xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

dff0055897206f9b94440e1aee1ef0055d1737a0

139

py

Python

src/meu_condominio/views/__init__.py

lucasjoao/meu_condominio

aac37911384726b1aa1a40237050801a39174dc7

[ "Unlicense" ]

null

src/meu_condominio/views/__init__.py

lucasjoao/meu_condominio

aac37911384726b1aa1a40237050801a39174dc7

[ "Unlicense" ]

null

src/meu_condominio/views/__init__.py

lucasjoao/meu_condominio

aac37911384726b1aa1a40237050801a39174dc7

[ "Unlicense" ]

null

# <controller> from initial_controller import * from espaco import * from financa import * from funcionario import * from morador import *

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5f157bd44335448ca5b682c871d9dd21d4c252a1

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py

Python

webpet/request/__init__.py

momoru-kun/webpet

7b388860c016133659118a9f7e57fead43ab116e

[ "MIT" ]

null

webpet/request/__init__.py

momoru-kun/webpet

7b388860c016133659118a9f7e57fead43ab116e

[ "MIT" ]

null

webpet/request/__init__.py

momoru-kun/webpet

7b388860c016133659118a9f7e57fead43ab116e

[ "MIT" ]

null

from .HttpRequest import HTTPRequest

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59

py

Python

pyts/__init__.py

zhangxu0307/pyts

c66a3874dedd33a8109e0955f69074df6fdedf6a

[ "MIT" ]

1

2019-05-10T08:10:00.000Z

pyts/__init__.py

zhangxu0307/pyts

c66a3874dedd33a8109e0955f69074df6fdedf6a

[ "MIT" ]

null

pyts/__init__.py

zhangxu0307/pyts

c66a3874dedd33a8109e0955f69074df6fdedf6a

[ "MIT" ]

1

2020-08-15T11:07:40.000Z

from . import transformation, classification, visualization

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6

5f21cdeb2159a5be7e29a4a0366a4aad8db86469

177

py

Python

src/radauth/models.py

andrewyager/radius_restserver

8e355afad202b5fcf105a7a69eec8531fcf369e6

[ "MIT" ]

1

2022-03-26T01:52:35.000Z

src/radauth/models.py

andrewyager/radius_restserver

8e355afad202b5fcf105a7a69eec8531fcf369e6

[ "MIT" ]

null

src/radauth/models.py

andrewyager/radius_restserver

8e355afad202b5fcf105a7a69eec8531fcf369e6

[ "MIT" ]

null

from django.db import models from django.contrib.auth.models import AbstractUser class RadiusUser(AbstractUser): pass RadiusUser._meta.get_field('username').max_length = 255

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39ff199f758d37e793983b65f253e7276d38d29c

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py

Python

TASK7/Q2.py

rutvik2611/hw

69a725cbfa2d9bd996029cc7b2a2f7d07978941a

[ "MIT" ]

null

TASK7/Q2.py

rutvik2611/hw

69a725cbfa2d9bd996029cc7b2a2f7d07978941a

[ "MIT" ]

null

TASK7/Q2.py

rutvik2611/hw

69a725cbfa2d9bd996029cc7b2a2f7d07978941a

[ "MIT" ]

null

class Shape: def __init__(self): pass def area(self): return 0 class Square(Shape): def __init__(self, length): self.length = length def area(self): return self.length * self.length unittest = Square(88) print(unittest.area()) unittest2 = Shape() print((unittest2.area()))

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6

263ed12d164fb9a637e998a69de6cb08ec19fe4c

84

py

Python

mesh/__init__.py

TaplierShiru/PyOpenGL_train_data_NeuralTexture

d34eba865fed68d7ded3629e93f9537be089b91a

[ "MIT" ]

null

mesh/__init__.py

TaplierShiru/PyOpenGL_train_data_NeuralTexture

d34eba865fed68d7ded3629e93f9537be089b91a

[ "MIT" ]

null

mesh/__init__.py

TaplierShiru/PyOpenGL_train_data_NeuralTexture

d34eba865fed68d7ded3629e93f9537be089b91a

[ "MIT" ]

null

from __future__ import absolute_import from .mesh import Mesh del absolute_import

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6

26817ed8524ef7f43c72a8691ddf3622d2efc4fd

144

py

Python

gpsearch/plotting/__init__.py

Fluid-Dynamics-Group/gpsearch

8c5758c9fb2b623ef79952c3e9c113cb157d79bc

[ "MIT" ]

6

2020-07-13T00:02:17.000Z

2022-03-11T08:49:27.000Z

gpsearch/plotting/__init__.py

Fluid-Dynamics-Group/gpsearch

8c5758c9fb2b623ef79952c3e9c113cb157d79bc

[ "MIT" ]

null

gpsearch/plotting/__init__.py

Fluid-Dynamics-Group/gpsearch

8c5758c9fb2b623ef79952c3e9c113cb157d79bc

[ "MIT" ]

9

2020-07-18T13:29:46.000Z

2022-03-22T15:14:14.000Z

from .plot_error import plot_error, get_cases, get_color from .plot_pdf import plot_pdf from .plot_smp import plot_smp, plot_smp2D, plot_smp3D

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1

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6

cd0b44a19b908070a704a482758b4ecf9f5ce3dd

46

py

Python

elvis/modeling/__init__.py

seo-95/elvis

a89c759acdf6ce64c7e6863aeb68dc0ba3293fed

[ "Apache-2.0" ]

1

2021-08-01T13:55:27.000Z

elvis/modeling/__init__.py

seo-95/elvis

a89c759acdf6ce64c7e6863aeb68dc0ba3293fed

[ "Apache-2.0" ]

null

elvis/modeling/__init__.py

seo-95/elvis

a89c759acdf6ce64c7e6863aeb68dc0ba3293fed

[ "Apache-2.0" ]

null

from .meta_arch import * from .models import *

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6

cd18004eaec654381fabaf36a09f4df127a25da8

41

py

Python

infrastructure/abstracts/__init__.py

bykof/dragonball-clicker

70e7683a2617472c0d073adaa71203584bf42c87

[ "MIT" ]

1

2020-04-26T01:46:55.000Z

infrastructure/abstracts/__init__.py

bykof/dragonball-clicker

70e7683a2617472c0d073adaa71203584bf42c87

[ "MIT" ]

null

infrastructure/abstracts/__init__.py

bykof/dragonball-clicker

70e7683a2617472c0d073adaa71203584bf42c87

[ "MIT" ]

1

2020-05-26T14:02:46.000Z

from .balance_client import BalanceClient

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1

0

6

cd608a69b1810ea0b9173a1d53c10e5250d08bba

380

py

Python

typed_python/compiler/function_metadata.py

APrioriInvestments/typed_python

a3191e5d30333eba156c2a910abc78f7813dcaa3

[ "Apache-2.0" ]

105

2019-12-02T01:44:46.000Z

2022-03-28T20:27:38.000Z

typed_python/compiler/function_metadata.py

APrioriInvestments/typed_python

a3191e5d30333eba156c2a910abc78f7813dcaa3

[ "Apache-2.0" ]

173

2019-10-08T19:37:06.000Z

2022-01-24T18:43:42.000Z

typed_python/compiler/function_metadata.py

APrioriInvestments/typed_python

a3191e5d30333eba156c2a910abc78f7813dcaa3

[ "Apache-2.0" ]

1

2020-01-23T00:06:42.000Z

class FunctionMetadata: def __init__(self): self._constantReturnValue = () def setConstantReturnValue(self, value): self._constantReturnValue = (value,) def hasConstantReturnValue(self): return self._constantReturnValue def getConstantReturnValue(self): return self._constantReturnValue[0] if self._constantReturnValue else None

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6

26e1accc6f1a0272a39ee14e7876e3e65600815c

155

py

Python

test/fixtures/__init__.py

rraallvv/python-client

65d0c3f835ed8ce3ba6bfa2565cac61f7da6b748

[ "Apache-2.0" ]

4

2020-11-03T21:13:13.000Z

2022-01-18T08:40:27.000Z

test/fixtures/__init__.py

rraallvv/python-client

65d0c3f835ed8ce3ba6bfa2565cac61f7da6b748

[ "Apache-2.0" ]

1

2020-08-09T21:36:02.000Z

test/fixtures/__init__.py

rraallvv/python-client

65d0c3f835ed8ce3ba6bfa2565cac61f7da6b748

[ "Apache-2.0" ]

1

2020-08-03T01:05:44.000Z

from .account import * from .block import * from .mempool import * from .miner import * from .node import * from .peer import * from .transaction import *

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6

f8095a683edaf2570a53e99165f2c7f5a3856640

35

py

Python

app_finalizada/main/models/__init__.py

NelsonMilla/mi-pimer-sitio-en-django

348ada5888361804350215f2967dbecd544857a2

[ "Apache-2.0" ]

1

2021-12-17T04:39:40.000Z

app_finalizada/main/models/__init__.py

NelsonMilla/mi-pimer-sitio-en-django

348ada5888361804350215f2967dbecd544857a2

[ "Apache-2.0" ]

null

app_finalizada/main/models/__init__.py

NelsonMilla/mi-pimer-sitio-en-django

348ada5888361804350215f2967dbecd544857a2

[ "Apache-2.0" ]

null

from main.models.blog_post import *

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1

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1

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6

f8349c836012a043efc2763d930bcc13e4e7d7c2

114

py

Python

nextcord/ext/interactions/slash/__init__.py

abrahammurciano/nextcord

e55be422a1b923fc498b04f82172d5a0d263eb71

[ "MIT" ]

null

nextcord/ext/interactions/slash/__init__.py

abrahammurciano/nextcord

e55be422a1b923fc498b04f82172d5a0d263eb71

[ "MIT" ]

null

nextcord/ext/interactions/slash/__init__.py

abrahammurciano/nextcord

e55be422a1b923fc498b04f82172d5a0d263eb71

[ "MIT" ]

null

from .slash_command import SlashCommand from .slash_context import SlashContext from .slash_decorator import slash

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6

f86ed4750d37d9362fa1b38a64d3476441f8fd89

161

py

Python

birg_chemometrics_tools/processing/dynamic_adaptive_binning.py

BiRG/chemometrics_tools

f96aa5fc2478ce454f110f4940ff29632c2e0324

[ "MIT" ]

null

birg_chemometrics_tools/processing/dynamic_adaptive_binning.py

BiRG/chemometrics_tools

f96aa5fc2478ce454f110f4940ff29632c2e0324

[ "MIT" ]

null

birg_chemometrics_tools/processing/dynamic_adaptive_binning.py

BiRG/chemometrics_tools

f96aa5fc2478ce454f110f4940ff29632c2e0324

[ "MIT" ]

null

from sklearn.base import BaseEstimator, TransformerMixin class DynamicAdaptiveBinning(BaseEstimator, TransformerMixin): def __init__(self, ): pass

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3e1e901eaa520d43fa5f45c5a1b1f74372a303da

638

py

Python

detector/object_detection/keras_retinanet/backend/tensorflow_backend.py

CianciarusoCataldo/nn-object-detector

a1a51f3e8ff295851759664c9155f8ceecb33256

[ "MIT" ]

1

2019-07-02T03:14:56.000Z

detector/object_detection/keras_retinanet/backend/tensorflow_backend.py

CianciarusoCataldo/nn-object-detector

a1a51f3e8ff295851759664c9155f8ceecb33256

[ "MIT" ]

9

2020-01-28T22:48:49.000Z

2022-02-10T00:11:17.000Z

detector/object_detection/keras_retinanet/backend/tensorflow_backend.py

CianciarusoCataldo/nn-object-detector

a1a51f3e8ff295851759664c9155f8ceecb33256

[ "MIT" ]

null

import tensorflow import keras def resize_images(*args, **kwargs): return tensorflow.image.resize_images(*args, **kwargs) def non_max_suppression(*args, **kwargs): return tensorflow.image.non_max_suppression(*args, **kwargs) def range(*args, **kwargs): return tensorflow.range(*args, **kwargs) def scatter_nd(*args, **kwargs): return tensorflow.scatter_nd(*args, **kwargs) def gather_nd(*args, **kwargs): return tensorflow.gather_nd(*args, **kwargs) def meshgrid(*args, **kwargs): return tensorflow.meshgrid(*args, **kwargs) def where(*args, **kwargs): return tensorflow.where(*args, **kwargs)

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e421a08fd70dc88cfc0c0c0f9505a5077ce3a039

2,294

py

Python

tests/test_iframes.py

alialdakheel/splinter

b4c48dc0af9ef98d7d9268f42f4d31a51e65fd68

[ "BSD-3-Clause" ]

null

tests/test_iframes.py

alialdakheel/splinter

b4c48dc0af9ef98d7d9268f42f4d31a51e65fd68

[ "BSD-3-Clause" ]

null

tests/test_iframes.py

alialdakheel/splinter

b4c48dc0af9ef98d7d9268f42f4d31a51e65fd68

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- # Copyright 2012 splinter authors. All rights reserved. # Use of this source code is governed by a BSD-style # license that can be found in the LICENSE file. from .base import supported_browsers from .fake_webapp import EXAMPLE_APP import pytest @pytest.mark.parametrize('browser_name', supported_browsers) def test_can_work_on_iframes_by_name(get_new_browser, browser_name): """can work on iframes and switch back to the page""" browser = get_new_browser(browser_name) browser.visit(EXAMPLE_APP) with browser.get_iframe("iframemodal-name") as frame: value = frame.find_by_tag("h1").value assert "IFrame Example Header" == value value = browser.find_by_tag("h1").value assert "Example Header" == value @pytest.mark.parametrize('browser_name', supported_browsers) def test_can_work_on_iframes_by_id(get_new_browser, browser_name): """can work on iframes and switch back to the page""" browser = get_new_browser(browser_name) browser.visit(EXAMPLE_APP) with browser.get_iframe("iframemodal") as frame: value = frame.find_by_tag("h1").value assert "IFrame Example Header" == value value = browser.find_by_tag("h1").value assert "Example Header" == value @pytest.mark.parametrize('browser_name', supported_browsers) def test_can_work_on_iframes_by_webelement(get_new_browser, browser_name): """can work on iframes and switch back to the page""" browser = get_new_browser(browser_name) browser.visit(EXAMPLE_APP) elem = browser.find_by_id('iframemodal').first with browser.get_iframe(elem) as frame: value = frame.find_by_tag("h1").value assert "IFrame Example Header" == value value = browser.find_by_tag("h1").value assert "Example Header" == value @pytest.mark.parametrize('browser_name', supported_browsers) def test_can_work_on_iframes_by_index(get_new_browser, browser_name): """can work on iframes and switch back to the page""" browser = get_new_browser(browser_name) browser.visit(EXAMPLE_APP) with browser.get_iframe(0) as frame: value = frame.find_by_tag("h1").value assert "IFrame Example Header" == value value = browser.find_by_tag("h1").value assert "Example Header" == value

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6

e42f4399153454fb25de80cd415fe1ce085e8361

80

py

Python

cedar/stores/tests/test_stores_gdrive.py

ceholden/cedar-datacube

d9463a28ce52665faaed069481d34a5ebe60558e

[ "BSD-3-Clause" ]

12

2019-07-19T17:35:24.000Z

2021-12-29T20:22:12.000Z

cedar/stores/tests/test_stores_gdrive.py

ceholden/cedar-datacube

d9463a28ce52665faaed069481d34a5ebe60558e

[ "BSD-3-Clause" ]

null

cedar/stores/tests/test_stores_gdrive.py

ceholden/cedar-datacube

d9463a28ce52665faaed069481d34a5ebe60558e

[ "BSD-3-Clause" ]

2

2019-10-06T06:36:39.000Z

2020-06-15T04:07:07.000Z

""" Tests for :py:mod:`cedar.stores.gdrive` """ from cedar.stores import gdrive

20

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6

e444aa17a5252213e15ac9bdd1985aa520b6db0d

34

py

Python

python/cinn/framework.py

edithgogo/CINN

bed13f4752d80d01a3e1d96a4cc4f5aa56b1e292

[ "Apache-2.0" ]

1

2019-10-23T09:16:23.000Z

python/cinn/framework.py

edithgogo/CINN

bed13f4752d80d01a3e1d96a4cc4f5aa56b1e292

[ "Apache-2.0" ]

null

python/cinn/framework.py

edithgogo/CINN

bed13f4752d80d01a3e1d96a4cc4f5aa56b1e292

[ "Apache-2.0" ]

null

from .core_api.framework import *

17

33

0.794118

5

34

5.2

1

0

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34

1

34

0.866667

0

1

0

true

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1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

e45b9075a850de3d2d19e0dbc3d7eb39588d169f

94

py

Python

lib/pyexcel/pyexcel/ext/ods.py

tinygg/QQ-Groups-Spider

a161282c6832ed40183905e96205edb5a57e8a05

[ "MIT" ]

null

lib/pyexcel/pyexcel/ext/ods.py

tinygg/QQ-Groups-Spider

a161282c6832ed40183905e96205edb5a57e8a05

[ "MIT" ]

null

lib/pyexcel/pyexcel/ext/ods.py

tinygg/QQ-Groups-Spider

a161282c6832ed40183905e96205edb5a57e8a05

[ "MIT" ]

1

2017-03-25T05:08:25.000Z

from ..deprecated import deprecated_pyexcel_ext deprecated_pyexcel_ext('0.2.2', __name__)

23.5

48

0.797872

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94

5.153846

0.615385

0.507463

0.597015

0

0.035714

0.106383

94

3

49

31.333333

0.761905

0

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true

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1

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null

0

1

0

1

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6

e47fc29273d58962c8ac1a431b9eda08dc8ef1b7

110

py

Python

mppi/__init__.py

marcodalessandro76/MPPI

ad60b73270b1f376ac501d47285146f1c3af457a

[ "MIT" ]

1

2019-05-04T09:26:36.000Z

mppi/__init__.py

marcodalessandro76/MPPI

ad60b73270b1f376ac501d47285146f1c3af457a

[ "MIT" ]

null

mppi/__init__.py

marcodalessandro76/MPPI

ad60b73270b1f376ac501d47285146f1c3af457a

[ "MIT" ]

null

import mppi.InputFiles import mppi.Calculators import mppi.Datasets import mppi.Parsers import mppi.Utilities

18.333333

23

0.863636

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110

6.333333

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110

5

24

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true

0

1

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null

1

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null

0

1

0

1

0

1

0

6

e482ae8f9715ce3f7508437d093cfc8aed16f44b

9,092

py

Python

fireant/tests/slicer/query_builder/test_build_pagination.py

vladaspasic/fireant

2dbae6a97a927ef62fdcd5f37fcb51a7d6d55334

[ "Apache-2.0" ]

null

fireant/tests/slicer/query_builder/test_build_pagination.py

vladaspasic/fireant

2dbae6a97a927ef62fdcd5f37fcb51a7d6d55334

[ "Apache-2.0" ]

null

fireant/tests/slicer/query_builder/test_build_pagination.py

vladaspasic/fireant

2dbae6a97a927ef62fdcd5f37fcb51a7d6d55334

[ "Apache-2.0" ]

null

from unittest import TestCase from unittest.mock import ( ANY, Mock, patch, ) import numpy as np import pandas as pd from pandas.testing import assert_frame_equal from fireant.slicer.queries.pagination import paginate from pypika import Order from ..mocks import ( cat_uni_dim_df, cont_cat_dim_df, cont_cat_uni_dim_df, ) TS = '$d$timestamp' mock_table_widget = Mock() mock_table_widget.group_pagination = False mock_chart_widget = Mock() mock_chart_widget.group_pagination = True mock_dimension_definition = Mock() mock_dimension_definition.alias = '$d$political_party' mock_metric_definition = Mock() mock_metric_definition.alias = '$m$votes' class SimplePaginationTests(TestCase): @patch('fireant.slicer.queries.pagination._simple_paginate') def test_that_with_no_widgets_using_group_pagination_that_simple_pagination_is_applied(self, mock_paginate): paginate(cont_cat_dim_df, [mock_table_widget]) mock_paginate.assert_called_once_with(ANY, ANY, ANY, ANY) @patch('fireant.slicer.queries.pagination._simple_paginate') def test_that_with_group_pagination_and_one_dimension_that_simple_pagination_is_applied(self, mock_paginate): paginate(cat_uni_dim_df, [mock_table_widget]) mock_paginate.assert_called_once_with(ANY, ANY, ANY, ANY) def test_paginate_with_limit_slice_data_frame_to_limit(self): paginated = paginate(cont_cat_dim_df, [mock_table_widget], limit=5) expected = cont_cat_dim_df[:5] assert_frame_equal(expected, paginated) def test_paginate_with_offset_slice_data_frame_from_offset(self): paginated = paginate(cont_cat_dim_df, [mock_table_widget], offset=5) expected = cont_cat_dim_df[5:] assert_frame_equal(expected, paginated) def test_paginate_with_limit_and_offset_slice_data_frame_from_offset_to_offset_plus_limit(self): paginated = paginate(cont_cat_dim_df, [mock_table_widget], limit=5, offset=5) expected = cont_cat_dim_df[5:10] assert_frame_equal(expected, paginated) def test_apply_sort_with_one_order_dimension_asc(self): paginated = paginate(cont_cat_dim_df, [mock_table_widget], orders=[(mock_dimension_definition, Order.asc)]) expected = cont_cat_dim_df.sort_values(by=[mock_dimension_definition.alias], ascending=True) assert_frame_equal(expected, paginated) def test_apply_sort_with_one_order_dimension_desc(self): paginated = paginate(cont_cat_dim_df, [mock_table_widget], orders=[(mock_dimension_definition, Order.desc)]) expected = cont_cat_dim_df.sort_values(by=[mock_dimension_definition.alias], ascending=False) assert_frame_equal(expected, paginated) def test_apply_sort_with_one_order_metric_asc(self): paginated = paginate(cont_cat_dim_df, [mock_table_widget], orders=[(mock_metric_definition, Order.asc)]) expected = cont_cat_dim_df.sort_values(by=[mock_metric_definition.alias], ascending=True) assert_frame_equal(expected, paginated) def test_apply_sort_with_one_order_metric_desc(self): paginated = paginate(cont_cat_dim_df, [mock_table_widget], orders=[(mock_metric_definition, Order.desc)]) expected = cont_cat_dim_df.sort_values(by=[mock_metric_definition.alias], ascending=False) assert_frame_equal(expected, paginated) def test_apply_sort_with_multiple_orders(self): paginated = paginate(cont_cat_dim_df, [mock_table_widget], orders=[(mock_dimension_definition, Order.asc), (mock_metric_definition, Order.desc)]) expected = cont_cat_dim_df.sort_values(by=[mock_dimension_definition.alias, mock_metric_definition.alias], ascending=[True, False]) assert_frame_equal(expected, paginated) def test_apply_sort_before_slice(self): paginated = paginate(cont_cat_dim_df, [mock_table_widget], orders=[(mock_metric_definition, Order.asc)], limit=5, offset=5) expected = cont_cat_dim_df.sort_values(by=[mock_metric_definition.alias], ascending=True)[5:10] assert_frame_equal(expected, paginated) class GroupPaginationTests(TestCase): @patch('fireant.slicer.queries.pagination._group_paginate') def test_with_one_widget_using_group_pagination_that_group_pagination_is_applied(self, mock_paginate): paginate(cont_cat_dim_df, [mock_chart_widget, mock_table_widget]) mock_paginate.assert_called_once_with(ANY, ANY, ANY, ANY) def test_paginate_with_limit_slice_data_frame_to_limit_in_each_group(self): paginated = paginate(cont_cat_dim_df, [mock_chart_widget], limit=2) index = cont_cat_dim_df.index reindex = pd.MultiIndex.from_product([index.levels[0], index.levels[1][:2]], names=index.names) expected = cont_cat_dim_df.reindex(reindex) \ .dropna() \ .astype(np.int64) assert_frame_equal(expected, paginated) def test_paginate_with_offset_slice_data_frame_from_offset_in_each_group(self): paginated = paginate(cont_cat_dim_df, [mock_chart_widget], offset=2) index = cont_cat_dim_df.index reindex = pd.MultiIndex.from_product([index.levels[0], index.levels[1][2:]], names=index.names) expected = cont_cat_dim_df.reindex(reindex) assert_frame_equal(expected, paginated) def test_paginate_with_limit_and_offset_slice_data_frame_from_offset_to_offset_plus_limit_in_each_group(self): paginated = paginate(cont_cat_dim_df, [mock_chart_widget], limit=1, offset=1) index = cont_cat_dim_df.index reindex = pd.MultiIndex.from_product([index.levels[0], index.levels[1][1:2]], names=index.names) expected = cont_cat_dim_df.reindex(reindex) \ .dropna() \ .astype(np.int64) assert_frame_equal(expected, paginated) def test_apply_sort_with_one_order_dimension_asc(self): paginated = paginate(cont_cat_dim_df, [mock_chart_widget], orders=[(mock_dimension_definition, Order.asc)]) expected = cont_cat_dim_df.sort_values(by=[TS, mock_dimension_definition.alias], ascending=True) assert_frame_equal(expected, paginated) def test_apply_sort_with_one_order_dimension_desc(self): paginated = paginate(cont_cat_dim_df, [mock_chart_widget], orders=[(mock_dimension_definition, Order.desc)]) expected = cont_cat_dim_df.sort_values(by=[TS, mock_dimension_definition.alias], ascending=(True, False)) assert_frame_equal(expected, paginated) def test_apply_sort_with_one_order_metric_asc(self): paginated = paginate(cont_cat_dim_df, [mock_chart_widget], orders=[(mock_metric_definition, Order.asc)]) expected = cont_cat_dim_df.iloc[[1, 0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]] assert_frame_equal(expected, paginated) def test_apply_sort_with_one_order_metric_desc(self): paginated = paginate(cont_cat_dim_df, [mock_chart_widget], orders=[(mock_metric_definition, Order.desc)]) expected = cont_cat_dim_df.iloc[[2, 0, 1, 4, 3, 6, 5, 8, 7, 10, 9, 12, 11]] assert_frame_equal(expected, paginated) def test_apply_sort_multiple_levels_df(self): paginated = paginate(cont_cat_uni_dim_df, [mock_chart_widget], orders=[(mock_metric_definition, Order.asc)]) sorted_groups = cont_cat_uni_dim_df.groupby(level=[1, 2]).sum().sort_values(by='$m$votes', ascending=True).index expected = cont_cat_uni_dim_df \ .groupby(level=0) \ .apply(lambda df: df.reset_index(level=0, drop=True).reindex(sorted_groups)) \ .dropna() expected[['$m$votes', '$m$wins']] = expected[['$m$votes', '$m$wins']].astype(np.int64) assert_frame_equal(expected, paginated) def test_apply_sort_with_multiple_orders(self): paginated = paginate(cont_cat_dim_df, [mock_chart_widget], orders=[(mock_dimension_definition, Order.asc), (mock_metric_definition, Order.desc)]) expected = cont_cat_dim_df.sort_values(by=[TS, mock_dimension_definition.alias, mock_metric_definition.alias], ascending=[True, True, False]) assert_frame_equal(expected, paginated) def test_apply_sort_before_slice(self): paginated = paginate(cont_cat_dim_df, [mock_chart_widget], limit=1, offset=1, orders=[(mock_metric_definition, Order.asc)]) expected = cont_cat_dim_df.iloc[[0, 3, 5, 7, 9, 11]] assert_frame_equal(expected, paginated)

45.688442

120

0.690387

1,176

9,092

4.891156

0.098639

0.041725

0.073018

0.087622

0.854659

0.839013

0.823018

0.807024

0.803894

0.777469

0

0.011105

0.217554

9,092

198

121

45.919192

0.797442

0

0.37931

0

0.024747

0.016388

0

0.158621

1

0.151724

false

0

0.055172

0

0.22069

0

null

0

1

0

null

0

6

900bd30770fc3a3e9ffc58aea48d1ec24bbecd19

203

py

Python

django_recurly/models.py

BuloZB/django-recurly

68457da7d37d3f591dc0ba2e80dead3d2463cb6d

[ "BSD-3-Clause" ]

null

django_recurly/models.py

BuloZB/django-recurly

68457da7d37d3f591dc0ba2e80dead3d2463cb6d

[ "BSD-3-Clause" ]

null

django_recurly/models.py

BuloZB/django-recurly

68457da7d37d3f591dc0ba2e80dead3d2463cb6d

[ "BSD-3-Clause" ]

null

import recurly from django.conf import settings recurly.API_KEY = settings.RECURLY_API_KEY if hasattr(settings, 'RECURLY_JS_PRIVATE_KEY'): recurly.js.PRIVATE_KEY = settings.RECURLY_JS_PRIVATE_KEY

22.555556

60

0.82266

30

203

5.233333

0.4

0.382166

0.305732

0.363057

0.343949

0

0.108374

203

8

61

25.375

0.867403

0

0.108374

0

1

0

true

0

0.4

0

0.4

0

null

1

0

1

0

null

0

1

0

1

0

6

5f88aad6706899310006ca4e5db7728c3d42be1b

21

py

Python

example_project/some_modules/third_modules/a123.py

Yuriy-Leonov/cython_imports_limit_issue

2f9e7c02798fb52185dabfe6ce3811c439ca2839

[ "MIT" ]

null

example_project/some_modules/third_modules/a123.py

Yuriy-Leonov/cython_imports_limit_issue

2f9e7c02798fb52185dabfe6ce3811c439ca2839

[ "MIT" ]

null

example_project/some_modules/third_modules/a123.py

Yuriy-Leonov/cython_imports_limit_issue

2f9e7c02798fb52185dabfe6ce3811c439ca2839

[ "MIT" ]

null

class A123: pass

7

11

0.619048

3

21

4.333333

1

0

0.214286

0.333333

21

2

12

10.5

0.714286

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

6

39652cf5847849c4d5e83b267391db745270369c

413

py

Python

flight_ad/wrangling/__init__.py

coelhosilva/flight-ad

5dc3079495a604ff5a2577e00ce64ec599f9bb33

[ "MIT" ]

2

2021-07-05T21:06:03.000Z

2021-08-11T21:35:12.000Z

flight_ad/wrangling/__init__.py

coelhosilva/flight-ad

5dc3079495a604ff5a2577e00ce64ec599f9bb33

[ "MIT" ]

null

flight_ad/wrangling/__init__.py

coelhosilva/flight-ad

5dc3079495a604ff5a2577e00ce64ec599f9bb33

[ "MIT" ]

2

2021-06-30T19:45:28.000Z

2021-11-29T11:07:52.000Z

"""Data wrangling tools.""" from .wrangler import DataWrangler from .operations import insert_missing_data, retrieve_all_parameters, map_parameters, resample_dataframe, get_touchdown_index, change_column_reference __all__ = [ 'DataWrangler', 'insert_missing_data', 'retrieve_all_parameters', 'map_parameters', 'resample_dataframe', 'get_touchdown_index', 'change_column_reference' ]

27.533333

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0.772397

44

413

6.704545

0.5

0.088136

0.115254

0.169492

0.718644

0

0.138015

413

14

151

29.5

0.828652

0.050847

0

0.331606

0.119171

0

1

0

false

0

0.181818

0

0.181818

0

null

0

1

0

1

0

null

0

6

39812557f060b09043b22ff9a11bbcee17db040a

148

py

Python

micado/launcher/occopus.py

maystery/micado-client

17e4d0f641ee496a9f28a625c558e9f244132152

[ "Apache-2.0" ]

null

micado/launcher/occopus.py

maystery/micado-client

17e4d0f641ee496a9f28a625c558e9f244132152

[ "Apache-2.0" ]

1

2022-03-29T12:34:27.000Z

micado/launcher/occopus.py

maystery/micado-client

17e4d0f641ee496a9f28a625c558e9f244132152

[ "Apache-2.0" ]

7

2020-08-06T19:13:20.000Z

2021-04-20T10:32:20.000Z

""" Low-level methods for handling a MiCADO master with Occopus """ class OccopusLauncher: """For launching a MiCADO Master with Occopus """

24.666667

59

0.716216

19

148

5.578947

0.684211

0.132075

0.245283

0.320755

0.45283

0

0.189189

148

6

60

24.666667

0.883333

0.722973

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

3995b806da523aafe477f944219acf5ea03c17d4

117

py

Python

curso/admin.py

Miguelrom/EasyApproval

14bc48086ca20a2830d0ff17961a7cec84ea42bc

[ "Apache-2.0" ]

null

curso/admin.py

Miguelrom/EasyApproval

14bc48086ca20a2830d0ff17961a7cec84ea42bc

[ "Apache-2.0" ]

3

2019-12-03T22:36:30.000Z

2019-12-12T01:27:34.000Z

curso/admin.py

Miguelrom/EasyApproval

14bc48086ca20a2830d0ff17961a7cec84ea42bc

[ "Apache-2.0" ]

12

2019-12-03T22:36:12.000Z

2019-12-12T05:52:15.000Z

from django.contrib import admin from .models import * admin.site.register(Curso) admin.site.register(Inscripcion)

16.714286

32

0.803419

16

117

5.875

0.625

0.234043

0.361702

0

0.102564

117

6

33

19.5

0.895238

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

39b3944f01ba3585764eaaf034564d1756285801

141

py

Python

b.py

Shrey2002/rockhacktober-2021

21af133a2225f7f23ad61e470e28df5808c45b68

[ "MIT" ]

1

2020-10-31T05:39:39.000Z

b.py

Shrey2002/rockhacktober-2021

21af133a2225f7f23ad61e470e28df5808c45b68

[ "MIT" ]

4

2021-10-03T11:12:25.000Z

2021-10-05T15:01:57.000Z

b.py

Shrey2002/rockhacktober-2021

21af133a2225f7f23ad61e470e28df5808c45b68

[ "MIT" ]

30

2021-10-02T14:24:35.000Z

2021-10-31T14:12:15.000Z

# 'guinea pig' is appended to the animals list animals.append('guinea pig') # Updated animals list print('Updated animals list: ', animals)

23.5

46

0.744681

20

141

5.25

0.55

0.314286

0.342857

0

0.148936

141

5

47

28.2

0.875

0.460993

0

0.438356

0

1

0

true

0

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

6

f2d7d2a3fdf38875f90bdb6cc27a0ee05730a521

204

py

Python

hello/admin.py

chenyuan99/OwlSavesCats

d8135848db5e6092467ee0d31aa46c36599cace1

[ "MIT" ]

null

hello/admin.py

chenyuan99/OwlSavesCats

d8135848db5e6092467ee0d31aa46c36599cace1

[ "MIT" ]

null

hello/admin.py

chenyuan99/OwlSavesCats

d8135848db5e6092467ee0d31aa46c36599cace1

[ "MIT" ]

null

from django.contrib import admin from .models import * # Register your models here. admin.site.register(Paperclip) admin.site.register(Author) admin.site.register(Comment) admin.site.register(ArticlePost)

29.142857

32

0.818627

28

204

5.964286

0.5

0.215569

0.407186

0

0.078431

204

7

33

29.142857

0.888298

0.127451

0

1

0

true

0

0.333333

0

0.333333

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1

0

1

0

null

0

1

0

1

0

6

843a87f26c634a5fc9679c6feca1ed854c130f90

49

py

Python

cmd/hello/hello.py

RafaelFino/learnops

3bb091641980696ba222e6fa3cfa71b8e92cc9b8

[ "Apache-2.0" ]

null

cmd/hello/hello.py

RafaelFino/learnops

3bb091641980696ba222e6fa3cfa71b8e92cc9b8

[ "Apache-2.0" ]

null

cmd/hello/hello.py

RafaelFino/learnops

3bb091641980696ba222e6fa3cfa71b8e92cc9b8

[ "Apache-2.0" ]

null

print("Ola! sou seu primeiro programa em Python")

49

0.77551

8

49

4.75

1

0

0.122449

49

1

49

0.883721

0

0.8

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

84665f1f1661123f2b78765f0882b8610e8f6581

1,586

py

Python

wrappers/python/tests/did/test_set_did_metadata.py

absltkaos/indy-sdk

bc14c5b514dc1c76ce62dd7f6bf804120bf69f5e

[ "Apache-2.0" ]

null

wrappers/python/tests/did/test_set_did_metadata.py

absltkaos/indy-sdk

bc14c5b514dc1c76ce62dd7f6bf804120bf69f5e

[ "Apache-2.0" ]

null

wrappers/python/tests/did/test_set_did_metadata.py

absltkaos/indy-sdk

bc14c5b514dc1c76ce62dd7f6bf804120bf69f5e

[ "Apache-2.0" ]

null

import pytest from indy import did, error @pytest.mark.asyncio async def test_set_did_metadata_works(wallet_handle, metadata): (_did, _) = await did.create_and_store_my_did(wallet_handle, "{}") await did.set_did_metadata(wallet_handle, _did, metadata) @pytest.mark.asyncio async def test_set_did_metadata_works_for_replace(wallet_handle, metadata): (_did, _) = await did.create_and_store_my_did(wallet_handle, "{}") await did.set_did_metadata(wallet_handle, _did, metadata) received_metadata = await did.get_did_metadata(wallet_handle, _did) assert metadata == received_metadata new_metadata = 'new metadata' await did.set_did_metadata(wallet_handle, _did, new_metadata) updated_metadata = await did.get_did_metadata(wallet_handle, _did) assert new_metadata == updated_metadata @pytest.mark.asyncio async def test_set_did_metadata_works_for_empty_string(wallet_handle): (_did, _) = await did.create_and_store_my_did(wallet_handle, "{}") await did.set_did_metadata(wallet_handle, _did, '') @pytest.mark.asyncio async def test_set_did_metadata_works_for_invalid_handle(wallet_handle, did_my1, metadata): (_did, _) = await did.create_and_store_my_did(wallet_handle, "{}") with pytest.raises(error.WalletInvalidHandle): invalid_wallet_handle = wallet_handle + 1 await did.set_did_metadata(invalid_wallet_handle, did_my1, metadata) @pytest.mark.asyncio async def test_set_did_metadata_works_for_unknown_did(wallet_handle, did_my1, metadata): await did.set_did_metadata(wallet_handle, did_my1, metadata)

37.761905

91

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081bd6e3e0c1910698accb6f7b7b3edb0454dc3a

6,344

py

Python

tests/typing/test_fixp_inst.py

bogdanvuk/pygears

a0b21d445e1d5c89ad66751447b8253536b835ee

[ "MIT" ]

120

2018-04-23T08:29:04.000Z

2022-03-30T14:41:52.000Z

tests/typing/test_fixp_inst.py

FZP1607152286/pygears

a0b21d445e1d5c89ad66751447b8253536b835ee

[ "MIT" ]

12

2019-07-09T17:12:58.000Z

2022-03-18T09:05:10.000Z

tests/typing/test_fixp_inst.py

FZP1607152286/pygears

a0b21d445e1d5c89ad66751447b8253536b835ee

[ "MIT" ]

12

2019-05-10T19:42:08.000Z

2022-03-28T18:26:44.000Z

from math import ceil, floor from pygears.typing import Fixp, Ufixp, Uint, Int def test_abs(): uq2_3 = Ufixp[2, 3] q2_3 = Fixp[2, 3] q3_4 = Fixp[3, 4] assert abs(uq2_3.max) == uq2_3.max assert abs(q2_3.min) == q3_4(abs(float(q2_3.min))) def test_add(): uq2_3 = Ufixp[2, 3] uq2_4 = Ufixp[2, 4] uq3_4 = Ufixp[3, 4] uq3_5 = Ufixp[3, 5] uq4_5 = Ufixp[4, 5] uq4_6 = Ufixp[4, 6] q2_3 = Fixp[2, 3] q2_4 = Fixp[2, 4] q3_4 = Fixp[3, 4] q3_5 = Fixp[3, 5] q4_5 = Fixp[4, 5] q4_6 = Fixp[4, 6] q5_6 = Fixp[5, 6] q5_7 = Fixp[5, 7] assert uq2_3.quant + uq3_4.quant == uq4_5(float(uq2_3.quant) + float(uq3_4.quant)) assert uq2_3.max + uq3_4.max == uq4_5(11.0) assert uq3_4.max + uq3_4.max == uq4_5(15.0) assert uq2_4.quant + uq3_4.quant == uq4_6(float(uq2_4.quant) + float(uq3_4.quant)) assert uq2_4.max + uq3_4.max == uq4_6(11.25) assert uq3_4.max + uq3_5.max == uq4_6(15.25) assert q2_3.quant + q3_4.quant == q4_5(float(q2_3.quant) + float(q3_4.quant)) assert q2_3.max + q3_4.max == q4_5(5.0) assert q3_4.max + q3_4.max == q4_5(7.0) assert q2_4.quant + q3_4.quant == q4_6(float(q2_4.quant) + float(q3_4.quant)) assert q2_4.max + q3_4.max == q4_6(5.25) assert q3_4.max + q3_5.max == q4_6(7.25) assert uq2_3.quant + q3_4.quant == q4_5(float(uq2_3.quant) + float(q3_4.quant)) assert uq2_3.max + q3_4.max == q4_5(7.0) assert q2_3.max + uq3_4.max == q5_6(9.0) assert uq3_4.max + q3_4.max == q5_6(11.0) assert uq2_4.quant + q3_4.quant == q4_6(float(uq2_4.quant) + float(q3_4.quant)) assert uq2_4.max + q3_4.max == q4_6(7.25) assert uq3_4.max + q3_5.max == q5_7(11.25) assert q2_4.max + uq3_4.max == q5_7(9.25) assert q2_3.min + q3_4.max == q4_5(1.5) assert q3_4.min + q3_4.max == q4_5(-0.5) assert q2_4.min + q3_4.max == q4_6(1.5) assert q3_4.min + q3_5.max == q4_6(-0.25) assert uq2_3.max + q3_4.min == q4_5(-0.5) assert q2_3.min + uq3_4.max == q5_6(5.5) assert uq3_4.max + q3_4.min == q5_6(3.5) assert uq2_4.max + q3_4.min == q4_6(-0.25) assert uq3_4.max + q3_5.min == q5_7(3.5) assert q2_4.min + uq3_4.max == q5_7(5.5) def test_ceil(): uq2_4 = Ufixp[2, 4] q2_3 = Fixp[2, 3] uq4_4 = Ufixp[4, 4] q6_3 = Fixp[6, 3] assert ceil(uq2_4.max) == Ufixp[3, 5](4.0) assert ceil(uq2_4(3.25)) == Ufixp[3, 5](4.0) assert ceil(q2_3.min) == Fixp[3, 4](-2.0) assert ceil(q2_3(-1.5)) == Fixp[3, 4](-1.0) assert ceil(uq4_4.max) == uq4_4.max assert ceil(q6_3.min) == q6_3.min def test_floor(): uq2_4 = Ufixp[2, 4] q2_3 = Fixp[2, 3] uq4_4 = Ufixp[4, 4] q6_3 = Fixp[6, 3] assert floor(uq2_4.max) == uq2_4(3.0) assert floor(uq2_4(3.25)) == uq2_4(3.0) assert floor(q2_3.min) == q2_3(-2.0) assert floor(q2_3(-1.5)) == q2_3(-2.0) assert floor(uq4_4.max) == uq4_4.max assert floor(q6_3.min) == q6_3.min def test_ge(): uq2_3 = Ufixp[2, 3] q2_3 = Fixp[2, 3] assert uq2_3(1.5) >= q2_3(1.5) assert q2_3(1.5) >= uq2_3(1.5) assert uq2_3.max >= q2_3.min assert q2_3.max >= uq2_3.min def test_gt(): uq2_3 = Ufixp[2, 3] q2_3 = Fixp[2, 3] assert uq2_3(2.0) > q2_3(1.5) assert q2_3(1.5) > uq2_3(1.0) assert uq2_3.max > q2_3.min assert q2_3.max > uq2_3.min def test_le(): uq2_3 = Ufixp[2, 3] q2_3 = Fixp[2, 3] assert uq2_3(1.5) <= q2_3(1.5) assert q2_3(1.5) <= uq2_3(1.5) assert uq2_3.min <= q2_3.max assert q2_3.min <= uq2_3.max def test_lt(): uq2_3 = Ufixp[2, 3] q2_3 = Fixp[2, 3] assert uq2_3(1.0) < q2_3(1.5) assert q2_3(1.0) < uq2_3(1.5) assert uq2_3.min < q2_3.max assert q2_3.min < uq2_3.max def test_lshift(): uq2_3 = Ufixp[2, 3] uq4_3 = Ufixp[4, 3] q2_3 = Fixp[2, 3] q4_3 = Fixp[4, 3] assert uq2_3.max << 2 == uq4_3(14.0) assert q2_3.min << 2 == q4_3.min assert uq2_3.max << 0 == uq2_3.max assert q2_3.min << 0 == q2_3.min def test_neg(): uq2_3 = Ufixp[2, 3] q2_3 = Fixp[2, 3] q3_4 = Fixp[3, 4] assert -uq2_3.max == q3_4(-float(uq2_3.max)) assert -q2_3.min == q3_4(-float(q2_3.min)) def test_rshift(): uq2_3 = Ufixp[2, 3] uq4_3 = Ufixp[4, 3] q2_3 = Fixp[2, 3] q4_3 = Fixp[4, 3] assert uq4_3(14.0) >> 2 == uq2_3.max assert q4_3.min >> 2 == q2_3.min assert uq2_3.max >> 0 == uq2_3.max assert q2_3.min >> 0 == q2_3.min def test_round(): uq2_4 = Ufixp[2, 4] q2_3 = Fixp[2, 3] uq4_4 = Ufixp[4, 4] q6_3 = Fixp[6, 3] assert round(uq2_4.max) == Ufixp[3, 5](4.0) assert round(uq2_4(3.25)) == Ufixp[3, 5](3.0) assert round(q2_3.min) == Fixp[3, 4](-2.0) assert round(q2_3(-1.5)) == Fixp[3, 4](-1.0) assert round(uq4_4.max) == uq4_4.max assert round(q6_3.min) == q6_3.min def test_sub_val(): uq2_3 = Ufixp[2, 3] uq2_4 = Ufixp[2, 4] uq3_4 = Ufixp[3, 4] uq3_5 = Ufixp[3, 5] q2_3 = Fixp[2, 3] q2_4 = Fixp[2, 4] q3_4 = Fixp[3, 4] q3_5 = Fixp[3, 5] q4_5 = Fixp[4, 5] q4_6 = Fixp[4, 6] q5_6 = Fixp[5, 6] q5_7 = Fixp[5, 7] assert uq2_3.quant - uq3_4.quant == q4_5(0.0) assert uq2_3.min - uq3_4.max == q4_5(-7.5) assert uq2_4.quant - uq3_4.quant == q4_6(float(uq2_4.quant) - float(uq3_4.quant)) assert uq2_4.min - uq3_4.max == q4_6(-7.5) assert uq3_4.min - uq3_5.max == q4_6(-7.75) assert q2_3.quant - q3_4.quant == q4_5(0.0) assert q2_3.min - q3_4.max == q4_5(-5.5) assert q3_4.min - q3_4.max == q4_5(-7.5) assert q3_4.max - q3_4.min == q4_5(7.5) assert q2_4.quant - q3_4.quant == q4_6(float(q2_4.quant) - float(q3_4.quant)) assert q2_4.min - q3_4.max == q4_6(-5.5) assert q2_4.max - q3_4.min == q4_6(5.75) assert q3_4.min - q3_5.max == q4_6(-7.75) assert q3_4.max - q3_5.min == q4_6(7.5) assert uq2_3.quant - q3_4.quant == q4_5(0.0) assert uq2_3.max - q3_4.min == q4_5(7.5) assert q2_3.min - uq3_4.max == q5_6(-9.5) assert uq3_4.max - q3_4.min == q5_6(11.5) assert q3_4.min - uq3_4.max == q5_6(-11.5) assert uq2_4.quant - q3_4.quant == q4_6(float(uq2_4.quant) - float(q3_4.quant)) assert uq2_4.max - q3_4.min == q4_6(7.75) assert uq3_4.max - q3_5.min == q5_7(11.5) assert q2_4.min - uq3_4.max == q5_7(-9.5)

26.323651

86

0.581494

1,394

6,344

2.403874

0.037303

0.050134

0.037601

0.031036

0.89436

0.845419

0.760072

0.655028

0.635034

0.515369

0

0.203112

0.240227

6,344

240

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26.433333

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false

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1

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1

0

null

0

1

0

6

f230a1c86e4d67ff097a14aa72d06bf39a869aef

16,430

py

Python

yepes/contrib/standards/migrations/0001_initial.py

samuelmaudo/yepes

1ef9a42d4eaa70d9b3e6e7fa519396c1e1174fcb

[ "BSD-3-Clause" ]

null

yepes/contrib/standards/migrations/0001_initial.py

samuelmaudo/yepes

1ef9a42d4eaa70d9b3e6e7fa519396c1e1174fcb

[ "BSD-3-Clause" ]

null

yepes/contrib/standards/migrations/0001_initial.py

samuelmaudo/yepes

1ef9a42d4eaa70d9b3e6e7fa519396c1e1174fcb

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models import yepes.contrib.standards.model_mixins import mptt.fields import yepes.fields class Migration(migrations.Migration): dependencies = [ ] initial = True operations = [ migrations.CreateModel( name='Region', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('name', yepes.fields.CharField(help_text='You can find region names and United Nations codes here: <a target="_blank" href="http://en.wikipedia.org/wiki/UN_M.49">http://en.wikipedia.org/wiki/UN_M.49</a>', unique=True, max_length=127, verbose_name='Native Name')), ('name_de', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='German Name', blank=True)), ('name_en', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='English Name', blank=True)), ('name_es', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Spanish Name', blank=True)), ('name_fr', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='French Name', blank=True)), ('name_pt', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Portuguese Name', blank=True)), ('name_ru', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Russian Name', blank=True)), ('name_zh', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Chinese Name', blank=True)), ('number', yepes.fields.CharField(min_length=3, charset='0-9', max_length=3, help_text='Specify numeric region code, for example "150".', unique=True, verbose_name='Number')), ('lft', models.PositiveIntegerField(editable=False, db_index=True)), ('rght', models.PositiveIntegerField(editable=False, db_index=True)), ('tree_id', models.PositiveIntegerField(editable=False, db_index=True)), ('level', models.PositiveIntegerField(editable=False, db_index=True)), ('parent', mptt.fields.TreeForeignKey(related_name='children', verbose_name='Parent Region', to='standards.Region', null=True)), ], options={ 'ordering': ['name'], 'verbose_name': 'Supranational Region', 'verbose_name_plural': 'Supranational Regions', }, ), migrations.CreateModel( name='Country', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('is_enabled', models.BooleanField(default=True, verbose_name='Status', db_index=True, choices=[(True, 'Enabled'), (False, 'Disabled')])), ('name', yepes.fields.CharField(help_text='You can find country names and ISO codes here: <a target="_blank" href="http://en.wikipedia.org/wiki/ISO_3166-1">http://en.wikipedia.org/wiki/ISO_3166-1</a>', unique=True, max_length=127, verbose_name='Native Name')), ('name_de', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='German Name', blank=True)), ('name_en', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='English Name', blank=True)), ('name_es', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Spanish Name', blank=True)), ('name_fr', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='French Name', blank=True)), ('name_pt', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Portuguese Name', blank=True)), ('name_ru', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Russian Name', blank=True)), ('name_zh', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Chinese Name', blank=True)), ('region', models.ForeignKey(related_name='countries', verbose_name='Region', to='standards.Region')), ('code', yepes.fields.CharField(min_length=2, force_upper=True, charset='A-Z', max_length=2, help_text='Specify 2-letter country code, for example "ES".', unique=True, verbose_name='Code')), ('long_code', yepes.fields.CharField(min_length=3, force_upper=True, charset='A-Z', max_length=3, help_text='Specify 3-letter country code, for example "ESP".', unique=True, verbose_name='Long Code')), ('number', yepes.fields.CharField(min_length=3, charset='0-9', max_length=3, help_text='Specify numeric country code, for example "724".', unique=True, verbose_name='Number')), ], options={ 'ordering': ['name'], 'verbose_name': 'Country', 'verbose_name_plural': 'Countries', }, ), migrations.CreateModel( name='CountrySubdivision', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('is_enabled', models.BooleanField(default=True, verbose_name='Status', db_index=True, choices=[(True, 'Enabled'), (False, 'Disabled')])), ('name', yepes.fields.CharField(unique=True, max_length=127, verbose_name='Native Name')), ('name_de', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='German Name', blank=True)), ('name_en', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='English Name', blank=True)), ('name_es', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Spanish Name', blank=True)), ('name_fr', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='French Name', blank=True)), ('name_pt', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Portuguese Name', blank=True)), ('name_ru', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Russian Name', blank=True)), ('name_zh', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Chinese Name', blank=True)), ('code', yepes.fields.CharField(min_length=4, force_upper=True, charset='A-Z0-9\\-', max_length=6, help_text='Specify country subdivision code, for example "ES-O".', unique=True, verbose_name='Code')), ('country', models.ForeignKey(related_name='subdivisions', verbose_name='Country', to='standards.Country')), ], options={ 'ordering': ['name'], 'verbose_name': 'Country Subdivision', 'verbose_name_plural': 'Country Subdivisions', }, ), migrations.CreateModel( name='Currency', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('is_enabled', models.BooleanField(default=True, verbose_name='Status', db_index=True, choices=[(True, 'Enabled'), (False, 'Disabled')])), ('name', yepes.fields.CharField(help_text='You can find currency names and ISO codes here: <a target="_blank" href="http://en.wikipedia.org/wiki/ISO_4217">http://en.wikipedia.org/wiki/ISO_4217</a>', unique=True, max_length=127, verbose_name='Native Name')), ('name_de', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='German Name', blank=True)), ('name_en', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='English Name', blank=True)), ('name_es', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Spanish Name', blank=True)), ('name_fr', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='French Name', blank=True)), ('name_pt', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Portuguese Name', blank=True)), ('name_ru', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Russian Name', blank=True)), ('name_zh', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Chinese Name', blank=True)), ('symbol', yepes.fields.CharField(help_text='Specify currency symbol, for example "\u20ac".', force_upper=True, max_length=7, verbose_name='Symbol', db_index=True)), ('code', yepes.fields.CharField(min_length=3, force_upper=True, charset='A-Z', max_length=3, help_text='Specify 3-letter currency code, for example "EUR".', unique=True, verbose_name='Code')), ('number', yepes.fields.CharField(min_length=3, charset='0-9', max_length=3, help_text='Specify numeric currency code, for example "978".', unique=True, verbose_name='Number')), ('decimals', yepes.fields.SmallIntegerField(default=2, help_text='Number of digits after the decimal separator.', min_value=0, verbose_name='Decimals', max_value=6)), ('countries', models.ManyToManyField(help_text='Countries using this currency.', related_name='currencies', verbose_name='Countries', to='standards.Country', blank=True)), ], options={ 'ordering': ['name'], 'verbose_name': 'Currency', 'verbose_name_plural': 'Currencies', }, ), migrations.CreateModel( name='GeographicArea', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('creation_date', models.DateTimeField(auto_now_add=True, verbose_name='Creation Date')), ('last_modified', models.DateTimeField(auto_now=True, verbose_name='Last Modified')), ('name', yepes.fields.CharField(unique=True, max_length=127, verbose_name='Native Name')), ('name_de', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='German Name', blank=True)), ('name_en', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='English Name', blank=True)), ('name_es', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Spanish Name', blank=True)), ('name_fr', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='French Name', blank=True)), ('name_pt', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Portuguese Name', blank=True)), ('name_ru', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Russian Name', blank=True)), ('name_zh', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Chinese Name', blank=True)), ('api_id', yepes.fields.IdentifierField(verbose_name='API Id')), ('description', yepes.fields.TextField(verbose_name='Description', blank=True)), ('excluded_countries', models.ManyToManyField(related_name='areas_that_exclude_it', verbose_name='Excluded Countries', to='standards.Country', blank=True)), ('excluded_subdivisions', models.ManyToManyField(related_name='areas_that_exclude_it', verbose_name='Excluded Subdivisions', to='standards.CountrySubdivision', blank=True)), ('included_countries', models.ManyToManyField(related_name='areas_that_include_it', verbose_name='Included Countries', to='standards.Country', blank=True)), ('included_subdivisions', models.ManyToManyField(related_name='areas_that_include_it', verbose_name='Included Subdivisions', to='standards.CountrySubdivision', blank=True)), ], options={ 'verbose_name': 'Geographic Area', 'verbose_name_plural': 'Geographic Areas', }, ), migrations.CreateModel( name='Language', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('is_enabled', models.BooleanField(default=True, verbose_name='Status', db_index=True, choices=[(True, 'Enabled'), (False, 'Disabled')])), ('name', yepes.fields.CharField(help_text='You can find language names and ISO codes here: <a target="_blank" href="http://en.wikipedia.org/wiki/List_of_ISO_639-3_codes">http://en.wikipedia.org/wiki/List_of_ISO_639-3_codes</a>', unique=True, max_length=127, verbose_name='Native Name')), ('name_de', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='German Name', blank=True)), ('name_en', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='English Name', blank=True)), ('name_es', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Spanish Name', blank=True)), ('name_fr', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='French Name', blank=True)), ('name_pt', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Portuguese Name', blank=True)), ('name_ru', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Russian Name', blank=True)), ('name_zh', yepes.contrib.standards.model_mixins.LocalizedNameField(db_index=True, max_length=127, verbose_name='Chinese Name', blank=True)), ('tag', yepes.fields.CharField(min_length=2, charset='a-z', force_lower=True, max_length=3, help_text='You can find an explanation about the language tags here: <a target="_blank" href="http://www.w3.org/International/articles/language-tags/Overview.en.php">http://www.w3.org/International/articles/language-tags/Overview.en.php</a>', unique=True, verbose_name='Tag')), ('iso_639_1', yepes.fields.CharField(min_length=2, charset='a-z', force_lower=True, max_length=2, blank=True, help_text='Specify 2-letter language code, for example "es".', verbose_name='ISO 639-1', db_index=True)), ('iso_639_2', yepes.fields.CharField(min_length=3, charset='a-z', force_lower=True, max_length=3, blank=True, help_text='Specify 3-letter language code, for example "spa".', verbose_name='ISO 639-2', db_index=True)), ('iso_639_3', yepes.fields.CharField(min_length=3, charset='a-z', force_lower=True, max_length=3, blank=True, help_text='Specify 3-letter language code, for example "spa".', verbose_name='ISO 639-3', db_index=True)), ('countries', models.ManyToManyField(help_text='Countries where this language is official.', related_name='languages', verbose_name='Countries', to='standards.Country', blank=True)), ], options={ 'ordering': ['name'], 'verbose_name': 'Language', 'verbose_name_plural': 'Languages', }, ), ]

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385

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0.056962

0

null

0

1

0

null

0

6

f275e05a9942235b3ad67f5b64542c077dfab9e5

33

py

Python

ExtractTable/__init__.py

RenaissanceAI/ExtractTable-py

59910387bdf314c7f0e4953fecfc6c4781d5b79a

[ "Apache-2.0" ]

null

ExtractTable/__init__.py

RenaissanceAI/ExtractTable-py

59910387bdf314c7f0e4953fecfc6c4781d5b79a

[ "Apache-2.0" ]

null

ExtractTable/__init__.py

RenaissanceAI/ExtractTable-py

59910387bdf314c7f0e4953fecfc6c4781d5b79a

[ "Apache-2.0" ]

null

from .client import ExtractTable

16.5

32

0.848485

4

33

7

1

0

0.121212

33

1

33

0.965517

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null

0

1

0

1

0

1

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6

f29abc40fc893cce874289161fa1d40c71f5ece1

137

py

Python

users/tests.py

Jonas-Quinn/deliverance

9a99cf9d24a4711dc055f7578df0ba48bdc9bbee

[ "MIT" ]

1

2020-02-11T07:25:47.000Z

users/tests.py

Jonas-Quinn/deliverance

9a99cf9d24a4711dc055f7578df0ba48bdc9bbee

[ "MIT" ]

9

2020-02-27T22:40:07.000Z

2022-03-12T00:14:39.000Z

users/tests.py

Jonas-Quinn/deliverance

9a99cf9d24a4711dc055f7578df0ba48bdc9bbee

[ "MIT" ]

null

from django.test import TestCase from django.utils import unittest from django.contrib.auth.models import User # Create your tests here.

27.4

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0.824818

21

137

5.380952

0.714286

0.265487

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0.124088

137

4

44

34.25

0.941667

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true

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1

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null

0

1

0

1

0

1

0

6

4b66046a88e68bf78b5f14825a74df64cb624703

137

py

Python

14-Python/Demos/Day-01/Demo-05.py

helghareeb/OSTrack2019

3ef5af0f56f8640e92c1f3c3b3d76b8df2783f48

[ "MIT" ]

5

2019-08-04T22:30:35.000Z

2020-02-24T11:18:22.000Z

14-Python/Demos/Day-01/Demo-05.py

helghareeb/OSTrack2019

3ef5af0f56f8640e92c1f3c3b3d76b8df2783f48

[ "MIT" ]

2

2019-08-11T21:51:32.000Z

2019-08-21T11:12:22.000Z

14-Python/Demos/Day-01/Demo-05.py

helghareeb/OSTrack2019

3ef5af0f56f8640e92c1f3c3b3d76b8df2783f48

[ "MIT" ]

14

2019-08-05T21:11:03.000Z

2019-09-29T16:05:52.000Z

# سم الله الرحمن الرحيم def add_numbers(a, b): return a + b print(add_numbers(1,2)) print(add_numbers(3,4)) print(add_numbers(6,7))

17.125

23

0.70073

27

137

3.407407

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0.48913

0

0.051282

0.145985

137

8

24

17.125

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0.153285

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false

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null

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0

1

0

null

0

1

0

1

0

6

4b7a7491f4d5369cee7de7115aaebee7222f472e

95,392

py

Python

features/bert_similarity_between_engaged_and_engaging_surfacing_tweet_vectors_feature.py

wantedly/recsys2020-challenge

d9967860cc4767380d28d2ed7af00d467cc6941a

[ "Apache-2.0" ]

35

2020-06-23T05:33:50.000Z

2021-11-22T08:22:42.000Z

features/bert_similarity_between_engaged_and_engaging_surfacing_tweet_vectors_feature.py

wantedly/recsys2020-challenge

d9967860cc4767380d28d2ed7af00d467cc6941a

[ "Apache-2.0" ]

15

2020-12-28T05:31:06.000Z

2021-01-22T06:49:28.000Z

features/bert_similarity_between_engaged_and_engaging_surfacing_tweet_vectors_feature.py

wantedly/recsys2020-challenge

d9967860cc4767380d28d2ed7af00d467cc6941a

[ "Apache-2.0" ]

2

2020-06-30T10:02:05.000Z

2021-05-22T09:57:19.000Z

from typing import List, Tuple from google.cloud import bigquery, bigquery_storage_v1beta1 import pandas as pd from base import BaseFeature, reduce_mem_usage class BertSimilarityBetweenEngagedAndEngagingSurfacingTweetVectorsFeature(BaseFeature): # 使わない def import_columns(self) -> List[str]: ... def make_features( self, df_train_input: pd.DataFrame, df_test_input: pd.DataFrame ) -> Tuple[pd.DataFrame, pd.DataFrame]: ... def read_and_save_features( self, train_table_name: str, test_table_name: str, train_output_path: str, test_output_path: str, ) -> None: df_train_features = self._read_from_bigquery(train_table_name) df_test_features = self._read_from_bigquery(test_table_name) df_train_features.columns = f"{self.name}_" + df_train_features.columns df_test_features.columns = f"{self.name}_" + df_test_features.columns if self.save_memory: self._logger.info("Reduce memory size - train data") df_train_features = reduce_mem_usage(df_train_features) self._logger.info("Reduce memory size - test data") df_test_features = reduce_mem_usage(df_test_features) self._logger.info(f"Saving features to {train_output_path}") df_train_features.to_feather(train_output_path) self._logger.info(f"Saving features to {test_output_path}") df_test_features.to_feather(test_output_path) def _read_from_bigquery(self, table_name: str) -> pd.DataFrame: self._logger.info(f"Reading from {table_name}") query = _QUERY.format(table_name=table_name) if self.debugging: query += " limit 10000" bqclient = bigquery.Client(project=self.PROJECT_ID) bqstorageclient = bigquery_storage_v1beta1.BigQueryStorageClient() df = ( bqclient.query(query) .result() .to_dataframe(bqstorage_client=bqstorageclient) ) return df _QUERY = r""" with surfacing_tweets as ( select tweet_id, engaging_user_id from `recsys2020.training` t group by tweet_id, engaging_user_id ), user_surfacing_tweet_vectors as ( select engaging_user_id as user_id, avg(gap_0) as gap_0, avg(gap_1) as gap_1, avg(gap_2) as gap_2, avg(gap_3) as gap_3, avg(gap_4) as gap_4, avg(gap_5) as gap_5, avg(gap_6) as gap_6, avg(gap_7) as gap_7, avg(gap_8) as gap_8, avg(gap_9) as gap_9, avg(gap_10) as gap_10, avg(gap_11) as gap_11, avg(gap_12) as gap_12, avg(gap_13) as gap_13, avg(gap_14) as gap_14, avg(gap_15) as gap_15, avg(gap_16) as gap_16, avg(gap_17) as gap_17, avg(gap_18) as gap_18, avg(gap_19) as gap_19, avg(gap_20) as gap_20, avg(gap_21) as gap_21, avg(gap_22) as gap_22, avg(gap_23) as gap_23, avg(gap_24) as gap_24, avg(gap_25) as gap_25, avg(gap_26) as gap_26, avg(gap_27) as gap_27, avg(gap_28) as gap_28, avg(gap_29) as gap_29, avg(gap_30) as gap_30, avg(gap_31) as gap_31, avg(gap_32) as gap_32, avg(gap_33) as gap_33, avg(gap_34) as gap_34, avg(gap_35) as gap_35, avg(gap_36) as gap_36, avg(gap_37) as gap_37, avg(gap_38) as gap_38, avg(gap_39) as gap_39, avg(gap_40) as gap_40, avg(gap_41) as gap_41, avg(gap_42) as gap_42, avg(gap_43) as gap_43, avg(gap_44) as gap_44, avg(gap_45) as gap_45, avg(gap_46) as gap_46, avg(gap_47) as gap_47, avg(gap_48) as gap_48, avg(gap_49) as gap_49, avg(gap_50) as gap_50, avg(gap_51) as gap_51, avg(gap_52) as gap_52, avg(gap_53) as gap_53, avg(gap_54) as gap_54, avg(gap_55) as gap_55, avg(gap_56) as gap_56, avg(gap_57) as gap_57, avg(gap_58) as gap_58, avg(gap_59) as gap_59, avg(gap_60) as gap_60, avg(gap_61) as gap_61, avg(gap_62) as gap_62, avg(gap_63) as gap_63, avg(gap_64) as gap_64, avg(gap_65) as gap_65, avg(gap_66) as gap_66, avg(gap_67) as gap_67, avg(gap_68) as gap_68, avg(gap_69) as gap_69, avg(gap_70) as gap_70, avg(gap_71) as gap_71, avg(gap_72) as gap_72, avg(gap_73) as gap_73, avg(gap_74) as gap_74, avg(gap_75) as gap_75, avg(gap_76) as gap_76, avg(gap_77) as gap_77, avg(gap_78) as gap_78, avg(gap_79) as gap_79, avg(gap_80) as gap_80, avg(gap_81) as gap_81, avg(gap_82) as gap_82, avg(gap_83) as gap_83, avg(gap_84) as gap_84, avg(gap_85) as gap_85, avg(gap_86) as gap_86, avg(gap_87) as gap_87, avg(gap_88) as gap_88, avg(gap_89) as gap_89, avg(gap_90) as gap_90, avg(gap_91) as gap_91, avg(gap_92) as gap_92, avg(gap_93) as gap_93, avg(gap_94) as gap_94, avg(gap_95) as gap_95, avg(gap_96) as gap_96, avg(gap_97) as gap_97, avg(gap_98) as gap_98, avg(gap_99) as gap_99, avg(gap_100) as gap_100, avg(gap_101) as gap_101, avg(gap_102) as gap_102, avg(gap_103) as gap_103, avg(gap_104) as gap_104, avg(gap_105) as gap_105, avg(gap_106) as gap_106, avg(gap_107) as gap_107, avg(gap_108) as gap_108, avg(gap_109) as gap_109, avg(gap_110) as gap_110, avg(gap_111) as gap_111, avg(gap_112) as gap_112, avg(gap_113) as gap_113, avg(gap_114) as gap_114, avg(gap_115) as gap_115, avg(gap_116) as gap_116, avg(gap_117) as gap_117, avg(gap_118) as gap_118, avg(gap_119) as gap_119, avg(gap_120) as gap_120, avg(gap_121) as gap_121, avg(gap_122) as gap_122, avg(gap_123) as gap_123, avg(gap_124) as gap_124, avg(gap_125) as gap_125, avg(gap_126) as gap_126, avg(gap_127) as gap_127, avg(gap_128) as gap_128, avg(gap_129) as gap_129, avg(gap_130) as gap_130, avg(gap_131) as gap_131, avg(gap_132) as gap_132, avg(gap_133) as gap_133, avg(gap_134) as gap_134, avg(gap_135) as gap_135, avg(gap_136) as gap_136, avg(gap_137) as gap_137, avg(gap_138) as gap_138, avg(gap_139) as gap_139, avg(gap_140) as gap_140, avg(gap_141) as gap_141, avg(gap_142) as gap_142, avg(gap_143) as gap_143, avg(gap_144) as gap_144, avg(gap_145) as gap_145, avg(gap_146) as gap_146, avg(gap_147) as gap_147, avg(gap_148) as gap_148, avg(gap_149) as gap_149, avg(gap_150) as gap_150, avg(gap_151) as gap_151, avg(gap_152) as gap_152, avg(gap_153) as gap_153, avg(gap_154) as gap_154, avg(gap_155) as gap_155, avg(gap_156) as gap_156, avg(gap_157) as gap_157, avg(gap_158) as gap_158, avg(gap_159) as gap_159, avg(gap_160) as gap_160, avg(gap_161) as gap_161, avg(gap_162) as gap_162, avg(gap_163) as gap_163, avg(gap_164) as gap_164, avg(gap_165) as gap_165, avg(gap_166) as gap_166, avg(gap_167) as gap_167, avg(gap_168) as gap_168, avg(gap_169) as gap_169, avg(gap_170) as gap_170, avg(gap_171) as gap_171, avg(gap_172) as gap_172, avg(gap_173) as gap_173, avg(gap_174) as gap_174, avg(gap_175) as gap_175, avg(gap_176) as gap_176, avg(gap_177) as gap_177, avg(gap_178) as gap_178, avg(gap_179) as gap_179, avg(gap_180) as gap_180, avg(gap_181) as gap_181, avg(gap_182) as gap_182, avg(gap_183) as gap_183, avg(gap_184) as gap_184, avg(gap_185) as gap_185, avg(gap_186) as gap_186, avg(gap_187) as gap_187, avg(gap_188) as gap_188, avg(gap_189) as gap_189, avg(gap_190) as gap_190, avg(gap_191) as gap_191, avg(gap_192) as gap_192, avg(gap_193) as gap_193, avg(gap_194) as gap_194, avg(gap_195) as gap_195, avg(gap_196) as gap_196, avg(gap_197) as gap_197, avg(gap_198) as gap_198, avg(gap_199) as gap_199, avg(gap_200) as gap_200, avg(gap_201) as gap_201, avg(gap_202) as gap_202, avg(gap_203) as gap_203, avg(gap_204) as gap_204, avg(gap_205) as gap_205, avg(gap_206) as gap_206, avg(gap_207) as gap_207, avg(gap_208) as gap_208, avg(gap_209) as gap_209, avg(gap_210) as gap_210, avg(gap_211) as gap_211, avg(gap_212) as gap_212, avg(gap_213) as gap_213, avg(gap_214) as gap_214, avg(gap_215) as gap_215, avg(gap_216) as gap_216, avg(gap_217) as gap_217, avg(gap_218) as gap_218, avg(gap_219) as gap_219, avg(gap_220) as gap_220, avg(gap_221) as gap_221, avg(gap_222) as gap_222, avg(gap_223) as gap_223, avg(gap_224) as gap_224, avg(gap_225) as gap_225, avg(gap_226) as gap_226, avg(gap_227) as gap_227, avg(gap_228) as gap_228, avg(gap_229) as gap_229, avg(gap_230) as gap_230, avg(gap_231) as gap_231, avg(gap_232) as gap_232, avg(gap_233) as gap_233, avg(gap_234) as gap_234, avg(gap_235) as gap_235, avg(gap_236) as gap_236, avg(gap_237) as gap_237, avg(gap_238) as gap_238, avg(gap_239) as gap_239, avg(gap_240) as gap_240, avg(gap_241) as gap_241, avg(gap_242) as gap_242, avg(gap_243) as gap_243, avg(gap_244) as gap_244, avg(gap_245) as gap_245, avg(gap_246) as gap_246, avg(gap_247) as gap_247, avg(gap_248) as gap_248, avg(gap_249) as gap_249, avg(gap_250) as gap_250, avg(gap_251) as gap_251, avg(gap_252) as gap_252, avg(gap_253) as gap_253, avg(gap_254) as gap_254, avg(gap_255) as gap_255, avg(gap_256) as gap_256, avg(gap_257) as gap_257, avg(gap_258) as gap_258, avg(gap_259) as gap_259, avg(gap_260) as gap_260, avg(gap_261) as gap_261, avg(gap_262) as gap_262, avg(gap_263) as gap_263, avg(gap_264) as gap_264, avg(gap_265) as gap_265, avg(gap_266) as gap_266, avg(gap_267) as gap_267, avg(gap_268) as gap_268, avg(gap_269) as gap_269, avg(gap_270) as gap_270, avg(gap_271) as gap_271, avg(gap_272) as gap_272, avg(gap_273) as gap_273, avg(gap_274) as gap_274, avg(gap_275) as gap_275, avg(gap_276) as gap_276, avg(gap_277) as gap_277, avg(gap_278) as gap_278, avg(gap_279) as gap_279, avg(gap_280) as gap_280, avg(gap_281) as gap_281, avg(gap_282) as gap_282, avg(gap_283) as gap_283, avg(gap_284) as gap_284, avg(gap_285) as gap_285, avg(gap_286) as gap_286, avg(gap_287) as gap_287, avg(gap_288) as gap_288, avg(gap_289) as gap_289, avg(gap_290) as gap_290, avg(gap_291) as gap_291, avg(gap_292) as gap_292, avg(gap_293) as gap_293, avg(gap_294) as gap_294, avg(gap_295) as gap_295, avg(gap_296) as gap_296, avg(gap_297) as gap_297, avg(gap_298) as gap_298, avg(gap_299) as gap_299, avg(gap_300) as gap_300, avg(gap_301) as gap_301, avg(gap_302) as gap_302, avg(gap_303) as gap_303, avg(gap_304) as gap_304, avg(gap_305) as gap_305, avg(gap_306) as gap_306, avg(gap_307) as gap_307, avg(gap_308) as gap_308, avg(gap_309) as gap_309, avg(gap_310) as gap_310, avg(gap_311) as gap_311, avg(gap_312) as gap_312, avg(gap_313) as gap_313, avg(gap_314) as gap_314, avg(gap_315) as gap_315, avg(gap_316) as gap_316, avg(gap_317) as gap_317, avg(gap_318) as gap_318, avg(gap_319) as gap_319, avg(gap_320) as gap_320, avg(gap_321) as gap_321, avg(gap_322) as gap_322, avg(gap_323) as gap_323, avg(gap_324) as gap_324, avg(gap_325) as gap_325, avg(gap_326) as gap_326, avg(gap_327) as gap_327, avg(gap_328) as gap_328, avg(gap_329) as gap_329, avg(gap_330) as gap_330, avg(gap_331) as gap_331, avg(gap_332) as gap_332, avg(gap_333) as gap_333, avg(gap_334) as gap_334, avg(gap_335) as gap_335, avg(gap_336) as gap_336, avg(gap_337) as gap_337, avg(gap_338) as gap_338, avg(gap_339) as gap_339, avg(gap_340) as gap_340, avg(gap_341) as gap_341, avg(gap_342) as gap_342, avg(gap_343) as gap_343, avg(gap_344) as gap_344, avg(gap_345) as gap_345, avg(gap_346) as gap_346, avg(gap_347) as gap_347, avg(gap_348) as gap_348, avg(gap_349) as gap_349, avg(gap_350) as gap_350, avg(gap_351) as gap_351, avg(gap_352) as gap_352, avg(gap_353) as gap_353, avg(gap_354) as gap_354, avg(gap_355) as gap_355, avg(gap_356) as gap_356, avg(gap_357) as gap_357, avg(gap_358) as gap_358, avg(gap_359) as gap_359, avg(gap_360) as gap_360, avg(gap_361) as gap_361, avg(gap_362) as gap_362, avg(gap_363) as gap_363, avg(gap_364) as gap_364, avg(gap_365) as gap_365, avg(gap_366) as gap_366, avg(gap_367) as gap_367, avg(gap_368) as gap_368, avg(gap_369) as gap_369, avg(gap_370) as gap_370, avg(gap_371) as gap_371, avg(gap_372) as gap_372, avg(gap_373) as gap_373, avg(gap_374) as gap_374, avg(gap_375) as gap_375, avg(gap_376) as gap_376, avg(gap_377) as gap_377, avg(gap_378) as gap_378, avg(gap_379) as gap_379, avg(gap_380) as gap_380, avg(gap_381) as gap_381, avg(gap_382) as gap_382, avg(gap_383) as gap_383, avg(gap_384) as gap_384, avg(gap_385) as gap_385, avg(gap_386) as gap_386, avg(gap_387) as gap_387, avg(gap_388) as gap_388, avg(gap_389) as gap_389, avg(gap_390) as gap_390, avg(gap_391) as gap_391, avg(gap_392) as gap_392, avg(gap_393) as gap_393, avg(gap_394) as gap_394, avg(gap_395) as gap_395, avg(gap_396) as gap_396, avg(gap_397) as gap_397, avg(gap_398) as gap_398, avg(gap_399) as gap_399, avg(gap_400) as gap_400, avg(gap_401) as gap_401, avg(gap_402) as gap_402, avg(gap_403) as gap_403, avg(gap_404) as gap_404, avg(gap_405) as gap_405, avg(gap_406) as gap_406, avg(gap_407) as gap_407, avg(gap_408) as gap_408, avg(gap_409) as gap_409, avg(gap_410) as gap_410, avg(gap_411) as gap_411, avg(gap_412) as gap_412, avg(gap_413) as gap_413, avg(gap_414) as gap_414, avg(gap_415) as gap_415, avg(gap_416) as gap_416, avg(gap_417) as gap_417, avg(gap_418) as gap_418, avg(gap_419) as gap_419, avg(gap_420) as gap_420, avg(gap_421) as gap_421, avg(gap_422) as gap_422, avg(gap_423) as gap_423, avg(gap_424) as gap_424, avg(gap_425) as gap_425, avg(gap_426) as gap_426, avg(gap_427) as gap_427, avg(gap_428) as gap_428, avg(gap_429) as gap_429, avg(gap_430) as gap_430, avg(gap_431) as gap_431, avg(gap_432) as gap_432, avg(gap_433) as gap_433, avg(gap_434) as gap_434, avg(gap_435) as gap_435, avg(gap_436) as gap_436, avg(gap_437) as gap_437, avg(gap_438) as gap_438, avg(gap_439) as gap_439, avg(gap_440) as gap_440, avg(gap_441) as gap_441, avg(gap_442) as gap_442, avg(gap_443) as gap_443, avg(gap_444) as gap_444, avg(gap_445) as gap_445, avg(gap_446) as gap_446, avg(gap_447) as gap_447, avg(gap_448) as gap_448, avg(gap_449) as gap_449, avg(gap_450) as gap_450, avg(gap_451) as gap_451, avg(gap_452) as gap_452, avg(gap_453) as gap_453, avg(gap_454) as gap_454, avg(gap_455) as gap_455, avg(gap_456) as gap_456, avg(gap_457) as gap_457, avg(gap_458) as gap_458, avg(gap_459) as gap_459, avg(gap_460) as gap_460, avg(gap_461) as gap_461, avg(gap_462) as gap_462, avg(gap_463) as gap_463, avg(gap_464) as gap_464, avg(gap_465) as gap_465, avg(gap_466) as gap_466, avg(gap_467) as gap_467, avg(gap_468) as gap_468, avg(gap_469) as gap_469, avg(gap_470) as gap_470, avg(gap_471) as gap_471, avg(gap_472) as gap_472, avg(gap_473) as gap_473, avg(gap_474) as gap_474, avg(gap_475) as gap_475, avg(gap_476) as gap_476, avg(gap_477) as gap_477, avg(gap_478) as gap_478, avg(gap_479) as gap_479, avg(gap_480) as gap_480, avg(gap_481) as gap_481, avg(gap_482) as gap_482, avg(gap_483) as gap_483, avg(gap_484) as gap_484, avg(gap_485) as gap_485, avg(gap_486) as gap_486, avg(gap_487) as gap_487, avg(gap_488) as gap_488, avg(gap_489) as gap_489, avg(gap_490) as gap_490, avg(gap_491) as gap_491, avg(gap_492) as gap_492, avg(gap_493) as gap_493, avg(gap_494) as gap_494, avg(gap_495) as gap_495, avg(gap_496) as gap_496, avg(gap_497) as gap_497, avg(gap_498) as gap_498, avg(gap_499) as gap_499, avg(gap_500) as gap_500, avg(gap_501) as gap_501, avg(gap_502) as gap_502, avg(gap_503) as gap_503, avg(gap_504) as gap_504, avg(gap_505) as gap_505, avg(gap_506) as gap_506, avg(gap_507) as gap_507, avg(gap_508) as gap_508, avg(gap_509) as gap_509, avg(gap_510) as gap_510, avg(gap_511) as gap_511, avg(gap_512) as gap_512, avg(gap_513) as gap_513, avg(gap_514) as gap_514, avg(gap_515) as gap_515, avg(gap_516) as gap_516, avg(gap_517) as gap_517, avg(gap_518) as gap_518, avg(gap_519) as gap_519, avg(gap_520) as gap_520, avg(gap_521) as gap_521, avg(gap_522) as gap_522, avg(gap_523) as gap_523, avg(gap_524) as gap_524, avg(gap_525) as gap_525, avg(gap_526) as gap_526, avg(gap_527) as gap_527, avg(gap_528) as gap_528, avg(gap_529) as gap_529, avg(gap_530) as gap_530, avg(gap_531) as gap_531, avg(gap_532) as gap_532, avg(gap_533) as gap_533, avg(gap_534) as gap_534, avg(gap_535) as gap_535, avg(gap_536) as gap_536, avg(gap_537) as gap_537, avg(gap_538) as gap_538, avg(gap_539) as gap_539, avg(gap_540) as gap_540, avg(gap_541) as gap_541, avg(gap_542) as gap_542, avg(gap_543) as gap_543, avg(gap_544) as gap_544, avg(gap_545) as gap_545, avg(gap_546) as gap_546, avg(gap_547) as gap_547, avg(gap_548) as gap_548, avg(gap_549) as gap_549, avg(gap_550) as gap_550, avg(gap_551) as gap_551, avg(gap_552) as gap_552, avg(gap_553) as gap_553, avg(gap_554) as gap_554, avg(gap_555) as gap_555, avg(gap_556) as gap_556, avg(gap_557) as gap_557, avg(gap_558) as gap_558, avg(gap_559) as gap_559, avg(gap_560) as gap_560, avg(gap_561) as gap_561, avg(gap_562) as gap_562, avg(gap_563) as gap_563, avg(gap_564) as gap_564, avg(gap_565) as gap_565, avg(gap_566) as gap_566, avg(gap_567) as gap_567, avg(gap_568) as gap_568, avg(gap_569) as gap_569, avg(gap_570) as gap_570, avg(gap_571) as gap_571, avg(gap_572) as gap_572, avg(gap_573) as gap_573, avg(gap_574) as gap_574, avg(gap_575) as gap_575, avg(gap_576) as gap_576, avg(gap_577) as gap_577, avg(gap_578) as gap_578, avg(gap_579) as gap_579, avg(gap_580) as gap_580, avg(gap_581) as gap_581, avg(gap_582) as gap_582, avg(gap_583) as gap_583, avg(gap_584) as gap_584, avg(gap_585) as gap_585, avg(gap_586) as gap_586, avg(gap_587) as gap_587, avg(gap_588) as gap_588, avg(gap_589) as gap_589, avg(gap_590) as gap_590, avg(gap_591) as gap_591, avg(gap_592) as gap_592, avg(gap_593) as gap_593, avg(gap_594) as gap_594, avg(gap_595) as gap_595, avg(gap_596) as gap_596, avg(gap_597) as gap_597, avg(gap_598) as gap_598, avg(gap_599) as gap_599, avg(gap_600) as gap_600, avg(gap_601) as gap_601, avg(gap_602) as gap_602, avg(gap_603) as gap_603, avg(gap_604) as gap_604, avg(gap_605) as gap_605, avg(gap_606) as gap_606, avg(gap_607) as gap_607, avg(gap_608) as gap_608, avg(gap_609) as gap_609, avg(gap_610) as gap_610, avg(gap_611) as gap_611, avg(gap_612) as gap_612, avg(gap_613) as gap_613, avg(gap_614) as gap_614, avg(gap_615) as gap_615, avg(gap_616) as gap_616, avg(gap_617) as gap_617, avg(gap_618) as gap_618, avg(gap_619) as gap_619, avg(gap_620) as gap_620, avg(gap_621) as gap_621, avg(gap_622) as gap_622, avg(gap_623) as gap_623, avg(gap_624) as gap_624, avg(gap_625) as gap_625, avg(gap_626) as gap_626, avg(gap_627) as gap_627, avg(gap_628) as gap_628, avg(gap_629) as gap_629, avg(gap_630) as gap_630, avg(gap_631) as gap_631, avg(gap_632) as gap_632, avg(gap_633) as gap_633, avg(gap_634) as gap_634, avg(gap_635) as gap_635, avg(gap_636) as gap_636, avg(gap_637) as gap_637, avg(gap_638) as gap_638, avg(gap_639) as gap_639, avg(gap_640) as gap_640, avg(gap_641) as gap_641, avg(gap_642) as gap_642, avg(gap_643) as gap_643, avg(gap_644) as gap_644, avg(gap_645) as gap_645, avg(gap_646) as gap_646, avg(gap_647) as gap_647, avg(gap_648) as gap_648, avg(gap_649) as gap_649, avg(gap_650) as gap_650, avg(gap_651) as gap_651, avg(gap_652) as gap_652, avg(gap_653) as gap_653, avg(gap_654) as gap_654, avg(gap_655) as gap_655, avg(gap_656) as gap_656, avg(gap_657) as gap_657, avg(gap_658) as gap_658, avg(gap_659) as gap_659, avg(gap_660) as gap_660, avg(gap_661) as gap_661, avg(gap_662) as gap_662, avg(gap_663) as gap_663, avg(gap_664) as gap_664, avg(gap_665) as gap_665, avg(gap_666) as gap_666, avg(gap_667) as gap_667, avg(gap_668) as gap_668, avg(gap_669) as gap_669, avg(gap_670) as gap_670, avg(gap_671) as gap_671, avg(gap_672) as gap_672, avg(gap_673) as gap_673, avg(gap_674) as gap_674, avg(gap_675) as gap_675, avg(gap_676) as gap_676, avg(gap_677) as gap_677, avg(gap_678) as gap_678, avg(gap_679) as gap_679, avg(gap_680) as gap_680, avg(gap_681) as gap_681, avg(gap_682) as gap_682, avg(gap_683) as gap_683, avg(gap_684) as gap_684, avg(gap_685) as gap_685, avg(gap_686) as gap_686, avg(gap_687) as gap_687, avg(gap_688) as gap_688, avg(gap_689) as gap_689, avg(gap_690) as gap_690, avg(gap_691) as gap_691, avg(gap_692) as gap_692, avg(gap_693) as gap_693, avg(gap_694) as gap_694, avg(gap_695) as gap_695, avg(gap_696) as gap_696, avg(gap_697) as gap_697, avg(gap_698) as gap_698, avg(gap_699) as gap_699, avg(gap_700) as gap_700, avg(gap_701) as gap_701, avg(gap_702) as gap_702, avg(gap_703) as gap_703, avg(gap_704) as gap_704, avg(gap_705) as gap_705, avg(gap_706) as gap_706, avg(gap_707) as gap_707, avg(gap_708) as gap_708, avg(gap_709) as gap_709, avg(gap_710) as gap_710, avg(gap_711) as gap_711, avg(gap_712) as gap_712, avg(gap_713) as gap_713, avg(gap_714) as gap_714, avg(gap_715) as gap_715, avg(gap_716) as gap_716, avg(gap_717) as gap_717, avg(gap_718) as gap_718, avg(gap_719) as gap_719, avg(gap_720) as gap_720, avg(gap_721) as gap_721, avg(gap_722) as gap_722, avg(gap_723) as gap_723, avg(gap_724) as gap_724, avg(gap_725) as gap_725, avg(gap_726) as gap_726, avg(gap_727) as gap_727, avg(gap_728) as gap_728, avg(gap_729) as gap_729, avg(gap_730) as gap_730, avg(gap_731) as gap_731, avg(gap_732) as gap_732, avg(gap_733) as gap_733, avg(gap_734) as gap_734, avg(gap_735) as gap_735, avg(gap_736) as gap_736, avg(gap_737) as gap_737, avg(gap_738) as gap_738, avg(gap_739) as gap_739, avg(gap_740) as gap_740, avg(gap_741) as gap_741, avg(gap_742) as gap_742, avg(gap_743) as gap_743, avg(gap_744) as gap_744, avg(gap_745) as gap_745, avg(gap_746) as gap_746, avg(gap_747) as gap_747, avg(gap_748) as gap_748, avg(gap_749) as gap_749, avg(gap_750) as gap_750, avg(gap_751) as gap_751, avg(gap_752) as gap_752, avg(gap_753) as gap_753, avg(gap_754) as gap_754, avg(gap_755) as gap_755, avg(gap_756) as gap_756, avg(gap_757) as gap_757, avg(gap_758) as gap_758, avg(gap_759) as gap_759, avg(gap_760) as gap_760, avg(gap_761) as gap_761, avg(gap_762) as gap_762, avg(gap_763) as gap_763, avg(gap_764) as gap_764, avg(gap_765) as gap_765, avg(gap_766) as gap_766, avg(gap_767) as gap_767 from surfacing_tweets inner join `recsys2020.pretrained_bert_gap` gap on surfacing_tweets.tweet_id = gap.tweet_id group by user_id ) select 1.0 / 768 * ( (engaged_user_surfacing_tweet_vectors.gap_0 * user_surfacing_tweet_vectors.gap_0) + (engaged_user_surfacing_tweet_vectors.gap_1 * user_surfacing_tweet_vectors.gap_1) + (engaged_user_surfacing_tweet_vectors.gap_2 * user_surfacing_tweet_vectors.gap_2) + (engaged_user_surfacing_tweet_vectors.gap_3 * user_surfacing_tweet_vectors.gap_3) + (engaged_user_surfacing_tweet_vectors.gap_4 * user_surfacing_tweet_vectors.gap_4) + (engaged_user_surfacing_tweet_vectors.gap_5 * user_surfacing_tweet_vectors.gap_5) + (engaged_user_surfacing_tweet_vectors.gap_6 * user_surfacing_tweet_vectors.gap_6) + (engaged_user_surfacing_tweet_vectors.gap_7 * user_surfacing_tweet_vectors.gap_7) + (engaged_user_surfacing_tweet_vectors.gap_8 * user_surfacing_tweet_vectors.gap_8) + (engaged_user_surfacing_tweet_vectors.gap_9 * user_surfacing_tweet_vectors.gap_9) + (engaged_user_surfacing_tweet_vectors.gap_10 * user_surfacing_tweet_vectors.gap_10) + (engaged_user_surfacing_tweet_vectors.gap_11 * user_surfacing_tweet_vectors.gap_11) + (engaged_user_surfacing_tweet_vectors.gap_12 * user_surfacing_tweet_vectors.gap_12) + (engaged_user_surfacing_tweet_vectors.gap_13 * user_surfacing_tweet_vectors.gap_13) + (engaged_user_surfacing_tweet_vectors.gap_14 * user_surfacing_tweet_vectors.gap_14) + (engaged_user_surfacing_tweet_vectors.gap_15 * user_surfacing_tweet_vectors.gap_15) + (engaged_user_surfacing_tweet_vectors.gap_16 * user_surfacing_tweet_vectors.gap_16) + (engaged_user_surfacing_tweet_vectors.gap_17 * user_surfacing_tweet_vectors.gap_17) + (engaged_user_surfacing_tweet_vectors.gap_18 * user_surfacing_tweet_vectors.gap_18) + (engaged_user_surfacing_tweet_vectors.gap_19 * user_surfacing_tweet_vectors.gap_19) + (engaged_user_surfacing_tweet_vectors.gap_20 * user_surfacing_tweet_vectors.gap_20) + (engaged_user_surfacing_tweet_vectors.gap_21 * user_surfacing_tweet_vectors.gap_21) + (engaged_user_surfacing_tweet_vectors.gap_22 * user_surfacing_tweet_vectors.gap_22) + (engaged_user_surfacing_tweet_vectors.gap_23 * user_surfacing_tweet_vectors.gap_23) + (engaged_user_surfacing_tweet_vectors.gap_24 * user_surfacing_tweet_vectors.gap_24) + (engaged_user_surfacing_tweet_vectors.gap_25 * user_surfacing_tweet_vectors.gap_25) + (engaged_user_surfacing_tweet_vectors.gap_26 * user_surfacing_tweet_vectors.gap_26) + (engaged_user_surfacing_tweet_vectors.gap_27 * user_surfacing_tweet_vectors.gap_27) + (engaged_user_surfacing_tweet_vectors.gap_28 * user_surfacing_tweet_vectors.gap_28) + (engaged_user_surfacing_tweet_vectors.gap_29 * user_surfacing_tweet_vectors.gap_29) + (engaged_user_surfacing_tweet_vectors.gap_30 * user_surfacing_tweet_vectors.gap_30) + (engaged_user_surfacing_tweet_vectors.gap_31 * user_surfacing_tweet_vectors.gap_31) + (engaged_user_surfacing_tweet_vectors.gap_32 * user_surfacing_tweet_vectors.gap_32) + (engaged_user_surfacing_tweet_vectors.gap_33 * user_surfacing_tweet_vectors.gap_33) + (engaged_user_surfacing_tweet_vectors.gap_34 * user_surfacing_tweet_vectors.gap_34) + (engaged_user_surfacing_tweet_vectors.gap_35 * user_surfacing_tweet_vectors.gap_35) + (engaged_user_surfacing_tweet_vectors.gap_36 * user_surfacing_tweet_vectors.gap_36) + (engaged_user_surfacing_tweet_vectors.gap_37 * user_surfacing_tweet_vectors.gap_37) + (engaged_user_surfacing_tweet_vectors.gap_38 * user_surfacing_tweet_vectors.gap_38) + (engaged_user_surfacing_tweet_vectors.gap_39 * user_surfacing_tweet_vectors.gap_39) + (engaged_user_surfacing_tweet_vectors.gap_40 * user_surfacing_tweet_vectors.gap_40) + (engaged_user_surfacing_tweet_vectors.gap_41 * user_surfacing_tweet_vectors.gap_41) + (engaged_user_surfacing_tweet_vectors.gap_42 * user_surfacing_tweet_vectors.gap_42) + (engaged_user_surfacing_tweet_vectors.gap_43 * user_surfacing_tweet_vectors.gap_43) + (engaged_user_surfacing_tweet_vectors.gap_44 * user_surfacing_tweet_vectors.gap_44) + (engaged_user_surfacing_tweet_vectors.gap_45 * user_surfacing_tweet_vectors.gap_45) + (engaged_user_surfacing_tweet_vectors.gap_46 * user_surfacing_tweet_vectors.gap_46) + (engaged_user_surfacing_tweet_vectors.gap_47 * user_surfacing_tweet_vectors.gap_47) + (engaged_user_surfacing_tweet_vectors.gap_48 * user_surfacing_tweet_vectors.gap_48) + (engaged_user_surfacing_tweet_vectors.gap_49 * user_surfacing_tweet_vectors.gap_49) + (engaged_user_surfacing_tweet_vectors.gap_50 * user_surfacing_tweet_vectors.gap_50) + (engaged_user_surfacing_tweet_vectors.gap_51 * user_surfacing_tweet_vectors.gap_51) + (engaged_user_surfacing_tweet_vectors.gap_52 * user_surfacing_tweet_vectors.gap_52) + (engaged_user_surfacing_tweet_vectors.gap_53 * user_surfacing_tweet_vectors.gap_53) + (engaged_user_surfacing_tweet_vectors.gap_54 * user_surfacing_tweet_vectors.gap_54) + (engaged_user_surfacing_tweet_vectors.gap_55 * user_surfacing_tweet_vectors.gap_55) + (engaged_user_surfacing_tweet_vectors.gap_56 * user_surfacing_tweet_vectors.gap_56) + (engaged_user_surfacing_tweet_vectors.gap_57 * user_surfacing_tweet_vectors.gap_57) + (engaged_user_surfacing_tweet_vectors.gap_58 * user_surfacing_tweet_vectors.gap_58) + (engaged_user_surfacing_tweet_vectors.gap_59 * user_surfacing_tweet_vectors.gap_59) + (engaged_user_surfacing_tweet_vectors.gap_60 * user_surfacing_tweet_vectors.gap_60) + (engaged_user_surfacing_tweet_vectors.gap_61 * user_surfacing_tweet_vectors.gap_61) + (engaged_user_surfacing_tweet_vectors.gap_62 * user_surfacing_tweet_vectors.gap_62) + (engaged_user_surfacing_tweet_vectors.gap_63 * user_surfacing_tweet_vectors.gap_63) + (engaged_user_surfacing_tweet_vectors.gap_64 * user_surfacing_tweet_vectors.gap_64) + (engaged_user_surfacing_tweet_vectors.gap_65 * user_surfacing_tweet_vectors.gap_65) + (engaged_user_surfacing_tweet_vectors.gap_66 * user_surfacing_tweet_vectors.gap_66) + (engaged_user_surfacing_tweet_vectors.gap_67 * user_surfacing_tweet_vectors.gap_67) + (engaged_user_surfacing_tweet_vectors.gap_68 * user_surfacing_tweet_vectors.gap_68) + (engaged_user_surfacing_tweet_vectors.gap_69 * user_surfacing_tweet_vectors.gap_69) + (engaged_user_surfacing_tweet_vectors.gap_70 * user_surfacing_tweet_vectors.gap_70) + (engaged_user_surfacing_tweet_vectors.gap_71 * user_surfacing_tweet_vectors.gap_71) + (engaged_user_surfacing_tweet_vectors.gap_72 * user_surfacing_tweet_vectors.gap_72) + (engaged_user_surfacing_tweet_vectors.gap_73 * user_surfacing_tweet_vectors.gap_73) + (engaged_user_surfacing_tweet_vectors.gap_74 * user_surfacing_tweet_vectors.gap_74) + (engaged_user_surfacing_tweet_vectors.gap_75 * user_surfacing_tweet_vectors.gap_75) + (engaged_user_surfacing_tweet_vectors.gap_76 * user_surfacing_tweet_vectors.gap_76) + (engaged_user_surfacing_tweet_vectors.gap_77 * user_surfacing_tweet_vectors.gap_77) + (engaged_user_surfacing_tweet_vectors.gap_78 * user_surfacing_tweet_vectors.gap_78) + (engaged_user_surfacing_tweet_vectors.gap_79 * user_surfacing_tweet_vectors.gap_79) + (engaged_user_surfacing_tweet_vectors.gap_80 * user_surfacing_tweet_vectors.gap_80) + (engaged_user_surfacing_tweet_vectors.gap_81 * user_surfacing_tweet_vectors.gap_81) + (engaged_user_surfacing_tweet_vectors.gap_82 * user_surfacing_tweet_vectors.gap_82) + (engaged_user_surfacing_tweet_vectors.gap_83 * user_surfacing_tweet_vectors.gap_83) + (engaged_user_surfacing_tweet_vectors.gap_84 * user_surfacing_tweet_vectors.gap_84) + (engaged_user_surfacing_tweet_vectors.gap_85 * user_surfacing_tweet_vectors.gap_85) + (engaged_user_surfacing_tweet_vectors.gap_86 * user_surfacing_tweet_vectors.gap_86) + (engaged_user_surfacing_tweet_vectors.gap_87 * user_surfacing_tweet_vectors.gap_87) + (engaged_user_surfacing_tweet_vectors.gap_88 * user_surfacing_tweet_vectors.gap_88) + (engaged_user_surfacing_tweet_vectors.gap_89 * user_surfacing_tweet_vectors.gap_89) + (engaged_user_surfacing_tweet_vectors.gap_90 * user_surfacing_tweet_vectors.gap_90) + (engaged_user_surfacing_tweet_vectors.gap_91 * user_surfacing_tweet_vectors.gap_91) + (engaged_user_surfacing_tweet_vectors.gap_92 * user_surfacing_tweet_vectors.gap_92) + (engaged_user_surfacing_tweet_vectors.gap_93 * user_surfacing_tweet_vectors.gap_93) + (engaged_user_surfacing_tweet_vectors.gap_94 * user_surfacing_tweet_vectors.gap_94) + (engaged_user_surfacing_tweet_vectors.gap_95 * user_surfacing_tweet_vectors.gap_95) + (engaged_user_surfacing_tweet_vectors.gap_96 * user_surfacing_tweet_vectors.gap_96) + (engaged_user_surfacing_tweet_vectors.gap_97 * user_surfacing_tweet_vectors.gap_97) + (engaged_user_surfacing_tweet_vectors.gap_98 * user_surfacing_tweet_vectors.gap_98) + (engaged_user_surfacing_tweet_vectors.gap_99 * user_surfacing_tweet_vectors.gap_99) + (engaged_user_surfacing_tweet_vectors.gap_100 * user_surfacing_tweet_vectors.gap_100) + (engaged_user_surfacing_tweet_vectors.gap_101 * user_surfacing_tweet_vectors.gap_101) + (engaged_user_surfacing_tweet_vectors.gap_102 * user_surfacing_tweet_vectors.gap_102) + (engaged_user_surfacing_tweet_vectors.gap_103 * user_surfacing_tweet_vectors.gap_103) + (engaged_user_surfacing_tweet_vectors.gap_104 * user_surfacing_tweet_vectors.gap_104) + (engaged_user_surfacing_tweet_vectors.gap_105 * user_surfacing_tweet_vectors.gap_105) + (engaged_user_surfacing_tweet_vectors.gap_106 * user_surfacing_tweet_vectors.gap_106) + (engaged_user_surfacing_tweet_vectors.gap_107 * user_surfacing_tweet_vectors.gap_107) + (engaged_user_surfacing_tweet_vectors.gap_108 * user_surfacing_tweet_vectors.gap_108) + (engaged_user_surfacing_tweet_vectors.gap_109 * user_surfacing_tweet_vectors.gap_109) + (engaged_user_surfacing_tweet_vectors.gap_110 * user_surfacing_tweet_vectors.gap_110) + (engaged_user_surfacing_tweet_vectors.gap_111 * user_surfacing_tweet_vectors.gap_111) + (engaged_user_surfacing_tweet_vectors.gap_112 * user_surfacing_tweet_vectors.gap_112) + (engaged_user_surfacing_tweet_vectors.gap_113 * user_surfacing_tweet_vectors.gap_113) + (engaged_user_surfacing_tweet_vectors.gap_114 * user_surfacing_tweet_vectors.gap_114) + (engaged_user_surfacing_tweet_vectors.gap_115 * user_surfacing_tweet_vectors.gap_115) + (engaged_user_surfacing_tweet_vectors.gap_116 * user_surfacing_tweet_vectors.gap_116) + (engaged_user_surfacing_tweet_vectors.gap_117 * user_surfacing_tweet_vectors.gap_117) + (engaged_user_surfacing_tweet_vectors.gap_118 * user_surfacing_tweet_vectors.gap_118) + (engaged_user_surfacing_tweet_vectors.gap_119 * user_surfacing_tweet_vectors.gap_119) + (engaged_user_surfacing_tweet_vectors.gap_120 * user_surfacing_tweet_vectors.gap_120) + (engaged_user_surfacing_tweet_vectors.gap_121 * user_surfacing_tweet_vectors.gap_121) + (engaged_user_surfacing_tweet_vectors.gap_122 * user_surfacing_tweet_vectors.gap_122) + (engaged_user_surfacing_tweet_vectors.gap_123 * user_surfacing_tweet_vectors.gap_123) + (engaged_user_surfacing_tweet_vectors.gap_124 * user_surfacing_tweet_vectors.gap_124) + (engaged_user_surfacing_tweet_vectors.gap_125 * user_surfacing_tweet_vectors.gap_125) + (engaged_user_surfacing_tweet_vectors.gap_126 * user_surfacing_tweet_vectors.gap_126) + (engaged_user_surfacing_tweet_vectors.gap_127 * user_surfacing_tweet_vectors.gap_127) + (engaged_user_surfacing_tweet_vectors.gap_128 * user_surfacing_tweet_vectors.gap_128) + (engaged_user_surfacing_tweet_vectors.gap_129 * user_surfacing_tweet_vectors.gap_129) + (engaged_user_surfacing_tweet_vectors.gap_130 * user_surfacing_tweet_vectors.gap_130) + (engaged_user_surfacing_tweet_vectors.gap_131 * user_surfacing_tweet_vectors.gap_131) + (engaged_user_surfacing_tweet_vectors.gap_132 * user_surfacing_tweet_vectors.gap_132) + (engaged_user_surfacing_tweet_vectors.gap_133 * user_surfacing_tweet_vectors.gap_133) + (engaged_user_surfacing_tweet_vectors.gap_134 * user_surfacing_tweet_vectors.gap_134) + (engaged_user_surfacing_tweet_vectors.gap_135 * user_surfacing_tweet_vectors.gap_135) + (engaged_user_surfacing_tweet_vectors.gap_136 * user_surfacing_tweet_vectors.gap_136) + (engaged_user_surfacing_tweet_vectors.gap_137 * user_surfacing_tweet_vectors.gap_137) + (engaged_user_surfacing_tweet_vectors.gap_138 * user_surfacing_tweet_vectors.gap_138) + (engaged_user_surfacing_tweet_vectors.gap_139 * user_surfacing_tweet_vectors.gap_139) + (engaged_user_surfacing_tweet_vectors.gap_140 * user_surfacing_tweet_vectors.gap_140) + (engaged_user_surfacing_tweet_vectors.gap_141 * user_surfacing_tweet_vectors.gap_141) + (engaged_user_surfacing_tweet_vectors.gap_142 * user_surfacing_tweet_vectors.gap_142) + (engaged_user_surfacing_tweet_vectors.gap_143 * user_surfacing_tweet_vectors.gap_143) + (engaged_user_surfacing_tweet_vectors.gap_144 * user_surfacing_tweet_vectors.gap_144) + (engaged_user_surfacing_tweet_vectors.gap_145 * user_surfacing_tweet_vectors.gap_145) + (engaged_user_surfacing_tweet_vectors.gap_146 * user_surfacing_tweet_vectors.gap_146) + (engaged_user_surfacing_tweet_vectors.gap_147 * user_surfacing_tweet_vectors.gap_147) + (engaged_user_surfacing_tweet_vectors.gap_148 * user_surfacing_tweet_vectors.gap_148) + (engaged_user_surfacing_tweet_vectors.gap_149 * user_surfacing_tweet_vectors.gap_149) + (engaged_user_surfacing_tweet_vectors.gap_150 * user_surfacing_tweet_vectors.gap_150) + (engaged_user_surfacing_tweet_vectors.gap_151 * user_surfacing_tweet_vectors.gap_151) + (engaged_user_surfacing_tweet_vectors.gap_152 * user_surfacing_tweet_vectors.gap_152) + (engaged_user_surfacing_tweet_vectors.gap_153 * user_surfacing_tweet_vectors.gap_153) + (engaged_user_surfacing_tweet_vectors.gap_154 * user_surfacing_tweet_vectors.gap_154) + (engaged_user_surfacing_tweet_vectors.gap_155 * user_surfacing_tweet_vectors.gap_155) + (engaged_user_surfacing_tweet_vectors.gap_156 * user_surfacing_tweet_vectors.gap_156) + (engaged_user_surfacing_tweet_vectors.gap_157 * user_surfacing_tweet_vectors.gap_157) + (engaged_user_surfacing_tweet_vectors.gap_158 * user_surfacing_tweet_vectors.gap_158) + (engaged_user_surfacing_tweet_vectors.gap_159 * user_surfacing_tweet_vectors.gap_159) + (engaged_user_surfacing_tweet_vectors.gap_160 * user_surfacing_tweet_vectors.gap_160) + (engaged_user_surfacing_tweet_vectors.gap_161 * user_surfacing_tweet_vectors.gap_161) + (engaged_user_surfacing_tweet_vectors.gap_162 * user_surfacing_tweet_vectors.gap_162) + (engaged_user_surfacing_tweet_vectors.gap_163 * user_surfacing_tweet_vectors.gap_163) + (engaged_user_surfacing_tweet_vectors.gap_164 * user_surfacing_tweet_vectors.gap_164) + (engaged_user_surfacing_tweet_vectors.gap_165 * user_surfacing_tweet_vectors.gap_165) + (engaged_user_surfacing_tweet_vectors.gap_166 * user_surfacing_tweet_vectors.gap_166) + (engaged_user_surfacing_tweet_vectors.gap_167 * user_surfacing_tweet_vectors.gap_167) + (engaged_user_surfacing_tweet_vectors.gap_168 * user_surfacing_tweet_vectors.gap_168) + (engaged_user_surfacing_tweet_vectors.gap_169 * user_surfacing_tweet_vectors.gap_169) + (engaged_user_surfacing_tweet_vectors.gap_170 * user_surfacing_tweet_vectors.gap_170) + (engaged_user_surfacing_tweet_vectors.gap_171 * user_surfacing_tweet_vectors.gap_171) + (engaged_user_surfacing_tweet_vectors.gap_172 * user_surfacing_tweet_vectors.gap_172) + (engaged_user_surfacing_tweet_vectors.gap_173 * user_surfacing_tweet_vectors.gap_173) + (engaged_user_surfacing_tweet_vectors.gap_174 * user_surfacing_tweet_vectors.gap_174) + (engaged_user_surfacing_tweet_vectors.gap_175 * user_surfacing_tweet_vectors.gap_175) + (engaged_user_surfacing_tweet_vectors.gap_176 * user_surfacing_tweet_vectors.gap_176) + (engaged_user_surfacing_tweet_vectors.gap_177 * user_surfacing_tweet_vectors.gap_177) + (engaged_user_surfacing_tweet_vectors.gap_178 * user_surfacing_tweet_vectors.gap_178) + (engaged_user_surfacing_tweet_vectors.gap_179 * user_surfacing_tweet_vectors.gap_179) + (engaged_user_surfacing_tweet_vectors.gap_180 * user_surfacing_tweet_vectors.gap_180) + (engaged_user_surfacing_tweet_vectors.gap_181 * user_surfacing_tweet_vectors.gap_181) + (engaged_user_surfacing_tweet_vectors.gap_182 * user_surfacing_tweet_vectors.gap_182) + (engaged_user_surfacing_tweet_vectors.gap_183 * user_surfacing_tweet_vectors.gap_183) + (engaged_user_surfacing_tweet_vectors.gap_184 * user_surfacing_tweet_vectors.gap_184) + (engaged_user_surfacing_tweet_vectors.gap_185 * user_surfacing_tweet_vectors.gap_185) + (engaged_user_surfacing_tweet_vectors.gap_186 * user_surfacing_tweet_vectors.gap_186) + (engaged_user_surfacing_tweet_vectors.gap_187 * user_surfacing_tweet_vectors.gap_187) + (engaged_user_surfacing_tweet_vectors.gap_188 * user_surfacing_tweet_vectors.gap_188) + (engaged_user_surfacing_tweet_vectors.gap_189 * user_surfacing_tweet_vectors.gap_189) + (engaged_user_surfacing_tweet_vectors.gap_190 * user_surfacing_tweet_vectors.gap_190) + (engaged_user_surfacing_tweet_vectors.gap_191 * user_surfacing_tweet_vectors.gap_191) + (engaged_user_surfacing_tweet_vectors.gap_192 * user_surfacing_tweet_vectors.gap_192) + (engaged_user_surfacing_tweet_vectors.gap_193 * user_surfacing_tweet_vectors.gap_193) + (engaged_user_surfacing_tweet_vectors.gap_194 * user_surfacing_tweet_vectors.gap_194) + (engaged_user_surfacing_tweet_vectors.gap_195 * user_surfacing_tweet_vectors.gap_195) + (engaged_user_surfacing_tweet_vectors.gap_196 * user_surfacing_tweet_vectors.gap_196) + (engaged_user_surfacing_tweet_vectors.gap_197 * user_surfacing_tweet_vectors.gap_197) + (engaged_user_surfacing_tweet_vectors.gap_198 * user_surfacing_tweet_vectors.gap_198) + (engaged_user_surfacing_tweet_vectors.gap_199 * user_surfacing_tweet_vectors.gap_199) + (engaged_user_surfacing_tweet_vectors.gap_200 * user_surfacing_tweet_vectors.gap_200) + (engaged_user_surfacing_tweet_vectors.gap_201 * user_surfacing_tweet_vectors.gap_201) + (engaged_user_surfacing_tweet_vectors.gap_202 * user_surfacing_tweet_vectors.gap_202) + (engaged_user_surfacing_tweet_vectors.gap_203 * user_surfacing_tweet_vectors.gap_203) + (engaged_user_surfacing_tweet_vectors.gap_204 * user_surfacing_tweet_vectors.gap_204) + (engaged_user_surfacing_tweet_vectors.gap_205 * user_surfacing_tweet_vectors.gap_205) + (engaged_user_surfacing_tweet_vectors.gap_206 * user_surfacing_tweet_vectors.gap_206) + (engaged_user_surfacing_tweet_vectors.gap_207 * user_surfacing_tweet_vectors.gap_207) + (engaged_user_surfacing_tweet_vectors.gap_208 * user_surfacing_tweet_vectors.gap_208) + (engaged_user_surfacing_tweet_vectors.gap_209 * user_surfacing_tweet_vectors.gap_209) + (engaged_user_surfacing_tweet_vectors.gap_210 * user_surfacing_tweet_vectors.gap_210) + (engaged_user_surfacing_tweet_vectors.gap_211 * user_surfacing_tweet_vectors.gap_211) + (engaged_user_surfacing_tweet_vectors.gap_212 * user_surfacing_tweet_vectors.gap_212) + (engaged_user_surfacing_tweet_vectors.gap_213 * user_surfacing_tweet_vectors.gap_213) + (engaged_user_surfacing_tweet_vectors.gap_214 * user_surfacing_tweet_vectors.gap_214) + (engaged_user_surfacing_tweet_vectors.gap_215 * user_surfacing_tweet_vectors.gap_215) + (engaged_user_surfacing_tweet_vectors.gap_216 * user_surfacing_tweet_vectors.gap_216) + (engaged_user_surfacing_tweet_vectors.gap_217 * user_surfacing_tweet_vectors.gap_217) + (engaged_user_surfacing_tweet_vectors.gap_218 * user_surfacing_tweet_vectors.gap_218) + (engaged_user_surfacing_tweet_vectors.gap_219 * user_surfacing_tweet_vectors.gap_219) + (engaged_user_surfacing_tweet_vectors.gap_220 * user_surfacing_tweet_vectors.gap_220) + (engaged_user_surfacing_tweet_vectors.gap_221 * user_surfacing_tweet_vectors.gap_221) + (engaged_user_surfacing_tweet_vectors.gap_222 * user_surfacing_tweet_vectors.gap_222) + (engaged_user_surfacing_tweet_vectors.gap_223 * user_surfacing_tweet_vectors.gap_223) + (engaged_user_surfacing_tweet_vectors.gap_224 * user_surfacing_tweet_vectors.gap_224) + (engaged_user_surfacing_tweet_vectors.gap_225 * user_surfacing_tweet_vectors.gap_225) + (engaged_user_surfacing_tweet_vectors.gap_226 * user_surfacing_tweet_vectors.gap_226) + (engaged_user_surfacing_tweet_vectors.gap_227 * user_surfacing_tweet_vectors.gap_227) + (engaged_user_surfacing_tweet_vectors.gap_228 * user_surfacing_tweet_vectors.gap_228) + (engaged_user_surfacing_tweet_vectors.gap_229 * user_surfacing_tweet_vectors.gap_229) + (engaged_user_surfacing_tweet_vectors.gap_230 * user_surfacing_tweet_vectors.gap_230) + (engaged_user_surfacing_tweet_vectors.gap_231 * user_surfacing_tweet_vectors.gap_231) + (engaged_user_surfacing_tweet_vectors.gap_232 * user_surfacing_tweet_vectors.gap_232) + (engaged_user_surfacing_tweet_vectors.gap_233 * user_surfacing_tweet_vectors.gap_233) + (engaged_user_surfacing_tweet_vectors.gap_234 * user_surfacing_tweet_vectors.gap_234) + (engaged_user_surfacing_tweet_vectors.gap_235 * user_surfacing_tweet_vectors.gap_235) + (engaged_user_surfacing_tweet_vectors.gap_236 * user_surfacing_tweet_vectors.gap_236) + (engaged_user_surfacing_tweet_vectors.gap_237 * user_surfacing_tweet_vectors.gap_237) + (engaged_user_surfacing_tweet_vectors.gap_238 * user_surfacing_tweet_vectors.gap_238) + (engaged_user_surfacing_tweet_vectors.gap_239 * user_surfacing_tweet_vectors.gap_239) + (engaged_user_surfacing_tweet_vectors.gap_240 * user_surfacing_tweet_vectors.gap_240) + (engaged_user_surfacing_tweet_vectors.gap_241 * user_surfacing_tweet_vectors.gap_241) + (engaged_user_surfacing_tweet_vectors.gap_242 * user_surfacing_tweet_vectors.gap_242) + (engaged_user_surfacing_tweet_vectors.gap_243 * user_surfacing_tweet_vectors.gap_243) + (engaged_user_surfacing_tweet_vectors.gap_244 * user_surfacing_tweet_vectors.gap_244) + (engaged_user_surfacing_tweet_vectors.gap_245 * user_surfacing_tweet_vectors.gap_245) + (engaged_user_surfacing_tweet_vectors.gap_246 * user_surfacing_tweet_vectors.gap_246) + (engaged_user_surfacing_tweet_vectors.gap_247 * user_surfacing_tweet_vectors.gap_247) + (engaged_user_surfacing_tweet_vectors.gap_248 * user_surfacing_tweet_vectors.gap_248) + (engaged_user_surfacing_tweet_vectors.gap_249 * user_surfacing_tweet_vectors.gap_249) + (engaged_user_surfacing_tweet_vectors.gap_250 * user_surfacing_tweet_vectors.gap_250) + (engaged_user_surfacing_tweet_vectors.gap_251 * user_surfacing_tweet_vectors.gap_251) + (engaged_user_surfacing_tweet_vectors.gap_252 * user_surfacing_tweet_vectors.gap_252) + (engaged_user_surfacing_tweet_vectors.gap_253 * user_surfacing_tweet_vectors.gap_253) + (engaged_user_surfacing_tweet_vectors.gap_254 * user_surfacing_tweet_vectors.gap_254) + (engaged_user_surfacing_tweet_vectors.gap_255 * user_surfacing_tweet_vectors.gap_255) + (engaged_user_surfacing_tweet_vectors.gap_256 * user_surfacing_tweet_vectors.gap_256) + (engaged_user_surfacing_tweet_vectors.gap_257 * user_surfacing_tweet_vectors.gap_257) + (engaged_user_surfacing_tweet_vectors.gap_258 * user_surfacing_tweet_vectors.gap_258) + (engaged_user_surfacing_tweet_vectors.gap_259 * user_surfacing_tweet_vectors.gap_259) + (engaged_user_surfacing_tweet_vectors.gap_260 * user_surfacing_tweet_vectors.gap_260) + (engaged_user_surfacing_tweet_vectors.gap_261 * user_surfacing_tweet_vectors.gap_261) + (engaged_user_surfacing_tweet_vectors.gap_262 * user_surfacing_tweet_vectors.gap_262) + (engaged_user_surfacing_tweet_vectors.gap_263 * user_surfacing_tweet_vectors.gap_263) + (engaged_user_surfacing_tweet_vectors.gap_264 * user_surfacing_tweet_vectors.gap_264) + (engaged_user_surfacing_tweet_vectors.gap_265 * user_surfacing_tweet_vectors.gap_265) + (engaged_user_surfacing_tweet_vectors.gap_266 * user_surfacing_tweet_vectors.gap_266) + (engaged_user_surfacing_tweet_vectors.gap_267 * user_surfacing_tweet_vectors.gap_267) + (engaged_user_surfacing_tweet_vectors.gap_268 * user_surfacing_tweet_vectors.gap_268) + (engaged_user_surfacing_tweet_vectors.gap_269 * user_surfacing_tweet_vectors.gap_269) + (engaged_user_surfacing_tweet_vectors.gap_270 * user_surfacing_tweet_vectors.gap_270) + (engaged_user_surfacing_tweet_vectors.gap_271 * user_surfacing_tweet_vectors.gap_271) + (engaged_user_surfacing_tweet_vectors.gap_272 * user_surfacing_tweet_vectors.gap_272) + (engaged_user_surfacing_tweet_vectors.gap_273 * user_surfacing_tweet_vectors.gap_273) + (engaged_user_surfacing_tweet_vectors.gap_274 * user_surfacing_tweet_vectors.gap_274) + (engaged_user_surfacing_tweet_vectors.gap_275 * user_surfacing_tweet_vectors.gap_275) + (engaged_user_surfacing_tweet_vectors.gap_276 * user_surfacing_tweet_vectors.gap_276) + (engaged_user_surfacing_tweet_vectors.gap_277 * user_surfacing_tweet_vectors.gap_277) + (engaged_user_surfacing_tweet_vectors.gap_278 * user_surfacing_tweet_vectors.gap_278) + (engaged_user_surfacing_tweet_vectors.gap_279 * user_surfacing_tweet_vectors.gap_279) + (engaged_user_surfacing_tweet_vectors.gap_280 * user_surfacing_tweet_vectors.gap_280) + (engaged_user_surfacing_tweet_vectors.gap_281 * user_surfacing_tweet_vectors.gap_281) + (engaged_user_surfacing_tweet_vectors.gap_282 * user_surfacing_tweet_vectors.gap_282) + (engaged_user_surfacing_tweet_vectors.gap_283 * user_surfacing_tweet_vectors.gap_283) + (engaged_user_surfacing_tweet_vectors.gap_284 * user_surfacing_tweet_vectors.gap_284) + (engaged_user_surfacing_tweet_vectors.gap_285 * user_surfacing_tweet_vectors.gap_285) + (engaged_user_surfacing_tweet_vectors.gap_286 * user_surfacing_tweet_vectors.gap_286) + (engaged_user_surfacing_tweet_vectors.gap_287 * user_surfacing_tweet_vectors.gap_287) + (engaged_user_surfacing_tweet_vectors.gap_288 * user_surfacing_tweet_vectors.gap_288) + (engaged_user_surfacing_tweet_vectors.gap_289 * user_surfacing_tweet_vectors.gap_289) + (engaged_user_surfacing_tweet_vectors.gap_290 * user_surfacing_tweet_vectors.gap_290) + (engaged_user_surfacing_tweet_vectors.gap_291 * user_surfacing_tweet_vectors.gap_291) + (engaged_user_surfacing_tweet_vectors.gap_292 * user_surfacing_tweet_vectors.gap_292) + (engaged_user_surfacing_tweet_vectors.gap_293 * user_surfacing_tweet_vectors.gap_293) + (engaged_user_surfacing_tweet_vectors.gap_294 * user_surfacing_tweet_vectors.gap_294) + (engaged_user_surfacing_tweet_vectors.gap_295 * user_surfacing_tweet_vectors.gap_295) + (engaged_user_surfacing_tweet_vectors.gap_296 * user_surfacing_tweet_vectors.gap_296) + (engaged_user_surfacing_tweet_vectors.gap_297 * user_surfacing_tweet_vectors.gap_297) + (engaged_user_surfacing_tweet_vectors.gap_298 * user_surfacing_tweet_vectors.gap_298) + (engaged_user_surfacing_tweet_vectors.gap_299 * user_surfacing_tweet_vectors.gap_299) + (engaged_user_surfacing_tweet_vectors.gap_300 * user_surfacing_tweet_vectors.gap_300) + (engaged_user_surfacing_tweet_vectors.gap_301 * user_surfacing_tweet_vectors.gap_301) + (engaged_user_surfacing_tweet_vectors.gap_302 * user_surfacing_tweet_vectors.gap_302) + (engaged_user_surfacing_tweet_vectors.gap_303 * user_surfacing_tweet_vectors.gap_303) + (engaged_user_surfacing_tweet_vectors.gap_304 * user_surfacing_tweet_vectors.gap_304) + (engaged_user_surfacing_tweet_vectors.gap_305 * user_surfacing_tweet_vectors.gap_305) + (engaged_user_surfacing_tweet_vectors.gap_306 * user_surfacing_tweet_vectors.gap_306) + (engaged_user_surfacing_tweet_vectors.gap_307 * user_surfacing_tweet_vectors.gap_307) + (engaged_user_surfacing_tweet_vectors.gap_308 * user_surfacing_tweet_vectors.gap_308) + (engaged_user_surfacing_tweet_vectors.gap_309 * user_surfacing_tweet_vectors.gap_309) + (engaged_user_surfacing_tweet_vectors.gap_310 * user_surfacing_tweet_vectors.gap_310) + (engaged_user_surfacing_tweet_vectors.gap_311 * user_surfacing_tweet_vectors.gap_311) + (engaged_user_surfacing_tweet_vectors.gap_312 * user_surfacing_tweet_vectors.gap_312) + (engaged_user_surfacing_tweet_vectors.gap_313 * user_surfacing_tweet_vectors.gap_313) + (engaged_user_surfacing_tweet_vectors.gap_314 * user_surfacing_tweet_vectors.gap_314) + (engaged_user_surfacing_tweet_vectors.gap_315 * user_surfacing_tweet_vectors.gap_315) + (engaged_user_surfacing_tweet_vectors.gap_316 * user_surfacing_tweet_vectors.gap_316) + (engaged_user_surfacing_tweet_vectors.gap_317 * user_surfacing_tweet_vectors.gap_317) + (engaged_user_surfacing_tweet_vectors.gap_318 * user_surfacing_tweet_vectors.gap_318) + (engaged_user_surfacing_tweet_vectors.gap_319 * user_surfacing_tweet_vectors.gap_319) + (engaged_user_surfacing_tweet_vectors.gap_320 * user_surfacing_tweet_vectors.gap_320) + (engaged_user_surfacing_tweet_vectors.gap_321 * user_surfacing_tweet_vectors.gap_321) + (engaged_user_surfacing_tweet_vectors.gap_322 * user_surfacing_tweet_vectors.gap_322) + (engaged_user_surfacing_tweet_vectors.gap_323 * user_surfacing_tweet_vectors.gap_323) + (engaged_user_surfacing_tweet_vectors.gap_324 * user_surfacing_tweet_vectors.gap_324) + (engaged_user_surfacing_tweet_vectors.gap_325 * user_surfacing_tweet_vectors.gap_325) + (engaged_user_surfacing_tweet_vectors.gap_326 * user_surfacing_tweet_vectors.gap_326) + (engaged_user_surfacing_tweet_vectors.gap_327 * user_surfacing_tweet_vectors.gap_327) + (engaged_user_surfacing_tweet_vectors.gap_328 * user_surfacing_tweet_vectors.gap_328) + (engaged_user_surfacing_tweet_vectors.gap_329 * user_surfacing_tweet_vectors.gap_329) + (engaged_user_surfacing_tweet_vectors.gap_330 * user_surfacing_tweet_vectors.gap_330) + (engaged_user_surfacing_tweet_vectors.gap_331 * user_surfacing_tweet_vectors.gap_331) + (engaged_user_surfacing_tweet_vectors.gap_332 * user_surfacing_tweet_vectors.gap_332) + (engaged_user_surfacing_tweet_vectors.gap_333 * user_surfacing_tweet_vectors.gap_333) + (engaged_user_surfacing_tweet_vectors.gap_334 * user_surfacing_tweet_vectors.gap_334) + (engaged_user_surfacing_tweet_vectors.gap_335 * user_surfacing_tweet_vectors.gap_335) + (engaged_user_surfacing_tweet_vectors.gap_336 * user_surfacing_tweet_vectors.gap_336) + (engaged_user_surfacing_tweet_vectors.gap_337 * user_surfacing_tweet_vectors.gap_337) + (engaged_user_surfacing_tweet_vectors.gap_338 * user_surfacing_tweet_vectors.gap_338) + (engaged_user_surfacing_tweet_vectors.gap_339 * user_surfacing_tweet_vectors.gap_339) + (engaged_user_surfacing_tweet_vectors.gap_340 * user_surfacing_tweet_vectors.gap_340) + (engaged_user_surfacing_tweet_vectors.gap_341 * user_surfacing_tweet_vectors.gap_341) + (engaged_user_surfacing_tweet_vectors.gap_342 * user_surfacing_tweet_vectors.gap_342) + (engaged_user_surfacing_tweet_vectors.gap_343 * user_surfacing_tweet_vectors.gap_343) + (engaged_user_surfacing_tweet_vectors.gap_344 * user_surfacing_tweet_vectors.gap_344) + (engaged_user_surfacing_tweet_vectors.gap_345 * user_surfacing_tweet_vectors.gap_345) + (engaged_user_surfacing_tweet_vectors.gap_346 * user_surfacing_tweet_vectors.gap_346) + (engaged_user_surfacing_tweet_vectors.gap_347 * user_surfacing_tweet_vectors.gap_347) + (engaged_user_surfacing_tweet_vectors.gap_348 * user_surfacing_tweet_vectors.gap_348) + (engaged_user_surfacing_tweet_vectors.gap_349 * user_surfacing_tweet_vectors.gap_349) + (engaged_user_surfacing_tweet_vectors.gap_350 * user_surfacing_tweet_vectors.gap_350) + (engaged_user_surfacing_tweet_vectors.gap_351 * user_surfacing_tweet_vectors.gap_351) + (engaged_user_surfacing_tweet_vectors.gap_352 * user_surfacing_tweet_vectors.gap_352) + (engaged_user_surfacing_tweet_vectors.gap_353 * user_surfacing_tweet_vectors.gap_353) + (engaged_user_surfacing_tweet_vectors.gap_354 * user_surfacing_tweet_vectors.gap_354) + (engaged_user_surfacing_tweet_vectors.gap_355 * user_surfacing_tweet_vectors.gap_355) + (engaged_user_surfacing_tweet_vectors.gap_356 * user_surfacing_tweet_vectors.gap_356) + (engaged_user_surfacing_tweet_vectors.gap_357 * user_surfacing_tweet_vectors.gap_357) + (engaged_user_surfacing_tweet_vectors.gap_358 * user_surfacing_tweet_vectors.gap_358) + (engaged_user_surfacing_tweet_vectors.gap_359 * user_surfacing_tweet_vectors.gap_359) + (engaged_user_surfacing_tweet_vectors.gap_360 * user_surfacing_tweet_vectors.gap_360) + (engaged_user_surfacing_tweet_vectors.gap_361 * user_surfacing_tweet_vectors.gap_361) + (engaged_user_surfacing_tweet_vectors.gap_362 * user_surfacing_tweet_vectors.gap_362) + (engaged_user_surfacing_tweet_vectors.gap_363 * user_surfacing_tweet_vectors.gap_363) + (engaged_user_surfacing_tweet_vectors.gap_364 * user_surfacing_tweet_vectors.gap_364) + (engaged_user_surfacing_tweet_vectors.gap_365 * user_surfacing_tweet_vectors.gap_365) + (engaged_user_surfacing_tweet_vectors.gap_366 * user_surfacing_tweet_vectors.gap_366) + (engaged_user_surfacing_tweet_vectors.gap_367 * user_surfacing_tweet_vectors.gap_367) + (engaged_user_surfacing_tweet_vectors.gap_368 * user_surfacing_tweet_vectors.gap_368) + (engaged_user_surfacing_tweet_vectors.gap_369 * user_surfacing_tweet_vectors.gap_369) + (engaged_user_surfacing_tweet_vectors.gap_370 * user_surfacing_tweet_vectors.gap_370) + (engaged_user_surfacing_tweet_vectors.gap_371 * user_surfacing_tweet_vectors.gap_371) + (engaged_user_surfacing_tweet_vectors.gap_372 * user_surfacing_tweet_vectors.gap_372) + (engaged_user_surfacing_tweet_vectors.gap_373 * user_surfacing_tweet_vectors.gap_373) + (engaged_user_surfacing_tweet_vectors.gap_374 * user_surfacing_tweet_vectors.gap_374) + (engaged_user_surfacing_tweet_vectors.gap_375 * user_surfacing_tweet_vectors.gap_375) + (engaged_user_surfacing_tweet_vectors.gap_376 * user_surfacing_tweet_vectors.gap_376) + (engaged_user_surfacing_tweet_vectors.gap_377 * user_surfacing_tweet_vectors.gap_377) + (engaged_user_surfacing_tweet_vectors.gap_378 * user_surfacing_tweet_vectors.gap_378) + (engaged_user_surfacing_tweet_vectors.gap_379 * user_surfacing_tweet_vectors.gap_379) + (engaged_user_surfacing_tweet_vectors.gap_380 * user_surfacing_tweet_vectors.gap_380) + (engaged_user_surfacing_tweet_vectors.gap_381 * user_surfacing_tweet_vectors.gap_381) + (engaged_user_surfacing_tweet_vectors.gap_382 * user_surfacing_tweet_vectors.gap_382) + (engaged_user_surfacing_tweet_vectors.gap_383 * user_surfacing_tweet_vectors.gap_383) + (engaged_user_surfacing_tweet_vectors.gap_384 * user_surfacing_tweet_vectors.gap_384) + (engaged_user_surfacing_tweet_vectors.gap_385 * user_surfacing_tweet_vectors.gap_385) + (engaged_user_surfacing_tweet_vectors.gap_386 * user_surfacing_tweet_vectors.gap_386) + (engaged_user_surfacing_tweet_vectors.gap_387 * user_surfacing_tweet_vectors.gap_387) + (engaged_user_surfacing_tweet_vectors.gap_388 * user_surfacing_tweet_vectors.gap_388) + (engaged_user_surfacing_tweet_vectors.gap_389 * user_surfacing_tweet_vectors.gap_389) + (engaged_user_surfacing_tweet_vectors.gap_390 * user_surfacing_tweet_vectors.gap_390) + (engaged_user_surfacing_tweet_vectors.gap_391 * user_surfacing_tweet_vectors.gap_391) + (engaged_user_surfacing_tweet_vectors.gap_392 * user_surfacing_tweet_vectors.gap_392) + (engaged_user_surfacing_tweet_vectors.gap_393 * user_surfacing_tweet_vectors.gap_393) + (engaged_user_surfacing_tweet_vectors.gap_394 * user_surfacing_tweet_vectors.gap_394) + (engaged_user_surfacing_tweet_vectors.gap_395 * user_surfacing_tweet_vectors.gap_395) + (engaged_user_surfacing_tweet_vectors.gap_396 * user_surfacing_tweet_vectors.gap_396) + (engaged_user_surfacing_tweet_vectors.gap_397 * user_surfacing_tweet_vectors.gap_397) + (engaged_user_surfacing_tweet_vectors.gap_398 * user_surfacing_tweet_vectors.gap_398) + (engaged_user_surfacing_tweet_vectors.gap_399 * user_surfacing_tweet_vectors.gap_399) + (engaged_user_surfacing_tweet_vectors.gap_400 * user_surfacing_tweet_vectors.gap_400) + (engaged_user_surfacing_tweet_vectors.gap_401 * user_surfacing_tweet_vectors.gap_401) + (engaged_user_surfacing_tweet_vectors.gap_402 * user_surfacing_tweet_vectors.gap_402) + (engaged_user_surfacing_tweet_vectors.gap_403 * user_surfacing_tweet_vectors.gap_403) + (engaged_user_surfacing_tweet_vectors.gap_404 * user_surfacing_tweet_vectors.gap_404) + (engaged_user_surfacing_tweet_vectors.gap_405 * user_surfacing_tweet_vectors.gap_405) + (engaged_user_surfacing_tweet_vectors.gap_406 * user_surfacing_tweet_vectors.gap_406) + (engaged_user_surfacing_tweet_vectors.gap_407 * user_surfacing_tweet_vectors.gap_407) + (engaged_user_surfacing_tweet_vectors.gap_408 * user_surfacing_tweet_vectors.gap_408) + (engaged_user_surfacing_tweet_vectors.gap_409 * user_surfacing_tweet_vectors.gap_409) + (engaged_user_surfacing_tweet_vectors.gap_410 * user_surfacing_tweet_vectors.gap_410) + (engaged_user_surfacing_tweet_vectors.gap_411 * user_surfacing_tweet_vectors.gap_411) + (engaged_user_surfacing_tweet_vectors.gap_412 * user_surfacing_tweet_vectors.gap_412) + (engaged_user_surfacing_tweet_vectors.gap_413 * user_surfacing_tweet_vectors.gap_413) + (engaged_user_surfacing_tweet_vectors.gap_414 * user_surfacing_tweet_vectors.gap_414) + (engaged_user_surfacing_tweet_vectors.gap_415 * user_surfacing_tweet_vectors.gap_415) + (engaged_user_surfacing_tweet_vectors.gap_416 * user_surfacing_tweet_vectors.gap_416) + (engaged_user_surfacing_tweet_vectors.gap_417 * user_surfacing_tweet_vectors.gap_417) + (engaged_user_surfacing_tweet_vectors.gap_418 * user_surfacing_tweet_vectors.gap_418) + (engaged_user_surfacing_tweet_vectors.gap_419 * user_surfacing_tweet_vectors.gap_419) + (engaged_user_surfacing_tweet_vectors.gap_420 * user_surfacing_tweet_vectors.gap_420) + (engaged_user_surfacing_tweet_vectors.gap_421 * user_surfacing_tweet_vectors.gap_421) + (engaged_user_surfacing_tweet_vectors.gap_422 * user_surfacing_tweet_vectors.gap_422) + (engaged_user_surfacing_tweet_vectors.gap_423 * user_surfacing_tweet_vectors.gap_423) + (engaged_user_surfacing_tweet_vectors.gap_424 * user_surfacing_tweet_vectors.gap_424) + (engaged_user_surfacing_tweet_vectors.gap_425 * user_surfacing_tweet_vectors.gap_425) + (engaged_user_surfacing_tweet_vectors.gap_426 * user_surfacing_tweet_vectors.gap_426) + (engaged_user_surfacing_tweet_vectors.gap_427 * user_surfacing_tweet_vectors.gap_427) + (engaged_user_surfacing_tweet_vectors.gap_428 * user_surfacing_tweet_vectors.gap_428) + (engaged_user_surfacing_tweet_vectors.gap_429 * user_surfacing_tweet_vectors.gap_429) + (engaged_user_surfacing_tweet_vectors.gap_430 * user_surfacing_tweet_vectors.gap_430) + (engaged_user_surfacing_tweet_vectors.gap_431 * user_surfacing_tweet_vectors.gap_431) + (engaged_user_surfacing_tweet_vectors.gap_432 * user_surfacing_tweet_vectors.gap_432) + (engaged_user_surfacing_tweet_vectors.gap_433 * user_surfacing_tweet_vectors.gap_433) + (engaged_user_surfacing_tweet_vectors.gap_434 * user_surfacing_tweet_vectors.gap_434) + (engaged_user_surfacing_tweet_vectors.gap_435 * user_surfacing_tweet_vectors.gap_435) + (engaged_user_surfacing_tweet_vectors.gap_436 * user_surfacing_tweet_vectors.gap_436) + (engaged_user_surfacing_tweet_vectors.gap_437 * user_surfacing_tweet_vectors.gap_437) + (engaged_user_surfacing_tweet_vectors.gap_438 * user_surfacing_tweet_vectors.gap_438) + (engaged_user_surfacing_tweet_vectors.gap_439 * user_surfacing_tweet_vectors.gap_439) + (engaged_user_surfacing_tweet_vectors.gap_440 * user_surfacing_tweet_vectors.gap_440) + (engaged_user_surfacing_tweet_vectors.gap_441 * user_surfacing_tweet_vectors.gap_441) + (engaged_user_surfacing_tweet_vectors.gap_442 * user_surfacing_tweet_vectors.gap_442) + (engaged_user_surfacing_tweet_vectors.gap_443 * user_surfacing_tweet_vectors.gap_443) + (engaged_user_surfacing_tweet_vectors.gap_444 * user_surfacing_tweet_vectors.gap_444) + (engaged_user_surfacing_tweet_vectors.gap_445 * user_surfacing_tweet_vectors.gap_445) + (engaged_user_surfacing_tweet_vectors.gap_446 * user_surfacing_tweet_vectors.gap_446) + (engaged_user_surfacing_tweet_vectors.gap_447 * user_surfacing_tweet_vectors.gap_447) + (engaged_user_surfacing_tweet_vectors.gap_448 * user_surfacing_tweet_vectors.gap_448) + (engaged_user_surfacing_tweet_vectors.gap_449 * user_surfacing_tweet_vectors.gap_449) + (engaged_user_surfacing_tweet_vectors.gap_450 * user_surfacing_tweet_vectors.gap_450) + (engaged_user_surfacing_tweet_vectors.gap_451 * user_surfacing_tweet_vectors.gap_451) + (engaged_user_surfacing_tweet_vectors.gap_452 * user_surfacing_tweet_vectors.gap_452) + (engaged_user_surfacing_tweet_vectors.gap_453 * user_surfacing_tweet_vectors.gap_453) + (engaged_user_surfacing_tweet_vectors.gap_454 * user_surfacing_tweet_vectors.gap_454) + (engaged_user_surfacing_tweet_vectors.gap_455 * user_surfacing_tweet_vectors.gap_455) + (engaged_user_surfacing_tweet_vectors.gap_456 * user_surfacing_tweet_vectors.gap_456) + (engaged_user_surfacing_tweet_vectors.gap_457 * user_surfacing_tweet_vectors.gap_457) + (engaged_user_surfacing_tweet_vectors.gap_458 * user_surfacing_tweet_vectors.gap_458) + (engaged_user_surfacing_tweet_vectors.gap_459 * user_surfacing_tweet_vectors.gap_459) + (engaged_user_surfacing_tweet_vectors.gap_460 * user_surfacing_tweet_vectors.gap_460) + (engaged_user_surfacing_tweet_vectors.gap_461 * user_surfacing_tweet_vectors.gap_461) + (engaged_user_surfacing_tweet_vectors.gap_462 * user_surfacing_tweet_vectors.gap_462) + (engaged_user_surfacing_tweet_vectors.gap_463 * user_surfacing_tweet_vectors.gap_463) + (engaged_user_surfacing_tweet_vectors.gap_464 * user_surfacing_tweet_vectors.gap_464) + (engaged_user_surfacing_tweet_vectors.gap_465 * user_surfacing_tweet_vectors.gap_465) + (engaged_user_surfacing_tweet_vectors.gap_466 * user_surfacing_tweet_vectors.gap_466) + (engaged_user_surfacing_tweet_vectors.gap_467 * user_surfacing_tweet_vectors.gap_467) + (engaged_user_surfacing_tweet_vectors.gap_468 * user_surfacing_tweet_vectors.gap_468) + (engaged_user_surfacing_tweet_vectors.gap_469 * user_surfacing_tweet_vectors.gap_469) + (engaged_user_surfacing_tweet_vectors.gap_470 * user_surfacing_tweet_vectors.gap_470) + (engaged_user_surfacing_tweet_vectors.gap_471 * user_surfacing_tweet_vectors.gap_471) + (engaged_user_surfacing_tweet_vectors.gap_472 * user_surfacing_tweet_vectors.gap_472) + (engaged_user_surfacing_tweet_vectors.gap_473 * user_surfacing_tweet_vectors.gap_473) + (engaged_user_surfacing_tweet_vectors.gap_474 * user_surfacing_tweet_vectors.gap_474) + (engaged_user_surfacing_tweet_vectors.gap_475 * user_surfacing_tweet_vectors.gap_475) + (engaged_user_surfacing_tweet_vectors.gap_476 * user_surfacing_tweet_vectors.gap_476) + (engaged_user_surfacing_tweet_vectors.gap_477 * user_surfacing_tweet_vectors.gap_477) + (engaged_user_surfacing_tweet_vectors.gap_478 * user_surfacing_tweet_vectors.gap_478) + (engaged_user_surfacing_tweet_vectors.gap_479 * user_surfacing_tweet_vectors.gap_479) + (engaged_user_surfacing_tweet_vectors.gap_480 * user_surfacing_tweet_vectors.gap_480) + (engaged_user_surfacing_tweet_vectors.gap_481 * user_surfacing_tweet_vectors.gap_481) + (engaged_user_surfacing_tweet_vectors.gap_482 * user_surfacing_tweet_vectors.gap_482) + (engaged_user_surfacing_tweet_vectors.gap_483 * user_surfacing_tweet_vectors.gap_483) + (engaged_user_surfacing_tweet_vectors.gap_484 * user_surfacing_tweet_vectors.gap_484) + (engaged_user_surfacing_tweet_vectors.gap_485 * user_surfacing_tweet_vectors.gap_485) + (engaged_user_surfacing_tweet_vectors.gap_486 * user_surfacing_tweet_vectors.gap_486) + (engaged_user_surfacing_tweet_vectors.gap_487 * user_surfacing_tweet_vectors.gap_487) + (engaged_user_surfacing_tweet_vectors.gap_488 * user_surfacing_tweet_vectors.gap_488) + (engaged_user_surfacing_tweet_vectors.gap_489 * user_surfacing_tweet_vectors.gap_489) + (engaged_user_surfacing_tweet_vectors.gap_490 * user_surfacing_tweet_vectors.gap_490) + (engaged_user_surfacing_tweet_vectors.gap_491 * user_surfacing_tweet_vectors.gap_491) + (engaged_user_surfacing_tweet_vectors.gap_492 * user_surfacing_tweet_vectors.gap_492) + (engaged_user_surfacing_tweet_vectors.gap_493 * user_surfacing_tweet_vectors.gap_493) + (engaged_user_surfacing_tweet_vectors.gap_494 * user_surfacing_tweet_vectors.gap_494) + (engaged_user_surfacing_tweet_vectors.gap_495 * user_surfacing_tweet_vectors.gap_495) + (engaged_user_surfacing_tweet_vectors.gap_496 * user_surfacing_tweet_vectors.gap_496) + (engaged_user_surfacing_tweet_vectors.gap_497 * user_surfacing_tweet_vectors.gap_497) + (engaged_user_surfacing_tweet_vectors.gap_498 * user_surfacing_tweet_vectors.gap_498) + (engaged_user_surfacing_tweet_vectors.gap_499 * user_surfacing_tweet_vectors.gap_499) + (engaged_user_surfacing_tweet_vectors.gap_500 * user_surfacing_tweet_vectors.gap_500) + (engaged_user_surfacing_tweet_vectors.gap_501 * user_surfacing_tweet_vectors.gap_501) + (engaged_user_surfacing_tweet_vectors.gap_502 * user_surfacing_tweet_vectors.gap_502) + (engaged_user_surfacing_tweet_vectors.gap_503 * user_surfacing_tweet_vectors.gap_503) + (engaged_user_surfacing_tweet_vectors.gap_504 * user_surfacing_tweet_vectors.gap_504) + (engaged_user_surfacing_tweet_vectors.gap_505 * user_surfacing_tweet_vectors.gap_505) + (engaged_user_surfacing_tweet_vectors.gap_506 * user_surfacing_tweet_vectors.gap_506) + (engaged_user_surfacing_tweet_vectors.gap_507 * user_surfacing_tweet_vectors.gap_507) + (engaged_user_surfacing_tweet_vectors.gap_508 * user_surfacing_tweet_vectors.gap_508) + (engaged_user_surfacing_tweet_vectors.gap_509 * user_surfacing_tweet_vectors.gap_509) + (engaged_user_surfacing_tweet_vectors.gap_510 * user_surfacing_tweet_vectors.gap_510) + (engaged_user_surfacing_tweet_vectors.gap_511 * user_surfacing_tweet_vectors.gap_511) + (engaged_user_surfacing_tweet_vectors.gap_512 * user_surfacing_tweet_vectors.gap_512) + (engaged_user_surfacing_tweet_vectors.gap_513 * user_surfacing_tweet_vectors.gap_513) + (engaged_user_surfacing_tweet_vectors.gap_514 * user_surfacing_tweet_vectors.gap_514) + (engaged_user_surfacing_tweet_vectors.gap_515 * user_surfacing_tweet_vectors.gap_515) + (engaged_user_surfacing_tweet_vectors.gap_516 * user_surfacing_tweet_vectors.gap_516) + (engaged_user_surfacing_tweet_vectors.gap_517 * user_surfacing_tweet_vectors.gap_517) + (engaged_user_surfacing_tweet_vectors.gap_518 * user_surfacing_tweet_vectors.gap_518) + (engaged_user_surfacing_tweet_vectors.gap_519 * user_surfacing_tweet_vectors.gap_519) + (engaged_user_surfacing_tweet_vectors.gap_520 * user_surfacing_tweet_vectors.gap_520) + (engaged_user_surfacing_tweet_vectors.gap_521 * user_surfacing_tweet_vectors.gap_521) + (engaged_user_surfacing_tweet_vectors.gap_522 * user_surfacing_tweet_vectors.gap_522) + (engaged_user_surfacing_tweet_vectors.gap_523 * user_surfacing_tweet_vectors.gap_523) + (engaged_user_surfacing_tweet_vectors.gap_524 * user_surfacing_tweet_vectors.gap_524) + (engaged_user_surfacing_tweet_vectors.gap_525 * user_surfacing_tweet_vectors.gap_525) + (engaged_user_surfacing_tweet_vectors.gap_526 * user_surfacing_tweet_vectors.gap_526) + (engaged_user_surfacing_tweet_vectors.gap_527 * user_surfacing_tweet_vectors.gap_527) + (engaged_user_surfacing_tweet_vectors.gap_528 * user_surfacing_tweet_vectors.gap_528) + (engaged_user_surfacing_tweet_vectors.gap_529 * user_surfacing_tweet_vectors.gap_529) + (engaged_user_surfacing_tweet_vectors.gap_530 * user_surfacing_tweet_vectors.gap_530) + (engaged_user_surfacing_tweet_vectors.gap_531 * user_surfacing_tweet_vectors.gap_531) + (engaged_user_surfacing_tweet_vectors.gap_532 * user_surfacing_tweet_vectors.gap_532) + (engaged_user_surfacing_tweet_vectors.gap_533 * user_surfacing_tweet_vectors.gap_533) + (engaged_user_surfacing_tweet_vectors.gap_534 * user_surfacing_tweet_vectors.gap_534) + (engaged_user_surfacing_tweet_vectors.gap_535 * user_surfacing_tweet_vectors.gap_535) + (engaged_user_surfacing_tweet_vectors.gap_536 * user_surfacing_tweet_vectors.gap_536) + (engaged_user_surfacing_tweet_vectors.gap_537 * user_surfacing_tweet_vectors.gap_537) + (engaged_user_surfacing_tweet_vectors.gap_538 * user_surfacing_tweet_vectors.gap_538) + (engaged_user_surfacing_tweet_vectors.gap_539 * user_surfacing_tweet_vectors.gap_539) + (engaged_user_surfacing_tweet_vectors.gap_540 * user_surfacing_tweet_vectors.gap_540) + (engaged_user_surfacing_tweet_vectors.gap_541 * user_surfacing_tweet_vectors.gap_541) + (engaged_user_surfacing_tweet_vectors.gap_542 * user_surfacing_tweet_vectors.gap_542) + (engaged_user_surfacing_tweet_vectors.gap_543 * user_surfacing_tweet_vectors.gap_543) + (engaged_user_surfacing_tweet_vectors.gap_544 * user_surfacing_tweet_vectors.gap_544) + (engaged_user_surfacing_tweet_vectors.gap_545 * user_surfacing_tweet_vectors.gap_545) + (engaged_user_surfacing_tweet_vectors.gap_546 * user_surfacing_tweet_vectors.gap_546) + (engaged_user_surfacing_tweet_vectors.gap_547 * user_surfacing_tweet_vectors.gap_547) + (engaged_user_surfacing_tweet_vectors.gap_548 * user_surfacing_tweet_vectors.gap_548) + (engaged_user_surfacing_tweet_vectors.gap_549 * user_surfacing_tweet_vectors.gap_549) + (engaged_user_surfacing_tweet_vectors.gap_550 * user_surfacing_tweet_vectors.gap_550) + (engaged_user_surfacing_tweet_vectors.gap_551 * user_surfacing_tweet_vectors.gap_551) + (engaged_user_surfacing_tweet_vectors.gap_552 * user_surfacing_tweet_vectors.gap_552) + (engaged_user_surfacing_tweet_vectors.gap_553 * user_surfacing_tweet_vectors.gap_553) + (engaged_user_surfacing_tweet_vectors.gap_554 * user_surfacing_tweet_vectors.gap_554) + (engaged_user_surfacing_tweet_vectors.gap_555 * user_surfacing_tweet_vectors.gap_555) + (engaged_user_surfacing_tweet_vectors.gap_556 * user_surfacing_tweet_vectors.gap_556) + (engaged_user_surfacing_tweet_vectors.gap_557 * user_surfacing_tweet_vectors.gap_557) + (engaged_user_surfacing_tweet_vectors.gap_558 * user_surfacing_tweet_vectors.gap_558) + (engaged_user_surfacing_tweet_vectors.gap_559 * user_surfacing_tweet_vectors.gap_559) + (engaged_user_surfacing_tweet_vectors.gap_560 * user_surfacing_tweet_vectors.gap_560) + (engaged_user_surfacing_tweet_vectors.gap_561 * user_surfacing_tweet_vectors.gap_561) + (engaged_user_surfacing_tweet_vectors.gap_562 * user_surfacing_tweet_vectors.gap_562) + (engaged_user_surfacing_tweet_vectors.gap_563 * user_surfacing_tweet_vectors.gap_563) + (engaged_user_surfacing_tweet_vectors.gap_564 * user_surfacing_tweet_vectors.gap_564) + (engaged_user_surfacing_tweet_vectors.gap_565 * user_surfacing_tweet_vectors.gap_565) + (engaged_user_surfacing_tweet_vectors.gap_566 * user_surfacing_tweet_vectors.gap_566) + (engaged_user_surfacing_tweet_vectors.gap_567 * user_surfacing_tweet_vectors.gap_567) + (engaged_user_surfacing_tweet_vectors.gap_568 * user_surfacing_tweet_vectors.gap_568) + (engaged_user_surfacing_tweet_vectors.gap_569 * user_surfacing_tweet_vectors.gap_569) + (engaged_user_surfacing_tweet_vectors.gap_570 * user_surfacing_tweet_vectors.gap_570) + (engaged_user_surfacing_tweet_vectors.gap_571 * user_surfacing_tweet_vectors.gap_571) + (engaged_user_surfacing_tweet_vectors.gap_572 * user_surfacing_tweet_vectors.gap_572) + (engaged_user_surfacing_tweet_vectors.gap_573 * user_surfacing_tweet_vectors.gap_573) + (engaged_user_surfacing_tweet_vectors.gap_574 * user_surfacing_tweet_vectors.gap_574) + (engaged_user_surfacing_tweet_vectors.gap_575 * user_surfacing_tweet_vectors.gap_575) + (engaged_user_surfacing_tweet_vectors.gap_576 * user_surfacing_tweet_vectors.gap_576) + (engaged_user_surfacing_tweet_vectors.gap_577 * user_surfacing_tweet_vectors.gap_577) + (engaged_user_surfacing_tweet_vectors.gap_578 * user_surfacing_tweet_vectors.gap_578) + (engaged_user_surfacing_tweet_vectors.gap_579 * user_surfacing_tweet_vectors.gap_579) + (engaged_user_surfacing_tweet_vectors.gap_580 * user_surfacing_tweet_vectors.gap_580) + (engaged_user_surfacing_tweet_vectors.gap_581 * user_surfacing_tweet_vectors.gap_581) + (engaged_user_surfacing_tweet_vectors.gap_582 * user_surfacing_tweet_vectors.gap_582) + (engaged_user_surfacing_tweet_vectors.gap_583 * user_surfacing_tweet_vectors.gap_583) + (engaged_user_surfacing_tweet_vectors.gap_584 * user_surfacing_tweet_vectors.gap_584) + (engaged_user_surfacing_tweet_vectors.gap_585 * user_surfacing_tweet_vectors.gap_585) + (engaged_user_surfacing_tweet_vectors.gap_586 * user_surfacing_tweet_vectors.gap_586) + (engaged_user_surfacing_tweet_vectors.gap_587 * user_surfacing_tweet_vectors.gap_587) + (engaged_user_surfacing_tweet_vectors.gap_588 * user_surfacing_tweet_vectors.gap_588) + (engaged_user_surfacing_tweet_vectors.gap_589 * user_surfacing_tweet_vectors.gap_589) + (engaged_user_surfacing_tweet_vectors.gap_590 * user_surfacing_tweet_vectors.gap_590) + (engaged_user_surfacing_tweet_vectors.gap_591 * user_surfacing_tweet_vectors.gap_591) + (engaged_user_surfacing_tweet_vectors.gap_592 * user_surfacing_tweet_vectors.gap_592) + (engaged_user_surfacing_tweet_vectors.gap_593 * user_surfacing_tweet_vectors.gap_593) + (engaged_user_surfacing_tweet_vectors.gap_594 * user_surfacing_tweet_vectors.gap_594) + (engaged_user_surfacing_tweet_vectors.gap_595 * user_surfacing_tweet_vectors.gap_595) + (engaged_user_surfacing_tweet_vectors.gap_596 * user_surfacing_tweet_vectors.gap_596) + (engaged_user_surfacing_tweet_vectors.gap_597 * user_surfacing_tweet_vectors.gap_597) + (engaged_user_surfacing_tweet_vectors.gap_598 * user_surfacing_tweet_vectors.gap_598) + (engaged_user_surfacing_tweet_vectors.gap_599 * user_surfacing_tweet_vectors.gap_599) + (engaged_user_surfacing_tweet_vectors.gap_600 * user_surfacing_tweet_vectors.gap_600) + (engaged_user_surfacing_tweet_vectors.gap_601 * user_surfacing_tweet_vectors.gap_601) + (engaged_user_surfacing_tweet_vectors.gap_602 * user_surfacing_tweet_vectors.gap_602) + (engaged_user_surfacing_tweet_vectors.gap_603 * user_surfacing_tweet_vectors.gap_603) + (engaged_user_surfacing_tweet_vectors.gap_604 * user_surfacing_tweet_vectors.gap_604) + (engaged_user_surfacing_tweet_vectors.gap_605 * user_surfacing_tweet_vectors.gap_605) + (engaged_user_surfacing_tweet_vectors.gap_606 * user_surfacing_tweet_vectors.gap_606) + (engaged_user_surfacing_tweet_vectors.gap_607 * user_surfacing_tweet_vectors.gap_607) + (engaged_user_surfacing_tweet_vectors.gap_608 * user_surfacing_tweet_vectors.gap_608) + (engaged_user_surfacing_tweet_vectors.gap_609 * user_surfacing_tweet_vectors.gap_609) + (engaged_user_surfacing_tweet_vectors.gap_610 * user_surfacing_tweet_vectors.gap_610) + (engaged_user_surfacing_tweet_vectors.gap_611 * user_surfacing_tweet_vectors.gap_611) + (engaged_user_surfacing_tweet_vectors.gap_612 * user_surfacing_tweet_vectors.gap_612) + (engaged_user_surfacing_tweet_vectors.gap_613 * user_surfacing_tweet_vectors.gap_613) + (engaged_user_surfacing_tweet_vectors.gap_614 * user_surfacing_tweet_vectors.gap_614) + (engaged_user_surfacing_tweet_vectors.gap_615 * user_surfacing_tweet_vectors.gap_615) + (engaged_user_surfacing_tweet_vectors.gap_616 * user_surfacing_tweet_vectors.gap_616) + (engaged_user_surfacing_tweet_vectors.gap_617 * user_surfacing_tweet_vectors.gap_617) + (engaged_user_surfacing_tweet_vectors.gap_618 * user_surfacing_tweet_vectors.gap_618) + (engaged_user_surfacing_tweet_vectors.gap_619 * user_surfacing_tweet_vectors.gap_619) + (engaged_user_surfacing_tweet_vectors.gap_620 * user_surfacing_tweet_vectors.gap_620) + (engaged_user_surfacing_tweet_vectors.gap_621 * user_surfacing_tweet_vectors.gap_621) + (engaged_user_surfacing_tweet_vectors.gap_622 * user_surfacing_tweet_vectors.gap_622) + (engaged_user_surfacing_tweet_vectors.gap_623 * user_surfacing_tweet_vectors.gap_623) + (engaged_user_surfacing_tweet_vectors.gap_624 * user_surfacing_tweet_vectors.gap_624) + (engaged_user_surfacing_tweet_vectors.gap_625 * user_surfacing_tweet_vectors.gap_625) + (engaged_user_surfacing_tweet_vectors.gap_626 * user_surfacing_tweet_vectors.gap_626) + (engaged_user_surfacing_tweet_vectors.gap_627 * user_surfacing_tweet_vectors.gap_627) + (engaged_user_surfacing_tweet_vectors.gap_628 * user_surfacing_tweet_vectors.gap_628) + (engaged_user_surfacing_tweet_vectors.gap_629 * user_surfacing_tweet_vectors.gap_629) + (engaged_user_surfacing_tweet_vectors.gap_630 * user_surfacing_tweet_vectors.gap_630) + (engaged_user_surfacing_tweet_vectors.gap_631 * user_surfacing_tweet_vectors.gap_631) + (engaged_user_surfacing_tweet_vectors.gap_632 * user_surfacing_tweet_vectors.gap_632) + (engaged_user_surfacing_tweet_vectors.gap_633 * user_surfacing_tweet_vectors.gap_633) + (engaged_user_surfacing_tweet_vectors.gap_634 * user_surfacing_tweet_vectors.gap_634) + (engaged_user_surfacing_tweet_vectors.gap_635 * user_surfacing_tweet_vectors.gap_635) + (engaged_user_surfacing_tweet_vectors.gap_636 * user_surfacing_tweet_vectors.gap_636) + (engaged_user_surfacing_tweet_vectors.gap_637 * user_surfacing_tweet_vectors.gap_637) + (engaged_user_surfacing_tweet_vectors.gap_638 * user_surfacing_tweet_vectors.gap_638) + (engaged_user_surfacing_tweet_vectors.gap_639 * user_surfacing_tweet_vectors.gap_639) + (engaged_user_surfacing_tweet_vectors.gap_640 * user_surfacing_tweet_vectors.gap_640) + (engaged_user_surfacing_tweet_vectors.gap_641 * user_surfacing_tweet_vectors.gap_641) + (engaged_user_surfacing_tweet_vectors.gap_642 * user_surfacing_tweet_vectors.gap_642) + (engaged_user_surfacing_tweet_vectors.gap_643 * user_surfacing_tweet_vectors.gap_643) + (engaged_user_surfacing_tweet_vectors.gap_644 * user_surfacing_tweet_vectors.gap_644) + (engaged_user_surfacing_tweet_vectors.gap_645 * user_surfacing_tweet_vectors.gap_645) + (engaged_user_surfacing_tweet_vectors.gap_646 * user_surfacing_tweet_vectors.gap_646) + (engaged_user_surfacing_tweet_vectors.gap_647 * user_surfacing_tweet_vectors.gap_647) + (engaged_user_surfacing_tweet_vectors.gap_648 * user_surfacing_tweet_vectors.gap_648) + (engaged_user_surfacing_tweet_vectors.gap_649 * user_surfacing_tweet_vectors.gap_649) + (engaged_user_surfacing_tweet_vectors.gap_650 * user_surfacing_tweet_vectors.gap_650) + (engaged_user_surfacing_tweet_vectors.gap_651 * user_surfacing_tweet_vectors.gap_651) + (engaged_user_surfacing_tweet_vectors.gap_652 * user_surfacing_tweet_vectors.gap_652) + (engaged_user_surfacing_tweet_vectors.gap_653 * user_surfacing_tweet_vectors.gap_653) + (engaged_user_surfacing_tweet_vectors.gap_654 * user_surfacing_tweet_vectors.gap_654) + (engaged_user_surfacing_tweet_vectors.gap_655 * user_surfacing_tweet_vectors.gap_655) + (engaged_user_surfacing_tweet_vectors.gap_656 * user_surfacing_tweet_vectors.gap_656) + (engaged_user_surfacing_tweet_vectors.gap_657 * user_surfacing_tweet_vectors.gap_657) + (engaged_user_surfacing_tweet_vectors.gap_658 * user_surfacing_tweet_vectors.gap_658) + (engaged_user_surfacing_tweet_vectors.gap_659 * user_surfacing_tweet_vectors.gap_659) + (engaged_user_surfacing_tweet_vectors.gap_660 * user_surfacing_tweet_vectors.gap_660) + (engaged_user_surfacing_tweet_vectors.gap_661 * user_surfacing_tweet_vectors.gap_661) + (engaged_user_surfacing_tweet_vectors.gap_662 * user_surfacing_tweet_vectors.gap_662) + (engaged_user_surfacing_tweet_vectors.gap_663 * user_surfacing_tweet_vectors.gap_663) + (engaged_user_surfacing_tweet_vectors.gap_664 * user_surfacing_tweet_vectors.gap_664) + (engaged_user_surfacing_tweet_vectors.gap_665 * user_surfacing_tweet_vectors.gap_665) + (engaged_user_surfacing_tweet_vectors.gap_666 * user_surfacing_tweet_vectors.gap_666) + (engaged_user_surfacing_tweet_vectors.gap_667 * user_surfacing_tweet_vectors.gap_667) + (engaged_user_surfacing_tweet_vectors.gap_668 * user_surfacing_tweet_vectors.gap_668) + (engaged_user_surfacing_tweet_vectors.gap_669 * user_surfacing_tweet_vectors.gap_669) + (engaged_user_surfacing_tweet_vectors.gap_670 * user_surfacing_tweet_vectors.gap_670) + (engaged_user_surfacing_tweet_vectors.gap_671 * user_surfacing_tweet_vectors.gap_671) + (engaged_user_surfacing_tweet_vectors.gap_672 * user_surfacing_tweet_vectors.gap_672) + (engaged_user_surfacing_tweet_vectors.gap_673 * user_surfacing_tweet_vectors.gap_673) + (engaged_user_surfacing_tweet_vectors.gap_674 * user_surfacing_tweet_vectors.gap_674) + (engaged_user_surfacing_tweet_vectors.gap_675 * user_surfacing_tweet_vectors.gap_675) + (engaged_user_surfacing_tweet_vectors.gap_676 * user_surfacing_tweet_vectors.gap_676) + (engaged_user_surfacing_tweet_vectors.gap_677 * user_surfacing_tweet_vectors.gap_677) + (engaged_user_surfacing_tweet_vectors.gap_678 * user_surfacing_tweet_vectors.gap_678) + (engaged_user_surfacing_tweet_vectors.gap_679 * user_surfacing_tweet_vectors.gap_679) + (engaged_user_surfacing_tweet_vectors.gap_680 * user_surfacing_tweet_vectors.gap_680) + (engaged_user_surfacing_tweet_vectors.gap_681 * user_surfacing_tweet_vectors.gap_681) + (engaged_user_surfacing_tweet_vectors.gap_682 * user_surfacing_tweet_vectors.gap_682) + (engaged_user_surfacing_tweet_vectors.gap_683 * user_surfacing_tweet_vectors.gap_683) + (engaged_user_surfacing_tweet_vectors.gap_684 * user_surfacing_tweet_vectors.gap_684) + (engaged_user_surfacing_tweet_vectors.gap_685 * user_surfacing_tweet_vectors.gap_685) + (engaged_user_surfacing_tweet_vectors.gap_686 * user_surfacing_tweet_vectors.gap_686) + (engaged_user_surfacing_tweet_vectors.gap_687 * user_surfacing_tweet_vectors.gap_687) + (engaged_user_surfacing_tweet_vectors.gap_688 * user_surfacing_tweet_vectors.gap_688) + (engaged_user_surfacing_tweet_vectors.gap_689 * user_surfacing_tweet_vectors.gap_689) + (engaged_user_surfacing_tweet_vectors.gap_690 * user_surfacing_tweet_vectors.gap_690) + (engaged_user_surfacing_tweet_vectors.gap_691 * user_surfacing_tweet_vectors.gap_691) + (engaged_user_surfacing_tweet_vectors.gap_692 * user_surfacing_tweet_vectors.gap_692) + (engaged_user_surfacing_tweet_vectors.gap_693 * user_surfacing_tweet_vectors.gap_693) + (engaged_user_surfacing_tweet_vectors.gap_694 * user_surfacing_tweet_vectors.gap_694) + (engaged_user_surfacing_tweet_vectors.gap_695 * user_surfacing_tweet_vectors.gap_695) + (engaged_user_surfacing_tweet_vectors.gap_696 * user_surfacing_tweet_vectors.gap_696) + (engaged_user_surfacing_tweet_vectors.gap_697 * user_surfacing_tweet_vectors.gap_697) + (engaged_user_surfacing_tweet_vectors.gap_698 * user_surfacing_tweet_vectors.gap_698) + (engaged_user_surfacing_tweet_vectors.gap_699 * user_surfacing_tweet_vectors.gap_699) + (engaged_user_surfacing_tweet_vectors.gap_700 * user_surfacing_tweet_vectors.gap_700) + (engaged_user_surfacing_tweet_vectors.gap_701 * user_surfacing_tweet_vectors.gap_701) + (engaged_user_surfacing_tweet_vectors.gap_702 * user_surfacing_tweet_vectors.gap_702) + (engaged_user_surfacing_tweet_vectors.gap_703 * user_surfacing_tweet_vectors.gap_703) + (engaged_user_surfacing_tweet_vectors.gap_704 * user_surfacing_tweet_vectors.gap_704) + (engaged_user_surfacing_tweet_vectors.gap_705 * user_surfacing_tweet_vectors.gap_705) + (engaged_user_surfacing_tweet_vectors.gap_706 * user_surfacing_tweet_vectors.gap_706) + (engaged_user_surfacing_tweet_vectors.gap_707 * user_surfacing_tweet_vectors.gap_707) + (engaged_user_surfacing_tweet_vectors.gap_708 * user_surfacing_tweet_vectors.gap_708) + (engaged_user_surfacing_tweet_vectors.gap_709 * user_surfacing_tweet_vectors.gap_709) + (engaged_user_surfacing_tweet_vectors.gap_710 * user_surfacing_tweet_vectors.gap_710) + (engaged_user_surfacing_tweet_vectors.gap_711 * user_surfacing_tweet_vectors.gap_711) + (engaged_user_surfacing_tweet_vectors.gap_712 * user_surfacing_tweet_vectors.gap_712) + (engaged_user_surfacing_tweet_vectors.gap_713 * user_surfacing_tweet_vectors.gap_713) + (engaged_user_surfacing_tweet_vectors.gap_714 * user_surfacing_tweet_vectors.gap_714) + (engaged_user_surfacing_tweet_vectors.gap_715 * user_surfacing_tweet_vectors.gap_715) + (engaged_user_surfacing_tweet_vectors.gap_716 * user_surfacing_tweet_vectors.gap_716) + (engaged_user_surfacing_tweet_vectors.gap_717 * user_surfacing_tweet_vectors.gap_717) + (engaged_user_surfacing_tweet_vectors.gap_718 * user_surfacing_tweet_vectors.gap_718) + (engaged_user_surfacing_tweet_vectors.gap_719 * user_surfacing_tweet_vectors.gap_719) + (engaged_user_surfacing_tweet_vectors.gap_720 * user_surfacing_tweet_vectors.gap_720) + (engaged_user_surfacing_tweet_vectors.gap_721 * user_surfacing_tweet_vectors.gap_721) + (engaged_user_surfacing_tweet_vectors.gap_722 * user_surfacing_tweet_vectors.gap_722) + (engaged_user_surfacing_tweet_vectors.gap_723 * user_surfacing_tweet_vectors.gap_723) + (engaged_user_surfacing_tweet_vectors.gap_724 * user_surfacing_tweet_vectors.gap_724) + (engaged_user_surfacing_tweet_vectors.gap_725 * user_surfacing_tweet_vectors.gap_725) + (engaged_user_surfacing_tweet_vectors.gap_726 * user_surfacing_tweet_vectors.gap_726) + (engaged_user_surfacing_tweet_vectors.gap_727 * user_surfacing_tweet_vectors.gap_727) + (engaged_user_surfacing_tweet_vectors.gap_728 * user_surfacing_tweet_vectors.gap_728) + (engaged_user_surfacing_tweet_vectors.gap_729 * user_surfacing_tweet_vectors.gap_729) + (engaged_user_surfacing_tweet_vectors.gap_730 * user_surfacing_tweet_vectors.gap_730) + (engaged_user_surfacing_tweet_vectors.gap_731 * user_surfacing_tweet_vectors.gap_731) + (engaged_user_surfacing_tweet_vectors.gap_732 * user_surfacing_tweet_vectors.gap_732) + (engaged_user_surfacing_tweet_vectors.gap_733 * user_surfacing_tweet_vectors.gap_733) + (engaged_user_surfacing_tweet_vectors.gap_734 * user_surfacing_tweet_vectors.gap_734) + (engaged_user_surfacing_tweet_vectors.gap_735 * user_surfacing_tweet_vectors.gap_735) + (engaged_user_surfacing_tweet_vectors.gap_736 * user_surfacing_tweet_vectors.gap_736) + (engaged_user_surfacing_tweet_vectors.gap_737 * user_surfacing_tweet_vectors.gap_737) + (engaged_user_surfacing_tweet_vectors.gap_738 * user_surfacing_tweet_vectors.gap_738) + (engaged_user_surfacing_tweet_vectors.gap_739 * user_surfacing_tweet_vectors.gap_739) + (engaged_user_surfacing_tweet_vectors.gap_740 * user_surfacing_tweet_vectors.gap_740) + (engaged_user_surfacing_tweet_vectors.gap_741 * user_surfacing_tweet_vectors.gap_741) + (engaged_user_surfacing_tweet_vectors.gap_742 * user_surfacing_tweet_vectors.gap_742) + (engaged_user_surfacing_tweet_vectors.gap_743 * user_surfacing_tweet_vectors.gap_743) + (engaged_user_surfacing_tweet_vectors.gap_744 * user_surfacing_tweet_vectors.gap_744) + (engaged_user_surfacing_tweet_vectors.gap_745 * user_surfacing_tweet_vectors.gap_745) + (engaged_user_surfacing_tweet_vectors.gap_746 * user_surfacing_tweet_vectors.gap_746) + (engaged_user_surfacing_tweet_vectors.gap_747 * user_surfacing_tweet_vectors.gap_747) + (engaged_user_surfacing_tweet_vectors.gap_748 * user_surfacing_tweet_vectors.gap_748) + (engaged_user_surfacing_tweet_vectors.gap_749 * user_surfacing_tweet_vectors.gap_749) + (engaged_user_surfacing_tweet_vectors.gap_750 * user_surfacing_tweet_vectors.gap_750) + (engaged_user_surfacing_tweet_vectors.gap_751 * user_surfacing_tweet_vectors.gap_751) + (engaged_user_surfacing_tweet_vectors.gap_752 * user_surfacing_tweet_vectors.gap_752) + (engaged_user_surfacing_tweet_vectors.gap_753 * user_surfacing_tweet_vectors.gap_753) + (engaged_user_surfacing_tweet_vectors.gap_754 * user_surfacing_tweet_vectors.gap_754) + (engaged_user_surfacing_tweet_vectors.gap_755 * user_surfacing_tweet_vectors.gap_755) + (engaged_user_surfacing_tweet_vectors.gap_756 * user_surfacing_tweet_vectors.gap_756) + (engaged_user_surfacing_tweet_vectors.gap_757 * user_surfacing_tweet_vectors.gap_757) + (engaged_user_surfacing_tweet_vectors.gap_758 * user_surfacing_tweet_vectors.gap_758) + (engaged_user_surfacing_tweet_vectors.gap_759 * user_surfacing_tweet_vectors.gap_759) + (engaged_user_surfacing_tweet_vectors.gap_760 * user_surfacing_tweet_vectors.gap_760) + (engaged_user_surfacing_tweet_vectors.gap_761 * user_surfacing_tweet_vectors.gap_761) + (engaged_user_surfacing_tweet_vectors.gap_762 * user_surfacing_tweet_vectors.gap_762) + (engaged_user_surfacing_tweet_vectors.gap_763 * user_surfacing_tweet_vectors.gap_763) + (engaged_user_surfacing_tweet_vectors.gap_764 * user_surfacing_tweet_vectors.gap_764) + (engaged_user_surfacing_tweet_vectors.gap_765 * user_surfacing_tweet_vectors.gap_765) + (engaged_user_surfacing_tweet_vectors.gap_766 * user_surfacing_tweet_vectors.gap_766) + (engaged_user_surfacing_tweet_vectors.gap_767 * user_surfacing_tweet_vectors.gap_767) ) as dot_product_of_engaged_tweet_and_engaging_user_surfacing_tweets from {table_name} t left join user_surfacing_tweet_vectors on t.engaging_user_id = user_surfacing_tweet_vectors.user_id left join user_surfacing_tweet_vectors as engaged_user_surfacing_tweet_vectors on t.engaged_user_id = engaged_user_surfacing_tweet_vectors.user_id order by t.tweet_id, t.engaging_user_id """ if __name__ == "__main__": BertSimilarityBetweenEngagedAndEngagingSurfacingTweetVectorsFeature.main()

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4b978523b533013082b7659779c982c894fd7ffc

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py

Python

main/main.py

EternalPo/PythonTest

54aab905e304151bb27d0798ab900e8a2bed3c50

[ "Apache-2.0" ]

null

main/main.py

EternalPo/PythonTest

54aab905e304151bb27d0798ab900e8a2bed3c50

[ "Apache-2.0" ]

null

main/main.py

EternalPo/PythonTest

54aab905e304151bb27d0798ab900e8a2bed3c50

[ "Apache-2.0" ]

null

import createClass import tick

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29a05aea2d6c02ea086a53e08e949fbafaf7dd47

158

py

Python

ermaket/api/system/hierarchy/__init__.py

SqrtMinusOne/ERMaket_Experiment

c4a7b61651edd15a619d9b690e2aaeaab4de282d

[ "Apache-2.0" ]

null

ermaket/api/system/hierarchy/__init__.py

SqrtMinusOne/ERMaket_Experiment

c4a7b61651edd15a619d9b690e2aaeaab4de282d

[ "Apache-2.0" ]

null

ermaket/api/system/hierarchy/__init__.py

SqrtMinusOne/ERMaket_Experiment

c4a7b61651edd15a619d9b690e2aaeaab4de282d

[ "Apache-2.0" ]

null

from .hierarchy import * from .elements import * from .access import * from .table import * from .section import * from .scripts import * from .form import *

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py

Python

Flask_Demo_All/Flask_day04_03_blueprint/cart/views.py

GalphaXie/LaoX

b7e8f9744292dc052c870e4d873052e9bfec19ee

[ "MIT" ]

null

Flask_Demo_All/Flask_day04_03_blueprint/cart/views.py

GalphaXie/LaoX

b7e8f9744292dc052c870e4d873052e9bfec19ee

[ "MIT" ]

12

2020-03-24T17:39:25.000Z

2022-03-12T00:01:24.000Z

Flask_Demo_All/Flask_day04_03_blueprint/cart/views.py

GalphaXie/LaoX

b7e8f9744292dc052c870e4d873052e9bfec19ee

[ "MIT" ]

null

from . import cart_blu from flask import render_template # 2. 使用蓝图去注册路由url @cart_blu.route('/list') def cart_list(): return render_template('cart.html')

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29edca14a9eaae33b5641e9c52867042fbb85adb

72,467

py

Python

main.py

PeculiarCarrot/AutoDeleteSRWorlds

73e40a4c0cd39cc1584a72106e1f9ab3e3c1df2c

[ "MIT" ]

null

main.py

PeculiarCarrot/AutoDeleteSRWorlds

73e40a4c0cd39cc1584a72106e1f9ab3e3c1df2c

[ "MIT" ]

null

main.py

PeculiarCarrot/AutoDeleteSRWorlds

73e40a4c0cd39cc1584a72106e1f9ab3e3c1df2c

[ "MIT" ]

null

import tkinter from tkinter import * from tkinter.filedialog import askdirectory import time from watchdog.observers import Observer from watchdog.events import PatternMatchingEventHandler import os.path import re from os import path import shutil from datetime import datetime import base64 WIDTH = 600 HEIGHT = 200 START_BTN_TXT = 'Start Deleting' STOP_BTN_TXT = 'Stop Deleting' SHOW_PATH_TXT = 'Show Path' HIDE_PATH_TXT = 'Hide Path' SELECT_DIR_TXT = 'Select ".minecraft/saves/" folder' NO_DIRECTORY_TXT = 'No directory chosen.' SAVE_PATH = './data.txt' pathLabel = None infoLabel = None startStopButton = None showHideButton = None dirObserver = Observer() eventHandler = None root = tkinter.Tk() root.title('Destroyer of Worlds') started = False dirPath = "" hidePath = False def chooseSaveDir(): global dirPath dirPath = askdirectory(title=SELECT_DIR_TXT) if started: toggleStart() updatePathRelatedThings() saveData() #messagebox.showinfo( "Hello Python", "Hello World") def createEventHandler(): global eventHandler patterns = "*" ignore_patterns = "" ignore_directories = False case_sensitive = True eventHandler = PatternMatchingEventHandler(patterns, ignore_patterns, ignore_directories, case_sensitive) eventHandler.on_created = on_created eventHandler.on_deleted = on_deleted eventHandler.on_modified = on_modified eventHandler.on_moved = on_moved def startObserver(): global dirObserver if dirObserver.is_alive(): return dirObserver = Observer() dirObserver.schedule(eventHandler, dirPath, recursive=False) dirObserver.start() def stopObserver(): if not dirObserver.is_alive(): return dirObserver.stop() dirObserver.join() def dirIsNewWorld(dir): return len(re.findall(r'\\New World $\+?\d+$$', dir)) > 0 or len(re.findall(r'\\New World-*$', dir)) > 0 def getAllSubfolders(): return [ f.path for f in os.scandir(dirPath) if f.is_dir() ] def on_created(event): print("Something created!") if not started: print("--Not started so idc") return #print("All Directories:\n" + str(getAllSubfolders())) if not event.is_directory: print("--Non-directory so idc") return time.sleep(4) levelExists = path.exists(path.join(event.src_path, 'level.dat')) isDefaultNewWorld = dirIsNewWorld(event.src_path) if levelExists and isDefaultNewWorld: purge(event) def purge(event): global infoLabel print("========BEGINNING THE PURGE============") saves = getAllSubfolders() count = 0 for save in saves: if save == event.src_path: continue shouldPurge = dirIsNewWorld(save) if shouldPurge: print("Purging " + save) try: shutil.rmtree(save) count += 1 except PermissionError: print(f"Don't have permission to remove {save}, skipping...") if count > 0: infoLabel['text'] = f"[{datetime.now().strftime('%H:%M:%S')}] Deleted {count} {'world' if count == 1 else 'worlds'}."; def on_deleted(event): pass def on_modified(event): pass def on_moved(event): pass def updatePathRelatedThings(): global pathLabel enabled = True if dirPath is None or dirPath == '': enabled = False if enabled: startObserver() else: stopObserver() updatePathLabel() if enabled and startStopButton['state'] == 'disabled': startStopButton['state'] = 'active' elif not enabled: startStopButton['state'] = 'disabled' def updatePathLabel(): global hidePath global pathLabel if dirPath is None or dirPath == '': pathLabel['text'] = NO_DIRECTORY_TXT else: if hidePath: pathLabel['text'] = '[Path hidden]' else: pathLabel['text'] = dirPath def toggleStart(): global started global hidePath started = not started if not started: # Stop it. Get some help. startStopButton['text'] = START_BTN_TXT else: # Start it startStopButton['text'] = STOP_BTN_TXT def center_window(): screen_width = root.winfo_screenwidth() screen_height = root.winfo_screenheight() x = (screen_width/2) - (WIDTH/2) y = (screen_height/2) - (HEIGHT) root.geometry('%dx%d+%d+%d' % (WIDTH, HEIGHT, x, y)) def loadData(): global dirPath global hidePath if path.exists(SAVE_PATH): with open(SAVE_PATH, "r") as f: dirPath = f.readline().rstrip() hidePath = f.readline().rstrip() == "True" if hidePath: showHideButton['text'] = SHOW_PATH_TXT else: showHideButton['text'] = HIDE_PATH_TXT updatePathRelatedThings() def saveData(): with open(SAVE_PATH, "w") as f: f.write(dirPath + "\n" + str(hidePath)); def toggleShowPath(): global hidePath hidePath = not hidePath if hidePath: showHideButton['text'] = SHOW_PATH_TXT else: showHideButton['text'] = HIDE_PATH_TXT updatePathLabel() saveData() def onDelCheckToggled(): saveData() def main(): global startStopButton global pathLabel global showHideButton global infoLabel root.minsize(WIDTH, HEIGHT) center_window() tmp = open("temp.ico","wb+") tmp.write(base64.b64decode(img)) tmp.close() root.iconbitmap("temp.ico") os.remove("temp.ico") chooseDirButton = Button(root, text = SELECT_DIR_TXT, command = chooseSaveDir) startStopButton = Button(root, text = START_BTN_TXT, command = toggleStart) showHideButton = Button(root, text = HIDE_PATH_TXT, command = toggleShowPath) pathLabel = Label(root, text = NO_DIRECTORY_TXT) infoLabel = Label(root, text = '') pathLabel.place(relx=0.5, rely=0.01, anchor=N) infoLabel.place(relx=0.5, rely=0.9, anchor=CENTER) chooseDirButton.place(relx=0.5, rely=0.15, anchor=N) showHideButton.place(relx=0.5, rely=0.3, anchor=N) startStopButton.place(relx=0.5, rely=0.7, anchor=CENTER) createEventHandler() loadData() root.mainloop() #the icon is a base64 string because it's easy, I'm so sorry img= """ 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""" main()

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4b0dc39c7f8b8f3235271296a72ed46a8baf0ae2

21

py

Python

appengine/gallery_api/__init__.py

bharati-software/blockly-games-Kannada

cc410e7656699f0fd1b23626917b17c61f5c168b

[ "Apache-2.0" ]

1,184

2015-01-02T19:07:55.000Z

2022-03-31T11:29:28.000Z

appengine/gallery_api/__init__.py

moniika/blockly-games

e99f3cfc1f2a2844dd3423c83202ed968296005e

[ "Apache-2.0" ]

171

2015-01-01T17:10:24.000Z

2022-03-28T03:18:07.000Z

appengine/gallery_api/__init__.py

moniika/blockly-games

e99f3cfc1f2a2844dd3423c83202ed968296005e

[ "Apache-2.0" ]

580

2015-01-05T00:36:37.000Z

2022-03-23T15:21:16.000Z

from common import *

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d9a61b06884b1e1bad989450551a4f07b6a78753

11,907

py

Python

engine/trainer.py

chanijung/reid-strong-baseline

96d787fac83de4d58027282f8b161141616928cc

[ "MIT" ]

null

engine/trainer.py

chanijung/reid-strong-baseline

96d787fac83de4d58027282f8b161141616928cc

[ "MIT" ]

null

engine/trainer.py

chanijung/reid-strong-baseline

96d787fac83de4d58027282f8b161141616928cc

[ "MIT" ]

null

# encoding: utf-8 """ @author: sherlock @contact: sherlockliao01@gmail.com """ import logging import torch import torch.nn as nn from ignite.engine import Engine, Events from ignite.handlers import ModelCheckpoint, Timer from ignite.metrics import RunningAverage from utils.reid_metric import R1_mAP # from ignite.contrib.handlers import TensorboardLogger # from ignite.contrib.handlers.tensorboard_logger import * global ITER ITER = 0 def create_supervised_trainer(model, optimizer, loss_fn, device=None): """ Factory function for creating a trainer for supervised models Args: model (`torch.nn.Module`): the model to train optimizer (`torch.optim.Optimizer`): the optimizer to use loss_fn (torch.nn loss function): the loss function to use device (str, optional): device type specification (default: None). Applies to both model and batches. Returns: Engine: a trainer engine with supervised update function """ if device: if torch.cuda.device_count() > 1: model = nn.DataParallel(model) model.to(device) def _update(engine, batch): model.train() optimizer.zero_grad() img, target = batch img = img.to(device) if torch.cuda.device_count() >= 1 else img target = target.to(device) if torch.cuda.device_count() >= 1 else target score, feat = model(img) loss = loss_fn(score, feat, target) loss.backward() optimizer.step() # compute acc acc = (score.max(1)[1] == target).float().mean() return loss.item(), acc.item() return Engine(_update) def create_supervised_trainer_with_center(model, center_criterion, optimizer, optimizer_center, loss_fn, cetner_loss_weight, k, m, device=None): """ Factory function for creating a trainer for supervised models Args: model (`torch.nn.Module`): the model to train optimizer (`torch.optim.Optimizer`): the optimizer to use loss_fn (torch.nn loss function): the loss function to use device (str, optional): device type specification (default: None). Applies to both model and batches. Returns: Engine: a trainer engine with supervised update function """ if device: if torch.cuda.device_count() > 1: model = nn.DataParallel(model) model.to(device) def _update(engine, batch): model.train() optimizer.zero_grad() optimizer_center.zero_grad() img, target, camids = batch img = img.to(device) if torch.cuda.device_count() >= 1 else img camids = torch.tensor(camids).to(device) if torch.cuda.device_count() >= 1 else img target = target.to(device) if torch.cuda.device_count() >= 1 else target score, feat = model(img) loss = loss_fn(score, feat, target, camids, engine.state.iteration, k, m) # print("Total loss is {}, center loss is {}".format(loss, center_criterion(feat, target))) loss.backward() optimizer.step() for param in center_criterion.parameters(): param.grad.data *= (1. / cetner_loss_weight) optimizer_center.step() # compute acc acc = (score.max(1)[1] == target).float().mean() return loss.item(), acc.item() return Engine(_update) def create_supervised_evaluator(model, metrics, device=None): """ Factory function for creating an evaluator for supervised models Args: model (`torch.nn.Module`): the model to train metrics (dict of str - :class:`ignite.metrics.Metric`): a map of metric names to Metrics device (str, optional): device type specification (default: None). Applies to both model and batches. Returns: Engine: an evaluator engine with supervised inference function """ if device: if torch.cuda.device_count() > 1: model = nn.DataParallel(model) model.to(device) def _inference(engine, batch): model.eval() with torch.no_grad(): data, pids, camids = batch data = data.to(device) if torch.cuda.device_count() >= 1 else data feat = model(data) return feat, pids, camids engine = Engine(_inference) for name, metric in metrics.items(): metric.attach(engine, name) return engine def do_train( cfg, model, train_loader, val_loader, optimizer, scheduler, loss_fn, num_query, start_epoch ): log_period = cfg.SOLVER.LOG_PERIOD checkpoint_period = cfg.SOLVER.CHECKPOINT_PERIOD eval_period = cfg.SOLVER.EVAL_PERIOD output_dir = cfg.OUTPUT_DIR device = cfg.MODEL.DEVICE epochs = cfg.SOLVER.MAX_EPOCHS logger = logging.getLogger("reid_baseline.train") logger.info("Start training") trainer = create_supervised_trainer(model, optimizer, loss_fn, device=device) evaluator = create_supervised_evaluator(model, metrics={'r1_mAP': R1_mAP(num_query, max_rank=50, feat_norm=cfg.TEST.FEAT_NORM)}, device=device) checkpointer = ModelCheckpoint(output_dir, cfg.MODEL.NAME, checkpoint_period, n_saved=10, require_empty=False) timer = Timer(average=True) trainer.add_event_handler(Events.EPOCH_COMPLETED, checkpointer, {'model': model, 'optimizer': optimizer}) timer.attach(trainer, start=Events.EPOCH_STARTED, resume=Events.ITERATION_STARTED, pause=Events.ITERATION_COMPLETED, step=Events.ITERATION_COMPLETED) # average metric to attach on trainer RunningAverage(output_transform=lambda x: x[0]).attach(trainer, 'avg_loss') RunningAverage(output_transform=lambda x: x[1]).attach(trainer, 'avg_acc') @trainer.on(Events.STARTED) def start_training(engine): engine.state.epoch = start_epoch @trainer.on(Events.EPOCH_STARTED) def adjust_learning_rate(engine): scheduler.step() @trainer.on(Events.ITERATION_COMPLETED) def log_training_loss(engine): global ITER ITER += 1 if ITER % log_period == 0: logger.info("Epoch[{}] Iteration[{}/{}] Loss: {:.3f}, Acc: {:.3f}, Base Lr: {:.2e}" .format(engine.state.epoch, ITER, len(train_loader), engine.state.metrics['avg_loss'], engine.state.metrics['avg_acc'], scheduler.get_lr()[0])) if len(train_loader) == ITER: ITER = 0 # adding handlers using `trainer.on` decorator API @trainer.on(Events.EPOCH_COMPLETED) def print_times(engine): logger.info('Epoch {} done. Time per batch: {:.3f}[s] Speed: {:.1f}[samples/s]' .format(engine.state.epoch, timer.value() * timer.step_count, train_loader.batch_size / timer.value())) logger.info('-' * 10) timer.reset() @trainer.on(Events.EPOCH_COMPLETED) def log_validation_results(engine): if engine.state.epoch % eval_period == 0: evaluator.run(val_loader) cmc, mAP = evaluator.state.metrics['r1_mAP'] logger.info("Validation Results - Epoch: {}".format(engine.state.epoch)) logger.info("mAP: {:.1%}".format(mAP)) for r in [1, 5, 10]: logger.info("CMC curve, Rank-{:<3}:{:.1%}".format(r, cmc[r - 1])) trainer.run(train_loader, max_epochs=epochs) def do_train_with_center( cfg, model, center_criterion, train_loader, val_loader, optimizer, optimizer_center, scheduler, loss_fn, num_query, start_epoch, k, m ): log_period = cfg.SOLVER.LOG_PERIOD checkpoint_period = cfg.SOLVER.CHECKPOINT_PERIOD eval_period = cfg.SOLVER.EVAL_PERIOD output_dir = cfg.OUTPUT_DIR device = cfg.MODEL.DEVICE epochs = cfg.SOLVER.MAX_EPOCHS logger = logging.getLogger("reid_baseline.train") logger.info("Start training") trainer = create_supervised_trainer_with_center(model, center_criterion, optimizer, optimizer_center, loss_fn, cfg.SOLVER.CENTER_LOSS_WEIGHT, k, m, device=device ) evaluator = create_supervised_evaluator(model, metrics={'r1_mAP': R1_mAP(num_query, max_rank=50, feat_norm=cfg.TEST.FEAT_NORM)}, device=device) checkpointer = ModelCheckpoint(output_dir, cfg.MODEL.NAME, checkpoint_period, n_saved=10, require_empty=False) timer = Timer(average=True) trainer.add_event_handler(Events.EPOCH_COMPLETED, checkpointer, {'model': model, 'optimizer': optimizer, 'center_param': center_criterion, 'optimizer_center': optimizer_center}) timer.attach(trainer, start=Events.EPOCH_STARTED, resume=Events.ITERATION_STARTED, pause=Events.ITERATION_COMPLETED, step=Events.ITERATION_COMPLETED) # average metric to attach on trainer RunningAverage(output_transform=lambda x: x[0]).attach(trainer, 'avg_loss') RunningAverage(output_transform=lambda x: x[1]).attach(trainer, 'avg_acc') @trainer.on(Events.STARTED) def start_training(engine): engine.state.epoch = start_epoch @trainer.on(Events.EPOCH_STARTED) def adjust_learning_rate(engine): scheduler.step() @trainer.on(Events.ITERATION_COMPLETED) def log_training_loss(engine): global ITER ITER += 1 if ITER % log_period == 0: logger.info("Epoch[{}] Iteration[{}/{}] Loss: {:.3f}, Acc: {:.3f}, Base Lr: {:.2e}" .format(engine.state.epoch, ITER, len(train_loader), engine.state.metrics['avg_loss'], engine.state.metrics['avg_acc'], scheduler.get_lr()[0])) if len(train_loader) == ITER: ITER = 0 # adding handlers using `trainer.on` decorator API @trainer.on(Events.EPOCH_COMPLETED) def print_times(engine): logger.info('Epoch {} done. Time per batch: {:.3f}[s] Speed: {:.1f}[samples/s]' .format(engine.state.epoch, timer.value() * timer.step_count, train_loader.batch_size / timer.value())) logger.info('-' * 10) timer.reset() @trainer.on(Events.EPOCH_COMPLETED) def log_validation_results(engine): if engine.state.epoch % eval_period == 0: evaluator.run(val_loader) cmc, mAP = evaluator.state.metrics['r1_mAP'] logger.info("Validation Results - Epoch: {}".format(engine.state.epoch)) logger.info("mAP: {:.1%}".format(mAP)) for r in [1, 5, 10]: logger.info("CMC curve, Rank-{:<3}:{:.1%}".format(r, cmc[r - 1])) ## Plot training result # # Define a Tensorboard logger # tb_logger = TensorboardLogger(log_dir=f"log/k{k}_m{m}/plot") # # Attach handler to plot trainer's loss every 100 iterations # tb_logger.attach_output_handler( # trainer, # event_name=Events.ITERATION_COMPLETED(every=100), # tag="training", # output_transform=lambda loss: {"batchloss": loss}, # ) # # Attach handler to dump evaluator's metrics every epoch completed # tb_logger.attach_output_handler( # evaluator, # event_name=Events.EPOCH_COMPLETED, # tag="training", # metric_names="all", # global_step_transform=tensorboard_logger.global_step_from_engine(trainer), # ) trainer.run(train_loader, max_epochs=epochs) # tb_logger.close()

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d9b59879734b0af8ed27e4bf424f5978944a7dfc

38

py

Python

fastiqa/all.py

baidut/PatchVQ

040486b6342dfd36695f1daea0b5c4d77d728a23

[ "Unlicense" ]

32

2020-12-05T09:11:20.000Z

2022-03-28T07:49:13.000Z

fastiqa/all.py

utlive/PatchVQ

040486b6342dfd36695f1daea0b5c4d77d728a23

[ "Unlicense" ]

5

2021-07-12T19:43:51.000Z

2022-01-28T13:16:16.000Z

fastiqa/all.py

utlive/PatchVQ

040486b6342dfd36695f1daea0b5c4d77d728a23

[ "Unlicense" ]

7

2020-12-29T21:52:07.000Z

2022-03-18T15:12:50.000Z

from .iqa import * from .vqa import *

12.666667

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0.210526

38

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6

d9bdd72be252f1abef8b5be6c568b161143a2118

6,422

py

Python

pytorch-cifar-master/models/small_CNN.py

robo-warrior/Permuted-Conv

cdfb803392680f44bf888eb098acaf0632f167dc

[ "MIT" ]

null

pytorch-cifar-master/models/small_CNN.py

robo-warrior/Permuted-Conv

cdfb803392680f44bf888eb098acaf0632f167dc

[ "MIT" ]

null

pytorch-cifar-master/models/small_CNN.py

robo-warrior/Permuted-Conv

cdfb803392680f44bf888eb098acaf0632f167dc

[ "MIT" ]

null

'''LeNet in PyTorch.''' import torch.nn as nn import torch.nn.functional as F import numpy as np class SmallCNN(nn.Module): def __init__(self, num_out_channels=100): super(SmallCNN, self).__init__() self.num_filters1 = 5 self.num_filters2 =10 self.conv1 = nn.Conv2d(in_channels=3, out_channels=self.num_filters1, kernel_size=3, padding=1) self.conv2 = nn.Conv2d(in_channels=self.num_filters1, out_channels=self.num_filters2, kernel_size=3, padding=1) self.fc = nn.Linear(8*8*self.num_filters2, num_out_channels) def forward(self, x): out = F.relu(self.conv1(x)) out = F.max_pool2d(out, 2) out = F.relu(self.conv2(out)) out = F.max_pool2d(out, 2) out = out.view(out.size(0), -1) out = self.fc(out) return out class SmallCNN_weighted(nn.Module): def __init__(self, num_out_channels=100): super(SmallCNN_weighted, self).__init__() self.num_filters1 = 5 self.num_filters2 = 10 # self.dwconv1 = nn.Conv2d(in_channels=3, out_channels=self.num_filters1 * 3, kernel_size=3, padding=1, bias=False, groups=3) self.dwconv1 = nn.Conv2d(in_channels=3, out_channels=self.num_filters1 * 3, kernel_size=3, padding=1, groups=3, bias=False) self.onexone1 = nn.Conv2d(in_channels=self.num_filters1 * 3, out_channels=self.num_filters1, kernel_size=1, groups=self.num_filters1) # self.dwconv2 = nn.Conv2d(in_channels=self.num_filters1, out_channels=self.num_filters2 * self.num_filters1, kernel_size=3, padding=1, bias=False, groups=self.num_filters1) self.dwconv2 = nn.Conv2d(in_channels=self.num_filters1, out_channels=self.num_filters2 * self.num_filters1, kernel_size=3, padding=1, groups=self.num_filters1, bias=False) self.onexone2 = nn.Conv2d(in_channels=self.num_filters2 * self.num_filters1, out_channels=self.num_filters2, kernel_size=1, groups=self.num_filters2) self.fc = nn.Linear(8 * 8 * self.num_filters2, num_out_channels) def forward(self, x): out = self.dwconv1(x) pos = [i for i in range(1, self.num_filters1 + 1)] ind = np.argsort(np.array(pos * (int)(out.shape[1]/self.num_filters1))) out = out[:, ind, :, :] out = F.relu(self.onexone1(out)) out = F.max_pool2d(out, 2) out = self.dwconv2(out) pos = [i for i in range(1, self.num_filters2 + 1)] ind = np.argsort(np.array(pos * (int)(out.shape[1] / self.num_filters2))) out = out[:, ind, :, :] out = F.relu(self.onexone2(out)) out = F.max_pool2d(out, 2) out = out.view(out.size(0), -1) out = self.fc(out) return out class SmallCNN_1x1(nn.Module): def __init__(self, num_out_channels=100): super(SmallCNN_1x1, self).__init__() self.num_filters1 = 5 self.num_filters2 = 10 # self.dwconv1 = nn.Conv2d(in_channels=3, out_channels=self.num_filters1 * 3, kernel_size=3, padding=1, bias=False, groups=3) self.dwconv1 = nn.Conv2d(in_channels=3, out_channels=self.num_filters1 * 3, kernel_size=3, padding=1, groups=3) self.onexone1 = nn.Conv2d(in_channels=self.num_filters1 * 3, out_channels=self.num_filters1, kernel_size=1, groups=self.num_filters1) # self.dwconv2 = nn.Conv2d(in_channels=self.num_filters1, out_channels=self.num_filters2 * self.num_filters1, kernel_size=3, padding=1, bias=False, groups=self.num_filters1) self.dwconv2 = nn.Conv2d(in_channels=self.num_filters1, out_channels=self.num_filters2 * self.num_filters1, kernel_size=3, padding=1, groups=self.num_filters1) self.onexone2 = nn.Conv2d(in_channels=self.num_filters2 * self.num_filters1, out_channels=self.num_filters2, kernel_size=1, groups=self.num_filters2) self.fc = nn.Linear(8 * 8 * self.num_filters2, num_out_channels) def forward(self, x): out = F.relu(self.onexone1(self.dwconv1(x))) out = F.max_pool2d(out, 2) out = F.relu(self.onexone2(self.dwconv2(out))) out = F.max_pool2d(out, 2) out = out.view(out.size(0), -1) out = self.fc(out) return out class E2ESmallCNN(nn.Module): def __init__(self, num_out_channels=100): super(E2ESmallCNN, self).__init__() self.num_filters1 = 5 self.num_filters2 =10 self.conv1 = nn.Conv2d(in_channels=3, out_channels=self.num_filters1, kernel_size=3, padding=1) self.conv2 = nn.Conv2d(in_channels=self.num_filters1, out_channels=self.num_filters2, kernel_size=3, padding=1) #16 x 16 x 10 self.conv3 = nn.Conv2d(in_channels=self.num_filters2, out_channels=1, kernel_size=7, padding=0) #10 x 10 x 1 def forward(self, x): out = F.relu(self.conv1(x)) out = F.max_pool2d(out, 2) out = F.relu(self.conv2(out)) out = F.relu(self.conv3(out)) out = out.view(out.size(0), -1) return out class E2ESmallCNN_1x1(nn.Module): def __init__(self, num_out_channels=100): super(E2ESmallCNN_1x1, self).__init__() self.num_filters1 = 5 self.num_filters2 = 10 self.num_filters3 = 1 self.dwconv1 = nn.Conv2d(in_channels=3, out_channels=self.num_filters1 * 3, kernel_size=3, padding=1, bias=False, groups=3) self.onexone1 = nn.Conv2d(in_channels=self.num_filters1 * 3, out_channels=self.num_filters1, kernel_size=1, groups=self.num_filters1) self.dwconv2 = nn.Conv2d(in_channels=self.num_filters1, out_channels=self.num_filters2 * self.num_filters1, kernel_size=3, padding=1, bias=False, groups=self.num_filters1) self.onexone2 = nn.Conv2d(in_channels=self.num_filters2 * self.num_filters1, out_channels=self.num_filters2, kernel_size=1, groups=self.num_filters2) # 16 x 16 x 10 self.dwconv3 = nn.Conv2d(in_channels=self.num_filters2, out_channels=self.num_filters3 * self.num_filters2, kernel_size=7, padding=0, bias=False, groups=self.num_filters2) # 10 x 10 x 10 self.onexone3 = nn.Conv2d(in_channels=self.num_filters3 * self.num_filters2, out_channels=self.num_filters3, kernel_size=1, groups=self.num_filters3) # 10 x 10 x 1 def forward(self, x): out = F.relu(self.onexone1(self.dwconv1(x))) out = F.max_pool2d(out, 2) out = F.relu(self.onexone2(self.dwconv2(out))) out = F.relu(self.onexone3(self.dwconv3(out))) out = out.view(out.size(0), -1) return out

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6,422

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0.237113

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null

0

1

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null

0

6

d9cbc26b963a53f001604892399b86b21703233e

67,050

py

Python

tests/test_customer.py

PabloCastellano/dj-stripe

d804a54698d659e834f7def88d19b4e2de1e392e

[ "MIT" ]

null

tests/test_customer.py

PabloCastellano/dj-stripe

d804a54698d659e834f7def88d19b4e2de1e392e

[ "MIT" ]

null

tests/test_customer.py

PabloCastellano/dj-stripe

d804a54698d659e834f7def88d19b4e2de1e392e

[ "MIT" ]

null

""" Customer Model Tests. """ import decimal from copy import deepcopy from unittest.mock import ANY, patch from django.contrib.auth import get_user_model from django.test import TestCase from django.utils import timezone from stripe.error import InvalidRequestError from djstripe import settings as djstripe_settings from djstripe.exceptions import MultipleSubscriptionException from djstripe.models import ( Card, Charge, Coupon, Customer, DjstripePaymentMethod, IdempotencyKey, Invoice, PaymentMethod, Plan, Price, Product, Subscription, ) from djstripe.settings import STRIPE_SECRET_KEY from . import ( FAKE_ACCOUNT, FAKE_BALANCE_TRANSACTION, FAKE_CARD, FAKE_CARD_AS_PAYMENT_METHOD, FAKE_CARD_V, FAKE_CHARGE, FAKE_COUPON, FAKE_CUSTOMER, FAKE_CUSTOMER_II, FAKE_CUSTOMER_III, FAKE_CUSTOMER_IV, FAKE_DISCOUNT_CUSTOMER, FAKE_INVOICE, FAKE_INVOICE_III, FAKE_INVOICEITEM, FAKE_PAYMENT_INTENT_I, FAKE_PAYMENT_METHOD_I, FAKE_PLAN, FAKE_PRICE, FAKE_PRODUCT, FAKE_SOURCE, FAKE_SUBSCRIPTION, FAKE_SUBSCRIPTION_II, FAKE_UPCOMING_INVOICE, IS_STATICMETHOD_AUTOSPEC_SUPPORTED, AssertStripeFksMixin, StripeList, datetime_to_unix, default_account, ) class TestCustomer(AssertStripeFksMixin, TestCase): def setUp(self): self.user = get_user_model().objects.create_user( username="pydanny", email="pydanny@gmail.com" ) self.customer = FAKE_CUSTOMER.create_for_user(self.user) self.payment_method, _ = DjstripePaymentMethod._get_or_create_source( FAKE_CARD, "card" ) self.card = self.payment_method.resolve() self.customer.default_source = self.payment_method self.customer.save() self.account = default_account() def test_str(self): self.assertEqual(str(self.customer), str(self.user)) self.customer.subscriber = None self.assertEqual(str(self.customer), self.customer.description) def test_balance(self): self.assertEqual(self.customer.balance, 0) self.assertEqual(self.customer.credits, 0) self.customer.balance = 1000 self.assertEqual(self.customer.balance, 1000) self.assertEqual(self.customer.credits, 0) self.assertEqual(self.customer.pending_charges, 1000) self.customer.balance = -1000 self.assertEqual(self.customer.balance, -1000) self.assertEqual(self.customer.credits, 1000) self.assertEqual(self.customer.pending_charges, 0) def test_customer_dashboard_url(self): expected_url = "https://dashboard.stripe.com/test/customers/{}".format( self.customer.id ) self.assertEqual(self.customer.get_stripe_dashboard_url(), expected_url) self.customer.livemode = True expected_url = "https://dashboard.stripe.com/customers/{}".format( self.customer.id ) self.assertEqual(self.customer.get_stripe_dashboard_url(), expected_url) unsaved_customer = Customer() self.assertEqual(unsaved_customer.get_stripe_dashboard_url(), "") def test_customer_sync_unsupported_source(self): fake_customer = deepcopy(FAKE_CUSTOMER_II) fake_customer["default_source"]["object"] = fake_customer["sources"]["data"][0][ "object" ] = "fish" user = get_user_model().objects.create_user( username="test_user_sync_unsupported_source" ) synced_customer = fake_customer.create_for_user(user) self.assertEqual(0, synced_customer.legacy_cards.count()) self.assertEqual(0, synced_customer.sources.count()) self.assertEqual( synced_customer.default_source, DjstripePaymentMethod.objects.get(id=fake_customer["default_source"]["id"]), ) def test_customer_sync_has_subscriber_metadata(self): user = get_user_model().objects.create(username="test_metadata", id=12345) fake_customer = deepcopy(FAKE_CUSTOMER) fake_customer["id"] = "cus_sync_has_subscriber_metadata" fake_customer["metadata"] = {"djstripe_subscriber": "12345"} customer = Customer.sync_from_stripe_data(fake_customer) self.assertEqual(customer.subscriber, user) self.assertEqual(customer.metadata, {"djstripe_subscriber": "12345"}) def test_customer_sync_has_subscriber_metadata_disabled(self): user = get_user_model().objects.create( username="test_metadata_disabled", id=98765 ) fake_customer = deepcopy(FAKE_CUSTOMER) fake_customer["id"] = "cus_test_metadata_disabled" fake_customer["metadata"] = {"djstripe_subscriber": "98765"} with patch( "djstripe.settings.SUBSCRIBER_CUSTOMER_KEY", return_value="", autospec=True ): customer = Customer.sync_from_stripe_data(fake_customer) self.assertNotEqual(customer.subscriber, user) self.assertNotEqual(customer.subscriber_id, 98765) self.assert_fks( customer, expected_blank_fks={ "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.Customer.subscriber", }, ) def test_customer_sync_has_bad_subscriber_metadata(self): fake_customer = deepcopy(FAKE_CUSTOMER) fake_customer["id"] = "cus_sync_has_bad_subscriber_metadata" fake_customer["metadata"] = {"djstripe_subscriber": "does_not_exist"} customer = Customer.sync_from_stripe_data(fake_customer) self.assertEqual(customer.subscriber, None) self.assertEqual(customer.metadata, {"djstripe_subscriber": "does_not_exist"}) self.assert_fks( customer, expected_blank_fks={ "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.Customer.subscriber", }, ) @patch("stripe.Customer.create", autospec=True) def test_customer_create_metadata_disabled(self, customer_mock): user = get_user_model().objects.create_user( username="test_user_create_metadata_disabled" ) fake_customer = deepcopy(FAKE_CUSTOMER) fake_customer["id"] = "cus_test_create_metadata_disabled" customer_mock.return_value = fake_customer djstripe_settings.SUBSCRIBER_CUSTOMER_KEY = "" customer = Customer.create(user) djstripe_settings.SUBSCRIBER_CUSTOMER_KEY = "djstripe_subscriber" customer_mock.assert_called_once_with( api_key=STRIPE_SECRET_KEY, email="", idempotency_key=None, metadata={}, stripe_account=None, ) self.assertEqual(customer.metadata, None) self.assert_fks( customer, expected_blank_fks={ "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.Customer.default_source", }, ) @patch( "stripe.Card.retrieve", return_value=FAKE_CUSTOMER_II["default_source"], autospec=True, ) def test_customer_sync_non_local_card(self, card_retrieve_mock): fake_customer = deepcopy(FAKE_CUSTOMER_II) fake_customer["id"] = fake_customer["sources"]["data"][0][ "customer" ] = "cus_test_sync_non_local_card" user = get_user_model().objects.create_user( username="test_user_sync_non_local_card" ) customer = fake_customer.create_for_user(user) self.assertEqual(customer.sources.count(), 0) self.assertEqual(customer.legacy_cards.count(), 1) self.assertEqual( customer.default_source.id, fake_customer["default_source"]["id"] ) @patch( "stripe.BankAccount.retrieve", return_value=FAKE_CUSTOMER_IV["default_source"], autospec=True, ) def test_customer_sync_bank_account_source(self, bank_account_retrieve_mock): fake_customer = deepcopy(FAKE_CUSTOMER_IV) user = get_user_model().objects.create_user( username="test_user_sync_bank_account_source" ) customer = fake_customer.create_for_user(user) self.assertEqual(customer.sources.count(), 0) self.assertEqual(customer.legacy_cards.count(), 0) self.assertEqual(customer.bank_account.count(), 1) self.assertEqual( customer.default_source.id, fake_customer["default_source"]["id"] ) self.assert_fks( customer, expected_blank_fks={ "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", }, ) @patch("stripe.Customer.create", autospec=True) def test_customer_sync_no_sources(self, customer_mock): fake_customer = deepcopy(FAKE_CUSTOMER) fake_customer["id"] = "cus_test_sync_no_sources" fake_customer["default_source"] = None fake_customer["sources"] = None customer_mock.return_value = fake_customer user = get_user_model().objects.create_user( username="test_user_sync_non_local_card" ) customer = Customer.create(user) self.assertEqual( customer_mock.call_args_list[0][1].get("metadata"), {"djstripe_subscriber": user.pk}, ) self.assertEqual(customer.sources.count(), 0) self.assertEqual(customer.legacy_cards.count(), 0) self.assertEqual(customer.default_source, None) self.assert_fks( customer, expected_blank_fks={ "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.Customer.default_source", }, ) def test_customer_sync_default_source_string(self): Customer.objects.all().delete() Card.objects.all().delete() customer_fake = deepcopy(FAKE_CUSTOMER) customer_fake["default_source"] = customer_fake["sources"]["data"][0][ "id" ] = "card_sync_source_string" customer = Customer.sync_from_stripe_data(customer_fake) self.assertEqual(customer.default_source.id, customer_fake["default_source"]) self.assertEqual(customer.legacy_cards.count(), 2) self.assertEqual(len(list(customer.customer_payment_methods)), 2) self.assert_fks( customer, expected_blank_fks={ "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.Customer.subscriber", }, ) @patch("stripe.Customer.retrieve", autospec=True) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_PAYMENT_METHOD_I) ) def test_customer_sync_default_payment_method_string( self, attach_mock, customer_retrieve_mock ): Customer.objects.all().delete() PaymentMethod.objects.all().delete() customer_fake = deepcopy(FAKE_CUSTOMER) customer_fake["invoice_settings"][ "default_payment_method" ] = FAKE_PAYMENT_METHOD_I["id"] customer_retrieve_mock.return_value = customer_fake customer = Customer.sync_from_stripe_data(customer_fake) self.assertEqual( customer.default_payment_method.id, customer_fake["invoice_settings"]["default_payment_method"], ) self.assertEqual(customer.payment_methods.count(), 1) self.assert_fks( customer, expected_blank_fks={ "djstripe.Customer.coupon", "djstripe.Customer.subscriber", }, ) @patch("stripe.Customer.retrieve", autospec=True) def test_customer_purge_leaves_customer_record(self, customer_retrieve_fake): self.customer.purge() customer = Customer.objects.get(id=self.customer.id) self.assertTrue(customer.subscriber is None) self.assertTrue(customer.default_source is None) self.assertTrue(not customer.legacy_cards.all()) self.assertTrue(not customer.sources.all()) self.assertTrue(get_user_model().objects.filter(pk=self.user.pk).exists()) @patch("stripe.Customer.create", autospec=True) def test_customer_purge_detaches_sources(self, customer_api_create_fake): fake_customer = deepcopy(FAKE_CUSTOMER_III) customer_api_create_fake.return_value = fake_customer user = get_user_model().objects.create_user( username="blah", email=FAKE_CUSTOMER_III["email"] ) Customer.get_or_create(user) customer = Customer.sync_from_stripe_data(deepcopy(FAKE_CUSTOMER_III)) self.assertIsNotNone(customer.default_source) self.assertNotEqual(customer.sources.count(), 0) with patch("stripe.Customer.retrieve", autospec=True), patch( "stripe.Source.retrieve", return_value=deepcopy(FAKE_SOURCE), autospec=True ): customer.purge() self.assertIsNone(customer.default_source) self.assertEqual(customer.sources.count(), 0) @patch( "stripe.Customer.create", return_value=deepcopy(FAKE_CUSTOMER_II), autospec=True ) def test_customer_purge_deletes_idempotency_key(self, customer_api_create_fake): # We need to call Customer.get_or_create (which setUp doesn't) # to get an idempotency key user = get_user_model().objects.create_user( username="blah", email=FAKE_CUSTOMER_II["email"] ) idempotency_key_action = "customer:create:{}".format(user.pk) self.assertFalse( IdempotencyKey.objects.filter(action=idempotency_key_action).exists() ) customer, created = Customer.get_or_create(user) self.assertTrue( IdempotencyKey.objects.filter(action=idempotency_key_action).exists() ) with patch("stripe.Customer.retrieve", autospec=True): customer.purge() self.assertFalse( IdempotencyKey.objects.filter(action=idempotency_key_action).exists() ) @patch("stripe.Customer.retrieve", autospec=True) def test_customer_delete_same_as_purge(self, customer_retrieve_fake): self.customer.delete() customer = Customer.objects.get(id=self.customer.id) self.assertTrue(customer.subscriber is None) self.assertTrue(customer.default_source is None) self.assertTrue(not customer.legacy_cards.all()) self.assertTrue(not customer.sources.all()) self.assertTrue(get_user_model().objects.filter(pk=self.user.pk).exists()) @patch("stripe.Customer.retrieve", autospec=True) def test_customer_purge_raises_customer_exception(self, customer_retrieve_mock): customer_retrieve_mock.side_effect = InvalidRequestError( "No such customer:", "blah" ) self.customer.purge() customer = Customer.objects.get(id=self.customer.id) self.assertTrue(customer.subscriber is None) self.assertTrue(customer.default_source is None) self.assertTrue(not customer.legacy_cards.all()) self.assertTrue(not customer.sources.all()) self.assertTrue(get_user_model().objects.filter(pk=self.user.pk).exists()) customer_retrieve_mock.assert_called_with( id=self.customer.id, api_key=STRIPE_SECRET_KEY, expand=ANY, stripe_account=None, ) self.assertEqual(3, customer_retrieve_mock.call_count) @patch("stripe.Customer.retrieve", autospec=True) def test_customer_delete_raises_unexpected_exception(self, customer_retrieve_mock): customer_retrieve_mock.side_effect = InvalidRequestError( "Unexpected Exception", "blah" ) with self.assertRaisesMessage(InvalidRequestError, "Unexpected Exception"): self.customer.purge() customer_retrieve_mock.assert_called_once_with( id=self.customer.id, api_key=STRIPE_SECRET_KEY, expand=ANY, stripe_account=None, ) def test_can_charge(self): self.assertTrue(self.customer.can_charge()) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_add_card_set_default_true(self, customer_retrieve_mock): self.customer.add_card(FAKE_CARD["id"]) self.customer.add_card(FAKE_CARD_V["id"]) self.assertEqual(2, Card.objects.count()) self.assertEqual(FAKE_CARD_V["id"], self.customer.default_source.id) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_add_card_set_default_false(self, customer_retrieve_mock): self.customer.add_card(FAKE_CARD["id"], set_default=False) self.customer.add_card(FAKE_CARD_V["id"], set_default=False) self.assertEqual(2, Card.objects.count()) self.assertEqual(FAKE_CARD["id"], self.customer.default_source.id) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_add_card_set_default_false_with_single_card_still_becomes_default( self, customer_retrieve_mock ): self.customer.add_card(FAKE_CARD["id"], set_default=False) self.assertEqual(2, Card.objects.count()) self.assertEqual(FAKE_CARD["id"], self.customer.default_source.id) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch("stripe.PaymentMethod.attach", return_value=deepcopy(FAKE_PAYMENT_METHOD_I)) def test_add_payment_method_obj(self, attach_mock, customer_retrieve_mock): self.assertEqual( self.customer.payment_methods.filter( id=FAKE_PAYMENT_METHOD_I["id"] ).count(), 0, ) payment_method = PaymentMethod.sync_from_stripe_data(FAKE_PAYMENT_METHOD_I) payment_method = self.customer.add_payment_method(payment_method) self.assertEqual(payment_method.customer.id, self.customer.id) self.assertEqual( self.customer.payment_methods.filter( id=FAKE_PAYMENT_METHOD_I["id"] ).count(), 1, ) self.assertEqual( self.customer.payment_methods.filter( id=FAKE_PAYMENT_METHOD_I["id"] ).first(), self.customer.default_payment_method, ) self.assertEqual( self.customer.default_payment_method.id, self.customer.invoice_settings["default_payment_method"], ) self.assert_fks(self.customer, expected_blank_fks={"djstripe.Customer.coupon"}) @patch("stripe.Customer.retrieve", autospec=True) @patch("stripe.PaymentMethod.attach", return_value=deepcopy(FAKE_PAYMENT_METHOD_I)) def test_add_payment_method_set_default_true( self, attach_mock, customer_retrieve_mock ): # clear default source so we can check can_charge() fake_customer = deepcopy(FAKE_CUSTOMER) fake_customer["default_source"] = None customer_retrieve_mock.return_value = fake_customer self.customer.default_source = None self.customer.save() self.assertEqual( self.customer.payment_methods.filter( id=FAKE_PAYMENT_METHOD_I["id"] ).count(), 0, ) payment_method = self.customer.add_payment_method(FAKE_PAYMENT_METHOD_I["id"]) self.assertEqual(payment_method.customer.id, self.customer.id) self.assertEqual( self.customer.payment_methods.filter( id=FAKE_PAYMENT_METHOD_I["id"] ).count(), 1, ) self.assertEqual( self.customer.payment_methods.filter( id=FAKE_PAYMENT_METHOD_I["id"] ).first(), self.customer.default_payment_method, ) self.assertEqual( self.customer.default_payment_method.id, self.customer.invoice_settings["default_payment_method"], ) self.assertTrue( self.customer.can_charge(), "Expect to be able to charge since we've set a default_payment_method", ) self.assert_fks( self.customer, expected_blank_fks={ "djstripe.Customer.coupon", "djstripe.Customer.default_source", }, ) @patch("stripe.Customer.retrieve", autospec=True) @patch("stripe.PaymentMethod.attach", return_value=deepcopy(FAKE_PAYMENT_METHOD_I)) def test_add_payment_method_set_default_false( self, attach_mock, customer_retrieve_mock ): # clear default source so we can check can_charge() fake_customer = deepcopy(FAKE_CUSTOMER) fake_customer["default_source"] = None customer_retrieve_mock.return_value = fake_customer self.customer.default_source = None self.customer.save() self.assertEqual( self.customer.payment_methods.filter( id=FAKE_PAYMENT_METHOD_I["id"] ).count(), 0, ) payment_method = self.customer.add_payment_method( FAKE_PAYMENT_METHOD_I["id"], set_default=False ) self.assertEqual(payment_method.customer.id, self.customer.id) self.assertEqual( self.customer.payment_methods.filter( id=FAKE_PAYMENT_METHOD_I["id"] ).count(), 1, ) self.assertFalse( self.customer.can_charge(), "Expect not to be able to charge since we've not set a " "default_payment_method", ) self.assert_fks( self.customer, expected_blank_fks={ "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.Customer.default_source", }, ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_cannot_charge(self, customer_retrieve_fake): self.customer.delete() self.assertFalse(self.customer.can_charge()) def test_charge_accepts_only_decimals(self): with self.assertRaises(ValueError): self.customer.charge(10) @patch("stripe.Coupon.retrieve", return_value=deepcopy(FAKE_COUPON), autospec=True) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_add_coupon_by_id(self, customer_retrieve_mock, coupon_retrieve_mock): self.assertEqual(self.customer.coupon, None) self.customer.add_coupon(FAKE_COUPON["id"]) customer_retrieve_mock.assert_called_once_with( api_key=STRIPE_SECRET_KEY, expand=ANY, id=FAKE_CUSTOMER["id"], stripe_account=None, ) @patch("stripe.Coupon.retrieve", return_value=deepcopy(FAKE_COUPON), autospec=True) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_add_coupon_by_object(self, customer_retrieve_mock, coupon_retrieve_mock): self.assertEqual(self.customer.coupon, None) coupon = Coupon.sync_from_stripe_data(FAKE_COUPON) fake_discount = deepcopy(FAKE_DISCOUNT_CUSTOMER) def fake_customer_save(self, *args, **kwargs): # fake the api coupon update behaviour coupon = self.pop("coupon", None) if coupon: self["discount"] = fake_discount else: self["discount"] = None return self with patch("tests.CustomerDict.save", new=fake_customer_save): self.customer.add_coupon(coupon) customer_retrieve_mock.assert_called_once_with( api_key=STRIPE_SECRET_KEY, expand=ANY, id=FAKE_CUSTOMER["id"], stripe_account=None, ) self.customer.refresh_from_db() self.assert_fks( self.customer, expected_blank_fks={"djstripe.Customer.default_payment_method"}, ) @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.BalanceTransaction.retrieve", return_value=deepcopy(FAKE_BALANCE_TRANSACTION), autospec=True, ) @patch("stripe.Charge.retrieve", autospec=True) @patch("stripe.PaymentIntent.retrieve", autospec=True) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_CARD_AS_PAYMENT_METHOD), autospec=True, ) def test_refund_charge( self, paymentmethod_card_retrieve_mock, payment_intent_retrieve_mock, charge_retrieve_mock, balance_transaction_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account fake_charge_no_invoice = deepcopy(FAKE_CHARGE) fake_charge_no_invoice.update({"invoice": None}) charge_retrieve_mock.return_value = fake_charge_no_invoice fake_payment_intent = deepcopy(FAKE_PAYMENT_INTENT_I) fake_payment_intent.update({"invoice": None}) payment_intent_retrieve_mock.return_value = fake_payment_intent charge, created = Charge._get_or_create_from_stripe_object( fake_charge_no_invoice ) self.assertTrue(created) self.assert_fks( charge, expected_blank_fks={ "djstripe.Account.branding_logo", "djstripe.Account.branding_icon", "djstripe.Charge.application_fee", "djstripe.Charge.dispute", "djstripe.Charge.latest_invoice (related name)", "djstripe.Charge.latest_upcominginvoice (related name)", "djstripe.Charge.invoice", "djstripe.Charge.on_behalf_of", "djstripe.Charge.source_transfer", "djstripe.Charge.transfer", "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.PaymentIntent.invoice (related name)", "djstripe.PaymentIntent.on_behalf_of", "djstripe.PaymentIntent.payment_method", "djstripe.PaymentIntent.upcominginvoice (related name)", }, ) charge.refund() refunded_charge, created2 = Charge._get_or_create_from_stripe_object( fake_charge_no_invoice ) self.assertFalse(created2) self.assertEqual(refunded_charge.refunded, True) self.assertEqual(refunded_charge.amount_refunded, decimal.Decimal("20.00")) self.assert_fks( refunded_charge, expected_blank_fks={ "djstripe.Account.branding_logo", "djstripe.Account.branding_icon", "djstripe.Charge.application_fee", "djstripe.Charge.dispute", "djstripe.Charge.latest_invoice (related name)", "djstripe.Charge.latest_upcominginvoice (related name)", "djstripe.Charge.invoice", "djstripe.Charge.on_behalf_of", "djstripe.Charge.source_transfer", "djstripe.Charge.transfer", "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.PaymentIntent.invoice (related name)", "djstripe.PaymentIntent.on_behalf_of", "djstripe.PaymentIntent.payment_method", "djstripe.PaymentIntent.upcominginvoice (related name)", }, ) @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.BalanceTransaction.retrieve", return_value=deepcopy(FAKE_BALANCE_TRANSACTION), autospec=True, ) @patch("stripe.Charge.retrieve", autospec=True) @patch("stripe.PaymentIntent.retrieve", autospec=True) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_CARD_AS_PAYMENT_METHOD), autospec=True, ) def test_refund_charge_object_returned( self, paymentmethod_card_retrieve_mock, payment_intent_retrieve_mock, charge_retrieve_mock, balance_transaction_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account fake_charge_no_invoice = deepcopy(FAKE_CHARGE) fake_charge_no_invoice.update({"invoice": None}) charge_retrieve_mock.return_value = fake_charge_no_invoice fake_payment_intent = deepcopy(FAKE_PAYMENT_INTENT_I) fake_payment_intent.update({"invoice": None}) payment_intent_retrieve_mock.return_value = fake_payment_intent charge, created = Charge._get_or_create_from_stripe_object( fake_charge_no_invoice ) self.assertTrue(created) self.assert_fks( charge, expected_blank_fks={ "djstripe.Account.branding_logo", "djstripe.Account.branding_icon", "djstripe.Charge.application_fee", "djstripe.Charge.dispute", "djstripe.Charge.latest_invoice (related name)", "djstripe.Charge.latest_upcominginvoice (related name)", "djstripe.Charge.invoice", "djstripe.Charge.on_behalf_of", "djstripe.Charge.source_transfer", "djstripe.Charge.transfer", "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.PaymentIntent.invoice (related name)", "djstripe.PaymentIntent.on_behalf_of", "djstripe.PaymentIntent.payment_method", "djstripe.PaymentIntent.upcominginvoice (related name)", }, ) refunded_charge = charge.refund() self.assertEqual(refunded_charge.refunded, True) self.assertEqual(refunded_charge.amount_refunded, decimal.Decimal("20.00")) self.assert_fks( refunded_charge, expected_blank_fks={ "djstripe.Account.branding_logo", "djstripe.Account.branding_icon", "djstripe.Charge.application_fee", "djstripe.Charge.dispute", "djstripe.Charge.latest_invoice (related name)", "djstripe.Charge.latest_upcominginvoice (related name)", "djstripe.Charge.invoice", "djstripe.Charge.on_behalf_of", "djstripe.Charge.source_transfer", "djstripe.Charge.transfer", "djstripe.Customer.coupon", "djstripe.Customer.default_payment_method", "djstripe.PaymentIntent.invoice (related name)", "djstripe.PaymentIntent.on_behalf_of", "djstripe.PaymentIntent.payment_method", "djstripe.PaymentIntent.upcominginvoice (related name)", }, ) def test_calculate_refund_amount_partial_refund(self): charge = Charge( id="ch_111111", customer=self.customer, amount=decimal.Decimal("500.00") ) self.assertEqual( charge._calculate_refund_amount(amount=decimal.Decimal("300.00")), 30000 ) def test_calculate_refund_above_max_refund(self): charge = Charge( id="ch_111111", customer=self.customer, amount=decimal.Decimal("500.00") ) self.assertEqual( charge._calculate_refund_amount(amount=decimal.Decimal("600.00")), 50000 ) @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.BalanceTransaction.retrieve", return_value=deepcopy(FAKE_BALANCE_TRANSACTION), autospec=True, ) @patch("stripe.Charge.retrieve", autospec=True) @patch("stripe.Charge.create", autospec=True) @patch("stripe.PaymentIntent.retrieve", autospec=True) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_CARD_AS_PAYMENT_METHOD), autospec=True, ) def test_charge_converts_dollars_into_cents( self, paymentmethod_card_retrieve_mock, payment_intent_retrieve_mock, charge_create_mock, charge_retrieve_mock, balance_transaction_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account fake_charge_copy = deepcopy(FAKE_CHARGE) fake_charge_copy.update({"invoice": None, "amount": 1000}) charge_create_mock.return_value = fake_charge_copy charge_retrieve_mock.return_value = fake_charge_copy fake_payment_intent = deepcopy(FAKE_PAYMENT_INTENT_I) fake_payment_intent.update({"invoice": None}) payment_intent_retrieve_mock.return_value = fake_payment_intent self.customer.charge(amount=decimal.Decimal("10.00")) _, kwargs = charge_create_mock.call_args self.assertEqual(kwargs["amount"], 1000) @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.BalanceTransaction.retrieve", return_value=deepcopy(FAKE_BALANCE_TRANSACTION), autospec=True, ) @patch("stripe.Charge.retrieve", autospec=True) @patch("stripe.Charge.create", autospec=True) @patch( "stripe.PaymentIntent.retrieve", return_value=deepcopy(FAKE_PAYMENT_INTENT_I), autospec=True, ) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_CARD_AS_PAYMENT_METHOD), autospec=True, ) @patch("stripe.Invoice.retrieve", autospec=True) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) @patch( "stripe.Subscription.retrieve", return_value=deepcopy(FAKE_SUBSCRIPTION), autospec=True, ) def test_charge_doesnt_require_invoice( self, subscription_retrieve_mock, product_retrieve_mock, invoice_retrieve_mock, paymentmethod_card_retrieve_mock, payment_intent_retrieve_mock, charge_create_mock, charge_retrieve_mock, balance_transaction_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account fake_charge_copy = deepcopy(FAKE_CHARGE) fake_charge_copy.update( {"invoice": FAKE_INVOICE["id"], "amount": FAKE_INVOICE["amount_due"]} ) fake_invoice_copy = deepcopy(FAKE_INVOICE) charge_create_mock.return_value = fake_charge_copy charge_retrieve_mock.return_value = fake_charge_copy invoice_retrieve_mock.return_value = fake_invoice_copy try: self.customer.charge(amount=decimal.Decimal("20.00")) except Invoice.DoesNotExist: self.fail(msg="Stripe Charge shouldn't throw Invoice DoesNotExist.") @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.BalanceTransaction.retrieve", return_value=deepcopy(FAKE_BALANCE_TRANSACTION), autospec=True, ) @patch("stripe.Charge.retrieve", autospec=True) @patch("stripe.Charge.create", autospec=True) @patch("stripe.PaymentIntent.retrieve", autospec=True) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_CARD_AS_PAYMENT_METHOD), autospec=True, ) def test_charge_passes_extra_arguments( self, paymentmethod_card_retrieve_mock, payment_intent_retrieve_mock, charge_create_mock, charge_retrieve_mock, balance_transaction_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account fake_charge_copy = deepcopy(FAKE_CHARGE) fake_charge_copy.update({"invoice": None}) charge_create_mock.return_value = fake_charge_copy charge_retrieve_mock.return_value = fake_charge_copy fake_payment_intent = deepcopy(FAKE_PAYMENT_INTENT_I) fake_payment_intent.update({"invoice": None}) payment_intent_retrieve_mock.return_value = fake_payment_intent self.customer.charge( amount=decimal.Decimal("10.00"), capture=True, destination=FAKE_ACCOUNT["id"], ) _, kwargs = charge_create_mock.call_args self.assertEqual(kwargs["capture"], True) self.assertEqual(kwargs["destination"], FAKE_ACCOUNT["id"]) @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.BalanceTransaction.retrieve", return_value=deepcopy(FAKE_BALANCE_TRANSACTION), autospec=True, ) @patch("stripe.Charge.retrieve", autospec=True) @patch("stripe.Charge.create", autospec=True) @patch("stripe.PaymentIntent.retrieve", autospec=True) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_CARD_AS_PAYMENT_METHOD), autospec=True, ) def test_charge_string_source( self, paymentmethod_card_retrieve_mock, payment_intent_retrieve_mock, charge_create_mock, charge_retrieve_mock, balance_transaction_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account fake_charge_copy = deepcopy(FAKE_CHARGE) fake_charge_copy.update({"invoice": None}) charge_create_mock.return_value = fake_charge_copy charge_retrieve_mock.return_value = fake_charge_copy fake_payment_intent = deepcopy(FAKE_PAYMENT_INTENT_I) fake_payment_intent.update({"invoice": None}) payment_intent_retrieve_mock.return_value = fake_payment_intent self.customer.charge(amount=decimal.Decimal("10.00"), source=self.card.id) @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.BalanceTransaction.retrieve", return_value=deepcopy(FAKE_BALANCE_TRANSACTION), autospec=True, ) @patch("stripe.Charge.retrieve", autospec=True) @patch("stripe.Charge.create", autospec=True) @patch("stripe.PaymentIntent.retrieve", autospec=True) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_CARD_AS_PAYMENT_METHOD), autospec=True, ) def test_charge_card_source( self, paymentmethod_card_retrieve_mock, payment_intent_retrieve_mock, charge_create_mock, charge_retrieve_mock, balance_transaction_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account fake_charge_copy = deepcopy(FAKE_CHARGE) fake_charge_copy.update({"invoice": None}) charge_create_mock.return_value = fake_charge_copy charge_retrieve_mock.return_value = fake_charge_copy fake_payment_intent = deepcopy(FAKE_PAYMENT_INTENT_I) fake_payment_intent.update({"invoice": None}) payment_intent_retrieve_mock.return_value = fake_payment_intent self.customer.charge(amount=decimal.Decimal("10.00"), source=self.card) @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.BalanceTransaction.retrieve", return_value=deepcopy(FAKE_BALANCE_TRANSACTION), autospec=True, ) @patch( "stripe.Subscription.retrieve", return_value=deepcopy(FAKE_SUBSCRIPTION), autospec=True, ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch("stripe.Charge.retrieve", return_value=deepcopy(FAKE_CHARGE), autospec=True) @patch( "stripe.PaymentIntent.retrieve", return_value=deepcopy(FAKE_PAYMENT_INTENT_I), autospec=True, ) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_CARD_AS_PAYMENT_METHOD), autospec=True, ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) @patch( "stripe.Invoice.list", return_value=StripeList( data=[deepcopy(FAKE_INVOICE), deepcopy(FAKE_INVOICE_III)] ), autospec=True, ) @patch("djstripe.models.Invoice.retry", autospec=True) def test_retry_unpaid_invoices( self, invoice_retry_mock, invoice_list_mock, product_retrieve_mock, paymentmethod_card_retrieve_mock, payment_intent_retrieve_mock, charge_retrieve_mock, customer_retrieve_mock, subscription_retrieve_mock, balance_transaction_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account self.customer.retry_unpaid_invoices() invoice = Invoice.objects.get(id=FAKE_INVOICE_III["id"]) invoice_retry_mock.assert_called_once_with(invoice) @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.BalanceTransaction.retrieve", return_value=deepcopy(FAKE_BALANCE_TRANSACTION), autospec=True, ) @patch( "stripe.Subscription.retrieve", return_value=deepcopy(FAKE_SUBSCRIPTION), autospec=True, ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch("stripe.Charge.retrieve", return_value=deepcopy(FAKE_CHARGE), autospec=True) @patch( "stripe.PaymentIntent.retrieve", return_value=deepcopy(FAKE_PAYMENT_INTENT_I), autospec=True, ) @patch( "stripe.PaymentMethod.retrieve", return_value=deepcopy(FAKE_CARD_AS_PAYMENT_METHOD), autospec=True, ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) @patch( "stripe.Invoice.list", return_value=StripeList(data=[deepcopy(FAKE_INVOICE)]), autospec=True, ) @patch("djstripe.models.Invoice.retry", autospec=True) def test_retry_unpaid_invoices_none_unpaid( self, invoice_retry_mock, invoice_list_mock, product_retrieve_mock, paymentmethod_card_retrieve_mock, payment_intent_retrieve_mock, charge_retrieve_mock, customer_retrieve_mock, subscription_retrieve_mock, balance_transaction_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account self.customer.retry_unpaid_invoices() self.assertFalse(invoice_retry_mock.called) @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.Subscription.retrieve", return_value=deepcopy(FAKE_SUBSCRIPTION), autospec=True, ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch("stripe.Charge.retrieve", return_value=deepcopy(FAKE_CHARGE), autospec=True) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) @patch( "stripe.Invoice.list", return_value=StripeList(data=[deepcopy(FAKE_INVOICE_III)]), ) @patch("djstripe.models.Invoice.retry", autospec=True) def test_retry_unpaid_invoices_expected_exception( self, invoice_retry_mock, invoice_list_mock, product_retrieve_mock, charge_retrieve_mock, customer_retrieve_mock, subscription_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account invoice_retry_mock.side_effect = InvalidRequestError( "Invoice is already paid", "blah" ) try: self.customer.retry_unpaid_invoices() except Exception: self.fail("Exception was unexpectedly raised.") @patch( "djstripe.models.Account.get_default_account", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.Subscription.retrieve", return_value=deepcopy(FAKE_SUBSCRIPTION), autospec=True, ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch("stripe.Charge.retrieve", return_value=deepcopy(FAKE_CHARGE), autospec=True) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) @patch( "stripe.Invoice.list", return_value=StripeList(data=[deepcopy(FAKE_INVOICE_III)]), ) @patch("djstripe.models.Invoice.retry", autospec=True) def test_retry_unpaid_invoices_unexpected_exception( self, invoice_retry_mock, invoice_list_mock, product_retrieve_mock, charge_retrieve_mock, customer_retrieve_mock, subscription_retrieve_mock, default_account_mock, ): default_account_mock.return_value = self.account invoice_retry_mock.side_effect = InvalidRequestError( "This should fail!", "blah" ) with self.assertRaisesMessage(InvalidRequestError, "This should fail!"): self.customer.retry_unpaid_invoices() @patch("stripe.Invoice.create", autospec=True) def test_send_invoice_success(self, invoice_create_mock): return_status = self.customer.send_invoice() self.assertTrue(return_status) invoice_create_mock.assert_called_once_with( api_key=STRIPE_SECRET_KEY, customer=self.customer.id ) @patch("stripe.Invoice.create", autospec=True) def test_send_invoice_failure(self, invoice_create_mock): invoice_create_mock.side_effect = InvalidRequestError( "Invoice creation failed.", "blah" ) return_status = self.customer.send_invoice() self.assertFalse(return_status) invoice_create_mock.assert_called_once_with( api_key=STRIPE_SECRET_KEY, customer=self.customer.id ) @patch("stripe.Coupon.retrieve", return_value=deepcopy(FAKE_COUPON), autospec=True) def test_sync_customer_with_discount(self, coupon_retrieve_mock): self.assertIsNone(self.customer.coupon) fake_customer = deepcopy(FAKE_CUSTOMER) fake_customer["discount"] = deepcopy(FAKE_DISCOUNT_CUSTOMER) customer = Customer.sync_from_stripe_data(fake_customer) self.assertEqual(customer.coupon.id, FAKE_COUPON["id"]) self.assertIsNotNone(customer.coupon_start) self.assertIsNone(customer.coupon_end) @patch("stripe.Coupon.retrieve", return_value=deepcopy(FAKE_COUPON), autospec=True) def test_sync_customer_discount_already_present(self, coupon_retrieve_mock): fake_customer = deepcopy(FAKE_CUSTOMER) fake_customer["discount"] = deepcopy(FAKE_DISCOUNT_CUSTOMER) # Set the customer's coupon to be what we'll sync customer = Customer.objects.get(id=FAKE_CUSTOMER["id"]) customer.coupon = Coupon.sync_from_stripe_data(FAKE_COUPON) customer.save() customer = Customer.sync_from_stripe_data(fake_customer) self.assertEqual(customer.coupon.id, FAKE_COUPON["id"]) def test_sync_customer_delete_discount(self): test_coupon = Coupon.sync_from_stripe_data(FAKE_COUPON) self.customer.coupon = test_coupon self.customer.save() self.assertEqual(self.customer.coupon.id, FAKE_COUPON["id"]) customer = Customer.sync_from_stripe_data(FAKE_CUSTOMER) self.assertEqual(customer.coupon, None) @patch( "djstripe.models.Invoice.sync_from_stripe_data", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.Invoice.list", return_value=StripeList( data=[deepcopy(FAKE_INVOICE), deepcopy(FAKE_INVOICE_III)] ), ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_sync_invoices( self, customer_retrieve_mock, invoice_list_mock, invoice_sync_mock ): self.customer._sync_invoices() self.assertEqual(2, invoice_sync_mock.call_count) @patch( "djstripe.models.Invoice.sync_from_stripe_data", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch("stripe.Invoice.list", return_value=StripeList(data=[]), autospec=True) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_sync_invoices_none( self, customer_retrieve_mock, invoice_list_mock, invoice_sync_mock ): self.customer._sync_invoices() self.assertEqual(0, invoice_sync_mock.call_count) @patch( "djstripe.models.Charge.sync_from_stripe_data", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.Charge.list", return_value=StripeList(data=[deepcopy(FAKE_CHARGE)]), autospec=True, ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_sync_charges( self, customer_retrieve_mock, charge_list_mock, charge_sync_mock ): self.customer._sync_charges() self.assertEqual(1, charge_sync_mock.call_count) @patch( "djstripe.models.Charge.sync_from_stripe_data", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch("stripe.Charge.list", return_value=StripeList(data=[]), autospec=True) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_sync_charges_none( self, customer_retrieve_mock, charge_list_mock, charge_sync_mock ): self.customer._sync_charges() self.assertEqual(0, charge_sync_mock.call_count) @patch( "djstripe.models.Subscription.sync_from_stripe_data", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.Subscription.list", return_value=StripeList( data=[deepcopy(FAKE_SUBSCRIPTION), deepcopy(FAKE_SUBSCRIPTION_II)] ), ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_sync_subscriptions( self, customer_retrieve_mock, subscription_list_mock, subscription_sync_mock ): self.customer._sync_subscriptions() self.assertEqual(2, subscription_sync_mock.call_count) @patch( "djstripe.models.Subscription.sync_from_stripe_data", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch("stripe.Subscription.list", return_value=StripeList(data=[]), autospec=True) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) def test_sync_subscriptions_none( self, customer_retrieve_mock, subscription_list_mock, subscription_sync_mock ): self.customer._sync_subscriptions() self.assertEqual(0, subscription_sync_mock.call_count) @patch( "stripe.Subscription.create", return_value=deepcopy(FAKE_SUBSCRIPTION), autospec=True, ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) def test_subscribe_price_string( self, product_retrieve_mock, customer_retrieve_mock, subscription_create_mock, ): price = Price.sync_from_stripe_data(deepcopy(FAKE_PRICE)) self.assert_fks(price, expected_blank_fks={}) self.customer.subscribe(price=price.id) @patch("stripe.Subscription.create", autospec=True) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) def test_subscription_shortcut_with_multiple_subscriptions( self, product_retrieve_mock, customer_retrieve_mock, subscription_create_mock ): price = Price.sync_from_stripe_data(deepcopy(FAKE_PRICE)) self.assert_fks(price, expected_blank_fks={}) subscription_fake_duplicate = deepcopy(FAKE_SUBSCRIPTION) subscription_fake_duplicate["id"] = "sub_6lsC8pt7IcF8jd" subscription_create_mock.side_effect = [ deepcopy(FAKE_SUBSCRIPTION), subscription_fake_duplicate, ] self.customer.subscribe(price=price) self.customer.subscribe(price=price) self.assertEqual(2, self.customer.subscriptions.count()) self.assertEqual(2, len(self.customer.valid_subscriptions)) with self.assertRaises(MultipleSubscriptionException): self.customer.subscription @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) def test_subscription_shortcut_with_invalid_subscriptions( self, product_retrieve_mock, customer_retrieve_mock ): price = Price.sync_from_stripe_data(deepcopy(FAKE_PRICE)) self.assert_fks(price, expected_blank_fks={}) fake_subscriptions = [ deepcopy(FAKE_SUBSCRIPTION), deepcopy(FAKE_SUBSCRIPTION), deepcopy(FAKE_SUBSCRIPTION), ] # update the status of all but one to be invalid, # we need to also change the id for sync to work fake_subscriptions[1]["status"] = "canceled" fake_subscriptions[1]["id"] = fake_subscriptions[1]["id"] + "foo1" fake_subscriptions[2]["status"] = "incomplete_expired" fake_subscriptions[2]["id"] = fake_subscriptions[2]["id"] + "foo2" for fake_subscription in fake_subscriptions: with patch( "stripe.Subscription.create", autospec=True, side_effect=[fake_subscription], ): self.customer.subscribe(price=price) self.assertEqual(3, self.customer.subscriptions.count()) self.assertEqual(1, len(self.customer.valid_subscriptions)) self.assertEqual( self.customer.valid_subscriptions[0], self.customer.subscription ) self.assertEqual(fake_subscriptions[0]["id"], self.customer.subscription.id) @patch( "djstripe.models.InvoiceItem.sync_from_stripe_data", return_value="pancakes", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.InvoiceItem.create", return_value=deepcopy(FAKE_INVOICEITEM), autospec=True, ) def test_add_invoice_item(self, invoiceitem_create_mock, invoiceitem_sync_mock): invoiceitem = self.customer.add_invoice_item( amount=decimal.Decimal("50.00"), currency="eur", description="test", invoice=77, subscription=25, ) self.assertEqual("pancakes", invoiceitem) invoiceitem_create_mock.assert_called_once_with( api_key=STRIPE_SECRET_KEY, amount=5000, customer=self.customer.id, currency="eur", description="test", discountable=None, invoice=77, metadata=None, subscription=25, ) @patch( "djstripe.models.InvoiceItem.sync_from_stripe_data", return_value="pancakes", autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) @patch( "stripe.InvoiceItem.create", return_value=deepcopy(FAKE_INVOICEITEM), autospec=True, ) def test_add_invoice_item_djstripe_objects( self, invoiceitem_create_mock, invoiceitem_sync_mock ): invoiceitem = self.customer.add_invoice_item( amount=decimal.Decimal("50.00"), currency="eur", description="test", invoice=Invoice(id=77), subscription=Subscription(id=25), ) self.assertEqual("pancakes", invoiceitem) invoiceitem_create_mock.assert_called_once_with( api_key=STRIPE_SECRET_KEY, amount=5000, customer=self.customer.id, currency="eur", description="test", discountable=None, invoice=77, metadata=None, subscription=25, ) def test_add_invoice_item_bad_decimal(self): with self.assertRaisesMessage( ValueError, "You must supply a decimal value representing dollars." ): self.customer.add_invoice_item(amount=5000, currency="usd") @patch( "stripe.Plan.retrieve", return_value=deepcopy(FAKE_PLAN), autospec=True, ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True, ) @patch( "stripe.Subscription.retrieve", return_value=deepcopy(FAKE_SUBSCRIPTION), autospec=True, ) @patch( "stripe.Invoice.upcoming", return_value=deepcopy(FAKE_UPCOMING_INVOICE), autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) def test_upcoming_invoice_plan( self, invoice_upcoming_mock, subscription_retrieve_mock, product_retrieve_mock, plan_retrieve_mock, ): invoice = self.customer.upcoming_invoice() self.assertIsNotNone(invoice) self.assertIsNone(invoice.id) self.assertIsNone(invoice.save()) subscription_retrieve_mock.assert_called_once_with( api_key=ANY, expand=ANY, id=FAKE_SUBSCRIPTION["id"], stripe_account=None ) plan_retrieve_mock.assert_not_called() items = invoice.invoiceitems.all() self.assertEqual(1, len(items)) self.assertEqual(FAKE_SUBSCRIPTION["id"], items[0].id) self.assertIsNotNone(invoice.plan) self.assertEqual(FAKE_PLAN["id"], invoice.plan.id) invoice._invoiceitems = [] items = invoice.invoiceitems.all() self.assertEqual(0, len(items)) self.assertIsNotNone(invoice.plan) @patch("stripe.Customer.retrieve", autospec=True) def test_delete_subscriber_without_customer_is_noop(self, customer_retrieve_mock): self.user.delete() for customer in self.user.djstripe_customers.all(): self.assertIsNone(customer.date_purged) @patch("stripe.Subscription.create", autospec=True) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) def test_is_subscribed_to_with_product( self, product_retrieve_mock, customer_retrieve_mock, subscription_create_mock ): price = Price.sync_from_stripe_data(deepcopy(FAKE_PRICE)) product = Product.sync_from_stripe_data(deepcopy(FAKE_PRODUCT)) subscription_fake = deepcopy(FAKE_SUBSCRIPTION) subscription_fake["current_period_end"] = datetime_to_unix( timezone.now() + timezone.timedelta(days=7) ) subscription_create_mock.return_value = subscription_fake self.customer.subscribe(price=price) assert self.customer.is_subscribed_to(product) @patch("stripe.Subscription.create", autospec=True) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) def test_is_subscribed_to_with_product_string( self, product_retrieve_mock, customer_retrieve_mock, subscription_create_mock ): price = Price.sync_from_stripe_data(deepcopy(FAKE_PRICE)) product = Product.sync_from_stripe_data(deepcopy(FAKE_PRODUCT)) subscription_fake = deepcopy(FAKE_SUBSCRIPTION) subscription_fake["current_period_end"] = datetime_to_unix( timezone.now() + timezone.timedelta(days=7) ) subscription_create_mock.return_value = subscription_fake self.customer.subscribe(price=price) assert self.customer.is_subscribed_to(product.id) # These tests use Plan which is deprecated in favor of Price class TestCustomerLegacy(AssertStripeFksMixin, TestCase): def setUp(self): self.user = get_user_model().objects.create_user( username="pydanny", email="pydanny@gmail.com" ) self.customer = FAKE_CUSTOMER.create_for_user(self.user) self.payment_method, _ = DjstripePaymentMethod._get_or_create_source( FAKE_CARD, "card" ) self.card = self.payment_method.resolve() self.customer.default_source = self.payment_method self.customer.save() self.account = default_account() @patch( "stripe.Subscription.create", return_value=deepcopy(FAKE_SUBSCRIPTION), autospec=True, ) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) def test_subscribe_plan_string( self, product_retrieve_mock, customer_retrieve_mock, subscription_create_mock, ): plan = Plan.sync_from_stripe_data(deepcopy(FAKE_PLAN)) self.assert_fks(plan, expected_blank_fks={}) self.customer.subscribe(plan=plan.id) @patch("stripe.Subscription.create", autospec=True) @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) def test_subscription_shortcut_with_multiple_subscriptions( self, product_retrieve_mock, customer_retrieve_mock, subscription_create_mock ): plan = Plan.sync_from_stripe_data(deepcopy(FAKE_PLAN)) self.assert_fks(plan, expected_blank_fks={}) subscription_fake_duplicate = deepcopy(FAKE_SUBSCRIPTION) subscription_fake_duplicate["id"] = "sub_6lsC8pt7IcF8jd" subscription_create_mock.side_effect = [ deepcopy(FAKE_SUBSCRIPTION), subscription_fake_duplicate, ] self.customer.subscribe(plan=plan) self.customer.subscribe(plan=plan) self.assertEqual(2, self.customer.subscriptions.count()) self.assertEqual(2, len(self.customer.valid_subscriptions)) with self.assertRaises(MultipleSubscriptionException): self.customer.subscription @patch( "stripe.Customer.retrieve", return_value=deepcopy(FAKE_CUSTOMER), autospec=True ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True ) def test_subscription_shortcut_with_invalid_subscriptions( self, product_retrieve_mock, customer_retrieve_mock ): plan = Plan.sync_from_stripe_data(deepcopy(FAKE_PLAN)) self.assert_fks(plan, expected_blank_fks={}) fake_subscriptions = [ deepcopy(FAKE_SUBSCRIPTION), deepcopy(FAKE_SUBSCRIPTION), deepcopy(FAKE_SUBSCRIPTION), ] # update the status of all but one to be invalid, # we need to also change the id for sync to work fake_subscriptions[1]["status"] = "canceled" fake_subscriptions[1]["id"] = fake_subscriptions[1]["id"] + "foo1" fake_subscriptions[2]["status"] = "incomplete_expired" fake_subscriptions[2]["id"] = fake_subscriptions[2]["id"] + "foo2" for fake_subscription in fake_subscriptions: with patch( "stripe.Subscription.create", autospec=True, side_effect=[fake_subscription], ): self.customer.subscribe(plan=plan) self.assertEqual(3, self.customer.subscriptions.count()) self.assertEqual(1, len(self.customer.valid_subscriptions)) self.assertEqual( self.customer.valid_subscriptions[0], self.customer.subscription ) self.assertEqual(fake_subscriptions[0]["id"], self.customer.subscription.id) @patch( "stripe.Plan.retrieve", return_value=deepcopy(FAKE_PLAN), autospec=True, ) @patch( "stripe.Product.retrieve", return_value=deepcopy(FAKE_PRODUCT), autospec=True, ) @patch( "stripe.Subscription.retrieve", return_value=deepcopy(FAKE_SUBSCRIPTION), autospec=True, ) @patch( "stripe.Invoice.upcoming", return_value=deepcopy(FAKE_UPCOMING_INVOICE), autospec=IS_STATICMETHOD_AUTOSPEC_SUPPORTED, ) def test_upcoming_invoice( self, invoice_upcoming_mock, subscription_retrieve_mock, product_retrieve_mock, plan_retrieve_mock, ): invoice = self.customer.upcoming_invoice() self.assertIsNotNone(invoice) self.assertIsNone(invoice.id) self.assertIsNone(invoice.save()) subscription_retrieve_mock.assert_called_once_with( api_key=ANY, expand=ANY, id=FAKE_SUBSCRIPTION["id"], stripe_account=None ) plan_retrieve_mock.assert_not_called() items = invoice.invoiceitems.all() self.assertEqual(1, len(items)) self.assertEqual(FAKE_SUBSCRIPTION["id"], items[0].id) self.assertIsNotNone(invoice.plan) self.assertEqual(FAKE_PLAN["id"], invoice.plan.id) invoice._invoiceitems = [] items = invoice.invoiceitems.all() self.assertEqual(0, len(items)) self.assertIsNotNone(invoice.plan)

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py

Python

app/ivr/__init__.py

itworxs/suite

36a6f354a826862c50d5e5f218eafb6c14152295

[ "MIT" ]

890

2017-02-25T07:11:09.000Z

2022-03-08T05:49:20.000Z

app/ivr/__init__.py

itworxs/suite

36a6f354a826862c50d5e5f218eafb6c14152295

[ "MIT" ]

11

2017-02-25T18:07:11.000Z

2020-10-19T13:09:41.000Z

app/ivr/__init__.py

nfriedly/suite

c58c772d98d1476cad0531b8a296f27ad2ab945c

[ "MIT" ]

276

2017-02-25T09:01:23.000Z

2022-03-19T02:24:02.000Z

from flask import Blueprint ivr = Blueprint('ivr', __name__) from . import views

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d9fd90ce5b2c1adb1c3a0ca83e1fda1d159e60af

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py

Python

weaver/lib/warning.py

zhangcandrew/weaver

acfb1fc372205488dd3be09323909f5049648998

[ "MIT" ]

null

weaver/lib/warning.py

zhangcandrew/weaver

acfb1fc372205488dd3be09323909f5049648998

[ "MIT" ]

null

weaver/lib/warning.py

zhangcandrew/weaver

acfb1fc372205488dd3be09323909f5049648998

[ "MIT" ]

null

from builtins import object class Warning(object): def __init__(self, location, warning): self.location = location self.warning = warning def __str__(self): return "WARNING (%s): %s" % (self.location, self.warning)

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py

Python

magnum/tests/unit/api/test_validation.py

ISCAS-VDI/magnum-base

5bb88e12b3e5d665ae1b345b62023d1016217e08

[ "Apache-2.0" ]

null

magnum/tests/unit/api/test_validation.py

ISCAS-VDI/magnum-base

5bb88e12b3e5d665ae1b345b62023d1016217e08

[ "Apache-2.0" ]

null

magnum/tests/unit/api/test_validation.py

ISCAS-VDI/magnum-base

5bb88e12b3e5d665ae1b345b62023d1016217e08

[ "Apache-2.0" ]

1

2020-09-09T14:35:08.000Z

# Copyright 2015 Huawei Technologies Co.,LTD. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or # implied. # See the License for the specific language governing permissions and # limitations under the License. import mock from oslo_config import cfg from six.moves import reload_module from magnum.api import validation as v from magnum.common import exception from magnum import objects from magnum.tests import base from magnum.tests.unit.objects import utils as obj_utils class TestValidation(base.BaseTestCase): def _test_enforce_bay_types( self, mock_bay_get_by_uuid, mock_pecan_request, bay_type, allowed_bay_types, assert_raised=False, *args): @v.enforce_bay_types(*allowed_bay_types) def test(self, *args): if hasattr(args[0], 'bay_uuid'): return args[0].name else: return args[1] context = mock_pecan_request.context bay = mock.MagicMock() bay.baymodel_id = 'baymodel_id' baymodel = obj_utils.get_test_baymodel(context, uuid='baymodel_id', coe=bay_type) bay.baymodel = baymodel mock_bay_get_by_uuid.return_value = bay if assert_raised: self.assertRaises( exception.InvalidParameterValue, test, self, *args) else: ret = test(self, *args) if hasattr(args[0], 'bay_uuid'): mock_bay_get_by_uuid.assert_called_once_with(context, args[0].bay_uuid) self.assertEqual(args[0].name, ret) else: mock_bay_get_by_uuid.assert_called_once_with(context, args[1]) self.assertEqual(args[1], ret) @mock.patch('pecan.request') @mock.patch('magnum.objects.Bay.get_by_uuid') def test_enforce_bay_types_one_allowed( self, mock_bay_get_by_uuid, mock_pecan_request): obj = mock.MagicMock() obj.name = 'test_object' obj.bay_uuid = 'bay_uuid' bay_type = 'swarm' allowed_bay_types = ['swarm'] self._test_enforce_bay_types( mock_bay_get_by_uuid, mock_pecan_request, bay_type, allowed_bay_types, False, obj) @mock.patch('pecan.request') @mock.patch('magnum.objects.Bay.get_by_uuid') def test_enforce_bay_types_two_allowed( self, mock_bay_get_by_uuid, mock_pecan_request): obj = mock.MagicMock() obj.name = 'test_object' obj.bay_uuid = 'bay_uuid' bay_type = 'swarm' allowed_bay_types = ['swarm', 'mesos'] self._test_enforce_bay_types( mock_bay_get_by_uuid, mock_pecan_request, bay_type, allowed_bay_types, False, obj) @mock.patch('pecan.request') @mock.patch('magnum.objects.Bay.get_by_uuid') def test_enforce_bay_types_not_allowed( self, mock_bay_get_by_uuid, mock_pecan_request): obj = mock.MagicMock() obj.name = 'test_object' obj.bay_uuid = 'bay_uuid' bay_type = 'swarm' allowed_bay_types = ['mesos'] self._test_enforce_bay_types( mock_bay_get_by_uuid, mock_pecan_request, bay_type, allowed_bay_types, True, obj) @mock.patch('pecan.request') @mock.patch('magnum.objects.Bay.get_by_uuid') def test_enforce_bay_types_with_bay_uuid(self, mock_bay_get_by_uuid, mock_pecan_request): bay_ident = 'e74c40e0-d825-11e2-a28f-0800200c9a66' bay_type = 'swarm' allowed_bay_types = ['swarm'] self._test_enforce_bay_types( mock_bay_get_by_uuid, mock_pecan_request, bay_type, allowed_bay_types, False, None, bay_ident) @mock.patch('pecan.request') @mock.patch('magnum.objects.Bay.get_by_uuid') def test_enforce_bay_types_with_bay_uuid_not_allowed(self, mock_bay_get_by_uuid, mock_pecan_request): bay_ident = 'e74c40e0-d825-11e2-a28f-0800200c9a66' bay_type = 'swarm' allowed_bay_types = ['mesos'] self._test_enforce_bay_types( mock_bay_get_by_uuid, mock_pecan_request, bay_type, allowed_bay_types, True, None, bay_ident) @mock.patch('pecan.request') @mock.patch('magnum.objects.Bay.get_by_name') def test_enforce_bay_types_with_bay_name(self, mock_bay_get_by_uuid, mock_pecan_request): bay_ident = 'bay_name' bay_type = 'swarm' allowed_bay_types = ['swarm'] self._test_enforce_bay_types( mock_bay_get_by_uuid, mock_pecan_request, bay_type, allowed_bay_types, False, None, bay_ident) @mock.patch('pecan.request') @mock.patch('magnum.objects.Bay.get_by_name') def test_enforce_bay_types_with_bay_name_not_allowed(self, mock_bay_get_by_uuid, mock_pecan_request): bay_ident = 'bay_name' bay_type = 'swarm' allowed_bay_types = ['mesos'] self._test_enforce_bay_types( mock_bay_get_by_uuid, mock_pecan_request, bay_type, allowed_bay_types, True, None, bay_ident) def _test_enforce_network_driver_types_create( self, network_driver_type, network_driver_config_dict, coe='kubernetes', assert_raised=False): @v.enforce_network_driver_types_create() def test(self, baymodel): pass for key, val in network_driver_config_dict.items(): cfg.CONF.set_override(key, val, 'baymodel') baymodel = mock.MagicMock() baymodel.name = 'test_baymodel' baymodel.network_driver = network_driver_type baymodel.coe = coe # Reload the validator module so that baymodel configs are # re-evaluated. reload_module(v) validator = v.K8sValidator validator.supported_network_drivers = ['flannel', 'type1', 'type2'] if assert_raised: self.assertRaises(exception.InvalidParameterValue, test, self, baymodel) else: test(self, baymodel) return baymodel def test_enforce_network_driver_types_one_allowed_create(self): self._test_enforce_network_driver_types_create( network_driver_type='type1', network_driver_config_dict={ 'kubernetes_allowed_network_drivers': ['type1']}) def test_enforce_network_driver_types_two_allowed_create(self): self._test_enforce_network_driver_types_create( network_driver_type='type1', network_driver_config_dict={ 'kubernetes_allowed_network_drivers': ['type1', 'type2']}) def test_enforce_network_driver_types_not_allowed_create(self): self._test_enforce_network_driver_types_create( network_driver_type='type1', network_driver_config_dict={ 'kubernetes_allowed_network_drivers': ['type2']}, assert_raised=True) def test_enforce_network_driver_types_all_allowed_create(self): for driver in ['flannel', 'type1', 'type2']: self._test_enforce_network_driver_types_create( network_driver_type=driver, network_driver_config_dict={ 'kubernetes_allowed_network_drivers': ['all']}) def test_enforce_network_driver_types_invalid_coe_create(self): self._test_enforce_network_driver_types_create( network_driver_type='flannel', network_driver_config_dict={}, coe='invalid_coe_type', assert_raised=True) def test_enforce_network_driver_types_default_create(self): baymodel = self._test_enforce_network_driver_types_create( network_driver_type=None, network_driver_config_dict={}) self.assertEqual('flannel', baymodel.network_driver) def test_enforce_network_driver_types_default_config_create(self): baymodel = self._test_enforce_network_driver_types_create( network_driver_type=None, network_driver_config_dict={ 'kubernetes_default_network_driver': 'type1'}) self.assertEqual('type1', baymodel.network_driver) def test_enforce_network_driver_types_default_invalid_create(self): self._test_enforce_network_driver_types_create( network_driver_type=None, network_driver_config_dict={ 'kubernetes_default_network_driver': 'invalid_driver'}, assert_raised=True) @mock.patch('pecan.request') @mock.patch('magnum.api.utils.get_resource') def _test_enforce_network_driver_types_update( self, mock_get_resource, mock_pecan_request, network_driver_type, network_driver_config_dict, assert_raised=False): @v.enforce_network_driver_types_update() def test(self, baymodel_ident, patch): pass for key, val in network_driver_config_dict.items(): cfg.CONF.set_override(key, val, 'baymodel') baymodel_ident = 'test_uuid_or_name' patch = [{'path': '/network_driver', 'value': network_driver_type, 'op': 'replace'}] context = mock_pecan_request.context baymodel = obj_utils.get_test_baymodel(context, uuid=baymodel_ident, coe='kubernetes') baymodel.network_driver = network_driver_type mock_get_resource.return_value = baymodel # Reload the validator module so that baymodel configs are # re-evaluated. reload_module(v) validator = v.K8sValidator validator.supported_network_drivers = ['flannel', 'type1', 'type2'] if assert_raised: self.assertRaises(exception.InvalidParameterValue, test, self, baymodel_ident, patch) else: test(self, baymodel_ident, patch) mock_get_resource.assert_called_once_with( 'BayModel', baymodel_ident) def test_enforce_network_driver_types_one_allowed_update(self): self._test_enforce_network_driver_types_update( network_driver_type='type1', network_driver_config_dict={ 'kubernetes_allowed_network_drivers': ['type1']}) def test_enforce_network_driver_types_two_allowed_update(self): self._test_enforce_network_driver_types_update( network_driver_type='type1', network_driver_config_dict={ 'kubernetes_allowed_network_drivers': ['type1', 'type2']}) def test_enforce_network_driver_types_not_allowed_update(self): self._test_enforce_network_driver_types_update( network_driver_type='type1', network_driver_config_dict={ 'kubernetes_allowed_network_drivers': ['type2']}, assert_raised=True) def test_enforce_network_driver_types_all_allowed_update(self): for driver in ['flannel', 'type1', 'type2']: self._test_enforce_network_driver_types_update( network_driver_type=driver, network_driver_config_dict={ 'kubernetes_allowed_network_drivers': ['all']}) def _test_enforce_volume_driver_types_create( self, volume_driver_type, coe='kubernetes', assert_raised=False): @v.enforce_volume_driver_types_create() def test(self, baymodel): pass baymodel = obj_utils.get_test_baymodel( {}, name='test_baymodel', coe=coe, volume_driver=volume_driver_type) if assert_raised: self.assertRaises(exception.InvalidParameterValue, test, self, baymodel) else: test(self, baymodel) def test_enforce_volume_driver_types_valid_create(self): self._test_enforce_volume_driver_types_create( volume_driver_type='cinder') def test_enforce_volume_driver_types_invalid_create(self): self._test_enforce_volume_driver_types_create( volume_driver_type='type', assert_raised=True) @mock.patch('pecan.request') @mock.patch('magnum.api.utils.get_resource') def _test_enforce_volume_driver_types_update( self, mock_get_resource, mock_pecan_request, volume_driver_type, op, assert_raised=False): @v.enforce_volume_driver_types_update() def test(self, baymodel_ident, patch): pass baymodel_ident = 'test_uuid_or_name' patch = [{'path': '/volume_driver', 'value': volume_driver_type, 'op': op}] context = mock_pecan_request.context baymodel = obj_utils.get_test_baymodel(context, uuid=baymodel_ident, coe='kubernetes') mock_get_resource.return_value = baymodel # Reload the validator module so that baymodel configs are # re-evaluated. reload_module(v) validator = v.K8sValidator validator.supported_volume_driver = ['cinder'] if assert_raised: self.assertRaises(exception.InvalidParameterValue, test, self, baymodel_ident, patch) else: test(self, baymodel_ident, patch) mock_get_resource.assert_called_once_with( 'BayModel', baymodel_ident) def test_enforce_volume_driver_types_supported_replace_update(self): self._test_enforce_volume_driver_types_update( volume_driver_type='cinder', op='replace') def test_enforce_volume_driver_types_not_supported_replace_update(self): self._test_enforce_volume_driver_types_update( volume_driver_type='type1', op='replace', assert_raised=True) def test_enforce_volume_driver_types_supported_add_update(self): self._test_enforce_volume_driver_types_update( volume_driver_type='cinder', op='add') def test_enforce_volume_driver_types_not_supported_add_update(self): self._test_enforce_volume_driver_types_update( volume_driver_type='type1', op='add', assert_raised=True) def test_enforce_volume_driver_types_remove_update(self): self._test_enforce_volume_driver_types_update( volume_driver_type='cinder', op='remove') def test_validate_bay_properties(self): allowed_properties = v.bay_update_allowed_properties for field in objects.Bay.fields: if field in allowed_properties: v.validate_bay_properties(set([field])) else: self.assertRaises(exception.InvalidParameterValue, v.validate_bay_properties, set([field]))

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8a10b71785977b3a6b732b22400099e6a8be5ead

92

py

Python

brick_data/sparql/__init__.py

jbkoh/brick_data

bab392b8b0b83c7a0c5427c08f3d9f2b22a8ab06

[ "Apache-2.0" ]

3

2020-09-24T18:53:55.000Z

2021-02-22T07:30:04.000Z

brick_data/sparql/__init__.py

jbkoh/brick-federation

bab392b8b0b83c7a0c5427c08f3d9f2b22a8ab06

[ "Apache-2.0" ]

2

2019-03-31T01:22:13.000Z

2019-05-28T00:49:36.000Z

brick_data/sparql/__init__.py

jbkoh/brick-federation

bab392b8b0b83c7a0c5427c08f3d9f2b22a8ab06

[ "Apache-2.0" ]

1

2019-05-28T18:58:51.000Z

from .brick_endpoint import BrickSparql from .brick_endpoint_async import BrickSparqlAsync

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8a228fd326b7b4bcafd53a4cfdce6a610119602c

141

py

Python

AET/imagenet/algorithms/__init__.py

pjwu1997/teil_project

b7439210c773bbd4f47099da2947e4f0702fcaac

[ "MIT" ]

114

2019-03-26T07:08:04.000Z

2022-03-19T12:27:45.000Z

AET/imagenet/algorithms/__init__.py

pjwu1997/teil_project

b7439210c773bbd4f47099da2947e4f0702fcaac

[ "MIT" ]

7

2019-04-23T03:20:36.000Z

2021-02-07T11:30:59.000Z

AET/imagenet/algorithms/__init__.py

pjwu1997/teil_project

b7439210c773bbd4f47099da2947e4f0702fcaac

[ "MIT" ]

29

2019-05-04T15:24:18.000Z

2022-03-19T12:27:47.000Z

from .Algorithm import * from .UnsupervisedModel import UnsupervisedModel from .FeatureClassificationModel import FeatureClassificationModel

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8a2385646b2b4b510c3b8eda943e1a7bef54fdfa

658

py

Python

data/train/python/8a2385646b2b4b510c3b8eda943e1a7bef54fdfaFileSystemService.py

harshp8l/deep-learning-lang-detection

2a54293181c1c2b1a2b840ddee4d4d80177efb33

[ "MIT" ]

84

2017-10-25T15:49:21.000Z

2021-11-28T21:25:54.000Z

data/train/python/8a2385646b2b4b510c3b8eda943e1a7bef54fdfaFileSystemService.py

vassalos/deep-learning-lang-detection

cbb00b3e81bed3a64553f9c6aa6138b2511e544e

[ "MIT" ]

5

2018-03-29T11:50:46.000Z

2021-04-26T13:33:18.000Z

data/train/python/8a2385646b2b4b510c3b8eda943e1a7bef54fdfaFileSystemService.py

vassalos/deep-learning-lang-detection

cbb00b3e81bed3a64553f9c6aa6138b2511e544e

[ "MIT" ]

24

2017-11-22T08:31:00.000Z

2022-03-27T01:22:31.000Z

# _*_ coding:utf-8 _*_ from web.broker.BrokerService import BrokerService __author__ = 'Administrator' class FileSystemService(object): def __init__(self): pass def partitionInfo(self, hostKey): broker = BrokerService.getBroker(hostKey) return broker.getDiskInfo() def ls(self, hostKey, path): broker = BrokerService.getBroker(hostKey) return broker.getPathDetail(path) def rm(self, hostKey, path): broker = BrokerService.getBroker(hostKey) return broker.rm(path) def cp(self, hostKey, path): broker = BrokerService.getBroker(hostKey) return broker.cp(path)

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8a354079fa9f239166741c007f8d1bb1a960a92a

126

py

Python

Beginner/assignment.py

saurabhpati/python.beginner

a1ed49eb0da7aea80d914ef8b6df162ebf8abae1

[ "MIT" ]

null

Beginner/assignment.py

saurabhpati/python.beginner

a1ed49eb0da7aea80d914ef8b6df162ebf8abae1

[ "MIT" ]

null

Beginner/assignment.py

saurabhpati/python.beginner

a1ed49eb0da7aea80d914ef8b6df162ebf8abae1

[ "MIT" ]

null

# Ease of assignmnent operations in python. counter, miles, name = 100 + 5j, 1000.0, 'John Doe'; print(counter, miles, name);

31.5

52

0.706349

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6

8a59703b3c1839c96053987d033ed463331ecc79

20

py

Python

odoo-13.0/addons/hw_drivers/controllers/__init__.py

VaibhavBhujade/Blockchain-ERP-interoperability

b5190a037fb6615386f7cbad024d51b0abd4ba03

[ "MIT" ]

null

odoo-13.0/addons/hw_drivers/controllers/__init__.py

VaibhavBhujade/Blockchain-ERP-interoperability

b5190a037fb6615386f7cbad024d51b0abd4ba03

[ "MIT" ]

null

odoo-13.0/addons/hw_drivers/controllers/__init__.py

VaibhavBhujade/Blockchain-ERP-interoperability

b5190a037fb6615386f7cbad024d51b0abd4ba03

[ "MIT" ]

null

from . import driver

20

0.8

3

20

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6

8a84e0653053d23cd6880fdad1f2501b30f3da90

3,652

py

Python

kitsune/kbforums/forms.py

jgmize/kitsune

8f23727a9c7fcdd05afc86886f0134fb08d9a2f0

[ "BSD-3-Clause" ]

null

kitsune/kbforums/forms.py

jgmize/kitsune

8f23727a9c7fcdd05afc86886f0134fb08d9a2f0

[ "BSD-3-Clause" ]

null

kitsune/kbforums/forms.py

jgmize/kitsune

8f23727a9c7fcdd05afc86886f0134fb08d9a2f0

[ "BSD-3-Clause" ]

null

from django import forms from tower import ugettext_lazy as _lazy from kitsune.kbforums.models import Thread, Post from kitsune.sumo.form_fields import StrippedCharField MSG_TITLE_REQUIRED = _lazy(u'Please provide a title.') MSG_TITLE_SHORT = _lazy(u'Your title is too short (%(show_value)s ' u'characters). It must be at least %(limit_value)s ' u'characters.') MSG_TITLE_LONG = _lazy(u'Please keep the length of your title to ' u'%(limit_value)s characters or less. It is ' u'currently %(show_value)s characters.') MSG_CONTENT_REQUIRED = _lazy(u'Please provide a message.') MSG_CONTENT_SHORT = _lazy(u'Your message is too short (%(show_value)s ' u'characters). It must be at least %(limit_value)s ' u'characters.') MSG_CONTENT_LONG = _lazy(u'Please keep the length of your message to ' u'%(limit_value)s characters or less. It is ' u'currently %(show_value)s characters.') class ReplyForm(forms.ModelForm): """Reply form for forum threads.""" content = StrippedCharField( label=_lazy('Content:'), min_length=5, max_length=10000, widget=forms.Textarea(attrs={'rows': 10, 'cols': 80}), error_messages={'required': MSG_CONTENT_REQUIRED, 'min_length': MSG_CONTENT_SHORT, 'max_length': MSG_CONTENT_LONG}) class Meta: model = Post fields = ('content', ) class NewThreadForm(forms.Form): """Form to start a new thread.""" title = StrippedCharField(min_length=5, max_length=255, label=_lazy('Title:'), widget=forms.TextInput(attrs={'size': 80}), error_messages={'required': MSG_TITLE_REQUIRED, 'min_length': MSG_TITLE_SHORT, 'max_length': MSG_TITLE_LONG}) content = StrippedCharField( label=_lazy('Content:'), min_length=5, max_length=10000, widget=forms.Textarea(attrs={'rows': 30, 'cols': 76}), error_messages={'required': MSG_CONTENT_REQUIRED, 'min_length': MSG_CONTENT_SHORT, 'max_length': MSG_CONTENT_LONG}) class EditThreadForm(forms.ModelForm): """Form to start a new thread.""" title = StrippedCharField(min_length=5, max_length=255, label=_lazy('Title:'), widget=forms.TextInput(attrs={'size': 80}), error_messages={'required': MSG_TITLE_REQUIRED, 'min_length': MSG_TITLE_SHORT, 'max_length': MSG_TITLE_LONG}) class Meta: model = Thread fields = ('title',) class EditPostForm(forms.Form): """Form to edit an existing post.""" content = StrippedCharField( label=_lazy('Content:'), min_length=5, max_length=10000, widget=forms.Textarea(attrs={'rows': 30, 'cols': 76}), error_messages={'required': MSG_CONTENT_REQUIRED, 'min_length': MSG_CONTENT_SHORT, 'max_length': MSG_CONTENT_LONG}) class Meta: model = Post exclude = ('thread', 'author', 'updated', 'created', 'updated_by')

41.977011

78

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382

3,652

4.89267

0.235602

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0.051364

0.034778

0.730337

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0

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3,652

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0.782776

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0

null

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1

0

1

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null

0

6

8ab1fcb53f3107bc02edbb2ac03056845d88920f

41

bzl

Python

gazelle/bzl/testdata/defaultvisibility/nested/dir/bar.bzl

jkjk822/bazel-skylib

85c9e3daeb1f15ca756d594eb2cc39d74517cb44

[ "Apache-2.0" ]

223

2017-10-10T15:14:00.000Z

2022-03-28T01:59:03.000Z

gazelle/bzl/testdata/defaultvisibility/nested/dir/bar.bzl

jkjk822/bazel-skylib

85c9e3daeb1f15ca756d594eb2cc39d74517cb44

[ "Apache-2.0" ]

241

2017-10-31T10:15:47.000Z

2022-03-30T20:20:50.000Z

gazelle/bzl/testdata/defaultvisibility/nested/dir/bar.bzl

jkjk822/bazel-skylib

85c9e3daeb1f15ca756d594eb2cc39d74517cb44

[ "Apache-2.0" ]

135

2017-11-27T22:12:20.000Z

2022-03-18T21:07:05.000Z

""" Doc string """ def asdf(): pass

5.857143

11

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5

41

4

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0.292683

41

6

12

6.833333

0.689655

0.243902

0

1

0.5

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

6

8acc031afe29565ca6503bc80208ffb27567abc3

162

py

Python

tests/ivan_test.py

ManuelMasferrer/MISW4101-202111-Grupo57-sandbox

27dcd9b17315b8a90f1adb94a107abfb14525025

[ "MIT" ]

null

tests/ivan_test.py

ManuelMasferrer/MISW4101-202111-Grupo57-sandbox

27dcd9b17315b8a90f1adb94a107abfb14525025

[ "MIT" ]

null

tests/ivan_test.py

ManuelMasferrer/MISW4101-202111-Grupo57-sandbox

27dcd9b17315b8a90f1adb94a107abfb14525025

[ "MIT" ]

1

2021-03-08T21:59:51.000Z

import unittest class TestIvan(unittest.TestCase): def test_add(self): self.assertEqual(1,1) def test_diff(self): self.assertEqual(1,3)

18

34

0.666667

22

162

4.818182

0.590909

0.132075

0.358491

0.377358

0

0.031746

0.222222

162

9

35

18

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0.333333

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0

1

0

null

0

1

0

1

0

6

0a228179aac0a67c05e941b2af94c0359d0e8a1e

209

py

Python

pili/errors.py

yavana/pili-python3.5

aa42e2c8400ed3972a918e5951f13ad640ddfa3d

[ "MIT" ]

null

pili/errors.py

yavana/pili-python3.5

aa42e2c8400ed3972a918e5951f13ad640ddfa3d

[ "MIT" ]

null

pili/errors.py

yavana/pili-python3.5

aa42e2c8400ed3972a918e5951f13ad640ddfa3d

[ "MIT" ]

null

class APIError(RuntimeError): def __init__(self, message): self.message = message def __str__(self): return "%s" % (self.message) def __repr__(self): return self.__str__()

23.222222

36

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23

209

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0.263158

209

8

37

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false

0

0.285714

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0

1

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null

1

0

1

0

null

0

1

0

1

0

6

0a2f3a25816f2503cb257559c981b6323587164e

20,217

py

Python

app/align.py

epfl-dcsl/ptf-persona

8720e6b529450083d25fa730ec28a9d2d0270aae

[ "Apache-2.0" ]

null

app/align.py

epfl-dcsl/ptf-persona

8720e6b529450083d25fa730ec28a9d2d0270aae

[ "Apache-2.0" ]

null

app/align.py

epfl-dcsl/ptf-persona

8720e6b529450083d25fa730ec28a9d2d0270aae

[ "Apache-2.0" ]

null

# Copyright 2019 École Polytechnique Fédérale de Lausanne. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== import itertools from . import app from modules.snap_align import snap_align as stage from common.parse import numeric_min_checker, add_dataset, path_exists_checker, filepath_key import tensorflow.contrib.gate as gate import tensorflow as tf import logging; logging.basicConfig(level=logging.DEBUG) import json from .common import make_counter device_type_name = "align" def add_common_arguments(parser): parser.add_argument("--align-counters", default=False, action="store_true", help="track the exit rate of the align/sort stages") parser.add_argument("--align-stages", dest="stages", default=1, type=numeric_min_checker(1, "must have at least 1 fused_align_sort"), help="number of align stages") parser.add_argument("--parallel-open-requests", type=numeric_min_checker(1, "must have at least 1 parallel open request"), help="if specified, the number of parallel open requests") parser.add_argument("--parallel-open-request-expansion-factor", default=1.5, type=numeric_min_checker(0.1, numeric_type=float, message="must have at least 0.1 expansion factor"), help="the expansion factor to multiple the number of client slots by to bound the capacity in the global pipeline. Not used if parallel_open_requests is set") class Align(app.Application): ingress_dtypes = (tf.string,) ingress_shapes = ((),) @staticmethod def name(): return "align" @staticmethod def help_message(): return "align a dataset using Snap" class_logger = logging.getLogger(name="AlignClass") class_logger.setLevel(level=logging.DEBUG) @classmethod def _make_graph_args(cls, parser): # TODO need to do the subparsers thing here when there ceph option is available add_common_arguments(parser=parser) parser.add_argument("--log-goodput", default=False, action='store_true', help="turn on all goodput and latency tracing") stage.LocalSnapStage.add_graph_args(parser=parser) @classmethod def device_counts(cls, args): return { device_type_name: args.stages } def _construct_graph(self, args, device_map, num_client_slots): # need to set ingress and egress queue devices = device_map[device_type_name] num_devices = len(devices) stages = tuple(stage.LocalSnapStage(args=args) for _ in range(num_devices)) gate_name = "ingress_gate" if args.parallel_open_requests is not None: capacity_between_gates = args.parallel_open_requests else: capacity_between_gates = int(num_client_slots * args.parallel_open_request_expansion_factor) if capacity_between_gates < 1: raise Exception("Capacity between gates is <1 ({c})".format(c=capacity_between_gates)) ingress = gate.IngressGate(dtypes=self.ingress_dtypes, shapes=self.ingress_shapes, capacity=capacity_between_gates, shared_name=gate_name, name=gate_name) def make_stages(): for stage, device in zip(stages, devices): with device(): device_graph = stage.make_graph(upstream_gate=ingress) try: # convert to a tuple if it returns a generator device_graph[0] except TypeError: device_graph = tuple(device_graph) run_first = stage.run_first assert len(run_first) > 0 for item in run_first: self._add_run_first(item) yield device_graph with tf.name_scope("align_pipeline"): outputs = tuple(make_stages()) assert len(outputs) == len(stages) example_output = outputs[0] egress = gate.EgressGate(capacity=capacity_between_gates, sample_tensors=example_output[1:], id_and_count_upstream=example_output[0], join=True) enqueue_ops = tuple(egress.enqueue(id_and_count=a[0], components=a[1:]) for a in outputs) if args.align_counters: if getattr(args, "summary", False): with tf.name_scope(None): with tf.name_scope("performance"): enqueue_ops = tuple(make_counter(counter_name="aligned_counter", summary_name="aligned_num_records", deps_and_counters=zip( enqueue_ops, (a[3] for a in outputs) ))) else: self.log.warning("Align counters requested, but no summary was requested. Please enable summary for this to work.") gate.add_gate_runner(gate_runner=gate.GateRunner(gate=egress, enqueue_ops=enqueue_ops, device=egress.device)) gate.add_credit_supplier_from_gates(upstream_gate=ingress, downstream_gate=egress) self.close_op = egress.close() unknown_shape = tf.TensorShape([None]) batch_ingress_shapes = tuple(unknown_shape.concatenate(ishape) for ishape in self.ingress_shapes) for _ in range(num_client_slots): ingress_placeholders = tuple(tf.placeholder(dtype=dtype, shape=shape) for dtype, shape in zip(self.ingress_dtypes, batch_ingress_shapes)) ingress_enqueue = ingress.enqueue_request(components=ingress_placeholders) egress_dequeue = egress.dequeue_request(request_id=ingress_enqueue) yield self.ClientSlot(ingress_placeholders=ingress_placeholders, egress_dequeue=egress_dequeue) @classmethod def make_client_args(cls, parser): # TODO assume that for now it is just the local filesystem. Will need to differentiate for other stuff later add_dataset(parser=parser) parser.add_argument("-d", "--dataset-dir", type=path_exists_checker(), help="Directory containing ALL of the chunk files") @classmethod def process_ingress_args(cls, args): dataset_dir = args.dataset_dir if dataset_dir is None: metadata_path = args.dataset[filepath_key] dataset_dir = metadata_path.parent files_to_remove = tuple(itertools.chain(dataset_dir.glob("*.results"), dataset_dir.glob("*.secondary*"))) if len(files_to_remove) > 0: cls.class_logger.info("Removing prior results before aligning: {}".format(files_to_remove)) for f in files_to_remove: assert f.is_file() f.unlink() if len(args.dataset["records"]) == 0: raise ValueError("Dataset must have non-zero number of records") return (dataset_dir / record["path"] for record in args.dataset["records"]) @staticmethod def parse_and_verify_results(results): record_ids = results[0] record_id_count = len(record_ids) assert record_id_count > 0 first_record_id = record_ids[0] assert all(rid == first_record_id for rid in record_ids) first_ordinals = results[1] assert len(first_ordinals) == record_id_count num_records = results[2] assert len(num_records) == record_id_count file_basenames = results[3] assert len(file_basenames) == record_id_count result_filenames = results[4:] assert len(result_filenames) > 0 assert all(len(r) == record_id_count for r in result_filenames) result_filename_column = result_filenames[0] extensions = set() for basename, result_column_name in zip(file_basenames, result_filename_column): column_basename, extension = result_column_name.rsplit(".", 1) assert extension == "results" assert column_basename == basename if extension not in extensions: extensions.add(extension) for index, secondary_column in enumerate(result_filenames[1:]): expected_column_extension = "secondary{}".format(index) extensions.add(expected_column_extension) for basename, result_column_name in zip(file_basenames, secondary_column): column_basename, extension = result_column_name.rsplit(".", 1) assert extension == expected_column_extension assert column_basename == basename return first_record_id, first_ordinals, num_records, file_basenames, extensions @classmethod def process_egress_results(cls, results, args): """ :param results: a list of [ record_id, first_ordinal, num_records, file_basename, written_records], where written_records is a list of results, then all the secondary files (all strings) :param args: :return: """ record_id, first_ordinals, num_records, file_basenames, extensions = cls.parse_and_verify_results(results=results) output_filepath = args.dataset.pop(filepath_key) columns = args.dataset["columns"] for extension in sorted(extensions): # will put results first, then all secondary if extension not in columns: columns.append(extension) with output_filepath.open("w+") as f: json.dump(args.dataset, f, indent=4) def _run_client_request(self, client_args, client_slot, sess): client_args = tuple(client_args) ingress_placeholder = client_slot.ingress_placeholders[0] egress_dequeue = client_slot.egress_dequeue results = sess.run(egress_dequeue, feed_dict={ingress_placeholder: tuple(str(c) for c in client_args)}) record_ids, first_ordinals, num_recordz, file_basenames = results[:4] full_file_pathz = tuple(results[4:]) utf8 = "utf-8" new_record_ids = tuple(i.decode(utf8) for i in record_ids) new_first_ordinals = tuple(int(i) for i in first_ordinals) new_num_recordz = tuple(int(i) for i in num_recordz) new_file_basenames = tuple(i.decode(utf8) for i in file_basenames) new_full_file_pathz = tuple( tuple(b.decode(utf8) for b in ffp) for ffp in full_file_pathz ) return (new_record_ids, new_first_ordinals, new_num_recordz, new_file_basenames) + new_full_file_pathz def stop(self, sess): try: sess.run(self.close_op) except Exception as e: self.log.error("{nm} closing. Got exception '{e}'".format(e=e, nm=self.name())) class CephAlign(app.Application): ingress_dtypes = (tf.string,) ingress_shapes = ((2),) @staticmethod def name(): return "ceph-align" @staticmethod def help_message(): return "align a dataset using Snap on a ceph filesystem" class_logger = logging.getLogger(name="CephAlignClass") class_logger.setLevel(level=logging.DEBUG) @classmethod def _make_graph_args(cls, parser): add_common_arguments(parser=parser) parser.add_argument("--log-goodput", default=False, action='store_true', help="turn on all goodput and latency tracing") stage.CephSnapStage.add_graph_args(parser=parser) @classmethod def device_counts(cls, args): return { device_type_name: args.stages } def _construct_graph(self, args, device_map, num_client_slots): devices = device_map[device_type_name] num_devices = len(devices) gate_name = "ingress_gate" if args.parallel_open_requests is not None: capacity_between_gates = args.parallel_open_requests else: capacity_between_gates = int(num_client_slots * args.parallel_open_request_expansion_factor) if capacity_between_gates < 1: raise Exception("Capacity between gates is <1 ({c})".format(c=capacity_between_gates)) ingress = gate.IngressGate(dtypes=self.ingress_dtypes, shapes=self.ingress_shapes, capacity=capacity_between_gates, shared_name=gate_name, name=gate_name) with tf.name_scope("align_pipeline"): stages = tuple(stage.CephSnapStage(args=args) for _ in range(num_devices)) def make_stages(): for stage, device in zip(stages, devices): with device(): device_graph = stage.make_graph(upstream_gate=ingress) try: # convert to a tuple if it returns a generator device_graph[0] except TypeError: device_graph = tuple(device_graph) run_first = stage.run_first assert len(run_first) > 0 for item in run_first: self._add_run_first(item) yield device_graph outputs = tuple(make_stages()) assert len(outputs) == len(stages) example_output = outputs[0] egress = gate.EgressGate(capacity=capacity_between_gates, sample_tensors=example_output[1:], id_and_count_upstream=example_output[0], join=True) enqueue_ops = tuple(egress.enqueue(id_and_count=a[0], components=a[1:]) for a in outputs) if args.align_counters: if getattr(args, "summary", False): with tf.name_scope(None): with tf.name_scope("performance"): enqueue_ops = tuple(make_counter(counter_name="aligned_counter", summary_name="aligned_num_records", deps_and_counters=zip( enqueue_ops, (a[3] for a in outputs) ))) else: self.log.warning("Align counters requested, but no summary was requested. Please enable summary for this to work.") gate.add_gate_runner(gate_runner=gate.GateRunner(gate=egress, enqueue_ops=enqueue_ops, device=egress.device)) gate.add_credit_supplier_from_gates(upstream_gate=ingress, downstream_gate=egress) self.close_op = egress.close() unknown_shape = tf.TensorShape([None]) batch_ingress_shapes = tuple(unknown_shape.concatenate(ishape) for ishape in self.ingress_shapes) for _ in range(num_client_slots): ingress_placeholders = tuple(tf.placeholder(dtype=dtype, shape=shape) for dtype, shape in zip(self.ingress_dtypes, batch_ingress_shapes)) ingress_enqueue = ingress.enqueue_request(components=ingress_placeholders) egress_dequeue = egress.dequeue_request(request_id=ingress_enqueue) yield self.ClientSlot(ingress_placeholders=ingress_placeholders, egress_dequeue=egress_dequeue) @classmethod def make_client_args(cls, parser): parser.add_argument("--namespace", default="", help="the namespace to access this dataset") parser.add_argument("--use-default-namespace", default=False, action="store_true", help="use the name of this record as the namespace") add_dataset(parser=parser) @classmethod def process_ingress_args(cls, args): dataset = args.dataset if args.use_default_namespace: namespace = dataset["name"] else: namespace = args.namespace record_keys = (a["path"] for a in dataset["records"]) return tuple(zip(record_keys, itertools.repeat(namespace))) @staticmethod def parse_and_verify_results(results): record_ids = results[0] record_id_count = len(record_ids) assert record_id_count > 0 first_record_id = record_ids[0] assert all(rid == first_record_id for rid in record_ids) first_ordinals = results[1] assert len(first_ordinals) == record_id_count num_records = results[2] assert len(num_records) == record_id_count file_keys = results[3] assert len(file_keys) == record_id_count namespaces = results[4] assert len(namespaces) == record_id_count first_namespace = namespaces[0] assert all(n == first_namespace for n in namespaces[1:]) result_filenames = results[5:] assert len(result_filenames) > 0 assert all(len(r) == record_id_count for r in result_filenames) result_filename_column = result_filenames[0] extensions = set() for basename, result_column_name in zip(file_keys, result_filename_column): column_basename, extension = result_column_name.rsplit(".", 1) assert extension == "results" assert column_basename == basename if extension not in extensions: extensions.add(extension) for index, secondary_column in enumerate(result_filenames[1:]): expected_column_extension = "secondary{}".format(index) extensions.add(expected_column_extension) for basename, result_column_name in zip(file_keys, secondary_column): column_basename, extension = result_column_name.rsplit(".", 1) assert extension == expected_column_extension assert column_basename == basename return first_record_id, first_ordinals, num_records, file_keys, first_namespace, extensions @classmethod def process_egress_results(cls, results, args): """ :param results: a list of [ record_id, first_ordinal, num_records, file_basename, written_records], where written_records is a list of results, then all the secondary files (all strings) :param args: :return: """ record_id, first_ordinals, num_records, file_keys, namespace, extensions = cls.parse_and_verify_results(results=results) output_filepath = args.dataset.pop(filepath_key) columns = args.dataset["columns"] for extension in sorted(extensions): # will put results first, then all secondary if extension not in columns: columns.append(extension) with output_filepath.open("w+") as f: json.dump(args.dataset, f, indent=4) def _run_client_request(self, client_args, client_slot, sess): client_args = tuple(client_args) ingress_placeholder = client_slot.ingress_placeholders[0] egress_dequeue = client_slot.egress_dequeue results = sess.run(egress_dequeue, feed_dict={ingress_placeholder: client_args}) record_ids, first_ordinals, num_recordz, keys, namespaces = results[:5] full_keys_records = results[5:] utf8 = "utf-8" new_record_ids = tuple(i.decode(utf8) for i in record_ids) new_first_ordinals = tuple(int(i) for i in first_ordinals) new_num_recordz = tuple(int(i) for i in num_recordz) new_keys = tuple(i.decode(utf8) for i in keys) new_namespaces = tuple(i.decode(utf8) for i in namespaces) new_full_keys_records = tuple( tuple(b.decode(utf8) for b in ffp) for ffp in full_keys_records ) return (new_record_ids, new_first_ordinals, new_num_recordz, new_keys, new_namespaces) + new_full_keys_records def stop(self, sess): try: sess.run(self.close_op) except Exception as e: self.log.error("{nm} closing. Got exception '{e}'".format(e=e, nm=self.name()))

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0a3909a891f68cf52824d3a13d50216ffa959b51

26

py

Python

readless/Segmentation/__init__.py

Santhoshkumard11/senpai

f517aba8f2b442714811bd7748b95ee6e5473820

[ "MIT" ]

59

2016-11-16T13:41:09.000Z

2022-01-26T01:56:38.000Z

readless/Segmentation/__init__.py

AndiChiou/senpai

f517aba8f2b442714811bd7748b95ee6e5473820

[ "MIT" ]

null

readless/Segmentation/__init__.py

AndiChiou/senpai

f517aba8f2b442714811bd7748b95ee6e5473820

[ "MIT" ]

13

2016-11-15T13:09:50.000Z

2021-03-13T11:04:45.000Z

from .texttiling import *

26

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6

0a4a6625d1d6f5459499ee3785a38662c70c6ce6

10,451

py

Python

fireworks/user_objects/firetasks/tests/test_filepad_tasks.py

jmmshn/fireworks

5c2f0586e76ab08cadf8b9f4f85638d838f15448

[ "BSD-3-Clause-LBNL" ]

251

2015-01-05T17:44:47.000Z

2022-03-28T07:25:42.000Z

fireworks/user_objects/firetasks/tests/test_filepad_tasks.py

jmmshn/fireworks

5c2f0586e76ab08cadf8b9f4f85638d838f15448

[ "BSD-3-Clause-LBNL" ]

332

2015-01-06T18:40:53.000Z

2022-03-18T04:44:33.000Z

fireworks/user_objects/firetasks/tests/test_filepad_tasks.py

jmmshn/fireworks

5c2f0586e76ab08cadf8b9f4f85638d838f15448

[ "BSD-3-Clause-LBNL" ]

176

2015-01-16T14:06:53.000Z

2022-02-15T00:45:57.000Z

__author__ = "Kiran Mathew, Johannes Hoermann" import os import unittest from ruamel.yaml import YAML from fireworks.user_objects.firetasks.filepad_tasks import ( AddFilesTask, DeleteFilesTask, GetFilesByQueryTask, GetFilesTask, ) from fireworks.utilities.filepad import FilePad module_dir = os.path.abspath(os.path.dirname(__file__)) class FilePadTasksTest(unittest.TestCase): def setUp(self): self.paths = [os.path.join(module_dir, "write.yaml"), os.path.join(module_dir, "delete.yaml")] self.identifiers = ["write", "delete"] self.fp = FilePad.auto_load() def test_addfilestask_run(self): t = AddFilesTask(paths=self.paths, identifiers=self.identifiers) t.run_task({}) write_file_contents, _ = self.fp.get_file("write") with open(self.paths[0]) as f: self.assertEqual(write_file_contents, f.read().encode()) del_file_contents, _ = self.fp.get_file("delete") with open(self.paths[1]) as f: self.assertEqual(del_file_contents, f.read().encode()) def test_deletefilestask_run(self): t = DeleteFilesTask(identifiers=self.identifiers) t.run_task({}) file_contents, doc = self.fp.get_file("write") self.assertIsNone(file_contents) self.assertIsNone(doc) file_contents, doc = self.fp.get_file("delete") self.assertIsNone(file_contents) self.assertIsNone(doc) def test_getfilestask_run(self): t = AddFilesTask(paths=self.paths, identifiers=self.identifiers) t.run_task({}) dest_dir = os.path.abspath(".") identifiers = ["write"] new_file_names = ["write_2.yaml"] t = GetFilesTask(identifiers=identifiers, dest_dir=dest_dir, new_file_names=new_file_names) t.run_task({}) write_file_contents, _ = self.fp.get_file("write") with open(os.path.join(dest_dir, new_file_names[0])) as f: self.assertEqual(write_file_contents, f.read().encode()) os.remove(os.path.join(dest_dir, new_file_names[0])) def test_getfilesbyquerytask_run(self): """Tests querying objects from FilePad by metadata""" t = AddFilesTask(paths=self.paths, identifiers=self.identifiers, metadata={"key": "value"}) t.run_task({}) dest_dir = os.path.abspath(".") new_file_names = ["test_file.yaml"] t = GetFilesByQueryTask(query={"metadata->key": "value"}, dest_dir=dest_dir, new_file_names=new_file_names) t.run_task({}) test_file_contents, _ = self.fp.get_file("test_idenfifier") self.assertEqual(test_file_contents, open(os.path.join(dest_dir, new_file_names[0])).read().encode()) os.remove(os.path.join(dest_dir, new_file_names[0])) def test_getfilesbyquerytask_run(self): """Tests querying objects from FilePad by metadata""" with open("original_test_file.txt", "w") as f: f.write("Some file with some content") t = AddFilesTask(paths=["original_test_file.txt"], identifiers=["some_identifier"], metadata={"key": "value"}) t.run_task({}) os.remove("original_test_file.txt") dest_dir = os.path.abspath(".") t = GetFilesByQueryTask( query={"metadata->key": "value"}, dest_dir=dest_dir, new_file_names=["queried_test_file.txt"] ) t.run_task({}) test_file_contents, _ = self.fp.get_file("some_identifier") with open(os.path.join(dest_dir, "queried_test_file.txt")) as f: self.assertEqual(test_file_contents, f.read().encode()) os.remove(os.path.join(dest_dir, "queried_test_file.txt")) def test_getfilesbyquerytask_metafile_run(self): """Tests writing metadata to a yaml file""" with open("original_test_file.txt", "w") as f: f.write("Some file with some content") t = AddFilesTask(paths=["original_test_file.txt"], identifiers=["test_identifier"], metadata={"key": "value"}) t.run_task({}) os.remove("original_test_file.txt") dest_dir = os.path.abspath(".") t = GetFilesByQueryTask( query={"metadata->key": "value"}, meta_file=True, meta_file_suffix=".meta.yaml", dest_dir=dest_dir, new_file_names=["queried_test_file.txt"], ) t.run_task({}) with open("queried_test_file.txt.meta.yaml") as f: yaml = YAML(typ="safe") metadata = yaml.load(f) self.assertEqual(metadata["key"], "value") os.remove(os.path.join(dest_dir, "queried_test_file.txt")) os.remove(os.path.join(dest_dir, "queried_test_file.txt.meta.yaml")) def test_getfilesbyquerytask_ignore_empty_result_run(self): """Tests on ignoring empty results from FilePad query""" dest_dir = os.path.abspath(".") t = GetFilesByQueryTask( query={"metadata->key": "value"}, fizzle_empty_result=False, dest_dir=dest_dir, new_file_names=["queried_test_file.txt"], ) t.run_task({}) # test successful if no exception raised def test_getfilesbyquerytask_raise_empty_result_run(self): """Tests on raising exception on empty results from FilePad query""" dest_dir = os.path.abspath(".") t = GetFilesByQueryTask( query={"metadata->key": "value"}, fizzle_empty_result=True, dest_dir=dest_dir, new_file_names=["queried_test_file.txt"], ) with self.assertRaises(ValueError): t.run_task({}) # test successful if exception raised def test_getfilesbyquerytask_ignore_degenerate_file_name(self): """Tests on ignoring degenerate file name in result from FilePad query""" with open("degenerate_file.txt", "w") as f: f.write("Some file with some content") t = AddFilesTask(paths=["degenerate_file.txt"], identifiers=["some_identifier"], metadata={"key": "value"}) t.run_task({}) with open("degenerate_file.txt", "w") as f: f.write("Some other file with some other content BUT same file name") t = AddFilesTask( paths=["degenerate_file.txt"], identifiers=["some_other_identifier"], metadata={"key": "value"} ) t.run_task({}) os.remove("degenerate_file.txt") t = GetFilesByQueryTask(query={"metadata->key": "value"}, fizzle_degenerate_file_name=False) t.run_task({}) # test successful if no exception raised def test_getfilesbyquerytask_raise_degenerate_file_name(self): """Tests on raising exception on degenerate file name from FilePad query""" with open("degenerate_file.txt", "w") as f: f.write("Some file with some content") t = AddFilesTask(paths=["degenerate_file.txt"], identifiers=["some_identifier"], metadata={"key": "value"}) t.run_task({}) with open("degenerate_file.txt", "w") as f: f.write("Some other file with some other content BUT same file name") t = AddFilesTask( paths=["degenerate_file.txt"], identifiers=["some_other_identifier"], metadata={"key": "value"} ) t.run_task({}) os.remove("degenerate_file.txt") t = GetFilesByQueryTask(query={"metadata->key": "value"}, fizzle_degenerate_file_name=True) with self.assertRaises(ValueError): t.run_task({}) # test successful if exception raised def test_getfilesbyquerytask_sort_ascending_name_run(self): """Tests on sorting queried files in ascending order""" file_contents = ["Some file with some content", "Some other file with some other content"] with open("degenerate_file.txt", "w") as f: f.write(file_contents[0]) t = AddFilesTask( paths=["degenerate_file.txt"], identifiers=["some_identifier"], metadata={"key": "value", "sort_key": 0} ) t.run_task({}) with open("degenerate_file.txt", "w") as f: f.write(file_contents[-1]) t = AddFilesTask( paths=["degenerate_file.txt"], identifiers=["some_other_identifier"], metadata={"key": "value", "sort_key": 1}, ) t.run_task({}) os.remove("degenerate_file.txt") t = GetFilesByQueryTask( query={"metadata->key": "value"}, fizzle_degenerate_file_name=False, sort_key="sort_key", sort_direction=1 ) t.run_task({}) with open("degenerate_file.txt") as f: self.assertEqual(file_contents[-1], f.read()) def test_getfilesbyquerytask_sort_descending_name_run(self): """Tests on sorting queried files in descending order""" file_contents = ["Some file with some content", "Some other file with some other content"] with open("degenerate_file.txt", "w") as f: f.write(file_contents[0]) t = AddFilesTask( paths=["degenerate_file.txt"], identifiers=["some_identifier"], metadata={"key": "value", "sort_key": 10} ) t.run_task({}) with open("degenerate_file.txt", "w") as f: f.write(file_contents[-1]) t = AddFilesTask( paths=["degenerate_file.txt"], identifiers=["some_other_identifier"], metadata={"key": "value", "sort_key": 20}, ) t.run_task({}) os.remove("degenerate_file.txt") t = GetFilesByQueryTask( query={"metadata->key": "value"}, fizzle_degenerate_file_name=False, sort_key="metadata.sort_key", sort_direction=-1, ) t.run_task({}) with open("degenerate_file.txt") as f: self.assertEqual(file_contents[0], f.read()) os.remove("degenerate_file.txt") def test_addfilesfrompatterntask_run(self): t = AddFilesTask(paths="*.yaml", directory=module_dir) t.run_task({}) write_file_contents, _ = self.fp.get_file(self.paths[0]) with open(self.paths[0]) as f: self.assertEqual(write_file_contents, f.read().encode()) del_file_contents, wdoc = self.fp.get_file(self.paths[1]) with open(self.paths[1]) as f: self.assertEqual(del_file_contents, f.read().encode()) def tearDown(self): self.fp.reset() if __name__ == "__main__": unittest.main()

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0.714902

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0

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0.102941

0

null

0

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null

0

6

0a5fc53690ace9832f04812b6291b498b86eb940

35

py

Python

basic_calculator/__init__.py

DDVHegde100/itp-w1-basic-calculator

feee4da15fa50acd2620b201d7bdae3a9f4e78de

[ "MIT" ]

null

basic_calculator/__init__.py

DDVHegde100/itp-w1-basic-calculator

feee4da15fa50acd2620b201d7bdae3a9f4e78de

[ "MIT" ]

null

basic_calculator/__init__.py

DDVHegde100/itp-w1-basic-calculator

feee4da15fa50acd2620b201d7bdae3a9f4e78de

[ "MIT" ]

1

2021-09-06T12:58:06.000Z

from .main import basic_calculator

17.5

34

0.857143

5

35

5.8

1

0

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1

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null

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1

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1

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1

0

6

6a7637a5335a4f409451e3ec3102079e199f4e34

15,057

py

Python

flink-python/pyflink/table/tests/test_table_environment_api.py

madfrog2047/flink

973dbc02ca8656ef4849abecac1652bbb7932107

[ "Apache-2.0" ]

3

2019-10-09T01:48:20.000Z

2019-10-09T01:53:15.000Z

flink-python/pyflink/table/tests/test_table_environment_api.py

madfrog2047/flink

973dbc02ca8656ef4849abecac1652bbb7932107

[ "Apache-2.0" ]

1

2019-08-27T18:30:10.000Z

flink-python/pyflink/table/tests/test_table_environment_api.py

madfrog2047/flink

973dbc02ca8656ef4849abecac1652bbb7932107

[ "Apache-2.0" ]

null

################################################################################ # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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 from py4j.compat import unicode from pyflink.dataset import ExecutionEnvironment from pyflink.datastream import StreamExecutionEnvironment from pyflink.table import DataTypes, CsvTableSink, StreamTableEnvironment, EnvironmentSettings from pyflink.table.table_config import TableConfig from pyflink.table.table_environment import BatchTableEnvironment from pyflink.table.types import RowType from pyflink.testing import source_sink_utils from pyflink.testing.test_case_utils import PyFlinkStreamTableTestCase, PyFlinkBatchTableTestCase from pyflink.util.exceptions import TableException class StreamTableEnvironmentTests(PyFlinkStreamTableTestCase): def test_register_table_source_scan(self): t_env = self.t_env field_names = ["a", "b", "c"] field_types = [DataTypes.BIGINT(), DataTypes.STRING(), DataTypes.STRING()] source_path = os.path.join(self.tempdir + '/streaming.csv') csv_source = self.prepare_csv_source(source_path, [], field_types, field_names) t_env.register_table_source("Source", csv_source) result = t_env.scan("Source") self.assertEqual( 'CatalogTable: (identifier: [`default_catalog`.`default_database`.`Source`]' ', fields: [a, b, c])', result._j_table.getQueryOperation().asSummaryString()) def test_register_table_sink(self): t_env = self.t_env field_names = ["a", "b", "c"] field_types = [DataTypes.BIGINT(), DataTypes.STRING(), DataTypes.STRING()] t_env.register_table_sink( "Sinks", source_sink_utils.TestAppendSink(field_names, field_types)) t_env.from_elements([(1, "Hi", "Hello")], ["a", "b", "c"]).insert_into("Sinks") self.t_env.execute("test") actual = source_sink_utils.results() expected = ['1,Hi,Hello'] self.assert_equals(actual, expected) def test_from_table_source(self): field_names = ["a", "b", "c"] field_types = [DataTypes.BIGINT(), DataTypes.STRING(), DataTypes.STRING()] source_path = os.path.join(self.tempdir + '/streaming.csv') csv_source = self.prepare_csv_source(source_path, [], field_types, field_names) result = self.t_env.from_table_source(csv_source) self.assertEqual( 'TableSource: (fields: [a, b, c])', result._j_table.getQueryOperation().asSummaryString()) def test_list_tables(self): source_path = os.path.join(self.tempdir + '/streaming.csv') field_names = ["a", "b", "c"] field_types = [DataTypes.INT(), DataTypes.STRING(), DataTypes.STRING()] data = [] csv_source = self.prepare_csv_source(source_path, data, field_types, field_names) t_env = self.t_env t_env.register_table_source("Orders", csv_source) t_env.register_table_sink( "Sinks", source_sink_utils.TestAppendSink(field_names, field_types)) t_env.register_table_sink( "Results", source_sink_utils.TestAppendSink(field_names, field_types)) actual = t_env.list_tables() expected = ['Orders', 'Results', 'Sinks'] self.assert_equals(actual, expected) def test_explain(self): schema = RowType()\ .add('a', DataTypes.INT())\ .add('b', DataTypes.STRING())\ .add('c', DataTypes.STRING()) t_env = self.t_env t = t_env.from_elements([], schema) result = t.select("1 + a, b, c") actual = t_env.explain(result) assert isinstance(actual, str) or isinstance(actual, unicode) def test_explain_with_extended(self): schema = RowType() \ .add('a', DataTypes.INT()) \ .add('b', DataTypes.STRING()) \ .add('c', DataTypes.STRING()) t_env = self.t_env t = t_env.from_elements([], schema) result = t.select("1 + a, b, c") actual = t_env.explain(result, True) assert isinstance(actual, str) or isinstance(actual, unicode) def test_explain_with_multi_sinks(self): t_env = self.t_env source = t_env.from_elements([(1, "Hi", "Hello"), (2, "Hello", "Hello")], ["a", "b", "c"]) field_names = ["a", "b", "c"] field_types = [DataTypes.BIGINT(), DataTypes.STRING(), DataTypes.STRING()] t_env.register_table_sink( "sink1", source_sink_utils.TestAppendSink(field_names, field_types)) t_env.register_table_sink( "sink2", source_sink_utils.TestAppendSink(field_names, field_types)) t_env.sql_update("insert into sink1 select * from %s where a > 100" % source) t_env.sql_update("insert into sink2 select * from %s where a < 100" % source) actual = t_env.explain(extended=True) assert isinstance(actual, str) or isinstance(actual, unicode) def test_sql_query(self): t_env = self.t_env source = t_env.from_elements([(1, "Hi", "Hello"), (2, "Hello", "Hello")], ["a", "b", "c"]) field_names = ["a", "b", "c"] field_types = [DataTypes.BIGINT(), DataTypes.STRING(), DataTypes.STRING()] t_env.register_table_sink( "sinks", source_sink_utils.TestAppendSink(field_names, field_types)) result = t_env.sql_query("select a + 1, b, c from %s" % source) result.insert_into("sinks") self.t_env.execute("test") actual = source_sink_utils.results() expected = ['2,Hi,Hello', '3,Hello,Hello'] self.assert_equals(actual, expected) def test_sql_update(self): t_env = self.t_env source = t_env.from_elements([(1, "Hi", "Hello"), (2, "Hello", "Hello")], ["a", "b", "c"]) field_names = ["a", "b", "c"] field_types = [DataTypes.BIGINT(), DataTypes.STRING(), DataTypes.STRING()] t_env.register_table_sink( "sinks", source_sink_utils.TestAppendSink(field_names, field_types)) t_env.sql_update("insert into sinks select * from %s" % source) self.t_env.execute("test_sql_job") actual = source_sink_utils.results() expected = ['1,Hi,Hello', '2,Hello,Hello'] self.assert_equals(actual, expected) def test_register_java_function(self): t_env = self.t_env t_env.register_java_function("scalar_func", "org.apache.flink.table.expressions.utils.RichFunc0") t_env.register_java_function( "agg_func", "org.apache.flink.table.functions.aggfunctions.ByteMaxAggFunction") t_env.register_java_function("table_func", "org.apache.flink.table.utils.TableFunc1") actual = t_env.list_user_defined_functions() expected = ['scalar_func', 'agg_func', 'table_func'] self.assert_equals(actual, expected) def test_create_table_environment(self): table_config = TableConfig() table_config.set_max_generated_code_length(32000) table_config.set_null_check(False) table_config.set_local_timezone("Asia/Shanghai") env = StreamExecutionEnvironment.get_execution_environment() t_env = StreamTableEnvironment.create(env, table_config) readed_table_config = t_env.get_config() self.assertFalse(readed_table_config.get_null_check()) self.assertEqual(readed_table_config.get_max_generated_code_length(), 32000) self.assertEqual(readed_table_config.get_local_timezone(), "Asia/Shanghai") def test_create_table_environment_with_blink_planner(self): t_env = StreamTableEnvironment.create( self.env, environment_settings=EnvironmentSettings.new_instance().use_blink_planner().build()) planner = t_env._j_tenv.getPlanner() self.assertEqual( planner.getClass().getName(), "org.apache.flink.table.planner.delegation.StreamPlanner") def test_table_environment_with_blink_planner(self): t_env = StreamTableEnvironment.create( self.env, environment_settings=EnvironmentSettings.new_instance().use_blink_planner().build()) source_path = os.path.join(self.tempdir + '/streaming.csv') sink_path = os.path.join(self.tempdir + '/result.csv') field_names = ["a", "b", "c"] field_types = [DataTypes.INT(), DataTypes.STRING(), DataTypes.STRING()] data = [(1, 'hi', 'hello'), (2, 'hello', 'hello')] csv_source = self.prepare_csv_source(source_path, data, field_types, field_names) t_env.register_table_source("source", csv_source) t_env.register_table_sink( "sink", CsvTableSink(field_names, field_types, sink_path)) source = t_env.scan("source") result = source.alias("a, b, c").select("1 + a, b, c") result.insert_into("sink") t_env.execute("blink_test") results = [] with open(sink_path, 'r') as f: results.append(f.readline()) results.append(f.readline()) self.assert_equals(results, ['2,hi,hello\n', '3,hello,hello\n']) class BatchTableEnvironmentTests(PyFlinkBatchTableTestCase): def test_explain(self): source_path = os.path.join(self.tempdir + '/streaming.csv') field_names = ["a", "b", "c"] field_types = [DataTypes.INT(), DataTypes.STRING(), DataTypes.STRING()] data = [] csv_source = self.prepare_csv_source(source_path, data, field_types, field_names) t_env = self.t_env t_env.register_table_source("Source", csv_source) source = t_env.scan("Source") result = source.alias("a, b, c").select("1 + a, b, c") actual = t_env.explain(result) self.assertIsInstance(actual, (str, unicode)) def test_explain_with_extended(self): schema = RowType() \ .add('a', DataTypes.INT()) \ .add('b', DataTypes.STRING()) \ .add('c', DataTypes.STRING()) t_env = self.t_env t = t_env.from_elements([], schema) result = t.select("1 + a, b, c") actual = t_env.explain(result, True) assert isinstance(actual, str) or isinstance(actual, unicode) def test_explain_with_multi_sinks(self): t_env = self.t_env source = t_env.from_elements([(1, "Hi", "Hello"), (2, "Hello", "Hello")], ["a", "b", "c"]) field_names = ["a", "b", "c"] field_types = [DataTypes.BIGINT(), DataTypes.STRING(), DataTypes.STRING()] t_env.register_table_sink( "sink1", CsvTableSink(field_names, field_types, "path1")) t_env.register_table_sink( "sink2", CsvTableSink(field_names, field_types, "path2")) t_env.sql_update("insert into sink1 select * from %s where a > 100" % source) t_env.sql_update("insert into sink2 select * from %s where a < 100" % source) with self.assertRaises(TableException): t_env.explain(extended=True) def test_register_java_function(self): t_env = self.t_env t_env.register_java_function("scalar_func", "org.apache.flink.table.expressions.utils.RichFunc0") t_env.register_java_function( "agg_func", "org.apache.flink.table.functions.aggfunctions.ByteMaxAggFunction") t_env.register_java_function("table_func", "org.apache.flink.table.utils.TableFunc1") actual = t_env.list_user_defined_functions() expected = ['scalar_func', 'agg_func', 'table_func'] self.assert_equals(actual, expected) def test_create_table_environment(self): table_config = TableConfig() table_config.set_max_generated_code_length(32000) table_config.set_null_check(False) table_config.set_local_timezone("Asia/Shanghai") env = ExecutionEnvironment.get_execution_environment() t_env = BatchTableEnvironment.create(env, table_config) readed_table_config = t_env.get_config() self.assertFalse(readed_table_config.get_null_check()) self.assertEqual(readed_table_config.get_max_generated_code_length(), 32000) self.assertEqual(readed_table_config.get_local_timezone(), "Asia/Shanghai") def test_create_table_environment_with_blink_planner(self): t_env = BatchTableEnvironment.create( environment_settings=EnvironmentSettings.new_instance().in_batch_mode() .use_blink_planner().build()) planner = t_env._j_tenv.getPlanner() self.assertEqual( planner.getClass().getName(), "org.apache.flink.table.planner.delegation.BatchPlanner") def test_table_environment_with_blink_planner(self): t_env = BatchTableEnvironment.create( environment_settings=EnvironmentSettings.new_instance().in_batch_mode() .use_blink_planner().build()) source_path = os.path.join(self.tempdir + '/streaming.csv') sink_path = os.path.join(self.tempdir + '/results') field_names = ["a", "b", "c"] field_types = [DataTypes.INT(), DataTypes.STRING(), DataTypes.STRING()] data = [(1, 'hi', 'hello'), (2, 'hello', 'hello')] csv_source = self.prepare_csv_source(source_path, data, field_types, field_names) t_env.register_table_source("source", csv_source) t_env.register_table_sink( "sink", CsvTableSink(field_names, field_types, sink_path)) source = t_env.scan("source") result = source.alias("a, b, c").select("1 + a, b, c") result.insert_into("sink") t_env.execute("blink_test") results = [] for root, dirs, files in os.walk(sink_path): for sub_file in files: with open(os.path.join(root, sub_file), 'r') as f: line = f.readline() while line is not None and line != '': results.append(line) line = f.readline() self.assert_equals(results, ['2,hi,hello\n', '3,hello,hello\n'])

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0.637444

1,819

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5.017042

0.13304

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0

null

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0

1

0

null

0

6

6a777b0d489dbcbc97cb8c7cac643772c23de6f4

31

py

Python

bigbang/datasets/domains/__init__.py

datactive/bigbang

ea2e9aab156490d1af965409adb60b68291281dc

[ "MIT" ]

71

2016-10-08T18:42:39.000Z

2022-03-10T10:06:53.000Z

bigbang/datasets/domains/__init__.py

datactive/bigbang

ea2e9aab156490d1af965409adb60b68291281dc

[ "MIT" ]

307

2016-07-10T17:37:41.000Z

2022-03-31T16:39:33.000Z

bigbang/datasets/domains/__init__.py

datactive/bigbang

ea2e9aab156490d1af965409adb60b68291281dc

[ "MIT" ]

21

2016-10-07T23:49:50.000Z

2022-02-08T17:25:22.000Z

from .domains import load_data

15.5

30

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5

31

5

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1

31

0.925926

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null

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1

0

1

0

6

6a813d7ca8a73b66b6219e011c47127383933a32

21

py

Python

api_gateway/api/__init__.py

microstack/api_gateway

4fc335d14508eb2ca2c9046c89b98ee59bf0efe3

[ "MIT" ]

null

api_gateway/api/__init__.py

microstack/api_gateway

4fc335d14508eb2ca2c9046c89b98ee59bf0efe3

[ "MIT" ]

3

2016-08-08T14:42:58.000Z

2016-09-03T15:29:10.000Z

api_gateway/api/__init__.py

microstack/api_gateway

4fc335d14508eb2ca2c9046c89b98ee59bf0efe3

[ "MIT" ]

null

from . import movies

10.5

20

0.761905

3

21

5.333333

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0

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21

1

21

0.941176

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null

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1

0

1

0

1

0

6

6aa30977ac63ecd018373860d5e9b84250a1a40c

106

py

Python

testsuite/modulegraph-dir/setup.py

xoviat/modulegraph2

766d00bdb40e5b2fe206b53a87b1bce3f9dc9c2a

[ "MIT" ]

9

2020-03-22T14:48:01.000Z

2021-05-30T12:18:12.000Z

testsuite/modulegraph-dir/setup.py

xoviat/modulegraph2

766d00bdb40e5b2fe206b53a87b1bce3f9dc9c2a

[ "MIT" ]

15

2020-01-06T10:02:32.000Z

2021-05-28T12:22:44.000Z

testsuite/modulegraph-dir/setup.py

ronaldoussoren/modulegraph2

b6ab1766b0098651b51083235ff8a18a5639128b

[ "MIT" ]

4

2020-05-10T18:51:41.000Z

2021-04-07T14:03:12.000Z

from distutils import log from setuptools import Command, setup from setuptools.command import egg_info

17.666667

39

0.839623

15

106

5.866667

0.6

0.318182

0

0.141509

106

5

40

21.2

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0

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0

true

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0

null

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1

0

1

0

1

0

6

6ab32b9f60a0ccf9f8994c01714f29c1711c0428

40

py

Python

cbfa/__init__.py

pomponchik/cbfa

28250cd1b7020a3171033d05483d668ec25cd9ff

[ "MIT" ]

8

2020-11-21T23:03:42.000Z

2022-02-09T11:44:20.000Z

cbfa/__init__.py

pomponchik/cbfa

28250cd1b7020a3171033d05483d668ec25cd9ff

[ "MIT" ]

null

cbfa/__init__.py

pomponchik/cbfa

28250cd1b7020a3171033d05483d668ec25cd9ff

[ "MIT" ]

null

from cbfa.class_based import ClassBased

20

39

0.875

6

40

5.666667

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0

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1

40

0.944444

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1

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1

0

1

0

6

6acd60f640aa65a3fd155905bde9a73be459efd6

244

py

Python

tests/docs/test_scopes_example.py

adriangb/di

f277bb7189c8e8bde41170afb3181e6600b06be8

[ "MIT" ]

57

2021-09-28T00:48:08.000Z

2022-03-16T16:50:39.000Z

tests/docs/test_scopes_example.py

ScareTrow/di

a89b6b7d52da41b6e094b50ee5a500c3478676fa

[ "MIT" ]

59

2021-09-25T00:06:22.000Z

2022-03-31T15:49:36.000Z

tests/docs/test_scopes_example.py

ScareTrow/di

a89b6b7d52da41b6e094b50ee5a500c3478676fa

[ "MIT" ]

3

2021-12-31T10:03:03.000Z

2021-12-31T16:07:54.000Z

import pytest from di.exceptions import ScopeViolationError from docs_src import invalid_scope_dependance def test_invalid_scope_dependance() -> None: with pytest.raises(ScopeViolationError): invalid_scope_dependance.framework()

24.4

45

0.815574

28

244

6.821429

0.607143

0.188482

0.34555

0

0.131148

244

9

46

27.111111

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0

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0

null

0

1

0

1

0

1

0

6

6ae0ffc965f8e57b535d67908927d526087ac1f1

135

py

Python

examples/fibonacci.py

tzaffi/mock-trace

9f3df8ebf3590d5fb96f23a676c2c59258f93324

[ "MIT" ]

null

examples/fibonacci.py

tzaffi/mock-trace

9f3df8ebf3590d5fb96f23a676c2c59258f93324

[ "MIT" ]

null

examples/fibonacci.py

tzaffi/mock-trace

9f3df8ebf3590d5fb96f23a676c2c59258f93324

[ "MIT" ]

null

def slow_fib(n: int) -> int: if n < 1: return 0 if n == 1: return 1 return slow_fib(n-1) + slow_fib(n-2)

15

40

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null

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1

0

null

0

1

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6

0a920849c21bd18281caff92248479bcd4562987

407

py

Python

zvt/recorders/joinquant/__init__.py

markqiu/zvt

1bcfb71279f2652c3600f0f8e45d941f98ceaa10

[ "MIT" ]

6

2020-09-03T10:02:00.000Z

2021-02-04T02:51:47.000Z

zvt/recorders/joinquant/__init__.py

wlwd13303/zvt

23105a5bfdc3a5080c6c22d11e9e53d216688dea

[ "MIT" ]

null

zvt/recorders/joinquant/__init__.py

wlwd13303/zvt

23105a5bfdc3a5080c6c22d11e9e53d216688dea

[ "MIT" ]

2

2020-07-08T04:15:40.000Z

2021-06-08T08:51:31.000Z

# -*- coding: utf-8 -*- from zvt.recorders.joinquant.fundamental import * from zvt.recorders.joinquant.overall import * from zvt.recorders.joinquant.meta import * from zvt.recorders.joinquant.quotes import * from zvt.recorders.joinquant.finance import * from zvt.recorders.joinquant.finance_qtr import * from zvt.recorders.joinquant.trading import * from zvt.recorders.joinquant.dividend_financing import *

40.7

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0.706422

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0

0.002703

0.090909

407

9

57

45.222222

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0

1

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true

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1

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null

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1

0

null

0

1

0

1

0

1

0

6

0aee0de446f4d9ff6326a2d62e008a1933663479

62

py

Python

padertorch/data/__init__.py

thequilo/padertorch

5e7ff6c2570739a0556d7c88bb93cd77017662a2

[ "MIT" ]

null

padertorch/data/__init__.py

thequilo/padertorch

5e7ff6c2570739a0556d7c88bb93cd77017662a2

[ "MIT" ]

null

padertorch/data/__init__.py

thequilo/padertorch

5e7ff6c2570739a0556d7c88bb93cd77017662a2

[ "MIT" ]

null

from . import batch from . import utils from .batch import *

12.4

20

0.725806

9

62

5

0.444444

0

0.209677

62

4

21

15.5

0.918367

0

1

0

true

0

1

0

1

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1

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null

1

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0

null

0

1

0

1

0

1

0

6

7c40d97d51c95325a4ac774bb0a4409582a6c278

6,982

py

Python

comanage_api/_names.py

fabric-testbed/python-comanage-api

31e5f0478a907aceb966441b60cacb4fcfe1f255

[ "MIT" ]

null

comanage_api/_names.py

fabric-testbed/python-comanage-api

31e5f0478a907aceb966441b60cacb4fcfe1f255

[ "MIT" ]

6

2021-09-14T20:37:28.000Z

2021-10-12T15:35:56.000Z

comanage_api/_names.py

fabric-testbed/python-comanage-api

31e5f0478a907aceb966441b60cacb4fcfe1f255

[ "MIT" ]

null

# comanage_api/_names.py """ Name API - https://spaces.at.internet2.edu/display/COmanage/Name+API Methods ------- names_add() -> dict ### NOT IMPLEMENTED ### Add a new Name. names_delete() -> bool ### NOT IMPLEMENTED ### Remove a Name. names_edit() -> bool ### NOT IMPLEMENTED ### Edit an existing Name. names_view_all() -> dict Retrieve all existing Names. names_view_per_person(person_type: str, person_id: int) -> dict Retrieve Names attached to a CO Person or Org Identity. names_view_one(name_id: int) -> dict Retrieve Names attached to a CO Person or Org Identity. """ import json def names_add(self) -> dict: """ ### NOT IMPLEMENTED ### Add a new Name. :param self: :return 501 Server Error: Not Implemented for url: mock://not_implemented_501.local: """ url = self._MOCK_501_URL resp = self._mock_session.get( url=url ) if resp.status_code == 201: return json.loads(resp.text) else: resp.raise_for_status() def names_delete(self) -> bool: """ ### NOT IMPLEMENTED ### Remove a Name. :param self: :return 501 Server Error: Not Implemented for url: mock://not_implemented_501.local: """ url = self._MOCK_501_URL resp = self._mock_session.get( url=url ) if resp.status_code == 200: return True else: resp.raise_for_status() def names_edit(self) -> bool: """ ### NOT IMPLEMENTED ### Edit an existing Name. :param self: :return 501 Server Error: Not Implemented for url: mock://not_implemented_501.local: """ url = self._MOCK_501_URL resp = self._mock_session.get( url=url ) if resp.status_code == 200: return True else: resp.raise_for_status() def names_view_all(self) -> dict: """ Retrieve all existing Names. :param self: :return { "ResponseType":"Names", "Version":"1.0", "Names": [ { "Version":"1.0", "Id":"<ID>", "Honorific":"<Honorific>", "Given":"<Given>", "Middle":"<Middle>", "Family":"<Family>", "Suffix":"<Suffix>", "Type":"<Type>", "Language":"<Language>", "PrimaryName":true|false, "Person": { "Type":("CO"|"Org"), "Id":"<ID>" } "Created":"<CreateTime>", "Modified":"<ModTime>" }, {...} ] }: Response Format HTTP Status Response Body Description 200 OK Name Response Name returned 401 Unauthorized Authentication required 500 Other Error Unknown error """ url = self._CO_API_URL + '/names.json' resp = self._s.get( url=url ) if resp.status_code == 200: return json.loads(resp.text) else: resp.raise_for_status() def names_view_per_person(self, person_type: str, person_id: int) -> dict: """ Retrieve Names attached to a CO Person or Org Identity. :param self: :param person_type: :param person_id: :return { "ResponseType":"Names", "Version":"1.0", "Names": [ { "Version":"1.0", "Id":"<ID>", "Honorific":"<Honorific>", "Given":"<Given>", "Middle":"<Middle>", "Family":"<Family>", "Suffix":"<Suffix>", "Type":"<Type>", "Language":"<Language>", "PrimaryName":true|false, "Person": { "Type":("CO"|"Org"), "Id":"<ID>" } "Created":"<CreateTime>", "Modified":"<ModTime>" }, {...} ] }: Response Format HTTP Status Response Body Description 200 OK Name Response Name returned 401 Unauthorized Authentication required 404 CO Person Unknown id not found for CO Person 404 Org Identity Unknown id not found for Org Identity 500 Other Error Unknown error """ if not person_type: person_type = 'copersonid' else: person_type = str(person_type).lower() if person_type not in self.PERSON_OPTIONS: raise TypeError("Invalid Fields 'person_type'") url = self._CO_API_URL + '/names.json' params = {str(person_type): str(person_id)} resp = self._s.get( url=url, params=params ) if resp.status_code == 200: return json.loads(resp.text) else: resp.raise_for_status() def names_view_one(self, name_id: int) -> dict: """ Retrieve Names attached to a CO Person or Org Identity. :param self: :param name_id: :return { "ResponseType":"Names", "Version":"1.0", "Names": [ { "Version":"1.0", "Id":"<ID>", "Honorific":"<Honorific>", "Given":"<Given>", "Middle":"<Middle>", "Family":"<Family>", "Suffix":"<Suffix>", "Type":"<Type>", "Language":"<Language>", "PrimaryName":true|false, "Person": { "Type":("CO"|"Org"), "Id":"<ID>" } "Created":"<CreateTime>", "Modified":"<ModTime>" }, {...} ] }: Response Format HTTP Status Response Body Description 200 OK Name Response Name returned 401 Unauthorized Authentication required 404 Name Unknown id not found 500 Other Error Unknown error """ url = self._CO_API_URL + '/names/' + str(name_id) + '.json' resp = self._s.get( url=url ) if resp.status_code == 200: return json.loads(resp.text) else: resp.raise_for_status()

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7c8116b53c095c98cc8fbd8eb2a527148d8056b3

62

py

Python

basicts/archs/BasicMTS_arch/__init__.py

zezhishao/BasicTS

584ca6f8215a6fc9976789b600996934ba2d499e

[ "Apache-2.0" ]

3

2022-02-22T12:50:08.000Z

2022-03-13T03:38:46.000Z

basicts/archs/BasicMTS_arch/__init__.py

zezhishao/BasicTS

584ca6f8215a6fc9976789b600996934ba2d499e

[ "Apache-2.0" ]

null

basicts/archs/BasicMTS_arch/__init__.py

zezhishao/BasicTS

584ca6f8215a6fc9976789b600996934ba2d499e

[ "Apache-2.0" ]

null

from basicts.archs.BasicMTS_arch.BasicMTS_arch import BasicMTS

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py

Python

rate/admin.py

tanql/RecommendApi

80dc9ea4c531c06e66b7c0b12b7089ed0a445874

[ "MIT" ]

1

2017-10-02T18:12:28.000Z

rate/admin.py

tanql/RecommendApi

80dc9ea4c531c06e66b7c0b12b7089ed0a445874

[ "MIT" ]

null

rate/admin.py

tanql/RecommendApi

80dc9ea4c531c06e66b7c0b12b7089ed0a445874

[ "MIT" ]

null

from django.contrib import admin from .models import Rating, Movie, Genre admin.site.register(Movie) admin.site.register(Rating) admin.site.register(Genre)

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7cb852affb6db25c25c9315811d19984bf601d40

2,499

py

Python

tests/protocol/test_command_list.py

kingosticks/mopidy-mpd

b3bbbfb89e2197669eba193db3d9f5ff1a925f8c

[ "Apache-2.0" ]

68

2019-12-24T22:09:05.000Z

2022-03-06T03:56:39.000Z

tests/protocol/test_command_list.py

kingosticks/mopidy-mpd

b3bbbfb89e2197669eba193db3d9f5ff1a925f8c

[ "Apache-2.0" ]

53

2019-12-20T23:11:11.000Z

2022-01-30T11:20:41.000Z

tests/protocol/test_command_list.py

kingosticks/mopidy-mpd

b3bbbfb89e2197669eba193db3d9f5ff1a925f8c

[ "Apache-2.0" ]

21

2019-12-20T23:06:20.000Z

2022-01-20T05:43:35.000Z

from tests import protocol class CommandListsTest(protocol.BaseTestCase): def test_command_list_begin(self): response = self.send_request("command_list_begin") assert [] == response def test_command_list_end(self): self.send_request("command_list_begin") self.send_request("command_list_end") self.assertInResponse("OK") def test_command_list_end_without_start_first_is_an_unknown_command(self): self.send_request("command_list_end") self.assertEqualResponse( 'ACK [5@0] {} unknown command "command_list_end"' ) def test_command_list_with_ping(self): self.send_request("command_list_begin") assert self.dispatcher.command_list_receiving assert not self.dispatcher.command_list_ok assert [] == self.dispatcher.command_list self.send_request("ping") assert "ping" in self.dispatcher.command_list self.send_request("command_list_end") self.assertInResponse("OK") assert not self.dispatcher.command_list_receiving assert not self.dispatcher.command_list_ok assert [] == self.dispatcher.command_list def test_command_list_with_error_returns_ack_with_correct_index(self): self.send_request("command_list_begin") self.send_request("play") # Known command self.send_request("paly") # Unknown command self.send_request("command_list_end") self.assertEqualResponse('ACK [5@1] {} unknown command "paly"') def test_command_list_ok_begin(self): response = self.send_request("command_list_ok_begin") assert [] == response def test_command_list_ok_with_ping(self): self.send_request("command_list_ok_begin") assert self.dispatcher.command_list_receiving assert self.dispatcher.command_list_ok assert [] == self.dispatcher.command_list self.send_request("ping") assert "ping" in self.dispatcher.command_list self.send_request("command_list_end") self.assertInResponse("list_OK") self.assertInResponse("OK") assert not self.dispatcher.command_list_receiving assert not self.dispatcher.command_list_ok assert [] == self.dispatcher.command_list # FIXME this should also include the special handling of idle within a # command list. That is that once a idle/noidle command is found inside a # commad list, the rest of the list seems to be ignored.

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6

7cd6cdf6a2cd6331be346bee3f3304f4f7886658

36

py

Python

trafficsignrecognition/correlationfilter/__init__.py

nontas/trafficsignrecognition

dcf0c2657c14098842ee5f9b9a5cf72be8be7d52

[ "BSD-3-Clause" ]

null

trafficsignrecognition/correlationfilter/__init__.py

nontas/trafficsignrecognition

dcf0c2657c14098842ee5f9b9a5cf72be8be7d52

[ "BSD-3-Clause" ]

1

2017-03-25T10:07:28.000Z

2017-03-28T08:34:41.000Z

trafficsignrecognition/correlationfilter/__init__.py

nontas/trafficsignrecognition

dcf0c2657c14098842ee5f9b9a5cf72be8be7d52

[ "BSD-3-Clause" ]

null

from .base import CorrelationFilter

18

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6

6b0ff01b72b169b4853a197dd401f51967c898f6

30

py

Python

pyjsoncfg/__init__.py

kr-g/pyjsoncfg

a8423500e2f01dc579c78a99b1a6510085659862

[ "MIT" ]

null

pyjsoncfg/__init__.py

kr-g/pyjsoncfg

a8423500e2f01dc579c78a99b1a6510085659862

[ "MIT" ]

1

2020-05-21T02:38:52.000Z

2020-05-21T15:36:17.000Z

pyjsoncfg/__init__.py

kr-g/pyjsoncfg

a8423500e2f01dc579c78a99b1a6510085659862

[ "MIT" ]

1

2020-05-21T14:10:55.000Z

from .pyjsoncfg import Config

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6b130a6d7a74dbd90b8f961c618a524bfac5bbd1

261,132

py

Python

instances/passenger_demand/pas-20210422-1717-int16e/22.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

instances/passenger_demand/pas-20210422-1717-int16e/22.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

instances/passenger_demand/pas-20210422-1717-int16e/22.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

""" PASSENGERS """ numPassengers = 31043 passenger_arriving = ( (10, 4, 10, 7, 4, 5, 6, 5, 3, 4, 0, 0, 0, 5, 15, 5, 4, 4, 3, 0, 2, 3, 4, 1, 0, 0), # 0 (2, 10, 11, 8, 5, 3, 3, 2, 5, 2, 0, 0, 0, 9, 10, 2, 5, 6, 4, 3, 5, 2, 8, 1, 0, 0), # 1 (1, 9, 6, 9, 8, 5, 5, 4, 1, 1, 2, 2, 0, 10, 4, 8, 11, 12, 5, 4, 2, 4, 4, 2, 4, 0), # 2 (7, 14, 5, 7, 6, 4, 0, 4, 3, 1, 3, 1, 0, 6, 8, 10, 5, 9, 7, 4, 3, 1, 0, 0, 2, 0), # 3 (11, 11, 13, 8, 7, 2, 5, 3, 3, 2, 4, 0, 0, 9, 3, 2, 9, 5, 5, 4, 3, 4, 2, 5, 0, 0), # 4 (10, 10, 5, 8, 9, 8, 3, 7, 6, 0, 5, 1, 0, 8, 16, 7, 3, 8, 5, 5, 1, 3, 5, 1, 0, 0), # 5 (13, 11, 8, 7, 8, 5, 8, 5, 7, 3, 1, 2, 0, 7, 9, 10, 9, 5, 8, 1, 1, 3, 1, 2, 1, 0), # 6 (14, 9, 7, 6, 6, 1, 5, 6, 7, 3, 2, 1, 0, 12, 12, 8, 2, 11, 6, 4, 1, 4, 1, 2, 1, 0), # 7 (12, 15, 7, 13, 10, 8, 4, 2, 2, 2, 2, 3, 0, 17, 10, 11, 9, 9, 1, 8, 2, 4, 6, 0, 2, 0), # 8 (6, 18, 9, 20, 8, 2, 8, 3, 2, 1, 0, 1, 0, 11, 14, 11, 9, 12, 9, 4, 3, 8, 7, 2, 1, 0), # 9 (18, 16, 13, 13, 6, 4, 7, 4, 7, 3, 1, 0, 0, 16, 7, 13, 6, 8, 8, 4, 3, 5, 6, 6, 1, 0), # 10 (13, 12, 13, 14, 9, 5, 4, 6, 7, 4, 2, 1, 0, 13, 16, 8, 8, 10, 8, 7, 5, 5, 2, 0, 2, 0), # 11 (15, 18, 13, 13, 12, 3, 8, 7, 3, 5, 3, 0, 0, 10, 13, 7, 11, 12, 10, 5, 4, 4, 2, 1, 3, 0), # 12 (12, 11, 10, 14, 7, 11, 5, 4, 6, 9, 2, 0, 0, 12, 13, 10, 8, 13, 11, 8, 3, 6, 3, 2, 1, 0), # 13 (15, 15, 21, 13, 12, 5, 6, 8, 5, 1, 3, 1, 0, 20, 11, 9, 7, 17, 7, 6, 7, 5, 5, 2, 1, 0), # 14 (19, 14, 10, 17, 10, 5, 9, 4, 10, 3, 1, 2, 0, 18, 19, 8, 10, 15, 3, 7, 5, 4, 1, 2, 1, 0), # 15 (11, 11, 13, 11, 11, 4, 1, 8, 7, 3, 2, 1, 0, 10, 16, 8, 6, 11, 10, 2, 4, 5, 10, 3, 0, 0), # 16 (10, 11, 8, 11, 11, 4, 5, 6, 4, 4, 3, 1, 0, 29, 14, 9, 5, 11, 3, 7, 5, 4, 6, 1, 1, 0), # 17 (13, 9, 13, 15, 5, 9, 8, 5, 5, 4, 0, 1, 0, 19, 18, 9, 9, 9, 12, 8, 6, 4, 3, 5, 1, 0), # 18 (22, 22, 14, 12, 16, 6, 9, 5, 9, 5, 2, 1, 0, 14, 20, 11, 18, 18, 2, 4, 5, 7, 2, 3, 2, 0), # 19 (14, 11, 13, 12, 12, 4, 2, 4, 6, 2, 2, 3, 0, 13, 16, 14, 5, 7, 10, 5, 4, 7, 2, 5, 1, 0), # 20 (13, 26, 17, 12, 19, 5, 5, 5, 6, 8, 4, 2, 0, 16, 16, 14, 13, 12, 8, 4, 9, 4, 7, 2, 5, 0), # 21 (8, 20, 15, 4, 10, 6, 6, 4, 10, 4, 0, 0, 0, 18, 11, 12, 7, 12, 8, 9, 2, 5, 6, 3, 1, 0), # 22 (17, 21, 17, 13, 15, 5, 10, 5, 8, 3, 2, 0, 0, 17, 11, 14, 4, 14, 8, 8, 2, 7, 2, 3, 2, 0), # 23 (23, 14, 9, 14, 14, 8, 7, 7, 6, 2, 2, 1, 0, 14, 22, 9, 10, 13, 8, 4, 4, 5, 9, 1, 0, 0), # 24 (20, 12, 12, 18, 9, 5, 12, 6, 8, 1, 3, 2, 0, 18, 14, 4, 5, 10, 13, 1, 5, 7, 7, 2, 1, 0), # 25 (15, 16, 11, 15, 12, 5, 1, 5, 9, 1, 0, 0, 0, 19, 16, 7, 13, 15, 10, 7, 7, 4, 1, 1, 0, 0), # 26 (23, 16, 11, 15, 15, 4, 7, 7, 5, 4, 3, 2, 0, 13, 18, 13, 17, 11, 9, 6, 3, 5, 3, 3, 1, 0), # 27 (19, 18, 17, 18, 12, 5, 3, 5, 9, 4, 2, 0, 0, 10, 11, 13, 11, 10, 9, 10, 3, 7, 6, 3, 2, 0), # 28 (16, 11, 16, 12, 12, 8, 8, 6, 5, 4, 3, 3, 0, 9, 10, 9, 16, 12, 13, 9, 3, 7, 8, 1, 3, 0), # 29 (12, 11, 14, 17, 13, 6, 6, 6, 5, 9, 5, 2, 0, 16, 19, 12, 13, 11, 7, 2, 6, 8, 3, 2, 2, 0), # 30 (14, 23, 17, 13, 20, 6, 6, 9, 6, 3, 1, 1, 0, 19, 16, 8, 8, 10, 8, 5, 4, 9, 4, 2, 1, 0), # 31 (18, 14, 13, 14, 15, 5, 4, 6, 5, 0, 2, 3, 0, 20, 17, 7, 11, 13, 7, 5, 4, 10, 1, 6, 3, 0), # 32 (20, 22, 18, 11, 10, 1, 10, 3, 4, 8, 1, 4, 0, 25, 17, 10, 7, 10, 5, 10, 3, 9, 5, 2, 1, 0), # 33 (21, 14, 11, 19, 11, 10, 4, 10, 9, 4, 1, 1, 0, 16, 10, 20, 15, 20, 14, 9, 3, 4, 8, 3, 1, 0), # 34 (16, 22, 17, 10, 13, 3, 5, 7, 6, 4, 4, 1, 0, 18, 18, 14, 10, 14, 9, 3, 3, 10, 4, 0, 0, 0), # 35 (11, 11, 10, 17, 7, 4, 11, 5, 8, 3, 4, 1, 0, 15, 13, 18, 11, 9, 2, 8, 7, 7, 3, 4, 0, 0), # 36 (10, 24, 13, 15, 13, 4, 3, 9, 5, 5, 3, 1, 0, 13, 16, 12, 7, 12, 10, 6, 11, 12, 4, 3, 2, 0), # 37 (19, 17, 9, 11, 9, 4, 8, 4, 4, 3, 3, 1, 0, 16, 20, 16, 14, 11, 12, 3, 0, 4, 8, 3, 2, 0), # 38 (12, 18, 18, 22, 11, 3, 5, 7, 7, 4, 2, 0, 0, 13, 24, 14, 10, 13, 12, 5, 5, 6, 4, 5, 2, 0), # 39 (15, 18, 13, 16, 13, 5, 6, 7, 4, 1, 3, 2, 0, 18, 18, 10, 11, 9, 6, 12, 1, 9, 6, 4, 2, 0), # 40 (18, 16, 9, 8, 11, 5, 9, 7, 6, 3, 3, 1, 0, 17, 14, 14, 9, 13, 6, 8, 4, 8, 6, 3, 2, 0), # 41 (14, 12, 10, 14, 9, 4, 8, 7, 4, 3, 2, 0, 0, 13, 13, 9, 13, 8, 16, 4, 3, 4, 2, 2, 1, 0), # 42 (24, 16, 13, 12, 20, 8, 7, 5, 5, 3, 1, 2, 0, 18, 12, 8, 8, 13, 8, 5, 6, 9, 5, 3, 2, 0), # 43 (16, 12, 12, 14, 18, 5, 9, 8, 3, 3, 1, 2, 0, 12, 17, 10, 8, 19, 11, 8, 6, 7, 3, 4, 2, 0), # 44 (11, 18, 14, 22, 13, 4, 11, 4, 8, 1, 3, 1, 0, 19, 13, 12, 14, 14, 3, 6, 5, 6, 4, 1, 3, 0), # 45 (21, 10, 14, 15, 7, 5, 6, 5, 10, 4, 0, 5, 0, 22, 14, 12, 10, 16, 9, 7, 3, 6, 6, 2, 1, 0), # 46 (14, 22, 14, 19, 15, 3, 9, 7, 5, 3, 0, 0, 0, 12, 21, 11, 8, 11, 6, 6, 9, 10, 2, 2, 2, 0), # 47 (28, 15, 8, 15, 14, 6, 5, 9, 12, 1, 0, 1, 0, 11, 13, 6, 9, 16, 3, 6, 3, 6, 0, 2, 3, 0), # 48 (10, 18, 17, 17, 14, 6, 6, 4, 5, 6, 1, 1, 0, 18, 15, 11, 10, 12, 7, 7, 4, 4, 3, 1, 0, 0), # 49 (13, 14, 8, 20, 13, 12, 6, 5, 3, 5, 5, 0, 0, 16, 14, 11, 5, 17, 7, 7, 5, 6, 5, 5, 1, 0), # 50 (19, 17, 22, 27, 16, 4, 2, 3, 7, 4, 1, 1, 0, 19, 10, 10, 9, 11, 10, 6, 2, 5, 6, 5, 1, 0), # 51 (12, 12, 19, 11, 9, 8, 7, 7, 8, 1, 1, 3, 0, 17, 18, 9, 6, 13, 8, 5, 4, 13, 3, 2, 1, 0), # 52 (10, 15, 13, 11, 13, 5, 5, 7, 4, 2, 1, 2, 0, 15, 15, 6, 6, 16, 4, 5, 6, 6, 4, 1, 3, 0), # 53 (24, 20, 16, 13, 5, 10, 8, 11, 2, 1, 2, 0, 0, 19, 18, 13, 7, 17, 11, 7, 5, 4, 3, 0, 0, 0), # 54 (18, 18, 14, 17, 11, 6, 6, 3, 5, 4, 0, 0, 0, 11, 19, 10, 5, 13, 10, 5, 4, 6, 5, 1, 2, 0), # 55 (20, 13, 14, 20, 15, 7, 7, 2, 7, 7, 3, 0, 0, 16, 19, 11, 6, 15, 11, 4, 4, 7, 8, 4, 1, 0), # 56 (16, 13, 20, 10, 6, 8, 3, 6, 7, 1, 1, 1, 0, 19, 17, 10, 9, 14, 4, 6, 5, 9, 6, 2, 2, 0), # 57 (19, 15, 10, 20, 8, 7, 6, 9, 3, 7, 3, 0, 0, 18, 15, 6, 8, 13, 5, 7, 4, 5, 3, 7, 4, 0), # 58 (14, 10, 13, 20, 15, 5, 4, 6, 2, 1, 2, 0, 0, 20, 13, 14, 9, 16, 7, 6, 1, 9, 2, 2, 2, 0), # 59 (13, 14, 7, 15, 9, 6, 5, 5, 3, 2, 2, 3, 0, 17, 16, 11, 2, 14, 5, 10, 4, 6, 6, 1, 1, 0), # 60 (16, 16, 13, 13, 11, 9, 6, 2, 8, 3, 2, 0, 0, 18, 9, 7, 12, 18, 6, 6, 3, 6, 5, 4, 2, 0), # 61 (15, 15, 15, 6, 10, 8, 5, 4, 5, 2, 2, 3, 0, 21, 14, 7, 8, 15, 14, 5, 3, 4, 8, 3, 2, 0), # 62 (16, 8, 23, 17, 10, 5, 4, 12, 9, 2, 2, 0, 0, 13, 21, 15, 9, 19, 4, 8, 7, 3, 5, 3, 1, 0), # 63 (18, 13, 22, 10, 6, 5, 4, 4, 3, 4, 2, 2, 0, 16, 16, 9, 5, 12, 6, 7, 6, 7, 6, 3, 1, 0), # 64 (15, 14, 15, 14, 16, 6, 9, 4, 5, 2, 6, 2, 0, 16, 9, 20, 7, 14, 8, 5, 4, 7, 8, 2, 1, 0), # 65 (19, 14, 22, 15, 14, 7, 7, 6, 8, 4, 3, 1, 0, 21, 20, 11, 8, 13, 4, 8, 5, 5, 5, 4, 0, 0), # 66 (16, 17, 13, 15, 9, 6, 3, 8, 6, 1, 6, 0, 0, 16, 21, 16, 11, 13, 6, 10, 5, 8, 3, 1, 2, 0), # 67 (20, 13, 13, 17, 12, 4, 7, 9, 6, 4, 4, 6, 0, 17, 14, 7, 7, 10, 10, 6, 2, 7, 2, 4, 1, 0), # 68 (15, 21, 13, 18, 11, 10, 5, 3, 5, 4, 2, 2, 0, 16, 12, 7, 15, 15, 4, 10, 3, 5, 4, 4, 1, 0), # 69 (15, 13, 17, 8, 9, 7, 5, 2, 6, 1, 5, 0, 0, 20, 9, 14, 3, 17, 6, 10, 8, 3, 6, 1, 0, 0), # 70 (12, 16, 13, 17, 15, 11, 11, 4, 11, 6, 2, 0, 0, 15, 14, 7, 11, 10, 0, 7, 4, 6, 2, 3, 1, 0), # 71 (20, 14, 12, 15, 13, 4, 8, 5, 3, 4, 1, 3, 0, 14, 16, 15, 13, 7, 6, 12, 8, 10, 10, 3, 0, 0), # 72 (17, 16, 16, 15, 16, 8, 6, 4, 4, 3, 4, 1, 0, 21, 16, 12, 14, 19, 7, 3, 7, 6, 5, 0, 1, 0), # 73 (17, 12, 15, 12, 12, 6, 6, 6, 6, 2, 2, 0, 0, 12, 17, 10, 9, 15, 5, 2, 7, 8, 8, 3, 2, 0), # 74 (13, 10, 14, 16, 12, 10, 7, 2, 8, 2, 3, 1, 0, 20, 8, 11, 11, 14, 4, 7, 3, 5, 1, 4, 0, 0), # 75 (19, 22, 10, 17, 7, 6, 10, 5, 6, 2, 4, 1, 0, 11, 16, 11, 4, 13, 7, 8, 3, 10, 1, 5, 3, 0), # 76 (9, 16, 18, 8, 7, 8, 4, 5, 2, 2, 5, 2, 0, 19, 16, 14, 10, 17, 7, 9, 2, 4, 5, 2, 0, 0), # 77 (16, 21, 13, 7, 13, 9, 8, 4, 4, 2, 5, 0, 0, 15, 20, 13, 5, 11, 16, 7, 3, 5, 6, 3, 1, 0), # 78 (18, 10, 14, 11, 10, 8, 11, 3, 12, 1, 2, 2, 0, 16, 12, 10, 8, 9, 8, 7, 4, 7, 4, 2, 1, 0), # 79 (14, 19, 9, 16, 19, 7, 6, 8, 8, 1, 5, 1, 0, 13, 14, 5, 5, 11, 6, 3, 5, 6, 6, 2, 3, 0), # 80 (11, 13, 10, 10, 18, 4, 4, 2, 3, 1, 1, 1, 0, 13, 2, 13, 7, 11, 4, 6, 3, 3, 4, 4, 3, 0), # 81 (16, 17, 11, 12, 11, 6, 6, 4, 7, 2, 5, 0, 0, 15, 14, 14, 19, 14, 2, 5, 1, 7, 3, 4, 1, 0), # 82 (15, 13, 15, 23, 10, 6, 3, 4, 3, 0, 1, 3, 0, 14, 18, 11, 8, 11, 11, 6, 1, 10, 3, 2, 0, 0), # 83 (17, 11, 14, 17, 16, 4, 5, 4, 5, 3, 1, 0, 0, 17, 15, 13, 6, 9, 5, 2, 1, 4, 6, 1, 0, 0), # 84 (18, 14, 16, 11, 10, 4, 4, 4, 6, 2, 2, 1, 0, 14, 11, 9, 4, 9, 8, 7, 3, 9, 2, 5, 0, 0), # 85 (13, 19, 11, 15, 9, 6, 8, 4, 5, 4, 1, 4, 0, 11, 19, 8, 5, 13, 4, 8, 7, 9, 2, 3, 2, 0), # 86 (10, 11, 13, 17, 12, 5, 9, 4, 10, 4, 3, 0, 0, 17, 15, 10, 9, 9, 10, 7, 3, 8, 6, 1, 1, 0), # 87 (18, 12, 15, 16, 7, 5, 1, 2, 8, 2, 3, 4, 0, 18, 18, 9, 3, 18, 8, 8, 1, 8, 3, 5, 0, 0), # 88 (21, 15, 17, 14, 14, 5, 5, 8, 6, 2, 0, 2, 0, 15, 12, 8, 12, 15, 3, 5, 2, 5, 4, 4, 2, 0), # 89 (18, 13, 15, 9, 10, 8, 4, 7, 5, 4, 3, 0, 0, 14, 8, 11, 5, 11, 9, 4, 2, 4, 8, 5, 2, 0), # 90 (16, 12, 12, 20, 10, 6, 6, 4, 1, 2, 2, 2, 0, 17, 11, 5, 9, 12, 8, 5, 3, 4, 5, 1, 0, 0), # 91 (22, 16, 9, 14, 7, 4, 5, 4, 10, 3, 2, 1, 0, 12, 9, 10, 12, 11, 10, 3, 4, 3, 5, 2, 1, 0), # 92 (19, 13, 20, 11, 12, 6, 8, 8, 12, 1, 1, 0, 0, 18, 17, 6, 3, 11, 5, 7, 2, 9, 6, 2, 2, 0), # 93 (19, 15, 11, 21, 8, 7, 4, 1, 6, 2, 2, 0, 0, 21, 14, 10, 6, 21, 6, 7, 3, 6, 3, 4, 0, 0), # 94 (15, 15, 12, 24, 14, 6, 8, 3, 10, 3, 3, 2, 0, 24, 12, 11, 7, 10, 7, 7, 5, 6, 4, 2, 0, 0), # 95 (13, 15, 14, 9, 18, 8, 4, 4, 6, 7, 2, 0, 0, 14, 11, 5, 9, 16, 11, 5, 6, 5, 4, 1, 3, 0), # 96 (12, 7, 15, 14, 18, 5, 4, 6, 7, 2, 6, 3, 0, 19, 16, 6, 6, 19, 2, 7, 4, 4, 8, 2, 2, 0), # 97 (11, 8, 8, 9, 9, 5, 3, 4, 6, 2, 2, 1, 0, 16, 19, 12, 5, 7, 11, 5, 6, 6, 3, 2, 1, 0), # 98 (10, 13, 11, 13, 14, 4, 4, 2, 10, 3, 1, 1, 0, 16, 14, 9, 6, 13, 3, 2, 3, 6, 5, 0, 0, 0), # 99 (20, 11, 10, 14, 12, 5, 7, 3, 7, 3, 4, 1, 0, 12, 10, 12, 1, 15, 4, 8, 6, 5, 7, 1, 2, 0), # 100 (11, 10, 11, 10, 15, 5, 5, 3, 7, 1, 1, 0, 0, 16, 12, 8, 10, 15, 9, 4, 5, 2, 4, 6, 2, 0), # 101 (12, 12, 13, 11, 11, 9, 6, 6, 6, 2, 3, 1, 0, 17, 12, 9, 9, 15, 6, 5, 5, 12, 6, 1, 0, 0), # 102 (16, 18, 12, 18, 8, 7, 2, 4, 9, 1, 1, 5, 0, 15, 17, 13, 4, 16, 2, 6, 4, 4, 3, 3, 3, 0), # 103 (17, 11, 12, 11, 13, 8, 6, 3, 5, 5, 3, 1, 0, 19, 5, 9, 6, 12, 9, 5, 5, 3, 10, 1, 0, 0), # 104 (13, 15, 12, 12, 11, 9, 4, 3, 4, 1, 4, 1, 0, 16, 17, 12, 2, 16, 6, 6, 3, 6, 7, 2, 0, 0), # 105 (11, 13, 12, 14, 7, 9, 7, 8, 7, 1, 2, 1, 0, 16, 11, 8, 5, 10, 7, 4, 4, 7, 1, 2, 1, 0), # 106 (11, 8, 11, 17, 16, 5, 6, 3, 7, 1, 2, 2, 0, 11, 13, 6, 4, 13, 6, 3, 2, 6, 10, 1, 1, 0), # 107 (17, 10, 9, 15, 15, 4, 5, 4, 12, 4, 2, 1, 0, 12, 14, 9, 7, 16, 3, 6, 4, 4, 1, 6, 1, 0), # 108 (26, 11, 14, 21, 13, 5, 5, 5, 3, 1, 5, 1, 0, 17, 10, 7, 6, 8, 8, 8, 3, 5, 2, 2, 1, 0), # 109 (14, 14, 21, 20, 21, 5, 1, 4, 2, 2, 1, 3, 0, 12, 14, 12, 9, 15, 3, 5, 3, 5, 5, 3, 0, 0), # 110 (19, 16, 19, 14, 14, 8, 2, 1, 7, 2, 2, 3, 0, 20, 10, 7, 9, 11, 6, 4, 4, 3, 5, 1, 1, 0), # 111 (20, 12, 10, 9, 15, 2, 6, 4, 8, 5, 2, 1, 0, 20, 8, 7, 8, 11, 8, 5, 3, 6, 8, 2, 2, 0), # 112 (11, 13, 17, 14, 16, 9, 6, 4, 7, 3, 2, 0, 0, 14, 16, 10, 6, 11, 7, 4, 2, 6, 2, 2, 2, 0), # 113 (13, 13, 13, 10, 13, 3, 3, 1, 4, 3, 5, 1, 0, 10, 15, 6, 9, 11, 1, 7, 3, 6, 3, 2, 0, 0), # 114 (10, 14, 17, 12, 14, 8, 5, 2, 5, 4, 1, 1, 0, 17, 10, 17, 9, 9, 10, 3, 5, 8, 3, 2, 0, 0), # 115 (14, 7, 14, 14, 17, 8, 5, 6, 3, 3, 1, 0, 0, 10, 11, 10, 8, 15, 6, 5, 7, 9, 6, 3, 1, 0), # 116 (11, 15, 15, 12, 13, 5, 3, 5, 7, 2, 1, 1, 0, 18, 8, 15, 11, 7, 8, 1, 4, 6, 5, 2, 1, 0), # 117 (17, 6, 15, 11, 12, 5, 5, 2, 5, 5, 2, 1, 0, 24, 7, 10, 6, 16, 2, 6, 9, 3, 4, 1, 1, 0), # 118 (17, 16, 17, 13, 7, 5, 4, 7, 4, 0, 3, 1, 0, 15, 10, 5, 7, 9, 1, 3, 5, 4, 3, 3, 1, 0), # 119 (11, 9, 14, 14, 15, 3, 3, 2, 6, 2, 1, 0, 0, 17, 11, 8, 9, 12, 9, 1, 1, 4, 6, 1, 2, 0), # 120 (12, 12, 14, 7, 14, 5, 3, 2, 7, 2, 2, 1, 0, 12, 11, 12, 7, 6, 4, 2, 0, 5, 5, 1, 0, 0), # 121 (11, 9, 14, 14, 15, 9, 9, 3, 6, 3, 0, 1, 0, 13, 7, 4, 6, 14, 6, 10, 4, 5, 6, 0, 0, 0), # 122 (8, 14, 19, 15, 17, 2, 1, 4, 5, 2, 2, 1, 0, 18, 11, 13, 11, 6, 10, 3, 4, 8, 2, 2, 0, 0), # 123 (14, 8, 12, 16, 8, 2, 5, 2, 6, 4, 1, 0, 0, 22, 11, 7, 8, 12, 9, 5, 4, 6, 0, 1, 0, 0), # 124 (17, 13, 10, 18, 10, 4, 9, 3, 5, 3, 0, 4, 0, 23, 12, 10, 7, 20, 9, 3, 7, 7, 6, 1, 0, 0), # 125 (12, 9, 9, 7, 10, 2, 6, 3, 6, 1, 2, 1, 0, 9, 16, 4, 10, 13, 2, 1, 5, 6, 2, 3, 0, 0), # 126 (14, 11, 6, 11, 15, 3, 5, 3, 8, 1, 2, 2, 0, 12, 9, 8, 7, 5, 7, 9, 5, 7, 4, 4, 1, 0), # 127 (13, 11, 13, 12, 14, 6, 5, 5, 3, 2, 1, 1, 0, 20, 12, 12, 6, 11, 13, 3, 6, 8, 1, 5, 2, 0), # 128 (18, 7, 12, 12, 13, 2, 3, 5, 7, 0, 1, 2, 0, 15, 11, 13, 12, 15, 6, 6, 1, 6, 4, 3, 1, 0), # 129 (8, 8, 12, 17, 11, 3, 7, 2, 2, 3, 0, 0, 0, 10, 7, 9, 10, 14, 6, 1, 3, 5, 4, 2, 1, 0), # 130 (13, 10, 17, 10, 9, 5, 4, 1, 4, 3, 2, 2, 0, 14, 10, 8, 11, 15, 7, 6, 3, 5, 2, 0, 0, 0), # 131 (22, 6, 13, 10, 11, 4, 9, 5, 10, 2, 3, 0, 0, 11, 15, 4, 7, 12, 13, 4, 2, 3, 5, 2, 2, 0), # 132 (8, 18, 15, 11, 13, 6, 4, 6, 11, 3, 0, 3, 0, 13, 13, 10, 11, 7, 7, 3, 5, 4, 2, 1, 0, 0), # 133 (14, 17, 10, 8, 11, 2, 8, 5, 7, 2, 3, 3, 0, 13, 8, 11, 8, 11, 4, 2, 3, 3, 3, 0, 1, 0), # 134 (7, 10, 11, 14, 7, 15, 7, 3, 3, 2, 0, 0, 0, 15, 6, 10, 4, 9, 3, 3, 6, 6, 6, 1, 1, 0), # 135 (13, 11, 9, 6, 10, 2, 0, 4, 4, 4, 2, 0, 0, 15, 9, 10, 7, 11, 3, 5, 1, 10, 1, 2, 0, 0), # 136 (15, 7, 11, 9, 10, 2, 2, 3, 4, 4, 1, 0, 0, 14, 14, 5, 3, 11, 6, 6, 4, 4, 5, 2, 2, 0), # 137 (6, 11, 14, 15, 9, 7, 4, 2, 0, 0, 3, 0, 0, 7, 12, 8, 8, 12, 3, 5, 4, 4, 1, 1, 1, 0), # 138 (10, 8, 13, 7, 11, 3, 4, 7, 5, 2, 3, 0, 0, 18, 13, 4, 8, 8, 3, 3, 3, 3, 6, 5, 2, 0), # 139 (14, 16, 13, 12, 13, 3, 0, 3, 6, 1, 2, 1, 0, 10, 7, 5, 7, 8, 5, 1, 3, 8, 5, 1, 1, 0), # 140 (14, 12, 18, 10, 12, 4, 2, 2, 7, 0, 1, 0, 0, 11, 4, 12, 7, 15, 6, 5, 1, 4, 5, 4, 2, 0), # 141 (11, 9, 14, 12, 6, 6, 2, 4, 8, 2, 4, 0, 0, 17, 12, 12, 5, 9, 8, 5, 2, 6, 9, 4, 0, 0), # 142 (15, 9, 10, 16, 7, 6, 7, 2, 2, 3, 2, 1, 0, 20, 11, 13, 9, 12, 7, 1, 10, 10, 3, 2, 2, 0), # 143 (17, 11, 7, 16, 14, 6, 4, 2, 6, 0, 1, 2, 0, 14, 12, 9, 7, 17, 5, 4, 2, 4, 5, 3, 0, 0), # 144 (12, 11, 12, 13, 8, 5, 5, 5, 6, 2, 1, 0, 0, 14, 11, 6, 9, 11, 7, 4, 4, 6, 5, 3, 1, 0), # 145 (9, 7, 9, 7, 6, 5, 4, 3, 6, 2, 1, 0, 0, 20, 8, 11, 12, 10, 5, 4, 5, 6, 4, 1, 1, 0), # 146 (14, 9, 10, 13, 8, 1, 4, 2, 7, 4, 1, 0, 0, 17, 15, 6, 6, 12, 5, 3, 4, 5, 3, 3, 0, 0), # 147 (12, 4, 8, 16, 10, 4, 5, 4, 5, 1, 1, 1, 0, 11, 7, 7, 6, 13, 3, 2, 3, 3, 3, 2, 2, 0), # 148 (13, 11, 17, 12, 8, 3, 5, 3, 4, 3, 4, 2, 0, 16, 8, 11, 4, 13, 4, 4, 3, 5, 3, 2, 1, 0), # 149 (10, 7, 19, 10, 8, 4, 7, 4, 6, 1, 3, 0, 0, 13, 10, 10, 8, 12, 5, 3, 4, 9, 3, 2, 0, 0), # 150 (16, 10, 7, 11, 11, 3, 5, 9, 3, 2, 2, 0, 0, 16, 5, 9, 6, 9, 2, 1, 1, 5, 6, 6, 0, 0), # 151 (11, 12, 6, 12, 9, 2, 3, 5, 5, 2, 1, 2, 0, 7, 9, 3, 4, 12, 6, 2, 4, 7, 5, 5, 0, 0), # 152 (11, 6, 10, 9, 8, 3, 3, 3, 7, 4, 1, 0, 0, 11, 14, 2, 11, 12, 4, 4, 8, 5, 4, 1, 0, 0), # 153 (14, 11, 7, 12, 12, 5, 7, 8, 7, 3, 2, 1, 0, 9, 15, 14, 4, 2, 7, 4, 6, 1, 5, 6, 2, 0), # 154 (11, 9, 10, 9, 14, 8, 5, 3, 3, 1, 1, 1, 0, 15, 11, 3, 6, 10, 4, 6, 3, 5, 6, 2, 0, 0), # 155 (14, 7, 14, 15, 8, 9, 5, 2, 5, 1, 4, 2, 0, 7, 10, 8, 3, 10, 5, 5, 4, 1, 5, 0, 1, 0), # 156 (10, 11, 13, 14, 6, 13, 3, 1, 7, 3, 0, 2, 0, 15, 10, 13, 5, 18, 5, 4, 2, 7, 4, 8, 1, 0), # 157 (14, 9, 7, 12, 7, 7, 3, 4, 7, 3, 3, 1, 0, 16, 11, 5, 4, 11, 8, 2, 3, 5, 9, 2, 0, 0), # 158 (11, 10, 9, 13, 14, 4, 3, 2, 2, 5, 0, 0, 0, 19, 6, 5, 5, 10, 5, 3, 2, 6, 7, 4, 2, 0), # 159 (8, 6, 11, 10, 13, 7, 3, 5, 6, 4, 0, 1, 0, 13, 10, 2, 3, 8, 8, 5, 4, 6, 2, 6, 0, 0), # 160 (6, 8, 15, 12, 9, 8, 3, 3, 8, 2, 1, 1, 0, 15, 7, 11, 3, 14, 6, 3, 4, 6, 1, 3, 1, 0), # 161 (12, 9, 14, 5, 10, 2, 3, 6, 2, 2, 1, 1, 0, 5, 13, 11, 2, 9, 4, 4, 1, 5, 2, 0, 0, 0), # 162 (8, 7, 8, 18, 5, 4, 3, 5, 1, 1, 0, 2, 0, 14, 6, 9, 3, 8, 5, 3, 3, 3, 2, 3, 1, 0), # 163 (13, 11, 7, 7, 10, 3, 5, 5, 5, 1, 1, 0, 0, 3, 8, 7, 5, 11, 3, 1, 3, 6, 6, 1, 1, 0), # 164 (16, 16, 6, 15, 7, 3, 2, 3, 3, 1, 0, 3, 0, 14, 19, 7, 7, 10, 3, 1, 5, 3, 1, 1, 2, 0), # 165 (13, 6, 8, 13, 16, 2, 4, 9, 4, 0, 1, 0, 0, 8, 8, 4, 4, 7, 5, 2, 5, 5, 5, 1, 0, 0), # 166 (10, 10, 9, 6, 7, 2, 1, 2, 5, 2, 3, 1, 0, 10, 12, 12, 6, 3, 4, 4, 5, 5, 1, 1, 0, 0), # 167 (11, 6, 6, 10, 12, 2, 1, 4, 6, 2, 2, 2, 0, 14, 13, 7, 7, 10, 2, 3, 5, 7, 4, 0, 0, 0), # 168 (17, 3, 5, 9, 7, 4, 2, 2, 5, 2, 0, 0, 0, 16, 9, 7, 5, 11, 4, 0, 4, 5, 7, 0, 0, 0), # 169 (10, 8, 8, 11, 6, 4, 2, 3, 5, 3, 1, 1, 0, 8, 10, 3, 4, 12, 3, 5, 2, 1, 3, 2, 0, 0), # 170 (6, 4, 4, 4, 5, 4, 3, 2, 2, 0, 0, 1, 0, 7, 6, 6, 2, 9, 4, 2, 4, 5, 3, 1, 0, 0), # 171 (8, 6, 14, 3, 8, 6, 2, 2, 5, 0, 1, 1, 0, 12, 5, 4, 3, 10, 1, 2, 2, 0, 5, 2, 1, 0), # 172 (12, 7, 11, 8, 6, 6, 4, 1, 4, 1, 0, 0, 0, 9, 10, 5, 2, 11, 3, 3, 2, 5, 2, 0, 0, 0), # 173 (6, 6, 9, 5, 5, 3, 3, 0, 3, 2, 0, 0, 0, 9, 9, 2, 2, 11, 2, 6, 4, 7, 2, 2, 1, 0), # 174 (4, 6, 6, 4, 9, 3, 3, 1, 6, 1, 1, 0, 0, 7, 7, 7, 4, 9, 6, 0, 2, 4, 2, 2, 1, 0), # 175 (7, 4, 10, 6, 4, 3, 2, 1, 4, 0, 0, 0, 0, 7, 15, 5, 2, 6, 2, 4, 1, 4, 3, 4, 0, 0), # 176 (7, 1, 2, 4, 4, 0, 2, 2, 2, 0, 0, 0, 0, 9, 6, 2, 6, 3, 3, 2, 3, 2, 0, 2, 0, 0), # 177 (3, 2, 5, 3, 3, 0, 5, 3, 4, 0, 2, 0, 0, 3, 4, 5, 6, 4, 3, 5, 1, 2, 1, 5, 1, 0), # 178 (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 179 ) station_arriving_intensity = ( (8.033384925394829, 8.840461695509067, 8.33805316738001, 9.943468438181492, 8.887496972175379, 5.021847891259743, 6.6336569845982645, 7.445081876767077, 9.744158499468812, 6.332824024835792, 6.728424262216965, 7.836664125289878, 8.134208340125381), # 0 (8.566923443231959, 9.424097110631614, 8.888554546128244, 10.600230805242587, 9.475984539958779, 5.353573734468089, 7.07115030602191, 7.9352219566491335, 10.387592522132655, 6.75036910764344, 7.172953817529811, 8.353946657302968, 8.671666635903767), # 1 (9.09875681436757, 10.005416273425567, 9.436867656875862, 11.254380327463672, 10.062340757999591, 5.683976183219912, 7.506909612737127, 8.423400396647072, 11.028458891004078, 7.166262040032874, 7.615717038042101, 8.869172243284888, 9.206983725135505), # 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1 (13, 23, 27, 24, 17, 13, 14, 11, 9, 7, 2, 2, 0, 24, 29, 15, 20, 22, 12, 7, 9, 9, 16, 4, 4, 0), # 2 (20, 37, 32, 31, 23, 17, 14, 15, 12, 8, 5, 3, 0, 30, 37, 25, 25, 31, 19, 11, 12, 10, 16, 4, 6, 0), # 3 (31, 48, 45, 39, 30, 19, 19, 18, 15, 10, 9, 3, 0, 39, 40, 27, 34, 36, 24, 15, 15, 14, 18, 9, 6, 0), # 4 (41, 58, 50, 47, 39, 27, 22, 25, 21, 10, 14, 4, 0, 47, 56, 34, 37, 44, 29, 20, 16, 17, 23, 10, 6, 0), # 5 (54, 69, 58, 54, 47, 32, 30, 30, 28, 13, 15, 6, 0, 54, 65, 44, 46, 49, 37, 21, 17, 20, 24, 12, 7, 0), # 6 (68, 78, 65, 60, 53, 33, 35, 36, 35, 16, 17, 7, 0, 66, 77, 52, 48, 60, 43, 25, 18, 24, 25, 14, 8, 0), # 7 (80, 93, 72, 73, 63, 41, 39, 38, 37, 18, 19, 10, 0, 83, 87, 63, 57, 69, 44, 33, 20, 28, 31, 14, 10, 0), # 8 (86, 111, 81, 93, 71, 43, 47, 41, 39, 19, 19, 11, 0, 94, 101, 74, 66, 81, 53, 37, 23, 36, 38, 16, 11, 0), # 9 (104, 127, 94, 106, 77, 47, 54, 45, 46, 22, 20, 11, 0, 110, 108, 87, 72, 89, 61, 41, 26, 41, 44, 22, 12, 0), # 10 (117, 139, 107, 120, 86, 52, 58, 51, 53, 26, 22, 12, 0, 123, 124, 95, 80, 99, 69, 48, 31, 46, 46, 22, 14, 0), # 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177 (2494, 2232, 2216, 2292, 1966, 955, 920, 802, 1014, 461, 353, 201, 0, 2618, 2257, 1663, 1349, 2113, 1146, 898, 689, 1013, 762, 435, 194, 0), # 178 (2494, 2232, 2216, 2292, 1966, 955, 920, 802, 1014, 461, 353, 201, 0, 2618, 2257, 1663, 1349, 2113, 1146, 898, 689, 1013, 762, 435, 194, 0), # 179 ) passenger_arriving_rate = ( (8.033384925394829, 8.103756554216645, 6.9483776394833425, 7.45760132863612, 5.924997981450252, 2.9294112699015167, 3.3168284922991322, 3.102117448652949, 3.2480528331562706, 1.5832060062089484, 1.1214040437028276, 0.6530553437741565, 0.0, 8.134208340125381, 7.183608781515721, 5.607020218514138, 4.749618018626844, 6.496105666312541, 4.342964428114128, 3.3168284922991322, 2.0924366213582264, 2.962498990725126, 2.4858671095453735, 1.3896755278966686, 0.7367051412924223, 0.0), # 0 (8.566923443231959, 8.638755684745645, 7.407128788440204, 7.95017310393194, 6.317323026639185, 3.122918011773052, 3.535575153010955, 3.306342481937139, 3.462530840710885, 1.6875922769108604, 1.1954923029216353, 0.6961622214419141, 0.0, 8.671666635903767, 7.657784435861053, 5.9774615146081755, 5.06277683073258, 6.92506168142177, 4.628879474711995, 3.535575153010955, 2.230655722695037, 3.1586615133195926, 2.650057701310647, 1.4814257576880407, 0.7853414258859679, 0.0), # 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19 (16.01744787427533, 15.990157289287811, 13.710571576310672, 14.718192806474825, 11.748249949814339, 5.781559371346751, 6.54145578814029, 6.112032857911145, 6.409282439181973, 3.1220604865543846, 2.213506975023774, 1.2884647870137858, 0.0, 16.05619070406532, 14.17311265715164, 11.067534875118868, 9.366181459663151, 12.818564878363945, 8.556846001075604, 6.54145578814029, 4.129685265247679, 5.874124974907169, 4.9060642688249425, 2.7421143152621346, 1.4536506626625285, 0.0), # 20 (16.123095202319785, 16.080997139079486, 13.78845937933296, 14.801819636107783, 11.819944003765428, 5.8144080917165, 6.578599881585408, 6.1466960978944165, 6.445690676196012, 3.139787040360623, 2.226086065290016, 1.2957834549703726, 0.0, 16.147432484283325, 14.253618004674097, 11.13043032645008, 9.419361121081867, 12.891381352392024, 8.605374537052183, 6.578599881585408, 4.153148636940357, 5.909972001882714, 4.933939878702596, 2.757691875866592, 1.461908830825408, 0.0), # 21 (16.18558598831933, 16.12743010970541, 13.82827181383638, 14.844565540209405, 11.85945789529128, 5.83119868256461, 6.59758618660448, 6.164414114845277, 6.464300704550355, 3.148848033951298, 2.232515883656091, 1.2995243985128655, 0.0, 16.194070701678125, 14.294768383641518, 11.162579418280455, 9.446544101853892, 12.92860140910071, 8.630179760783388, 6.59758618660448, 4.1651419161175784, 5.92972894764564, 4.948188513403136, 2.7656543627672763, 1.4661300099732195, 0.0), # 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169 (9.051721035559014, 6.3648080918602945, 8.24671245092618, 8.383913300313743, 7.508111077796515, 3.7348589830137664, 2.8395318853884426, 2.870006173352032, 4.137834513104661, 1.4780023665326634, 1.1660965235200045, 0.7003360289462612, 0.0, 10.014737137259289, 7.7036963184088725, 5.830482617600023, 4.43400709959799, 8.275669026209322, 4.018008642692845, 2.8395318853884426, 2.6677564164384044, 3.7540555388982577, 2.7946377667712485, 1.649342490185236, 0.5786189174418451, 0.0), # 170 (8.7144060266056, 6.12060086437976, 7.949862747163971, 8.077966231182643, 7.23698591619222, 3.602287460082452, 2.7323336282190445, 2.7684873651590554, 3.992249464214377, 1.4232975961531957, 1.1231306424235596, 0.6747035047616515, 0.0, 9.652448572530185, 7.421738552378166, 5.615653212117798, 4.269892788459586, 7.984498928428754, 3.8758823112226777, 2.7323336282190445, 2.5730624714874657, 3.61849295809611, 2.692655410394215, 1.5899725494327943, 0.5564182603981601, 0.0), # 171 (8.368132617954185, 5.870969105593635, 7.643552333059449, 7.762917379748876, 6.9573543676460305, 3.4651989117507385, 2.6225003178960526, 2.663454158303514, 3.8415007486298056, 1.3670845149756323, 1.0789486511884518, 0.648320582564263, 0.0, 9.278900437035686, 7.1315264082068905, 5.3947432559422595, 4.101253544926896, 7.683001497259611, 3.7288358216249198, 2.6225003178960526, 2.475142079821956, 3.4786771838230153, 2.587639126582959, 1.52871046661189, 0.5337244641448761, 0.0), # 172 (8.014157008649567, 5.616753978879182, 7.328988674411616, 7.439968986705571, 6.6703103561212815, 3.3241513044079904, 2.51041737048732, 2.5553376264330825, 3.6862143809538255, 1.309570444434913, 1.0337153986384477, 0.62128721290063, 0.0, 8.89554760994954, 6.83415934190693, 5.168576993192238, 3.9287113333047383, 7.372428761907651, 3.5774726770063157, 2.51041737048732, 2.37439378886285, 3.3351551780606408, 2.479989662235191, 1.4657977348823235, 0.5106139980799257, 0.0), # 173 (7.6537353977365505, 5.358796647613667, 7.00737923701947, 7.110323292745849, 6.376947805581297, 3.179702604443573, 2.3964702020607005, 2.4445688431954404, 3.527016375789314, 1.250962705965979, 0.9875957335973142, 0.5937033463172892, 0.0, 8.503844970445494, 6.53073680949018, 4.93797866798657, 3.7528881178979363, 7.054032751578628, 3.4223963804736166, 2.3964702020607005, 2.2712161460311235, 3.1884739027906486, 2.370107764248617, 1.401475847403894, 0.4871633316012425, 0.0), # 174 (7.288123984259929, 5.097938275174352, 6.679931486682011, 6.7751825385628415, 6.078360639989406, 3.0324107782468537, 2.2810442286840464, 2.331578882238264, 3.36453274773915, 1.19146862100377, 0.9407545048888186, 0.5656689333607753, 0.0, 8.105247397697292, 6.222358266968527, 4.703772524444093, 3.574405863011309, 6.7290654954783, 3.26421043513357, 2.2810442286840464, 2.1660076987477526, 3.039180319994703, 2.2583941795209475, 1.3359862973364023, 0.46344893410675936, 0.0), # 175 (6.91857896726451, 4.835020024938507, 6.347852889198238, 6.435748964849671, 5.775642783308939, 2.882833792207196, 2.164524866425212, 2.216798817209233, 3.199389511406209, 1.131295510983227, 0.8933565613367281, 0.537283924577624, 0.0, 7.701209770878679, 5.910123170353863, 4.46678280668364, 3.39388653294968, 6.398779022812418, 3.103518344092926, 2.164524866425212, 2.0591669944337117, 2.8878213916544695, 2.1452496549498905, 1.2695705778396478, 0.4395472749944098, 0.0), # 176 (6.546356545795092, 4.570883060283395, 6.012350910367152, 6.093224812299459, 5.469888159503225, 2.731529612713966, 2.0472975313520503, 2.100659721756022, 3.0322126813933705, 1.07065069733929, 0.8455667517648098, 0.5086482705143706, 0.0, 7.2931869691634, 5.595130975658075, 4.227833758824048, 3.211952092017869, 6.064425362786741, 2.9409236104584306, 2.0472975313520503, 1.9510925805099755, 2.7349440797516125, 2.0310749374331536, 1.2024701820734305, 0.4155348236621269, 0.0), # 177 (6.172712918896475, 4.306368544586282, 5.6746330159877525, 5.74881232160534, 5.162190692535588, 2.5790562061565305, 1.929747639532414, 1.9835926695263104, 2.863628272303512, 1.0097415015069002, 0.7975499249968301, 0.4798619217175504, 0.0, 6.882633871725203, 5.278481138893053, 3.98774962498415, 3.0292245045207, 5.727256544607024, 2.7770297373368344, 1.929747639532414, 1.8421830043975218, 2.581095346267794, 1.916270773868447, 1.1349266031975505, 0.3914880495078438, 0.0), # 178 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 179 ) passenger_allighting_rate = ( (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 0 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 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16 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 17 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 18 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 19 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 20 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 21 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 22 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 23 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 24 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 25 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 26 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 27 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 28 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 29 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 30 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 31 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 32 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 33 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 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178 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 179 ) """ parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html """ #initial entropy entropy = 8991598675325360468762009371570610170 #index for seed sequence child child_seed_index = ( 1, # 0 21, # 1 )

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6b4b16d8b1e8f736e8f7df81c6a0153e4afcf355

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py

Python

aries_cloudagent/protocols/present_proof/v1_0/handlers/tests/test_presentation_handler.py

brianorwhatever/aries-cloudagent-python

9eb97df5956ed1156e6de353d87455b8df952483

[ "Apache-2.0" ]

null

aries_cloudagent/protocols/present_proof/v1_0/handlers/tests/test_presentation_handler.py

brianorwhatever/aries-cloudagent-python

9eb97df5956ed1156e6de353d87455b8df952483

[ "Apache-2.0" ]

22

2021-02-13T18:48:53.000Z

2021-04-27T07:29:50.000Z

aries_cloudagent/protocols/present_proof/v1_0/handlers/tests/test_presentation_handler.py

brianorwhatever/aries-cloudagent-python

9eb97df5956ed1156e6de353d87455b8df952483

[ "Apache-2.0" ]

2

2021-02-19T17:53:37.000Z

2021-02-19T17:56:48.000Z

import pytest from asynctest import ( mock as async_mock, TestCase as AsyncTestCase, ) from ......messaging.request_context import RequestContext from ......messaging.responder import MockResponder from ......transport.inbound.receipt import MessageReceipt from ...messages.presentation import Presentation from .. import presentation_handler as handler class TestPresentationHandler(AsyncTestCase): async def test_called(self): request_context = RequestContext.test_context() request_context.message_receipt = MessageReceipt() request_context.settings["debug.auto_verify_presentation"] = False with async_mock.patch.object( handler, "PresentationManager", autospec=True ) as mock_pres_mgr, async_mock.patch.object( request_context, "session", async_mock.CoroutineMock() ) as mock_session: mock_pres_mgr.return_value.receive_presentation = async_mock.CoroutineMock() request_context.message = Presentation() request_context.connection_ready = True request_context.connection_record = async_mock.MagicMock() handler_inst = handler.PresentationHandler() responder = MockResponder() await handler_inst.handle(request_context, responder) mock_pres_mgr.assert_called_once_with(mock_session.return_value) mock_pres_mgr.return_value.receive_presentation.assert_called_once_with( request_context.message, request_context.connection_record ) assert not responder.messages async def test_called_auto_verify(self): request_context = RequestContext.test_context() request_context.message_receipt = MessageReceipt() request_context.settings["debug.auto_verify_presentation"] = True with async_mock.patch.object( handler, "PresentationManager", autospec=True ) as mock_pres_mgr, async_mock.patch.object( request_context, "session", async_mock.CoroutineMock() ) as mock_session: mock_pres_mgr.return_value.receive_presentation = async_mock.CoroutineMock() mock_pres_mgr.return_value.verify_presentation = async_mock.CoroutineMock() request_context.message = Presentation() request_context.connection_ready = True request_context.connection_record = async_mock.MagicMock() handler_inst = handler.PresentationHandler() responder = MockResponder() await handler_inst.handle(request_context, responder) mock_pres_mgr.assert_called_once_with(mock_session.return_value) mock_pres_mgr.return_value.receive_presentation.assert_called_once_with( request_context.message, request_context.connection_record ) assert not responder.messages

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8618c0d99c72b492848c63677d2a8751916e0ec5

226

py

Python

app/data/entities/__all_entities__.py

lokaimoma/Bugza

93ffe344cb0be7dc4c45965f52798e02d05d320b

[ "Unlicense" ]

2

2022-02-14T23:53:00.000Z

2022-03-24T12:19:49.000Z

app/data/entities/__all_entities__.py

lokaimoma/Bugza

93ffe344cb0be7dc4c45965f52798e02d05d320b

[ "Unlicense" ]

null

app/data/entities/__all_entities__.py

lokaimoma/Bugza

93ffe344cb0be7dc4c45965f52798e02d05d320b

[ "Unlicense" ]

null

# Created by Kelvin_Clark on 1/30/2022, 10:43 PM from app.data.entities.user import User from app.data.entities.project import Project from app.data.entities.ticket import Ticket from app.data.entities.comments import Comment

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8621a03131d969a32df583614a14a2cc855c74f9

12,336

py

Python

docs/algorithms/insertion_sort.py

Mararsh/Vegetables

e582a96ba33454c1f3188080eb4719d992dad6f2

[ "Apache-2.0" ]

null

docs/algorithms/insertion_sort.py

Mararsh/Vegetables

e582a96ba33454c1f3188080eb4719d992dad6f2

[ "Apache-2.0" ]

null

docs/algorithms/insertion_sort.py

Mararsh/Vegetables

e582a96ba33454c1f3188080eb4719d992dad6f2

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ Title : Insertion Sorting Objective : Show each step of comparing and movement in intuitive way Created by: Mara Created on: 2018/3/20 19:31 """ import random import matplotlib.pyplot as plt import imageio import os ODATA = [] DATA_LENGTH = 6 def generate_data(number): while len(ODATA) < number: data = random.randint(0, number-1) if data not in ODATA: ODATA.append(data) print("\nDATA: " + str(ODATA)) def clear_pix(): for name in os.listdir(): if os.path.isfile(name): [fname, fename] = os.path.splitext(name) if fname != "ok" and (fename == ".png" or fename == ".gif"): os.remove(name) def clear_png(): for name in os.listdir(): if os.path.isfile(name): [fname, fename] = os.path.splitext(name) if fename == ".png" and fname != "ok": os.remove(name) def clear_gif(): for name in os.listdir(): if os.path.isfile(name): [fname, fename] = os.path.splitext(name) print(fname + " " + fename) if fename == ".gif": os.remove(name) def create_gif(image_list, gif_name, interval): frames = [] for image_name in image_list: frames.append(imageio.imread(image_name)) # Save them as frames into a gif imageio.mimsave(gif_name, frames, 'GIF', duration=interval) def insertion_sort_in_front(): DATA = ODATA.copy() compare_count = 0 move_count = 0; pix = 0 image_list = [] print("\n** insertion_sort_in_front") print("** This algorithm always inserts the smaller data in the front.") print("DATA: " + str(DATA)) for i in range(1, DATA_LENGTH): check_value = DATA[i] print("i=" + str(i) + " checking '" + str(check_value)+ "'") k = i-1 print(" k=" + str(k) + " comparing:'" + str(check_value) + "' and '" + str(DATA[k]) + "'") compare_count = compare_count + 1 while k>=0 and DATA[k]>check_value: tmp = DATA[k] DATA[k + 1] = tmp move_count = move_count + 1 print(" moving: '" + str(tmp) + "' to next location " + str(k+1)) print(" DATA: [", end="") for m in range(0, DATA_LENGTH): if m == k + 1: print('\033[1;33;40m', end="") print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") elif m == k: print('\033[1;33;40m', end="") print("*", end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") elif m <= i: print('\033[1;32;40m', end="") print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") else: print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("]") title = "i=" + str(i) + " checking '" + str(check_value)+ "' moving: '" + str(tmp) + "' to next location " + str(k+1) new_pix = draw_move(title, DATA, i, k+1, k, pix, True) image_list.append(new_pix) pix = pix + 1 k=k-1 if k>=0 : print(" k=" + str(k) + " comparing:'" + str(check_value) + "' and '" + str(DATA[k]) + "'") compare_count = compare_count + 1 insert_location = k+1 if insert_location != i: print(" inserting:'" + str(check_value) + "' at location " + str(insert_location)) DATA[insert_location] = check_value print(" DATA: [", end="") for m in range(0, DATA_LENGTH): if m == insert_location: print('\033[1;33;40m', end="") print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") elif m <= i: print('\033[1;32;40m', end="") print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") else: print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("]") title = "i=" + str(i) + " checking '" + str(check_value) + " inserting:'" + str(check_value) + "' at location " + str(insert_location) new_pix = draw_insertion(title, DATA, insert_location, i, pix, True) image_list.append(new_pix) pix = pix + 1 new_pix = draw_insertion("Finished!", DATA, -1, DATA_LENGTH, pix, True) image_list.append(new_pix) image_list.append("ok.png") return compare_count, move_count, image_list def set_insert_label(barlist, insert_location): index = 0 for bar in barlist: height = bar.get_height() x = bar.get_x() label = "d[" + str(index) + "]=" + str(height) if index == insert_location: label = "inserted " + label plt.text(x, 1.03 * height, label, rotation=0) index = index+1 def draw_insertion(title, data, insert_location, i, pix, is_front): plt.clf() plt.xlabel("index") plt.ylabel("data") plt.title(title) data_len = len(data) x = range(data_len) # plt.xlim(x, x) barlist = plt.bar(x, data, width=0.62) # plt.grid() set_insert_label(barlist, insert_location) for m in range(0, data_len): if m == insert_location: barlist[m].set_color('blue') elif is_front is True and m <= i: barlist[m].set_color('green') elif is_front is False and m >= i: barlist[m].set_color('green') else: barlist[m].set_color('lightgray') name = 'insertion_sort_' + str(pix) + '.png' plt.savefig(name) # plt.show() return name def set_move_label(barlist, k, blank): index = 0 for bar in barlist: height = bar.get_height() x = bar.get_x() label = "d[" + str(index) + "]=" + str(height) if index == blank: label = "d[" + str(index) + "]=*" elif index == k: label = "moved " + label plt.text(x, 1.03 * height, label, rotation=0) index = index+1 def draw_move(title, data, i, k, blank, pix, is_front): plt.clf() plt.xlabel("index") plt.ylabel("data") plt.title(title); data_len = len(data) x = range(data_len) barlist = plt.bar(x, data, width=0.5) set_move_label(barlist, k, blank) for m in range(0, data_len): if m == k: barlist[m].set_color('orange') elif m == blank: barlist[m].set_color('white') barlist[m].set_edgecolor('black') elif is_front is True and m <= i: barlist[m].set_color('green') elif is_front is False and m >= i: barlist[m].set_color('green') else: barlist[m].set_color('lightgray') name = 'insertion_sort_' + str(pix) + '.png' plt.savefig(name) # plt.show() return name def insertion_sort_in_end(): DATA = ODATA.copy() compare_count = 0 move_count = 0; pix = 0 image_list = [] print("\n** insertion_sort_in_end") print("** This algorithm always inserts the larger data in the end.") print("DATA: " + str(DATA)) for i in range(DATA_LENGTH-2, -1, -1): check_value = DATA[i] print("i=" + str(i) + " checking '" + str(check_value)+ "'") k=i+1 print(" k=" + str(k) + " comparing:'" + str(check_value) + "' and '" + str(DATA[k]) + "'") compare_count = compare_count + 1 while k<= DATA_LENGTH-1 and DATA[k] < check_value: tmp = DATA[k] DATA[k - 1] = tmp move_count = move_count + 1 print(" moving: '" + str(tmp) + "' to previous location " + str(k-1)) print(" DATA: [", end="") for m in range(0, DATA_LENGTH): if m == k - 1: print('\033[1;33;40m', end="") print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") elif m == k: print('\033[1;33;40m', end="") print("*", end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") elif m >= i: print('\033[1;32;40m', end="") print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") else: print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("]") title = "i=" + str(i) + " checking '" + str(check_value)+ "' moving: '" + str(tmp) + "' to previous location " + str(k-1) new_pix = draw_move(title, DATA, i, k-1, k, pix, False) image_list.append(new_pix) pix = pix + 1 k=k+1 if k<= DATA_LENGTH-1: compare_count = compare_count + 1 print(" k=" + str(k) + " comparing:'" + str(check_value) + "' and '" + str(DATA[k]) + "'") insert_location = k-1 if insert_location != i: print(" inserting:'" + str(check_value) + "' at location " + str(insert_location)) DATA[insert_location] = check_value print(" DATA: [", end="") for m in range(0, DATA_LENGTH): if m >= i: print('\033[1;32;40m', end="") print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") elif m == insert_location: print('\033[1;33;40m', end="") print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("\033[0m", end="") else: print(str(DATA[m]), end="") if m != (DATA_LENGTH - 1): print(", ", end="") print("]") title = "i=" + str(i) + " checking '" + str(check_value) + " inserting:'" + str(check_value) + "' at location " + str(insert_location) new_pix = draw_insertion(title, DATA, insert_location, i, pix, False) image_list.append(new_pix) pix = pix + 1 new_pix = draw_insertion("Finished!", DATA, -1, -1, pix, False) image_list.append(new_pix) image_list.append("ok.png") return compare_count, move_count, image_list if __name__ == '__main__': generate_data(DATA_LENGTH) clear_pix() compare_count, move_count, image_list = insertion_sort_in_front() print("## Data size: " + str(DATA_LENGTH)) print("## Total compared: " + str(compare_count)) print("## Total moved: " + str(move_count)) create_gif(image_list, "insertion_sort_in_front_" + str(DATA_LENGTH) + "_0.3.gif", 0.3) create_gif(image_list, "insertion_sort_in_front_" + str(DATA_LENGTH) + "_1.gif", 1) create_gif(image_list, "insertion_sort_in_front_" + str(DATA_LENGTH) + "_3.gif", 3) clear_png() compare_count, move_count, image_list = insertion_sort_in_end() print("## Data size: " + str(DATA_LENGTH)) print("## Total compared: " + str(compare_count)) print("## Total moved: " + str(move_count)) create_gif(image_list, "insertion_sort_in_end_" + str(DATA_LENGTH) + "_0.3.gif", 0.3) create_gif(image_list, "insertion_sort_in_end_" + str(DATA_LENGTH) + "_1.gif", 1) create_gif(image_list, "insertion_sort_in_end_" + str(DATA_LENGTH) + "_3.gif", 3) clear_png()

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0.024063

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0.347357

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0

null

0

1

0

null

0

6

8633b8be314a5b66f9b367c0d19c8cc664ea37ed

46

py

Python

lib/workers/__init__.py

JohnEskimSmith/jarm

fc2bcbd6fd5c6587522a97d583b3985ccdcde406

[ "BSD-3-Clause" ]

2

2020-11-28T12:22:52.000Z

2020-12-17T09:10:09.000Z

lib/workers/__init__.py

JohnEskimSmith/jarm

fc2bcbd6fd5c6587522a97d583b3985ccdcde406

[ "BSD-3-Clause" ]

null

lib/workers/__init__.py

JohnEskimSmith/jarm

fc2bcbd6fd5c6587522a97d583b3985ccdcde406

[ "BSD-3-Clause" ]

null

from .tasks import * from .factories import *

15.333333

24

0.73913

6

46

5.666667

0.666667

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0.173913

46

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0

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null

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0

1

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1

0

6

8648968722a4d09d0fe3386353ae9932ca5b539e

5,649

py

Python

tests/test_worksheet.py

aaaddress1/boobsnail

c0c2067d7271ca76ee721998d28e8c3c81a48397

[ "MIT" ]

169

2021-05-26T13:35:16.000Z

2021-09-06T08:04:19.000Z

tests/test_worksheet.py

H4xl0r/boobsnail

c0c2067d7271ca76ee721998d28e8c3c81a48397

[ "MIT" ]

2

2021-06-01T13:46:37.000Z

2021-07-12T19:06:37.000Z

tests/test_worksheet.py

H4xl0r/boobsnail

c0c2067d7271ca76ee721998d28e8c3c81a48397

[ "MIT" ]

29

2021-05-27T17:28:29.000Z

2021-09-04T19:24:50.000Z

from unittest import TestCase from excel4lib.sheet import * class TestWorksheet(TestCase): def test_column_iterate(self): worksheet = Worksheet("test.csv") worksheet.set_current_cords(1, 1) for i in range(1,10): for j in range(1, 10): worksheet.add_cell(Cell(i, j, "{}{}".format(i,j))) i = 1 for col in worksheet.column_iterate(): j = 1 for c in col[1]: self.assertEqual(str(col[1][c]), "{}{}".format(i,j), "Should be {}{}".format(i,j)) j = j + 1 i = i + 1 def test_get_cell(self): worksheet = Worksheet("test.csv") worksheet.set_current_cords(1, 1) worksheet.add_next_cell(Cell(-1, -1, "A")) worksheet.add_next_cell(Cell(-1, -1, "A")) worksheet.add_next_cell(Cell(-1, -1, "")) worksheet.add_next_cell(Cell(-1, -1, "")) worksheet.add_next_cell(Cell(-1, -1, "A")) worksheet.set_current_cords(2, 1) worksheet.add_next_cell(Cell(-1, -1, "B")) worksheet.add_next_cell(Cell(-1, -1, "B")) cell = worksheet.get_cell(1,1) self.assertEqual(str(cell), "A", "Should be: A") cell = worksheet.get_cell(10, 1) self.assertEqual(cell, None, "Should be: None") def test_is_reserved(self): worksheet = Worksheet("test.csv") for i in range(1,5): worksheet.add_cell(Cell(1,i)) self.assertEqual(worksheet.is_reserved(1, 1, 2), True, "Should be True") self.assertEqual(worksheet.is_reserved(2, 1, 2), False, "Should be False") for i in range(8,12): worksheet.add_cell(Cell(1,i)) self.assertEqual(worksheet.is_reserved(6, 8, 2), False, "Should be False") def test_add_next_cell(self): worksheet = Worksheet("test.csv") worksheet.set_current_cords(1,1) worksheet.add_next_cell(Cell(-1,-1,"A")) worksheet.add_next_cell(Cell(-1, -1, "A")) worksheet.add_next_cell(Cell(-1, -1, "")) worksheet.add_next_cell(Cell(-1, -1, "")) worksheet.add_next_cell(Cell(-1, -1, "A")) worksheet.set_current_cords(2, 1) worksheet.add_next_cell(Cell(-1, -1, "B")) worksheet.add_next_cell(Cell(-1, -1, "B")) csv = worksheet.to_csv() val = """A;B;\nA;B;\n;;\n;;\nA;;\n""" self.assertEqual(csv, val, "Should be: {}".format(val)) def test_add_cell(self): worksheet = Worksheet("test.csv") worksheet.add_cell(Cell(1,1, "A")) worksheet.add_cell(Cell(2,1, "B")) worksheet.add_cell(Cell(1,2, "A")) worksheet.add_cell(Cell(2,2, "B")) worksheet.add_cell(Cell(1,5, "A")) csv = worksheet.to_csv() val = """A;B;\nA;B;\n;;\n;;\nA;;\n""" self.assertEqual(csv, val, "Should be: {}".format(val)) def test_replace_cell(self): worksheet = Worksheet("test.csv") worksheet.add_cell(Cell(1,1, "A")) worksheet.add_cell(Cell(2,1, "B")) worksheet.add_cell(Cell(1,2, "A")) worksheet.add_cell(Cell(2,2, "B")) c = Cell(1,5, "A") c2 = Cell(1,5, "C") worksheet.add_cell(c) worksheet.replace_cell(c, c2) csv = worksheet.to_csv() val = """A;B;\nA;B;\n;;\n;;\nC;;\n""" self.assertEqual(csv, val, "Should be: {}".format(val)) def test_add_above(self): worksheet = Worksheet("test.csv") # Cell is in first row c = Cell(1, 1, "A") worksheet.add_cell(c) worksheet.add_above(Cell(1,1, "B"), c) csv = worksheet.to_csv() val = """B;\nA;\n""" self.assertEqual(csv, val, "Should be: {}".format(val)) # Cell above is empty worksheet = Worksheet("test.csv") c = Cell(1, 2, "A") worksheet.add_cell(c) worksheet.add_above(Cell(1,1, "B"), c) csv = worksheet.to_csv() val = """B;\nA;\n""" self.assertEqual(csv, val, "Should be: {}".format(val)) # Cell above is reserved but below is not worksheet = Worksheet("test.csv") c = Cell(1, 2, "A") worksheet.add_cell(c) worksheet.add_cell(Cell(1, 1, "A")) worksheet.add_above(Cell(1,2, "B"), c) csv = worksheet.to_csv() val = """A;\nB;\nA;\n""" self.assertEqual(csv, val, "Should be: {}".format(val)) # Cell above and below are reserved worksheet = Worksheet("test.csv") c = Cell(1, 2, "A") worksheet.add_cell(c) worksheet.add_cell(Cell(1, 1, "A")) worksheet.add_cell(Cell(1, 3, "A")) worksheet.add_above(Cell(1,2, "B"), c) csv = worksheet.to_csv() val = """A;\nB;\nA;\nA;\n""" self.assertEqual(csv, val, "Should be: {}".format(val)) # Cell above and below are reserved worksheet = Worksheet("test.csv") c = Cell(1, 2, "A") worksheet.add_cell(c) worksheet.add_cell(Cell(1, 1, "A")) worksheet.add_cell(Cell(1, 3, "A")) worksheet.add_cell(Cell(1, 4, "A")) worksheet.add_cell(Cell(1, 6, "A")) worksheet.add_above(Cell(1,2, "B"), c) csv = worksheet.to_csv() val = """A;\nB;\nA;\nA;\nA;\nA;\n""" self.assertEqual(csv, val, "Should be: {}".format(val)) def test_remove_cell(self): worksheet = Worksheet("test.csv") c = Cell(1, 1, "A") worksheet.add_cell(c) c = worksheet.get_cell(1,1) self.assertEqual(str(c), "A", "Should be A") worksheet.remove_cell(c) c = worksheet.get_cell(1, 1) self.assertEqual(c, None, "Should be None")

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false

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0

null

0

1

0

null

0

6

864cacf0a3f71f6d071e8b72ebf7ce01bf827681

8,060

py

Python

gamd/langevin/dual_boost_integrators.py

MiaoLab20/GaMD-OpenMM

22c641b0a684cdd5c756f47aa6a64d8f962d65fc

[ "MIT" ]

14

2021-05-28T21:09:41.000Z

2022-01-25T08:47:51.000Z

gamd/langevin/dual_boost_integrators.py

pablo-arantes/GaMD-OpenMM

5cf53b1525f0b25f2a07d0fc29fa77d3e39455aa

[ "MIT" ]

5

2021-04-12T15:15:28.000Z

2021-04-12T16:18:45.000Z

gamd/langevin/dual_boost_integrators.py

pablo-arantes/GaMD-OpenMM

5cf53b1525f0b25f2a07d0fc29fa77d3e39455aa

[ "MIT" ]

6

2021-09-07T10:25:19.000Z

2021-11-07T17:57:51.000Z

from abc import ABC from gamd.langevin.base_integrator import GroupBoostIntegrator from simtk import unit as unit from ..stage_integrator import BoostType from ..stage_integrator import BoostMethod from ..stage_integrator import ComputeType class DualBoostIntegrator(GroupBoostIntegrator, ABC): def __init__(self, group, dt, ntcmdprep, ntcmd, ntebprep, nteb, nstlim, ntave, sigma0p, sigma0d, collision_rate, temperature, restart_filename): """ Parameters ---------- :param group: The system group provided used by OpenMM for the Dihedral Energy and Forces. :param dt: The Amount of time between each time step. :param ntcmdprep: The number of conventional MD steps for system equilibration. :param ntcmd: The total number of conventional MD steps (including ntcmdprep). (must be a multiple of ntave) :param ntebprep: The number of GaMD pre-equilibration steps. :param nteb: The number of GaMD equilibration steps (including ntebprep). (must be a multiple of ntave) :param nstlim: The total number of simulation steps. :param ntave: The number of steps used to smooth the average and sigma of potential energy (corresponds to a running average window size). :param sigma0p: The upper limit of the standard deviation of the potential boost that allows for accurate reweighting. Applies to the total boost portion. :param sigma0d: The upper limit of the standard deviation of the potential boost that allows for accurate reweighting. Applies to the dihedral boost portion. :param collision_rate: Collision rate (gamma) compatible with 1/picoseconds, default: 1.0/unit.picoseconds :param temperature: "Bath" temperature value compatible with units.kelvin, default: 298.15*unit.kelvin :param restart_filename: The file name of the restart file. (default=None indicates new simulation.) """ group_dict = {group: "Dihedral"} super(DualBoostIntegrator, self).__init__(group_dict, BoostType.DUAL_TOTAL_DIHEDRAL, BoostMethod.DUAL_DEPENDENT_GROUP_TOTAL, dt, ntcmdprep, ntcmd, ntebprep, nteb, nstlim, ntave, collision_rate, temperature, restart_filename) self.addGlobalVariable("sigma0_" + BoostType.TOTAL.value, sigma0p) self.addGlobalVariable("sigma0_" + BoostType.DIHEDRAL.value, sigma0d) class LowerBoundIntegrator(DualBoostIntegrator): def __init__(self, group, dt=2.0 * unit.femtoseconds, ntcmdprep=200000, ntcmd=1000000, ntebprep=200000, nteb=1000000, nstlim=3000000, ntave=50000, sigma0p=6.0 * unit.kilocalories_per_mole, sigma0d=6.0 * unit.kilocalories_per_mole, collision_rate=1.0 / unit.picoseconds, temperature=298.15 * unit.kelvin, restart_filename=None): """ Parameters ---------- :param group: The system group provided used by OpenMM for the Dihedral Energy and Forces. :param dt: The Amount of time between each time step. :param ntcmdprep: The number of conventional MD steps for system equilibration. :param ntcmd: The total number of conventional MD steps (including ntcmdprep). (must be a multiple of ntave) :param ntebprep: The number of GaMD pre-equilibration steps. :param nteb: The number of GaMD equilibration steps (including ntebprep). (must be a multiple of ntave) :param nstlim: The total number of simulation steps. :param ntave: The number of steps used to smooth the average and sigma of potential energy (corresponds to a running average window size). :param sigma0p: The upper limit of the standard deviation of the potential boost that allows for accurate reweighting. Applies to the total boost portion. :param sigma0d: The upper limit of the standard deviation of the potential boost that allows for accurate reweighting. Applies to the dihedral boost portion. :param collision_rate: Collision rate (gamma) compatible with 1/picoseconds, default: 1.0/unit.picoseconds :param temperature: "Bath" temperature value compatible with units.kelvin, default: 298.15*unit.kelvin :param restart_filename: The file name of the restart file. (default=None indicates new simulation.) """ self.__group = group super(LowerBoundIntegrator, self).__init__(group, dt, ntcmdprep, ntcmd, ntebprep, nteb, nstlim, ntave, sigma0p, sigma0d, collision_rate, temperature, restart_filename) def _calculate_threshold_energy_and_effective_harmonic_constant( self, compute_type): super()._lower_bound_calculate_threshold_energy_and_effective_harmonic_constant( compute_type) class UpperBoundIntegrator(DualBoostIntegrator): def __init__(self, group, dt=2.0 * unit.femtoseconds, ntcmdprep=200000, ntcmd=1000000, ntebprep=200000, nteb=1000000, nstlim=3000000, ntave=50000, sigma0p=6.0 * unit.kilocalories_per_mole, sigma0d=6.0 * unit.kilocalories_per_mole, collision_rate=1.0 / unit.picoseconds, temperature=298.15 * unit.kelvin, restart_filename=None): """ Parameters ---------- :param group: The system group provided used by OpenMM for the Dihedral Energy and Forces. :param dt: The Amount of time between each time step. :param ntcmdprep: The number of conventional MD steps for system equilibration. :param ntcmd: The total number of conventional MD steps (including ntcmdprep). (must be a multiple of ntave) :param ntebprep: The number of GaMD pre-equilibration steps. :param nteb: The number of GaMD equilibration steps (including ntebprep). (must be a multiple of ntave) :param nstlim: The total number of simulation steps. :param ntave: The number of steps used to smooth the average and sigma of potential energy (corresponds to a running average window size). :param sigma0p: The upper limit of the standard deviation of the potential boost that allows for accurate reweighting. Applies to the total boost portion. :param sigma0d: The upper limit of the standard deviation of the potential boost that allows for accurate reweighting. Applies to the dihedral boost portion. :param collision_rate: Collision rate (gamma) compatible with 1/picoseconds, default: 1.0/unit.picoseconds :param temperature: "Bath" temperature value compatible with units.kelvin, default: 298.15*unit.kelvin :param restart_filename: The file name of the restart file. (default=None indicates new simulation.) """ self.__group = group super(UpperBoundIntegrator, self).__init__(group, dt, ntcmdprep, ntcmd, ntebprep, nteb, nstlim, ntave, sigma0p, sigma0d, collision_rate, temperature, restart_filename) def _calculate_threshold_energy_and_effective_harmonic_constant( self, compute_type): super()._upper_bound_calculate_threshold_energy_and_effective_harmonic_constant( compute_type)

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project_template/PACKAGE_NAME/__init__.py

DonaldWhyte/python-package-boilerplate

99f4fde0127d1e611d4056769379182fc0b684fb

[ "MIT" ]

1

2021-06-27T22:46:16.000Z

project_template/PACKAGE_NAME/__init__.py

DonaldWhyte/python-package-boilerplate

99f4fde0127d1e611d4056769379182fc0b684fb

[ "MIT" ]

null

project_template/PACKAGE_NAME/__init__.py

DonaldWhyte/python-package-boilerplate

99f4fde0127d1e611d4056769379182fc0b684fb

[ "MIT" ]

null

"""TODO: package docstring.""" def hello(): """Say hello.""" print("Hello world!")

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Python

r6siegetracker/__init__.py

captainturtle/siege-stats

de1d6dc2a9967f5de654cb6735a0775e9fc237d8

[ "Apache-2.0" ]

10

2018-10-04T00:36:41.000Z

2021-06-06T12:30:39.000Z

r6siegetracker/__init__.py

captainturtle/siege-stats

de1d6dc2a9967f5de654cb6735a0775e9fc237d8

[ "Apache-2.0" ]

2

2018-10-04T00:37:32.000Z

2018-10-12T20:20:22.000Z

r6siegetracker/__init__.py

captainturtle/siege-stats

de1d6dc2a9967f5de654cb6735a0775e9fc237d8

[ "Apache-2.0" ]

4

2019-05-16T03:41:11.000Z

2021-06-16T19:32:21.000Z

from r6siegetracker.connect import UbiConnection from r6siegetracker.track import R6Tracker from r6siegetracker.constants import *

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Python

supar/models/dependency.py

zeeshansayyed/multiparser

f77e7c688ec51bc09f52441900fbe27c5c62f6bc

[ "MIT" ]

null

supar/models/dependency.py

zeeshansayyed/multiparser

f77e7c688ec51bc09f52441900fbe27c5c62f6bc

[ "MIT" ]

null

supar/models/dependency.py

zeeshansayyed/multiparser

f77e7c688ec51bc09f52441900fbe27c5c62f6bc

[ "MIT" ]

1

2021-09-10T14:58:02.000Z

# -*- coding: utf-8 -*- import torch import torch.nn as nn from supar.modules import (LSTM, MLP, BertEmbedding, Biaffine, CharLSTM, Triaffine) from supar.modules.dropout import IndependentDropout, SharedDropout from supar.modules.treecrf import CRF2oDependency, CRFDependency, MatrixTree from supar.utils import Config from supar.utils.alg import eisner, eisner2o, mst from supar.utils.transform import CoNLL from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence class BiaffineDependencyModel(nn.Module): r""" The implementation of Biaffine Dependency Parser. References: - Timothy Dozat and Christopher D. Manning. 2017. `Deep Biaffine Attention for Neural Dependency Parsing`_. Args: n_words (int): The size of the word vocabulary. n_feats (int): The size of the feat vocabulary. n_rels (int): The number of labels in the treebank. feat (str): Specifies which type of additional feature to use: ``'char'`` | ``'bert'`` | ``'tag'``. ``'char'``: Character-level representations extracted by CharLSTM. ``'bert'``: BERT representations, other pretrained langugae models like XLNet are also feasible. ``'tag'``: POS tag embeddings. Default: ``'char'``. n_embed (int): The size of word embeddings. Default: 100. n_feat_embed (int): The size of feature representations. Default: 100. n_char_embed (int): The size of character embeddings serving as inputs of CharLSTM, required if ``feat='char'``. Default: 50. bert (str): Specifies which kind of language model to use, e.g., ``'bert-base-cased'`` and ``'xlnet-base-cased'``. This is required if ``feat='bert'``. The full list can be found in `transformers`_. Default: ``None``. n_bert_layers (int): Specifies how many last layers to use. Required if ``feat='bert'``. The final outputs would be the weight sum of the hidden states of these layers. Default: 4. mix_dropout (float): The dropout ratio of BERT layers. Required if ``feat='bert'``. Default: .0. embed_dropout (float): The dropout ratio of input embeddings. Default: .33. n_lstm_hidden (int): The size of LSTM hidden states. Default: 400. n_lstm_layers (int): The number of LSTM layers. Default: 3. lstm_dropout (float): The dropout ratio of LSTM. Default: .33. n_mlp_arc (int): Arc MLP size. Default: 500. n_mlp_rel (int): Label MLP size. Default: 100. mlp_dropout (float): The dropout ratio of MLP layers. Default: .33. feat_pad_index (int): The index of the padding token in the feat vocabulary. Default: 0. pad_index (int): The index of the padding token in the word vocabulary. Default: 0. unk_index (int): The index of the unknown token in the word vocabulary. Default: 1. .. _Deep Biaffine Attention for Neural Dependency Parsing: https://openreview.net/forum?id=Hk95PK9le .. _transformers: https://github.com/huggingface/transformers """ def __init__(self, n_words, n_rels, n_tags=None, n_chars=None, feat='tag,char,bert', n_embed=100, n_feat_embed=100, n_char_embed=50, char_pad_index=0, bert=None, n_bert_layers=4, mix_dropout=.0, bert_pad_index=0, embed_dropout=.33, n_lstm_hidden=400, n_lstm_layers=3, lstm_dropout=.33, n_mlp_arc=500, n_mlp_rel=100, mlp_dropout=.33, pad_index=0, unk_index=1, **kwargs): super().__init__() self.args = Config().update(locals()) # the embedding layer self.word_embed = nn.Embedding(num_embeddings=n_words, embedding_dim=n_embed) self.n_input = n_embed if 'tag' in feat: self.tag_embed = nn.Embedding(num_embeddings=n_tags, embedding_dim=n_feat_embed) self.n_input += n_feat_embed if 'char' in feat: self.char_embed = CharLSTM(n_chars=n_chars, n_embed=n_char_embed, n_out=n_feat_embed, pad_index=char_pad_index) self.n_input += n_feat_embed if 'bert' in feat: self.bert_embed = BertEmbedding(model=bert, n_layers=n_bert_layers, n_out=n_feat_embed, pad_index=bert_pad_index, dropout=mix_dropout) self.n_input += self.bert_embed.n_out self.embed_dropout = IndependentDropout(p=embed_dropout) # the lstm layer self.lstm = LSTM(input_size=self.n_input, hidden_size=n_lstm_hidden, num_layers=n_lstm_layers, bidirectional=True, dropout=lstm_dropout) self.lstm_dropout = SharedDropout(p=lstm_dropout) # the MLP layers self.mlp_arc_d = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_arc, dropout=mlp_dropout) self.mlp_arc_h = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_arc, dropout=mlp_dropout) self.mlp_rel_d = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_rel, dropout=mlp_dropout) self.mlp_rel_h = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_rel, dropout=mlp_dropout) # the Biaffine layers self.arc_attn = Biaffine(n_in=n_mlp_arc, bias_x=True, bias_y=False) self.rel_attn = Biaffine(n_in=n_mlp_rel, n_out=n_rels, bias_x=True, bias_y=True) self.criterion = nn.CrossEntropyLoss() self.pad_index = pad_index self.unk_index = unk_index def load_pretrained(self, embed=None): if embed is not None: self.pretrained = nn.Embedding.from_pretrained(embed) nn.init.zeros_(self.word_embed.weight) return self def forward(self, words, feats): r""" Args: words (~torch.LongTensor): ``[batch_size, seq_len]``. Word indices. feats (~torch.LongTensor): Feat indices. If feat is ``'char'`` or ``'bert'``, the size of feats should be ``[batch_size, seq_len, fix_len]``. if ``'tag'``, the size is ``[batch_size, seq_len]``. Returns: ~torch.Tensor, ~torch.Tensor: The first tensor of shape ``[batch_size, seq_len, seq_len]`` holds scores of all possible arcs. The second of shape ``[batch_size, seq_len, seq_len, n_labels]`` holds scores of all possible labels on each arc. """ batch_size, seq_len = words.shape # get the mask and lengths of given batch mask = words.ne(self.pad_index) ext_words = words # set the indices larger than num_embeddings to unk_index if hasattr(self, 'pretrained'): ext_mask = words.ge(self.word_embed.num_embeddings) ext_words = words.masked_fill(ext_mask, self.unk_index) # get outputs from embedding layers word_embed = self.word_embed(ext_words) if hasattr(self, 'pretrained'): word_embed += self.pretrained(words) feat_embeds = [] if 'tag' in self.args.feat: feat_embeds.append(self.tag_embed(feats.pop())) if 'char' in self.args.feat: feat_embeds.append(self.char_embed(feats.pop(0))) if 'bert' in self.args.feat: feat_embeds.append(self.bert_embed(feats.pop(0))) if 'lemma' in self.args.feat: feat_embeds.append(self.lemma_embed(feats.pop(0))) if len(feat_embeds) > 0: word_embed, feat_embed = self.embed_dropout(word_embed, torch.cat(feat_embeds, -1)) # concatenate the word and feat representations embed = torch.cat((word_embed, feat_embed), -1) else: word_embed = self.embed_dropout(word_embed) embed = torch.cat((word_embed), -1) x = pack_padded_sequence(embed, mask.sum(1), True, False) x, _ = self.lstm(x) x, _ = pad_packed_sequence(x, True, total_length=seq_len) x = self.lstm_dropout(x) # apply MLPs to the BiLSTM output states arc_d = self.mlp_arc_d(x) arc_h = self.mlp_arc_h(x) rel_d = self.mlp_rel_d(x) rel_h = self.mlp_rel_h(x) # [batch_size, seq_len, seq_len] s_arc = self.arc_attn(arc_d, arc_h) # [batch_size, seq_len, seq_len, n_rels] s_rel = self.rel_attn(rel_d, rel_h).permute(0, 2, 3, 1) # set the scores that exceed the length of each sentence to -inf s_arc.masked_fill_(~mask.unsqueeze(1), float('-inf')) return s_arc, s_rel def loss(self, s_arc, s_rel, arcs, rels, mask, partial=False): r""" Args: s_arc (~torch.Tensor): ``[batch_size, seq_len, seq_len]``. Scores of all possible arcs. s_rel (~torch.Tensor): ``[batch_size, seq_len, seq_len, n_labels]``. Scores of all possible labels on each arc. arcs (~torch.LongTensor): ``[batch_size, seq_len]``. The tensor of gold-standard arcs. rels (~torch.LongTensor): ``[batch_size, seq_len]``. The tensor of gold-standard labels. mask (~torch.BoolTensor): ``[batch_size, seq_len]``. The mask for covering the unpadded tokens. partial (bool): ``True`` denotes the trees are partially annotated. Default: ``False``. Returns: ~torch.Tensor: The training loss. """ if partial: mask = mask & arcs.ge(0) s_arc, arcs = s_arc[mask], arcs[mask] s_rel, rels = s_rel[mask], rels[mask] s_rel = s_rel[torch.arange(len(arcs)), arcs] arc_loss = self.criterion(s_arc, arcs) rel_loss = self.criterion(s_rel, rels) return arc_loss + rel_loss def decode(self, s_arc, s_rel, mask, tree=False, proj=False): r""" Args: s_arc (~torch.Tensor): ``[batch_size, seq_len, seq_len]``. Scores of all possible arcs. s_rel (~torch.Tensor): ``[batch_size, seq_len, seq_len, n_labels]``. Scores of all possible labels on each arc. mask (~torch.BoolTensor): ``[batch_size, seq_len]``. The mask for covering the unpadded tokens. tree (bool): If ``True``, ensures to output well-formed trees. Default: ``False``. proj (bool): If ``True``, ensures to output projective trees. Default: ``False``. Returns: ~torch.Tensor, ~torch.Tensor: Predicted arcs and labels of shape ``[batch_size, seq_len]``. """ lens = mask.sum(1) arc_preds = s_arc.argmax(-1) bad = [not CoNLL.istree(seq[1:i+1], proj) for i, seq in zip(lens.tolist(), arc_preds.tolist())] if tree and any(bad): alg = eisner if proj else mst arc_preds[bad] = alg(s_arc[bad], mask[bad]) rel_preds = s_rel.argmax(-1).gather(-1, arc_preds.unsqueeze(-1)).squeeze(-1) return arc_preds, rel_preds class CRFNPDependencyModel(BiaffineDependencyModel): r""" The implementation of non-projective CRF Dependency Parser. References: - Xuezhe Ma and Eduard Hovy. 2017. `Neural Probabilistic Model for Non-projective MST Parsing`_. - Terry Koo, Amir Globerson, Xavier Carreras and Michael Collins. 2007. `Structured Prediction Models via the Matrix-Tree Theorem`_. Args: n_words (int): The size of the word vocabulary. n_feats (int): The size of the feat vocabulary. n_rels (int): The number of labels in the treebank. feat (str): Specifies which type of additional feature to use: ``'char'`` | ``'bert'`` | ``'tag'``. ``'char'``: Character-level representations extracted by CharLSTM. ``'bert'``: BERT representations, other pretrained langugae models like XLNet are also feasible. ``'tag'``: POS tag embeddings. Default: ``'char'``. n_embed (int): The size of word embeddings. Default: 100. n_feat_embed (int): The size of feature representations. Default: 100. n_char_embed (int): The size of character embeddings serving as inputs of CharLSTM, required if ``feat='char'``. Default: 50. bert (str): Specifies which kind of language model to use, e.g., ``'bert-base-cased'`` and ``'xlnet-base-cased'``. This is required if ``feat='bert'``. The full list can be found in `transformers`_. Default: ``None``. n_bert_layers (int): Specifies how many last layers to use. Required if ``feat='bert'``. The final outputs would be the weight sum of the hidden states of these layers. Default: 4. mix_dropout (float): The dropout ratio of BERT layers. Required if ``feat='bert'``. Default: .0. embed_dropout (float): The dropout ratio of input embeddings. Default: .33. n_lstm_hidden (int): The size of LSTM hidden states. Default: 400. n_lstm_layers (int): The number of LSTM layers. Default: 3. lstm_dropout (float): The dropout ratio of LSTM. Default: .33. n_mlp_arc (int): Arc MLP size. Default: 500. n_mlp_rel (int): Label MLP size. Default: 100. mlp_dropout (float): The dropout ratio of MLP layers. Default: .33. feat_pad_index (int): The index of the padding token in the feat vocabulary. Default: 0. pad_index (int): The index of the padding token in the word vocabulary. Default: 0. unk_index (int): The index of the unknown token in the word vocabulary. Default: 1. .. _Neural Probabilistic Model for Non-projective MST Parsing: https://www.aclweb.org/anthology/I17-1007/ .. _Structured Prediction Models via the Matrix-Tree Theorem: https://www.aclweb.org/anthology/D07-1015/ """ def __init__(self, **kwargs): super().__init__(**kwargs) self.matrix_tree = MatrixTree() def loss(self, s_arc, s_rel, arcs, rels, mask, mbr=True): r""" Args: s_arc (~torch.Tensor): ``[batch_size, seq_len, seq_len]``. Scores of all possible arcs. s_rel (~torch.Tensor): ``[batch_size, seq_len, seq_len, n_labels]``. Scores of all possible labels on each arc. arcs (~torch.LongTensor): ``[batch_size, seq_len]``. The tensor of gold-standard arcs. rels (~torch.LongTensor): ``[batch_size, seq_len]``. The tensor of gold-standard labels. mask (~torch.BoolTensor): ``[batch_size, seq_len]``. The mask for covering the unpadded tokens. mbr (bool): If ``True``, returns marginals for MBR decoding. Default: ``True``. Returns: ~torch.Tensor, ~torch.Tensor: The training loss and original arc scores of shape ``[batch_size, seq_len, seq_len]`` if ``mbr=False``, or marginals otherwise. """ batch_size, seq_len = mask.shape arc_loss, arc_probs = self.matrix_tree(s_arc, mask, arcs, mbr) s_rel, rels = s_rel[mask], rels[mask] s_rel = s_rel[torch.arange(len(rels)), arcs[mask]] rel_loss = self.criterion(s_rel, rels) loss = arc_loss + rel_loss return loss, arc_probs class CRFDependencyModel(BiaffineDependencyModel): r""" The implementation of first-order CRF Dependency Parser. References: - Yu Zhang, Zhenghua Li and Min Zhang, 2020. `Efficient Second-Order TreeCRF for Neural Dependency Parsing`_. Args: n_words (int): The size of the word vocabulary. n_feats (int): The size of the feat vocabulary. n_rels (int): The number of labels in the treebank. feat (str): Specifies which type of additional feature to use: ``'char'`` | ``'bert'`` | ``'tag'``. ``'char'``: Character-level representations extracted by CharLSTM. ``'bert'``: BERT representations, other pretrained langugae models like XLNet are also feasible. ``'tag'``: POS tag embeddings. Default: ``'char'``. n_embed (int): The size of word embeddings. Default: 100. n_feat_embed (int): The size of feature representations. Default: 100. n_char_embed (int): The size of character embeddings serving as inputs of CharLSTM, required if ``feat='char'``. Default: 50. bert (str): Specifies which kind of language model to use, e.g., ``'bert-base-cased'`` and ``'xlnet-base-cased'``. This is required if ``feat='bert'``. The full list can be found in `transformers`_. Default: ``None``. n_bert_layers (int): Specifies how many last layers to use. Required if ``feat='bert'``. The final outputs would be the weight sum of the hidden states of these layers. Default: 4. mix_dropout (float): The dropout ratio of BERT layers. Required if ``feat='bert'``. Default: .0. embed_dropout (float): The dropout ratio of input embeddings. Default: .33. n_lstm_hidden (int): The size of LSTM hidden states. Default: 400. n_lstm_layers (int): The number of LSTM layers. Default: 3. lstm_dropout (float): The dropout ratio of LSTM. Default: .33. n_mlp_arc (int): Arc MLP size. Default: 500. n_mlp_rel (int): Label MLP size. Default: 100. mlp_dropout (float): The dropout ratio of MLP layers. Default: .33. feat_pad_index (int): The index of the padding token in the feat vocabulary. Default: 0. pad_index (int): The index of the padding token in the word vocabulary. Default: 0. unk_index (int): The index of the unknown token in the word vocabulary. Default: 1. .. _Efficient Second-Order TreeCRF for Neural Dependency Parsing: https://www.aclweb.org/anthology/2020.acl-main.302/ """ def __init__(self, **kwargs): super().__init__(**kwargs) self.crf = CRFDependency() def loss(self, s_arc, s_rel, arcs, rels, mask, mbr=True, partial=False): r""" Args: s_arc (~torch.Tensor): ``[batch_size, seq_len, seq_len]``. Scores of all possible arcs. s_rel (~torch.Tensor): ``[batch_size, seq_len, seq_len, n_labels]``. Scores of all possible labels on each arc. arcs (~torch.LongTensor): ``[batch_size, seq_len]``. The tensor of gold-standard arcs. rels (~torch.LongTensor): ``[batch_size, seq_len]``. The tensor of gold-standard labels. mask (~torch.BoolTensor): ``[batch_size, seq_len]``. The mask for covering the unpadded tokens. mbr (bool): If ``True``, returns marginals for MBR decoding. Default: ``True``. partial (bool): ``True`` denotes the trees are partially annotated. Default: ``False``. Returns: ~torch.Tensor, ~torch.Tensor: The training loss and original arc scores of shape ``[batch_size, seq_len, seq_len]`` if ``mbr=False``, or marginals otherwise. """ batch_size, seq_len = mask.shape arc_loss, arc_probs = self.crf(s_arc, mask, arcs, mbr, partial) # -1 denotes un-annotated arcs if partial: mask = mask & arcs.ge(0) s_rel, rels = s_rel[mask], rels[mask] s_rel = s_rel[torch.arange(len(rels)), arcs[mask]] rel_loss = self.criterion(s_rel, rels) loss = arc_loss + rel_loss return loss, arc_probs class CRF2oDependencyModel(BiaffineDependencyModel): r""" The implementation of second-order CRF Dependency Parser. References: - Yu Zhang, Zhenghua Li and Min Zhang. 2020. `Efficient Second-Order TreeCRF for Neural Dependency Parsing`_. Args: n_words (int): The size of the word vocabulary. n_feats (int): The size of the feat vocabulary. n_rels (int): The number of labels in the treebank. feat (str): Specifies which type of additional feature to use: ``'char'`` | ``'bert'`` | ``'tag'``. ``'char'``: Character-level representations extracted by CharLSTM. ``'bert'``: BERT representations, other pretrained langugae models like XLNet are also feasible. ``'tag'``: POS tag embeddings. Default: ``'char'``. n_embed (int): The size of word embeddings. Default: 100. n_feat_embed (int): The size of feature representations. Default: 100. n_char_embed (int): The size of character embeddings serving as inputs of CharLSTM, required if ``feat='char'``. Default: 50. bert (str): Specifies which kind of language model to use, e.g., ``'bert-base-cased'`` and ``'xlnet-base-cased'``. This is required if ``feat='bert'``. The full list can be found in `transformers`_. Default: ``None``. n_bert_layers (int): Specifies how many last layers to use. Required if ``feat='bert'``. The final outputs would be the weight sum of the hidden states of these layers. Default: 4. mix_dropout (float): The dropout ratio of BERT layers. Required if ``feat='bert'``. Default: .0. embed_dropout (float): The dropout ratio of input embeddings. Default: .33. n_lstm_hidden (int): The size of LSTM hidden states. Default: 400. n_lstm_layers (int): The number of LSTM layers. Default: 3. lstm_dropout (float): The dropout ratio of LSTM. Default: .33. n_mlp_arc (int): Arc MLP size. Default: 500. n_mlp_sib (int): Sibling MLP size. Default: 100. n_mlp_rel (int): Label MLP size. Default: 100. mlp_dropout (float): The dropout ratio of MLP layers. Default: .33. feat_pad_index (int): The index of the padding token in the feat vocabulary. Default: 0. pad_index (int): The index of the padding token in the word vocabulary. Default: 0. unk_index (int): The index of the unknown token in the word vocabulary. Default: 1. .. _Efficient Second-Order TreeCRF for Neural Dependency Parsing: https://www.aclweb.org/anthology/2020.acl-main.302/ """ def __init__(self, n_words, n_feats, n_rels, feat='char', n_embed=100, n_feat_embed=100, n_char_embed=50, bert=None, n_bert_layers=4, mix_dropout=.0, embed_dropout=.33, n_lstm_hidden=400, n_lstm_layers=3, lstm_dropout=.33, n_mlp_arc=500, n_mlp_sib=100, n_mlp_rel=100, mlp_dropout=.33, feat_pad_index=0, pad_index=0, unk_index=1, **kwargs): super().__init__(**Config().update(locals())) # the embedding layer self.word_embed = nn.Embedding(num_embeddings=n_words, embedding_dim=n_embed) if feat == 'char': self.feat_embed = CharLSTM(n_chars=n_feats, n_embed=n_char_embed, n_out=n_feat_embed, pad_index=feat_pad_index) elif feat == 'bert': self.feat_embed = BertEmbedding(model=bert, n_layers=n_bert_layers, n_out=n_feat_embed, pad_index=feat_pad_index, dropout=mix_dropout) self.n_feat_embed = self.feat_embed.n_out elif feat == 'tag': self.feat_embed = nn.Embedding(num_embeddings=n_feats, embedding_dim=n_feat_embed) else: raise RuntimeError("The feat type should be in ['char', 'bert', 'tag'].") self.embed_dropout = IndependentDropout(p=embed_dropout) # the lstm layer self.lstm = LSTM(input_size=n_embed+n_feat_embed, hidden_size=n_lstm_hidden, num_layers=n_lstm_layers, bidirectional=True, dropout=lstm_dropout) self.lstm_dropout = SharedDropout(p=lstm_dropout) # the MLP layers self.mlp_arc_d = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_arc, dropout=mlp_dropout) self.mlp_arc_h = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_arc, dropout=mlp_dropout) self.mlp_sib_s = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_sib, dropout=mlp_dropout) self.mlp_sib_d = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_sib, dropout=mlp_dropout) self.mlp_sib_h = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_sib, dropout=mlp_dropout) self.mlp_rel_d = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_rel, dropout=mlp_dropout) self.mlp_rel_h = MLP(n_in=n_lstm_hidden*2, n_out=n_mlp_rel, dropout=mlp_dropout) # the Biaffine layers self.arc_attn = Biaffine(n_in=n_mlp_arc, bias_x=True, bias_y=False) self.sib_attn = Triaffine(n_in=n_mlp_sib, bias_x=True, bias_y=True) self.rel_attn = Biaffine(n_in=n_mlp_rel, n_out=n_rels, bias_x=True, bias_y=True) self.criterion = nn.CrossEntropyLoss() self.pad_index = pad_index self.unk_index = unk_index self.crf = CRF2oDependency() def forward(self, words, feats): r""" Args: words (~torch.LongTensor): ``[batch_size, seq_len]``. Word indices. feats (~torch.LongTensor): Feat indices. If feat is ``'char'`` or ``'bert'``, the size of feats should be ``[batch_size, seq_len, fix_len]`` if ``'tag'``, the size is ``[batch_size, seq_len]``. Returns: ~torch.Tensor, ~torch.Tensor, ~torch.Tensor: Scores of all possible arcs (``[batch_size, seq_len, seq_len]``), dependent-head-sibling triples (``[batch_size, seq_len, seq_len, seq_len]``) and all possible labels on each arc (``[batch_size, seq_len, seq_len, n_labels]``). """ batch_size, seq_len = words.shape # get the mask and lengths of given batch mask = words.ne(self.pad_index) ext_words = words # set the indices larger than num_embeddings to unk_index if hasattr(self, 'pretrained'): ext_mask = words.ge(self.word_embed.num_embeddings) ext_words = words.masked_fill(ext_mask, self.unk_index) # get outputs from embedding layers word_embed = self.word_embed(ext_words) if hasattr(self, 'pretrained'): word_embed += self.pretrained(words) feat_embed = self.feat_embed(feats) word_embed, feat_embed = self.embed_dropout(word_embed, feat_embed) # concatenate the word and feat representations embed = torch.cat((word_embed, feat_embed), -1) x = pack_padded_sequence(embed, mask.sum(1), True, False) x, _ = self.lstm(x) x, _ = pad_packed_sequence(x, True, total_length=seq_len) x = self.lstm_dropout(x) # apply MLPs to the BiLSTM output states arc_d = self.mlp_arc_d(x) arc_h = self.mlp_arc_h(x) sib_s = self.mlp_sib_s(x) sib_d = self.mlp_sib_d(x) sib_h = self.mlp_sib_h(x) rel_d = self.mlp_rel_d(x) rel_h = self.mlp_rel_h(x) # [batch_size, seq_len, seq_len] s_arc = self.arc_attn(arc_d, arc_h) # [batch_size, seq_len, seq_len, seq_len] s_sib = self.sib_attn(sib_s, sib_d, sib_h).permute(0, 3, 1, 2) # [batch_size, seq_len, seq_len, n_rels] s_rel = self.rel_attn(rel_d, rel_h).permute(0, 2, 3, 1) # set the scores that exceed the length of each sentence to -inf s_arc.masked_fill_(~mask.unsqueeze(1), float('-inf')) return s_arc, s_sib, s_rel def loss(self, s_arc, s_sib, s_rel, arcs, sibs, rels, mask, mbr=True, partial=False): r""" Args: s_arc (~torch.Tensor): ``[batch_size, seq_len, seq_len]``. Scores of all possible arcs. s_sib (~torch.Tensor): ``[batch_size, seq_len, seq_len, seq_len]``. Scores of all possible dependent-head-sibling triples. s_rel (~torch.Tensor): ``[batch_size, seq_len, seq_len, n_labels]``. Scores of all possible labels on each arc. arcs (~torch.LongTensor): ``[batch_size, seq_len]``. The tensor of gold-standard arcs. sibs (~torch.LongTensor): ``[batch_size, seq_len]``. The tensor of gold-standard siblings. rels (~torch.LongTensor): ``[batch_size, seq_len]``. The tensor of gold-standard labels. mask (~torch.BoolTensor): ``[batch_size, seq_len]``. The mask for covering the unpadded tokens. mbr (bool): If ``True``, returns marginals for MBR decoding. Default: ``True``. partial (bool): ``True`` denotes the trees are partially annotated. Default: ``False``. Returns: ~torch.Tensor, ~torch.Tensor: The training loss and original arc scores of shape ``[batch_size, seq_len, seq_len]`` if ``mbr=False``, or marginals otherwise. """ batch_size, seq_len = mask.shape scores, target = (s_arc, s_sib), (arcs, sibs) arc_loss, arc_probs = self.crf(scores, mask, target, mbr, partial) # -1 denotes un-annotated arcs if partial: mask = mask & arcs.ge(0) s_rel, rels = s_rel[mask], rels[mask] s_rel = s_rel[torch.arange(len(rels)), arcs[mask]] rel_loss = self.criterion(s_rel, rels) loss = arc_loss + rel_loss return loss, arc_probs def decode(self, s_arc, s_sib, s_rel, mask, tree=False, mbr=True, proj=False): r""" Args: s_arc (~torch.Tensor): ``[batch_size, seq_len, seq_len]``. Scores of all possible arcs. s_sib (~torch.Tensor): ``[batch_size, seq_len, seq_len, seq_len]``. Scores of all possible dependent-head-sibling triples. s_rel (~torch.Tensor): ``[batch_size, seq_len, seq_len, n_labels]``. Scores of all possible labels on each arc. mask (~torch.BoolTensor): ``[batch_size, seq_len]``. The mask for covering the unpadded tokens. tree (bool): If ``True``, ensures to output well-formed trees. Default: ``False``. mbr (bool): If ``True``, performs MBR decoding. Default: ``True``. proj (bool): If ``True``, ensures to output projective trees. Default: ``False``. Returns: ~torch.Tensor, ~torch.Tensor: Predicted arcs and labels of shape ``[batch_size, seq_len]``. """ lens = mask.sum(1) arc_preds = s_arc.argmax(-1) bad = [not CoNLL.istree(seq[1:i+1], proj) for i, seq in zip(lens.tolist(), arc_preds.tolist())] if tree and any(bad): if proj and not mbr: arc_preds = eisner2o((s_arc, s_sib), mask) else: alg = eisner if proj else mst arc_preds[bad] = alg(s_arc[bad], mask[bad]) rel_preds = s_rel.argmax(-1).gather(-1, arc_preds.unsqueeze(-1)).squeeze(-1) return arc_preds, rel_preds

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null

0

6

86d128b4f23c7cf804ecb3577731faaa5386e7e1

27

py

Python

__init__.py

roadpepe/keyBinder

cea643cf79dcc8828433300dbb9a59ee2a995617

[ "Apache-2.0" ]

1

2021-08-04T00:11:17.000Z

__init__.py

MyBadProjects/keyBinder

0798e8073b2c5f98e88cc4cd3c8e670e0e9845d7

[ "Apache-2.0" ]

null

__init__.py

MyBadProjects/keyBinder

0798e8073b2c5f98e88cc4cd3c8e670e0e9845d7

[ "Apache-2.0" ]

null

from keyBinder import Bind

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null

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1

0

1

0

1

0

6

86e93ab3502625c8bd52ee6de982c88b7c44868b

3,782

py

Python

dalib/modules/domain_discriminator.py

Neronjust2017/TransferBed

eaa703a4bc10eaf6216fe1394cd272f6e75489e2

[ "MIT" ]

1

2021-07-14T02:00:08.000Z

dalib/modules/domain_discriminator.py

Neronjust2017/TransferBed

eaa703a4bc10eaf6216fe1394cd272f6e75489e2

[ "MIT" ]

null

dalib/modules/domain_discriminator.py

Neronjust2017/TransferBed

eaa703a4bc10eaf6216fe1394cd272f6e75489e2

[ "MIT" ]

null

from typing import List, Dict import torch.nn as nn __all__ = ['DomainDiscriminator'] # __all__ = ['DomainDiscriminator', 'MultiSourceDomainDiscriminator'] class DomainDiscriminator(nn.Sequential): r"""Domain discriminator model from `"Domain-Adversarial Training of Neural Networks" (ICML 2015) <https://arxiv.org/abs/1505.07818>`_ Distinguish whether the input features come from the source domain or the target domain. The source domain label is 1 and the target domain label is 0. Args: in_feature (int): dimension of the input feature hidden_size (int): dimension of the hidden features batch_norm (bool): whether use :class:`~torch.nn.BatchNorm1d`. Use :class:`~torch.nn.Dropout` if ``batch_norm`` is False. Default: True. Shape: - Inputs: (minibatch, `in_feature`) - Outputs: :math:`(minibatch, 1)` """ def __init__(self, in_feature: int, hidden_size: int, batch_norm=True): if batch_norm: super(DomainDiscriminator, self).__init__( nn.Linear(in_feature, hidden_size), nn.BatchNorm1d(hidden_size), nn.ReLU(), nn.Linear(hidden_size, hidden_size), nn.BatchNorm1d(hidden_size), nn.ReLU(), nn.Linear(hidden_size, 1), nn.Sigmoid() ) else: super(DomainDiscriminator, self).__init__( nn.Linear(in_feature, hidden_size), nn.ReLU(inplace=True), nn.Dropout(0.5), nn.Linear(hidden_size, hidden_size), nn.ReLU(inplace=True), nn.Dropout(0.5), nn.Linear(hidden_size, 1), nn.Sigmoid() ) def get_parameters(self) -> List[Dict]: return [{"params": self.parameters(), "lr": 1.}] # class MultiSourceDomainDiscriminator(nn.Sequential): # r"""Domain discriminator model from # `"Domain-Adversarial Training of Neural Networks" (ICML 2015) <https://arxiv.org/abs/1505.07818>`_ # # Distinguish whether the input features come from the source domain or the target domain. # The source domain label is 1 and the target domain label is 0. # # Args: # in_feature (int): dimension of the input feature # hidden_size (int): dimension of the hidden features # batch_norm (bool): whether use :class:`~torch.nn.BatchNorm1d`. # Use :class:`~torch.nn.Dropout` if ``batch_norm`` is False. Default: True. # # Shape: # - Inputs: (minibatch, `in_feature`) # - Outputs: :math:`(minibatch, 1)` # """ # # def __init__(self, in_feature: int, hidden_size: int, num_domains: int, batch_norm=True): # if batch_norm: # super(MultiSourceDomainDiscriminator, self).__init__( # nn.Linear(in_feature, hidden_size), # nn.BatchNorm1d(hidden_size), # nn.ReLU(), # nn.Linear(hidden_size, hidden_size), # nn.BatchNorm1d(hidden_size), # nn.ReLU(), # nn.Linear(hidden_size, num_domains), # nn.Softmax(dim=1) # ) # else: # super(MultiSourceDomainDiscriminator, self).__init__( # nn.Linear(in_feature, hidden_size), # nn.ReLU(inplace=True), # nn.Dropout(0.5), # nn.Linear(hidden_size, hidden_size), # nn.ReLU(inplace=True), # nn.Dropout(0.5), # nn.Linear(hidden_size, 1), # nn.Softmax(dim=1) # ) # # def get_parameters(self) -> List[Dict]: # return [{"params": self.parameters(), "lr": 1.}]

38.20202

104

0.574299

421

3,782

4.969121

0.2019

0.114723

0.068834

0.061185

0.891969

0.883843

0.859465

0

0.020198

0.306187

3,782

98

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0.777058

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0

null

0

1

0

null

0

6

810287f34f54dc6b2afb671e297aa3d93b2bc80a

92

py

Python

python/katana/local/graph.py

chakpongchung/katana

3278a39b504e0aeaec30d06cf629ab97dfeb3f22

[ "BSD-3-Clause" ]

64

2020-05-22T23:32:00.000Z

2022-03-18T10:42:45.000Z

python/katana/local/graph.py

chakpongchung/katana

3278a39b504e0aeaec30d06cf629ab97dfeb3f22

[ "BSD-3-Clause" ]

705

2020-02-17T20:50:38.000Z

2022-03-31T16:28:09.000Z

python/katana/local/graph.py

chakpongchung/katana

3278a39b504e0aeaec30d06cf629ab97dfeb3f22

[ "BSD-3-Clause" ]

93

2020-03-18T17:34:07.000Z

2022-03-29T02:11:09.000Z

import katana.local._graph_numba from katana.local._graph import Graph __all__ = ["Graph"]

18.4

37

0.793478

13

92

5.076923

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0.333333

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0.108696

92

4

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null

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1

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1

0

6

811e9e0aca27993dd0cdd1f119f209f392d7b326

498

py

Python

feincms3/plugins/__init__.py

sacovo/feincms3

029a5233208e0da4b339b67a4468d314d94cff0f

[ "BSD-3-Clause" ]

null

feincms3/plugins/__init__.py

sacovo/feincms3

029a5233208e0da4b339b67a4468d314d94cff0f

[ "BSD-3-Clause" ]

null

feincms3/plugins/__init__.py

sacovo/feincms3

029a5233208e0da4b339b67a4468d314d94cff0f

[ "BSD-3-Clause" ]

null

# flake8: noqa from . import html, snippet try: import requests except ImportError: # pragma: no cover pass else: from . import external try: import imagefield except ImportError: # pragma: no cover pass else: from . import image try: import feincms3.cleanse except ImportError: # pragma: no cover pass else: from . import richtext try: import versatileimagefield except ImportError: # pragma: no cover pass else: from . import versatileimage

16.6

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0.265896

0.289017

0.554913

0

0.005333

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498

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40

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null

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1

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1

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6

814487dafb15d67e14cc0a14a5de0e57c10f11ad

119

pyw

Python

sql_sankey_desktop.pyw

Talon24/SanQL

9c6db0be4db57f2c2ec4b9ff62d96f6ccf42daae

[ "MIT" ]

3

2019-11-01T12:03:41.000Z

2022-02-25T11:50:08.000Z

sql_sankey_desktop.pyw

Talon24/SanQL

9c6db0be4db57f2c2ec4b9ff62d96f6ccf42daae

[ "MIT" ]

4

2019-10-02T12:33:04.000Z

2021-11-15T15:08:38.000Z

sql_sankey_desktop.pyw

Talon24/SanQL

9c6db0be4db57f2c2ec4b9ff62d96f6ccf42daae

[ "MIT" ]

null

"""Windows sql_sankey starter.""" import sql_sankey_desktop if __name__ == '__main__': sql_sankey_desktop.main()

17

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15

119

5

0.6

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0

0.134454

119

6

34

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0

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true

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1

0

null

0

1

0

1

0

6

d48e89a21c9a0422fa17cf790f097e7b1eea4bfe

1,566

py

Python

source/tests/test_workspaces_app.py

awslabs/workspaces-cost-optimizer

d95b9b505c79f634b7eadd81c829abf1dff33534

[ "Apache-2.0" ]

43

2018-03-12T18:06:18.000Z

2021-09-24T20:31:39.000Z

source/tests/test_workspaces_app.py

awslabs/workspaces-cost-optimizer

d95b9b505c79f634b7eadd81c829abf1dff33534

[ "Apache-2.0" ]

24

2017-08-17T13:14:43.000Z

2021-10-07T03:58:06.000Z

source/tests/test_workspaces_app.py

awslabs/workspaces-cost-optimizer

d95b9b505c79f634b7eadd81c829abf1dff33534

[ "Apache-2.0" ]

28

2018-03-12T17:25:52.000Z

2021-09-27T18:40:53.000Z

import sys import os from unittest import mock mock.patch.dict(os.environ, {'AutoStopTimeoutHours': '1'}).start() sys.path.append('engine') import ecs.workspaces_app def test_process_input_regions_1(): ecs.workspaces_app.REGIONS = [] valid_workspaces_regions = ['us-east-1'] result = ecs.workspaces_app.process_input_regions(valid_workspaces_regions) assert result == {'us-east-1'} def test_process_input_regions_2(): ecs.workspaces_app.REGIONS = 'us-west-2, us-east-1, us-east-2' valid_workspaces_regions = ['us-east-1', 'us-west-2'] result = ecs.workspaces_app.process_input_regions(valid_workspaces_regions) assert result == {'us-east-1', 'us-west-2'} def test_process_input_regions_3(): ecs.workspaces_app.REGIONS = '"us-west-2", "us-east-1", us-east-2' valid_workspaces_regions = ['us-east-1', 'us-west-2'] result = ecs.workspaces_app.process_input_regions(valid_workspaces_regions) assert result == {'us-east-1', 'us-west-2'} def test_process_input_regions_4(): ecs.workspaces_app.REGIONS = '"us-west-2", "us-east-1", us-east-2' valid_workspaces_regions = ['us-east-1', 'us-west-2'] result = ecs.workspaces_app.process_input_regions(valid_workspaces_regions) assert result == {'us-east-1', 'us-west-2'} def test_process_input_regions_5(): ecs.workspaces_app.REGIONS = '"us-west-2", us-east-2, 1234,ajdfbkjfb' valid_workspaces_regions = ['us-east-1', 'us-west-2'] result = ecs.workspaces_app.process_input_regions(valid_workspaces_regions) assert result == {'us-west-2'}

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0

null

0

6

d4bfa28a8312f1c9e937c46f79e9976b9ccb5545

122

py

Python

app_python/app/dependencies.py

a1d4r/devops

05938bdcb629571fd61f61a590b2173f90b136f0

[ "MIT" ]

null

app_python/app/dependencies.py

a1d4r/devops

05938bdcb629571fd61f61a590b2173f90b136f0

[ "MIT" ]

null

app_python/app/dependencies.py

a1d4r/devops

05938bdcb629571fd61f61a590b2173f90b136f0

[ "MIT" ]

3

2021-08-19T15:58:14.000Z

2021-09-13T18:01:51.000Z

from typing import Iterator from app.db import VisitsStorage, db def get_db() -> Iterator[VisitsStorage]: yield db

15.25

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6

d4cc9e4c59b35355133cb8fcc3563245d4b2b503

60

py

Python

api/repository/__init__.py

Pupsen-Vupsen/trik-testsys-api

75f7812500a7e601d9753d88630df593f9034edf

[ "Apache-2.0" ]

null

api/repository/__init__.py

Pupsen-Vupsen/trik-testsys-api

75f7812500a7e601d9753d88630df593f9034edf

[ "Apache-2.0" ]

null

api/repository/__init__.py

Pupsen-Vupsen/trik-testsys-api

75f7812500a7e601d9753d88630df593f9034edf

[ "Apache-2.0" ]

null

from . import SubmitRepository from . import UserRepository

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6

d4f6ce4cd3da974201441324848e9747ffc7aab1

18,523

py

Python

scripts/check_gdata_token_unittest.py

bpsinc-native/src_third_party_chromite

b07cf18203c98a14c59819387754428e887ca164

[ "BSD-3-Clause" ]

null

scripts/check_gdata_token_unittest.py

bpsinc-native/src_third_party_chromite

b07cf18203c98a14c59819387754428e887ca164

[ "BSD-3-Clause" ]

null

scripts/check_gdata_token_unittest.py

bpsinc-native/src_third_party_chromite

b07cf18203c98a14c59819387754428e887ca164

[ "BSD-3-Clause" ]

null

#!/usr/bin/python # Copyright (c) 2012 The Chromium OS Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Unit tests for cros_portage_upgrade.py.""" import filecmp import mox import os import shutil import gdata.service from gdata.projecthosting import client as gdata_ph_client from gdata.spreadsheet import service as gdata_ss_service from chromite.lib import cros_build_lib as build_lib from chromite.lib import cros_test_lib from chromite.lib import gdata_lib from chromite.scripts import check_gdata_token as cgt # pylint: disable=W0212,R0904,E1120,E1101 class MainTest(cros_test_lib.MoxOutputTestCase): """Test argument handling at the main method level.""" def testHelp(self): """Test that --help is functioning""" argv = [ '--help' ] with self.OutputCapturer() as output: # Running with --help should exit with code==0. self.AssertFuncSystemExitZero(cgt.main, argv) # Verify that a message beginning with "Usage: " was printed. stdout = output.GetStdout() self.assertTrue(stdout.startswith('Usage: ')) def testMainOutsideChroot(self): """Test flow outside chroot""" argv = [] mocked_outsidechroot = self.mox.CreateMock(cgt.OutsideChroot) # Create replay script. self.mox.StubOutWithMock(build_lib, 'IsInsideChroot') self.mox.StubOutWithMock(cgt.OutsideChroot, '__new__') build_lib.IsInsideChroot().AndReturn(False) cgt.OutsideChroot.__new__(cgt.OutsideChroot, argv, ).AndReturn(mocked_outsidechroot) mocked_outsidechroot.Run() self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): cgt.main(argv) self.mox.VerifyAll() def testMainInsideChroot(self): """Test flow inside chroot""" argv = [] mocked_insidechroot = self.mox.CreateMock(cgt.InsideChroot) # Create replay script. self.mox.StubOutWithMock(build_lib, 'IsInsideChroot') self.mox.StubOutWithMock(cgt.InsideChroot, '__new__') build_lib.IsInsideChroot().AndReturn(True) cgt.InsideChroot.__new__(cgt.InsideChroot ).AndReturn(mocked_insidechroot) mocked_insidechroot.Run() self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): cgt.main(argv) self.mox.VerifyAll() class OutsideChrootTest(cros_test_lib.MoxOutputTestCase): """Test flow when run outside chroot.""" def _MockOutsideChroot(self, *args): """Prepare mocked OutsideChroot object with |args|.""" mocked_outsidechroot = self.mox.CreateMock(cgt.OutsideChroot) mocked_outsidechroot.args = list(args) if args else [] return mocked_outsidechroot def testOutsideChrootRestartFail(self): mocked_outsidechroot = self._MockOutsideChroot() self.mox.StubOutWithMock(build_lib, 'RunCommand') cmd = ['check_gdata_token'] run_result = cros_test_lib.EasyAttr(returncode=1) # Create replay script. build_lib.RunCommand(cmd, enter_chroot=True, print_cmd=False, error_code_ok=True).AndReturn(run_result) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): # Test should exit with failure. self.AssertFuncSystemExitNonZero(cgt.OutsideChroot.Run, mocked_outsidechroot) self.mox.VerifyAll() self.AssertOutputContainsError() def testOutsideChrootNoTokenFile(self): mocked_outsidechroot = self._MockOutsideChroot('foo') self.mox.StubOutWithMock(cgt, '_ChrootPathToExternalPath') self.mox.StubOutWithMock(os.path, 'exists') self.mox.StubOutWithMock(build_lib, 'RunCommand') cmd = ['check_gdata_token', 'foo'] run_result = cros_test_lib.EasyAttr(returncode=0) # Create replay script. build_lib.RunCommand(cmd, enter_chroot=True, print_cmd=False, error_code_ok=True).AndReturn(run_result) cgt._ChrootPathToExternalPath(cgt.TOKEN_FILE).AndReturn('chr-tok') os.path.exists('chr-tok').AndReturn(False) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): # Test should exit with failure. self.AssertFuncSystemExitNonZero(cgt.OutsideChroot.Run, mocked_outsidechroot) self.mox.VerifyAll() self.AssertOutputContainsError() def testOutsideChrootNewTokenFile(self): mocked_outsidechroot = self._MockOutsideChroot('foo') self.mox.StubOutWithMock(cgt, '_ChrootPathToExternalPath') self.mox.StubOutWithMock(os.path, 'exists') self.mox.StubOutWithMock(shutil, 'copy2') self.mox.StubOutWithMock(build_lib, 'RunCommand') cmd = ['check_gdata_token', 'foo'] run_result = cros_test_lib.EasyAttr(returncode=0) # Create replay script. build_lib.RunCommand(cmd, enter_chroot=True, print_cmd=False, error_code_ok=True).AndReturn(run_result) cgt._ChrootPathToExternalPath(cgt.TOKEN_FILE).AndReturn('chr-tok') os.path.exists('chr-tok').AndReturn(True) os.path.exists(cgt.TOKEN_FILE).AndReturn(False) shutil.copy2('chr-tok', cgt.TOKEN_FILE) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): cgt.OutsideChroot.Run(mocked_outsidechroot) self.mox.VerifyAll() def testOutsideChrootDifferentTokenFile(self): mocked_outsidechroot = self._MockOutsideChroot('foo') self.mox.StubOutWithMock(cgt, '_ChrootPathToExternalPath') self.mox.StubOutWithMock(os.path, 'exists') self.mox.StubOutWithMock(shutil, 'copy2') self.mox.StubOutWithMock(filecmp, 'cmp') self.mox.StubOutWithMock(build_lib, 'RunCommand') cmd = ['check_gdata_token', 'foo'] run_result = cros_test_lib.EasyAttr(returncode=0) # Create replay script. build_lib.RunCommand(cmd, enter_chroot=True, print_cmd=False, error_code_ok=True).AndReturn(run_result) cgt._ChrootPathToExternalPath(cgt.TOKEN_FILE).AndReturn('chr-tok') os.path.exists('chr-tok').AndReturn(True) os.path.exists(cgt.TOKEN_FILE).AndReturn(True) filecmp.cmp(cgt.TOKEN_FILE, 'chr-tok').AndReturn(False) shutil.copy2('chr-tok', cgt.TOKEN_FILE) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): cgt.OutsideChroot.Run(mocked_outsidechroot) self.mox.VerifyAll() def testOutsideChrootNoChangeInTokenFile(self): mocked_outsidechroot = self._MockOutsideChroot('foo') self.mox.StubOutWithMock(cgt, '_ChrootPathToExternalPath') self.mox.StubOutWithMock(os.path, 'exists') self.mox.StubOutWithMock(filecmp, 'cmp') self.mox.StubOutWithMock(build_lib, 'RunCommand') cmd = ['check_gdata_token', 'foo'] run_result = cros_test_lib.EasyAttr(returncode=0) # Create replay script. build_lib.RunCommand(cmd, enter_chroot=True, print_cmd=False, error_code_ok=True).AndReturn(run_result) cgt._ChrootPathToExternalPath(cgt.TOKEN_FILE).AndReturn('chr-tok') os.path.exists('chr-tok').AndReturn(True) os.path.exists(cgt.TOKEN_FILE).AndReturn(True) filecmp.cmp(cgt.TOKEN_FILE, 'chr-tok').AndReturn(True) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): cgt.OutsideChroot.Run(mocked_outsidechroot) self.mox.VerifyAll() class InsideChrootTest(cros_test_lib.MoxOutputTestCase): """Test flow when run inside chroot.""" def _MockInsideChroot(self): """Prepare mocked OutsideChroot object.""" mic = self.mox.CreateMock(cgt.InsideChroot) mic.creds = self.mox.CreateMock(gdata_lib.Creds) mic.gd_client = self.mox.CreateMock(gdata_ss_service.SpreadsheetsService) mic.it_client = self.mox.CreateMock(gdata_ph_client.ProjectHostingClient) return mic def testLoadTokenFile(self): mocked_insidechroot = self._MockInsideChroot() self.mox.StubOutWithMock(os.path, 'exists') # Create replay script os.path.exists(cgt.TOKEN_FILE).AndReturn(True) mocked_insidechroot.creds.LoadAuthToken(cgt.TOKEN_FILE) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._LoadTokenFile(mocked_insidechroot) self.mox.VerifyAll() self.assertTrue(result) def testSaveTokenFile(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_insidechroot.creds.StoreAuthTokenIfNeeded(cgt.TOKEN_FILE) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): cgt.InsideChroot._SaveTokenFile(mocked_insidechroot) self.mox.VerifyAll() def testLoadTokenFileMissing(self): mocked_insidechroot = self._MockInsideChroot() self.mox.StubOutWithMock(os.path, 'exists') # Create replay script os.path.exists(cgt.TOKEN_FILE).AndReturn(False) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._LoadTokenFile(mocked_insidechroot) self.mox.VerifyAll() self.assertFalse(result) def testInsideChrootValidateOK(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_insidechroot._LoadTokenFile() mocked_insidechroot._ValidateTrackerToken().AndReturn(True) mocked_insidechroot._ValidateDocsToken().AndReturn(True) mocked_insidechroot._SaveTokenFile() self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): cgt.InsideChroot.Run(mocked_insidechroot) self.mox.VerifyAll() def testInsideChrootTrackerValidateFailGenerateOK(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_insidechroot._LoadTokenFile() mocked_insidechroot._ValidateTrackerToken().AndReturn(True) mocked_insidechroot._ValidateDocsToken().AndReturn(False) mocked_insidechroot._GenerateDocsToken().AndReturn(True) mocked_insidechroot._SaveTokenFile() self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): cgt.InsideChroot.Run(mocked_insidechroot) self.mox.VerifyAll() def testInsideChrootDocsValidateFailGenerateOK(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_insidechroot._LoadTokenFile() mocked_insidechroot._ValidateTrackerToken().AndReturn(False) mocked_insidechroot._GenerateTrackerToken().AndReturn(True) mocked_insidechroot._ValidateDocsToken().AndReturn(True) mocked_insidechroot._SaveTokenFile() self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): cgt.InsideChroot.Run(mocked_insidechroot) self.mox.VerifyAll() def testInsideChrootTrackerValidateFailGenerateFail(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_insidechroot._LoadTokenFile() mocked_insidechroot._ValidateTrackerToken().AndReturn(False) mocked_insidechroot._GenerateTrackerToken().AndReturn(False) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): # Test should exit with failure. self.AssertFuncSystemExitNonZero(cgt.InsideChroot.Run, mocked_insidechroot) self.mox.VerifyAll() self.AssertOutputContainsError() def testInsideChrootDocsValidateFailGenerateFail(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_insidechroot._LoadTokenFile() mocked_insidechroot._ValidateTrackerToken().AndReturn(True) mocked_insidechroot._ValidateDocsToken().AndReturn(False) mocked_insidechroot._GenerateDocsToken().AndReturn(False) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): # Test should exit with failure. self.AssertFuncSystemExitNonZero(cgt.InsideChroot.Run, mocked_insidechroot) self.mox.VerifyAll() self.AssertOutputContainsError() def testGenerateTrackerTokenOK(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_creds = mocked_insidechroot.creds mocked_itclient = mocked_insidechroot.it_client mocked_creds.user = 'joe@chromium.org' mocked_creds.password = 'shhh' auth_token = 'SomeToken' mocked_itclient.auth_token = cros_test_lib.EasyAttr(token_string=auth_token) mocked_creds.LoadCreds(cgt.CRED_FILE) mocked_itclient.ClientLogin(mocked_creds.user, mocked_creds.password, source='Package Status', service='code', account_type='GOOGLE') mocked_creds.SetTrackerAuthToken(auth_token) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._GenerateTrackerToken(mocked_insidechroot) self.assertTrue(result, '_GenerateTrackerToken should have passed') self.mox.VerifyAll() def testGenerateTrackerTokenFail(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_creds = mocked_insidechroot.creds mocked_itclient = mocked_insidechroot.it_client mocked_creds.user = 'joe@chromium.org' mocked_creds.password = 'shhh' mocked_creds.LoadCreds(cgt.CRED_FILE) mocked_itclient.ClientLogin(mocked_creds.user, mocked_creds.password, source='Package Status', service='code', account_type='GOOGLE' ).AndRaise(gdata.client.BadAuthentication()) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._GenerateTrackerToken(mocked_insidechroot) self.assertFalse(result, '_GenerateTrackerToken should have failed') self.mox.VerifyAll() self.AssertOutputContainsError() def testValidateTrackerTokenOK(self): mocked_insidechroot = self._MockInsideChroot() mocked_itclient = mocked_insidechroot.it_client self.mox.StubOutWithMock(gdata.gauth.ClientLoginToken, '__new__') # Create replay script. auth_token = 'SomeToken' mocked_insidechroot.creds.tracker_auth_token = auth_token gdata.gauth.ClientLoginToken.__new__(gdata.gauth.ClientLoginToken, auth_token).AndReturn('TokenObj') mocked_itclient.get_issues('chromium-os', query=mox.IgnoreArg()) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._ValidateTrackerToken(mocked_insidechroot) self.mox.VerifyAll() self.assertTrue(result, '_ValidateTrackerToken should have passed') def testValidateTrackerTokenFail(self): mocked_insidechroot = self._MockInsideChroot() mocked_itclient = mocked_insidechroot.it_client self.mox.StubOutWithMock(gdata.gauth.ClientLoginToken, '__new__') # Create replay script. auth_token = 'SomeToken' mocked_insidechroot.creds.tracker_auth_token = auth_token gdata.gauth.ClientLoginToken.__new__(gdata.gauth.ClientLoginToken, auth_token).AndReturn('TokenObj') mocked_itclient.get_issues('chromium-os', query=mox.IgnoreArg() ).AndRaise(gdata.client.Error()) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._ValidateTrackerToken(mocked_insidechroot) self.assertFalse(result, '_ValidateTrackerToken should have failed') self.mox.VerifyAll() def testGenerateDocsTokenOK(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_creds = mocked_insidechroot.creds mocked_gdclient = mocked_insidechroot.gd_client mocked_creds.user = 'joe@chromium.org' mocked_creds.password = 'shhh' auth_token = 'SomeToken' mocked_creds.LoadCreds(cgt.CRED_FILE) mocked_gdclient.ProgrammaticLogin() mocked_gdclient.GetClientLoginToken().AndReturn(auth_token) mocked_creds.SetDocsAuthToken(auth_token) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._GenerateDocsToken(mocked_insidechroot) self.assertTrue(result, '_GenerateDocsToken should have passed') self.mox.VerifyAll() def testGenerateDocsTokenFail(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. mocked_creds = mocked_insidechroot.creds mocked_gdclient = mocked_insidechroot.gd_client mocked_creds.user = 'joe@chromium.org' mocked_creds.password = 'shhh' mocked_creds.LoadCreds(cgt.CRED_FILE) mocked_gdclient.ProgrammaticLogin( ).AndRaise(gdata.service.BadAuthentication()) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._GenerateDocsToken(mocked_insidechroot) self.assertFalse(result, '_GenerateTrackerToken should have failed') self.mox.VerifyAll() self.AssertOutputContainsError() def testValidateDocsTokenOK(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. auth_token = 'SomeToken' mocked_insidechroot.creds.docs_auth_token = auth_token mocked_insidechroot.gd_client.SetClientLoginToken(auth_token) mocked_insidechroot.gd_client.GetSpreadsheetsFeed() self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._ValidateDocsToken(mocked_insidechroot) self.assertTrue(result, '_ValidateDocsToken should have passed') self.mox.VerifyAll() def testValidateDocsTokenFail(self): mocked_insidechroot = self._MockInsideChroot() # Create replay script. auth_token = 'SomeToken' mocked_insidechroot.creds.docs_auth_token = auth_token mocked_insidechroot.gd_client.SetClientLoginToken(auth_token) expired_error = gdata.service.RequestError({'reason': 'Token expired'}) mocked_insidechroot.gd_client.GetSpreadsheetsFeed().AndRaise(expired_error) self.mox.ReplayAll() # Run test verification. with self.OutputCapturer(): result = cgt.InsideChroot._ValidateDocsToken(mocked_insidechroot) self.assertFalse(result, '_ValidateDocsToken should have failed') self.mox.VerifyAll() if __name__ == '__main__': cros_test_lib.main()

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1

0

null

0

6

be0a19e746d6b3b75651020efb2c56ff859adec2

6,718

py

Python

test/cached_dependent_dependency_manager_test.py

AustinHellerRepo/Common

2d42599e5d7c0d5fcba2d2c9a726d51f946f67bc

[ "MIT" ]

null

test/cached_dependent_dependency_manager_test.py

AustinHellerRepo/Common

2d42599e5d7c0d5fcba2d2c9a726d51f946f67bc

[ "MIT" ]

null

test/cached_dependent_dependency_manager_test.py

AustinHellerRepo/Common

2d42599e5d7c0d5fcba2d2c9a726d51f946f67bc

[ "MIT" ]

null

from __future__ import annotations import unittest from typing import List, Tuple, Dict from src.austin_heller_repo.common import SingleDependentDependencyManager class SingleDependentDependencyManagerTest(unittest.TestCase): def test_initialize(self): def on_dependent_dependency_satisfied_callback(dependent, dependency, key): raise NotImplementedError() manager = SingleDependentDependencyManager( on_dependent_dependency_satisfied_callback=on_dependent_dependency_satisfied_callback, is_dependency_reusable=False ) self.assertIsNotNone(manager) def test_one_dependent_and_one_dependency(self): found_pairs = [] # type: List[Tuple[str, str]] def on_dependent_dependency_satisfied_callback(dependent, dependency, key): nonlocal found_pairs found_pairs.append((dependent, dependency)) manager = SingleDependentDependencyManager( on_dependent_dependency_satisfied_callback=on_dependent_dependency_satisfied_callback, is_dependency_reusable=False ) manager.add_dependent( key="key", dependent="dependent 0" ) self.assertEqual([], found_pairs) manager.add_dependency( key="key", dependency="dependency 0" ) self.assertEqual([("dependent 0", "dependency 0")], found_pairs) def test_one_dependency_and_one_dependent(self): found_pairs = [] # type: List[Tuple[str, str]] def on_dependent_dependency_satisfied_callback(dependent, dependency, key): nonlocal found_pairs found_pairs.append((dependent, dependency)) manager = SingleDependentDependencyManager( on_dependent_dependency_satisfied_callback=on_dependent_dependency_satisfied_callback, is_dependency_reusable=False ) manager.add_dependency( key="key", dependency="dependency 0" ) self.assertEqual([], found_pairs) manager.add_dependent( key="key", dependent="dependent 0" ) self.assertEqual([("dependent 0", "dependency 0")], found_pairs) def test_one_dependent_and_one_unrelated_dependency(self): found_pairs = [] # type: List[Tuple[str, str]] def on_dependent_dependency_satisfied_callback(dependent, dependency, key): nonlocal found_pairs found_pairs.append((dependent, dependency)) manager = SingleDependentDependencyManager( on_dependent_dependency_satisfied_callback=on_dependent_dependency_satisfied_callback, is_dependency_reusable=False ) manager.add_dependent( key="key", dependent="dependent 0" ) self.assertEqual([], found_pairs) manager.add_dependency( key="unrelated", dependency="dependency 0" ) self.assertEqual([], found_pairs) def test_one_dependency_and_one_unrelated_dependent(self): found_pairs = [] # type: List[Tuple[str, str]] def on_dependent_dependency_satisfied_callback(dependent, dependency, key): nonlocal found_pairs found_pairs.append((dependent, dependency)) manager = SingleDependentDependencyManager( on_dependent_dependency_satisfied_callback=on_dependent_dependency_satisfied_callback, is_dependency_reusable=False ) manager.add_dependency( key="key", dependency="dependency 0" ) self.assertEqual([], found_pairs) manager.add_dependent( key="unrelated", dependent="dependent 0" ) self.assertEqual([], found_pairs) def test_one_dependent_and_one_reusable_dependency(self): found_pairs = [] # type: List[Tuple[str, str]] def on_dependent_dependency_satisfied_callback(dependent, dependency, key): nonlocal found_pairs found_pairs.append((dependent, dependency)) manager = SingleDependentDependencyManager( on_dependent_dependency_satisfied_callback=on_dependent_dependency_satisfied_callback, is_dependency_reusable=True ) manager.add_dependent( key="key", dependent="dependent 0" ) self.assertEqual([], found_pairs) manager.add_dependency( key="key", dependency="dependency 0" ) self.assertEqual([("dependent 0", "dependency 0")], found_pairs) def test_two_reusable_dependencies_and_three_dependents_add_another_dependency_and_three_dependents(self): found_pairs = [] # type: List[Tuple[str, str]] def on_dependent_dependency_satisfied_callback(dependent, dependency, key): nonlocal found_pairs found_pairs.append((dependent, dependency)) manager = SingleDependentDependencyManager( on_dependent_dependency_satisfied_callback=on_dependent_dependency_satisfied_callback, is_dependency_reusable=True ) for index in range(2): manager.add_dependency( key="key", dependency=f"dependency {index}" ) self.assertEqual([], found_pairs) for index in range(3): manager.add_dependent( key="key", dependent=f"dependent {index}" ) if index == 0: self.assertEqual([("dependent 0", "dependency 0")], found_pairs) elif index == 1: self.assertEqual([("dependent 0", "dependency 0"), ("dependent 1", "dependency 1")], found_pairs) elif index == 2: self.assertEqual([("dependent 0", "dependency 0"), ("dependent 1", "dependency 1"), ("dependent 2", "dependency 0")], found_pairs) manager.add_dependency( key="key", dependency="dependency 2" ) self.assertEqual([("dependent 0", "dependency 0"), ("dependent 1", "dependency 1"), ("dependent 2", "dependency 0")], found_pairs) for index in range(3, 3): manager.add_dependent( key="key", dependent=f"dependent {index}" ) if index == 3: self.assertEqual([("dependent 0", "dependency 0"), ("dependent 1", "dependency 1"), ("dependent 2", "dependency 0"), ("dependent 3", "dependency 1")], found_pairs) elif index == 4: self.assertEqual([("dependent 0", "dependency 0"), ("dependent 1", "dependency 1"), ("dependent 2", "dependency 0"), ("dependent 3", "dependency 1"), ("dependent 4", "dependency 0")], found_pairs) elif index == 5: self.assertEqual([("dependent 0", "dependency 0"), ("dependent 1", "dependency 1"), ("dependent 2", "dependency 0"), ("dependent 3", "dependency 1"), ("dependent 4", "dependency 0"), ("dependent 5", "dependency 2")], found_pairs) def test_one_dependency_and_one_dependent_multiple_times(self): found_pairs = [] # type: List[Tuple[str, str]] def on_dependent_dependency_satisfied_callback(dependent, dependency, key): nonlocal found_pairs found_pairs.append((dependent, dependency)) manager = SingleDependentDependencyManager( on_dependent_dependency_satisfied_callback=on_dependent_dependency_satisfied_callback, is_dependency_reusable=False ) for index in range(1000000): manager.add_dependency( key="key", dependency="dependency 0" ) self.assertEqual(index, len(found_pairs)) manager.add_dependent( key="key", dependent="dependent 0" ) self.assertEqual(index + 1, len(found_pairs))

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py

Python

src/azure-cli/azure/cli/command_modules/netappfiles/tests/latest/test_snapshot_policy_commands.py

xaliciayang/azure-cli

38c80c875e8a79d08d06a2f42ec82fd54934343e

[ "MIT" ]

1

2021-05-03T21:33:51.000Z

src/azure-cli/azure/cli/command_modules/netappfiles/tests/latest/test_snapshot_policy_commands.py

xaliciayang/azure-cli

38c80c875e8a79d08d06a2f42ec82fd54934343e

[ "MIT" ]

1

2021-02-25T19:22:13.000Z

src/azure-cli/azure/cli/command_modules/netappfiles/tests/latest/test_snapshot_policy_commands.py

xaliciayang/azure-cli

38c80c875e8a79d08d06a2f42ec82fd54934343e

[ "MIT" ]

1

2021-03-02T09:26:15.000Z

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- from azure.cli.testsdk import ScenarioTest, ResourceGroupPreparer import unittest LOCATION = "centralus" VOLUME_DEFAULT = "--service-level 'Premium' --usage-threshold 100" class AzureNetAppFilesSnapshotPolicyServiceScenarioTest(ScenarioTest): def setup_vnet(self, vnet_name, subnet_name): self.cmd("az network vnet create -n %s -g {rg} -l %s --address-prefix 10.5.0.0/16" % (vnet_name, LOCATION)) self.cmd("az network vnet subnet create -n %s --vnet-name %s --address-prefixes '10.5.0.0/24' " "--delegations 'Microsoft.Netapp/volumes' -g {rg}" % (subnet_name, vnet_name)) def current_subscription(self): subs = self.cmd("az account show").get_output_in_json() return subs['id'] def create_volume(self, account_name, pool_name, volume_name, snapshot_policy_id=None): vnet_name = "cli-vnet-lefr-02" subnet_name = "default" # create vnet and pool self.setup_vnet(vnet_name, subnet_name) self.cmd("netappfiles pool create -g {rg} -a %s -p %s -l %s --service-level 'Premium' --size 4" % (account_name, pool_name, LOCATION)).get_output_in_json() # create volume return self.cmd("netappfiles volume create -g {rg} -a %s -p %s -v %s -l %s --vnet %s --subnet %s " "--file-path %s %s --snapshot-policy-id %s" % (account_name, pool_name, volume_name, LOCATION, vnet_name, subnet_name, volume_name, VOLUME_DEFAULT, snapshot_policy_id)).get_output_in_json() @ResourceGroupPreparer(name_prefix='cli_netappfiles_test_snapshot_policy_') def test_create_delete_snapshot_policies(self): # create account account_name = self.create_random_name(prefix='cli-acc-', length=24) snapshot_policy_name = self.create_random_name(prefix='cli-sn-pol-', length=16) self.cmd("az netappfiles account create -g {rg} -a '%s' -l %s" % (account_name, LOCATION)).get_output_in_json() # create snapshot policy using long parameter names and validate result hourly_snapshots_to_keep = 1 hourly_minute = 10 daily_snapshots_to_keep = 2 daily_minute = 20 daily_hour = 2 weekly_snapshots_to_keep = 3 weekly_minute = 30 weekly_hour = 3 weekly_day = "Monday" monthly_snapshots_to_keep = 4 monthly_minute = 40 monthly_hour = 4 monthly_days_of_month = "1,3,20" enabled = True tags = "Tag1=Value1" snapshot_policy = self.cmd("az netappfiles snapshot policy create -g {rg} -a %s --snapshot-policy-name %s " "--location %s --hourly-snapshots %s --daily-snapshots %s " "--weekly-snapshots %s --monthly-snapshots %s --hourly-minute %s " "--daily-minute %s --weekly-minute %s --monthly-minute %s --daily-hour %s " "--weekly-hour %s --monthly-hour %s --weekly-day %s --monthly-days %s " "--enabled %s --tags %s" % (account_name, snapshot_policy_name, LOCATION, hourly_snapshots_to_keep, daily_snapshots_to_keep, weekly_snapshots_to_keep, monthly_snapshots_to_keep, hourly_minute, daily_minute, weekly_minute, monthly_minute, daily_hour, weekly_hour, monthly_hour, weekly_day, monthly_days_of_month, enabled, tags)).get_output_in_json() assert snapshot_policy['name'] == account_name + "/" + snapshot_policy_name assert snapshot_policy['hourlySchedule']['snapshotsToKeep'] == hourly_snapshots_to_keep assert snapshot_policy['hourlySchedule']['minute'] == hourly_minute assert snapshot_policy['dailySchedule']['snapshotsToKeep'] == daily_snapshots_to_keep assert snapshot_policy['dailySchedule']['minute'] == daily_minute assert snapshot_policy['dailySchedule']['hour'] == daily_hour assert snapshot_policy['weeklySchedule']['snapshotsToKeep'] == weekly_snapshots_to_keep assert snapshot_policy['weeklySchedule']['minute'] == weekly_minute assert snapshot_policy['weeklySchedule']['hour'] == weekly_hour assert snapshot_policy['weeklySchedule']['day'] == weekly_day assert snapshot_policy['monthlySchedule']['snapshotsToKeep'] == monthly_snapshots_to_keep assert snapshot_policy['monthlySchedule']['minute'] == monthly_minute assert snapshot_policy['monthlySchedule']['hour'] == monthly_hour assert snapshot_policy['monthlySchedule']['daysOfMonth'] == monthly_days_of_month assert snapshot_policy['enabled'] == enabled assert snapshot_policy['tags']['Tag1'] == 'Value1' assert snapshot_policy['provisioningState'] is not None # validate snapshot policy exist snapshot_policy_list = self.cmd("az netappfiles snapshot policy list -g {rg} -a '%s'" % account_name).get_output_in_json() assert len(snapshot_policy_list) == 1 # delete snapshot policy self.cmd("az netappfiles snapshot policy delete -g {rg} -a %s --snapshot-policy-name %s" % (account_name, snapshot_policy_name)) # create snapshot policy using short parameter names and validate result snapshot_policy = self.cmd("az netappfiles snapshot policy create -g {rg} -a %s " "--snapshot-policy-name %s -l %s -u %s -d %s -w %s -m %s " "--hourly-minute %s --daily-minute %s --weekly-minute %s --monthly-minute %s " "--daily-hour %s --weekly-hour %s --monthly-hour %s --weekly-day %s " "--monthly-days %s --enabled %s --tags %s" % (account_name, snapshot_policy_name, LOCATION, hourly_snapshots_to_keep, daily_snapshots_to_keep, weekly_snapshots_to_keep, monthly_snapshots_to_keep, hourly_minute, daily_minute, weekly_minute, monthly_minute, daily_hour, weekly_hour, monthly_hour, weekly_day, monthly_days_of_month, enabled, tags)).get_output_in_json() assert snapshot_policy['name'] == account_name + "/" + snapshot_policy_name assert snapshot_policy['hourlySchedule']['snapshotsToKeep'] == hourly_snapshots_to_keep assert snapshot_policy['hourlySchedule']['minute'] == hourly_minute assert snapshot_policy['dailySchedule']['snapshotsToKeep'] == daily_snapshots_to_keep assert snapshot_policy['dailySchedule']['minute'] == daily_minute assert snapshot_policy['dailySchedule']['hour'] == daily_hour assert snapshot_policy['weeklySchedule']['snapshotsToKeep'] == weekly_snapshots_to_keep assert snapshot_policy['weeklySchedule']['minute'] == weekly_minute assert snapshot_policy['weeklySchedule']['hour'] == weekly_hour assert snapshot_policy['weeklySchedule']['day'] == weekly_day assert snapshot_policy['monthlySchedule']['snapshotsToKeep'] == monthly_snapshots_to_keep assert snapshot_policy['monthlySchedule']['minute'] == monthly_minute assert snapshot_policy['monthlySchedule']['hour'] == monthly_hour assert snapshot_policy['monthlySchedule']['daysOfMonth'] == monthly_days_of_month assert snapshot_policy['enabled'] == enabled assert snapshot_policy['tags']['Tag1'] == 'Value1' # delete snapshot policy self.cmd("az netappfiles snapshot policy delete -g {rg} -a %s --snapshot-policy-name %s" % (account_name, snapshot_policy_name)) # validate snapshot policy doesn't exist snapshot_policy_list = self.cmd("az netappfiles snapshot policy list -g {rg} -a '%s'" % account_name).get_output_in_json() assert len(snapshot_policy_list) == 0 @ResourceGroupPreparer(name_prefix='cli_netappfiles_test_snapshot_policy_') def test_list_snapshot_policy(self): # create account account_name = self.create_random_name(prefix='cli-acc-', length=24) self.cmd("az netappfiles account create -g {rg} -a '%s' -l %s" % (account_name, LOCATION)).get_output_in_json() # create 3 snapshot policies snapshot_policies = [self.create_random_name(prefix='cli', length=16), self.create_random_name(prefix='cli', length=16), self.create_random_name(prefix='cli', length=16)] hourly_snapshots_to_keep = 1 hourly_minute = 10 for snapshot_policy_name in snapshot_policies: self.cmd("az netappfiles snapshot policy create -g {rg} -a %s --snapshot-policy-name %s -l %s -u %s --hourly-minute %s" % (account_name, snapshot_policy_name, LOCATION, hourly_snapshots_to_keep, hourly_minute)) # validate that both snapshot policies exist snapshot_policy_list = self.cmd("az netappfiles snapshot policy list -g {rg} -a '%s'" % account_name).get_output_in_json() assert len(snapshot_policy_list) == 3 # delete all snapshot policies for snapshot_policy_name in snapshot_policies: self.cmd("az netappfiles snapshot policy delete -g {rg} -a %s --snapshot-policy-name %s" % (account_name, snapshot_policy_name)) # validate that no snapshot policies exist snapshot_policy_list = self.cmd("az netappfiles snapshot policy list -g {rg} -a '%s'" % account_name).get_output_in_json() assert len(snapshot_policy_list) == 0 @ResourceGroupPreparer(name_prefix='cli_netappfiles_test_snapshot_policy_') def test_get_snapshot_policy_by_name(self): # create account account_name = self.create_random_name(prefix='cli-acc-', length=24) self.cmd("az netappfiles account create -g {rg} -a '%s' -l %s" % (account_name, LOCATION)).get_output_in_json() # create snapshot policy snapshot_policy_name = self.create_random_name(prefix='cli-sn-pol-', length=16) hourly_snapshots = 1 hourly_minute = 10 self.cmd("az netappfiles snapshot policy create -g {rg} -a %s --snapshot-policy-name %s -l %s -u %s --hourly-minute %s" % (account_name, snapshot_policy_name, LOCATION, hourly_snapshots, hourly_minute)).get_output_in_json() # get snapshot policy by name and validate snapshot_policy = self.cmd("az netappfiles snapshot policy show -g {rg} -a %s --snapshot-policy-name %s" % (account_name, snapshot_policy_name)).get_output_in_json() assert snapshot_policy['name'] == account_name + '/' + snapshot_policy_name assert snapshot_policy['hourlySchedule']['snapshotsToKeep'] == hourly_snapshots assert snapshot_policy['hourlySchedule']['minute'] == hourly_minute # get snapshot policy by resource id and validate snapshot_policy_from_id = self.cmd("az netappfiles snapshot policy show --ids %s" % snapshot_policy['id']).get_output_in_json() assert snapshot_policy_from_id['name'] == account_name + '/' + snapshot_policy_name assert snapshot_policy['hourlySchedule']['snapshotsToKeep'] == hourly_snapshots assert snapshot_policy['hourlySchedule']['minute'] == hourly_minute @ResourceGroupPreparer(name_prefix='cli_netappfiles_test_snapshot_policy_') def test_update_snapshot_policy(self): # create account account_name = self.create_random_name(prefix='cli-acc-', length=24) self.cmd("az netappfiles account create -g {rg} -a '%s' -l %s" % (account_name, LOCATION)).get_output_in_json() # create snapshot policy snapshot_policy_name = self.create_random_name(prefix='cli-sn-pol-', length=16) hourly_snapshots_to_keep = 1 hourly_minute = 10 daily_snapshots_to_keep = 2 daily_minute = 20 daily_hour = 2 weekly_snapshots_to_keep = 3 weekly_minute = 30 weekly_hour = 3 weekly_day = "Monday" monthly_snapshots_to_keep = 4 monthly_minute = 40 monthly_hour = 4 monthly_days_of_month = "2,5,30" enabled = True tags = "Tag1=Value1" self.cmd("az netappfiles snapshot policy create -g {rg} -a %s --snapshot-policy-name %s -l %s -u %s -d %s -w %s -m %s " "--hourly-minute %s --daily-minute %s --weekly-minute %s --monthly-minute %s --daily-hour %s " "--weekly-hour %s --monthly-hour %s --weekly-day %s --monthly-days %s --enabled %s --tags %s" % (account_name, snapshot_policy_name, LOCATION, hourly_snapshots_to_keep, daily_snapshots_to_keep, weekly_snapshots_to_keep, monthly_snapshots_to_keep, hourly_minute, daily_minute, weekly_minute, monthly_minute, daily_hour, weekly_hour, monthly_hour, weekly_day, monthly_days_of_month, enabled, tags)).get_output_in_json() # update snapshot policy hourly_snapshots_to_keep = 5 hourly_minute = 50 daily_snapshots_to_keep = 6 daily_minute = 0 daily_hour = 6 weekly_snapshots_to_keep = 7 weekly_minute = 10 weekly_hour = 7 weekly_day = "Wednesday" monthly_snapshots_to_keep = 8 monthly_minute = 20 monthly_hour = 8 monthly_days_of_month = "1,2,20" enabled = False self.cmd("az netappfiles snapshot policy update -g {rg} -a %s --snapshot-policy-name %s -l %s -u %s -d %s -w %s -m %s " "--hourly-minute %s --daily-minute %s --weekly-minute %s --monthly-minute %s --daily-hour %s " "--weekly-hour %s --monthly-hour %s --weekly-day %s --monthly-days %s --enabled %s" % (account_name, snapshot_policy_name, LOCATION, hourly_snapshots_to_keep, daily_snapshots_to_keep, weekly_snapshots_to_keep, monthly_snapshots_to_keep, hourly_minute, daily_minute, weekly_minute, monthly_minute, daily_hour, weekly_hour, monthly_hour, weekly_day, monthly_days_of_month, enabled)).get_output_in_json() # get updated snapshot policy and validate update snapshot_policy = self.cmd("az netappfiles snapshot policy show -g {rg} -a %s --snapshot-policy-name %s" % (account_name, snapshot_policy_name)).get_output_in_json() assert snapshot_policy['name'] == account_name + "/" + snapshot_policy_name assert snapshot_policy['hourlySchedule']['snapshotsToKeep'] == hourly_snapshots_to_keep assert snapshot_policy['hourlySchedule']['minute'] == hourly_minute assert snapshot_policy['dailySchedule']['snapshotsToKeep'] == daily_snapshots_to_keep assert snapshot_policy['dailySchedule']['minute'] == daily_minute assert snapshot_policy['dailySchedule']['hour'] == daily_hour assert snapshot_policy['weeklySchedule']['snapshotsToKeep'] == weekly_snapshots_to_keep assert snapshot_policy['weeklySchedule']['minute'] == weekly_minute assert snapshot_policy['weeklySchedule']['hour'] == weekly_hour assert snapshot_policy['weeklySchedule']['day'] == weekly_day assert snapshot_policy['monthlySchedule']['snapshotsToKeep'] == monthly_snapshots_to_keep assert snapshot_policy['monthlySchedule']['minute'] == monthly_minute assert snapshot_policy['monthlySchedule']['hour'] == monthly_hour assert snapshot_policy['monthlySchedule']['daysOfMonth'] == monthly_days_of_month assert snapshot_policy['enabled'] == enabled assert snapshot_policy['tags']['Tag1'] == 'Value1' @unittest.skip("Waiting for a fix on swagger and sdk") @ResourceGroupPreparer(name_prefix='cli_netappfiles_test_snapshot_policy_') def test_snapshot_policy_list_volumes(self): raise unittest.SkipTest("Skipping - need to fix NFSAAS-12189") # create account account_name = self.create_random_name(prefix='cli-acc-', length=24) self.cmd("az netappfiles account create -g {rg} -a '%s' -l %s" % (account_name, LOCATION)).get_output_in_json() # create snapshot policy snapshot_policy_name = self.create_random_name(prefix='cli-sn-pol-', length=16) hourly_snapshots_to_keep = 1 hourly_minute = 10 enabled = True self.cmd("az netappfiles snapshot policy create -g {rg} -a %s --snapshot-policy-name %s -l %s -u %s --hourly-minute %s --enabled %s" % (account_name, snapshot_policy_name, LOCATION, hourly_snapshots_to_keep, hourly_minute, enabled) ).get_output_in_json() snapshot_policy = self.cmd("az netappfiles snapshot policy show -g {rg} -a %s --snapshot-policy-name %s" % (account_name, snapshot_policy_name)).get_output_in_json() # create volume pool_name = self.create_random_name(prefix='cli-pool-', length=24) volume_name = self.create_random_name(prefix='cli-vol-', length=24) self.create_volume(account_name, pool_name, volume_name, snapshot_policy_id=snapshot_policy['id']) list_volumes = self.cmd("az netappfiles snapshot policy volumes -g {rg} -a %s --snapshot-policy-name %s" % (account_name, snapshot_policy_name)).get_output_in_json() assert len(list_volumes) == 1 # create second volume volume_name = self.create_random_name(prefix='cli-vol-', length=24) self.create_volume(account_name, pool_name, volume_name, snapshot_policy_id=snapshot_policy['id']) list_volumes = self.cmd("az netappfiles snapshot policy volumes -g {rg} -a %s --snapshot-policy-name %s" % (account_name, snapshot_policy_name)).get_output_in_json() assert len(list_volumes) == 2

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07aeff5963c4b8165b489ac2c164d38f263efa00

23

py

Python

agnpy/targets/__init__.py

vuillaut/agnpy

b3c9c09ca59c067f0739510e26e43e2693b42c99

[ "BSD-3-Clause" ]

25

2020-01-24T09:27:45.000Z

2022-03-03T11:58:06.000Z

agnpy/targets/__init__.py

vuillaut/agnpy

b3c9c09ca59c067f0739510e26e43e2693b42c99

[ "BSD-3-Clause" ]

107

2020-02-14T16:21:14.000Z

2022-03-24T16:38:28.000Z

agnpy/targets/__init__.py

vuillaut/agnpy

b3c9c09ca59c067f0739510e26e43e2693b42c99

[ "BSD-3-Clause" ]

17

2020-01-18T05:46:51.000Z

2022-03-20T21:33:28.000Z

from .targets import *

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07ba957c24cbf994fb8ef005ad539edb47a8df9e

206

py

Python

modereddit.py

axsaucedo/real-time-ml-pipelines

88200b5ababa90245c6c979842cf8dc536b50287

[ "MIT" ]

2

2020-05-02T20:01:59.000Z

2020-06-01T07:03:51.000Z

modereddit.py

axsaucedo/real-time-ml-pipelines

88200b5ababa90245c6c979842cf8dc536b50287

[ "MIT" ]

null

modereddit.py

axsaucedo/real-time-ml-pipelines

88200b5ababa90245c6c979842cf8dc536b50287

[ "MIT" ]

1

2020-05-02T20:02:01.000Z

#!/bin/python3 from modereddit.main import get_argument_parser from modereddit.main import main if __name__ == "__main__": parser = get_argument_parser() args = parser.parse_args() main(args)

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07c35b70f814bb8e1ed446d1a497d07c2e568203

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py

Python

utils/time.py

Cearaj/XJ9

7ae81c28ce46969d2115993d0602cb42173971f3

[ "WTFPL" ]

null

utils/time.py

Cearaj/XJ9

7ae81c28ce46969d2115993d0602cb42173971f3

[ "WTFPL" ]

null

utils/time.py

Cearaj/XJ9

7ae81c28ce46969d2115993d0602cb42173971f3

[ "WTFPL" ]

null

import time def format_seconds(seconds): return time.strftime("%H:%M:%S", time.gmtime(seconds))

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