.zip_file_name = "outside" # nested zip and nested file self.tmpdir = tempfile.TemporaryDirectory() self.nested_zipped_file_name = "nested" self.nested_dir_name = ZIP_TEST_FILENAME_LIST["nested_dir_name"] self.nested_dir_path = os.path.join(self.tmpdir.name, self.nested_dir_name) self.nested_zip_file_name = \ ZIP_TEST_FILENAME_LIST["nested_zip_file_name"] # directory and file self.dir_name1 = ZIP_TEST_FILENAME_LIST["dir_name1"] self.dir_name2 = ZIP_TEST_FILENAME_LIST["dir_name2"] self.zipped_file_name = ZIP_TEST_FILENAME_LIST["zipped_file_name"] self.testfile_name = ZIP_TEST_FILENAME_LIST["testfile_name"] # paths used in making outside.zip dir_path1 = os.path.join(self.tmpdir.name, self.dir_name1) dir_path2 = os.path.join(self.tmpdir.name, self.dir_name2) testfile_path = os.path.join(self.tmpdir.name, self.testfile_name) nested_dir_path = os.path.join(self.tmpdir.name, self.nested_dir_name) zipped_file_path = os.path.join(dir_path2, self.zipped_file_name) nested_zipped_file_path = os.path.join( nested_dir_path, self.nested_zipped_file_name) nested_zip_file_path = os.path.join( dir_path1, self.nested_zip_file_name) # paths used in tests self.zip_file_path = self.zip_file_name + ".zip" self.zipped_file_path = os.path.join(self.dir_name2, self.zipped_file_name) self.nested_zip_path = os.path.join( self.dir_name1, self.nested_zip_file_name) self.nested_zipped_file_path = os.path.join( self.nested_dir_name, self.nested_zipped_file_name) os.mkdir(dir_path1) os.mkdir(dir_path2) os.mkdir(nested_dir_path) with open(zipped_file_path, "w") as tmpfile: tmpfile.write(self.test_string) with open(nested_zipped_file_path, "w") as tmpfile: tmpfile.write(self.nested_test_string) with open(testfile_path, "w") as tmpfile: tmpfile.write(self.test_string) make_zip(nested_zip_file_path, root_dir=self.tmpdir.name, base_dir=self.nested_dir_name) shutil.rmtree(nested_dir_path) # this will include outside.zip itself into the zip make_zip(self.zip_file_path, root_dir=self.tmpdir.name, base_dir=".") def tearDown(self): self.tmpdir.cleanup() local.remove(self.zip_file_path) def test_read_bytes(self): with local.open_zip(os.path.abspath(self.zip_file_path)) as z: with z.open(self.zipped_file_path, "rb") as zipped_file: self.assertEqual(self.test_string_b, zipped_file.read()) def test_read_string(self): with local.open_zip(os.path.abspath(self.zip_file_path)) as z: with z.open(self.zipped_file_path, "r") as zipped_file: self.assertEqual(self.test_string, zipped_file.readline()) def test_write_bytes(self): testfile_name = "testfile3" test_string = "this is a written string\n" test_string_b = test_string.encode("utf-8") with local.open_zip(os.path.abspath(self.zip_file_path), 'w') as z: with z.open(testfile_name, "wb") as zipped_file: zipped_file.write(test_string_b) with local.open_zip(os.path.abspath(self.zip_file_path)) as z: with z.open(testfile_name, "rb") as zipped_file: self.assertEqual(test_string_b, zipped_file.readline()) def test_write_string(self): testfile_name = "testfile3" test_string = "this is a written string\n" with local.open_zip(os.path.abspath(self.zip_file_path), 'w') as z: with z.open(testfile_name, "w") as zipped_file: zipped_file.write(test_string) with local.open_zip(os.path.abspath(self.zip_file_path)) as z: with z.open(testfile_name, "r") as zipped_file: self.assertEqual(test_string, zipped_file.readline()) def test_open_non_exist(self): non_exist_file = "non_exist_file.txt" with local.open_zip(os.path.abspath(self.zip_file_path)) as z: # ZipFile raises KeyError while io module raises IOError self.assertRaises(KeyError, z.open, non_exist_file) @parameterized.expand([ # not normalized path ['././{}//../{}/{}'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"])] ]) def test_open_non_normalized_path(self, path_or_prefix): with local.open_zip(os.path.abspath(self.zip_file_path)) as z: with z.open(path_or_prefix, "r") as zipped_file: self.assertEqual(self.test_string, zipped_file.read()) @parameterized.expand([ # default case get the first level from the root ["", [ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["testfile_name"]], False], # Problem 1 in issue #66 [ZIP_TEST_FILENAME_LIST["dir_name2"], [ZIP_TEST_FILENAME_LIST["zipped_file_name"]], False], # problem 2 in issue #66 [ZIP_TEST_FILENAME_LIST["dir_name2"], [ZIP_TEST_FILENAME_LIST["zipped_file_name"]], False], # not normalized path ['{}//{}//../'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), [ZIP_TEST_FILENAME_LIST["zipped_file_name"]], False], # not normalized path root ['{}//..//'.format(ZIP_TEST_FILENAME_LIST["dir_name2"]), [ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["testfile_name"]], False], # not normalized path beyond root ['//..//', [ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["testfile_name"]], False], # not normalized path beyond root ['{}//..//'.format(ZIP_TEST_FILENAME_LIST["dir_name2"]), [ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["testfile_name"]], False], # starting with slash ['/', [ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["testfile_name"]], False], # recursive test ['', [ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], os.path.join(ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["nested_zip_file_name"]), os.path.join(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), ZIP_TEST_FILENAME_LIST["testfile_name"]], True], [ZIP_TEST_FILENAME_LIST["dir_name2"], [ZIP_TEST_FILENAME_LIST["zipped_file_name"]], True], # problem 2 in issue #66 [ZIP_TEST_FILENAME_LIST["dir_name2"], [ZIP_TEST_FILENAME_LIST["zipped_file_name"]], True], # not normalized path ['{}//{}//../'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), [ZIP_TEST_FILENAME_LIST["zipped_file_name"]], True], # not normalized path root ['{}//..//'.format(ZIP_TEST_FILENAME_LIST["dir_name2"]), [ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], os.path.join(ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["nested_zip_file_name"]), os.path.join(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), ZIP_TEST_FILENAME_LIST["testfile_name"]], True], # not normalized path beyond root ['//..//', [ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], os.path.join(ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["nested_zip_file_name"]), os.path.join(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), ZIP_TEST_FILENAME_LIST["testfile_name"]], True], # starting with slash ['/', [ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], os.path.join(ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["nested_zip_file_name"]), os.path.join(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), ZIP_TEST_FILENAME_LIST["testfile_name"]], True]] ) def test_list(self, path_or_prefix, expected_list, recursive): with local.open_zip(self.zip_file_path) as z: zip_generator = z.list(path_or_prefix, recursive=recursive) zip_list = list(zip_generator) self.assertEqual(sorted(expected_list), sorted(zip_list)) @parameterized.expand([ # non_exist_file ['does_not_exist', FileNotFoundError], # not exist but share the prefix ['{}'.format(ZIP_TEST_FILENAME_LIST["dir_name2"][:1]), FileNotFoundError], # broken path ['{}//{}/'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"][:1]), FileNotFoundError], # list a file ['{}//{}///'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), NotADirectoryError] ]) def test_list_with_errors(self, path_or_prefix, error): with local.open_zip(self.zip_file_path) as z: with self.assertRaises(error): list(z.list(path_or_prefix)) with self.assertRaises(error): list(z.list(path_or_prefix, recursive=True)) @parameterized.expand([ # path ends with slash ['{}//'.format(ZIP_TEST_FILENAME_LIST["dir_name2"]), True], # not normalized path ['{}//{}'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), False], ['{}//..//{}/{}'.format(ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), False], # problem 2 in issue #66 [ZIP_TEST_FILENAME_LIST["dir_name2"], True], # not normalized path ['{}//{}//../'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), True], # not normalized path root ['{}//..//'.format(ZIP_TEST_FILENAME_LIST["dir_name2"]), False], # not normalized path beyond root ['//..//', False], # starting with slash ['/', False]] ) def test_isdir(self, path_or_prefix, expected): with local.open_zip(self.zip_file_path) as z: self.assertEqual(z.isdir(path_or_prefix), expected) @parameterized.expand(NON_EXIST_LIST) def test_isdir_non_exist(self, path_or_prefix): with local.open_zip(self.zip_file_path) as z: self.assertFalse(z.isdir(path_or_prefix)) def test_mkdir(self): with local.open_zip(self.zip_file_path) as z: self.assertRaises(io.UnsupportedOperation, z.mkdir, "test") def test_makedirs(self): with local.open_zip(self.zip_file_path) as z: self.assertRaises(io.UnsupportedOperation, z.makedirs, "test/test") def test_pickle(self): pickle_file_name = "test_pickle.pickle" test_data = {'test_elem1': b'balabala', 'test_elem2': 'balabala'} pickle_zip = "test_pickle.zip" with open(pickle_file_name, "wb") as f: pickle.dump(test_data, f) with ZipFile(pickle_zip, "w") as test_zip: test_zip.write(pickle_file_name) with local.open_zip(pickle_zip) as z: with z.open(pickle_file_name, 'rb') as f: loaded_obj = pickle.load(f) self.assertEqual(test_data, loaded_obj) os.remove(pickle_file_name) os.remove(pickle_zip) @parameterized.expand([ # path ends with slash ['{}//'.format(ZIP_TEST_FILENAME_LIST["dir_name2"]), True], # not normalized path ['{}//{}'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), True], ['{}//..//{}/{}'.format(ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), True], ['{}//..//{}/{}'.format(ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"][:-1] ), False], # # not normalized path ['{}//{}//../'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), True], # not normalized path root ['{}//..//'.format(ZIP_TEST_FILENAME_LIST["dir_name2"]), False], # not normalized path beyond root ['//..//', False], # starting with slash ['/', False]] ) def test_exists(self, path_or_prefix, expected): with local.open_zip(self.zip_file_path) as z: self.assertEqual(z.exists(path_or_prefix), expected) @parameterized.expand(NON_EXIST_LIST) def test_not_exists(self, non_exist_file): with local.open_zip(self.zip_file_path) as z: self.assertFalse(z.exists(non_exist_file)) def test_remove(self): with local.open_zip(self.zip_file_path) as z: self.assertRaises(io.UnsupportedOperation, z.remove, "test/test", False) def test_nested_zip(self): with local.open_zip(self.zip_file_path) as z: with z.open_zip( self.nested_zip_path) as nested_zip: with nested_zip.open(self.nested_zipped_file_path) as f: self.assertEqual(f.read(), self.nested_test_string) with nested_zip.open(self.nested_zipped_file_path, "r") as f: self.assertEqual(f.read(), self.nested_test_string) with nested_zip.open(self.nested_zipped_file_path, "rb") as f: self.assertEqual(f.read(), self.nested_test_string_b) @parameterized.expand([ # path ends with slash ['{}//'.format(ZIP_TEST_FILENAME_LIST["dir_name2"]), '{}/'.format(ZIP_TEST_FILENAME_LIST["dir_name2"])], # not normalized path ['{}//{}'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), '{}/{}'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"])], ['{}//..//{}/{}'.format(ZIP_TEST_FILENAME_LIST["dir_name1"], ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), '{}/{}'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"])], ['{}//{}//../'.format(ZIP_TEST_FILENAME_LIST["dir_name2"], ZIP_TEST_FILENAME_LIST["zipped_file_name"]), '{}/'.format(ZIP_TEST_FILENAME_LIST["dir_name2"])] ]) def test_stat(self, path_or_prefix, expected): with local.open_zip(self.zip_file_path) as z: self.assertEqual(expected, z.stat(path_or_prefix).filename) @parameterized.expand([ # not normalized path root '{}//..//'.format(ZIP_TEST_FILENAME_LIST["dir_name2"]), # not normalized path beyond root '//..//', # root '/'] + NON_EXIST_LIST) def test_stat_non_exist(self, path_or_prefix): with local.open_zip(self.zip_file_path) as z: with self.assertRaises(FileNotFoundError): z.stat(path_or_prefix) def test_stat_file(self): test_file_name = 'testdir2/testfile1' expected = ZipFile(self.zip_file_path).getinfo(test_file_name) with local.open_zip(self.zip_file_path) as z: stat = z.stat(test_file_name) self.assertIsInstance(stat, ZipFileStat) self.assertTrue(stat.filename.endswith(test_file_name)) self.assertEqual(stat.size, expected.file_size) self.assertEqual(stat.mode, expected.external_attr >> 16) self.assertFalse(stat.isdir()) expected_mtime = datetime(*expected.date_time).timestamp() self.assertIsInstance(stat.last_modified, float) self.assertEqual(stat.last_modified, expected_mtime) for k in ('filename', 'orig_filename', 'comment', 'create_system', 'create_version', 'extract_version', 'flag_bits', 'volume', 'internal_attr', 'external_attr', 'CRC', 'header_offset', 'compress_size', 'compress_type'): self.assertEqual(getattr(stat, k), getattr(expected, k)) def test_stat_directory(self): test_dir_name = 'testdir2/' expected = ZipFile(self.zip_file_path).getinfo(test_dir_name) with local.open_zip(self.zip_file_path) as z: stat = z.stat(test_dir_name) self.assertIsInstance(stat, ZipFileStat) self.assertTrue(stat.filename.endswith(test_dir_name)) self.assertEqual(stat.size, expected.file_size) self.assertEqual(stat.mode, expected.external_attr >> 16) self.assertTrue(stat.isdir()) expected_mtime = datetime(*expected.date_time).timestamp() self.assertIsInstance(stat.last_modified, float) self.assertEqual(stat.last_modified, expected_mtime) for k in ('filename', 'orig_filename', 'comment', 'create_system', 'create_version', 'extract_version', 'flag_bits', 'volume', 'internal_attr', 'external_attr', 'CRC', 'header_offset', 'compress_size', 'compress_type'): self.assertEqual(getattr(stat, k), getattr(expected, k)) def test_writing_after_listing(self): testfile_name = "testfile3" test_string = "this is a written string\n" with local.open_zip( os.path.abspath(self.zip_file_path), 'w') as z: list(z.list()) with z.open(testfile_name, "w") as zipped_file: zipped_file.write(test_string) @pytest.mark.skipif(sys.version_info > (3, 5), reason="requires python3.5 or lower") def test_mode_w_exception(self): testfile_name = "testfile3" test_string = "this is a written string\n" with local.open_zip( os.path.abspath(self.zip_file_path)) as z: with self.assertRaises(ValueError): with z.open(testfile_name, "w") as zipped_file: zipped_file.write(test_string) class TestZipWithLargeData(unittest.TestCase): def setUp(self): # The following zip layout is created for all the tests # outside.zip # | - testfile1 n = 1 << 20 self.test_string = make_random_str(n) # the most outside zip self.zip_file_name = "outside" # nested zip and nested file self.tmpdir = tempfile.TemporaryDirectory() # test file self.testfile_name = "testfile1" # paths used in making outside.zip testfile_path = os.path.join(self.tmpdir.name, self.testfile_name) # paths used in tests self.zip_file_path = self.zip_file_name + ".zip" with open(testfile_path, "w") as tmpfile: tmpfile.write(self.test_string) # this will include outside.zip itself into the zip make_zip(self.zip_file_path, root_dir=self.tmpdir.name, base_dir=".") def tearDown(self): self.tmpdir.cleanup() local.remove(self.zip_file_path) def test_read_multi_processes(self): barrier = multiprocessing.Barrier(2) with local.open_zip( os.path.abspath(self.zip_file_path)) as z: with z.open(self.testfile_name) as f: f.read() def func(): # accessing the shared container isn't supported in v2 with self.assertRaises(RuntimeError): with z.open(self.testfile_name) as f: barrier.wait() f.read() p1 = multiprocessing.Process(target=func) p2 = multiprocessing.Process(target=func) p1.start() p2.start() p1.join(timeout=1) p2.join(timeout=1) self.assertEqual(p1.exitcode, 0) self.assertEqual(p2.exitcode, 0) NO_DIRECTORY_FILENAME_LIST = { "dir1_name": "testdir1", "dir2_name": "testdir2", "dir3_name": "testdir3", "testfile1_name": "testfile1", "testfile2_name": "testfile2", "testfile3_name": "testfile3", "testfile4_name": "testfile4", } class TestZipListNoDirectory(unittest.TestCase): def setUp(self): # The following zip layout is created for all the tests # The difference is despite showing in the following layout for # readabilty, the directories are not included in the zip # outside.zip # | - testdir1 # | - | - testfile1 # | - | - testdir2 # | - | - | - testfile2 # | - testdir3 # | | - testfile3 # | - testfile4 self.test_string = "this is a test string\n" # the most outside zip self.zip_file_name = "outside.zip" # nested zip and nested file self.tmpdir = tempfile.TemporaryDirectory() # directory and file self.dir1_name = NO_DIRECTORY_FILENAME_LIST["dir1_name"] self.dir2_name = NO_DIRECTORY_FILENAME_LIST["dir2_name"] self.dir3_name = NO_DIRECTORY_FILENAME_LIST["dir3_name"] self.testfile1_name = NO_DIRECTORY_FILENAME_LIST["testfile1_name"] self.testfile2_name = NO_DIRECTORY_FILENAME_LIST["testfile2_name"] self.testfile3_name = NO_DIRECTORY_FILENAME_LIST["testfile3_name"] self.testfile4_name = NO_DIRECTORY_FILENAME_LIST["testfile4_name"] # paths used in making outside.zip dir1_path = os.path.join(self.tmpdir.name, self.dir1_name) dir2_path = os.path.join(dir1_path, self.dir2_name) dir3_path = os.path.join(self.tmpdir.name, self.dir3_name) testfile1_path = os.path.join(dir1_path, self.testfile1_name) testfile2_path = os.path.join(dir2_path, self.testfile2_name) testfile3_path = os.path.join(dir3_path, self.testfile3_name) testfile4_path = os.path.join(self.tmpdir.name, self.testfile4_name) # paths used in tests for dir in [dir1_path, dir2_path, dir3_path]: os.mkdir(dir) for file_path in [testfile1_path, testfile2_path, testfile3_path, testfile4_path]: with open(file_path, "w") as f: f.write(self.test_string) # create zip without directory self.pwd = os.getcwd() os.chdir(self.tmpdir.name) cmd = ["zip", "-rD", self.zip_file_name, "."] process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE) stdout, stderr = process.communicate() assert stderr == b"" def tearDown(self): os.chdir(self.pwd) self.tmpdir.cleanup() @parameterized.expand([ # default case get the first level from the root ["", [NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], False], # Problem 1 in issue #66 [NO_DIRECTORY_FILENAME_LIST["dir1_name"], [NO_DIRECTORY_FILENAME_LIST["testfile1_name"], NO_DIRECTORY_FILENAME_LIST["dir2_name"]], False], # problem 2 in issue #66 [os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir2_name"]), [NO_DIRECTORY_FILENAME_LIST["testfile2_name"]], False], # not normalized path ['{}//{}//../'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), [NO_DIRECTORY_FILENAME_LIST["testfile1_name"], NO_DIRECTORY_FILENAME_LIST["dir2_name"]], False], # not normalized path root ['{}//..//'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"]), [NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], False], # not normalized path beyond root ['//..//', [NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], False], # not normalized path beyond root ['{}//..//'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"]), [NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], False], # starting with slash ['/', [NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], False], # recursive test ['', [os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir2_name"], NO_DIRECTORY_FILENAME_LIST["testfile2_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile3_name"]), NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], True], [NO_DIRECTORY_FILENAME_LIST["dir1_name"], [NO_DIRECTORY_FILENAME_LIST["testfile1_name"], os.path.join(NO_DIRECTORY_FILENAME_LIST["dir2_name"], NO_DIRECTORY_FILENAME_LIST["testfile2_name"])], True], # problem 2 in issue #66 [NO_DIRECTORY_FILENAME_LIST["dir1_name"], [NO_DIRECTORY_FILENAME_LIST["testfile1_name"], os.path.join(NO_DIRECTORY_FILENAME_LIST["dir2_name"], NO_DIRECTORY_FILENAME_LIST["testfile2_name"])], True], # not normalized path ['{}//{}//../'.format( NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), [NO_DIRECTORY_FILENAME_LIST["testfile1_name"], os.path.join(NO_DIRECTORY_FILENAME_LIST["dir2_name"], NO_DIRECTORY_FILENAME_LIST["testfile2_name"])], True], # not normalized path root ['{}//..//'.format(NO_DIRECTORY_FILENAME_LIST["dir2_name"]), [os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir2_name"], NO_DIRECTORY_FILENAME_LIST["testfile2_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile3_name"]), NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], True], # not normalized path beyond root ['//..//', [os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir2_name"], NO_DIRECTORY_FILENAME_LIST["testfile2_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile3_name"]), NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], True], # not normalized path beyond root ['{}//..//../'.format(NO_DIRECTORY_FILENAME_LIST["dir2_name"]), [os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir2_name"], NO_DIRECTORY_FILENAME_LIST["testfile2_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile3_name"]), NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], True], # starting with slash ['/', [os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir2_name"], NO_DIRECTORY_FILENAME_LIST["testfile2_name"]), os.path.join(NO_DIRECTORY_FILENAME_LIST["dir3_name"], NO_DIRECTORY_FILENAME_LIST["testfile3_name"]), NO_DIRECTORY_FILENAME_LIST["testfile4_name"]], True] ]) def test_list(self, path_or_prefix, expected_list, recursive): with local.open_zip(self.zip_file_name) as z: zip_generator = z.list(path_or_prefix, recursive=recursive) zip_list = list(zip_generator) self.assertEqual(sorted(expected_list), sorted(zip_list)) @parameterized.expand([ # non_exist_file ['does_not_exist', FileNotFoundError], # not exist but share the prefix ['t', FileNotFoundError], # broken path ['{}//t/'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"]), FileNotFoundError], # list a file ['{}//{}///'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), NotADirectoryError], # list a non_exist_dir but share the surfix ['{}/'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"][:-1]), FileNotFoundError] ]) def test_list_with_errors(self, path_or_prefix, error): with local.open_zip(self.zip_file_name) as z: with self.assertRaises(error): list(z.list(path_or_prefix)) with self.assertRaises(error): list(z.list(path_or_prefix, recursive=True)) @parameterized.expand([ # path ends with slash ['{}//'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"]), True], # not normalized path ['{}//{}'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), False], ['{}//..//{}/{}'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["dir2_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), False], # problem 2 in issue #66 [NO_DIRECTORY_FILENAME_LIST["dir1_name"], True], # not normalized path ['{}//{}//../'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"], NO_DIRECTORY_FILENAME_LIST["testfile1_name"]), True], # not normalized path root ['{}//..//'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"]), False], # not normalized path beyond root ['//..//', False], # not normalized path beyond root ['{}//..//'.format(NO_DIRECTORY_FILENAME_LIST["dir1_name"]), False], # starting with slash ['/', False] ]) def test_isdir(self, path_or_prefix, expected): with local.open_zip(self.zip_file_name) as z: self.assertEqual(z.isdir(path_or_prefix), expected) @parameterized.expand([ ["does_not_exist"], ["does_not_exist/"], ["does/not/exist"] ]) def test_isdir_not_exist(self, dir): with local.open_zip(self.zip_file_name) as z: self.assertFalse(z.isdir(dir))

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0.602286

4,114

35,171

4.784638

0.062713

0.13229

0.085349

0.108108

0.828795

0.806594

0.784698

0.746037

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0.699858

0

0.01248

0.282335

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0.767363

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0.125305

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0.07465

1

0.054432

false

0

0.023328

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0.082426

0

null

0

1

0

null

0

6

c4e7a2a2ac1c872fead87410405f22d1617f105a

74

py

Python

src/utils/callbacks/__init__.py

kryvokhyzha/bert-for-ukranian-ner

48da40f09cb216ad51a97c303998157858fbe8bc

[ "MIT" ]

null

src/utils/callbacks/__init__.py

kryvokhyzha/bert-for-ukranian-ner

48da40f09cb216ad51a97c303998157858fbe8bc

[ "MIT" ]

null

src/utils/callbacks/__init__.py

kryvokhyzha/bert-for-ukranian-ner

48da40f09cb216ad51a97c303998157858fbe8bc

[ "MIT" ]

null

from utils.callbacks.AccuracyCallbackCustom import AccuracyCallbackCustom

37

73

0.918919

6

74

11.333333

0.833333

0

0.054054

74

1

74

0.971429

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

1

0

6

4848054099bf561beeffed4aa75a0a6768d7dbb6

36

py

Python

tests/test_mathformsmk.py

KarlosMuradyan/mathformsmk

de916750bfcdff3c7a1f226a66ddaed7b2e9b92f

[ "MIT" ]

null

tests/test_mathformsmk.py

KarlosMuradyan/mathformsmk

de916750bfcdff3c7a1f226a66ddaed7b2e9b92f

[ "MIT" ]

null

tests/test_mathformsmk.py

KarlosMuradyan/mathformsmk

de916750bfcdff3c7a1f226a66ddaed7b2e9b92f

[ "MIT" ]

null

from mathformsmk import mathformsmk

18

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36

8

0.75

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36

1

36

1

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1

0

true

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0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

4863e39ebc09e78ccd37269574e1238fe9bab7fb

3,471

py

Python

tests/admin/test_user_phones.py

joshua-cerniglia/duo_client_python

9d91cdd505d9ed999f8d79305181587d626186bd

[ "Apache-2.0" ]

96

2015-01-02T08:03:29.000Z

2022-03-28T13:31:39.000Z

tests/admin/test_user_phones.py

joshua-cerniglia/duo_client_python

9d91cdd505d9ed999f8d79305181587d626186bd

[ "Apache-2.0" ]

87

2015-05-12T02:44:33.000Z

2022-01-20T05:53:27.000Z

tests/admin/test_user_phones.py

joshua-cerniglia/duo_client_python

9d91cdd505d9ed999f8d79305181587d626186bd

[ "Apache-2.0" ]

110

2015-03-03T20:23:42.000Z

2021-12-16T23:01:29.000Z

from .. import util import duo_client.admin from .base import TestAdmin class TestUserPhones(TestAdmin): def test_get_user_phones_iterator(self): """Test to get phones iterator by user id """ iterator = self.client_list.get_user_phones_iterator( 'DU012345678901234567') response = next(iterator) uri, args = response['uri'].split('?') self.assertEqual(response['method'], 'GET') self.assertEqual(uri, '/admin/v1/users/DU012345678901234567/phones') self.assertEqual(util.params_to_dict(args), { 'account_id':[self.client.account_id], 'limit': ['100'], 'offset': ['0'], }) def test_get_user_phones(self): """Test to get phones by user id """ response = self.client_list.get_user_phones('DU012345678901234567')[0] uri, args = response['uri'].split('?') self.assertEqual(response['method'], 'GET') self.assertEqual(uri, '/admin/v1/users/DU012345678901234567/phones') self.assertEqual(util.params_to_dict(args), { 'account_id':[self.client.account_id], 'limit': ['100'], 'offset': ['0'], }) def test_get_user_phones_with_offset(self): """Test to get phones by user id with pagination params """ response = self.client_list.get_user_phones( 'DU012345678901234567', offset=30)[0] uri, args = response['uri'].split('?') self.assertEqual(response['method'], 'GET') self.assertEqual(uri, '/admin/v1/users/DU012345678901234567/phones') self.assertEqual(util.params_to_dict(args), { 'account_id':[self.client.account_id], 'limit': ['100'], 'offset': ['0'], }) def test_get_user_phones_with_limit(self): """Test to get phones by user id with pagination params """ response = self.client_list.get_user_phones( 'DU012345678901234567', limit=10)[0] uri, args = response['uri'].split('?') self.assertEqual(response['method'], 'GET') self.assertEqual(uri, '/admin/v1/users/DU012345678901234567/phones') self.assertEqual(util.params_to_dict(args), { 'account_id':[self.client.account_id], 'limit': ['10'], 'offset': ['0'], }) def test_get_user_phones_with_limit_and_offset(self): """Test to get phones by user id with pagination params """ response = self.client_list.get_user_phones( 'DU012345678901234567', limit=10, offset=30)[0] uri, args = response['uri'].split('?') self.assertEqual(response['method'], 'GET') self.assertEqual(uri, '/admin/v1/users/DU012345678901234567/phones') self.assertEqual(util.params_to_dict(args), { 'account_id':[self.client.account_id], 'limit': ['10'], 'offset': ['30'], }) if __name__ == '__main': unittest.main()

38.566667

78

0.519447

334

3,471

5.197605

0.140719

0.129608

0.074885

0.040323

0.889401

0.866935

0.851382

0.804147

0.783986

0

0.096128

0.352636

3,471

89

79

39

0.676458

0.075771

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0.636364

0

0.160731

0.067759

0

0.227273

1

0.075758

false

0

0.045455

0

0.136364

0

null

0

1

0

null

0

6

4886dc933255d27840a44f9c2fc19a05adc03c51

22

py

Python

hello-scripts/harrison-mitchell.py

StuWares/Hacktoberfest2018

fb1efa15c37cd03bb9da89981aa26d152414a273

[ "MIT" ]

null

hello-scripts/harrison-mitchell.py

StuWares/Hacktoberfest2018

fb1efa15c37cd03bb9da89981aa26d152414a273

[ "MIT" ]

null

hello-scripts/harrison-mitchell.py

StuWares/Hacktoberfest2018

fb1efa15c37cd03bb9da89981aa26d152414a273

[ "MIT" ]

null

print("He"+"l"*2+"o")

11

21

0.454545

5

22

2

1

0

0.047619

0.045455

22

1

22

0.428571

0

0.181818

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

6ff884019d0c956fdc3e80e0cc76347601fa2f55

11,100

py

Python

boardfarm/lib/gui_helper.py

superice119/boardfarm

c525b4da94bf745d30c4a9f675aa4a7ae184b1fd

[ "BSD-3-Clause-Clear" ]

null

boardfarm/lib/gui_helper.py

superice119/boardfarm

c525b4da94bf745d30c4a9f675aa4a7ae184b1fd

[ "BSD-3-Clause-Clear" ]

null

boardfarm/lib/gui_helper.py

superice119/boardfarm

c525b4da94bf745d30c4a9f675aa4a7ae184b1fd

[ "BSD-3-Clause-Clear" ]

null

# Copyright (c) 2018 # # All rights reserved. # # This file is distributed under the Clear BSD license. # The full text can be found in LICENSE in the root directory. # vim: tabstop=8 expandtab shiftwidth=4 softtabstop=4 import time from selenium.common.exceptions import NoSuchElementException from selenium.webdriver.support.select import Select def enter_input(web_gui, input_path, input_value): """To enter the text box value in web page :param web_gui: web driver after initailizing page :type web_gui : string :param input_path : element id of particular box :type input_path : string :param input_value : text box value to be enter :type input_value : string :raises Exception : If error thrown returns False :return: True :rtype: boolean """ try: input_tab = web_gui.find_element_by_id(input_path) input_tab.clear() input_tab.send_keys(input_value) return True except NoSuchElementException: return False def click_button_id(web_gui, clickbutton): """To click the button using the element id :param web_gui: web driver after initailizing page :type web_gui : string :param clickbutton : web element id of the button :type clickbutton : string :raises Exception : If error thrown returns False :return: True :rtype: boolean """ try: click_tab = web_gui.find_element_by_id(clickbutton) click_tab.click() time.sleep(5) return True except NoSuchElementException: return False def click_button_xpath(web_gui, clickbutton): """To click the page button using the xpath :param web_gui: web driver after initailizing page :type web_gui : string :param clickbutton : web element id of the button :type clickbutton : string :raises Exception : If error thrown returns False :return: True :rtype: boolean """ try: click_tab = web_gui.find_element_by_xpath(clickbutton) click_tab.click() time.sleep(5) return True except NoSuchElementException: return False def select_option_by_id(web_gui, select_button, select_value): """To select the option from drop down using id :param web_gui: web driver after initailizing page :type web_gui : string :param select_button : web element id of drop down :type select_button : string :param select_value : value to be selected :type select_value : string :raises Exception : If error thrown returns False :return : value to be chosen :rtype : string """ try: select = Select(web_gui.find_element_by_id(select_button)) select.select_by_visible_text(select_value) time.sleep(5) return select except NoSuchElementException: return None def select_option_by_name(web_gui, select_button, select_value): """To select the option from drop down using element name :param web_gui: web driver after initailizing page :type web_gui : string :param select_button : web element id of drop down :type select_button : string :param select_value : value to be selected :type select_value : string :raises Exception : If error thrown returns None :return : value to be chosen :rtype : string """ try: select = Select(web_gui.find_element_by_name(select_button)) select.select_by_visible_text(select_value) time.sleep(5) return select except NoSuchElementException: return None def select_option_by_xpath(web_gui, select_button, select_value): """To select the option from drop down using xpath :param web_gui: web driver after initailizing page :type web_gui : string :param select_button : web element id of drop down :type select_button : string :param select_value : value to be selected :type select_value : string :raises Exception : If error thrown returns None :return : value to be chosen :rtype : string """ try: select = Select(web_gui.find_element_by_xpath(select_button)) select.select_by_visible_text(select_value) time.sleep(5) return select except NoSuchElementException: return None def get_drop_down_value(web_gui, get_value): """To get the drop down value using id :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : text value to check whether it exists in drop down :type get_value : string :raises Exception : If error thrown returns None :return : value to be chosen :rtype : string """ try: select = Select(web_gui.find_element_by_id(get_value)) selected_option = select.first_selected_option selected_value = selected_option.text return selected_value except NoSuchElementException: return None def get_radio_button_value(web_gui, get_value): """To get the radio button status whether chosen or not :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : web element id for the radio button :type get_value : string :raises Exception : If error thrown returns None :return : True or False :rtype : boolean """ try: radio_button = web_gui.find_elements_by_id(get_value) for radiobutton in radio_button: radio = radiobutton.get_attribute('src') if "radio-box-checked" in radio: return True else: return False except NoSuchElementException: return None def get_text_value(web_gui, get_value): """To get the radio button status whether chosen or not :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : web element id for the radio button :type get_value : string :raises Exception : If error thrown returns None :return : True or False :rtype : boolean """ try: text_button = web_gui.find_element_by_id(get_value) text_value = text_button.text return text_value except NoSuchElementException: return None def get_text_value_by_xpath(web_gui, get_value): """To get the text box value using xpath :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : web element xpath for the text box :type get_value : string :raises Exception : If error thrown returns None :return : text box value for required element :rtype : string or boolean """ try: text_button = web_gui.find_element_by_xpath(get_value) text_value = text_button.text return text_value except NoSuchElementException: return None def get_value_from_disabled_input(web_gui, get_value): """To get the value for diabled element :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : web element id for required input :type get_value : string :raises Exception : If error thrown returns None :return : text value for required element :rtype : string """ js = "return document.getElementById(\"{!s}\").value;".format( str(get_value)) text_value = web_gui.execute_script(js) return str(text_value) def get_icon_check_value_by_id(web_gui, get_value): """To get the icon button status whether chosen or not using id :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : web element id for the icon button :type get_value : string :raises Exception : If error thrown returns None :return : True if icon button selected else false :rtype : boolean """ try: icon_button = web_gui.find_elements_by_id(get_value) for iconbutton in icon_button: icon = iconbutton.get_attribute('src') if "icon-check.svg" in icon: return True else: return False except NoSuchElementException: return None def get_icon_check_value_by_xpath(web_gui, get_value): """To get the icon button status whether chosen or not using xpath :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : web element xpath for the icon button :type get_value : string :raises Exception : If error thrown returns None :return : True if icon button selected else false :rtype : boolean """ try: icon_button = web_gui.find_elements_by_xpath(get_value) for iconbutton in icon_button: icon = iconbutton.get_attribute('src') if "icon-check.svg" in icon: return True else: return False except NoSuchElementException: return None def check_element_is_enable_by_id(web_gui, check_value): """To get the enabled text button value using id :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : web element id for the enabled element :type get_value : string :raises Exception : If error thrown returns None :return : enabled text button value :rtype : string or boolean """ try: text_button = web_gui.find_element_by_id(check_value) text_value = text_button.is_enabled() return text_value except NoSuchElementException: return None def get_check_box_value_by_id(web_gui, get_value): """To get the check box whether chosen or not using id :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : web element id for the check box :type get_value : string :raises Exception : If error thrown returns None :return : true or false based on check box status :rtype : bool """ try: box_button = web_gui.find_elements_by_id(get_value) for boxbutton in box_button: box = boxbutton.get_attribute('src') if "check-box-checked.png" in box or 'radio-box-checked.png' in box: return True else: return False except NoSuchElementException: return None def get_check_box_value_by_xpath(web_gui, get_value): """To get the check box whether chosen or not using xpath :param web_gui: web driver after initailizing page :type web_gui : string :param get_value : web element xpath for the check box :type get_value : string :raises Exception : If error thrown returns None :return : true or false based on check box status :rtype : boolean """ try: box_button = web_gui.find_elements_by_xpath(get_value) for boxbutton in box_button: box = boxbutton.get_attribute('src') if "check-box-checked.png" in box or 'radio-box-checked.png' in box: return True else: return False except NoSuchElementException: return None

31.714286

80

0.679369

1,512

11,100

4.795635

0.08664

0.052958

0.024273

0.030892

0.845263

0.841953

0.820852

0.807475

0.79989

0.787616

0

0.001461

0.25991

11,100

349

81

31.805158

0.881193

0.481261

0

0.664286

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6ff9c2509a147ce16db92ea206c57b895d473d04

235

py

Python

plots/model_explorer/plotters/bar_plot/date_distribution/__init__.py

ZviBaratz/pylabber

35337284f3d0615249f642743b993b7dad407390

[ "Apache-2.0" ]

3

2020-08-28T21:33:07.000Z

2021-07-19T17:52:17.000Z

plots/model_explorer/plotters/bar_plot/date_distribution/__init__.py

TheLabbingProject/pylabber

27d6073e7bde871c16912a8ea5e0e389711bbd9f

[ "Apache-2.0" ]

74

2019-09-04T11:40:16.000Z

2022-01-03T19:43:04.000Z

plots/model_explorer/plotters/bar_plot/date_distribution/__init__.py

ZviBaratz/pylabber

35337284f3d0615249f642743b993b7dad407390

[ "Apache-2.0" ]

3

2019-05-07T07:09:05.000Z

2019-08-30T15:40:47.000Z

from plots.model_explorer.plotters.bar_plot.date_distribution.configuration import ( DateDistributionConfiguration, ) from plots.model_explorer.plotters.bar_plot.date_distribution.date_distribution import ( DateDistribution, )

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82f00f758a329d238b5910d192e23413353d4959

199

py

Python

src/utils/io.py

shirin1996/PyBot

4676ccca6b47fce4d3f20a7e158ea9278eb1b508

[ "MIT" ]

1

2022-01-30T20:27:31.000Z

src/utils/io.py

shirinyamani/MsgBot

0b95cea203ff97d631fba7cbf48c23c76f7d91e9

[ "MIT" ]

null

src/utils/io.py

shirinyamani/MsgBot

0b95cea203ff97d631fba7cbf48c23c76f7d91e9

[ "MIT" ]

null

import json def read_json(file_name): with open(file_name, 'r') as f: return json.load(f) def write_json(data, file_name): with open(file_name, 'w') as f: json.dump(data, f)

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d204008f3a1e70dea11c0be776f29fb0236fb655

4,218

py

Python

test/integration/remote_plugins/plugins/system_registration_test.py

scott-taubman/beer-garden

bac825849f7791e14064942566fbec63a83e6f87

[ "MIT" ]

230

2018-02-03T01:33:45.000Z

2022-02-20T22:07:25.000Z

test/integration/remote_plugins/plugins/system_registration_test.py

scott-taubman/beer-garden

bac825849f7791e14064942566fbec63a83e6f87

[ "MIT" ]

961

2018-02-06T11:22:40.000Z

2022-03-24T15:22:33.000Z

test/integration/remote_plugins/plugins/system_registration_test.py

scott-taubman/beer-garden

bac825849f7791e14064942566fbec63a83e6f87

[ "MIT" ]

33

2018-02-04T18:00:07.000Z

2021-12-15T13:07:22.000Z

import pytest from brewtils.errors import ValidationError try: from helper import delete_plugins from helper.assertion import assert_system_running from helper.plugin import ( TestPluginV1, TestPluginV1BetterDescriptions, TestPluginV2, create_plugin, start_plugin, stop_plugin, ) except (ImportError, ValueError): from ...helper import delete_plugins from ...helper.assertion import assert_system_running from ...helper.plugin import ( TestPluginV1, TestPluginV1BetterDescriptions, TestPluginV2, create_plugin, start_plugin, stop_plugin, ) @pytest.mark.usefixtures("easy_client") class TestSystemRegistration(object): @pytest.fixture(autouse=True) def delete_test_plugin(self): """Ensure there are no "test" plugins before or after the test""" delete_plugins(self.easy_client, "test") yield delete_plugins(self.easy_client, "test") def test_system_register_successful(self): plugin = create_plugin("test", "1.0.0", TestPluginV1) start_plugin(plugin, self.easy_client) assert_system_running(self.easy_client, "test", "1.0.0") stop_plugin(plugin) def test_system_register_update_data(self): # Register the standard plugin, then stop it plugin = create_plugin("test", "1.0.0", TestPluginV1) start_plugin(plugin, self.easy_client) assert_system_running(self.easy_client, "test", "1.0.0") stop_plugin(plugin) # Now create the new plugin and register that one plugin = create_plugin( "test", "1.0.0", TestPluginV1BetterDescriptions, description="A better description", metadata={"foo": "bar"}, icon_name="fa-coffee", display_name="new_display_name", ) start_plugin(plugin, self.easy_client) assert_system_running( self.easy_client, "test", "1.0.0", system={ "description": "A better description", "metadata": {"foo": "bar"}, "icon_name": "fa-coffee", "display_name": "new_display_name", }, ) stop_plugin(plugin) def test_system_register_dev_different_commands(self): # Register the standard plugin, then stop it plugin = create_plugin("test", "1.0.0.dev", TestPluginV1) start_plugin(plugin, self.easy_client) assert_system_running(self.easy_client, "test", "1.0.0.dev") stop_plugin(plugin) # Now create the new plugin and register that one plugin = create_plugin("test", "1.0.0.dev", TestPluginV2) start_plugin(plugin, self.easy_client) assert_system_running(self.easy_client, "test", "1.0.0.dev") stop_plugin(plugin) def test_system_register_different_commands_should_fail(self): plugin = create_plugin("test", "1.0.0", TestPluginV1) start_plugin(plugin, self.easy_client) assert_system_running(self.easy_client, "test", "1.0.0") stop_plugin(plugin) plugin = create_plugin("test", "1.0.0", TestPluginV2) with pytest.raises(ValidationError): self.easy_client.create_system(plugin.system) def test_system_register_different_versions(self): plugin = create_plugin("test", "1.0.0", TestPluginV1) start_plugin(plugin, self.easy_client) assert_system_running(self.easy_client, "test", "1.0.0") plugin = create_plugin("test", "2.0.0", TestPluginV2) start_plugin(plugin, self.easy_client) assert_system_running(self.easy_client, "test", "1.0.0") assert_system_running(self.easy_client, "test", "2.0.0") def test_system_register_same_instance_name(self): plugin = create_plugin("test", "1.0.0", TestPluginV1) start_plugin(plugin, self.easy_client) assert_system_running(self.easy_client, "test", "1.0.0") plugin = create_plugin("test", "1.0.0", TestPluginV1) with pytest.raises(ValidationError): self.easy_client.create_system(plugin.system)

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null

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6

d21ea368193945127c11d948d6e43cd9c4c55fac

22

py

Python

xlibris/__init__.py

konsbn/xlibris

d6ae33cd58212db3160b22128af9f209921f6205

[ "MIT" ]

9

2016-01-12T18:56:19.000Z

2021-09-24T16:08:14.000Z

xlibris/__init__.py

konsbn/xlibris

d6ae33cd58212db3160b22128af9f209921f6205

[ "MIT" ]

null

xlibris/__init__.py

konsbn/xlibris

d6ae33cd58212db3160b22128af9f209921f6205

[ "MIT" ]

1

2021-09-21T21:37:11.000Z

from xlibris import *

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1

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1

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6

d243175cd6681cc44ab0a359d42a5ecadb9c3acb

9,900

py

Python

src/tests/control/test_teams.py

upsidedownpancake/pretix

bfeeb1028c9eccab4936029db7c38edd4cd5aad5

[ "ECL-2.0", "Apache-2.0" ]

null

src/tests/control/test_teams.py

upsidedownpancake/pretix

bfeeb1028c9eccab4936029db7c38edd4cd5aad5

[ "ECL-2.0", "Apache-2.0" ]

null

src/tests/control/test_teams.py

upsidedownpancake/pretix

bfeeb1028c9eccab4936029db7c38edd4cd5aad5

[ "ECL-2.0", "Apache-2.0" ]

null

import pytest from django.core import mail as djmail from django.utils.timezone import now from pretix.base.models import Event, Organizer, Team, User @pytest.fixture def organizer(): return Organizer.objects.create(name='Dummy', slug='dummy') @pytest.fixture def event(organizer): event = Event.objects.create( organizer=organizer, name='Dummy', slug='dummy', date_from=now() ) return event @pytest.fixture def admin_team(organizer): return Team.objects.create(organizer=organizer, can_change_teams=True, name='Admin team') @pytest.fixture def admin_user(admin_team): u = User.objects.create_user('dummy@dummy.dummy', 'dummy') admin_team.members.add(u) return u @pytest.mark.django_db def test_list_of_teams(event, admin_user, client): client.login(email='dummy@dummy.dummy', password='dummy') resp = client.get('/control/organizer/dummy/teams') assert 'Admin team' in resp.rendered_content @pytest.mark.django_db def test_team_detail_view(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') resp = client.get('/control/organizer/dummy/team/{}/'.format(admin_team.pk)) assert 'Admin team' in resp.rendered_content assert admin_user.email in resp.rendered_content @pytest.mark.django_db def test_team_add_user(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') u = User.objects.create_user('dummy2@dummy.dummy', 'dummy') resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'user': u.email }, follow=True) assert 'Admin team' in resp.rendered_content assert admin_user.email in resp.rendered_content assert u.email in resp.rendered_content assert u in admin_team.members.all() @pytest.mark.django_db def test_team_create_invite(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') djmail.outbox = [] resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'user': 'foo@example.org' }, follow=True) assert 'Admin team' in resp.rendered_content assert admin_user.email in resp.rendered_content assert 'foo@example.org' in resp.rendered_content assert admin_team.invites.first().email == 'foo@example.org' assert len(djmail.outbox) == 1 @pytest.mark.django_db def test_team_create_token(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') djmail.outbox = [] resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'name': 'Test token' }, follow=True) assert 'Test token' in resp.rendered_content assert admin_team.tokens.first().name == 'Test token' assert admin_team.tokens.first().token in resp.rendered_content @pytest.mark.django_db def test_team_remove_token(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') tk = admin_team.tokens.create(name='Test token') resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'remove-token': str(tk.pk) }, follow=True) assert tk.token not in resp.rendered_content assert 'Test token' in resp.rendered_content tk.refresh_from_db() assert not tk.active @pytest.mark.django_db def test_team_revoke_invite(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') inv = admin_team.invites.create(email='foo@example.org') resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'remove-invite': str(inv.pk) }, follow=True) assert 'Admin team' in resp.rendered_content assert admin_user.email in resp.rendered_content assert not admin_team.invites.exists() @pytest.mark.django_db def test_team_remove_user(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') u = User.objects.create_user('dummy2@dummy.dummy', 'dummy') admin_team.members.add(u) resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'remove-member': u.pk }, follow=True) assert 'Admin team' in resp.rendered_content assert admin_user.email in resp.rendered_content assert u not in admin_team.members.all() @pytest.mark.django_db def test_team_remove_last_admin(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'remove-member': admin_user.pk }, follow=True) assert 'alert-danger' in resp.rendered_content assert admin_user in admin_team.members.all() t2 = Team.objects.create(organizer=event.organizer, name='Admin team 2') resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'remove-member': admin_user.pk }, follow=True) assert 'alert-danger' in resp.rendered_content assert admin_user in admin_team.members.all() t2.members.add(admin_user) resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'remove-member': admin_user.pk }, follow=True) assert 'alert-danger' in resp.rendered_content assert admin_user in admin_team.members.all() t2.can_change_teams = True t2.save() resp = client.post('/control/organizer/dummy/team/{}/'.format(admin_team.pk), { 'remove-member': admin_user.pk }, follow=True) assert 'alert-danger' not in resp.rendered_content assert admin_user not in admin_team.members.all() @pytest.mark.django_db def test_create_team(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') client.post('/control/organizer/dummy/team/add', { 'name': 'Foo', 'can_create_events': 'on', 'limit_events': str(event.pk), 'can_change_event_settings': 'on' }, follow=True) t = Team.objects.last() assert t.can_change_event_settings assert t.can_create_events assert not t.can_change_organizer_settings assert list(t.limit_events.all()) == [event] assert list(t.members.all()) == [admin_user] @pytest.mark.django_db def test_update_team(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') client.post('/control/organizer/dummy/team/{}/edit'.format(admin_team.pk), { 'name': 'Admin', 'can_change_teams': 'on', 'limit_events': str(event.pk), 'can_change_event_settings': 'on' }, follow=True) admin_team.refresh_from_db() assert admin_team.can_change_event_settings assert not admin_team.can_change_organizer_settings assert list(admin_team.limit_events.all()) == [event] @pytest.mark.django_db def test_update_last_team_to_be_no_admin(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') resp = client.post('/control/organizer/dummy/team/{}/edit'.format(admin_team.pk), { 'name': 'Admin', 'can_change_event_settings': 'on' }, follow=True) assert 'alert-danger' in resp.rendered_content @pytest.mark.django_db def test_remove_team(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') t2 = Team.objects.create(organizer=event.organizer, name='Admin team 2') resp = client.post('/control/organizer/dummy/team/{}/delete'.format(t2.pk), {}, follow=True) assert Team.objects.count() == 1 assert 'alert-success' in resp.rendered_content @pytest.mark.django_db def test_remove_last_admin_team(event, admin_user, admin_team, client): client.login(email='dummy@dummy.dummy', password='dummy') resp = client.post('/control/organizer/dummy/team/{}/delete'.format(admin_team.pk), {}, follow=True) assert Team.objects.count() == 1 assert 'alert-danger' in resp.rendered_content @pytest.mark.django_db def test_invite_invalid_token(event, admin_team, client): i = admin_team.invites.create(email='foo@bar.com') resp = client.get('/control/invite/foo{}bar'.format(i.token), follow=True) assert b'alert-danger' in resp.content assert b'invalid link' in resp.content @pytest.mark.django_db def test_invite_existing_team_member(event, admin_team, client): u = User.objects.create_user('dummy2@dummy.dummy', 'dummy') admin_team.members.add(u) client.login(email='dummy2@dummy.dummy', password='dummy') i = admin_team.invites.create(email='foo@bar.com') resp = client.get('/control/invite/{}'.format(i.token), follow=True) assert b'alert-danger' in resp.content assert b'already are part of' in resp.content @pytest.mark.django_db def test_invite_authenticated(event, admin_team, client): u = User.objects.create_user('dummy2@dummy.dummy', 'dummy') client.login(email='dummy2@dummy.dummy', password='dummy') i = admin_team.invites.create(email='foo@bar.com') resp = client.get('/control/invite/{}'.format(i.token), follow=True) assert b'alert-success' in resp.content assert u in admin_team.members.all() assert not admin_team.invites.exists() @pytest.mark.django_db def test_invite_new_user(event, admin_team, client): i = admin_team.invites.create(email='foo@bar.com') resp = client.get('/control/invite/{}'.format(i.token), follow=True) assert b'<form' in resp.content resp = client.post('/control/invite/{}'.format(i.token), { 'email': 'dummy@example.org', 'password': 'asdsdgfgjh', 'password_repeat': 'asdsdgfgjh' }, follow=True) assert b'alert-success' in resp.content assert admin_team.members.filter(email='dummy@example.org').exists() assert not admin_team.invites.exists()

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null

0

1

0

6

9631f802745b75178fbc96c16fb234d1bdef2377

7,017

py

Python

math_recognition/decoder.py

bkkaggle/math-recognition

aecfb21656a7744945862f4b34520905e50f3ad1

[ "MIT" ]

10

2019-12-27T04:35:42.000Z

2021-01-26T14:37:12.000Z

math_recognition/decoder.py

bilal2vec/math-recognition

aecfb21656a7744945862f4b34520905e50f3ad1

[ "MIT" ]

1

2020-10-26T06:25:25.000Z

2020-10-31T01:31:27.000Z

math_recognition/decoder.py

bkkaggle/math-recognition

aecfb21656a7744945862f4b34520905e50f3ad1

[ "MIT" ]

3

2020-02-11T06:22:15.000Z

2020-11-08T10:52:57.000Z

import os import random from typing import Dict, Tuple from overrides import overrides import numpy as np import pandas as pd import torch import torch.nn as nn import torch.nn.functional as F import torchvision import allennlp from allennlp.common import Registrable, Params from allennlp.data.vocabulary import Vocabulary from allennlp.modules.token_embedders import Embedding from math_recognition.attention import CaptioningAttention device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") class CaptioningDecoder(nn.Module, Registrable): def __init__(self, vocab: Vocabulary): super(CaptioningDecoder, self).__init__() self.vocab = vocab def forward(self, x: torch.Tensor, h: torch.Tensor, c: torch.Tensor, predicted_indices: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]: raise NotImplementedError() def get_output_dim(self) -> int: raise NotImplementedError() # Input dim is dim of h and c def get_input_dim(self) -> int: raise NotImplementedError() @CaptioningDecoder.register('image-captioning') class ImageCaptioningDecoder(CaptioningDecoder): def __init__(self, vocab: Vocabulary, attention: CaptioningAttention, embedding_dim:int = 256, decoder_dim:int = 256): super(ImageCaptioningDecoder, self).__init__(vocab=vocab) self._vocab_size = self.vocab.get_vocab_size() self._embedding_dim = embedding_dim self._decoder_dim = decoder_dim self._embedding = Embedding(self._vocab_size, self._embedding_dim) self._attention = attention self._decoder_cell = nn.LSTMCell(self._embedding.get_output_dim() + self._attention.get_output_dim(), self._decoder_dim) self._linear = nn.Linear(self._decoder_dim, self._vocab_size) @overrides def forward(self, x: torch.Tensor, h: torch.Tensor, c: torch.Tensor, predicted_indices: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]: # Shape: (batch_size, embedding_dim) embedding = self._embedding(predicted_indices).float().view(-1, self._embedding_dim) # Shape: (batch_size, encoder_dim) (batch_size, h * w, 1) attention, attention_weights = self._attention(x, h) ## Change to not use teacher forcing all the time # Shape: (batch_size, decoder_dim) (batch_size, decoder_dim) h, c = self._decoder_cell(torch.cat([attention, embedding], dim=1), (h, c)) # Get output predictions (one per character in vocab) # Shape: (batch_size, vocab_size) preds = self._linear(h) return h, c, preds, attention_weights @overrides def get_output_dim(self) -> int: return self._vocab_size @overrides def get_input_dim(self) -> int: return self._decoder_dim @CaptioningDecoder.register('WAP') class WAPDecoder(CaptioningDecoder): def __init__(self, vocab: Vocabulary, attention: CaptioningAttention, embedding_dim:int = 256, decoder_dim:int = 256): super(WAPDecoder, self).__init__(vocab=vocab) self._vocab_size = self.vocab.get_vocab_size() self._embedding_dim = embedding_dim self._decoder_dim = decoder_dim self._embedding = Embedding(self._vocab_size, self._embedding_dim) self._attention = attention self._decoder_cell = nn.GRUCell(self._embedding.get_output_dim() + self._attention.get_output_dim(), self._decoder_dim) self._linear = nn.Linear(self._decoder_dim, self._vocab_size) @overrides def forward(self, x: torch.Tensor, h: torch.Tensor, predicted_indices: torch.Tensor, sum_attention_weights: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]: # Shape: (batch_size, embedding_dim) embedding = self._embedding(predicted_indices).float().view(-1, self._embedding_dim) # Shape: (batch_size, encoder_dim) (batch_size, h * w, 1) (batch_size, h * w) attention, attention_weights, sum_attention_weights = self._attention(x, h, sum_attention_weights) ## Change to not use teacher forcing all the time # Shape: (batch_size, decoder_dim) (batch_size, decoder_dim) h = self._decoder_cell(torch.cat([attention, embedding], dim=1), h) # Get output predictions (one per character in vocab) # Shape: (batch_size, vocab_size) preds = self._linear(h) return h, preds, attention_weights, sum_attention_weights @overrides def get_output_dim(self) -> int: return self._vocab_size @overrides def get_input_dim(self) -> int: return self._decoder_dim @CaptioningDecoder.register('multiscale') class MultiscaleDecoder(CaptioningDecoder): def __init__(self, vocab: Vocabulary, attention: CaptioningAttention, embedding_dim: int = 256, decoder_dim:int = 256): super(MultiscaleDecoder, self).__init__(vocab=vocab) self._vocab_size = self.vocab.get_vocab_size() self._embedding_dim = embedding_dim self._decoder_dim = decoder_dim self._embedding = Embedding(self._vocab_size, self._embedding_dim) self._dropout = nn.Dropout(0.1) # Output size of state cell must be decoder dim since state is transformed by the state cell self._state_cell = nn.GRUCell(self._embedding.get_output_dim(), self._decoder_dim) self._attention = attention self._decoder_cell = nn.GRUCell(self._attention.get_output_dim(), self._decoder_dim) self._linear = nn.Linear(self._decoder_dim, self._vocab_size) @overrides def forward(self, x: torch.Tensor, h: torch.Tensor, predicted_indices: torch.Tensor, sum_attention_weights_0: torch.Tensor, sum_attention_weights_1: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]: # Shape: (batch_size, embedding_dim) embedding = self._embedding(predicted_indices).float().view(-1, self._embedding_dim) embedding = self._dropout(embedding) # Shape: (batch_size, decoder_dim) h = self._state_cell(embedding, h) # Shape: (batch_size, encoder_dim) (batch_size, h * w, 1) attention, attention_weights, sum_attention_weights_0, sum_attention_weights_1 = self._attention(x, h, sum_attention_weights_0, sum_attention_weights_1) ## Change to not use teacher forcing all the time # Shape: (batch_size, decoder_dim) (batch_size, decoder_dim) h = self._decoder_cell(attention, h) # Get output predictions (one per character in vocab) # Shape: (batch_size, vocab_size) preds = self._linear(h) return h, preds, attention_weights, sum_attention_weights_0, sum_attention_weights_1 @overrides def get_output_dim(self) -> int: return self._vocab_size @overrides def get_input_dim(self) -> int: return self._decoder_dim

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null

0

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null

0

6

96ab5d1f5e7c7653545ff148f0a826eb8b00be7e

17,542

py

Python

rest_api/simple_supply_rest_api/database.py

celio-jpeg/bev

2a7473a93885ac91d2aa32048dd760d5976934b8

[ "Apache-2.0" ]

1

2020-10-27T15:28:40.000Z

rest_api/simple_supply_rest_api/database.py

celio-jpeg/bev

2a7473a93885ac91d2aa32048dd760d5976934b8

[ "Apache-2.0" ]

null

rest_api/simple_supply_rest_api/database.py

celio-jpeg/bev

2a7473a93885ac91d2aa32048dd760d5976934b8

[ "Apache-2.0" ]

null

import asyncio import logging import aiopg import psycopg2 from psycopg2.extras import RealDictCursor LATEST_BLOCK_NUM = """ SELECT max(block_num) FROM blocks """ LOGGER = logging.getLogger(__name__) class Database(object): """Manages connection to the postgres database and makes async queries """ def __init__(self, host, port, name, user, password, loop): self._dsn = 'dbname={} user={} password={} host={} port={}'.format( name, user, password, host, port) self._loop = loop self._conn = None async def connect(self, retries=5, initial_delay=1, backoff=2): """Initializes a connection to the database Args: retries (int): Number of times to retry the connection initial_delay (int): Number of seconds wait between reconnects backoff (int): Multiplies the delay after each retry """ LOGGER.info('Connecting to database') delay = initial_delay for attempt in range(retries): try: self._conn = await aiopg.connect( dsn=self._dsn, loop=self._loop, echo=True) LOGGER.info('Successfully connected to database') return except psycopg2.OperationalError: LOGGER.debug( 'Connection failed.' ' Retrying connection (%s retries remaining)', retries - attempt) await asyncio.sleep(delay) delay *= backoff self._conn = await aiopg.connect( dsn=self._dsn, loop=self._loop, echo=True) LOGGER.info('Successfully connected to database') def disconnect(self): """Closes connection to the database """ self._conn.close() async def fetch_current_elections_resources(self, voter_id, timestamp): fetch_elections = """ SELECT e.*,v.name AS "admin_name",(SELECT vote_id FROM votes WHERE voter_id='{0}' AND election_id=e.election_id LIMIT 1) IS NOT NULL AS "voted" FROM elections e JOIN voters v ON e.admin_id = v.voter_id AND election_id IN (SELECT election_id FROM poll_registrations WHERE voter_id='{0}' AND status='1' AND ({2}) >= start_block_num AND ({2}) < end_block_num) AND start_timestamp <= {1} AND end_timestamp >= {1} AND e.status = '1' AND ({2}) >= e.start_block_num AND ({2}) < e.end_block_num ORDER BY start_timestamp DESC; """.format(voter_id, timestamp, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch_elections) return await cursor.fetchall() async def fetch_past_elections_resources(self, voter_id, timestamp): fetch_elections = """ SELECT e.*,v.name AS "admin_name",(SELECT vote_id FROM votes WHERE voter_id='{0}' AND election_id=e.election_id LIMIT 1) IS NOT NULL AS "voted" FROM elections e JOIN voters v ON e.admin_id = v.voter_id AND election_id IN (SELECT election_id FROM poll_registrations WHERE voter_id='{0}' AND status='1' AND ({2}) >= start_block_num AND ({2}) < end_block_num) AND end_timestamp < {1} AND e.status = '1' AND ({2}) >= e.start_block_num AND ({2}) < e.end_block_num ORDER BY start_timestamp DESC; """.format(voter_id, timestamp, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch_elections) return await cursor.fetchall() async def fetch_public_elections_resources(self, timestamp): fetch_elections = """ SELECT * FROM elections WHERE start_timestamp <= {0} AND end_timestamp >= {0} AND status = '1' AND results_permission = 'PUBLIC' AND ({1}) >= start_block_num AND ({1}) < end_block_num ORDER BY start_timestamp DESC; """.format(timestamp, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch_elections) return await cursor.fetchall() async def fetch_public_past_elections_resources(self, voter_id, timestamp): fetch_elections = """ SELECT e.*,v.name AS "admin_name",(SELECT vote_id FROM votes WHERE voter_id='{0}' AND election_id=e.election_id LIMIT 1) IS NOT NULL AS "voted" FROM elections e JOIN voters v ON e.admin_id = v.voter_id WHERE e.results_permission = 'PUBLIC' AND e.status = '1' AND e.end_timestamp < {1} AND ({2}) >= e.start_block_num AND ({2}) < e.end_block_num ORDER BY start_timestamp DESC; """.format(voter_id, timestamp, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch_elections) return await cursor.fetchall() async def fetch_admin_elections_resources(self, admin_id): fetch_elections = """ SELECT * FROM elections WHERE admin_id = '{0}' AND ({1}) >= start_block_num AND ({1}) < end_block_num ORDER BY start_timestamp DESC; """.format(admin_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch_elections) return await cursor.fetchall() async def fetch_admins_resources(self): fetch = """ SELECT voter_id, name, type FROM voters WHERE ({0}) >= start_block_num AND ({0}) < end_block_num AND type = 'ADMIN' OR type = 'SUPERADMIN' ORDER BY type DESC; """.format(LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchall() async def fetch_voters_resources(self, voter_id=None): fetch = """ SELECT voter_id FROM voters WHERE type = 'VOTER' AND voter_id LIKE '%{0}%' AND ({1}) >= start_block_num AND ({1}) < end_block_num ORDER BY type DESC; """.format(voter_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchall() async def insert_voting_option_num_vote_resource(self, voting_option_id, name, election_id): num_votes = 0 insert = """ INSERT INTO count_votes ( voting_option_id, name, election_id, num_votes) VALUES ('{}', '{}', '{}', '{}') """.format( voting_option_id, name, election_id, num_votes) async with self._conn.cursor() as cursor: await cursor.execute(insert) self._conn.commit() async def update_voting_option_num_vote_resource(self, voting_option_id, num_votes): update = """ UPDATE count_votes SET num_votes = '{1}' WHERE voting_option_id = '{0}' """.format( voting_option_id, num_votes) async with self._conn.cursor() as cursor: await cursor.execute(update) self._conn.commit() async def fetch_auth_resource(self, public_key=None): fetch = """ SELECT * FROM auth WHERE public_key='{}' """.format(public_key) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def fetch_voter_resource(self, voter_id=None, public_key=None): fetch = """ SELECT * FROM voters WHERE """ + ("""voter_id""" if voter_id else """public_key""") + """='{0}' AND ({1}) >= start_block_num AND ({1}) < end_block_num; """.format(voter_id if voter_id else public_key, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def is_voter_created(self, voter_id): fetch = """ SELECT voter_id FROM voters WHERE voter_id = '{0}'; """.format(voter_id) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def is_superadmin_created(self): fetch = """ SELECT voter_id FROM voters WHERE type='SUPERADMIN' """ async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def fetch_election_with_can_vote_resource(self, voter_id=None, election_id=None): fetch = """ SELECT e.*, v.name AS "admin_name", (SELECT voter_id FROM poll_registrations WHERE voter_id='{0}' AND election_id='{1}' AND status='1' LIMIT 1) IS NOT NULL AS "can_vote", (SELECT vote_id FROM votes WHERE voter_id='{0}' AND election_id='{1}' LIMIT 1) IS NOT NULL AS "voted" FROM elections e JOIN voters v ON e.admin_id = v.voter_id WHERE election_id='{1}' AND e.status = '1' AND ({2}) >= e.start_block_num AND ({2}) < e.end_block_num; """.format(voter_id, election_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def fetch_election_resource(self, election_id=None): fetch = """ SELECT e.*, v.name AS "admin_name" FROM elections e JOIN voters v ON e.admin_id = v.voter_id WHERE election_id='{0}' AND ({1}) >= e.start_block_num AND ({1}) < e.end_block_num; """.format(election_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def fetch_election_with_can_vote_resource_admin(self, voter_id=None, election_id=None): fetch = """ SELECT e.*, v.name AS "admin_name", (SELECT voter_id FROM poll_registrations WHERE voter_id='{0}' AND election_id='{1}' AND status='1' LIMIT 1) IS NOT NULL AS "can_vote", (SELECT vote_id FROM votes WHERE voter_id='{0}' AND election_id='{1}' LIMIT 1) IS NOT NULL AS "voted" FROM elections e JOIN voters v ON e.admin_id = v.voter_id WHERE election_id='{1}' AND ({2}) >= e.start_block_num AND ({2}) < e.end_block_num; """.format(voter_id, election_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def fetch_number_of_votes(self, election_id=None): fetch = """ SELECT * FROM count_votes WHERE election_id='{0}'; """.format(election_id) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchall() async def fetch_poll_book(self, election_id=None): fetch = """ SELECT * FROM poll_registrations WHERE election_id='{0}' AND status='1' AND ({1}) >= start_block_num AND ({1}) < end_block_num; """.format(election_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchall() async def fetch_poll_book_registration(self, election_id=None, voter_id=None): fetch = """ SELECT * FROM poll_registrations WHERE election_id='{0}' AND voter_id='{1}' AND status='1' AND ({2}) >= start_block_num AND ({2}) < end_block_num; """.format(election_id, voter_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def count_poll_book(self, election_id=None): fetch = """ SELECT COUNT(*) FROM poll_registrations WHERE election_id='{0}' AND status='1' AND ({1}) >= start_block_num AND ({1}) < end_block_num; """.format(election_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def fetch_voting_option_resource(self, voting_option_id=None): fetch = """ SELECT * FROM voting_options WHERE voting_option_id='{0}' AND status='1' AND ({1}) >= start_block_num AND ({1}) < end_block_num; """.format(voting_option_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def fetch_voting_option_num_vote_resource(self, voting_option_id=None): fetch = """ SELECT * FROM count_votes WHERE voting_option_id='{0}'; """.format(voting_option_id) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def fetch_election_voting_options_resource(self, election_id=None): fetch = """ SELECT * FROM voting_options WHERE election_id='{0}' AND status='1' AND ({1}) >= start_block_num AND ({1}) < end_block_num; """.format(election_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchall() async def fetch_vote_resource(self, vote_id=None): fetch = """ SELECT * FROM votes WHERE timestamp=(SELECT MAX(timestamp) FROM votes WHERE vote_id='{0}') AND ({1}) >= start_block_num AND ({1}) < end_block_num; """.format(vote_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def fetch_my_vote__election_resource(self, voter_id=None, election_id=None): fetch = """ SELECT * FROM votes WHERE timestamp=(SELECT MAX(timestamp) FROM votes WHERE voter_id='{0}' AND election_id='{1}') AND ({2}) >= start_block_num AND ({2}) < end_block_num; """.format(voter_id, election_id, LATEST_BLOCK_NUM) async with self._conn.cursor(cursor_factory=RealDictCursor) as cursor: await cursor.execute(fetch) return await cursor.fetchone() async def create_auth_entry(self, public_key, encrypted_private_key, hashed_password): insert = """ INSERT INTO auth ( public_key, encrypted_private_key, hashed_password ) VALUES ('{}', '{}', '{}'); """.format( public_key, encrypted_private_key.hex(), hashed_password.hex()) async with self._conn.cursor() as cursor: await cursor.execute(insert) self._conn.commit()

39.958998

117

0.554669

1,968

17,542

4.702744

0.082317

0.051864

0.036521

0.047758

0.823555

0.796542

0.781199

0.763803

0.724581

0.696164

0

0.009434

0.353437

17,542

438

118

40.050228

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0.006043

0

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false

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0.088889

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null

0

1

0

null

0

6

7365f8520f73fbdd517b7991acc3da9b4d316501

24

py

Python

UIC/models/__init__.py

hikvisionresearch/Unsupervised-Image-Classification

0db8f00ece36ef0ee491e082e21b47fedf05c30d

[ "MIT" ]

30

2021-05-11T09:13:52.000Z

2022-03-16T10:55:45.000Z

UIC/models/__init__.py

hikvisionresearch/Unsupervised-Image-Classification

0db8f00ece36ef0ee491e082e21b47fedf05c30d

[ "MIT" ]

1

2021-08-22T15:28:09.000Z

UIC/models/__init__.py

hikvisionresearch/Unsupervised-Image-Classification

0db8f00ece36ef0ee491e082e21b47fedf05c30d

[ "MIT" ]

2

2021-05-16T04:09:35.000Z

2021-08-14T11:55:43.000Z

from .resnet50 import *

12

23

0.75

3

24

6

1

0

0.1

0.166667

24

1

24

0.8

0

1

0

true

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null

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1

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null

0

1

0

1

0

1

0

6

73b33908dac28882d10968660cd6539b91c629b4

8,820

py

Python

dfirtrack_config/tests/artifact/test_artifact_exporter_spreadsheet_xls_config_forms.py

stuhli/dfirtrack

9260c91e4367b36d4cb1ae7efe4e2d2452f58e6e

[ "Apache-2.0" ]

273

2018-04-18T22:09:15.000Z

2021-06-04T09:15:48.000Z

dfirtrack_config/tests/artifact/test_artifact_exporter_spreadsheet_xls_config_forms.py

stuhli/dfirtrack

9260c91e4367b36d4cb1ae7efe4e2d2452f58e6e

[ "Apache-2.0" ]

75

2018-08-31T11:05:37.000Z

2021-06-08T14:15:07.000Z

dfirtrack_config/tests/artifact/test_artifact_exporter_spreadsheet_xls_config_forms.py

stuhli/dfirtrack

9260c91e4367b36d4cb1ae7efe4e2d2452f58e6e

[ "Apache-2.0" ]

61

2018-11-12T22:55:48.000Z

2021-06-06T15:16:16.000Z

from django.test import TestCase from dfirtrack_artifacts.models import Artifactstatus from dfirtrack_config.forms import ArtifactExporterSpreadsheetXlsConfigForm class ArtifactExporterSpreadsheetXlsConfigFormTestCase(TestCase): """artifact exporter spreadsheet XLS config form tests""" @classmethod def setUpTestData(cls): # create object Artifactstatus.objects.create( artifactstatus_name='artifactstatus_1', artifactstatus_slug='artifactstatus_1', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_choice_artifactstatus_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_choice_artifactstatus'].label, 'Export only artifacts with this artifactstatus', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_id_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_id'].label, 'Export artifact ID' ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_system_id_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_system_id'].label, 'Export system ID' ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_system_name_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_system_name'].label, 'Export system name' ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifactstatus_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifactstatus'].label, 'Export artifactstatus', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifactpriority_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifactpriority'].label, 'Export artifactpriority', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifacttype_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifacttype'].label, 'Export artifacttype' ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_source_path_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_source_path'].label, 'Export source path', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_storage_path_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_storage_path'].label, 'Export storage path', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_note_internal_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_note_internal'].label, 'Export internal note', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_note_external_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_note_external'].label, 'Export external note', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_note_analysisresult_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_note_analysisresult'].label, 'Export analysis result', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_md5_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_md5'].label, 'Export MD5' ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_sha1_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_sha1'].label, 'Export SHA1' ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_sha256_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_sha256'].label, 'Export SHA256' ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_create_time_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_create_time'].label, 'Export create time', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_artifact_modify_time_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_artifact_modify_time'].label, 'Export modify time', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_worksheet_artifactstatus_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_worksheet_artifactstatus'].label, 'Export worksheet to explain artifactstatus', ) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_worksheet_artifacttype_form_label( self, ): """test form label""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm() # compare self.assertEqual( form.fields['artifactlist_xls_worksheet_artifacttype'].label, 'Export worksheet to explain artifacttype', ) def test_artifact_exporter_spreadsheet_xls_config_form_empty(self): """test minimum form requirements / INVALID""" # get object form = ArtifactExporterSpreadsheetXlsConfigForm(data={}) # compare self.assertFalse(form.is_valid()) def test_artifact_exporter_spreadsheet_xls_config_artifactlist_xls_choice_artifactstatus_form_filled( self, ): """test minimum form requirements / VALID""" # get object artifactstatus_id = Artifactstatus.objects.get( artifactstatus_name='artifactstatus_1' ) # get object form = ArtifactExporterSpreadsheetXlsConfigForm( data={ 'artifactlist_xls_choice_artifactstatus': [ artifactstatus_id, ], } ) # compare self.assertTrue(form.is_valid())

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0.151163

0

null

0

1

0

null

0

6

73bb28bf3c556576785e72ce8701f0dd36e35546

7,817

py

Python

model/config.py

nachiket273/efficientnetv2

fdcbcf48ad84d4b16c0edc18f55a27ee5bafd2de

[ "MIT" ]

1

2021-12-01T20:12:49.000Z

model/config.py

nachiket273/efficientnetv2

fdcbcf48ad84d4b16c0edc18f55a27ee5bafd2de

[ "MIT" ]

null

model/config.py

nachiket273/efficientnetv2

fdcbcf48ad84d4b16c0edc18f55a27ee5bafd2de

[ "MIT" ]

null

CFG = { 'in_ch': 3, 'out_ch': 24, 'kernel_size': 3, 'stride': 2, 'width_mult': 1, 'divisor': 8, 'actn_layer': None, 'layers': [ {'channels': 24, 'expansion': 1, 'kernel_size': 3, 'stride': 1, 'nums': 2, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 48, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 4, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 64, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 4, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 128, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 6, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 160, 'expansion': 6, 'kernel_size': 3, 'stride': 1, 'nums': 9, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 256, 'expansion': 6, 'kernel_size': 3, 'stride': 2, 'nums': 15, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True} ] } def get_default_cfg(): return CFG def get_cfg(name='efficientnetv2_s'): name = name.lower() if name == 'efficientnetv2_s': cfg = get_default_cfg() elif name == 'efficientnetv2_m': cfg = get_default_cfg() cfg['layers'] = [ {'channels': 24, 'expansion': 1, 'kernel_size': 3, 'stride': 1, 'nums': 3, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 48, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 5, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 80, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 5, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 160, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 7, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 176, 'expansion': 6, 'kernel_size': 3, 'stride': 1, 'nums': 14, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 304, 'expansion': 6, 'kernel_size': 3, 'stride': 2, 'nums': 18, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 512, 'expansion': 6, 'kernel_size': 3, 'stride': 1, 'nums': 5, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True} ] elif name == 'efficientnetv2_l': cfg = get_default_cfg() cfg['layers'] = [ {'channels': 32, 'expansion': 1, 'kernel_size': 3, 'stride': 1, 'nums': 4, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 64, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 7, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 96, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 7, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 192, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 10, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 224, 'expansion': 6, 'kernel_size': 3, 'stride': 1, 'nums': 19, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 384, 'expansion': 6, 'kernel_size': 3, 'stride': 2, 'nums': 25, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 640, 'expansion': 6, 'kernel_size': 3, 'stride': 1, 'nums': 7, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True} ] elif name == 'efficientnetv2_xl': cfg = get_default_cfg() cfg['layers'] = [ {'channels': 32, 'expansion': 1, 'kernel_size': 3, 'stride': 1, 'nums': 4, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 64, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 8, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 96, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 8, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': True, 'use_se': False}, {'channels': 192, 'expansion': 4, 'kernel_size': 3, 'stride': 2, 'nums': 16, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 256, 'expansion': 6, 'kernel_size': 3, 'stride': 1, 'nums': 24, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 512, 'expansion': 6, 'kernel_size': 3, 'stride': 2, 'nums': 32, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True}, {'channels': 640, 'expansion': 6, 'kernel_size': 3, 'stride': 1, 'nums': 8, 'norm_layer': None, 'dropout_ratio': 0.1, 'dc_ratio': 0.2, 'reduction_ratio': 0.25, 'actn_layer': None, 'fused': False, 'use_se': True} ] else: raise ValueError("No pretrained config available" " for name {}".format(name)) return cfg

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0.028369

0

null

0

1

0

null

0

6

73ea795b18c880afbf438b724b855276692a0da1

2,762

py

Python

account/migrations/0001_initial.py

JishnuTU/D-M-Intelligence-S

aa094bc8a4d20fddd9c6a043559833226f46044d

[ "MIT" ]

4

2019-10-17T00:27:09.000Z

2021-04-09T05:17:19.000Z

account/migrations/0001_initial.py

Jishnu04/D-M-Intelligence-S

aa094bc8a4d20fddd9c6a043559833226f46044d

[ "MIT" ]

1

2020-07-09T18:39:16.000Z

2020-09-21T11:30:17.000Z

account/migrations/0001_initial.py

Jishnu04/D-M-Intelligence-S

aa094bc8a4d20fddd9c6a043559833226f46044d

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.10.5 on 2017-02-12 08:11 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('home', '0001_initial'), ] operations = [ migrations.CreateModel( name='Accomadation', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=70)), ('usertype', models.CharField(max_length=50)), ('capacity', models.IntegerField()), ('status', models.BooleanField(default=False)), ('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='updates_capacity', to='home.User')), ], ), migrations.CreateModel( name='Hospital', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=70)), ('usertype', models.CharField(max_length=50)), ('canoccupy', models.IntegerField()), ('status', models.BooleanField(default=False)), ('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='updates_occupy', to='home.User')), ], ), migrations.CreateModel( name='Pronearea', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=70)), ('usertype', models.CharField(max_length=50)), ('population', models.IntegerField()), ('status', models.BooleanField(default=False)), ('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='updates_population', to='home.User')), ], ), migrations.CreateModel( name='Volunteer', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=70)), ('usertype', models.CharField(max_length=50)), ('humanaid', models.IntegerField()), ('status', models.BooleanField(default=False)), ('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='updates_humanaid', to='home.User')), ], ), ]

43.84127

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0.580014

266

2,762

5.879699

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0.076726

0.092072

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0.77046

0.703325

0

0.018417

0.272629

2,762

62

144

44.548387

0.76008

0.02462

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0

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0

false

0

0.055556

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null

0

1

0

1

0

null

0

6

fbb3965ef572cb99f9fe6ec71c63a225cc16c6f0

89

py

Python

tests/data/modules/test_1920/plugins/__init__.py

inmanta/inmanta-core

ae2153d57f124d00ad1b58e6d4bc6818364be4a8

[ "Apache-2.0" ]

6

2021-03-09T10:24:02.000Z

2022-01-16T03:52:11.000Z

tests/data/modules/test_1920/plugins/__init__.py

inmanta/inmanta-core

ae2153d57f124d00ad1b58e6d4bc6818364be4a8

[ "Apache-2.0" ]

1,319

2020-12-18T08:52:29.000Z

2022-03-31T18:17:32.000Z

tests/data/modules/test_1920/plugins/__init__.py

inmanta/inmanta-core

ae2153d57f124d00ad1b58e6d4bc6818364be4a8

[ "Apache-2.0" ]

4

2021-03-03T15:36:50.000Z

2022-03-11T11:41:51.000Z

from inmanta.plugins import plugin @plugin def some_name() -> "bool": return False

12.714286

34

0.707865

12

89

5.166667

0.916667

0

0.191011

89

6

35

14.833333

0.861111

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0.044944

0

1

0.25

true

0

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0

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0

null

0

1

0

null

0

1

0

1

0

6

837668f001ebb2a8dd37fdad6281fd12594ce5f6

45

py

Python

enthought/pyface/constant.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/pyface/constant.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/pyface/constant.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from pyface.constant import *

15

29

0.777778

6

45

5.833333

1

0

0.155556

45

2

30

22.5

0.921053

0.266667

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

8388c23bf816498c9fb30f19eadf0721ff38c0b3

135

py

Python

roman/ur/__init__.py

drMJ/roman

9650e73ec6fbb2d8044aa1bbf89fd671843ea54e

[ "MIT" ]

14

2020-04-03T03:48:35.000Z

2021-11-08T11:17:41.000Z

roman/ur/__init__.py

drMJ/roman

9650e73ec6fbb2d8044aa1bbf89fd671843ea54e

[ "MIT" ]

5

2020-04-17T21:59:35.000Z

2022-01-21T23:21:45.000Z

roman/ur/__init__.py

drMJ/roman

9650e73ec6fbb2d8044aa1bbf89fd671843ea54e

[ "MIT" ]

10

2020-04-16T15:44:25.000Z

2021-11-10T08:22:52.000Z

from .realtime.constants import * from .arm import * from .connection import * from .sim_connection import * from .controllers import *

27

33

0.777778

17

135

6.117647

0.470588

0.384615

0

0.140741

135

5

34

27

0.896552

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

83893a090af1a7cb63f45b4de726e633bc2ebbe7

557

py

Python

service/classification/dataset/transform.py

Navan0/poc-of-hm

9b14325908445462721d7bed64e09b6c5d39f694

[ "Apache-2.0" ]

null

service/classification/dataset/transform.py

Navan0/poc-of-hm

9b14325908445462721d7bed64e09b6c5d39f694

[ "Apache-2.0" ]

null

service/classification/dataset/transform.py

Navan0/poc-of-hm

9b14325908445462721d7bed64e09b6c5d39f694

[ "Apache-2.0" ]

null

from torchvision import transforms xception_default_data_transforms = { 'train': transforms.Compose([ transforms.Resize((299, 299)), transforms.ToTensor(), transforms.Normalize([0.5]*3, [0.5]*3) ]), 'val': transforms.Compose([ transforms.Resize((299, 299)), transforms.ToTensor(), transforms.Normalize([0.5] * 3, [0.5] * 3) ]), 'test': transforms.Compose([ transforms.Resize((299, 299)), transforms.ToTensor(), transforms.Normalize([0.5] * 3, [0.5] * 3) ]), }

27.85

50

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557

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0.056604

0.311321

0.773585

0

0.085714

0.245961

557

19

51

29.315789

0.671429

0

0.666667

0

0.021544

0

1

0

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Python

src/core/sobol_gen/utility.py

JustinRuan/Pathological-images

478f0b568068e591e282e9566786e683ec39a108

[ "MIT" ]

2

2022-01-17T12:04:02.000Z

2022-03-08T21:59:39.000Z

sobol_gen/utility.py

elderfd/sobol_gen

25bbfae734239bef4304cb1b0b32662b517d1b56

[ "MIT" ]

null

sobol_gen/utility.py

elderfd/sobol_gen

25bbfae734239bef4304cb1b0b32662b517d1b56

[ "MIT" ]

1

2020-03-08T09:00:43.000Z

import numpy def high_bit_pos(i): """Converts a positive integer to base 2 and returns the position of the high order bit. Keyword arguments: i -- Integer to find high order bit within """ if i < 0: raise RuntimeError("Supplied value {0} was not positive".format(i)) i = numpy.floor(i) bit = 0 while i > 0: bit += 1 i //= 2 return bit def low_bit_pos(i): """Converts a positive integer to base 2 and returns the position of the low order bit. Keyword arguments: i -- Integer to find high order bit within """ if i < 0: raise RuntimeError("Supplied value {0} was not positive".format(i)) i = numpy.floor(i) bit = 1 while i != 2 * (i // 2): bit += 1 i //= 2 return bit

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py

Python

veripb/__init__.py

StephanGocht/refpy

e244dc5c21ebb2887c428b3b3ada003528afa27a

[ "MIT" ]

5

2020-03-03T16:16:56.000Z

2022-01-31T09:23:36.000Z

veripb/__init__.py

StephanGocht/VeriPB

a6b4314be574f09af0736600583dc714a469c0d7

[ "MIT" ]

25

2019-11-19T17:23:21.000Z

2022-02-23T16:51:46.000Z

veripb/__init__.py

StephanGocht/refpy

e244dc5c21ebb2887c428b3b3ada003528afa27a

[ "MIT" ]

1

2019-07-02T12:19:15.000Z

from veripb.exceptions import ParseError, InvalidProof from veripb.utils import run,runUI,run_cmd_main

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py

Python

__init__.py

yswd82/pymoi

73d3ad221bbd431916ff94ee1bbf64b75ee3bbc7

[ "MIT" ]

1

2021-08-15T01:26:02.000Z

__init__.py

yswd82/pymoi

73d3ad221bbd431916ff94ee1bbf64b75ee3bbc7

[ "MIT" ]

4

2021-08-10T06:06:51.000Z

2021-08-17T09:38:10.000Z

__init__.py

yswd82/pymoi

73d3ad221bbd431916ff94ee1bbf64b75ee3bbc7

[ "MIT" ]

null

from pymoi import core, reader, util

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83c15c4c25e6d5e5a9d3653a755a44f2dc84b667

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py

Python

tests/unit/gapic/transcoder_v1beta1/test_transcoder_service.py

renovate-bot/python-video-transcoder-1

e9c1c229fe88d200d0f60314814078e79e3f1524

[ "Apache-2.0" ]

5

2021-03-05T22:36:04.000Z

2022-02-01T09:58:04.000Z

tests/unit/gapic/transcoder_v1beta1/test_transcoder_service.py

renovate-bot/python-video-transcoder-1

e9c1c229fe88d200d0f60314814078e79e3f1524

[ "Apache-2.0" ]

51

2020-08-24T15:43:20.000Z

2022-03-07T16:43:36.000Z

tests/unit/gapic/transcoder_v1beta1/test_transcoder_service.py

renovate-bot/python-video-transcoder-1

e9c1c229fe88d200d0f60314814078e79e3f1524

[ "Apache-2.0" ]

8

2020-08-24T15:39:52.000Z

2022-02-24T17:43:24.000Z

# -*- coding: utf-8 -*- # Copyright 2020 Google LLC # # 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 os import mock import packaging.version import grpc from grpc.experimental import aio import math import pytest from proto.marshal.rules.dates import DurationRule, TimestampRule from google.api_core import client_options from google.api_core import exceptions as core_exceptions from google.api_core import gapic_v1 from google.api_core import grpc_helpers from google.api_core import grpc_helpers_async from google.api_core import path_template from google.auth import credentials as ga_credentials from google.auth.exceptions import MutualTLSChannelError from google.cloud.video.transcoder_v1beta1.services.transcoder_service import ( TranscoderServiceAsyncClient, ) from google.cloud.video.transcoder_v1beta1.services.transcoder_service import ( TranscoderServiceClient, ) from google.cloud.video.transcoder_v1beta1.services.transcoder_service import pagers from google.cloud.video.transcoder_v1beta1.services.transcoder_service import transports from google.cloud.video.transcoder_v1beta1.services.transcoder_service.transports.base import ( _GOOGLE_AUTH_VERSION, ) from google.cloud.video.transcoder_v1beta1.types import resources from google.cloud.video.transcoder_v1beta1.types import services from google.oauth2 import service_account from google.protobuf import duration_pb2 # type: ignore from google.protobuf import timestamp_pb2 # type: ignore import google.auth # TODO(busunkim): Once google-auth >= 1.25.0 is required transitively # through google-api-core: # - Delete the auth "less than" test cases # - Delete these pytest markers (Make the "greater than or equal to" tests the default). requires_google_auth_lt_1_25_0 = pytest.mark.skipif( packaging.version.parse(_GOOGLE_AUTH_VERSION) >= packaging.version.parse("1.25.0"), reason="This test requires google-auth < 1.25.0", ) requires_google_auth_gte_1_25_0 = pytest.mark.skipif( packaging.version.parse(_GOOGLE_AUTH_VERSION) < packaging.version.parse("1.25.0"), reason="This test requires google-auth >= 1.25.0", ) def client_cert_source_callback(): return b"cert bytes", b"key bytes" # If default endpoint is localhost, then default mtls endpoint will be the same. # This method modifies the default endpoint so the client can produce a different # mtls endpoint for endpoint testing purposes. def modify_default_endpoint(client): return ( "foo.googleapis.com" if ("localhost" in client.DEFAULT_ENDPOINT) else client.DEFAULT_ENDPOINT ) def test__get_default_mtls_endpoint(): api_endpoint = "example.googleapis.com" api_mtls_endpoint = "example.mtls.googleapis.com" sandbox_endpoint = "example.sandbox.googleapis.com" sandbox_mtls_endpoint = "example.mtls.sandbox.googleapis.com" non_googleapi = "api.example.com" assert TranscoderServiceClient._get_default_mtls_endpoint(None) is None assert ( TranscoderServiceClient._get_default_mtls_endpoint(api_endpoint) == api_mtls_endpoint ) assert ( TranscoderServiceClient._get_default_mtls_endpoint(api_mtls_endpoint) == api_mtls_endpoint ) assert ( TranscoderServiceClient._get_default_mtls_endpoint(sandbox_endpoint) == sandbox_mtls_endpoint ) assert ( TranscoderServiceClient._get_default_mtls_endpoint(sandbox_mtls_endpoint) == sandbox_mtls_endpoint ) assert ( TranscoderServiceClient._get_default_mtls_endpoint(non_googleapi) == non_googleapi ) @pytest.mark.parametrize( "client_class", [TranscoderServiceClient, TranscoderServiceAsyncClient,] ) def test_transcoder_service_client_from_service_account_info(client_class): creds = ga_credentials.AnonymousCredentials() with mock.patch.object( service_account.Credentials, "from_service_account_info" ) as factory: factory.return_value = creds info = {"valid": True} client = client_class.from_service_account_info(info) assert client.transport._credentials == creds assert isinstance(client, client_class) assert client.transport._host == "transcoder.googleapis.com:443" @pytest.mark.parametrize( "transport_class,transport_name", [ (transports.TranscoderServiceGrpcTransport, "grpc"), (transports.TranscoderServiceGrpcAsyncIOTransport, "grpc_asyncio"), ], ) def test_transcoder_service_client_service_account_always_use_jwt( transport_class, transport_name ): with mock.patch.object( service_account.Credentials, "with_always_use_jwt_access", create=True ) as use_jwt: creds = service_account.Credentials(None, None, None) transport = transport_class(credentials=creds, always_use_jwt_access=True) use_jwt.assert_called_once_with(True) with mock.patch.object( service_account.Credentials, "with_always_use_jwt_access", create=True ) as use_jwt: creds = service_account.Credentials(None, None, None) transport = transport_class(credentials=creds, always_use_jwt_access=False) use_jwt.assert_not_called() @pytest.mark.parametrize( "client_class", [TranscoderServiceClient, TranscoderServiceAsyncClient,] ) def test_transcoder_service_client_from_service_account_file(client_class): creds = ga_credentials.AnonymousCredentials() with mock.patch.object( service_account.Credentials, "from_service_account_file" ) as factory: factory.return_value = creds client = client_class.from_service_account_file("dummy/file/path.json") assert client.transport._credentials == creds assert isinstance(client, client_class) client = client_class.from_service_account_json("dummy/file/path.json") assert client.transport._credentials == creds assert isinstance(client, client_class) assert client.transport._host == "transcoder.googleapis.com:443" def test_transcoder_service_client_get_transport_class(): transport = TranscoderServiceClient.get_transport_class() available_transports = [ transports.TranscoderServiceGrpcTransport, ] assert transport in available_transports transport = TranscoderServiceClient.get_transport_class("grpc") assert transport == transports.TranscoderServiceGrpcTransport @pytest.mark.parametrize( "client_class,transport_class,transport_name", [ (TranscoderServiceClient, transports.TranscoderServiceGrpcTransport, "grpc"), ( TranscoderServiceAsyncClient, transports.TranscoderServiceGrpcAsyncIOTransport, "grpc_asyncio", ), ], ) @mock.patch.object( TranscoderServiceClient, "DEFAULT_ENDPOINT", modify_default_endpoint(TranscoderServiceClient), ) @mock.patch.object( TranscoderServiceAsyncClient, "DEFAULT_ENDPOINT", modify_default_endpoint(TranscoderServiceAsyncClient), ) def test_transcoder_service_client_client_options( client_class, transport_class, transport_name ): # Check that if channel is provided we won't create a new one. with mock.patch.object(TranscoderServiceClient, "get_transport_class") as gtc: transport = transport_class(credentials=ga_credentials.AnonymousCredentials()) client = client_class(transport=transport) gtc.assert_not_called() # Check that if channel is provided via str we will create a new one. with mock.patch.object(TranscoderServiceClient, "get_transport_class") as gtc: client = client_class(transport=transport_name) gtc.assert_called() # Check the case api_endpoint is provided. options = client_options.ClientOptions(api_endpoint="squid.clam.whelk") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(client_options=options) patched.assert_called_once_with( credentials=None, credentials_file=None, host="squid.clam.whelk", scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is # "never". with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "never"}): with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class() patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT is # "always". with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "always"}): with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class() patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_MTLS_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case api_endpoint is not provided and GOOGLE_API_USE_MTLS_ENDPOINT has # unsupported value. with mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "Unsupported"}): with pytest.raises(MutualTLSChannelError): client = client_class() # Check the case GOOGLE_API_USE_CLIENT_CERTIFICATE has unsupported value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": "Unsupported"} ): with pytest.raises(ValueError): client = client_class() # Check the case quota_project_id is provided options = client_options.ClientOptions(quota_project_id="octopus") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(client_options=options) patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id="octopus", client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) @pytest.mark.parametrize( "client_class,transport_class,transport_name,use_client_cert_env", [ ( TranscoderServiceClient, transports.TranscoderServiceGrpcTransport, "grpc", "true", ), ( TranscoderServiceAsyncClient, transports.TranscoderServiceGrpcAsyncIOTransport, "grpc_asyncio", "true", ), ( TranscoderServiceClient, transports.TranscoderServiceGrpcTransport, "grpc", "false", ), ( TranscoderServiceAsyncClient, transports.TranscoderServiceGrpcAsyncIOTransport, "grpc_asyncio", "false", ), ], ) @mock.patch.object( TranscoderServiceClient, "DEFAULT_ENDPOINT", modify_default_endpoint(TranscoderServiceClient), ) @mock.patch.object( TranscoderServiceAsyncClient, "DEFAULT_ENDPOINT", modify_default_endpoint(TranscoderServiceAsyncClient), ) @mock.patch.dict(os.environ, {"GOOGLE_API_USE_MTLS_ENDPOINT": "auto"}) def test_transcoder_service_client_mtls_env_auto( client_class, transport_class, transport_name, use_client_cert_env ): # This tests the endpoint autoswitch behavior. Endpoint is autoswitched to the default # mtls endpoint, if GOOGLE_API_USE_CLIENT_CERTIFICATE is "true" and client cert exists. # Check the case client_cert_source is provided. Whether client cert is used depends on # GOOGLE_API_USE_CLIENT_CERTIFICATE value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env} ): options = client_options.ClientOptions( client_cert_source=client_cert_source_callback ) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(client_options=options) if use_client_cert_env == "false": expected_client_cert_source = None expected_host = client.DEFAULT_ENDPOINT else: expected_client_cert_source = client_cert_source_callback expected_host = client.DEFAULT_MTLS_ENDPOINT patched.assert_called_once_with( credentials=None, credentials_file=None, host=expected_host, scopes=None, client_cert_source_for_mtls=expected_client_cert_source, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case ADC client cert is provided. Whether client cert is used depends on # GOOGLE_API_USE_CLIENT_CERTIFICATE value. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env} ): with mock.patch.object(transport_class, "__init__") as patched: with mock.patch( "google.auth.transport.mtls.has_default_client_cert_source", return_value=True, ): with mock.patch( "google.auth.transport.mtls.default_client_cert_source", return_value=client_cert_source_callback, ): if use_client_cert_env == "false": expected_host = client.DEFAULT_ENDPOINT expected_client_cert_source = None else: expected_host = client.DEFAULT_MTLS_ENDPOINT expected_client_cert_source = client_cert_source_callback patched.return_value = None client = client_class() patched.assert_called_once_with( credentials=None, credentials_file=None, host=expected_host, scopes=None, client_cert_source_for_mtls=expected_client_cert_source, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) # Check the case client_cert_source and ADC client cert are not provided. with mock.patch.dict( os.environ, {"GOOGLE_API_USE_CLIENT_CERTIFICATE": use_client_cert_env} ): with mock.patch.object(transport_class, "__init__") as patched: with mock.patch( "google.auth.transport.mtls.has_default_client_cert_source", return_value=False, ): patched.return_value = None client = client_class() patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) @pytest.mark.parametrize( "client_class,transport_class,transport_name", [ (TranscoderServiceClient, transports.TranscoderServiceGrpcTransport, "grpc"), ( TranscoderServiceAsyncClient, transports.TranscoderServiceGrpcAsyncIOTransport, "grpc_asyncio", ), ], ) def test_transcoder_service_client_client_options_scopes( client_class, transport_class, transport_name ): # Check the case scopes are provided. options = client_options.ClientOptions(scopes=["1", "2"],) with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(client_options=options) patched.assert_called_once_with( credentials=None, credentials_file=None, host=client.DEFAULT_ENDPOINT, scopes=["1", "2"], client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) @pytest.mark.parametrize( "client_class,transport_class,transport_name", [ (TranscoderServiceClient, transports.TranscoderServiceGrpcTransport, "grpc"), ( TranscoderServiceAsyncClient, transports.TranscoderServiceGrpcAsyncIOTransport, "grpc_asyncio", ), ], ) def test_transcoder_service_client_client_options_credentials_file( client_class, transport_class, transport_name ): # Check the case credentials file is provided. options = client_options.ClientOptions(credentials_file="credentials.json") with mock.patch.object(transport_class, "__init__") as patched: patched.return_value = None client = client_class(client_options=options) patched.assert_called_once_with( credentials=None, credentials_file="credentials.json", host=client.DEFAULT_ENDPOINT, scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) def test_transcoder_service_client_client_options_from_dict(): with mock.patch( "google.cloud.video.transcoder_v1beta1.services.transcoder_service.transports.TranscoderServiceGrpcTransport.__init__" ) as grpc_transport: grpc_transport.return_value = None client = TranscoderServiceClient( client_options={"api_endpoint": "squid.clam.whelk"} ) grpc_transport.assert_called_once_with( credentials=None, credentials_file=None, host="squid.clam.whelk", scopes=None, client_cert_source_for_mtls=None, quota_project_id=None, client_info=transports.base.DEFAULT_CLIENT_INFO, always_use_jwt_access=True, ) def test_create_job(transport: str = "grpc", request_type=services.CreateJobRequest): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.create_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = resources.Job( name="name_value", input_uri="input_uri_value", output_uri="output_uri_value", priority=898, state=resources.Job.ProcessingState.PENDING, failure_reason="failure_reason_value", ttl_after_completion_days=2670, template_id="template_id_value", ) response = client.create_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == services.CreateJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, resources.Job) assert response.name == "name_value" assert response.input_uri == "input_uri_value" assert response.output_uri == "output_uri_value" assert response.priority == 898 assert response.state == resources.Job.ProcessingState.PENDING assert response.failure_reason == "failure_reason_value" assert response.ttl_after_completion_days == 2670 def test_create_job_from_dict(): test_create_job(request_type=dict) def test_create_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.create_job), "__call__") as call: client.create_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == services.CreateJobRequest() @pytest.mark.asyncio async def test_create_job_async( transport: str = "grpc_asyncio", request_type=services.CreateJobRequest ): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.create_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( resources.Job( name="name_value", input_uri="input_uri_value", output_uri="output_uri_value", priority=898, state=resources.Job.ProcessingState.PENDING, failure_reason="failure_reason_value", ttl_after_completion_days=2670, ) ) response = await client.create_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == services.CreateJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, resources.Job) assert response.name == "name_value" assert response.input_uri == "input_uri_value" assert response.output_uri == "output_uri_value" assert response.priority == 898 assert response.state == resources.Job.ProcessingState.PENDING assert response.failure_reason == "failure_reason_value" assert response.ttl_after_completion_days == 2670 @pytest.mark.asyncio async def test_create_job_async_from_dict(): await test_create_job_async(request_type=dict) def test_create_job_field_headers(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.CreateJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.create_job), "__call__") as call: call.return_value = resources.Job() client.create_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_create_job_field_headers_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.CreateJobRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.create_job), "__call__") as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(resources.Job()) await client.create_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_create_job_flattened(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.create_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = resources.Job() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.create_job( parent="parent_value", job=resources.Job(name="name_value"), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0].parent == "parent_value" assert args[0].job == resources.Job(name="name_value") def test_create_job_flattened_error(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.create_job( services.CreateJobRequest(), parent="parent_value", job=resources.Job(name="name_value"), ) @pytest.mark.asyncio async def test_create_job_flattened_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.create_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = resources.Job() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(resources.Job()) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.create_job( parent="parent_value", job=resources.Job(name="name_value"), ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0].parent == "parent_value" assert args[0].job == resources.Job(name="name_value") @pytest.mark.asyncio async def test_create_job_flattened_error_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.create_job( services.CreateJobRequest(), parent="parent_value", job=resources.Job(name="name_value"), ) def test_list_jobs(transport: str = "grpc", request_type=services.ListJobsRequest): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_jobs), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = services.ListJobsResponse( next_page_token="next_page_token_value", ) response = client.list_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == services.ListJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListJobsPager) assert response.next_page_token == "next_page_token_value" def test_list_jobs_from_dict(): test_list_jobs(request_type=dict) def test_list_jobs_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_jobs), "__call__") as call: client.list_jobs() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == services.ListJobsRequest() @pytest.mark.asyncio async def test_list_jobs_async( transport: str = "grpc_asyncio", request_type=services.ListJobsRequest ): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_jobs), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( services.ListJobsResponse(next_page_token="next_page_token_value",) ) response = await client.list_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == services.ListJobsRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListJobsAsyncPager) assert response.next_page_token == "next_page_token_value" @pytest.mark.asyncio async def test_list_jobs_async_from_dict(): await test_list_jobs_async(request_type=dict) def test_list_jobs_field_headers(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.ListJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_jobs), "__call__") as call: call.return_value = services.ListJobsResponse() client.list_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_list_jobs_field_headers_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.ListJobsRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_jobs), "__call__") as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( services.ListJobsResponse() ) await client.list_jobs(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_list_jobs_flattened(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_jobs), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = services.ListJobsResponse() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.list_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0].parent == "parent_value" def test_list_jobs_flattened_error(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.list_jobs( services.ListJobsRequest(), parent="parent_value", ) @pytest.mark.asyncio async def test_list_jobs_flattened_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_jobs), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = services.ListJobsResponse() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( services.ListJobsResponse() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.list_jobs(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0].parent == "parent_value" @pytest.mark.asyncio async def test_list_jobs_flattened_error_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.list_jobs( services.ListJobsRequest(), parent="parent_value", ) def test_list_jobs_pager(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_jobs), "__call__") as call: # Set the response to a series of pages. call.side_effect = ( services.ListJobsResponse( jobs=[resources.Job(), resources.Job(), resources.Job(),], next_page_token="abc", ), services.ListJobsResponse(jobs=[], next_page_token="def",), services.ListJobsResponse(jobs=[resources.Job(),], next_page_token="ghi",), services.ListJobsResponse(jobs=[resources.Job(), resources.Job(),],), RuntimeError, ) metadata = () metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)), ) pager = client.list_jobs(request={}) assert pager._metadata == metadata results = [i for i in pager] assert len(results) == 6 assert all(isinstance(i, resources.Job) for i in results) def test_list_jobs_pages(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.list_jobs), "__call__") as call: # Set the response to a series of pages. call.side_effect = ( services.ListJobsResponse( jobs=[resources.Job(), resources.Job(), resources.Job(),], next_page_token="abc", ), services.ListJobsResponse(jobs=[], next_page_token="def",), services.ListJobsResponse(jobs=[resources.Job(),], next_page_token="ghi",), services.ListJobsResponse(jobs=[resources.Job(), resources.Job(),],), RuntimeError, ) pages = list(client.list_jobs(request={}).pages) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token @pytest.mark.asyncio async def test_list_jobs_async_pager(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials, ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_jobs), "__call__", new_callable=mock.AsyncMock ) as call: # Set the response to a series of pages. call.side_effect = ( services.ListJobsResponse( jobs=[resources.Job(), resources.Job(), resources.Job(),], next_page_token="abc", ), services.ListJobsResponse(jobs=[], next_page_token="def",), services.ListJobsResponse(jobs=[resources.Job(),], next_page_token="ghi",), services.ListJobsResponse(jobs=[resources.Job(), resources.Job(),],), RuntimeError, ) async_pager = await client.list_jobs(request={},) assert async_pager.next_page_token == "abc" responses = [] async for response in async_pager: responses.append(response) assert len(responses) == 6 assert all(isinstance(i, resources.Job) for i in responses) @pytest.mark.asyncio async def test_list_jobs_async_pages(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials, ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_jobs), "__call__", new_callable=mock.AsyncMock ) as call: # Set the response to a series of pages. call.side_effect = ( services.ListJobsResponse( jobs=[resources.Job(), resources.Job(), resources.Job(),], next_page_token="abc", ), services.ListJobsResponse(jobs=[], next_page_token="def",), services.ListJobsResponse(jobs=[resources.Job(),], next_page_token="ghi",), services.ListJobsResponse(jobs=[resources.Job(), resources.Job(),],), RuntimeError, ) pages = [] async for page_ in (await client.list_jobs(request={})).pages: pages.append(page_) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token def test_get_job(transport: str = "grpc", request_type=services.GetJobRequest): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = resources.Job( name="name_value", input_uri="input_uri_value", output_uri="output_uri_value", priority=898, state=resources.Job.ProcessingState.PENDING, failure_reason="failure_reason_value", ttl_after_completion_days=2670, template_id="template_id_value", ) response = client.get_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == services.GetJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, resources.Job) assert response.name == "name_value" assert response.input_uri == "input_uri_value" assert response.output_uri == "output_uri_value" assert response.priority == 898 assert response.state == resources.Job.ProcessingState.PENDING assert response.failure_reason == "failure_reason_value" assert response.ttl_after_completion_days == 2670 def test_get_job_from_dict(): test_get_job(request_type=dict) def test_get_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job), "__call__") as call: client.get_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == services.GetJobRequest() @pytest.mark.asyncio async def test_get_job_async( transport: str = "grpc_asyncio", request_type=services.GetJobRequest ): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( resources.Job( name="name_value", input_uri="input_uri_value", output_uri="output_uri_value", priority=898, state=resources.Job.ProcessingState.PENDING, failure_reason="failure_reason_value", ttl_after_completion_days=2670, ) ) response = await client.get_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == services.GetJobRequest() # Establish that the response is the type that we expect. assert isinstance(response, resources.Job) assert response.name == "name_value" assert response.input_uri == "input_uri_value" assert response.output_uri == "output_uri_value" assert response.priority == 898 assert response.state == resources.Job.ProcessingState.PENDING assert response.failure_reason == "failure_reason_value" assert response.ttl_after_completion_days == 2670 @pytest.mark.asyncio async def test_get_job_async_from_dict(): await test_get_job_async(request_type=dict) def test_get_job_field_headers(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.GetJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job), "__call__") as call: call.return_value = resources.Job() client.get_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_get_job_field_headers_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.GetJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job), "__call__") as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(resources.Job()) await client.get_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_get_job_flattened(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = resources.Job() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.get_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0].name == "name_value" def test_get_job_flattened_error(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.get_job( services.GetJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_get_job_flattened_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = resources.Job() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(resources.Job()) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.get_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0].name == "name_value" @pytest.mark.asyncio async def test_get_job_flattened_error_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.get_job( services.GetJobRequest(), name="name_value", ) def test_delete_job(transport: str = "grpc", request_type=services.DeleteJobRequest): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.delete_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = None response = client.delete_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == services.DeleteJobRequest() # Establish that the response is the type that we expect. assert response is None def test_delete_job_from_dict(): test_delete_job(request_type=dict) def test_delete_job_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.delete_job), "__call__") as call: client.delete_job() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == services.DeleteJobRequest() @pytest.mark.asyncio async def test_delete_job_async( transport: str = "grpc_asyncio", request_type=services.DeleteJobRequest ): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.delete_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) response = await client.delete_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == services.DeleteJobRequest() # Establish that the response is the type that we expect. assert response is None @pytest.mark.asyncio async def test_delete_job_async_from_dict(): await test_delete_job_async(request_type=dict) def test_delete_job_field_headers(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.DeleteJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.delete_job), "__call__") as call: call.return_value = None client.delete_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_delete_job_field_headers_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.DeleteJobRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.delete_job), "__call__") as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) await client.delete_job(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_delete_job_flattened(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.delete_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = None # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.delete_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0].name == "name_value" def test_delete_job_flattened_error(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.delete_job( services.DeleteJobRequest(), name="name_value", ) @pytest.mark.asyncio async def test_delete_job_flattened_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.delete_job), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = None call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.delete_job(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0].name == "name_value" @pytest.mark.asyncio async def test_delete_job_flattened_error_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.delete_job( services.DeleteJobRequest(), name="name_value", ) def test_create_job_template( transport: str = "grpc", request_type=services.CreateJobTemplateRequest ): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_job_template), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = resources.JobTemplate(name="name_value",) response = client.create_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == services.CreateJobTemplateRequest() # Establish that the response is the type that we expect. assert isinstance(response, resources.JobTemplate) assert response.name == "name_value" def test_create_job_template_from_dict(): test_create_job_template(request_type=dict) def test_create_job_template_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_job_template), "__call__" ) as call: client.create_job_template() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == services.CreateJobTemplateRequest() @pytest.mark.asyncio async def test_create_job_template_async( transport: str = "grpc_asyncio", request_type=services.CreateJobTemplateRequest ): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_job_template), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( resources.JobTemplate(name="name_value",) ) response = await client.create_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == services.CreateJobTemplateRequest() # Establish that the response is the type that we expect. assert isinstance(response, resources.JobTemplate) assert response.name == "name_value" @pytest.mark.asyncio async def test_create_job_template_async_from_dict(): await test_create_job_template_async(request_type=dict) def test_create_job_template_field_headers(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.CreateJobTemplateRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_job_template), "__call__" ) as call: call.return_value = resources.JobTemplate() client.create_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_create_job_template_field_headers_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.CreateJobTemplateRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_job_template), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( resources.JobTemplate() ) await client.create_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_create_job_template_flattened(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_job_template), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = resources.JobTemplate() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.create_job_template( parent="parent_value", job_template=resources.JobTemplate(name="name_value"), job_template_id="job_template_id_value", ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0].parent == "parent_value" assert args[0].job_template == resources.JobTemplate(name="name_value") assert args[0].job_template_id == "job_template_id_value" def test_create_job_template_flattened_error(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.create_job_template( services.CreateJobTemplateRequest(), parent="parent_value", job_template=resources.JobTemplate(name="name_value"), job_template_id="job_template_id_value", ) @pytest.mark.asyncio async def test_create_job_template_flattened_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.create_job_template), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = resources.JobTemplate() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( resources.JobTemplate() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.create_job_template( parent="parent_value", job_template=resources.JobTemplate(name="name_value"), job_template_id="job_template_id_value", ) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0].parent == "parent_value" assert args[0].job_template == resources.JobTemplate(name="name_value") assert args[0].job_template_id == "job_template_id_value" @pytest.mark.asyncio async def test_create_job_template_flattened_error_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.create_job_template( services.CreateJobTemplateRequest(), parent="parent_value", job_template=resources.JobTemplate(name="name_value"), job_template_id="job_template_id_value", ) def test_list_job_templates( transport: str = "grpc", request_type=services.ListJobTemplatesRequest ): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = services.ListJobTemplatesResponse( next_page_token="next_page_token_value", ) response = client.list_job_templates(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == services.ListJobTemplatesRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListJobTemplatesPager) assert response.next_page_token == "next_page_token_value" def test_list_job_templates_from_dict(): test_list_job_templates(request_type=dict) def test_list_job_templates_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__" ) as call: client.list_job_templates() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == services.ListJobTemplatesRequest() @pytest.mark.asyncio async def test_list_job_templates_async( transport: str = "grpc_asyncio", request_type=services.ListJobTemplatesRequest ): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( services.ListJobTemplatesResponse(next_page_token="next_page_token_value",) ) response = await client.list_job_templates(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == services.ListJobTemplatesRequest() # Establish that the response is the type that we expect. assert isinstance(response, pagers.ListJobTemplatesAsyncPager) assert response.next_page_token == "next_page_token_value" @pytest.mark.asyncio async def test_list_job_templates_async_from_dict(): await test_list_job_templates_async(request_type=dict) def test_list_job_templates_field_headers(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.ListJobTemplatesRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__" ) as call: call.return_value = services.ListJobTemplatesResponse() client.list_job_templates(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] @pytest.mark.asyncio async def test_list_job_templates_field_headers_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.ListJobTemplatesRequest() request.parent = "parent/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( services.ListJobTemplatesResponse() ) await client.list_job_templates(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "parent=parent/value",) in kw["metadata"] def test_list_job_templates_flattened(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = services.ListJobTemplatesResponse() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.list_job_templates(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0].parent == "parent_value" def test_list_job_templates_flattened_error(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.list_job_templates( services.ListJobTemplatesRequest(), parent="parent_value", ) @pytest.mark.asyncio async def test_list_job_templates_flattened_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = services.ListJobTemplatesResponse() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( services.ListJobTemplatesResponse() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.list_job_templates(parent="parent_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0].parent == "parent_value" @pytest.mark.asyncio async def test_list_job_templates_flattened_error_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.list_job_templates( services.ListJobTemplatesRequest(), parent="parent_value", ) def test_list_job_templates_pager(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( services.ListJobTemplatesResponse( job_templates=[ resources.JobTemplate(), resources.JobTemplate(), resources.JobTemplate(), ], next_page_token="abc", ), services.ListJobTemplatesResponse(job_templates=[], next_page_token="def",), services.ListJobTemplatesResponse( job_templates=[resources.JobTemplate(),], next_page_token="ghi", ), services.ListJobTemplatesResponse( job_templates=[resources.JobTemplate(), resources.JobTemplate(),], ), RuntimeError, ) metadata = () metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("parent", ""),)), ) pager = client.list_job_templates(request={}) assert pager._metadata == metadata results = [i for i in pager] assert len(results) == 6 assert all(isinstance(i, resources.JobTemplate) for i in results) def test_list_job_templates_pages(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials,) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__" ) as call: # Set the response to a series of pages. call.side_effect = ( services.ListJobTemplatesResponse( job_templates=[ resources.JobTemplate(), resources.JobTemplate(), resources.JobTemplate(), ], next_page_token="abc", ), services.ListJobTemplatesResponse(job_templates=[], next_page_token="def",), services.ListJobTemplatesResponse( job_templates=[resources.JobTemplate(),], next_page_token="ghi", ), services.ListJobTemplatesResponse( job_templates=[resources.JobTemplate(), resources.JobTemplate(),], ), RuntimeError, ) pages = list(client.list_job_templates(request={}).pages) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token @pytest.mark.asyncio async def test_list_job_templates_async_pager(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials, ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( services.ListJobTemplatesResponse( job_templates=[ resources.JobTemplate(), resources.JobTemplate(), resources.JobTemplate(), ], next_page_token="abc", ), services.ListJobTemplatesResponse(job_templates=[], next_page_token="def",), services.ListJobTemplatesResponse( job_templates=[resources.JobTemplate(),], next_page_token="ghi", ), services.ListJobTemplatesResponse( job_templates=[resources.JobTemplate(), resources.JobTemplate(),], ), RuntimeError, ) async_pager = await client.list_job_templates(request={},) assert async_pager.next_page_token == "abc" responses = [] async for response in async_pager: responses.append(response) assert len(responses) == 6 assert all(isinstance(i, resources.JobTemplate) for i in responses) @pytest.mark.asyncio async def test_list_job_templates_async_pages(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials, ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.list_job_templates), "__call__", new_callable=mock.AsyncMock, ) as call: # Set the response to a series of pages. call.side_effect = ( services.ListJobTemplatesResponse( job_templates=[ resources.JobTemplate(), resources.JobTemplate(), resources.JobTemplate(), ], next_page_token="abc", ), services.ListJobTemplatesResponse(job_templates=[], next_page_token="def",), services.ListJobTemplatesResponse( job_templates=[resources.JobTemplate(),], next_page_token="ghi", ), services.ListJobTemplatesResponse( job_templates=[resources.JobTemplate(), resources.JobTemplate(),], ), RuntimeError, ) pages = [] async for page_ in (await client.list_job_templates(request={})).pages: pages.append(page_) for page_, token in zip(pages, ["abc", "def", "ghi", ""]): assert page_.raw_page.next_page_token == token def test_get_job_template( transport: str = "grpc", request_type=services.GetJobTemplateRequest ): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job_template), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = resources.JobTemplate(name="name_value",) response = client.get_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == services.GetJobTemplateRequest() # Establish that the response is the type that we expect. assert isinstance(response, resources.JobTemplate) assert response.name == "name_value" def test_get_job_template_from_dict(): test_get_job_template(request_type=dict) def test_get_job_template_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job_template), "__call__") as call: client.get_job_template() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == services.GetJobTemplateRequest() @pytest.mark.asyncio async def test_get_job_template_async( transport: str = "grpc_asyncio", request_type=services.GetJobTemplateRequest ): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job_template), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( resources.JobTemplate(name="name_value",) ) response = await client.get_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == services.GetJobTemplateRequest() # Establish that the response is the type that we expect. assert isinstance(response, resources.JobTemplate) assert response.name == "name_value" @pytest.mark.asyncio async def test_get_job_template_async_from_dict(): await test_get_job_template_async(request_type=dict) def test_get_job_template_field_headers(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.GetJobTemplateRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job_template), "__call__") as call: call.return_value = resources.JobTemplate() client.get_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_get_job_template_field_headers_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.GetJobTemplateRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job_template), "__call__") as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( resources.JobTemplate() ) await client.get_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_get_job_template_flattened(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job_template), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = resources.JobTemplate() # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.get_job_template(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0].name == "name_value" def test_get_job_template_flattened_error(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.get_job_template( services.GetJobTemplateRequest(), name="name_value", ) @pytest.mark.asyncio async def test_get_job_template_flattened_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object(type(client.transport.get_job_template), "__call__") as call: # Designate an appropriate return value for the call. call.return_value = resources.JobTemplate() call.return_value = grpc_helpers_async.FakeUnaryUnaryCall( resources.JobTemplate() ) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.get_job_template(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0].name == "name_value" @pytest.mark.asyncio async def test_get_job_template_flattened_error_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.get_job_template( services.GetJobTemplateRequest(), name="name_value", ) def test_delete_job_template( transport: str = "grpc", request_type=services.DeleteJobTemplateRequest ): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_job_template), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None response = client.delete_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == services.DeleteJobTemplateRequest() # Establish that the response is the type that we expect. assert response is None def test_delete_job_template_from_dict(): test_delete_job_template(request_type=dict) def test_delete_job_template_empty_call(): # This test is a coverage failsafe to make sure that totally empty calls, # i.e. request == None and no flattened fields passed, work. client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc", ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_job_template), "__call__" ) as call: client.delete_job_template() call.assert_called() _, args, _ = call.mock_calls[0] assert args[0] == services.DeleteJobTemplateRequest() @pytest.mark.asyncio async def test_delete_job_template_async( transport: str = "grpc_asyncio", request_type=services.DeleteJobTemplateRequest ): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # Everything is optional in proto3 as far as the runtime is concerned, # and we are mocking out the actual API, so just send an empty request. request = request_type() # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_job_template), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) response = await client.delete_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == services.DeleteJobTemplateRequest() # Establish that the response is the type that we expect. assert response is None @pytest.mark.asyncio async def test_delete_job_template_async_from_dict(): await test_delete_job_template_async(request_type=dict) def test_delete_job_template_field_headers(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.DeleteJobTemplateRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_job_template), "__call__" ) as call: call.return_value = None client.delete_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] @pytest.mark.asyncio async def test_delete_job_template_field_headers_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Any value that is part of the HTTP/1.1 URI should be sent as # a field header. Set these to a non-empty value. request = services.DeleteJobTemplateRequest() request.name = "name/value" # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_job_template), "__call__" ) as call: call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) await client.delete_job_template(request) # Establish that the underlying gRPC stub method was called. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0] == request # Establish that the field header was sent. _, _, kw = call.mock_calls[0] assert ("x-goog-request-params", "name=name/value",) in kw["metadata"] def test_delete_job_template_flattened(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_job_template), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. client.delete_job_template(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) == 1 _, args, _ = call.mock_calls[0] assert args[0].name == "name_value" def test_delete_job_template_flattened_error(): client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): client.delete_job_template( services.DeleteJobTemplateRequest(), name="name_value", ) @pytest.mark.asyncio async def test_delete_job_template_flattened_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Mock the actual call within the gRPC stub, and fake the request. with mock.patch.object( type(client.transport.delete_job_template), "__call__" ) as call: # Designate an appropriate return value for the call. call.return_value = None call.return_value = grpc_helpers_async.FakeUnaryUnaryCall(None) # Call the method with a truthy value for each flattened field, # using the keyword arguments to the method. response = await client.delete_job_template(name="name_value",) # Establish that the underlying call was made with the expected # request object values. assert len(call.mock_calls) _, args, _ = call.mock_calls[0] assert args[0].name == "name_value" @pytest.mark.asyncio async def test_delete_job_template_flattened_error_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), ) # Attempting to call a method with both a request object and flattened # fields is an error. with pytest.raises(ValueError): await client.delete_job_template( services.DeleteJobTemplateRequest(), name="name_value", ) def test_credentials_transport_error(): # It is an error to provide credentials and a transport instance. transport = transports.TranscoderServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) with pytest.raises(ValueError): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport, ) # It is an error to provide a credentials file and a transport instance. transport = transports.TranscoderServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) with pytest.raises(ValueError): client = TranscoderServiceClient( client_options={"credentials_file": "credentials.json"}, transport=transport, ) # It is an error to provide scopes and a transport instance. transport = transports.TranscoderServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) with pytest.raises(ValueError): client = TranscoderServiceClient( client_options={"scopes": ["1", "2"]}, transport=transport, ) def test_transport_instance(): # A client may be instantiated with a custom transport instance. transport = transports.TranscoderServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) client = TranscoderServiceClient(transport=transport) assert client.transport is transport def test_transport_get_channel(): # A client may be instantiated with a custom transport instance. transport = transports.TranscoderServiceGrpcTransport( credentials=ga_credentials.AnonymousCredentials(), ) channel = transport.grpc_channel assert channel transport = transports.TranscoderServiceGrpcAsyncIOTransport( credentials=ga_credentials.AnonymousCredentials(), ) channel = transport.grpc_channel assert channel @pytest.mark.parametrize( "transport_class", [ transports.TranscoderServiceGrpcTransport, transports.TranscoderServiceGrpcAsyncIOTransport, ], ) def test_transport_adc(transport_class): # Test default credentials are used if not provided. with mock.patch.object(google.auth, "default") as adc: adc.return_value = (ga_credentials.AnonymousCredentials(), None) transport_class() adc.assert_called_once() def test_transport_grpc_default(): # A client should use the gRPC transport by default. client = TranscoderServiceClient(credentials=ga_credentials.AnonymousCredentials(),) assert isinstance(client.transport, transports.TranscoderServiceGrpcTransport,) def test_transcoder_service_base_transport_error(): # Passing both a credentials object and credentials_file should raise an error with pytest.raises(core_exceptions.DuplicateCredentialArgs): transport = transports.TranscoderServiceTransport( credentials=ga_credentials.AnonymousCredentials(), credentials_file="credentials.json", ) def test_transcoder_service_base_transport(): # Instantiate the base transport. with mock.patch( "google.cloud.video.transcoder_v1beta1.services.transcoder_service.transports.TranscoderServiceTransport.__init__" ) as Transport: Transport.return_value = None transport = transports.TranscoderServiceTransport( credentials=ga_credentials.AnonymousCredentials(), ) # Every method on the transport should just blindly # raise NotImplementedError. methods = ( "create_job", "list_jobs", "get_job", "delete_job", "create_job_template", "list_job_templates", "get_job_template", "delete_job_template", ) for method in methods: with pytest.raises(NotImplementedError): getattr(transport, method)(request=object()) with pytest.raises(NotImplementedError): transport.close() @requires_google_auth_gte_1_25_0 def test_transcoder_service_base_transport_with_credentials_file(): # Instantiate the base transport with a credentials file with mock.patch.object( google.auth, "load_credentials_from_file", autospec=True ) as load_creds, mock.patch( "google.cloud.video.transcoder_v1beta1.services.transcoder_service.transports.TranscoderServiceTransport._prep_wrapped_messages" ) as Transport: Transport.return_value = None load_creds.return_value = (ga_credentials.AnonymousCredentials(), None) transport = transports.TranscoderServiceTransport( credentials_file="credentials.json", quota_project_id="octopus", ) load_creds.assert_called_once_with( "credentials.json", scopes=None, default_scopes=("https://www.googleapis.com/auth/cloud-platform",), quota_project_id="octopus", ) @requires_google_auth_lt_1_25_0 def test_transcoder_service_base_transport_with_credentials_file_old_google_auth(): # Instantiate the base transport with a credentials file with mock.patch.object( google.auth, "load_credentials_from_file", autospec=True ) as load_creds, mock.patch( "google.cloud.video.transcoder_v1beta1.services.transcoder_service.transports.TranscoderServiceTransport._prep_wrapped_messages" ) as Transport: Transport.return_value = None load_creds.return_value = (ga_credentials.AnonymousCredentials(), None) transport = transports.TranscoderServiceTransport( credentials_file="credentials.json", quota_project_id="octopus", ) load_creds.assert_called_once_with( "credentials.json", scopes=("https://www.googleapis.com/auth/cloud-platform",), quota_project_id="octopus", ) def test_transcoder_service_base_transport_with_adc(): # Test the default credentials are used if credentials and credentials_file are None. with mock.patch.object(google.auth, "default", autospec=True) as adc, mock.patch( "google.cloud.video.transcoder_v1beta1.services.transcoder_service.transports.TranscoderServiceTransport._prep_wrapped_messages" ) as Transport: Transport.return_value = None adc.return_value = (ga_credentials.AnonymousCredentials(), None) transport = transports.TranscoderServiceTransport() adc.assert_called_once() @requires_google_auth_gte_1_25_0 def test_transcoder_service_auth_adc(): # If no credentials are provided, we should use ADC credentials. with mock.patch.object(google.auth, "default", autospec=True) as adc: adc.return_value = (ga_credentials.AnonymousCredentials(), None) TranscoderServiceClient() adc.assert_called_once_with( scopes=None, default_scopes=("https://www.googleapis.com/auth/cloud-platform",), quota_project_id=None, ) @requires_google_auth_lt_1_25_0 def test_transcoder_service_auth_adc_old_google_auth(): # If no credentials are provided, we should use ADC credentials. with mock.patch.object(google.auth, "default", autospec=True) as adc: adc.return_value = (ga_credentials.AnonymousCredentials(), None) TranscoderServiceClient() adc.assert_called_once_with( scopes=("https://www.googleapis.com/auth/cloud-platform",), quota_project_id=None, ) @pytest.mark.parametrize( "transport_class", [ transports.TranscoderServiceGrpcTransport, transports.TranscoderServiceGrpcAsyncIOTransport, ], ) @requires_google_auth_gte_1_25_0 def test_transcoder_service_transport_auth_adc(transport_class): # If credentials and host are not provided, the transport class should use # ADC credentials. with mock.patch.object(google.auth, "default", autospec=True) as adc: adc.return_value = (ga_credentials.AnonymousCredentials(), None) transport_class(quota_project_id="octopus", scopes=["1", "2"]) adc.assert_called_once_with( scopes=["1", "2"], default_scopes=("https://www.googleapis.com/auth/cloud-platform",), quota_project_id="octopus", ) @pytest.mark.parametrize( "transport_class", [ transports.TranscoderServiceGrpcTransport, transports.TranscoderServiceGrpcAsyncIOTransport, ], ) @requires_google_auth_lt_1_25_0 def test_transcoder_service_transport_auth_adc_old_google_auth(transport_class): # If credentials and host are not provided, the transport class should use # ADC credentials. with mock.patch.object(google.auth, "default", autospec=True) as adc: adc.return_value = (ga_credentials.AnonymousCredentials(), None) transport_class(quota_project_id="octopus") adc.assert_called_once_with( scopes=("https://www.googleapis.com/auth/cloud-platform",), quota_project_id="octopus", ) @pytest.mark.parametrize( "transport_class,grpc_helpers", [ (transports.TranscoderServiceGrpcTransport, grpc_helpers), (transports.TranscoderServiceGrpcAsyncIOTransport, grpc_helpers_async), ], ) def test_transcoder_service_transport_create_channel(transport_class, grpc_helpers): # If credentials and host are not provided, the transport class should use # ADC credentials. with mock.patch.object( google.auth, "default", autospec=True ) as adc, mock.patch.object( grpc_helpers, "create_channel", autospec=True ) as create_channel: creds = ga_credentials.AnonymousCredentials() adc.return_value = (creds, None) transport_class(quota_project_id="octopus", scopes=["1", "2"]) create_channel.assert_called_with( "transcoder.googleapis.com:443", credentials=creds, credentials_file=None, quota_project_id="octopus", default_scopes=("https://www.googleapis.com/auth/cloud-platform",), scopes=["1", "2"], default_host="transcoder.googleapis.com", ssl_credentials=None, options=[ ("grpc.max_send_message_length", -1), ("grpc.max_receive_message_length", -1), ], ) @pytest.mark.parametrize( "transport_class", [ transports.TranscoderServiceGrpcTransport, transports.TranscoderServiceGrpcAsyncIOTransport, ], ) def test_transcoder_service_grpc_transport_client_cert_source_for_mtls(transport_class): cred = ga_credentials.AnonymousCredentials() # Check ssl_channel_credentials is used if provided. with mock.patch.object(transport_class, "create_channel") as mock_create_channel: mock_ssl_channel_creds = mock.Mock() transport_class( host="squid.clam.whelk", credentials=cred, ssl_channel_credentials=mock_ssl_channel_creds, ) mock_create_channel.assert_called_once_with( "squid.clam.whelk:443", credentials=cred, credentials_file=None, scopes=None, ssl_credentials=mock_ssl_channel_creds, quota_project_id=None, options=[ ("grpc.max_send_message_length", -1), ("grpc.max_receive_message_length", -1), ], ) # Check if ssl_channel_credentials is not provided, then client_cert_source_for_mtls # is used. with mock.patch.object(transport_class, "create_channel", return_value=mock.Mock()): with mock.patch("grpc.ssl_channel_credentials") as mock_ssl_cred: transport_class( credentials=cred, client_cert_source_for_mtls=client_cert_source_callback, ) expected_cert, expected_key = client_cert_source_callback() mock_ssl_cred.assert_called_once_with( certificate_chain=expected_cert, private_key=expected_key ) def test_transcoder_service_host_no_port(): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), client_options=client_options.ClientOptions( api_endpoint="transcoder.googleapis.com" ), ) assert client.transport._host == "transcoder.googleapis.com:443" def test_transcoder_service_host_with_port(): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), client_options=client_options.ClientOptions( api_endpoint="transcoder.googleapis.com:8000" ), ) assert client.transport._host == "transcoder.googleapis.com:8000" def test_transcoder_service_grpc_transport_channel(): channel = grpc.secure_channel("http://localhost/", grpc.local_channel_credentials()) # Check that channel is used if provided. transport = transports.TranscoderServiceGrpcTransport( host="squid.clam.whelk", channel=channel, ) assert transport.grpc_channel == channel assert transport._host == "squid.clam.whelk:443" assert transport._ssl_channel_credentials == None def test_transcoder_service_grpc_asyncio_transport_channel(): channel = aio.secure_channel("http://localhost/", grpc.local_channel_credentials()) # Check that channel is used if provided. transport = transports.TranscoderServiceGrpcAsyncIOTransport( host="squid.clam.whelk", channel=channel, ) assert transport.grpc_channel == channel assert transport._host == "squid.clam.whelk:443" assert transport._ssl_channel_credentials == None # Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are # removed from grpc/grpc_asyncio transport constructor. @pytest.mark.parametrize( "transport_class", [ transports.TranscoderServiceGrpcTransport, transports.TranscoderServiceGrpcAsyncIOTransport, ], ) def test_transcoder_service_transport_channel_mtls_with_client_cert_source( transport_class, ): with mock.patch( "grpc.ssl_channel_credentials", autospec=True ) as grpc_ssl_channel_cred: with mock.patch.object( transport_class, "create_channel" ) as grpc_create_channel: mock_ssl_cred = mock.Mock() grpc_ssl_channel_cred.return_value = mock_ssl_cred mock_grpc_channel = mock.Mock() grpc_create_channel.return_value = mock_grpc_channel cred = ga_credentials.AnonymousCredentials() with pytest.warns(DeprecationWarning): with mock.patch.object(google.auth, "default") as adc: adc.return_value = (cred, None) transport = transport_class( host="squid.clam.whelk", api_mtls_endpoint="mtls.squid.clam.whelk", client_cert_source=client_cert_source_callback, ) adc.assert_called_once() grpc_ssl_channel_cred.assert_called_once_with( certificate_chain=b"cert bytes", private_key=b"key bytes" ) grpc_create_channel.assert_called_once_with( "mtls.squid.clam.whelk:443", credentials=cred, credentials_file=None, scopes=None, ssl_credentials=mock_ssl_cred, quota_project_id=None, options=[ ("grpc.max_send_message_length", -1), ("grpc.max_receive_message_length", -1), ], ) assert transport.grpc_channel == mock_grpc_channel assert transport._ssl_channel_credentials == mock_ssl_cred # Remove this test when deprecated arguments (api_mtls_endpoint, client_cert_source) are # removed from grpc/grpc_asyncio transport constructor. @pytest.mark.parametrize( "transport_class", [ transports.TranscoderServiceGrpcTransport, transports.TranscoderServiceGrpcAsyncIOTransport, ], ) def test_transcoder_service_transport_channel_mtls_with_adc(transport_class): mock_ssl_cred = mock.Mock() with mock.patch.multiple( "google.auth.transport.grpc.SslCredentials", __init__=mock.Mock(return_value=None), ssl_credentials=mock.PropertyMock(return_value=mock_ssl_cred), ): with mock.patch.object( transport_class, "create_channel" ) as grpc_create_channel: mock_grpc_channel = mock.Mock() grpc_create_channel.return_value = mock_grpc_channel mock_cred = mock.Mock() with pytest.warns(DeprecationWarning): transport = transport_class( host="squid.clam.whelk", credentials=mock_cred, api_mtls_endpoint="mtls.squid.clam.whelk", client_cert_source=None, ) grpc_create_channel.assert_called_once_with( "mtls.squid.clam.whelk:443", credentials=mock_cred, credentials_file=None, scopes=None, ssl_credentials=mock_ssl_cred, quota_project_id=None, options=[ ("grpc.max_send_message_length", -1), ("grpc.max_receive_message_length", -1), ], ) assert transport.grpc_channel == mock_grpc_channel def test_job_path(): project = "squid" location = "clam" job = "whelk" expected = "projects/{project}/locations/{location}/jobs/{job}".format( project=project, location=location, job=job, ) actual = TranscoderServiceClient.job_path(project, location, job) assert expected == actual def test_parse_job_path(): expected = { "project": "octopus", "location": "oyster", "job": "nudibranch", } path = TranscoderServiceClient.job_path(**expected) # Check that the path construction is reversible. actual = TranscoderServiceClient.parse_job_path(path) assert expected == actual def test_job_template_path(): project = "cuttlefish" location = "mussel" job_template = "winkle" expected = "projects/{project}/locations/{location}/jobTemplates/{job_template}".format( project=project, location=location, job_template=job_template, ) actual = TranscoderServiceClient.job_template_path(project, location, job_template) assert expected == actual def test_parse_job_template_path(): expected = { "project": "nautilus", "location": "scallop", "job_template": "abalone", } path = TranscoderServiceClient.job_template_path(**expected) # Check that the path construction is reversible. actual = TranscoderServiceClient.parse_job_template_path(path) assert expected == actual def test_common_billing_account_path(): billing_account = "squid" expected = "billingAccounts/{billing_account}".format( billing_account=billing_account, ) actual = TranscoderServiceClient.common_billing_account_path(billing_account) assert expected == actual def test_parse_common_billing_account_path(): expected = { "billing_account": "clam", } path = TranscoderServiceClient.common_billing_account_path(**expected) # Check that the path construction is reversible. actual = TranscoderServiceClient.parse_common_billing_account_path(path) assert expected == actual def test_common_folder_path(): folder = "whelk" expected = "folders/{folder}".format(folder=folder,) actual = TranscoderServiceClient.common_folder_path(folder) assert expected == actual def test_parse_common_folder_path(): expected = { "folder": "octopus", } path = TranscoderServiceClient.common_folder_path(**expected) # Check that the path construction is reversible. actual = TranscoderServiceClient.parse_common_folder_path(path) assert expected == actual def test_common_organization_path(): organization = "oyster" expected = "organizations/{organization}".format(organization=organization,) actual = TranscoderServiceClient.common_organization_path(organization) assert expected == actual def test_parse_common_organization_path(): expected = { "organization": "nudibranch", } path = TranscoderServiceClient.common_organization_path(**expected) # Check that the path construction is reversible. actual = TranscoderServiceClient.parse_common_organization_path(path) assert expected == actual def test_common_project_path(): project = "cuttlefish" expected = "projects/{project}".format(project=project,) actual = TranscoderServiceClient.common_project_path(project) assert expected == actual def test_parse_common_project_path(): expected = { "project": "mussel", } path = TranscoderServiceClient.common_project_path(**expected) # Check that the path construction is reversible. actual = TranscoderServiceClient.parse_common_project_path(path) assert expected == actual def test_common_location_path(): project = "winkle" location = "nautilus" expected = "projects/{project}/locations/{location}".format( project=project, location=location, ) actual = TranscoderServiceClient.common_location_path(project, location) assert expected == actual def test_parse_common_location_path(): expected = { "project": "scallop", "location": "abalone", } path = TranscoderServiceClient.common_location_path(**expected) # Check that the path construction is reversible. actual = TranscoderServiceClient.parse_common_location_path(path) assert expected == actual def test_client_withDEFAULT_CLIENT_INFO(): client_info = gapic_v1.client_info.ClientInfo() with mock.patch.object( transports.TranscoderServiceTransport, "_prep_wrapped_messages" ) as prep: client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), client_info=client_info, ) prep.assert_called_once_with(client_info) with mock.patch.object( transports.TranscoderServiceTransport, "_prep_wrapped_messages" ) as prep: transport_class = TranscoderServiceClient.get_transport_class() transport = transport_class( credentials=ga_credentials.AnonymousCredentials(), client_info=client_info, ) prep.assert_called_once_with(client_info) @pytest.mark.asyncio async def test_transport_close_async(): client = TranscoderServiceAsyncClient( credentials=ga_credentials.AnonymousCredentials(), transport="grpc_asyncio", ) with mock.patch.object( type(getattr(client.transport, "grpc_channel")), "close" ) as close: async with client: close.assert_not_called() close.assert_called_once() def test_transport_close(): transports = { "grpc": "_grpc_channel", } for transport, close_name in transports.items(): client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport ) with mock.patch.object( type(getattr(client.transport, close_name)), "close" ) as close: with client: close.assert_not_called() close.assert_called_once() def test_client_ctx(): transports = [ "grpc", ] for transport in transports: client = TranscoderServiceClient( credentials=ga_credentials.AnonymousCredentials(), transport=transport ) # Test client calls underlying transport. with mock.patch.object(type(client.transport), "close") as close: close.assert_not_called() with client: pass close.assert_called()

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f7c91231a685403d79689aac00c0aa044b7c8356

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Python

pydoof/search_api/search.py

doofinder/pydoof

18ebdbf5710d08bc00dcc28b9c035a9fe47306f0

[ "MIT" ]

null

pydoof/search_api/search.py

doofinder/pydoof

18ebdbf5710d08bc00dcc28b9c035a9fe47306f0

[ "MIT" ]

12

2015-05-14T17:09:51.000Z

2021-12-22T16:47:05.000Z

pydoof/search_api/search.py

doofinder/pydoof

18ebdbf5710d08bc00dcc28b9c035a9fe47306f0

[ "MIT" ]

1

2022-01-04T09:09:31.000Z

from enum import Enum, unique from pydoof.search_api.api_client import SearchAPIClient from pydoof.helpers import parse_query_params @unique class QueryNames(Enum): MATCH_AND = "match_and" MATCH_OR = "match_or" FUZZY = "fuzzy" PHONETIC = "phonetic_text" @unique class Transformers(Enum): BASIC = "basic" ONLY_IDS = "onlyid" def query(hashid, query, filter_=None, exclude=None, index_name=None, query_name=None, sort=None, page=None, rpp=None, transformer=None, no_stats=None, **opts): """ Queries items indexed in a search engine. Args: hashid (str): Unique search engine id. Indicates to which search engine we are doing the query. query (str): The terms we are looking for in the items of the search engine. filter_ (dict, optional): A dictionary that indicates a filter for items. For instance, look for those items of color "blue". Default to None. exclude (dict, optional): A dictionary that indicates an exclude rule for items. For instance, exclude those items that belong to `Foo` category. Default to None index_name (str, optional): A unique name for a search engine index. If provided, it will limit result to that index. query_name (str, optional): Indicates a query name to used. It could be one of "match_and", "match_or", "fuzzy", or "phonetic_text". If you do not provide one, search API will select the best one. Default to None. sort (lst, optional): Indicates a sorting rule for results. If sort is a list of strings, each element will define a field to sort by in ascending order. If sort is a list of dictionaries, you can set the order. For instance, sort: [{'color': 'desc'}] will sort results by color name in descending order. If you do not provided one, results will be ordered by score in descending order. Default to None. page (int, optional): Indicates a page of results. If you provide a page, `query` will return the results from that page. Default to None. rpp (int, optional): Indicates how many results to fetch by page, minimum 1, maximum 100. Default to 10. transformer (str, optional): Indicates a transformation to apply to items in result. It could be one of "basic" or "onlyid". If none is set, items will not be transformed. Default to None. no_stats (bool, optional): Indicates if the query should be recorded in search stats. If it is true, it will not be recorded. Default to False. """ query_params = parse_query_params({ 'hashid': hashid, 'query': query, 'filter': filter_, 'exclude': exclude, 'type': index_name, 'query_name': query_name, 'sort': sort, 'page': page, 'rpp': rpp, 'transformer': transformer, 'nostats': no_stats }) api_client = SearchAPIClient(**opts) return api_client.get( '/5/search', query_params=query_params ) def suggest(hashid, query, filter_=None, exclude=None, sort=None, page=None, rpp=None, transformer=None, no_stats=None, **opts): """ Fetchs suggestions for terms based on the items indexed in a search engine. Args: hashid (str): Unique search engine id. Indicates to which search engine we are doing the query. query (str): The terms we are looking for in the items of the search engine. filter_ (dict, optional): A dictionary that indicates a filter for items. For instance, look for those items of color "blue". Default to None. exclude (dict, optional): A dictionary that indicates an exclude rule for items. For instance, exclude those items that belong to `Foo` category. Default to None sort (lst, optional): Indicates a sorting rule for results. If sort is a list of strings, each element will define a field to sort by in ascending order. If sort is a list of dictionaries, you can set the order. For instance, sort: [{'color': 'desc'}] will sort results by color name in descending order. If you do not provided one, results will be ordered by score in descending order. Default to None. page (int, optional): Indicates a page of results. If you provide a page, `suggest` will return the results from that page. Default to None. rpp (int, optional): Indicates how many results to fetch by page, minimum 1, maximum 100. Default to 10. transformer (str, optional): Indicates a transformation to apply to items in result. It could be one of "basic" or "onlyid". If none is set, items will not be transformed. Default to None. no_stats (bool, optional): Indicates if the query should be recorded in search stats. If it is true, it will not be recorded. Default to False. """ query_params = parse_query_params({ 'hashid': hashid, 'query': query, 'filter': filter_, 'exclude': exclude, 'sort': sort, 'page': page, 'rpp': rpp, 'transformer': transformer, 'nostats': no_stats }) api_client = SearchAPIClient(**opts) return api_client.get( '/5/suggest', query_params=query_params )

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79

0.62542

759

5,657

4.600791

0.181818

0.03866

0.040951

0.026346

0.814719

0.81071

0.793528

0

0.00354

0.300866

5,657

134

80

42.216418

0.879393

0.671557

0

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0

0.117759

0

1

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false

0

0.057692

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0.288462

0

null

0

1

0

null

0

6

f70086a12cb7a805133ce4cd015dbd84c54c0b65

28

py

Python

ent2id/__init__.py

skojaku/ent2id

1483cc9430999db7a6598dfdf0afa7302ada4893

[ "CC0-1.0" ]

null

ent2id/__init__.py

skojaku/ent2id

1483cc9430999db7a6598dfdf0afa7302ada4893

[ "CC0-1.0" ]

null

ent2id/__init__.py

skojaku/ent2id

1483cc9430999db7a6598dfdf0afa7302ada4893

[ "CC0-1.0" ]

null

from ent2id.Ent2Id import *

14

27

0.785714

4

28

5.5

0.75

0

0.083333

0.142857

28

1

28

0.833333

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

f734df86fba52bb0e5b0075c1880a25fc79ec783

113

py

Python

Python/pythonProject/exercise/ex047.py

JoaoMoreira2002/Linguagens-de-programacao

b91a902188428238a567c8f52b2ac9028378c4df

[ "MIT" ]

null

Python/pythonProject/exercise/ex047.py

JoaoMoreira2002/Linguagens-de-programacao

b91a902188428238a567c8f52b2ac9028378c4df

[ "MIT" ]

null

Python/pythonProject/exercise/ex047.py

JoaoMoreira2002/Linguagens-de-programacao

b91a902188428238a567c8f52b2ac9028378c4df

[ "MIT" ]

null

for x in range(0, 11): for c in range(0, 11): print(x, 'x', c, '= {}'.format(x * c)) print('\t')

22.6

46

0.442478

21

113

2.380952

0.47619

0.28

0.32

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0

0.075949

0.300885

113

4

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28.25

0.556962

0

0.061947

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1

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false

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null

1

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1

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null

0

1

0

6

f737f3d4131b56174d565a0575f0331decd3591a

20,724

py

Python

orttraining/orttraining/test/python/orttraining_test_checkpoint.py

mszhanyi/onnxruntime

6f85d3e5c81c919022ac4a77e5a051da8518b15d

[ "MIT" ]

669

2018-12-03T22:00:31.000Z

2019-05-06T19:42:49.000Z

orttraining/orttraining/test/python/orttraining_test_checkpoint.py

mszhanyi/onnxruntime

6f85d3e5c81c919022ac4a77e5a051da8518b15d

[ "MIT" ]

440

2018-12-03T21:09:56.000Z

2019-05-06T20:47:23.000Z

orttraining/orttraining/test/python/orttraining_test_checkpoint.py

mszhanyi/onnxruntime

6f85d3e5c81c919022ac4a77e5a051da8518b15d

[ "MIT" ]

140

2018-12-03T21:15:28.000Z

2019-05-06T18:02:36.000Z

#!/usr/bin/env python3 # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. import subprocess import os import shutil import sys from checkpoint._test_helpers import makedir from _test_commons import _single_run, _distributed_run checkpoint_dir = os.path.abspath("checkpoint/checkpoint_dir/") makedir(checkpoint_dir) # test workflow: # - there are a total of three files that are used for checkpointing tests: # - orttraining_test_checkpoint.py: co-ordinating all the checkpoint tests # - orttraining_test_save_checkpoint.py: responsible for saving all checkpoint files and trained states # - orttraining_test_load_checkpoint.py: loading the saved checkpoints and the saved states and asserting whether # the saved states match the loaded states. # - and tests encompassing checkpointing tests for scenarios: # - from [onnxruntime orttrainer][full_precision, mixed_precision][single node training, data parallel training, distributed zero, distributed megatron, distributed zero+megatron training] to # [onnxruntime orttrainer, pytorch][full_precision, mixed_precision][single node training, data parallel training, distributed zero, distributed megatron, distributed zero+megatron training] # - all tests cannot be written in the same process because: # - some of them require to be run in a distributed environment (using mpirun) while others can be run using a single process. # - there is a known limitation where the distributed training run context is implemented as a singleton, so in the same process, no more than one # orttrainer can be instantiated. Hence the need to run these tests in different processes one at a time. # - workflow: # - orttraining_test_checkpoint.py calls orttraining_test_save_checkpoint.py to save following files to disk # - ORTTrainer checkpoint files through the ORTTrainer.save_checkpoint method # - ORTTrainer states through pickle after extracting all the states of the ORTTrainer through the ORTTrainer.state_dict method # - for each configuration across [onnxruntime orttrainer][full_precision, mixed_precision][single node training, data parallel training, distributed zero training] # - orttraining_test_checkpoint.py calls orttraining_test_load_checkpoint.py to load each checkpoint into each orttrainer configuration # - Saved ORTTrainer checkpoint files are loaded into an ORTTrainer using the ORTTrainer.load_checkpoint method for each ORTTrainer configuration. # - Saved states are loaded into a python dictionary (called the state dictionary) through pickle # - state dictionary is extracted from the ORTTrainer after it has loaded the checkpoint file and the onnx graph has been initialized (by calling eval_step) # through the ORTTrainer.state_dict method. # - the loaded state dictionary (through pickle) is compared against the extracted state dictionary for: # - equality (or near equality) of model states # - equality (or near equality) of optimizer states # - In some cases the comparison is not directly possible; for example single node trainer to a distributed zero trainer because the extracted state # dictionary is a distributed one and cannot be compared against a single node trainer directly. # - First these states are saved using pickle for each rank to a file on disk # - Wait for all ranks to complete writing the file to disk using barrier() # - Load all states and aggregate them into 1 state dictionary # - Compare this aggregated state dictionary against the original one loaded from disk. # - Similarly, it is not possible to compare mixed precision zero trainer state_dict against full precision zero trainer state_dict because the # full precision states are sharded in the mixed precision trainer run and not shareded in the full precision trainer run. To compare these two state_dicts: # - Both state_dicts (mixed precision and full precision) are saved to file for all ranks. # - Wait for all ranks to complete writing the file to disk using barrier() # - Load all states and aggregate them into 1 state dictionary fpr both the configs. # - Compare this aggregated state dictionaries against one another. save_checkpoint_file = os.path.join("checkpoint", "orttraining_test_save_checkpoint.py") load_checkpoint_file = os.path.join("checkpoint", "orttraining_test_load_checkpoint.py") aggregate_checkpoint_file = os.path.join("checkpoint", "orttraining_test_checkpoint_aggregation.py") optim_state_file = os.path.join("checkpoint", "orttraining_test_load_optimizer_state.py") backend_api_file = os.path.join("checkpoint", "orttraining_test_backend_api.py") single_node_full_precision_path = os.path.join(checkpoint_dir, "single_node", "full_precision") single_node_mixed_precision_path = os.path.join(checkpoint_dir, "single_node", "mixed_precision") distributed_zero_full_precision_lamb_path = os.path.join(checkpoint_dir, "distributed_zero", "full_precision", "lamb") distributed_zero_mixed_precision_lamb_path = os.path.join(checkpoint_dir, "distributed_zero", "mixed_precision", "lamb") # megatron saving and loading uses a different model single_node_full_precision_bart_path = os.path.join(checkpoint_dir, "bart", "single_node", "full_precision") single_node_mixed_precision_bart_path = os.path.join(checkpoint_dir, "bart", "single_node", "mixed_precision") distributed_zero_full_precision_lamb_bart_path = os.path.join( checkpoint_dir, "bart", "distributed_zero", "full_precision", "lamb" ) distributed_zero_mixed_precision_lamb_bart_path = os.path.join( checkpoint_dir, "bart", "distributed_zero", "mixed_precision", "lamb" ) distributed_megatron_full_precision_lamb_path = os.path.join( checkpoint_dir, "bart", "distributed_megatron", "full_precision", "lamb" ) distributed_megatron_mixed_precision_lamb_path = os.path.join( checkpoint_dir, "bart", "distributed_megatron", "mixed_precision", "lamb" ) distributed_zero_megatron_full_precision_adam_path = os.path.join( checkpoint_dir, "bart", "distributed_zero_megatron", "full_precision", "adam" ) distributed_zero_megatron_mixed_precision_adam_path = os.path.join( checkpoint_dir, "bart", "distributed_zero_megatron", "mixed_precision", "adam" ) distributed_zero_megatron_full_precision_lamb_path = os.path.join( checkpoint_dir, "bart", "distributed_zero_megatron", "full_precision", "lamb" ) distributed_zero_megatron_mixed_precision_lamb_path = os.path.join( checkpoint_dir, "bart", "distributed_zero_megatron", "mixed_precision", "lamb" ) # save all checkpoint files (pre-checkpoint) _single_run(save_checkpoint_file, "single_node_full_precision", single_node_full_precision_path) _single_run(save_checkpoint_file, "single_node_mixed_precision", single_node_mixed_precision_path) _distributed_run( save_checkpoint_file, "distributed_zero_full_precision_lamb", distributed_zero_full_precision_lamb_path ) _distributed_run( save_checkpoint_file, "distributed_zero_mixed_precision_lamb", distributed_zero_mixed_precision_lamb_path ) _single_run(save_checkpoint_file, "single_node_full_precision_bart", single_node_full_precision_bart_path) _single_run(save_checkpoint_file, "single_node_mixed_precision_bart", single_node_mixed_precision_bart_path) _distributed_run( save_checkpoint_file, "distributed_zero_full_precision_lamb_bart", distributed_zero_full_precision_lamb_bart_path ) _distributed_run( save_checkpoint_file, "distributed_zero_mixed_precision_lamb_bart", distributed_zero_mixed_precision_lamb_bart_path ) _distributed_run( save_checkpoint_file, "distributed_megatron_full_precision_lamb", distributed_megatron_full_precision_lamb_path ) _distributed_run( save_checkpoint_file, "distributed_megatron_mixed_precision_lamb", distributed_megatron_mixed_precision_lamb_path ) _distributed_run( save_checkpoint_file, "distributed_zero_megatron_full_precision_lamb", distributed_zero_megatron_full_precision_lamb_path, ) _distributed_run( save_checkpoint_file, "distributed_zero_megatron_mixed_precision_lamb", distributed_zero_megatron_mixed_precision_lamb_path, ) # load checkpoint files (post-checkpoint) # going to single node trainer _single_run( load_checkpoint_file, "test_load_from_single_node_full_precision_into_single_node_full_precision", single_node_full_precision_path, ) _single_run( load_checkpoint_file, "test_load_from_single_node_mixed_precision_into_single_node_full_precision", single_node_mixed_precision_path, ) _single_run( load_checkpoint_file, "test_load_from_single_node_mixed_precision_into_single_node_mixed_precision", single_node_mixed_precision_path, ) _single_run( load_checkpoint_file, "test_load_from_single_node_full_precision_into_single_node_mixed_precision", single_node_full_precision_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_zero_full_precision_into_single_node_full_precision", distributed_zero_full_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_zero_mixed_precision_into_single_node_full_precision", distributed_zero_mixed_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_zero_mixed_precision_into_single_node_mixed_precision", distributed_zero_mixed_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_zero_full_precision_into_single_node_mixed_precision", distributed_zero_full_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_megatron_full_precision_into_single_node_full_precision", distributed_megatron_full_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_megatron_mixed_precision_into_single_node_full_precision", distributed_megatron_mixed_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_megatron_mixed_precision_into_single_node_mixed_precision", distributed_megatron_mixed_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_megatron_full_precision_into_single_node_mixed_precision", distributed_megatron_full_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_full_precision_into_single_node_full_precision", distributed_zero_megatron_full_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_mixed_precision_into_single_node_full_precision", distributed_zero_megatron_mixed_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_mixed_precision_into_single_node_mixed_precision", distributed_zero_megatron_mixed_precision_lamb_path, ) _single_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_full_precision_into_single_node_mixed_precision", distributed_zero_megatron_full_precision_lamb_path, ) # going to distributed zero trainer _distributed_run( load_checkpoint_file, "test_load_from_single_node_full_precision_into_distributed_zero_full_precision", single_node_full_precision_path, ) _distributed_run( load_checkpoint_file, "test_load_from_single_node_mixed_precision_into_distributed_zero_full_precision", single_node_mixed_precision_path, ) _distributed_run( load_checkpoint_file, "test_load_from_single_node_mixed_precision_into_distributed_zero_mixed_precision", single_node_mixed_precision_path, ) _distributed_run( load_checkpoint_file, "test_load_from_single_node_full_precision_into_distributed_zero_mixed_precision", single_node_full_precision_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_full_precision_into_distributed_zero_full_precision", distributed_zero_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_mixed_precision_into_distributed_zero_full_precision", distributed_zero_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_mixed_precision_into_distributed_zero_mixed_precision", distributed_zero_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_full_precision_into_distributed_zero_mixed_precision", distributed_zero_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_full_precision_into_distributed_zero_full_precision", distributed_megatron_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_mixed_precision_into_distributed_zero_full_precision", distributed_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_mixed_precision_into_distributed_zero_mixed_precision", distributed_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_full_precision_into_distributed_zero_mixed_precision", distributed_megatron_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_full_precision_into_distributed_zero_full_precision", distributed_zero_megatron_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_mixed_precision_into_distributed_zero_full_precision", distributed_zero_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_mixed_precision_into_distributed_zero_mixed_precision", distributed_zero_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_full_precision_into_distributed_zero_mixed_precision", distributed_zero_megatron_full_precision_lamb_path, ) # going to distributed zero+megatron trainer _distributed_run( load_checkpoint_file, "test_load_from_single_node_full_precision_into_distributed_megatron_full_precision", single_node_full_precision_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_single_node_mixed_precision_into_distributed_megatron_full_precision", single_node_mixed_precision_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_single_node_mixed_precision_into_distributed_megatron_mixed_precision", single_node_mixed_precision_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_single_node_full_precision_into_distributed_megatron_mixed_precision", single_node_full_precision_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_full_precision_into_distributed_megatron_full_precision", distributed_zero_full_precision_lamb_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_mixed_precision_into_distributed_megatron_full_precision", distributed_zero_mixed_precision_lamb_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_mixed_precision_into_distributed_megatron_mixed_precision", distributed_zero_mixed_precision_lamb_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_full_precision_into_distributed_megatron_mixed_precision", distributed_zero_full_precision_lamb_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_full_precision_into_distributed_megatron_full_precision", distributed_megatron_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_mixed_precision_into_distributed_megatron_full_precision", distributed_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_mixed_precision_into_distributed_megatron_mixed_precision", distributed_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_full_precision_into_distributed_megatron_mixed_precision", distributed_megatron_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_full_precision_into_distributed_megatron_full_precision", distributed_zero_megatron_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_mixed_precision_into_distributed_megatron_full_precision", distributed_zero_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_mixed_precision_into_distributed_megatron_mixed_precision", distributed_zero_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_full_precision_into_distributed_megatron_mixed_precision", distributed_zero_megatron_full_precision_lamb_path, ) # going to distributed zero+megatron trainer _distributed_run( load_checkpoint_file, "test_load_from_single_node_full_precision_into_distributed_zero_megatron_full_precision", single_node_full_precision_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_single_node_mixed_precision_into_distributed_zero_megatron_full_precision", single_node_mixed_precision_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_single_node_mixed_precision_into_distributed_zero_megatron_mixed_precision", single_node_mixed_precision_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_single_node_full_precision_into_distributed_zero_megatron_mixed_precision", single_node_full_precision_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_full_precision_into_distributed_zero_megatron_full_precision", distributed_zero_full_precision_lamb_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_mixed_precision_into_distributed_zero_megatron_full_precision", distributed_zero_mixed_precision_lamb_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_mixed_precision_into_distributed_zero_megatron_mixed_precision", distributed_zero_mixed_precision_lamb_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_full_precision_into_distributed_zero_megatron_mixed_precision", distributed_zero_full_precision_lamb_bart_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_full_precision_into_distributed_zero_megatron_full_precision", distributed_megatron_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_mixed_precision_into_distributed_zero_megatron_full_precision", distributed_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_mixed_precision_into_distributed_zero_megatron_mixed_precision", distributed_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_megatron_full_precision_into_distributed_zero_megatron_mixed_precision", distributed_megatron_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_full_precision_into_distributed_zero_megatron_full_precision", distributed_zero_megatron_full_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_mixed_precision_into_distributed_zero_megatron_full_precision", distributed_zero_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_mixed_precision_into_distributed_zero_megatron_mixed_precision", distributed_zero_megatron_mixed_precision_lamb_path, ) _distributed_run( load_checkpoint_file, "test_load_from_distributed_zero_megatron_full_precision_into_distributed_zero_megatron_mixed_precision", distributed_zero_megatron_full_precision_lamb_path, ) shutil.rmtree(checkpoint_dir)

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null

0

6

f74fc6b035940199a7b9518dd7958f38c4ea4cdc

443

py

Python

tests/test_main.py

ChickenProp/gragrapy

9c24719c6fc843df2c506388aa21e64617cccc8d

[ "MIT" ]

1

2017-04-30T18:26:19.000Z

tests/test_main.py

ChickenProp/gragrapy

9c24719c6fc843df2c506388aa21e64617cccc8d

[ "MIT" ]

4

2017-06-19T09:44:59.000Z

2017-06-19T09:58:57.000Z

tests/test_main.py

ChickenProp/gragrapy

9c24719c6fc843df2c506388aa21e64617cccc8d

[ "MIT" ]

null

from __future__ import (absolute_import, print_function, unicode_literals, division) from .context import gragrapy as gg from gragrapy.__main__ import parse_kwargs def test_parse_kwargs(): assert parse_kwargs([]) == {} assert parse_kwargs(['a=b', 'c=d']) == {'a': 'b', 'c': 'd'} assert parse_kwargs(['a=1', 'c=-5']) == {'a': 1, 'c': -5} assert parse_kwargs(['a=b=c', 'c=d']) == {'a': 'b=c', 'c': 'd'}

36.916667

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1

0

6

f77d32b42006912619abf517ddfd74f62f725987

37,933

py

Python

models/resnet_small.py

zhaoguangxiang/pytorch-cifar

509994fd2035009c7f53192a4c497b97f6295e6e

[ "MIT" ]

null

models/resnet_small.py

zhaoguangxiang/pytorch-cifar

509994fd2035009c7f53192a4c497b97f6295e6e

[ "MIT" ]

null

models/resnet_small.py

zhaoguangxiang/pytorch-cifar

509994fd2035009c7f53192a4c497b97f6295e6e

[ "MIT" ]

null

'''ResNet in PyTorch. For Pre-activation ResNet, see 'preact_resnet.py'. Reference: [1] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun Deep Residual Learning for Image Recognition. arXiv:1512.03385 resnet same as the origin paper ''' import torch import torch.nn as nn import torch.nn.functional as F import numpy as np class BasicBlock(nn.Module): expansion = 1 def __init__(self, in_planes, planes, stride=1): super(BasicBlock, self).__init__() self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False) self.bn1 = nn.BatchNorm2d(planes) self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=1, padding=1, bias=False) self.bn2 = nn.BatchNorm2d(planes) self.shortcut = nn.Sequential() if stride != 1 or in_planes != self.expansion*planes: self.shortcut = nn.Sequential( nn.Conv2d(in_planes, self.expansion*planes, kernel_size=1, stride=stride, bias=False), nn.BatchNorm2d(self.expansion*planes) ) def forward(self, x): out = F.relu(self.bn1(self.conv1(x))) out = self.bn2(self.conv2(out)) out += self.shortcut(x) out = F.relu(out) return out class Bottleneck(nn.Module): expansion = 4 def __init__(self, in_planes, planes, stride=1): super(Bottleneck, self).__init__() self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=1, bias=False) self.bn1 = nn.BatchNorm2d(planes) self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=stride, padding=1, bias=False) self.bn2 = nn.BatchNorm2d(planes) self.conv3 = nn.Conv2d(planes, self.expansion*planes, kernel_size=1, bias=False) self.bn3 = nn.BatchNorm2d(self.expansion*planes) self.shortcut = nn.Sequential() if stride != 1 or in_planes != self.expansion*planes: self.shortcut = nn.Sequential( nn.Conv2d(in_planes, self.expansion*planes, kernel_size=1, stride=stride, bias=False), nn.BatchNorm2d(self.expansion*planes) ) def forward(self, x): out = F.relu(self.bn1(self.conv1(x))) out = F.relu(self.bn2(self.conv2(out))) out = self.bn3(self.conv3(out)) out += self.shortcut(x) out = F.relu(out) return out class ResSmall(nn.Module): def __init__(self, block, num_blocks, num_classes=10): super(ResSmall, self).__init__() self.in_planes = 16 self.conv1 = nn.Conv2d(3, 16, kernel_size=3, stride=1, padding=1, bias=False) self.bn1 = nn.BatchNorm2d(16) self.layer1 = self._make_layer(block, 16, num_blocks[0], stride=1) self.layer2 = self._make_layer(block, 32, num_blocks[1], stride=2) self.layer3 = self._make_layer(block, 64, num_blocks[2], stride=2) self.linear = nn.Linear(64*block.expansion, num_classes) def _make_layer(self, block, planes, num_blocks, stride): strides = [stride] + [1]*(num_blocks-1) layers = [] for stride in strides: layers.append(block(self.in_planes, planes, stride)) self.in_planes = planes * block.expansion return nn.Sequential(*layers) def forward(self, x): out = F.relu(self.bn1(self.conv1(x))) out = self.layer1(out) out = self.layer2(out) out = self.layer3(out) out = F.avg_pool2d(out, 8) out = out.view(out.size(0), -1) out = self.linear(out) return out def ResSmall20(): return ResSmall(BasicBlock, [3, 3, 3]) def ResSmall32(): return ResSmall(BasicBlock, [5, 5, 5]) def ResSmall44(): return ResSmall(BasicBlock, [7, 7, 7]) def ResSmall56(): return ResSmall(BasicBlock, [9, 9, 9]) def ResSmall110(): return ResSmall(BasicBlock, [18, 18, 18]) class BaseBlock(nn.Module): expansion = 1 def __init__(self, in_planes, planes, stride=1): super(BaseBlock, self).__init__() self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False) self.bn1 = nn.BatchNorm2d(planes) self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=1, padding=1, bias=False) self.bn2 = nn.BatchNorm2d(planes) # self.shortcut = nn.Sequential() # if stride != 1 or in_planes != self.expansion * planes: # self.shortcut = nn.Sequential( # nn.Conv2d(in_planes, self.expansion * planes, kernel_size=1, stride=stride, bias=False), # nn.BatchNorm2d(self.expansion * planes) # ) def forward(self, x): # print('x size', x.size()) out = F.relu(self.bn1(self.conv1(x))) out = self.bn2(self.conv2(out)) # out += self.shortcut(x) # out = F.relu(out) return out class RfSmall(nn.Module): def __init__(self, block, num_blocks, args, num_classes=10): super(RfSmall, self).__init__() self.in_planes = 16 self.conv1 = nn.Conv2d(3, 16, kernel_size=3, stride=1, padding=1, bias=False) self.bn1 = nn.BatchNorm2d(16) self.num_blocks = num_blocks self.layer_list = nn.ModuleList() self.shortcut_list = nn.ModuleList() self.num_big_block = len(num_blocks) layer1, shortcut1 = self._make_layer(block, 16, num_blocks[0], stride=1) layer2, shortcut2 = self._make_layer(block, 32, num_blocks[1], stride=2) layer3, shortcut3 = self._make_layer(block, 64, num_blocks[2], stride=2) self.layer_list.extend([layer1, layer2, layer3]) self.shortcut_list.extend([shortcut1, shortcut2, shortcut3]) self.linear = nn.Linear(64*block.expansion, num_classes) def _make_layer(self, block, planes, num_blocks, stride): strides = [stride] + [1]*(num_blocks-1) layers = nn.ModuleList() shortcuts = nn.ModuleList() for stride in strides: # 64*64, 64*64 .. # 64*128(stride=2) 128*128 .. # 128*256(stride=2),256*256,.. # 256*512(stride=2) 512*512 .. layers.append(block(self.in_planes, planes, stride)) shortcut = nn.Sequential() if stride != 1 or self.in_planes != block.expansion * planes: shortcut = nn.Sequential( nn.Conv2d(self.in_planes, block.expansion * planes, kernel_size=1, stride=stride, bias=False), nn.BatchNorm2d(block.expansion * planes) ) shortcuts.append(shortcut) self.in_planes = planes * block.expansion return layers, shortcuts def forward(self, x): out = F.relu(self.bn1(self.conv1(x))) for i in range(self.num_big_block): for j in range(self.num_blocks[i]): # out = F.relu(self.bn1(self.conv1(x))) # out = self.bn2(self.conv2(out)) # out += self.shortcut(x) # out = F.relu(out) # return out layer_i = self.layer_list[i] shortcut_i = self.shortcut_list[i] res = shortcut_i[j](out) out = layer_i[j](out) out += res out = F.relu(out) out = F.avg_pool2d(out, 8) out = out.view(out.size(0), -1) # print('out size',out.size()) out = self.linear(out) return out def RfSmall56(args): return RfSmall(block=BaseBlock, num_blocks=[9, 9, 9], args=args) def RfSmall110(args): return RfSmall(block=BaseBlock, num_blocks=[18, 18, 18], args=args) class LmRnnSmall(nn.Module): # 只考虑分别设计三个rnn，然后bsz包含height 和width 的情况,层间使用残差连接。dim_type=channel,pass_hidden=0 def __init__(self, block, num_blocks, args, num_classes=10): super(LmRnnSmall, self).__init__() self.in_planes = 16 self.conv1 = nn.Conv2d(3, 16, kernel_size=3, stride=1, padding=1, bias=False) self.bn1 = nn.BatchNorm2d(16) self.num_blocks = num_blocks self.num_big_block = len(num_blocks) self.layer_list = nn.ModuleList() self.shortcut_list = nn.ModuleList() self.rnn_list = nn.ModuleList() self.m_out_list = nn.ModuleList() self.rnn_memory_size_list = [] self.args = args self.memory_type = args.memory_type # self.pass_hidden = args.pass_hidden self.rnn_ratio = args.rnn_ratio # self.dim_type = args.dim_type self.rnn_res = args.rnn_res layer1, shortcut1, rnn1, m_out_linear1, rnn_memory_size1 = self._make_layer(block, 16, num_blocks[0], stride=1) layer2, shortcut2, rnn2, m_out_linear2, rnn_memory_size2 = self._make_layer(block, 32, num_blocks[1], stride=2) layer3, shortcut3, rnn3, m_out_linear3, rnn_memory_size3 = self._make_layer(block, 64, num_blocks[2], stride=2) self.layer_list.extend([layer1, layer2, layer3]) self.shortcut_list.extend([shortcut1, shortcut2, shortcut3]) self.rnn_list.extend([rnn1, rnn2, rnn3]) self.m_out_list.extend([m_out_linear1, m_out_linear2, m_out_linear3]) self.rnn_memory_size_list.extend([rnn_memory_size1,rnn_memory_size2,rnn_memory_size3]) self.linear = nn.Linear(64*block.expansion, num_classes) def _make_layer(self, block, planes, num_blocks, stride): strides = [stride] + [1]*(num_blocks-1) layers = nn.ModuleList() shortcuts = nn.ModuleList() rnn_input_size = block.expansion * planes rnn_memory_size = int(self.args.rnn_ratio * block.expansion * planes) if self.memory_type == 'rnn': rnn = torch.nn.RNNCell(rnn_input_size, rnn_memory_size, bias=True, nonlinearity='tanh') elif self.memory_type == 'lstm': rnn = torch.nn.LSTMCell(rnn_input_size, rnn_memory_size, bias=True) elif self.memory_type == 'gru': rnn = torch.nn.GRUCell(rnn_input_size, rnn_memory_size, bias=True) else: rnn = None if self.rnn_ratio != 1: m_out_linear = nn.Linear(self.rnn_memory_size, rnn_input_size) else: m_out_linear = None for i in range(num_blocks): # 对rnn来说，第一个残差连接虽然等维度，考虑到其他都是传h0，我就把当做和其他大块间残差的一样的 stride = strides[i] # 16*16, 16*16 .. # 16*32(stride=2) 32*32 .. # 32*64(stride=2),64*64 .. layers.append(block(self.in_planes, planes, stride)) if i == 0: shortcut = nn.Sequential() if stride != 1 or self.in_planes != block.expansion * planes: shortcut = nn.Sequential( nn.Conv2d(self.in_planes, block.expansion * planes, kernel_size=1, stride=stride, bias=False), nn.BatchNorm2d(block.expansion * planes) ) shortcuts.append(shortcut) self.in_planes = planes * block.expansion return layers, shortcuts, rnn, m_out_linear,rnn_memory_size def set_m_rnn(self, x, rnn_memory_size): origin_bsz, channel, height, width, = x.size() bsz = height * width * origin_bsz if self.memory_type in ['rnn', 'gru']: hx = torch.zeros(bsz, rnn_memory_size).cuda().type_as(x) return hx if self.memory_type == 'lstm': hx = torch.zeros(bsz, rnn_memory_size).cuda().type_as(x) cx = torch.zeros(bsz, rnn_memory_size).cuda().type_as(x) return (hx, cx) def m_rnn(self, x, rnn, rnn_hidden): origin_bsz, channel, height, width = x.size() in_x = x.permute(0, 2, 3, 1).reshape(origin_bsz*height*width, channel) if self.memory_type in ['rnn', 'gru']: hx = rnn(in_x, rnn_hidden) m_output = hx # bsz, self.rnn_memory_size rnn_hidden = hx elif self.memory_type == 'lstm': hx, cx = rnn(in_x, rnn_hidden) m_output = hx # bsz, self.rnn_memory_size rnn_hidden = (hx, cx) return m_output, rnn_hidden def forward(self, x): out = F.relu(self.bn1(self.conv1(x))) # out size torch.Size([128, 16, 32, 32]) for i in range(self.num_big_block): for j in range(self.num_blocks[i]): layer_i = self.layer_list[i] shortcut_i = self.shortcut_list[i] # print('layer i=0,j=0', layer_i[j]) # print('big_block%d| layer%d| rnn%d: %s|' % (i, j, i, str(self.rnn_list[i]))) # print('out size', out.size()) if j == 0: res = shortcut_i[j](out) else: if j == 1: rnn_hidden = self.set_m_rnn(out, self.rnn_memory_size_list[i]) bsz, channel, height, width = out.size() m_out, rnn_hidden = self.m_rnn(out, self.rnn_list[i], rnn_hidden) if self.m_out_list[i] is not None: m_out = self.m_out_list[i](m_out) m_out = torch.reshape(m_out, (bsz, height, width, channel)).permute((0, 3, 1, 2)) res = m_out out = layer_i[j](out) # [bsz,dim,h,w] out += res out = F.relu(out) out = F.avg_pool2d(out, 8) out = out.view(out.size(0), -1) out = self.linear(out) return out def LmRnnSmall56(args): return LmRnnSmall(block=BaseBlock, num_blocks=[9, 9, 9], args=args) def LmRnnSmall110(args): return LmRnnSmall(block=BaseBlock, num_blocks=[18, 18, 18], args=args) class LmRnnKbSmallCIFAR10(nn.Module): # keep batch size same as origin, 32*32*16 ,16*16*32 8*8*64 as the input_size can pass hidden or not pass hidden def __init__(self, block, num_blocks, args, num_classes=10): super(LmRnnKbSmallCIFAR10, self).__init__() self.in_planes = 16 self.conv1 = nn.Conv2d(3, 16, kernel_size=3, stride=1, padding=1, bias=False) self.bn1 = nn.BatchNorm2d(16) self.num_blocks = num_blocks self.num_big_block = len(num_blocks) self.layer_list = nn.ModuleList() self.shortcut_list = nn.ModuleList() self.rnn_list = nn.ModuleList() self.m_out_list = nn.ModuleList() self.rnn_memory_size_list = [] self.convs_list = nn.ModuleList() self.deconvs_list = nn.ModuleList() self.args = args self.memory_type = args.memory_type self.pass_hidden = args.pass_hidden # self.keep_block_residual = args.keep_block_residual self.rnn_ratio = args.rnn_ratio self.num_downs = args.num_downs self.down_rate = 4 ** self.num_downs layer1, shortcut1, rnn1, m_out_linear1, rnn_memory_size1, convs1, deconvs1 = self._make_layer(block, 16, num_blocks[0], stride=1, fm=32) layer2, shortcut2, rnn2, m_out_linear2, rnn_memory_size2, convs2, deconvs2 = self._make_layer(block, 32, num_blocks[1], stride=2, fm=16) layer3, shortcut3, rnn3, m_out_linear3, rnn_memory_size3, convs3, deconvs3 = self._make_layer(block, 64, num_blocks[2], stride=2, fm=8) self.layer_list.extend([layer1, layer2, layer3]) self.shortcut_list.extend([shortcut1, shortcut2, shortcut3]) self.rnn_list.extend([rnn1, rnn2, rnn3]) self.m_out_list.extend([m_out_linear1, m_out_linear2, m_out_linear3]) self.rnn_memory_size_list.extend([rnn_memory_size1, rnn_memory_size2, rnn_memory_size3]) self.convs_list.extend([convs1, convs2, convs3]) self.deconvs_list.extend([deconvs1, deconvs2, deconvs3]) self.linear = nn.Linear(64*block.expansion, num_classes) def _make_layer(self, block, planes, num_blocks, stride, fm): strides = [stride] + [1]*(num_blocks-1) layers = nn.ModuleList() shortcuts = nn.ModuleList() cur_fig_size = int(fm * fm / self.down_rate) rnn_input_size = block.expansion * planes * cur_fig_size rnn_memory_size = int(self.args.rnn_ratio * block.expansion * planes * cur_fig_size) if self.memory_type == 'rnn': rnn = torch.nn.RNNCell(rnn_input_size, rnn_memory_size, bias=True, nonlinearity='tanh') elif self.memory_type == 'lstm': rnn = torch.nn.LSTMCell(rnn_input_size, rnn_memory_size, bias=True) elif self.memory_type == 'gru': rnn = torch.nn.GRUCell(rnn_input_size, rnn_memory_size, bias=True) else: rnn = None if self.rnn_ratio != 1: m_out_linear = nn.Linear(rnn_memory_size, rnn_input_size) else: m_out_linear = None if self.num_downs > 0: convs = nn.ModuleList() deconvs = nn.ModuleList() for j in range(self.num_downs): convs.append(nn.Conv2d(in_channels=block.expansion*planes, out_channels=block.expansion*planes, kernel_size=3, stride=2, padding=1)) deconvs.append(nn.ConvTranspose2d(block.expansion*planes, block.expansion*planes, kernel_size=3, stride=2, padding=1)) else: convs=None deconvs=None for i in range(num_blocks): # 对rnn来说，第一个残差连接虽然等维度，考虑到其他都是传h0，我就把当做和其他大块间残差的一样的 stride = strides[i] # 16*16, 16*16 .. # 16*32(stride=2) 32*32 .. # 32*64(stride=2),64*64 .. layers.append(block(self.in_planes, planes, stride)) if i == 0: if not self.pass_hidden: shortcut = nn.Sequential() if stride != 1 or self.in_planes != block.expansion * planes: shortcut = nn.Sequential( nn.Conv2d(self.in_planes, block.expansion * planes, kernel_size=1, stride=stride, bias=False), nn.BatchNorm2d(block.expansion * planes) ) shortcuts.append(shortcut) else: # if self.keep_block_residual: # shortcut = nn.Sequential() # if stride != 1 or self.in_planes != block.expansion * planes: # shortcut = nn.Sequential( # nn.Conv2d(self.in_planes, block.expansion * planes, kernel_size=1, stride=stride, # bias=False), # nn.BatchNorm2d(block.expansion * planes) # ) # shortcuts.append(shortcut) memory_shortcut = nn.Sequential() if stride != 1 or self.in_planes != block.expansion * planes: memory_shortcut = nn.Sequential(nn.Linear(rnn_memory_size*2, rnn_memory_size), nn.BatchNorm2d(rnn_memory_size)) shortcuts.append(memory_shortcut) self.in_planes = planes * block.expansion return layers, shortcuts, rnn, m_out_linear, rnn_memory_size, convs, deconvs def set_m_rnn(self, x, rnn_memory_size): # origin_bsz, channel, height, width, = x.size() # bsz = height * width * origin_bsz bsz = x.size()[0] if self.memory_type in ['rnn', 'gru']: hx = torch.zeros(bsz, rnn_memory_size).cuda().type_as(x) return hx if self.memory_type == 'lstm': hx = torch.zeros(bsz, rnn_memory_size).cuda().type_as(x) cx = torch.zeros(bsz, rnn_memory_size).cuda().type_as(x) return (hx, cx) def m_rnn(self, x, cur_i, rnn_hidden): input_size_list = [] rnn = self.rnn_list[cur_i] if self.convs_list: # 可能四层dim变长的deconv更合理 convs = self.convs_list[cur_i] for j in range(self.num_downs): input_size_list.append(x.size()) x = convs[j](x) bsz, channel, new_height, new_width = x.size() x = x.permute([0, 2, 3, 1]).reshape(bsz, int(self.rnn_memory_size_list[cur_i]/ self.args.rnn_ratio)) # bsz, new_height * new_width * channel if self.memory_type in ['rnn', 'gru']: hx = rnn(x, rnn_hidden) m_output = hx # bsz, self.rnn_memory_size rnn_hidden = hx elif self.memory_type == 'lstm': hx, cx = rnn(x, rnn_hidden) m_output = hx # bsz, self.rnn_memory_size rnn_hidden = (hx, cx) if self.m_out_list[cur_i] is not None: m_output = self.m_out_list[cur_i](m_output) m_output = torch.reshape(m_output, (bsz, new_height, new_height, channel,)).permute((0, 3, 1, 2)) if self.deconvs_list: deconvs = self.deconvs_list[cur_i] for j in range(self.num_downs): m_output = deconvs[j](m_output, output_size=input_size_list[-j-1]) return m_output, rnn_hidden def forward(self, x): out = F.relu(self.bn1(self.conv1(x))) # out size torch.Size([128, 16, 32, 32]) rnn_hidden = 0 # 0 to error for i in range(self.num_big_block): for j in range(self.num_blocks[i]): layer_i = self.layer_list[i] shortcut_i = self.shortcut_list[i] print('layer i=0,j=0', layer_i[j]) print('big_block%d| layer%d| rnn%d: %s|' % (i, j, i, str(self.rnn_list[i]))) print('out size', out.size()) if not self.pass_hidden or i == 0: if j == 0: res = shortcut_i[j](out) else: if j == 1: rnn_hidden = self.set_m_rnn(out, self.rnn_memory_size_list[i]) m_out, rnn_hidden = self.m_rnn(out, i, rnn_hidden) res = m_out if self.pass_hidden and i > 0: if j == 0: print('shortcut_i[j]', shortcut_i[j]) rnn_hidden = shortcut_i[j](rnn_hidden) m_out, rnn_hidden = self.m_rnn(out, i, rnn_hidden) res = m_out out = layer_i[j](out) # [bsz,dim,h,w] out += res out = F.relu(out) out = F.avg_pool2d(out, 8) out = out.view(out.size(0), -1) out = self.linear(out) return out def LmRnnKbSmall56CIFAR10(args): return LmRnnKbSmallCIFAR10(block=BaseBlock, num_blocks=[9, 9, 9], args=args) def LmRnnKbSmall110CIFAR10(args): return LmRnnKbSmallCIFAR10(block=BaseBlock, num_blocks=[18, 18, 18], args=args) class DepthTransposeCNN(nn.Module): def __init__(self,in_dim, out_dim, kernel_size=4, is_out=False): super(DepthTransposeCNN, self).__init__() self.nets = nn.ModuleList() self.is_out = is_out self.nets.extend([nn.ConvTranspose2d(in_channels=in_dim, out_channels=in_dim, kernel_size=kernel_size, stride=2, padding=1, groups=in_dim), nn.ConvTranspose2d(in_channels=in_dim, out_channels=out_dim, kernel_size=1, stride=1, padding=0, bias=False)]) if not is_out: self.nets.extend([nn.BatchNorm2d(in_dim), nn.ReLU(True), nn.BatchNorm2d(out_dim), nn.ReLU(True)]) def forward(self, x, output_size): bsz, dim, h, w = output_size if self.is_out: x = self.nets[0](x, output_size=[bsz, dim * 2, h, w]) x = self.nets[1](x, output_size=output_size) else: x = self.nets[0](x, output_size=[bsz, dim * 2, h, w]) x = self.nets[2](x) x = self.nets[3](x) x = self.nets[1](x, output_size=output_size) x = self.nets[4](x) x = self.nets[5](x) return x class TransposeCNN(nn.Module): def __init__(self, in_dim, out_dim, kernel_size=4, is_out=False): super(TransposeCNN, self).__init__() self.nets = nn.ModuleList() self.is_out = is_out self.nets.extend([nn.ConvTranspose2d(in_channels=in_dim, out_channels=out_dim, kernel_size=kernel_size, stride=2, padding=1), ]) if not is_out: self.nets.extend([nn.BatchNorm2d(out_dim), nn.ReLU(True)]) def forward(self, x, output_size): if self.is_out: x = self.nets[0](x, output_size=output_size) else: x = self.nets[0](x, output_size=output_size) x = self.nets[1](x) x = self.nets[2](x) return x class LmRnnConsistentSmallCIFAR10(nn.Module): # keep batch size same as origin, 32*32*16 ,16*16*32 8*8*64 as the input_size can pass hidden or not pass hidden def __init__(self, block, num_blocks, args, num_classes=10): super(LmRnnConsistentSmallCIFAR10, self).__init__() self.in_planes = 16 self.conv1 = nn.Conv2d(3, 16, kernel_size=3, stride=1, padding=1, bias=False) self.bn1 = nn.BatchNorm2d(16) self.num_blocks = num_blocks self.num_big_block = len(num_blocks) self.layer_list = nn.ModuleList() self.shortcut_list = nn.ModuleList() self.rnn_list = nn.ModuleList() self.m_out_list = nn.ModuleList() self.rnn_memory_size_list = [] self.convs_list = nn.ModuleList() self.deconvs_list = nn.ModuleList() self.args = args self.memory_type = args.memory_type self.rnn_ratio = args.rnn_ratio self.conv_activate = args.conv_activate self.memory_before = args.memory_before self.depth_separate = args.depth_separate self.consistent_separate_rnn = args.consistent_separate_rnn self.dcgan_init = args.dcgan_init self.dcgan_kernel= args.dcgan_kernel self.dcgan_share_conv = args.dcgan_share_conv layer1, shortcut1, rnn1, m_out_linear1, rnn_memory_size1, convs1, deconvs1 = self._make_layer(block, 16, num_blocks[0], stride=1, fm=32,) layer2, shortcut2, rnn2, m_out_linear2, rnn_memory_size2, convs2, deconvs2 = self._make_layer(block, 32, num_blocks[1], stride=2, fm=16,) layer3, shortcut3, rnn3, m_out_linear3, rnn_memory_size3, convs3, deconvs3 = self._make_layer(block, 64, num_blocks[2], stride=2, fm=8,) self.layer_list.extend([layer1, layer2, layer3]) self.shortcut_list.extend([shortcut1, shortcut2, shortcut3]) if not self.consistent_separate_rnn: rnn2 = rnn1 rnn3 = rnn1 self.rnn_list.extend([rnn1, rnn2, rnn3]) if not self.consistent_separate_rnn: m_out_linear2 = m_out_linear1 m_out_linear3 = m_out_linear1 self.m_out_list.extend([m_out_linear1, m_out_linear2, m_out_linear3]) self.rnn_memory_size_list.extend([rnn_memory_size1, rnn_memory_size2, rnn_memory_size3]) if self.dcgan_share_conv: # 32*32*16, 16*16*32, 8*8*64, 4*4*128,2*2*256,1*1*512 # 1*1*512, 2*2*256, 4*4*128, 8*8*64, 16*16*32, 32*32*16, dim_list = [512, 256, 128, 64, 32, 16] convs2 = convs1[1:] convs3 = convs1[2:] deconvs2 = deconvs1[:-2].append(DepthTransposeCNN(in_dim=dim_list[-3], out_dim=dim_list[-2], kernel_size=self.dcgan_kernel, is_out=True) if self.depth_separate else TransposeCNN(in_dim=dim_list[-3], out_dim=dim_list[-2], kernel_size=self.dcgan_kernel, is_out=True)) deconvs3 = deconvs2[:-3].append(DepthTransposeCNN(in_dim=dim_list[-4], out_dim=dim_list[-3], kernel_size=self.dcgan_kernel, is_out=True) if self.depth_separate else TransposeCNN(in_dim=dim_list[-4], out_dim=dim_list[-3], kernel_size=self.dcgan_kernel, is_out=True)) self.convs_list.extend([convs1, convs2, convs3]) self.deconvs_list.extend([deconvs1, deconvs2, deconvs3]) if self.dcgan_init: self.deconvs_list.apply(self.weight_init) self.convs_list.apply(self.weight_init) self.linear = nn.Linear(64*block.expansion, num_classes) def _make_layer(self, block, planes, num_blocks, stride, fm, ): strides = [stride] + [1]*(num_blocks-1) layers = nn.ModuleList() shortcuts = nn.ModuleList() down_rate = fm num_downs = int(np.log(fm)/np.log(2)) cur_fig_size = int(fm * fm / down_rate) # build rnn rnn_input_size = block.expansion * planes * cur_fig_size rnn_memory_size = int(self.args.rnn_ratio * block.expansion * planes * cur_fig_size) assert rnn_memory_size == 512 * self.rnn_ratio if self.consistent_separate_rnn or fm ==32: if self.memory_type == 'rnn': rnn = torch.nn.RNNCell(rnn_input_size, rnn_memory_size, bias=True, nonlinearity='tanh') elif self.memory_type == 'lstm': rnn = torch.nn.LSTMCell(rnn_input_size, rnn_memory_size, bias=True) elif self.memory_type == 'gru': rnn = torch.nn.GRUCell(rnn_input_size, rnn_memory_size, bias=True) else: rnn = None # rnn out linear if self.rnn_ratio != 1: m_out_linear = nn.Linear(rnn_memory_size, rnn_input_size) else: m_out_linear = None else: rnn = None m_out_linear = None if self.conv_activate == 'lrelu': conv_activation = nn.LeakyReLU(True) elif self.conv_activate == 'relu': conv_activation = nn.ReLU(True) if num_downs > 0 or (self.dcgan_share_conv and fm != 32): dcgan_kernel=self.dcgan_kernel convs = nn.ModuleList() deconvs = nn.ModuleList() output_dim = block.expansion*planes for j in range(num_downs): output_dim = output_dim * 2 # print('output_dim:', output_dim) if j == num_downs-1: if self.depth_separate: cur_conv = nn.Sequential(nn.Conv2d(in_channels=int(output_dim / 2), out_channels=int(output_dim / 2), kernel_size=dcgan_kernel, stride=2, padding=1, groups=int(output_dim / 2)), nn.Conv2d(in_channels=int(output_dim / 2), out_channels=output_dim, kernel_size=1, stride=1, padding=0, bias=False)) else: cur_conv = nn.Sequential(nn.Conv2d(in_channels=int(output_dim/2), out_channels=output_dim, kernel_size=dcgan_kernel, stride=2, padding=1)) else: if self.depth_separate: cur_conv = nn.Sequential(nn.Conv2d(in_channels=int(output_dim / 2), out_channels=int(output_dim / 2), kernel_size=dcgan_kernel, stride=2, padding=1, groups=int(output_dim / 2)), nn.BatchNorm2d(int(output_dim / 2)), nn.ReLU(True), nn.Conv2d(in_channels=int(output_dim / 2), out_channels=output_dim, kernel_size=1, stride=1, padding=0, bias=False), nn.BatchNorm2d(output_dim), nn.ReLU(True)) else: cur_conv = nn.Sequential(nn.Conv2d(in_channels=int(output_dim/2), out_channels=output_dim, kernel_size=dcgan_kernel, stride=2, padding=1), nn.BatchNorm2d(output_dim), conv_activation) convs.append(cur_conv) for j in range(num_downs): output_dim = int(output_dim / 2) # print('output_dim:',output_dim) if j == num_downs-1: is_out = True else: is_out = False if self.depth_separate: cur_deconv = DepthTransposeCNN(in_dim=output_dim * 2, out_dim=output_dim, kernel_size=self.dcgan_kernel, is_out=is_out) else: cur_deconv = TransposeCNN(in_dim=output_dim * 2, out_dim=output_dim, kernel_size=self.dcgan_kernel, is_out=is_out) deconvs.append(cur_deconv) else: convs=None deconvs=None for i in range(num_blocks): stride = strides[i] # 16*16, 16*16 .. 16*32(stride=2) 32*32 .. 32*64(stride=2),64*64 .. layers.append(block(self.in_planes, planes, stride)) if i == 0: shortcut = nn.Sequential() if stride != 1 or self.in_planes != block.expansion * planes: shortcut = nn.Sequential( nn.Conv2d(self.in_planes, block.expansion * planes, kernel_size=1, stride=stride, bias=False), nn.BatchNorm2d(block.expansion * planes) ) shortcuts.append(shortcut) self.in_planes = planes * block.expansion return layers, shortcuts, rnn, m_out_linear, rnn_memory_size, convs, deconvs def weight_init(self, m): classname = m.__class__.__name__ if classname.find('Conv') != -1: nn.init.normal_(m.weight.data, 0.0, 0.02) elif classname.find('BatchNorm') != -1: nn.init.normal_(m.weight.data, 1.0, 0.02) nn.init.constant_(m.bias.data, 0) return m def init_rnn_state(self, x, rnn_memory_size): # origin_bsz, channel, height, width, = x.size() # bsz = height * width * origin_bsz bsz = x.size()[0] if self.memory_type in ['rnn', 'gru']: hx = torch.zeros(bsz, rnn_memory_size).cuda().type_as(x) return hx if self.memory_type == 'lstm': hx = torch.zeros(bsz, rnn_memory_size).cuda().type_as(x) cx = torch.zeros(bsz, rnn_memory_size).cuda().type_as(x) return (hx, cx) def m_rnn(self, x, cur_i, rnn_hidden): input_size_list = [] rnn = self.rnn_list[cur_i] num_downs = 5 - cur_i if self.convs_list: # 5,4,3,的deconv使得dim一致 convs = self.convs_list[cur_i] for j in range(num_downs): input_size_list.append(x.size()) # [128, 16, 32, 32] # [128,32,16,16] # [128,64, 8, 8] # [128,128,4,4] # [128, 256, 2, 2] # [128, 512, 1, 1] x = convs[j](x) bsz, channel, new_height, new_width = x.size() # print("self.convs_list[cur_i]",self.convs_list[cur_i]) # print('after conv x size',x.size()) x = x.permute([0, 2, 3, 1]).reshape(bsz, int(self.rnn_memory_size_list[cur_i] / self.args.rnn_ratio)) # bsz, new_height * new_width * channel if self.memory_type in ['rnn', 'gru']: hx = rnn(x, rnn_hidden) m_output = hx # bsz, self.rnn_memory_size rnn_hidden = hx elif self.memory_type == 'lstm': hx, cx = rnn(x, rnn_hidden) m_output = hx # bsz, self.rnn_memory_size rnn_hidden = (hx, cx) if self.m_out_list[cur_i] is not None: m_output = self.m_out_list[cur_i](m_output) m_output = torch.reshape(m_output, (bsz, new_height, new_height, channel,)).permute((0, 3, 1, 2)) if self.deconvs_list: deconvs = self.deconvs_list[cur_i] for j in range(num_downs): # print('j:%d deconv_in: %s| deconv j:%s' % (j, m_output.size(),deconvs[j])) m_output = deconvs[j](m_output, output_size=input_size_list[-j - 1]) return m_output, rnn_hidden def forward(self, x): out = F.relu(self.bn1(self.conv1(x))) # out size torch.Size([128, 16, 32, 32]) [128,32,16,16] rnn_hidden = 0 # 0 to error for i in range(self.num_big_block): for j in range(self.num_blocks[i]): layer_i = self.layer_list[i] # shortcut_i = self.shortcut_list[i] # print('layer i=0,j=0', layer_i[j]) # print('big_block%d| layer%d| out size%s|' % (i, j, out.size())) if i == 0 and j == 0: rnn_hidden = self.init_rnn_state(out, self.rnn_memory_size_list[i]) if self.memory_before: if j == 0: m_in = self.shortcut_list[i][j](out) else: m_in =out m_out, rnn_hidden = self.m_rnn(m_in, i, rnn_hidden) res = m_out out = layer_i[j](out) # [bsz,dim,h,w] out += res out = F.relu(out) else: out = layer_i[j](out) m_out, rnn_hidden = self.m_rnn(out, i, rnn_hidden) out += m_out out = F.avg_pool2d(out, 8) out = out.view(out.size(0), -1) out = self.linear(out) return out def LmRnnConsistentSmall56CIFAR10(args): return LmRnnConsistentSmallCIFAR10(block=BaseBlock, num_blocks=[9, 9, 9], args=args) def test(): net = ResSmall20() y = net(torch.randn(1, 3, 32, 32)) print(y.size()) # test()

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null

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null

0

6

f79cd10364a46270c3d2e287240313f54b9a12a9

1,253

py

Python

Data Scraping/dist_code_extractor.py

jeevannavar/Case-Pendency

338c7d8edab6adec97650d8882e18105bcdbd8ba

[ "MIT" ]

null

Data Scraping/dist_code_extractor.py

jeevannavar/Case-Pendency

338c7d8edab6adec97650d8882e18105bcdbd8ba

[ "MIT" ]

null

Data Scraping/dist_code_extractor.py

jeevannavar/Case-Pendency

338c7d8edab6adec97650d8882e18105bcdbd8ba

[ "MIT" ]

null

string = '<option value="1" >Malda</option><option value="2" >Hooghly</option><option value="3" >Calcutta</option><option value="4" >Jalpaiguri</option><option value="6" >Coochbehar</option><option value="7" >Paschim Medinpur</option><option value="8" >Birbhum</option><option value="9" >Purba Medinipur</option><option value="10" >Purulia</option><option value="11" >Howrah</option><option value="12" >Murshidabad</option><option value="13" >South Dinajpur</option><option value="14" >North Twenty Four Parganas</option><option value="17" >Darjeeling</option><option value="18" >Purba Bardhaman</option><option value="19" >Bankura</option><option value="20" >South Twenty Four Parganas</option><option value="21" >North Dinajpur</option><option value="22" >Nadia</option><option value="23" >kalimpong</option><option value="24" >Paschim Bardhaman</option><option value="25" >Jhargram</option> </select>' separated = string.split("</option>") codes = [each[15:].split('" >') for each in separated[:-1]] print(codes) #districts = [each[1] for each in codes] #codes = [each[0] for each in codes] codes = [",".join([each[1],each[0]]) for each in codes] print(len(codes)) print("\n".join(sorted(codes))) #print("\n".join(districts))

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6

f79e814b239a077552d880188a2a383279126415

3,445

py

Python

tests/test_methods_datetime.py

vmstarchenko/sxml

3b6fc3a89f404acfe298491555d15df269125e8f

[ "MIT" ]

null

tests/test_methods_datetime.py

vmstarchenko/sxml

3b6fc3a89f404acfe298491555d15df269125e8f

[ "MIT" ]

null

tests/test_methods_datetime.py

vmstarchenko/sxml

3b6fc3a89f404acfe298491555d15df269125e8f

[ "MIT" ]

null

import datetime import textwrap import sxml import pytest from freezegun import freeze_time UTC = datetime.timezone.utc UTC4 = datetime.timezone(datetime.timedelta(hours=4)) UTC_4 = datetime.timezone(datetime.timedelta(hours=-4)) def test_strftime(): parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.strftime ''')) assert parse(datetime.datetime(2000, 1, 2, 3, 4, 5)) == '2000-01-02T03:04:05' parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.strftime format: '%Y/%m/%d' ''')) assert parse(datetime.datetime(2000, 1, 2, 3, 4, 5)) == '2000/01/02' def test_fromtimestamp(): parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.fromtimestamp ''')) assert parse(946771445) == datetime.datetime(2000, 1, 2, 3, 4, 5) parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.fromtimestamp ''')) assert parse('946771445.000') == datetime.datetime(2000, 1, 2, 3, 4, 5) @freeze_time('2000-01-02T03:04:05+0000') def test_parse(): parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.parse ''')) assert parse('2000-01-02T03:04:05+0000') == datetime.datetime(2000, 1, 2, 3, 4, 5, tzinfo=UTC) parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.parse ''')) assert parse('Now') == datetime.datetime(2000, 1, 2, 3, 4, 5, tzinfo=UTC) parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.parse timezone: '+0400' ''')) assert parse('Now GMT') == datetime.datetime(2000, 1, 2, 3, 4, 5, tzinfo=UTC) @freeze_time(datetime.datetime(2000, 1, 2, 3, 4, 5, tzinfo=UTC_4)) def test_parse_other_timezone(): parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.parse ''')) assert parse('2000-01-02T03:04:05+0000') == datetime.datetime(2000, 1, 2, 3, 4, 5, tzinfo=UTC) parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.parse ''')) assert parse('Now') == datetime.datetime(2000, 1, 2, 7, 4, 5, tzinfo=UTC) parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.parse timezone: '+0800' ''')) assert parse('Now') == datetime.datetime(2000, 1, 2, 7, 4, 5, tzinfo=UTC) @freeze_time(datetime.datetime(2000, 1, 2, 3, 4, 5, tzinfo=UTC)) def test_parse_other_base(): parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.parse now: '2001-02-03T04:05:06' ''')) assert parse('Now') == datetime.datetime(2001, 2, 3, 4, 5, 6, tzinfo=UTC) parse = sxml.HtmlPipeline([{ '$apply': 'datetime.parse', 'now': datetime.datetime(2001, 2, 3, 4, 5, 6) }]) assert parse('Now') == datetime.datetime(2001, 2, 3, 4, 5, 6, tzinfo=UTC) parse = sxml.HtmlPipeline.from_string(textwrap.dedent(r''' $chain: - $apply: datetime.parse now: !Opt now_option ''')) now = datetime.datetime(2003, 2, 3, 4, 5, 6, tzinfo=UTC) assert parse('Now', options={'now_option': now}) == now

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null

0

1

0

null

0

6

e3980c0877ddcb73e92a28834bad84aed6d18bc3

21

py

Python

tools/__init__.py

GreenBlitz/Rapid-React-Vision

a30793e176ef6f2bdc73f12535645ef2ec57126a

[ "Apache-2.0" ]

6

2019-12-17T03:16:38.000Z

2020-07-10T10:45:24.000Z

tools/__init__.py

GreenBlitz/Rapid-React-Vision

a30793e176ef6f2bdc73f12535645ef2ec57126a

[ "Apache-2.0" ]

5

2021-03-19T01:10:11.000Z

2022-02-10T13:37:29.000Z

sys_app/models/__init__.py

sf0402/horse-admin

dd3f5c2d317763a1daeef40ce7833371e6ed5ce0

[ "MIT" ]

1

2020-11-10T07:54:52.000Z

from .system import *

21

0.761905

3

21

5.333333

1

0

0.142857

21

1

21

0.888889

0

1

0

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null

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1

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null

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1

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1

0

1

0

6

e3c31ca98eab08a674c1b9243ff41d3a6608b725

43

py

Python

Tests/Runnable2/r_classmodname_t.py

jwilk/Pyrex

83dfbae1261788933472e3f9c501ad74c61a37c5

[ "Apache-2.0" ]

5

2019-05-26T20:48:36.000Z

2021-07-09T01:38:38.000Z

Tests/Runnable2/r_classmodname_t.py

jwilk/Pyrex

83dfbae1261788933472e3f9c501ad74c61a37c5

[ "Apache-2.0" ]

null

Tests/Runnable2/r_classmodname_t.py

jwilk/Pyrex

83dfbae1261788933472e3f9c501ad74c61a37c5

[ "Apache-2.0" ]

1

2022-02-10T07:14:58.000Z

from r_classmodname import Spam print Spam

14.333333

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7

43

5.142857

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0

0.139535

43

2

32

21.5

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null

0

0.5

null

0.5

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1

0

null

0

1

0

1

0

1

0

6

e3d3f61891e930427ed79848960dfa5a1cfa408c

112

py

Python

normflowpy/flows/helpers.py

haihabi/NormFlowPy

a15ea6a704254a925f25dc94b22459ca2e0beaf5

[ "MIT" ]

null

normflowpy/flows/helpers.py

haihabi/NormFlowPy

a15ea6a704254a925f25dc94b22459ca2e0beaf5

[ "MIT" ]

null

normflowpy/flows/helpers.py

haihabi/NormFlowPy

a15ea6a704254a925f25dc94b22459ca2e0beaf5

[ "MIT" ]

null

import torch def safe_log(x: torch.Tensor, eps=1e-22) -> torch.Tensor: return torch.log(x.clamp(min=eps))

18.666667

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null

0

1

0

null

0

1

0

1

0

6

5403922e603ba4720ff05ba55d5ba44f1b460afa

42

py

Python

topgun/models/__init__.py

muntumdwara/TopGun

fc253faa8ac0a7c9b7d000c2ea018bba9c584d27

[ "MIT" ]

null

topgun/models/__init__.py

muntumdwara/TopGun

fc253faa8ac0a7c9b7d000c2ea018bba9c584d27

[ "MIT" ]

null

topgun/models/__init__.py

muntumdwara/TopGun

fc253faa8ac0a7c9b7d000c2ea018bba9c584d27

[ "MIT" ]

null

from .ddm import dividend_discount_models

21

41

0.880952

6

42

5.833333

1

0

0.095238

42

2

41

21

0.921053

0

1

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true

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1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

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6

5403f41fc2f077dfdf1769dbfd8692016c996232

446

py

Python

bunny/api/models/__init__.py

senpai-development/SenpaiSlasher

89842e584b4cd60731ce9c43315c08b02a8dc8e3

[ "MIT" ]

null

bunny/api/models/__init__.py

senpai-development/SenpaiSlasher

89842e584b4cd60731ce9c43315c08b02a8dc8e3

[ "MIT" ]

null

bunny/api/models/__init__.py

senpai-development/SenpaiSlasher

89842e584b4cd60731ce9c43315c08b02a8dc8e3

[ "MIT" ]

1

2021-10-31T02:40:03.000Z

from .channel import * # noqa: F401 F403 from .guild import * # noqa: F401 F403 from .intents import * # noqa: F401 F403 from .member import * # noqa: F401 F403 from .message import * # noqa: F401 F403 from .misc import * # noqa: F401 F403 from .presence import * # noqa: F401 F403 from .role import * # noqa: F401 F403 from .team import * # noqa: F401 F403 from .user import * # noqa: F401 F403 from .voice import * # noqa: F401 F403

37.166667

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0.363036

0.508251

0.653465

0.726073

0

0.190202

0.221973

446

11

43

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0.682997

0.392377

0

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true

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null

0

1

0

1

0

1

0

6

5410396c26149a6538e9eb2cf4e15c4e5c951483

2,988

py

Python

python_bindings/correctness/tuple_select.py

rafaelravedutti/Halide

9417210e7eca49b224028834dbed09cb2d62b1cd

[ "Apache-2.0" ]

107

2018-08-16T05:32:52.000Z

2022-02-11T19:44:25.000Z

python_bindings/correctness/tuple_select.py

rafaelravedutti/Halide

9417210e7eca49b224028834dbed09cb2d62b1cd

[ "Apache-2.0" ]

79

2019-02-22T03:27:45.000Z

2022-02-24T23:03:28.000Z

python_bindings/correctness/tuple_select.py

rafaelravedutti/Halide

9417210e7eca49b224028834dbed09cb2d62b1cd

[ "Apache-2.0" ]

16

2018-08-21T09:45:13.000Z

2021-12-11T03:32:15.000Z

import halide as hl import numpy as np def test_tuple_select(): x = hl.Var('x') y = hl.Var('y') # ternary tuple_select with Expr condition f = hl.Func('f') f[x, y] = hl.tuple_select(x + y < 30, (x, y), (x-1, y-2)) a, b = f.realize(200, 200) for xx in range(a.height()): for yy in range(a.width()): correct_a = xx if xx + yy < 30 else xx-1 correct_b = yy if xx + yy < 30 else yy-2 assert a[xx, yy] == correct_a assert b[xx, yy] == correct_b # ternary tuple_select with Tuple condition f = hl.Func('f') f[x, y] = hl.tuple_select((x < 30, y < 30), (x, y), (x-1, y-2)) a, b = f.realize(200, 200) for xx in range(a.height()): for yy in range(a.width()): correct_a = xx if xx < 30 else xx-1 correct_b = yy if yy < 30 else yy-2 assert a[xx, yy] == correct_a assert b[xx, yy] == correct_b # multiway tuple_select with Expr condition f = hl.Func('f') f[x, y] = hl.tuple_select(x + y < 30, (x, y), x + y < 100, (x-1, y-2), (x-100, y-200)) a, b = f.realize(200, 200) for xx in range(a.height()): for yy in range(a.width()): correct_a = xx if xx + yy < 30 else xx-1 if xx + yy < 100 else xx - 100 correct_b = yy if xx + yy < 30 else yy-2 if xx + yy < 100 else yy - 200 assert a[xx, yy] == correct_a assert b[xx, yy] == correct_b # multiway tuple_select with Tuple condition f = hl.Func('f') f[x, y] = hl.tuple_select((x < 30, y < 30), (x, y), (x < 100, y < 100), (x-1, y-2), (x-100, y-200)) a, b = f.realize(200, 200) for xx in range(a.height()): for yy in range(a.width()): correct_a = xx if xx < 30 else xx-1 if xx < 100 else xx - 100 correct_b = yy if yy < 30 else yy-2 if yy < 100 else yy - 200 assert a[xx, yy] == correct_a assert b[xx, yy] == correct_b # Failure case: mixing Expr and Tuple in multiway try: f = hl.Func('f') f[x, y] = hl.tuple_select((x < 30, y < 30), (x, y), x + y < 100, (x-1, y-2), (x-100, y-200)) except RuntimeError as e: assert 'tuple_select() may not mix Expr and Tuple for the condition elements.' in str(e) else: assert False, 'Did not see expected exception!' # Failure case: Tuples of mixed sizes try: f = hl.Func('f') f[x, y] = hl.tuple_select((x < 30, y < 30), (x, y, 0), (1, 2, 3, 4)) except RuntimeError as e: assert 'tuple_select() requires all Tuples to have identical sizes' in str(e) else: assert False, 'Did not see expected exception!' if __name__ == "__main__": test_tuple_select()

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6

581ec34406a8d3ce10fc41df03681e89b51b67ea

34

py

Python

Programmers/src/12925/solution.py

lstar2397/algorithms

686ea882079e26111f86b5bd5a7ab1b14ccf0fa2

[ "MIT" ]

null

Programmers/src/12925/solution.py

lstar2397/algorithms

686ea882079e26111f86b5bd5a7ab1b14ccf0fa2

[ "MIT" ]

null

Programmers/src/12925/solution.py

lstar2397/algorithms

686ea882079e26111f86b5bd5a7ab1b14ccf0fa2

[ "MIT" ]

null

def solution(s): return int(s)

17

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6

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null

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1

0

1

0

6

5861b0edf72a3563c5f7e40f8c6bf4f94a4c77d8

1,770

py

Python

reversi/strategies/coordinator/__init__.py

y-tetsu/othello

73eabfe22d6b44bbfa0b436e6287e3e7356620f4

[ "MIT" ]

10

2020-07-24T22:04:51.000Z

2022-03-25T06:09:48.000Z

reversi/strategies/coordinator/__init__.py

y-tetsu/othello

73eabfe22d6b44bbfa0b436e6287e3e7356620f4

[ "MIT" ]

12

2021-04-30T09:53:18.000Z

2022-02-25T04:16:02.000Z

reversi/strategies/coordinator/__init__.py

y-tetsu/othello

73eabfe22d6b44bbfa0b436e6287e3e7356620f4

[ "MIT" ]

1

2021-11-25T13:12:32.000Z

from ...strategies.coordinator.scorer import TableScorer, PossibilityScorer, OpeningScorer, WinLoseScorer, NumberScorer, EdgeScorer, CornerScorer, BlankScorer, EdgeCornerScorer # noqa: E501 from ...strategies.coordinator.selector import Selector, Selector_W from ...strategies.coordinator.orderer import Orderer, Orderer_B, Orderer_C, Orderer_P, Orderer_BC, Orderer_CB, Orderer_PCB from ...strategies.coordinator.evaluator import Evaluator, Evaluator_T, Evaluator_P, Evaluator_O, Evaluator_W, Evaluator_N, Evaluator_N_Fast, Evaluator_E, Evaluator_C, Evaluator_B, Evaluator_Ec, Evaluator_TP, Evaluator_TPO, Evaluator_NW, Evaluator_PW, Evaluator_TPW, Evaluator_TPW_Fast, Evaluator_TPOW, Evaluator_TPWE, Evaluator_TPWE_Fast, Evaluator_TPWEC, Evaluator_PWE, Evaluator_BW, Evaluator_EcW, Evaluator_BWEc, Evaluator_PBWEc, Evaluator_TPWEB # noqa: E501 __all__ = [ 'TableScorer', 'PossibilityScorer', 'OpeningScorer', 'WinLoseScorer', 'NumberScorer', 'EdgeScorer', 'CornerScorer', 'BlankScorer', 'EdgeCornerScorer', 'Selector', 'Selector_W', 'Orderer', 'Orderer_B', 'Orderer_C', 'Orderer_P', 'Orderer_BC', 'Orderer_CB', 'Orderer_PCB', 'Evaluator', 'Evaluator_T', 'Evaluator_P', 'Evaluator_O', 'Evaluator_W', 'Evaluator_N', 'Evaluator_N_Fast', 'Evaluator_E', 'Evaluator_C', 'Evaluator_B', 'Evaluator_Ec', 'Evaluator_TP', 'Evaluator_TPO', 'Evaluator_NW', 'Evaluator_PW', 'Evaluator_TPW', 'Evaluator_TPW_Fast', 'Evaluator_TPOW', 'Evaluator_TPWE', 'Evaluator_TPWE_Fast', 'Evaluator_TPWEC', 'Evaluator_PWE', 'Evaluator_BW', 'Evaluator_EcW', 'Evaluator_BWEc', 'Evaluator_PBWEc', 'Evaluator_TPWEB', ]

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null

0

6

58836653c820d017fba63997dc1db865808e4a91

39

py

Python

djangolive/utils/__init__.py

Tomvictor/djangolive

fbb482395e4b9be5b947480047868870bb77f344

[ "MIT" ]

1

2021-04-06T17:53:06.000Z

djangolive/utils/__init__.py

Tomvictor/djangolive

fbb482395e4b9be5b947480047868870bb77f344

[ "MIT" ]

6

2021-04-16T16:06:55.000Z

2021-04-24T07:13:07.000Z

djangolive/utils/__init__.py

Tomvictor/djangolive

fbb482395e4b9be5b947480047868870bb77f344

[ "MIT" ]

null

from ._archive import ZipResponseMixin

19.5

38

0.871795

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39

8.25

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39

0.942857

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null

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0

1

0

1

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6

588b00f0c8a740075b5bd925c05175c12eb1037b

180

py

Python

student_mgmt/__init__.py

MustafaRaad/Student_management__Certificate

a9e8ca6cbf2f2ab39d6a44b2bd56baf8a8042505

[ "MIT" ]

null

student_mgmt/__init__.py

MustafaRaad/Student_management__Certificate

a9e8ca6cbf2f2ab39d6a44b2bd56baf8a8042505

[ "MIT" ]

null

student_mgmt/__init__.py

MustafaRaad/Student_management__Certificate

a9e8ca6cbf2f2ab39d6a44b2bd56baf8a8042505

[ "MIT" ]

null

""" ########################################## ## Developed By:Mustafa Raad Mutashar ## ## mustafa.raad.7@gmail.com 2020 ## ########################################## """

25.714286

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180

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0.127778

180

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1

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null

0

1

0

6

5436a01008f2e4eb7b96ef96a5fd72bd2eeedae8

41

py

Python

libpyka/db/__init__.py

karakawa88/libpyka

3cd29b68f26ca6bce6239545142b7cc410d97bd1

[ "MIT" ]

null

libpyka/db/__init__.py

karakawa88/libpyka

3cd29b68f26ca6bce6239545142b7cc410d97bd1

[ "MIT" ]

null

libpyka/db/__init__.py

karakawa88/libpyka

3cd29b68f26ca6bce6239545142b7cc410d97bd1

[ "MIT" ]

null

from .SQLException import SQLException

10.25

38

0.829268

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41

8.5

0.75

0

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41

3

39

13.666667

0.971429

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null

0

1

0

1

0

1

0

6

5499ebec09d878806d2d332e24b49dea33e29dbb

166

py

Python

chapter 1/c1q28.py

jonathanmonreal/nltk-examples

95fb0b28c9ba433bac20990715496edc469293b4

[ "Apache-2.0" ]

2

2015-08-06T18:58:44.000Z

2018-05-11T13:00:28.000Z

chapter 1/c1q28.py

jonathanmonreal/nltk-examples

95fb0b28c9ba433bac20990715496edc469293b4

[ "Apache-2.0" ]

null

chapter 1/c1q28.py

jonathanmonreal/nltk-examples

95fb0b28c9ba433bac20990715496edc469293b4

[ "Apache-2.0" ]

null

# Jonathan Monreal from __future__ import division import nltk def percentage(word, text): return 100 * ([word.lower() for word in text].count(word)/len(text))

20.75

72

0.728916

24

166

4.875

0.75

0

0.021429

0.156627

166

7

73

23.714286

0.814286

0.096386

0

1

0.25

false

0

0.5

0.25

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

54bee0d7627971277e34b7a4ffd4c77ded02b310

94

py

Python

HedyNet/promotions/views.py

akjohnson/HedyNet

77771605fa8987435bd74ce8ec2a33008e3f8fd1

[ "Apache-2.0" ]

null

HedyNet/promotions/views.py

akjohnson/HedyNet

77771605fa8987435bd74ce8ec2a33008e3f8fd1

[ "Apache-2.0" ]

null

HedyNet/promotions/views.py

akjohnson/HedyNet

77771605fa8987435bd74ce8ec2a33008e3f8fd1

[ "Apache-2.0" ]

null

from mailchimp2 import SubscribeFormView class GeekGirlCon(SubscribeFormView): pass

15.666667

40

0.787234

8

94

9.25

0.875

0

0.012987

0.180851

94

5

41

18.8

0.948052

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

54c0a541f65af9a0faf84e33006251254543388e

39

py

Python

test_suite/suite/test08/other_mod.py

joncatanio/cannoli

410f6bea362bf9e33eecc0e01fb080dadd14ef23

[ "MIT" ]

755

2017-12-09T05:34:43.000Z

2022-03-26T09:15:56.000Z

test_suite/suite/test08/other_mod.py

joncatanio/cannoli

410f6bea362bf9e33eecc0e01fb080dadd14ef23

[ "MIT" ]

8

2017-12-12T01:03:18.000Z

2020-06-29T01:41:03.000Z

test_suite/suite/test08/other_mod.py

joncatanio/cannoli

410f6bea362bf9e33eecc0e01fb080dadd14ef23

[ "MIT" ]

23

2018-05-17T17:48:23.000Z

2022-03-26T09:15:57.000Z

def func(): print("other_mod call")

13

26

0.641026

6

39

4

1

0

0.179487

39

2

27

19.5

0.75

0

0.358974

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1

0.5

true

0

0.5

1

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null

0

1

0

null

0

1

0

1

0

6

b738df8fb2406cc2c09ee8ef32cc652e1423b01a

8,987

py

Python

adventofcode/day11.py

jcfvalente/adventofcode2020

ec0deede4661dd80945d96cb72b034579b9ac62e

[ "MIT" ]

null

adventofcode/day11.py

jcfvalente/adventofcode2020

ec0deede4661dd80945d96cb72b034579b9ac62e

[ "MIT" ]

null

adventofcode/day11.py

jcfvalente/adventofcode2020

ec0deede4661dd80945d96cb72b034579b9ac62e

[ "MIT" ]

null

from adventofcode.inputs import reader import copy def solve_part_one(seats_map: list) -> int: seats_stable = False aux_seats_map = [] seats_map = [list(row) for row in seats_map] while not seats_stable: # Keeping doing this while the seats change internal_stable = True if aux_seats_map: seats_map = copy.deepcopy(aux_seats_map) else: aux_seats_map = copy.deepcopy(seats_map) for row in range(0, len(seats_map)): # each row for seat_position in range(0, len(seats_map[row])): # each set if seats_map[row][seat_position] == ".": continue occupied = 0 # North if row - 1 >= 0: # N if seats_map[row - 1][seat_position] == "#": occupied += 1 # NE if seat_position - 1 >= 0: if seats_map[row - 1][seat_position - 1] == "#": occupied += 1 # NW if seat_position + 1 < len(seats_map[row]): if seats_map[row - 1][seat_position + 1] == "#": occupied += 1 # South if row + 1 < len(seats_map): # S if seats_map[row + 1][seat_position] == "#": occupied += 1 # SE if seat_position - 1 >= 0: if seats_map[row + 1][seat_position - 1] == "#": occupied += 1 # NW if seat_position + 1 < len(seats_map[row]): if seats_map[row + 1][seat_position + 1] == "#": occupied += 1 # East if seat_position - 1 >= 0: if seats_map[row][seat_position - 1] == "#": occupied += 1 # West if seat_position + 1 < len(seats_map[row]): if seats_map[row][seat_position + 1] == "#": occupied += 1 # Update setting status if seats_map[row][seat_position] == "L" and occupied == 0: aux_seats_map[row][seat_position] = "#" internal_stable = False continue if seats_map[row][seat_position] == "#" and occupied >= 4: aux_seats_map[row][seat_position] = "L" internal_stable = False continue if internal_stable: # If we get here it means no seats have changed, it's stable seats_map = aux_seats_map seats_stable = True return count_occupied_seats(seats_map) def solve_part_two(seats_map: list) -> int: seats_stable = False aux_seats_map = [] seats_map = [list(row) for row in seats_map] while not seats_stable: # Keeping doing this while the seats change internal_stable = True if aux_seats_map: seats_map = copy.deepcopy(aux_seats_map) else: aux_seats_map = copy.deepcopy(seats_map) for row in range(0, len(seats_map)): for seat_position in range(0, len(seats_map[row])): if seats_map[row][seat_position] == ".": continue occupied = 0 # North if row - 1 >= 0: # N first_try = row - 1 while first_try >= 0: if seats_map[first_try][seat_position] != ".": if seats_map[first_try][seat_position] == "#": occupied += 1 break else: break first_try -= 1 # NE if seat_position - 1 >= 0: up_try = row - 1 left_try = seat_position - 1 while up_try >= 0 and left_try >= 0: if seats_map[up_try][left_try] != ".": if seats_map[up_try][left_try] == "#": occupied += 1 break else: break up_try -= 1 left_try -= 1 # NW if seat_position + 1 < len(seats_map[row]): up_try = row - 1 right_try = seat_position + 1 while up_try >= 0 and right_try < len(seats_map[row]): if seats_map[up_try][right_try] != ".": if seats_map[up_try][right_try] == "#": occupied += 1 break else: break up_try -= 1 right_try += 1 # South if row + 1 < len(seats_map): # S first_try = row + 1 while first_try < len(seats_map): if seats_map[first_try][seat_position] != ".": if seats_map[first_try][seat_position] == "#": occupied += 1 break else: break first_try += 1 # SE if seat_position - 1 >= 0: down_try = row + 1 left_try = seat_position - 1 while down_try < len(seats_map) and left_try >= 0: if seats_map[down_try][left_try] != ".": if seats_map[down_try][left_try] == "#": occupied += 1 break else: break down_try += 1 left_try -= 1 # SW if seat_position + 1 < len(seats_map[row]): down_try = row + 1 right_try = seat_position + 1 while down_try < len(seats_map) and right_try < len(seats_map[row]): if seats_map[down_try][right_try] != ".": if seats_map[down_try][right_try] == "#": occupied += 1 break else: break down_try += 1 right_try += 1 # East left_first_try = seat_position - 1 while left_first_try >= 0: if seats_map[row][left_first_try] == "#": occupied += 1 break elif seats_map[row][left_first_try] == "L": break left_first_try -= 1 # West right_first_try = seat_position + 1 while right_first_try < len(seats_map[row]): if seats_map[row][right_first_try] == "#": occupied += 1 break elif seats_map[row][right_first_try] == "L": break right_first_try += 1 # Update setting status if seats_map[row][seat_position] == "L" and occupied == 0: aux_seats_map[row][seat_position] = "#" internal_stable = False continue if seats_map[row][seat_position] == "#" and occupied >= 5: aux_seats_map[row][seat_position] = "L" internal_stable = False continue if internal_stable: # If we get here it means no seats have changed, it's stable seats_map = aux_seats_map seats_stable = True # Count the seats return count_occupied_seats(seats_map) def count_occupied_seats(puzzle: list) -> int: occupied_seats = 0 for row in puzzle: for seat in row: if seat == "#": occupied_seats += 1 return occupied_seats if __name__ == '__main__': puzzle_input = reader.read_file('adventofcode/inputs/day11.txt') solve_part_one(puzzle_input) solve_part_two(puzzle_input)

40.85

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0

null

0

1

0

1

0

null

0

6

b741acce954698c96769fd78fe934510ae2f593a

9,552

py

Python

tests/test_attention.py

ZeroDesigner/alphafold2

25255ab69314480316e5dc978e2cac1d2c8aa9d1

[ "MIT" ]

1

2022-01-21T04:58:18.000Z

tests/test_attention.py

ZeroDesigner/alphafold2

25255ab69314480316e5dc978e2cac1d2c8aa9d1

[ "MIT" ]

null

tests/test_attention.py

ZeroDesigner/alphafold2

25255ab69314480316e5dc978e2cac1d2c8aa9d1

[ "MIT" ]

null

import torch from alphafold2_pytorch.alphafold2 import Alphafold2 from alphafold2_pytorch.utils import * def test_main(): model = Alphafold2( dim = 32, depth = 2, heads = 2, dim_head = 32 ) seq = torch.randint(0, 21, (2, 128)) msa = torch.randint(0, 21, (2, 5, 64)) mask = torch.ones_like(seq).bool() msa_mask = torch.ones_like(msa).bool() distogram = model( seq, msa, mask = mask, msa_mask = msa_mask ) assert True def test_no_msa(): model = Alphafold2( dim = 32, depth = 2, heads = 2, dim_head = 32 ) seq = torch.randint(0, 21, (2, 128)) mask = torch.ones_like(seq).bool() distogram = model( seq, mask = mask ) assert True def test_anglegrams(): model = Alphafold2( dim = 32, depth = 2, heads = 2, dim_head = 32, predict_angles = True ) seq = torch.randint(0, 21, (2, 128)) msa = torch.randint(0, 21, (2, 5, 64)) mask = torch.ones_like(seq).bool() msa_mask = torch.ones_like(msa).bool() distogram, theta, phi, omega = model( seq, msa, mask = mask, msa_mask = msa_mask ) assert True def test_msa_tie_row_attn(): model = Alphafold2( dim = 32, depth = 2, heads = 2, dim_head = 32, msa_tie_row_attn = True ) seq = torch.randint(0, 21, (2, 128)) msa = torch.randint(0, 21, (2, 5, 64)) mask = torch.ones_like(seq).bool() msa_mask = torch.ones_like(msa).bool() distogram = model( seq, msa, mask = mask, msa_mask = msa_mask ) assert True def test_templates(): model = Alphafold2( dim = 32, depth = 2, heads = 2, dim_head = 32, attn_types = ('full', 'intra_attn', 'seq_only') ) seq = torch.randint(0, 21, (2, 16)) mask = torch.ones_like(seq).bool() msa = torch.randint(0, 21, (2, 5, 32)) msa_mask = torch.ones_like(msa).bool() templates_seq = torch.randint(0, 21, (2, 2, 16)) templates_coors = torch.randn(2, 2, 16, 3) templates_mask = torch.ones_like(templates_seq).bool() distogram = model( seq, msa, mask = mask, msa_mask = msa_mask, templates_seq = templates_seq, templates_coors = templates_coors, templates_mask = templates_mask ) def test_embeddings(): model = Alphafold2( dim = 32, depth = 2, heads = 2, dim_head = 32 ) seq = torch.randint(0, 21, (2, 16)) mask = torch.ones_like(seq).bool() embedds = torch.randn(2, 1, 16, 1280) # without mask distogram = model( seq, mask = mask, embedds = embedds, msa_mask = None ) # with mask embedds_mask = torch.ones_like(embedds[..., -1]).bool() distogram = model( seq, mask = mask, embedds = embedds, msa_mask = embedds_mask ) assert True def test_coords_se3(): model = Alphafold2( dim = 32, depth = 2, heads = 2, dim_head = 32, predict_coords = True, num_backbone_atoms = 3, structure_module_dim = 1, structure_module_depth = 1, structure_module_heads = 1, structure_module_dim_head = 1, structure_module_knn = 2 ) seq = torch.randint(0, 21, (2, 8)) mask = torch.ones_like(seq).bool() msa = torch.randint(0, 21, (2, 5, 16)) msa_mask = torch.ones_like(msa).bool() coords = model( seq, msa, mask = mask, msa_mask = msa_mask ) assert coords.shape == (2, 8 * 14, 3), 'must output coordinates' def test_coords_se3_with_global_nodes(): model = Alphafold2( dim = 32, depth = 2, heads = 2, dim_head = 32, predict_coords = True, num_backbone_atoms = 3, structure_module_dim = 1, structure_module_depth = 1, structure_module_heads = 1, structure_module_dim_head = 1, structure_module_knn = 2, structure_num_global_nodes = 2 ) seq = torch.randint(0, 21, (2, 8)) mask = torch.ones_like(seq).bool() msa = torch.randint(0, 21, (2, 5, 16)) msa_mask = torch.ones_like(msa).bool() coords = model( seq, msa, mask = mask, msa_mask = msa_mask ) assert coords.shape == (2, 8 * 14, 3), 'must output coordinates' def test_edges_to_equivariant_network(): model = Alphafold2( dim = 32, depth = 1, heads = 2, dim_head = 32, use_se3_transformer = False, predict_coords = True, predict_angles = True, num_backbone_atoms = 3 ) seq = torch.randint(0, 21, (2, 16)) mask = torch.ones_like(seq).bool() msa = torch.randint(0, 21, (2, 5, 32)) msa_mask = torch.ones_like(msa).bool() coords, confidences = model( seq, msa, mask = mask, msa_mask = msa_mask, return_confidence = True ) assert True, 'should run without errors' def test_real_value_distance_with_coords(): model = Alphafold2( dim = 32, depth = 1, heads = 2, dim_head = 16, predict_coords = True, predict_real_value_distances = True, num_backbone_atoms = 3, structure_module_dim = 1, structure_module_depth = 1, structure_module_heads = 1, structure_module_dim_head = 1, structure_module_knn = 2 ) seq = torch.randint(0, 21, (2, 8)) mask = torch.ones_like(seq).bool() msa = torch.randint(0, 21, (2, 5, 16)) msa_mask = torch.ones_like(msa).bool() coords = model( seq, msa, mask = mask, msa_mask = msa_mask ) assert coords.shape == (2, 8 * 14, 3), 'must output coordinates' def test_coords_se3_backwards(): model = Alphafold2( dim = 256, depth = 2, heads = 2, dim_head = 32, predict_coords = True, num_backbone_atoms = 3, structure_module_dim = 1, structure_module_depth = 1, structure_module_heads = 1, structure_module_dim_head = 1, structure_module_knn = 1 ) seq = torch.randint(0, 21, (2, 8)) mask = torch.ones_like(seq).bool() msa = torch.randint(0, 21, (2, 5, 16)) msa_mask = torch.ones_like(msa).bool() coords = model( seq, msa, mask = mask, msa_mask = msa_mask ) coords.sum().backward() assert True, 'must be able to go backwards through MDS and center distogram' def test_coords_En(): model = Alphafold2( dim = 256, depth = 2, heads = 2, dim_head = 32, use_se3_transformer = False, predict_coords = True, num_backbone_atoms = 3 ) seq = torch.randint(0, 21, (2, 16)) mask = torch.ones_like(seq).bool() msa = torch.randint(0, 21, (2, 5, 32)) msa_mask = torch.ones_like(msa).bool() coords = model( seq, msa, mask = mask, msa_mask = msa_mask ) # get masks : cloud is all points in prot. chain is all for which we have labels cloud_mask = scn_cloud_mask(seq, boolean = True) flat_cloud_mask = rearrange(cloud_mask, 'b l c -> b (l c)') chain_mask = (mask.unsqueeze(-1) * cloud_mask) flat_chain_mask = rearrange(chain_mask, 'b l c -> b (l c)') # put in sidechainnet format wrapper = torch.zeros(*cloud_mask.shape, 3).to(coords.device).type(coords.type()) wrapper[cloud_mask] = coords[flat_cloud_mask] assert wrapper[chain_mask].shape == coords[flat_chain_mask].shape, 'must output coordinates' def test_coords_En_backwards(): model = Alphafold2( dim = 256, depth = 2, heads = 2, dim_head = 32, use_se3_transformer = False, predict_coords = True, num_backbone_atoms = 3 ) seq = torch.randint(0, 21, (2, 16)) mask = torch.ones_like(seq).bool() msa = torch.randint(0, 21, (2, 5, 32)) msa_mask = torch.ones_like(msa).bool() coords = model( seq, msa, mask = mask, msa_mask = msa_mask ) coords.sum().backward() assert True, 'must be able to go backwards through MDS and center distogram' def test_confidence_En(): model = Alphafold2( dim = 256, depth = 1, heads = 2, dim_head = 32, use_se3_transformer = False, predict_coords = True, num_backbone_atoms = 3 ) seq = torch.randint(0, 21, (2, 16)) mask = torch.ones_like(seq).bool() msa = torch.randint(0, 21, (2, 5, 32)) msa_mask = torch.ones_like(msa).bool() coords, confidences = model( seq, msa, mask = mask, msa_mask = msa_mask, return_confidence = True ) assert coords.shape[:-1] == confidences.shape[:-1] def test_reversible(): model = Alphafold2( dim = 32, depth = 2, heads = 2, dim_head = 32, reversible = True ) seq = torch.randint(0, 21, (2, 128)) msa = torch.randint(0, 21, (2, 5, 64)) mask = torch.ones_like(seq).bool() msa_mask = torch.ones_like(msa).bool() distogram = model( seq, msa, mask = mask, msa_mask = msa_mask ) distogram.sum().backward() assert True

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py

Python

routeros_ssh_connector/__init__.py

hosin211/routeros_ssh_connector

4728aff41c359b47b9a9c5b78b5689c9f7771a62

[ "MIT" ]

6

2021-08-03T08:15:24.000Z

2022-01-21T17:43:44.000Z

routeros_ssh_connector/__init__.py

hosin211/routeros_ssh_connector

4728aff41c359b47b9a9c5b78b5689c9f7771a62

[ "MIT" ]

null

routeros_ssh_connector/__init__.py

hosin211/routeros_ssh_connector

4728aff41c359b47b9a9c5b78b5689c9f7771a62

[ "MIT" ]

1

2022-01-29T16:04:04.000Z

from routeros_ssh_connector.connector import *

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py

Python

stix2generator/test/test_stix21_registry.py

majacQ/cti-stix-generator

7465ecd29ef6caabf9f1b60ad45dad789c475028

[ "BSD-3-Clause" ]

null

stix2generator/test/test_stix21_registry.py

majacQ/cti-stix-generator

7465ecd29ef6caabf9f1b60ad45dad789c475028

[ "BSD-3-Clause" ]

null

stix2generator/test/test_stix21_registry.py

majacQ/cti-stix-generator

7465ecd29ef6caabf9f1b60ad45dad789c475028

[ "BSD-3-Clause" ]

null

import json import pytest import stix2 import stix2.exceptions import stix2generator import stix2generator.language.builder import stix2generator.generation.object_generator def get_stix21_spec_names(): """ Gets the spec names from the STIX 2.1 registry. We need to know this to be able to test those specifications. """ registry = stix2generator._get_registry("2.1") return registry.keys() STIX21_SPEC_NAMES = get_stix21_spec_names() @pytest.fixture(scope="module") def generator_random_props(): """ Creates a generator which randomly includes or excludes properties. """ config = stix2generator.generation.object_generator.Config( minimize_ref_properties=False ) generator = stix2generator.create_object_generator(config, None, "2.1") return generator @pytest.fixture(scope="module") def generator_min_props(): """ Creates a generator which omits all optional properties. """ config = stix2generator.generation.object_generator.Config( minimize_ref_properties=False, optional_property_probability=0 ) generator = stix2generator.create_object_generator(config, None, "2.1") return generator @pytest.fixture(scope="module") def generator_all_props(): """ Creates a generator which includes all optional properties. """ config = stix2generator.generation.object_generator.Config( minimize_ref_properties=False, optional_property_probability=1 ) generator = stix2generator.create_object_generator(config, None, "2.1") return generator @pytest.mark.parametrize("spec_name", STIX21_SPEC_NAMES) def test_generation_random_props(generator_random_props, spec_name, num_trials): for _ in range(num_trials): obj_dict = generator_random_props.generate(spec_name) # Ensure json-serializability json.dumps(obj_dict, ensure_ascii=False) # Distinguish between a STIX object spec and a "helper" spec used # by STIX object specs. Only makes sense to stix2.parse() the former. if spec_name[0].isupper(): try: stix2.parse(obj_dict, version="2.1") except stix2.exceptions.ParseError: # Maybe we can use this to mean this was an SCO? # Try a re-parse as an SCO. Need a better way to make the # distinction... stix2.parse_observable(obj_dict, version="2.1") @pytest.mark.parametrize("spec_name", STIX21_SPEC_NAMES) def test_generation_min_props(generator_min_props, spec_name): obj_dict = generator_min_props.generate(spec_name) # Ensure json-serializability json.dumps(obj_dict, ensure_ascii=False) # Distinguish between a STIX object spec and a "helper" spec used # by STIX object specs. Only makes sense to stix2.parse() the former. if spec_name[0].isupper(): try: stix2.parse(obj_dict, version="2.1") except stix2.exceptions.ParseError: # Maybe we can use this to mean this was an SCO? # Try a re-parse as an SCO. Need a better way to make the # distinction... stix2.parse_observable(obj_dict, version="2.1") @pytest.mark.parametrize("spec_name", STIX21_SPEC_NAMES) def test_generation_all_props(generator_all_props, spec_name): obj_dict = generator_all_props.generate(spec_name) # Ensure json-serializability json.dumps(obj_dict, ensure_ascii=False) # Distinguish between a STIX object spec and a "helper" spec used # by STIX object specs. Only makes sense to stix2.parse() the former. if spec_name[0].isupper(): try: stix2.parse(obj_dict, version="2.1") except stix2.exceptions.ParseError: # Maybe we can use this to mean this was an SCO? # Try a re-parse as an SCO. Need a better way to make the # distinction... stix2.parse_observable(obj_dict, version="2.1") # Test "relationship" separately since it is lower-cased, but nevertheless # parseable by stix2. I wanted to keep it all lower-case so people # couldn't use it like an SDO/SCO in the prototyping language. def test_generation_random_props_relationship( generator_random_props, num_trials ): for _ in range(num_trials): rel_dict = generator_random_props.generate("relationship") json.dumps(rel_dict, ensure_ascii=False) stix2.parse(rel_dict, version="2.1") def test_generation_min_props_relationship(generator_min_props): rel_dict = generator_min_props.generate("relationship") json.dumps(rel_dict, ensure_ascii=False) stix2.parse(rel_dict, version="2.1") def test_generation_all_props_relationship(generator_all_props): rel_dict = generator_all_props.generate("relationship") json.dumps(rel_dict, ensure_ascii=False) stix2.parse(rel_dict, version="2.1") # Similar for sightings. def test_generation_random_props_sighting( generator_random_props, num_trials ): for _ in range(num_trials): rel_dict = generator_random_props.generate("sighting") json.dumps(rel_dict, ensure_ascii=False) stix2.parse(rel_dict, version="2.1") def test_generation_min_props_sighting(generator_min_props): rel_dict = generator_min_props.generate("sighting") json.dumps(rel_dict, ensure_ascii=False) stix2.parse(rel_dict, version="2.1") def test_generation_all_props_sighting(generator_all_props): rel_dict = generator_all_props.generate("sighting") json.dumps(rel_dict, ensure_ascii=False) stix2.parse(rel_dict, version="2.1")

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Python

cycle_2018/migrations/0009_auto_20180222_1459.py

RobBickel/nyt-fec

802df867c3b31fff8e922be00bab6f40a5db2d00

[ "Apache-2.0" ]

17

2018-03-27T15:09:58.000Z

2020-05-13T11:32:43.000Z

cycle_2018/migrations/0009_auto_20180222_1459.py

RobBickel/nyt-fec

802df867c3b31fff8e922be00bab6f40a5db2d00

[ "Apache-2.0" ]

59

2018-03-21T17:08:15.000Z

2021-12-13T19:47:37.000Z

cycle_2018/migrations/0009_auto_20180222_1459.py

RobBickel/nyt-fec

802df867c3b31fff8e922be00bab6f40a5db2d00

[ "Apache-2.0" ]

11

2018-09-11T23:18:32.000Z

2021-12-15T08:43:58.000Z

# Generated by Django 2.0.1 on 2018-02-22 14:59 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('cycle_2018', '0008_schedulee'), ] operations = [ migrations.AddField( model_name='filing', name='status', field=models.CharField(choices=[('ACTIVE', 'active'), ('SUPERSEDED', 'superseded by amendment'), ('COVERED', 'covered by periodic'), ('MEMO', 'memo')], default='ACTIVE', max_length=50), ), migrations.AddField( model_name='schedulea', name='status', field=models.CharField(choices=[('ACTIVE', 'active'), ('SUPERSEDED', 'superseded by amendment'), ('COVERED', 'covered by periodic'), ('MEMO', 'memo')], default='ACTIVE', max_length=50), ), migrations.AddField( model_name='scheduleb', name='status', field=models.CharField(choices=[('ACTIVE', 'active'), ('SUPERSEDED', 'superseded by amendment'), ('COVERED', 'covered by periodic'), ('MEMO', 'memo')], default='ACTIVE', max_length=50), ), migrations.AddField( model_name='schedulee', name='status', field=models.CharField(choices=[('ACTIVE', 'active'), ('SUPERSEDED', 'superseded by amendment'), ('COVERED', 'covered by periodic'), ('MEMO', 'memo')], default='ACTIVE', max_length=50), ), ]

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b20ddc17f3f99ef6cb191d7292f089f56babaf23

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py

Python

src/models/pytorch/networks.py

AntonioGUJ/AirwaySegmentation_Keras

7da4c88dfde6f0dd2f8f181b2d3fd07dc2d28638

[ "MIT" ]

15

2021-04-09T12:42:35.000Z

2022-03-22T09:01:57.000Z

src/models/pytorch/networks.py

id-b3/bronchinet

5acf5243da2a0e38041bbbf2ffd033291eff13a4

[ "MIT" ]

13

2021-03-31T11:16:12.000Z

2022-02-10T06:11:16.000Z

src/models/pytorch/networks.py

id-b3/bronchinet

5acf5243da2a0e38041bbbf2ffd033291eff13a4

[ "MIT" ]

9

2021-04-13T13:27:51.000Z

2022-02-25T07:03:25.000Z

from typing import Tuple, List, Dict, Union, Any from torch.nn import Conv3d, MaxPool3d, Upsample, BatchNorm3d, Dropout3d, ReLU, LeakyReLU, Sigmoid import torch.nn as nn import torch from common.exceptionmanager import catch_error_exception from common.functionutil import ImagesUtil from imageoperators.imageoperator import CropImage from models.networks import UNetBase LIST_AVAIL_NETWORKS = ['UNet3DOriginal', 'UNet3DGeneral', 'UNet3DPlugin', ] class UNet(UNetBase, nn.Module): def __init__(self, size_image_in: Union[Tuple[int, int, int], Tuple[int, int]], num_levels: int, num_featmaps_in: int, num_channels_in: int, num_classes_out: int, is_use_valid_convols: bool = False, num_levels_valid_convols: int = UNetBase._num_levels_valid_convols_default, ) -> None: super(UNet, self).__init__(size_image_in, num_levels, num_featmaps_in, num_channels_in, num_classes_out, is_use_valid_convols=is_use_valid_convols, num_levels_valid_convols=num_levels_valid_convols) nn.Module.__init__(self) self._shape_input = ImagesUtil.get_shape_channels_first(self._shape_input) self._shape_output = ImagesUtil.get_shape_channels_first(self._shape_output) def get_network_input_args(self) -> Dict[str, Any]: raise NotImplementedError def _build_info_crop_where_merge(self) -> None: indexes_output_where_merge = [i for i, elem in enumerate(self._names_operations_layers_all) if elem == 'upsample'] self._sizes_crop_where_merge = [self._sizes_output_all_layers[ind] for ind in indexes_output_where_merge][::-1] def _crop_image_2d(self, input: torch.Tensor, size_crop: Tuple[int, int]) -> torch.Tensor: size_input_image = input.shape[-2:] limits_out_image = self._get_limits_output_crop(size_input_image, size_crop) return CropImage._compute2d_channels_first(input, limits_out_image) def _crop_image_3d(self, input: torch.Tensor, size_crop: Tuple[int, int, int]) -> torch.Tensor: size_input_image = input.shape[-3:] limits_out_image = self._get_limits_output_crop(size_input_image, size_crop) return CropImage._compute3d_channels_first(input, limits_out_image) class UNet3DOriginal(UNet): _num_levels_fixed = 5 def __init__(self, size_image_in: Tuple[int, int, int], num_featmaps_in: int = 16, num_channels_in: int = 1, num_classes_out: int = 1 ) -> None: super(UNet3DOriginal, self).__init__(size_image_in, self._num_levels_fixed, num_featmaps_in, num_channels_in, num_classes_out, is_use_valid_convols=False) self._build_model() def get_network_input_args(self) -> Dict[str, Any]: return {'size_image': self._size_image_in, 'num_featmaps_in': self._num_featmaps_in, 'num_channels_in': self._num_channels_in, 'num_classes_out': self._num_classes_out} def _build_model(self) -> None: num_featmaps_lev1 = self._num_featmaps_in self._convolution_down_lev1_1 = Conv3d(self._num_channels_in, num_featmaps_lev1, kernel_size=3, padding=1) self._convolution_down_lev1_2 = Conv3d(num_featmaps_lev1, num_featmaps_lev1, kernel_size=3, padding=1) self._pooling_down_lev1 = MaxPool3d(kernel_size=2, padding=0) num_featmaps_lev2 = 2 * num_featmaps_lev1 self._convolution_down_lev2_1 = Conv3d(num_featmaps_lev1, num_featmaps_lev2, kernel_size=3, padding=1) self._convolution_down_lev2_2 = Conv3d(num_featmaps_lev2, num_featmaps_lev2, kernel_size=3, padding=1) self._pooling_down_lev2 = MaxPool3d(kernel_size=2, padding=0) num_featmaps_lev3 = 2 * num_featmaps_lev2 self._convolution_down_lev3_1 = Conv3d(num_featmaps_lev2, num_featmaps_lev3, kernel_size=3, padding=1) self._convolution_down_lev3_2 = Conv3d(num_featmaps_lev3, num_featmaps_lev3, kernel_size=3, padding=1) self._pooling_down_lev3 = MaxPool3d(kernel_size=2, padding=0) num_featmaps_lev4 = 2 * num_featmaps_lev3 self._convolution_down_lev4_1 = Conv3d(num_featmaps_lev3, num_featmaps_lev4, kernel_size=3, padding=1) self._convolution_down_lev4_2 = Conv3d(num_featmaps_lev4, num_featmaps_lev4, kernel_size=3, padding=1) self._pooling_down_lev4 = MaxPool3d(kernel_size=2, padding=0) num_featmaps_lev5 = 2 * num_featmaps_lev4 self._convolution_down_lev5_1 = Conv3d(num_featmaps_lev4, num_featmaps_lev5, kernel_size=3, padding=1) self._convolution_down_lev5_2 = Conv3d(num_featmaps_lev5, num_featmaps_lev5, kernel_size=3, padding=1) self._upsample_up_lev5 = Upsample(scale_factor=2, mode='nearest') num_feats_lev4pl5 = num_featmaps_lev4 + num_featmaps_lev5 self._convolution_up_lev4_1 = Conv3d(num_feats_lev4pl5, num_featmaps_lev4, kernel_size=3, padding=1) self._convolution_up_lev4_2 = Conv3d(num_featmaps_lev4, num_featmaps_lev4, kernel_size=3, padding=1) self._upsample_up_lev4 = Upsample(scale_factor=2, mode='nearest') num_feats_lev3pl4 = num_featmaps_lev3 + num_featmaps_lev4 self._convolution_up_lev3_1 = Conv3d(num_feats_lev3pl4, num_featmaps_lev3, kernel_size=3, padding=1) self._convolution_up_lev3_2 = Conv3d(num_featmaps_lev3, num_featmaps_lev3, kernel_size=3, padding=1) self._upsample_up_lev3 = Upsample(scale_factor=2, mode='nearest') num_feats_lev2pl3 = num_featmaps_lev2 + num_featmaps_lev3 self._convolution_up_lev2_1 = Conv3d(num_feats_lev2pl3, num_featmaps_lev2, kernel_size=3, padding=1) self._convolution_up_lev2_2 = Conv3d(num_featmaps_lev2, num_featmaps_lev2, kernel_size=3, padding=1) self._upsample_up_lev2 = Upsample(scale_factor=2, mode='nearest') num_feats_lev1pl2 = num_featmaps_lev1 + num_featmaps_lev2 self._convolution_up_lev1_1 = Conv3d(num_feats_lev1pl2, num_featmaps_lev1, kernel_size=3, padding=1) self._convolution_up_lev1_2 = Conv3d(num_featmaps_lev1, num_featmaps_lev1, kernel_size=3, padding=1) self._classification_last = Conv3d(num_featmaps_lev1, self._num_classes_out, kernel_size=1, padding=0) self._activation_last = Sigmoid() def forward(self, input: torch.Tensor) -> torch.Tensor: hidden_nxt = self._convolution_down_lev1_1(input) hidden_nxt = self._convolution_down_lev1_2(hidden_nxt) hidden_skip_lev1 = hidden_nxt hidden_nxt = self._pooling_down_lev1(hidden_nxt) hidden_nxt = self._convolution_down_lev2_1(hidden_nxt) hidden_nxt = self._convolution_down_lev2_2(hidden_nxt) hidden_skip_lev2 = hidden_nxt hidden_nxt = self._pooling_down_lev2(hidden_nxt) hidden_nxt = self._convolution_down_lev3_1(hidden_nxt) hidden_nxt = self._convolution_down_lev3_2(hidden_nxt) hidden_skip_lev3 = hidden_nxt hidden_nxt = self._pooling_down_lev3(hidden_nxt) hidden_nxt = self._convolution_down_lev4_1(hidden_nxt) hidden_nxt = self._convolution_down_lev4_2(hidden_nxt) hidden_skip_lev4 = hidden_nxt hidden_nxt = self._pooling_down_lev4(hidden_nxt) hidden_nxt = self._convolution_down_lev5_1(hidden_nxt) hidden_nxt = self._convolution_down_lev5_2(hidden_nxt) hidden_nxt = self._upsample_up_lev5(hidden_nxt) hidden_nxt = torch.cat([hidden_nxt, hidden_skip_lev4], dim=1) hidden_nxt = self._convolution_up_lev4_1(hidden_nxt) hidden_nxt = self._convolution_up_lev4_2(hidden_nxt) hidden_nxt = self._upsample_up_lev4(hidden_nxt) hidden_nxt = torch.cat([hidden_nxt, hidden_skip_lev3], dim=1) hidden_nxt = self._convolution_up_lev3_1(hidden_nxt) hidden_nxt = self._convolution_up_lev3_2(hidden_nxt) hidden_nxt = self._upsample_up_lev3(hidden_nxt) hidden_nxt = torch.cat([hidden_nxt, hidden_skip_lev2], dim=1) hidden_nxt = self._convolution_up_lev2_1(hidden_nxt) hidden_nxt = self._convolution_up_lev2_2(hidden_nxt) hidden_nxt = self._upsample_up_lev2(hidden_nxt) hidden_nxt = torch.cat([hidden_nxt, hidden_skip_lev1], dim=1) hidden_nxt = self._convolution_up_lev1_1(hidden_nxt) hidden_nxt = self._convolution_up_lev1_2(hidden_nxt) output = self._activation_last(self._classification_last(hidden_nxt)) return output class UNet3DGeneral(UNet): _num_levels_default = 5 _num_featmaps_in_default = 16 _num_channels_in_default = 1 _num_classes_out_default = 1 _dropout_rate_default = 0.2 _type_activate_hidden_default = 'relu' _type_activate_output_default = 'sigmoid' _num_convols_levels_down_default = 2 _num_convols_levels_up_default = 2 _sizes_kernel_convols_levels_down_default = (3, 3, 3) _sizes_kernel_convols_levels_up_default = (3, 3, 3) _sizes_pooling_levels_default = (2, 2, 2) def __init__(self, size_image_in: Tuple[int, int, int], num_levels: int = _num_levels_default, num_featmaps_in: int = _num_featmaps_in_default, num_channels_in: int = _num_channels_in_default, num_classes_out: int = _num_classes_out_default, is_use_valid_convols: bool = False, type_activate_hidden: str = _type_activate_hidden_default, type_activate_output: str = _type_activate_output_default, num_featmaps_levels: List[int] = None, num_convols_levels_down: Union[int, Tuple[int, ...]] = _num_convols_levels_down_default, num_convols_levels_up: Union[int, Tuple[int, ...]] = _num_convols_levels_up_default, sizes_kernel_convols_levels_down: Union[Tuple[int, int, int], List[Tuple[int, int, int]]] = _sizes_kernel_convols_levels_down_default, sizes_kernel_convols_levels_up: Union[Tuple[int, int, int], List[Tuple[int, int, int]]] = _sizes_kernel_convols_levels_up_default, sizes_pooling_levels: Union[Tuple[int, int, int], List[Tuple[int, int, int]]] = _sizes_pooling_levels_default, is_disable_convol_pooling_axialdim_lastlevel: bool = False, is_use_dropout: bool = False, dropout_rate: float = _dropout_rate_default, is_use_dropout_levels_down: Union[bool, List[bool]] = True, is_use_dropout_levels_up: Union[bool, List[bool]] = True, is_use_batchnormalize=False, is_use_batchnormalize_levels_down: Union[bool, List[bool]] = True, is_use_batchnormalize_levels_up: Union[bool, List[bool]] = True ) -> None: super(UNet, self).__init__(size_image_in, num_levels, num_featmaps_in, num_channels_in, num_classes_out, is_use_valid_convols=is_use_valid_convols) self._type_activate_hidden = type_activate_hidden self._type_activate_output = type_activate_output if num_featmaps_levels: self._num_featmaps_levels = num_featmaps_levels else: # default: double featmaps after every pooling self._num_featmaps_levels = [self._num_featmaps_in] for i in range(1, self._num_levels): self._num_featmaps_levels[i] = 2 * self._num_featmaps_levels[i - 1] if type(num_convols_levels_down) == int: self._num_convols_levels_down = [num_convols_levels_down] * self._num_levels else: self._num_convols_levels_down = num_convols_levels_down if type(num_convols_levels_up) == int: self._num_convols_levels_up = [num_convols_levels_up] * (self._num_levels - 1) else: self._num_convols_levels_up = num_convols_levels_up if type(sizes_kernel_convols_levels_down) == tuple: self._sizes_kernel_convols_levels_down = [sizes_kernel_convols_levels_down] * self._num_levels else: self._sizes_kernel_convols_levels_down = sizes_kernel_convols_levels_down if type(sizes_kernel_convols_levels_up) == tuple: self._sizes_kernel_convols_levels_up = [sizes_kernel_convols_levels_up] * (self._num_levels - 1) else: self._sizes_kernel_convols_levels_up = sizes_kernel_convols_levels_up if type(sizes_pooling_levels) == tuple: self._sizes_pooling_levels = [sizes_pooling_levels] * self._num_levels else: self._sizes_pooling_levels = sizes_pooling_levels self._sizes_upsample_levels = self._sizes_pooling_levels[:-1] if is_disable_convol_pooling_axialdim_lastlevel: size_kernel_convol_lastlevel = self._sizes_kernel_convols_levels_down[-1] self._sizes_kernel_convols_levels_down[-1] = (1, size_kernel_convol_lastlevel[1], size_kernel_convol_lastlevel[2]) size_pooling_lastlevel = self._sizes_pooling_levels[-1] self._sizes_pooling_levels[-1] = (1, size_pooling_lastlevel[1], size_pooling_lastlevel[2]) self._is_use_dropout = is_use_dropout if is_use_dropout: self._dropout_rate = dropout_rate if type(is_use_dropout_levels_down) == bool: self._is_use_dropout_levels_down = [is_use_dropout_levels_down] * self._num_levels else: self._is_use_dropout_levels_down = is_use_dropout_levels_down if type(is_use_dropout_levels_up) == bool: self._is_use_dropout_levels_up = [is_use_dropout_levels_up] * (self._num_levels - 1) else: self._is_use_dropout_levels_up = is_use_dropout_levels_up self._is_use_batchnormalize = is_use_batchnormalize if is_use_batchnormalize: if type(is_use_batchnormalize_levels_down) == bool: self._is_use_batchnormalize_levels_down = [is_use_batchnormalize_levels_down] * self._num_levels else: self._is_use_batchnormalize_levels_down = is_use_batchnormalize_levels_down if type(is_use_batchnormalize_levels_up) == bool: self._is_use_batchnormalize_levels_up = [is_use_batchnormalize_levels_up] * (self._num_levels - 1) else: self._is_use_batchnormalize_levels_up = is_use_batchnormalize_levels_up self._build_model() def get_network_input_args(self) -> Dict[str, Any]: return {'size_image_in': self._size_image_in, 'num_levels': self._num_levels, 'num_featmaps_in': self._num_featmaps_in, 'num_channels_in': self._num_channels_in, 'num_classes_out': self._num_classes_out, 'is_use_valid_convols': self._is_use_valid_convols} def _build_model(self) -> None: value_padding_convols = 0 if self._is_use_valid_convols else 1 self._convolutions_levels_down = [[] for i in range(self._num_levels)] self._convolutions_levels_up = [[] for i in range(self._num_levels - 1)] self._poolings_levels_down = [] self._upsamples_levels_up = [] self._batchnormalize_levels_down = [[] for i in range(self._num_levels)] self._batchnormalize_levels_up = [[] for i in range(self._num_levels - 1)] # ENCODING LAYERS for i_lev in range(self._num_levels): num_featmaps_in_level = self._num_channels_in if i_lev == 0 else self._num_featmaps_levels[i_lev - 1] num_featmaps_out_level = self._num_featmaps_levels[i_lev] for i_con in range(self._num_convols_levels_down[i_lev]): num_featmaps_in_convol = num_featmaps_in_level if i_con else num_featmaps_in_level num_featmaps_out_convol = num_featmaps_out_level new_convolution = Conv3d(num_featmaps_in_convol, num_featmaps_out_convol, kernel_size=self._sizes_kernel_convols_levels_down[i_lev], padding=value_padding_convols) self._convolutions_levels_down[i_lev].append(new_convolution) if self._is_use_batchnormalize and self._is_use_batchnormalize_levels_down[i_lev]: new_batchnormalize = BatchNorm3d(num_featmaps_out_convol) self._batchnormalize_levels_down[i_lev].append(new_batchnormalize) if (i_lev != self._num_levels - 1): new_pooling = MaxPool3d(kernel_size=self._sizes_pooling_levels[i_lev], padding=0) self._poolings_levels_down.append(new_pooling) # DECODING LAYERS for i_lev in range(self._num_levels - 2, -1, -1): num_featmaps_in_level = self._num_featmaps_levels[i_lev - 1] + self._num_featmaps_levels[i_lev] num_featmaps_out_level = self._num_featmaps_levels[i_lev] new_upsample = Upsample(scale_factor=self._sizes_upsample_levels[i_lev], mode='nearest') self._upsamples_levels_up.append(new_upsample) for i_con in range(self._num_convols_levels_up[i_lev]): num_featmaps_in_convol = num_featmaps_in_level if i_con else num_featmaps_in_level num_featmaps_out_convol = num_featmaps_out_level new_convolution = Conv3d(num_featmaps_in_convol, num_featmaps_out_convol, kernel_size=self._sizes_kernel_convols_levels_up[i_lev], padding=value_padding_convols) self._convolutions_levels_up[i_lev].append(new_convolution) if self._is_use_batchnormalize and self._is_use_batchnormalize_levels_up[i_lev]: new_batchnormalize = BatchNorm3d(num_featmaps_out_convol) self._batchnormalize_levels_up[i_lev].append(new_batchnormalize) self._classification_last = Conv3d(self._num_featmaps_in, self._num_classes_out, kernel_size=1, padding=0) if self._is_use_dropout: self._dropout_all_levels = Dropout3d(self._dropout_rate, inplace=True) if self._type_activate_hidden == 'relu': self._activation_hidden = ReLU(inplace=True) elif self._type_activate_hidden == 'leaky_relu': self._activation_hidden = LeakyReLU(inplace=True) elif self._type_activate_hidden == 'none': def func_activation_none(input: torch.Tensor) -> torch.Tensor: return input self._activation_hidden = func_activation_none else: message = 'Type activation hidden not existing: \'%s\'' % (self._type_activate_hidden) catch_error_exception(message) if self._type_activate_output == 'sigmoid': self._activation_last = Sigmoid() elif self._type_activate_output == 'linear': def func_activation_linear(input: torch.Tensor) -> torch.Tensor: return input self._activation_last = func_activation_linear else: message = 'Type activation output not existing: \'%s\' ' % (self._type_activate_output) catch_error_exception(message) def forward(self, input: torch.Tensor) -> torch.Tensor: hidden_nxt = input hidden_skips_levels = [] # ENCODING LAYERS for i_lev in range(self._num_levels): for i_con in range(self._num_convols_levels_down[i_lev]): hidden_nxt = self._activation_hidden(self._convolutions_levels_down[i_lev][i_con](hidden_nxt)) if self._is_use_batchnormalize and self._is_use_batchnormalize_levels_down[i_lev]: hidden_nxt = self._batchnormalize_levels_down[i_lev][i_con](hidden_nxt) if self._is_use_dropout and self._is_use_dropout_levels_down[i_lev]: hidden_nxt = self._dropout_all_levels(hidden_nxt) if (i_lev != self._num_levels - 1): hidden_skips_levels.append(hidden_nxt) hidden_nxt = self._poolings_levels_down[i_lev](hidden_nxt) # DECODING LAYERS for i_lev in range(self._num_levels - 2, -1, -1): hidden_nxt = self._upsamples_levels_up[i_lev](hidden_nxt) hidden_skip_this = hidden_skips_levels[i_lev] if self._is_use_valid_convols: hidden_skip_this = self._crop_image_3d(hidden_skip_this, self._sizes_crop_where_merge[3]) hidden_nxt = torch.cat([hidden_nxt, hidden_skip_this], dim=1) for i_con in range(self._num_convols_levels_up[i_lev]): hidden_nxt = self._activation_hidden(self._convolutions_levels_up[i_lev][i_con](hidden_nxt)) if self._is_use_batchnormalize and self._is_use_batchnormalize_levels_up[i_lev]: hidden_nxt = self._batchnormalize_levels_up[i_lev][i_con](hidden_nxt) if self._is_use_dropout and self._is_use_dropout_levels_up[i_lev]: hidden_nxt = self._dropout_all_levels(hidden_nxt) output = self._activation_last(self._classification_last(hidden_nxt)) return output class UNet3DPlugin(UNet): _num_levels_fixed = 5 _num_levels_valid_convols_fixed = 3 _num_featmaps_in_default = 16 _num_channels_in_default = 1 _num_classes_out_default = 1 _dropout_rate_default = 0.2 _type_activate_hidden_default = 'relu' _type_activate_output_default = 'sigmoid' def __init__(self, size_image_in: Tuple[int, int, int], num_featmaps_in: int = _num_featmaps_in_default, num_channels_in: int = _num_channels_in_default, num_classes_out: int = _num_classes_out_default, is_use_valid_convols: bool = False, is_valid_convols_deep_levels: bool = False ) -> None: super(UNet3DPlugin, self).__init__(size_image_in, self._num_levels_fixed, num_featmaps_in, num_channels_in, num_classes_out, is_use_valid_convols=is_use_valid_convols, num_levels_valid_convols=self._num_levels_valid_convols_fixed) self._type_activate_hidden = self._type_activate_hidden_default self._type_activate_output = self._type_activate_output_default self._is_valid_convols_deep_levels = is_valid_convols_deep_levels self._build_model() def get_network_input_args(self) -> Dict[str, Any]: return {'size_image_in': self._size_image_in, 'num_featmaps_in': self._num_featmaps_in, 'num_channels_in': self._num_channels_in, 'num_classes_out': self._num_classes_out, 'is_use_valid_convols': self._is_use_valid_convols} def _build_model(self) -> None: value_padding = 0 if self._is_use_valid_convols else 1 value_padding_deep_levels = 0 if self._is_valid_convols_deep_levels else 1 num_featmaps_lev1 = self._num_featmaps_in self._convolution_down_lev1_1 = Conv3d(self._num_channels_in, num_featmaps_lev1, kernel_size=3, padding=value_padding) self._convolution_down_lev1_2 = Conv3d(num_featmaps_lev1, num_featmaps_lev1, kernel_size=3, padding=value_padding) self._pooling_down_lev1 = MaxPool3d(kernel_size=2, padding=0) num_featmaps_lev2 = 2 * num_featmaps_lev1 self._convolution_down_lev2_1 = Conv3d(num_featmaps_lev1, num_featmaps_lev2, kernel_size=3, padding=value_padding) self._convolution_down_lev2_2 = Conv3d(num_featmaps_lev2, num_featmaps_lev2, kernel_size=3, padding=value_padding) self._pooling_down_lev2 = MaxPool3d(kernel_size=2, padding=0) num_featmaps_lev3 = 2 * num_featmaps_lev2 self._convolution_down_lev3_1 = Conv3d(num_featmaps_lev2, num_featmaps_lev3, kernel_size=3, padding=value_padding) self._convolution_down_lev3_2 = Conv3d(num_featmaps_lev3, num_featmaps_lev3, kernel_size=3, padding=value_padding) self._pooling_down_lev3 = MaxPool3d(kernel_size=2, padding=0) num_featmaps_lev4 = 2 * num_featmaps_lev3 self._convolution_down_lev4_1 = Conv3d(num_featmaps_lev3, num_featmaps_lev4, kernel_size=3, padding=value_padding_deep_levels) self._convolution_down_lev4_2 = Conv3d(num_featmaps_lev4, num_featmaps_lev4, kernel_size=3, padding=value_padding_deep_levels) self._pooling_down_lev4 = MaxPool3d(kernel_size=2, padding=0) num_featmaps_lev5 = 2 * num_featmaps_lev4 self._convolution_down_lev5_1 = Conv3d(num_featmaps_lev4, num_featmaps_lev5, kernel_size=3, padding=value_padding_deep_levels) self._convolution_down_lev5_2 = Conv3d(num_featmaps_lev5, num_featmaps_lev5, kernel_size=3, padding=value_padding_deep_levels) self._upsample_up_lev5 = Upsample(scale_factor=2, mode='nearest') num_feats_lev4pl5 = num_featmaps_lev4 + num_featmaps_lev5 self._convolution_up_lev4_1 = Conv3d(num_feats_lev4pl5, num_featmaps_lev4, kernel_size=3, padding=value_padding_deep_levels) self._convolution_up_lev4_2 = Conv3d(num_featmaps_lev4, num_featmaps_lev4, kernel_size=3, padding=value_padding_deep_levels) self._upsample_up_lev4 = Upsample(scale_factor=2, mode='nearest') num_feats_lev3pl4 = num_featmaps_lev3 + num_featmaps_lev4 self._convolution_up_lev3_1 = Conv3d(num_feats_lev3pl4, num_featmaps_lev3, kernel_size=3, padding=value_padding) self._convolution_up_lev3_2 = Conv3d(num_featmaps_lev3, num_featmaps_lev3, kernel_size=3, padding=value_padding) self._upsample_up_lev3 = Upsample(scale_factor=2, mode='nearest') num_feats_lev2pl3 = num_featmaps_lev2 + num_featmaps_lev3 self._convolution_up_lev2_1 = Conv3d(num_feats_lev2pl3, num_featmaps_lev2, kernel_size=3, padding=value_padding) self._convolution_up_lev2_2 = Conv3d(num_featmaps_lev2, num_featmaps_lev2, kernel_size=3, padding=value_padding) self._upsample_up_lev2 = Upsample(scale_factor=2, mode='nearest') num_feats_lay1pl2 = num_featmaps_lev1 + num_featmaps_lev2 self._convolution_up_lev1_1 = Conv3d(num_feats_lay1pl2, num_featmaps_lev1, kernel_size=3, padding=value_padding) self._convolution_up_lev1_2 = Conv3d(num_featmaps_lev1, num_featmaps_lev1, kernel_size=3, padding=value_padding) self._classification_last = Conv3d(num_featmaps_lev1, self._num_classes_out, kernel_size=1, padding=0) if self._type_activate_hidden == 'relu': self._activation_hidden = ReLU(inplace=True) elif self._type_activate_hidden == 'leaky_relu': self._activation_hidden = LeakyReLU(inplace=True) elif self._type_activate_hidden == 'linear': def func_activation_linear(input: torch.Tensor) -> torch.Tensor: return input self._activation_hidden = func_activation_linear else: message = 'Type activation hidden not existing: \'%s\'' % (self._type_activate_hidden) catch_error_exception(message) if self._type_activate_output == 'sigmoid': self._activation_last = Sigmoid() elif self._type_activate_output == 'linear': def func_activation_linear(input: torch.Tensor) -> torch.Tensor: return input self._activation_last = func_activation_linear else: message = 'Type activation output not existing: \'%s\' ' % (self._type_activate_output) catch_error_exception(message) def forward(self, input: torch.Tensor) -> torch.Tensor: hidden_nxt = self._activation_hidden(self._convolution_down_lev1_1(input)) hidden_nxt = self._activation_hidden(self._convolution_down_lev1_2(hidden_nxt)) hidden_skip_lev1 = hidden_nxt hidden_nxt = self._pooling_down_lev1(hidden_nxt) hidden_nxt = self._activation_hidden(self._convolution_down_lev2_1(hidden_nxt)) hidden_nxt = self._activation_hidden(self._convolution_down_lev2_2(hidden_nxt)) hidden_skip_lev2 = hidden_nxt hidden_nxt = self._pooling_down_lev2(hidden_nxt) hidden_nxt = self._activation_hidden(self._convolution_down_lev3_1(hidden_nxt)) hidden_nxt = self._activation_hidden(self._convolution_down_lev3_2(hidden_nxt)) hidden_skip_lev3 = hidden_nxt hidden_nxt = self._pooling_down_lev3(hidden_nxt) hidden_nxt = self._activation_hidden(self._convolution_down_lev4_1(hidden_nxt)) hidden_nxt = self._activation_hidden(self._convolution_down_lev4_2(hidden_nxt)) hidden_skip_lev4 = hidden_nxt hidden_nxt = self._pooling_down_lev4(hidden_nxt) hidden_nxt = self._activation_hidden(self._convolution_down_lev5_1(hidden_nxt)) hidden_nxt = self._activation_hidden(self._convolution_down_lev5_2(hidden_nxt)) hidden_nxt = self._upsample_up_lev5(hidden_nxt) if self._is_use_valid_convols: hidden_skip_lev4 = self._crop_image_3d(hidden_skip_lev4, self._sizes_crop_where_merge[3]) hidden_nxt = torch.cat([hidden_nxt, hidden_skip_lev4], dim=1) hidden_nxt = self._activation_hidden(self._convolution_up_lev4_1(hidden_nxt)) hidden_nxt = self._activation_hidden(self._convolution_up_lev4_2(hidden_nxt)) hidden_nxt = self._upsample_up_lev4(hidden_nxt) if self._is_use_valid_convols: hidden_skip_lev3 = self._crop_image_3d(hidden_skip_lev3, self._sizes_crop_where_merge[2]) hidden_nxt = torch.cat([hidden_nxt, hidden_skip_lev3], dim=1) hidden_nxt = self._activation_hidden(self._convolution_up_lev3_1(hidden_nxt)) hidden_nxt = self._activation_hidden(self._convolution_up_lev3_2(hidden_nxt)) hidden_nxt = self._upsample_up_lev3(hidden_nxt) if self._is_use_valid_convols: hidden_skip_lev2 = self._crop_image_3d(hidden_skip_lev2, self._sizes_crop_where_merge[1]) hidden_nxt = torch.cat([hidden_nxt, hidden_skip_lev2], dim=1) hidden_nxt = self._activation_hidden(self._convolution_up_lev2_1(hidden_nxt)) hidden_nxt = self._activation_hidden(self._convolution_up_lev2_2(hidden_nxt)) hidden_nxt = self._upsample_up_lev2(hidden_nxt) if self._is_use_valid_convols: hidden_skip_lev1 = self._crop_image_3d(hidden_skip_lev1, self._sizes_crop_where_merge[0]) hidden_nxt = torch.cat([hidden_nxt, hidden_skip_lev1], dim=1) hidden_nxt = self._activation_hidden(self._convolution_up_lev1_1(hidden_nxt)) hidden_nxt = self._activation_hidden(self._convolution_up_lev1_2(hidden_nxt)) output = self._activation_last(self._classification_last(hidden_nxt)) return output

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b7e6db9c4273e4fc7abb8446c256bf64257ad556

7,234

py

Python

tests/test_case_when.py

MojixCoder/tortoise-orm

2f6396815a603f515d48648ebf339ffad4d15176

[ "Apache-2.0" ]

2,847

2018-08-27T12:02:21.000Z

2022-03-31T01:30:40.000Z

tests/test_case_when.py

MojixCoder/tortoise-orm

2f6396815a603f515d48648ebf339ffad4d15176

[ "Apache-2.0" ]

983

2018-08-24T16:42:41.000Z

2022-03-30T05:14:49.000Z

tests/test_case_when.py

MojixCoder/tortoise-orm

2f6396815a603f515d48648ebf339ffad4d15176

[ "Apache-2.0" ]

323

2018-09-04T23:38:42.000Z

2022-03-31T06:49:17.000Z

from tests.testmodels import IntFields from tortoise import Tortoise from tortoise.contrib import test from tortoise.expressions import Case, F, Q, When from tortoise.functions import Coalesce class TestCaseWhen(test.TestCase): async def setUp(self): self.intfields = [await IntFields.create(intnum=val) for val in range(10)] self.db = Tortoise.get_connection("models") async def test_single_when(self): category = Case(When(intnum__gte=8, then="big"), default="default") sql = IntFields.all().annotate(category=category).values("intnum", "category").sql() dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum`,CASE WHEN `intnum`>=8 THEN 'big' ELSE 'default' END `category` FROM `intfields`" else: expected_sql = 'SELECT "intnum" "intnum",CASE WHEN "intnum">=8 THEN \'big\' ELSE \'default\' END "category" FROM "intfields"' self.assertEqual(sql, expected_sql) async def test_multi_when(self): category = Case( When(intnum__gte=8, then="big"), When(intnum__lte=2, then="small"), default="default" ) sql = IntFields.all().annotate(category=category).values("intnum", "category").sql() dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum`,CASE WHEN `intnum`>=8 THEN 'big' WHEN `intnum`<=2 THEN 'small' ELSE 'default' END `category` FROM `intfields`" else: expected_sql = 'SELECT "intnum" "intnum",CASE WHEN "intnum">=8 THEN \'big\' WHEN "intnum"<=2 THEN \'small\' ELSE \'default\' END "category" FROM "intfields"' self.assertEqual(sql, expected_sql) async def test_q_object_when(self): category = Case(When(Q(intnum__gt=2, intnum__lt=8), then="middle"), default="default") sql = IntFields.all().annotate(category=category).values("intnum", "category").sql() dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum`,CASE WHEN `intnum`>2 AND `intnum`<8 THEN 'middle' ELSE 'default' END `category` FROM `intfields`" else: expected_sql = 'SELECT "intnum" "intnum",CASE WHEN "intnum">2 AND "intnum"<8 THEN \'middle\' ELSE \'default\' END "category" FROM "intfields"' self.assertEqual(sql, expected_sql) async def test_F_then(self): category = Case(When(intnum__gte=8, then=F("intnum_null")), default="default") sql = IntFields.all().annotate(category=category).values("intnum", "category").sql() dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum`,CASE WHEN `intnum`>=8 THEN `intnum_null` ELSE 'default' END `category` FROM `intfields`" else: expected_sql = 'SELECT "intnum" "intnum",CASE WHEN "intnum">=8 THEN "intnum_null" ELSE \'default\' END "category" FROM "intfields"' self.assertEqual(sql, expected_sql) async def test_AE_then(self): # AE: ArithmeticExpression category = Case(When(intnum__gte=8, then=F("intnum") + 1), default="default") sql = IntFields.all().annotate(category=category).values("intnum", "category").sql() dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum`,CASE WHEN `intnum`>=8 THEN `intnum`+1 ELSE 'default' END `category` FROM `intfields`" else: expected_sql = 'SELECT "intnum" "intnum",CASE WHEN "intnum">=8 THEN "intnum"+1 ELSE \'default\' END "category" FROM "intfields"' self.assertEqual(sql, expected_sql) async def test_func_then(self): category = Case(When(intnum__gte=8, then=Coalesce("intnum_null", 10)), default="default") sql = IntFields.all().annotate(category=category).values("intnum", "category").sql() dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum`,CASE WHEN `intnum`>=8 THEN COALESCE(`intnum_null`,10) ELSE 'default' END `category` FROM `intfields`" else: expected_sql = 'SELECT "intnum" "intnum",CASE WHEN "intnum">=8 THEN COALESCE("intnum_null",10) ELSE \'default\' END "category" FROM "intfields"' self.assertEqual(sql, expected_sql) async def test_F_default(self): category = Case(When(intnum__gte=8, then="big"), default=F("intnum_null")) sql = IntFields.all().annotate(category=category).values("intnum", "category").sql() dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum`,CASE WHEN `intnum`>=8 THEN 'big' ELSE `intnum_null` END `category` FROM `intfields`" else: expected_sql = 'SELECT "intnum" "intnum",CASE WHEN "intnum">=8 THEN \'big\' ELSE "intnum_null" END "category" FROM "intfields"' self.assertEqual(sql, expected_sql) async def test_AE_default(self): # AE: ArithmeticExpression category = Case(When(intnum__gte=8, then=8), default=F("intnum") + 1) sql = IntFields.all().annotate(category=category).values("intnum", "category").sql() dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum`,CASE WHEN `intnum`>=8 THEN 8 ELSE `intnum`+1 END `category` FROM `intfields`" else: expected_sql = 'SELECT "intnum" "intnum",CASE WHEN "intnum">=8 THEN 8 ELSE "intnum"+1 END "category" FROM "intfields"' self.assertEqual(sql, expected_sql) async def test_func_default(self): category = Case(When(intnum__gte=8, then=8), default=Coalesce("intnum_null", 10)) sql = IntFields.all().annotate(category=category).values("intnum", "category").sql() dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum`,CASE WHEN `intnum`>=8 THEN 8 ELSE COALESCE(`intnum_null`,10) END `category` FROM `intfields`" else: expected_sql = 'SELECT "intnum" "intnum",CASE WHEN "intnum">=8 THEN 8 ELSE COALESCE("intnum_null",10) END "category" FROM "intfields"' self.assertEqual(sql, expected_sql) async def test_case_when_in_where(self): category = Case( When(intnum__gte=8, then="big"), When(intnum__lte=2, then="small"), default="middle" ) sql = ( IntFields.all() .annotate(category=category) .filter(category__in=["big", "small"]) .values("intnum") .sql() ) dialect = self.db.schema_generator.DIALECT if dialect == "mysql": expected_sql = "SELECT `intnum` `intnum` FROM `intfields` WHERE CASE WHEN `intnum`>=8 THEN 'big' WHEN `intnum`<=2 THEN 'small' ELSE 'middle' END IN ('big','small')" else: expected_sql = "SELECT \"intnum\" \"intnum\" FROM \"intfields\" WHERE CASE WHEN \"intnum\">=8 THEN 'big' WHEN \"intnum\"<=2 THEN 'small' ELSE 'middle' END IN ('big','small')" self.assertEqual(sql, expected_sql)

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186

0.641968

896

7,234

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0.089427

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1

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false

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0

null

0

1

0

null

0

6

4d8032c98304a1e066abdd9a808af2b54d8f5eef

1,180

py

Python

wechatpayv3/merchantrisk.py

MacGuffinLife/wechatpayv3

964abc59604fae10e68c9735b2af1a242772ab9d

[ "MIT" ]

null

wechatpayv3/merchantrisk.py

MacGuffinLife/wechatpayv3

964abc59604fae10e68c9735b2af1a242772ab9d

[ "MIT" ]

null

wechatpayv3/merchantrisk.py

MacGuffinLife/wechatpayv3

964abc59604fae10e68c9735b2af1a242772ab9d

[ "MIT" ]

null

# -*- coding: utf-8 -*- from .type import RequestType def merchantrisk_callback_create(self, notify_url=None): """创建商户违规通知回调地址 :param notify_url: 通知地址，示例值:'https://www.weixin.qq.com/wxpay/pay.php' """ params = {} if notify_url: params.update({'notify_url': notify_url}) path = '/v3/merchant-risk-manage/violation-notifications' return self._core.request(path, method=RequestType.POST, data=params) def merchantrisk_callback_query(self): """查询商户违规通知回调地址 """ path = '/v3/merchant-risk-manage/violation-notifications' return self._core.request(path) def merchantrisk_callback_update(self, notify_url=None): """修改商户违规通知回调地址 :param notify_url: 通知地址，示例值:'https://www.weixin.qq.com/wxpay/pay.php' """ params = {} if notify_url: params.update({'notify_url': notify_url}) path = '/v3/merchant-risk-manage/violation-notifications' return self._core.request(path, method=RequestType.PUT, data=params) def merchantrisk_callback_delete(self): """查询商户违规通知回调地址 """ path = '/v3/merchant-risk-manage/violation-notifications' return self._core.request(path, method=RequestType.DELETE)

29.5

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1,180

5.583333

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0.782338

0.700249

0

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0.15678

1,180

39

74

30.25641

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0.189831

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0

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0.210526

false

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