xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

8e2469477e62481030a99518adb64b34a3daef77

164

py

Python

agent/__init__.py

johnnylord/trytry-segmentation

a88d75571ddba92bd10ac2d7303bee9426188b62

[ "MIT" ]

null

agent/__init__.py

johnnylord/trytry-segmentation

a88d75571ddba92bd10ac2d7303bee9426188b62

[ "MIT" ]

null

agent/__init__.py

johnnylord/trytry-segmentation

a88d75571ddba92bd10ac2d7303bee9426188b62

[ "MIT" ]

null

import sys from .classification import ClassAgent from .segmentation import SegmentAgent def get_agent_cls(name): return getattr(sys.modules[__name__], name)

20.5

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null

0

1

0

null

0

1

0

5

8e3d7ab03a2cb9fe47a807c5fe66844b9c84895c

203

py

Python

easy_equities_client/utils/dataclasses.py

Cipher099/easy-equities-client

89786584a5e6fecd08d5dfce518197ac9c3a20ef

[ "MIT" ]

7

2021-07-26T09:51:42.000Z

2022-03-17T08:34:47.000Z

easy_equities_client/utils/dataclasses.py

Cipher099/easy-equities-client

89786584a5e6fecd08d5dfce518197ac9c3a20ef

[ "MIT" ]

1

2021-08-08T21:45:25.000Z

2021-08-17T07:41:16.000Z

easy_equities_client/utils/dataclasses.py

Cipher099/easy-equities-client

89786584a5e6fecd08d5dfce518197ac9c3a20ef

[ "MIT" ]

4

2021-08-07T14:21:35.000Z

2022-02-21T18:51:03.000Z

from dataclasses import asdict from typing import Iterable, List, TypeVar _T = TypeVar("_T") def list_of_dataclasses_to_dicts(values: Iterable[_T]) -> List[dict]: return list(map(asdict, values))

22.555556

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8

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null

0

1

0

null

0

1

0

5

8e45528a3fd3143885db559e49dc6cfce5c21457

27

py

Python

hello_everybody.py

athosmartins/python_course

267b745bedd56f89b18cbfae3b4efe71bb969525

[ "CC0-1.0" ]

null

hello_everybody.py

athosmartins/python_course

267b745bedd56f89b18cbfae3b4efe71bb969525

[ "CC0-1.0" ]

null

hello_everybody.py

athosmartins/python_course

267b745bedd56f89b18cbfae3b4efe71bb969525

[ "CC0-1.0" ]

null

print('hello everybody')

13.5

26

0.703704

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6.333333

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1

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null

0

1

0

1

0

5

f3f7b58b0ab562caa741b4775e70d574d9fb0aa9

9,443

py

Python

ecnet/datasets/load_data.py

ECRL/ECNet

85bd81862e705440bd8dc5fa843465bfd4101048

[ "MIT" ]

5

2020-05-13T02:03:11.000Z

2021-02-05T19:01:48.000Z

ecnet/datasets/load_data.py

ecrl/ecnet

85bd81862e705440bd8dc5fa843465bfd4101048

[ "MIT" ]

5

2019-02-06T22:59:50.000Z

2021-04-27T01:55:07.000Z

ecnet/datasets/load_data.py

TJKessler/ECNet

e7fe3e1674a3dd66f46f61337374ca8778031e34

[ "MIT" ]

2

2017-09-13T20:57:55.000Z

2017-09-21T01:05:25.000Z

r"""Pre-bundled data interface""" from typing import List, Tuple, Union from os import path from .structs import QSPRDatasetFromFile _DATA_PATH = path.join( path.dirname(path.abspath(__file__)), 'data' ) def _open_smiles_file(smiles_fn: str) -> List[str]: """ Args: smiles_fn (str): filename/path for SMILES file Returns: list[str]: [smiles_0, ..., smiles_N] """ with open(smiles_fn, 'r') as smi_file: smiles = smi_file.readlines() smi_file.close() smiles = [s.replace('\n', '') for s in smiles] return smiles def _open_target_file(target_fn: str) -> List[List[float]]: """ Args: target_fn (str): filename/path for target values file Returns: list[list[float]]: lists of target values, in preparation for torch.tensor of shape (n_targets, 1) """ with open(target_fn, 'r') as tar_file: target = tar_file.readlines() tar_file.close() target = [[float(t.replace('\n', ''))] for t in target] return target def _get_prop_paths(prop: str) -> Tuple[str, str]: """ Args: prop (str): any in ['bp', 'cn', 'cp', 'kv', 'lhv', 'mon', 'pp', 'ron', 'ysi', 'mp'] Returns: tuple[str, str]: (path to smiles file (str), path to targets file (str)) """ return ( path.join(_DATA_PATH, '{}.smiles'.format(prop)), path.join(_DATA_PATH, '{}.target'.format(prop)) ) def _get_file_data(prop: str) -> Tuple[List[str], List[List[float]]]: """ Args: prop (str): any in ['bp', 'cn', 'cp', 'kv', 'lhv', 'mon', 'pp', 'ron', 'ysi', 'mp'] Returns: tuple[list[str], list[list[float]]]: (smiles, targets) """ fn_smiles, fn_target = _get_prop_paths(prop) smiles = _open_smiles_file(fn_smiles) target = _open_target_file(fn_target) return (smiles, target) def _load_set(prop: str, backend: str) -> QSPRDatasetFromFile: """ Args: prop (str): any in ['bp', 'cn', 'cp', 'kv', 'lhv', 'mon', 'pp', 'ron', 'ysi', 'mp'] Returns: QSPRDatasetFromFile: loaded set """ fn_smiles, fn_target = _get_prop_paths(prop) target_vals = _open_target_file(fn_target) return QSPRDatasetFromFile(fn_smiles, target_vals, backend) def load_bp(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads boiling point data; target values given in Celsius Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('bp') return _load_set('bp', backend) def load_cn(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads cetane number data; target values given in CN units Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('cn') return _load_set('cn', backend) def load_cp(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads cloud point data; target values given in Celsius Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('cp') return _load_set('cp', backend) def load_kv(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads kinematic viscosity data; target values given in mm^2/s (cSt) at 313 deg. K Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('kv') return _load_set('kv', backend) def load_lhv(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads lower heating value data; target values given in MJ/kg = kJ/g Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('lhv') return _load_set('lhv', backend) def load_mon(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads motor octane number data; target values given in MON units Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('mon') return _load_set('mon', backend) def load_mp(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads melting point data; target values given in Celsius Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('mp') return _load_set('mp', backend) def load_pp(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads pour point data; target values given in Celsius Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('pp') return _load_set('pp', backend) def load_ron(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads research octane number data; target values given in RON units Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('ron') return _load_set('ron', backend) def load_ysi(as_dataset: bool = False, backend: str = 'padel') -> Union[ Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: """ Loads yield sooting index data; target values given in unified YSI units Args: as_dataset (bool, optional): if True, return QSPRDatasetFromFile object housing data; otherwise, return tuple of smiles and target values backend (str, optional): any in ['padel', 'alvadesc'] Returns: Union[Tuple[List[str], List[List[float]]], QSPRDatasetFromFile]: either tuple of (smiles, target vals) or QSPRDatasetFromFile """ if not as_dataset: return _get_file_data('ysi') return _load_set('ysi', backend)

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5

6d0f1a1e2699254c830411fa60cb5b5ca1a88e0d

128

py

Python

python/pandemic_simulator/environment/pandemic_testing_strategies/__init__.py

stacyvjong/PandemicSimulator

eca906f5dc8135d7c90a1582b96621235f745c17

[ "Apache-2.0" ]

null

python/pandemic_simulator/environment/pandemic_testing_strategies/__init__.py

stacyvjong/PandemicSimulator

eca906f5dc8135d7c90a1582b96621235f745c17

[ "Apache-2.0" ]

null

python/pandemic_simulator/environment/pandemic_testing_strategies/__init__.py

stacyvjong/PandemicSimulator

eca906f5dc8135d7c90a1582b96621235f745c17

[ "Apache-2.0" ]

null

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128

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5

6d11436e5588fcc9c520b1697a0e7d2bbbdf96dc

157

py

Python

UBM/__init__.py

inkenbrandt/UBM

f3b22058305761d63654a8caa671ec3b75d6209c

[ "MIT" ]

1

2019-09-07T17:26:59.000Z

UBM/__init__.py

inkenbrandt/UBM

f3b22058305761d63654a8caa671ec3b75d6209c

[ "MIT" ]

null

UBM/__init__.py

inkenbrandt/UBM

f3b22058305761d63654a8caa671ec3b75d6209c

[ "MIT" ]

1

2020-04-07T19:27:05.000Z

__version__ = '0.0.7' __author__ = 'Paul Inkenbrandt' __name__ = 'UBM' import UBM from UBM.calcs import * from UBM.getdata import * from UBM.zonal import *

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1

0

5

6d1dab31d6742d3d9a9102656c9cff651bbf13cf

84

py

Python

mfr/extensions/jsc3d/__init__.py

yacchin1205/RDM-modular-file-renderer

5bd18175a681d21e7be7fe0238132335a1cd8ded

[ "Apache-2.0" ]

36

2015-08-31T20:24:22.000Z

2021-12-17T17:02:44.000Z

mfr/extensions/jsc3d/__init__.py

yacchin1205/RDM-modular-file-renderer

5bd18175a681d21e7be7fe0238132335a1cd8ded

[ "Apache-2.0" ]

190

2015-01-02T06:22:01.000Z

2022-01-19T11:27:03.000Z

mfr/extensions/jsc3d/__init__.py

yacchin1205/RDM-modular-file-renderer

5bd18175a681d21e7be7fe0238132335a1cd8ded

[ "Apache-2.0" ]

47

2015-01-27T15:45:22.000Z

2021-01-27T22:43:03.000Z

from .render import JSC3DRenderer # noqa from .export import JSC3DExporter # noqa

28

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0.166667

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true

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1

0

1

0

5

6d44b36342e73bb5b2f36448bdbd37bce3c0f015

78

py

Python

app/models/posts.py

domanisamuel/uliza-api

5b4844671902aeca9243f60f86abaa5bcb3547e5

[ "MIT" ]

1

2019-09-14T19:44:24.000Z

app/models/posts.py

domanisamuel/uliza-api

5b4844671902aeca9243f60f86abaa5bcb3547e5

[ "MIT" ]

null

app/models/posts.py

domanisamuel/uliza-api

5b4844671902aeca9243f60f86abaa5bcb3547e5

[ "MIT" ]

1

2019-10-30T08:41:57.000Z

# posts model # create an empty list posts=[] def posts_db(): return posts

15.6

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5

edc45524c146ef744d65f9b9718efb2d1671e7a8

40

py

Python

test_enumerate.py

sbyount/pynet_test

a82e73cdac57f263361b287b543543ace4c7984c

[ "Apache-2.0" ]

null

test_enumerate.py

sbyount/pynet_test

a82e73cdac57f263361b287b543543ace4c7984c

[ "Apache-2.0" ]

null

test_enumerate.py

sbyount/pynet_test

a82e73cdac57f263361b287b543543ace4c7984c

[ "Apache-2.0" ]

null

nums = range(10) print nums # comment

6.666667

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40

4.5

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1

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5

edcf872a37333f7ff80ecd959d65419ccc53c6e9

357

py

Python

tests/test_util/test_first_and_only.py

u8sand/FAIRshake

8f6f3dde42de29b88e9a43bdd43f848382e3bad7

[ "Apache-2.0" ]

null

tests/test_util/test_first_and_only.py

u8sand/FAIRshake

8f6f3dde42de29b88e9a43bdd43f848382e3bad7

[ "Apache-2.0" ]

8

2018-06-05T17:01:43.000Z

2018-06-22T01:19:39.000Z

tests/test_util/test_first_and_only.py

u8sand/FAIRshake

8f6f3dde42de29b88e9a43bdd43f848382e3bad7

[ "Apache-2.0" ]

1

2018-06-06T17:22:28.000Z

from app.util.first_and_only import first, first_and_only def test_first(): assert first([1, 2]) == 1 def test_first_and_only(): assert first_and_only([1]) == 1 try: first_and_only([]) assert "Doesn't raise when empty." except: pass try: first_and_only([1, 2]) assert "Doesn't raise when more than one." except: pass

17.85

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null

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1

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5

ede594daf6f76c803cffaf03481e14fe0b86ee81

293

py

Python

park/api/loader.py

galperins4/ARK-Python

3a9bddfd605a6d4675cc1de00ab46c6304a7cf49

[ "MIT" ]

3

2017-12-22T06:27:57.000Z

2018-01-09T18:18:35.000Z

park/api/loader.py

faustbrian/ARK-Python-Client

3a9bddfd605a6d4675cc1de00ab46c6304a7cf49

[ "MIT" ]

2

2018-03-22T04:37:19.000Z

2018-05-04T03:16:47.000Z

park/api/loader.py

faustbrian/ARK-Python-Client

3a9bddfd605a6d4675cc1de00ab46c6304a7cf49

[ "MIT" ]

3

2017-12-22T19:13:49.000Z

2018-01-20T20:28:14.000Z

#!/usr/bin/env python from park.api.api import API class Loader(API): def status(self): return self.get('api/loader/status') def sync(self): return self.get('api/loader/status/sync') def autoconfigure(self): return self.get('api/loader/autoconfigure')

19.533333

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0.219895

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293

14

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false

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null

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1

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null

0

1

0

1

0

5

610c6d386558cc3ef93e10342bb3e92024584984

33

py

Python

DoraemonPocket/src/multiprocessor/__init__.py

lizhihao6/DoraemonPocket

4f1407efa8e2099bf80de9bbed324bf68d2f3640

[ "MIT" ]

null

DoraemonPocket/src/multiprocessor/__init__.py

lizhihao6/DoraemonPocket

4f1407efa8e2099bf80de9bbed324bf68d2f3640

[ "MIT" ]

null

DoraemonPocket/src/multiprocessor/__init__.py

lizhihao6/DoraemonPocket

4f1407efa8e2099bf80de9bbed324bf68d2f3640

[ "MIT" ]

null

from .main import multiprocessing

33

0.878788

4

33

7.25

1

0

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33

1

33

0.966667

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true

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null

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1

0

null

0

1

0

1

0

5

611a237aabd4c4c9c19a9162a40fb720a8684efb

141

py

Python

backend/apps/likes/admin.py

MgArreaza13/wonderhumans

865b65e4afa1ac32976a8c53959a7c58543dbe60

[ "MIT" ]

null

backend/apps/likes/admin.py

MgArreaza13/wonderhumans

865b65e4afa1ac32976a8c53959a7c58543dbe60

[ "MIT" ]

null

backend/apps/likes/admin.py

MgArreaza13/wonderhumans

865b65e4afa1ac32976a8c53959a7c58543dbe60

[ "MIT" ]

null

# From Django from django.contrib import admin # My models from .models import * # Register your models here. admin.site.register(LikeFeed)

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py

Python

intents/data/spider_eval/preprocess/get_tables.py

chhavip/debaised-analysis

3597d35ce74f8d20384d57f12f7eb65020f9370b

[ "Apache-2.0" ]

1

2020-06-24T20:57:02.000Z

intents/data/spider_eval/preprocess/get_tables.py

chhavip/debaised-analysis

3597d35ce74f8d20384d57f12f7eb65020f9370b

[ "Apache-2.0" ]

30

2020-06-01T13:42:25.000Z

2022-03-31T03:58:55.000Z

intents/data/spider_eval/preprocess/get_tables.py

chhavip/debaised-analysis

3597d35ce74f8d20384d57f12f7eb65020f9370b

[ "Apache-2.0" ]

10

2020-06-10T05:43:59.000Z

2020-08-20T10:32:24.000Z

version https://git-lfs.github.com/spec/v1 oid sha256:df305b7beb6ed92a2118aa747c60c9bc6b9fb07302365d63d9bd51e602ef1305 size 5440

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b63a83c7e92408720915aadb0bc88b9d1b47b708

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py

Python

LerpColors.py

Wally869/GradientsLibrary

cff88e7d3eb189623d3ab484af59ca7b8226746a

[ "CC0-1.0" ]

null

LerpColors.py

Wally869/GradientsLibrary

cff88e7d3eb189623d3ab484af59ca7b8226746a

[ "CC0-1.0" ]

null

LerpColors.py

Wally869/GradientsLibrary

cff88e7d3eb189623d3ab484af59ca7b8226746a

[ "CC0-1.0" ]

1

2022-03-20T21:07:16.000Z

from __future__ import annotations from typing import List, Dict def LerpColor(initialColor: List[float], targetColor: List[float], lerping_factor: float) -> List[float]: return [initialColor[i] + (targetColor[i] - initialColor[i]) * lerping_factor for i in range(len(initialColor))] def LerpColorMultipleSteps(initialColor: List[float], targetColor: List[float], number_steps: int) -> List[List[float]]: return [LerpColor(initialColor, targetColor, i/number_steps) for i in range(number_steps + 1)]

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py

Python

cajitos_site/bar/__init__.py

OlgaKuratkina/cajitos

0bc13f71281a1a67c8bcd1a3ae343ad0b14d9bad

[ "MIT" ]

null

cajitos_site/bar/__init__.py

OlgaKuratkina/cajitos

0bc13f71281a1a67c8bcd1a3ae343ad0b14d9bad

[ "MIT" ]

7

2020-05-08T19:51:22.000Z

2022-03-11T23:37:57.000Z

cajitos_site/bar/__init__.py

OlgaKuratkina/cajitos

0bc13f71281a1a67c8bcd1a3ae343ad0b14d9bad

[ "MIT" ]

null

from flask import Blueprint bar = Blueprint('bar', __name__, url_prefix='/bar')

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b684806df970cfaabc50fbb0819ea2373b2cd81c

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py

Python

application/guard.py

pachecobruno/python-ddd

81812848a567d4605df346ef3630718d320706cc

[ "MIT" ]

null

application/guard.py

pachecobruno/python-ddd

81812848a567d4605df346ef3630718d320706cc

[ "MIT" ]

null

application/guard.py

pachecobruno/python-ddd

81812848a567d4605df346ef3630718d320706cc

[ "MIT" ]

null

# def goard_not_empty(value): # pass

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py

Python

seffaflik/elektrik/__init__.py

tgbaozkn/seffaflik

b16bae9bf882ee81511c7f69428e58d22ec25600

[ "MIT" ]

10

2020-06-20T10:56:04.000Z

2022-02-03T18:23:59.000Z

seffaflik/elektrik/__init__.py

tgbaozkn/seffaflik

b16bae9bf882ee81511c7f69428e58d22ec25600

[ "MIT" ]

1

2022-02-01T11:31:33.000Z

2022-02-03T20:30:01.000Z

seffaflik/elektrik/__init__.py

tgbaozkn/seffaflik

b16bae9bf882ee81511c7f69428e58d22ec25600

[ "MIT" ]

6

2020-12-09T14:55:46.000Z

2022-03-31T11:50:36.000Z

from seffaflik.elektrik import (piyasalar, santraller, tuketim, uretim)

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fcf351e70693983cbd311144fed5ea836d9968c3

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py

Python

venv/lib/python3.7/site-packages/serial/abc/__init__.py

FilipKatulski/Data_logger

ba2671c310cd0529e30ef73c99963564953beb64

[ "MIT" ]

16

2020-09-20T22:32:54.000Z

2021-04-02T17:14:25.000Z

Venv-IDE/Lib/site-packages/serial/abc/__init__.py

myhumankit/Blind_IDE

5262a5dd106f3f52a374a6c1ef68ff53d8847001

[ "MIT" ]

9

2022-02-21T11:44:01.000Z

2022-03-14T15:36:08.000Z

Venv-IDE/Lib/site-packages/serial/abc/__init__.py

myhumankit/Blind_IDE

5262a5dd106f3f52a374a6c1ef68ff53d8847001

[ "MIT" ]

1

2022-02-21T03:09:29.000Z

# region Backwards Compatibility from __future__ import nested_scopes, generators, division, absolute_import, with_statement, \ print_function, unicode_literals from ..utilities.compatibility import backport backport() from . import model, properties

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py

Python

scikits/odes/tests/test_user_return_vals_cvode.py

cklb/odes

945a461754c8155bca88aa83d725f77720a40539

[ "BSD-3-Clause" ]

95

2015-02-12T15:33:24.000Z

2022-03-07T12:57:46.000Z

scikits/odes/tests/test_user_return_vals_cvode.py

cklb/odes

945a461754c8155bca88aa83d725f77720a40539

[ "BSD-3-Clause" ]

89

2015-01-22T12:42:26.000Z

2022-01-09T17:02:49.000Z

scikits/odes/tests/test_user_return_vals_cvode.py

cklb/odes

945a461754c8155bca88aa83d725f77720a40539

[ "BSD-3-Clause" ]

29

2015-01-30T09:20:56.000Z

2022-02-23T03:50:15.000Z

from numpy.testing import TestCase, run_module_suite from .. import ode from ..sundials.cvode import StatusEnum def normal_rhs(t, y, ydot): ydot[0] = t def complex_rhs(t, y, ydot): ydot[0] = t - y def rhs_with_return(t, y, ydot): ydot[0] = t return 0 def rhs_problem_late(t, y, ydot): ydot[0] = t if t > 0.5: return 1 def rhs_problem_immediate(t, y, ydot): return 1 def rhs_error_late(t, y, ydot): ydot[0] = t if t > 0.5: return -1 def rhs_error_immediate(t, y, ydot): return -1 def normal_root(t, y, g): g[0] = 1 def root_with_return(t, y, g): g[0] = 1 return 0 def root_late(t, y, g): g[0] = 1 if t > 0.5: g[0] = 0 def root_immediate(t, y, g): g[0] = 0 def root_error_late(t, y, g): g[0] = t if t > 0.5: return 1 def root_error_immediate(t, y, g): return 1 def normal_jac(t, y, fy, J): J[0][0] = 0 def jac_with_return(t, y, fy, J): J[0][0] = 0 return 0 def jac_problem_late(t, y, fy, J): J[0][0] = 1 if t > 0: return 1 def jac_problem_immediate(t, y, fy, J): return 1 def jac_error_late(t, y, fy, J): J[0][0] = 1 if t > 0: return -1 def jac_error_immediate(t, y, fy, J): return -1 def normal_jac_vec(v, Jv, t, y): Jv[0] = 0 def jac_vec_with_return(v, Jv, t, y): Jv[0] = 0 return None def jac_vec_problem_late(v, Jv, t, y): Jv[0] = v[0] if t > 0: return 1 def jac_vec_problem_immediate(v, Jv, t, y): return 1 def jac_vec_error_late(v, Jv, t, y): Jv[0] = v[0] if t > 0: return -1 def jac_vec_error_immediate(v, Jv, t, y): return -1 class TestCVodeReturn(TestCase): def __init__(self, *args, **kwargs): super(TestCVodeReturn, self).__init__(*args, **kwargs) self.solvername = "cvode" def test_normal_rhs(self): solver = ode(self.solvername, normal_rhs, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.SUCCESS, soln.flag ) def test_rhs_with_return(self): solver = ode(self.solvername, rhs_with_return, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.SUCCESS, soln.flag ) def test_rhs_problem_late(self): solver = ode(self.solvername, rhs_problem_late, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.TOO_MUCH_WORK, soln.flag ) def test_rhs_problem_immediate(self): solver = ode(self.solvername, rhs_problem_immediate, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.FIRST_RHSFUNC_ERR, soln.flag ) def test_rhs_error_late(self): solver = ode(self.solvername, rhs_error_late, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.RHSFUNC_FAIL, soln.flag ) def test_rhs_error_immediate(self): solver = ode(self.solvername, rhs_error_immediate, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.RHSFUNC_FAIL, soln.flag ) def test_normal_root(self): solver = ode(self.solvername, normal_rhs, rootfn=normal_root, nr_rootfns=1, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.SUCCESS, soln.flag ) def test_root_with_return(self): solver = ode(self.solvername, normal_rhs, rootfn=root_with_return, nr_rootfns=1, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.SUCCESS, soln.flag ) def test_root_late(self): solver = ode(self.solvername, normal_rhs, rootfn=root_late, nr_rootfns=1, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.ROOT_RETURN, soln.flag ) def test_root_immediate(self): solver = ode(self.solvername, normal_rhs, rootfn=root_immediate, nr_rootfns=1, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.SUCCESS, soln.flag ) def test_root_error_late(self): solver = ode(self.solvername, normal_rhs, rootfn=root_error_late, nr_rootfns=1, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.RTFUNC_FAIL, soln.flag ) def test_root_error_immediate(self): solver = ode(self.solvername, normal_rhs, rootfn=root_error_immediate, nr_rootfns=1, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.RTFUNC_FAIL, soln.flag ) def test_normal_jac(self): solver = ode(self.solvername, normal_rhs, jacfn=normal_jac, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.SUCCESS, soln.flag ) def test_jac_with_return(self): solver = ode(self.solvername, normal_rhs, jacfn=jac_with_return, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.SUCCESS, soln.flag ) def test_jac_problem_late(self): solver = ode(self.solvername, complex_rhs, jacfn=jac_problem_late, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.CONV_FAILURE, soln.flag ) def test_jac_problem_immediate(self): solver = ode(self.solvername, normal_rhs, jacfn=jac_problem_immediate, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.CONV_FAILURE, soln.flag ) def test_jac_error_late(self): solver = ode(self.solvername, complex_rhs, jacfn=jac_error_late, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.LSETUP_FAIL, soln.flag ) def test_jac_error_immediate(self): solver = ode(self.solvername, normal_rhs, jacfn=jac_error_immediate, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.LSETUP_FAIL, soln.flag ) def test_normal_jac_vec(self): solver = ode(self.solvername, normal_rhs, jac_times_vecfn=normal_jac_vec, old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.SUCCESS, soln.flag ) def test_jac_vec_with_return(self): solver = ode(self.solvername, normal_rhs, jac_times_vecfn=jac_vec_with_return, linsolver="spgmr", old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.SUCCESS, soln.flag ) def test_jac_vec_problem_late(self): solver = ode(self.solvername, complex_rhs, jac_times_vecfn=jac_vec_problem_late, linsolver="spgmr", old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.TOO_MUCH_WORK, soln.flag ) def test_jac_vec_problem_immediate(self): solver = ode(self.solvername, normal_rhs, jac_times_vecfn=jac_vec_problem_immediate, linsolver="spgmr", old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.TOO_MUCH_WORK, soln.flag ) def test_jac_vec_error_late(self): solver = ode(self.solvername, complex_rhs, jac_times_vecfn=jac_vec_error_late, linsolver="spgmr", old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.LSOLVE_FAIL, soln.flag ) def test_jac_vec_error_immediate(self): solver = ode(self.solvername, normal_rhs, jac_times_vecfn=jac_vec_error_immediate, linsolver="spgmr", old_api=False) soln = solver.solve([0, 1], [1]) self.assertEqual( StatusEnum.LSOLVE_FAIL, soln.flag ) class TestCVodesReturn(TestCVodeReturn): def __init__(self, *args, **kwargs): super(TestCVodesReturn, self).__init__(*args, **kwargs) self.solvername = "cvodes" if __name__ == "__main__": try: run_module_suite() except NameError: test = TestCVodeReturn() TestCVodeReturn.test_normal_rhs()

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py

Python

sappy/tests/__init__.py

jacebrowning/sappy

ab5da21f36385a3b3d34f1a6c1f60686f4522499

[ "MIT" ]

8

2016-06-10T14:21:42.000Z

2018-07-10T20:36:21.000Z

sappy/tests/__init__.py

jacebrowning/sappy

ab5da21f36385a3b3d34f1a6c1f60686f4522499

[ "MIT" ]

8

2016-06-10T22:10:02.000Z

2021-03-31T20:20:21.000Z

sappy/tests/__init__.py

jacebrowning/sappy

ab5da21f36385a3b3d34f1a6c1f60686f4522499

[ "MIT" ]

2

2016-06-10T21:34:47.000Z

2016-06-15T18:35:53.000Z

"""Unit tests for the `sappy` package."""

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1e6f828c44a9c149140baa0a2810e2171491c950

374

py

Python

stores/services.py

WorqHat/contact-tracing

77adfdeb009ef0a4900a36d8756526cbdf3f60d2

[ "MIT" ]

null

stores/services.py

WorqHat/contact-tracing

77adfdeb009ef0a4900a36d8756526cbdf3f60d2

[ "MIT" ]

null

stores/services.py

WorqHat/contact-tracing

77adfdeb009ef0a4900a36d8756526cbdf3f60d2

[ "MIT" ]

null

from django.contrib.gis.geos import Point from django.contrib.gis.db.models.functions import Distance from django.contrib.gis.measure import D from django.contrib.gis.geos import GEOSGeometry # import your models here def get_nearby_stores_within(latitude: float, longitude: float, km: int=10, limit: int=None, srid: int=4326): # Your code goes here: return None

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949c0d9cddfd7fb0e501b0de642b35b222a10d8d

213

py

Python

nimfa/utils/__init__.py

askerdb/nimfa

3e3353e60d53fd409b53c46fde23f4f6fef64aaf

[ "BSD-3-Clause" ]

325

2015-04-05T01:37:17.000Z

2020-02-01T08:06:02.000Z

nimfa/utils/__init__.py

askerdb/nimfa

3e3353e60d53fd409b53c46fde23f4f6fef64aaf

[ "BSD-3-Clause" ]

32

2015-03-30T12:55:47.000Z

2020-01-17T10:53:54.000Z

nimfa/utils/__init__.py

askerdb/nimfa

3e3353e60d53fd409b53c46fde23f4f6fef64aaf

[ "BSD-3-Clause" ]

104

2015-03-25T22:42:47.000Z

2020-01-30T23:06:36.000Z

""" This package contains implementations of linear algebra operations for sparse and dense matrices and utils for convenient operation of nimfa library. """ from . import linalg from . import utils

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5

94b2ca1387d03070aee2e234f8a5114c59e7f0e1

386

py

Python

pages/themes/beginners/sequenceDataTypes/examples/list_of_tuples.py

ProgressBG-Python-Course/ProgressBG-VC2-Python

03b892a42ee1fad3d4f97e328e06a4b1573fd356

[ "MIT" ]

null

pages/themes/beginners/sequenceDataTypes/examples/list_of_tuples.py

ProgressBG-Python-Course/ProgressBG-VC2-Python

03b892a42ee1fad3d4f97e328e06a4b1573fd356

[ "MIT" ]

null

pages/themes/beginners/sequenceDataTypes/examples/list_of_tuples.py

ProgressBG-Python-Course/ProgressBG-VC2-Python

03b892a42ee1fad3d4f97e328e06a4b1573fd356

[ "MIT" ]

null

### create list_of_tuples: points = [ (1,2), (3,4), (5,6) ] ### retrieve the first element from the first tuple: print(points[0][0]) # 1 ### retrieve the last element from the first tuple: print(points[0][-1]) # 2 ### retrieve the first element from the last tuple: print(points[-1][0]) # 5 ### retrieve the last element from the last tuple: print(points[-1][-1]) # 6

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0.31746

0.181818

0.231405

0.190083

0.842975

0.586777

0

0.058065

0.196891

386

24

53

16.083333

0.722581

0.57513

0

1

0

false

0

0.444444

0

null

0

1

0

null

0

1

0

5

94dafd270099e8ff2bfddd997ed67d6afc111ffa

75

py

Python

higgins/__init__.py

bfortuner/higgins

c8ab098c1496ee9b45efc3fc667d894d86031f67

[ "MIT" ]

null

higgins/__init__.py

bfortuner/higgins

c8ab098c1496ee9b45efc3fc667d894d86031f67

[ "MIT" ]

null

higgins/__init__.py

bfortuner/higgins

c8ab098c1496ee9b45efc3fc667d894d86031f67

[ "MIT" ]

null

from dotenv import dotenv_values, load_dotenv load_dotenv(".env.secret")

15

45

0.8

11

75

5.181818

0.636364

0.350877

0

0.106667

75

4

46

18.75

0.850746

0

0.146667

0

1

0

true

0

0.5

0

0.5

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1

0

null

1

0

1

0

null

0

1

0

1

0

5

bfab9ffb141f68395208dd47218c008366b1fdb8

41

py

Python

src/tweet_extraction/test1.py

Swadesh13/twitter-data-collection

b72c1d94b36c3a981f68ddc01b950fd36b3d19e1

[ "MIT" ]

null

src/tweet_extraction/test1.py

Swadesh13/twitter-data-collection

b72c1d94b36c3a981f68ddc01b950fd36b3d19e1

[ "MIT" ]

null

src/tweet_extraction/test1.py

Swadesh13/twitter-data-collection

b72c1d94b36c3a981f68ddc01b950fd36b3d19e1

[ "MIT" ]

1

2021-04-26T04:57:26.000Z

def f(t): t.append(1) t.append(2)

13.666667

15

0.512195

9

41

2.333333

0.666667

0

0.066667

0.268293

41

3

16

13.666667

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0

1

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false

0

0.333333

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1

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null

1

0

1

0

null

0

1

0

5

bfc967eb646999613b6d9cedbba5a89d5752dfd0

26,800

py

Python

tests/test_album.py

spankders/pyspotify

b18ac0c72771e6c3418f0d57b775ae5c6e1ab44e

[ "Apache-2.0" ]

1

2019-07-20T08:31:49.000Z

tests/test_album.py

spankders/pyspotify

b18ac0c72771e6c3418f0d57b775ae5c6e1ab44e

[ "Apache-2.0" ]

null

tests/test_album.py

spankders/pyspotify

b18ac0c72771e6c3418f0d57b775ae5c6e1ab44e

[ "Apache-2.0" ]

null

from __future__ import unicode_literals import unittest import spotify from spotify import compat import tests from tests import mock @mock.patch('spotify.album.lib', spec=spotify.lib) class AlbumTest(unittest.TestCase): def setUp(self): self.session = tests.create_session_mock() def test_create_without_uri_or_sp_album_fails(self, lib_mock): with self.assertRaises(AssertionError): spotify.Album(self.session) @mock.patch('spotify.Link', spec=spotify.Link) def test_create_from_uri(self, link_mock, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) link_instance_mock = link_mock.return_value link_instance_mock.as_album.return_value = spotify.Album( self.session, sp_album=sp_album) uri = 'spotify:album:foo' result = spotify.Album(self.session, uri=uri) link_mock.assert_called_with(self.session, uri=uri) link_instance_mock.as_album.assert_called_with() lib_mock.sp_album_add_ref.assert_called_with(sp_album) self.assertEqual(result._sp_album, sp_album) @mock.patch('spotify.Link', spec=spotify.Link) def test_create_from_uri_fail_raises_error(self, link_mock, lib_mock): link_instance_mock = link_mock.return_value link_instance_mock.as_album.return_value = None uri = 'spotify:album:foo' with self.assertRaises(ValueError): spotify.Album(self.session, uri=uri) def test_adds_ref_to_sp_album_when_created(self, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) spotify.Album(self.session, sp_album=sp_album) lib_mock.sp_album_add_ref.assert_called_with(sp_album) def test_releases_sp_album_when_album_dies(self, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) album = None # noqa tests.gc_collect() lib_mock.sp_album_release.assert_called_with(sp_album) @mock.patch('spotify.Link', spec=spotify.Link) def test_repr(self, link_mock, lib_mock): link_instance_mock = link_mock.return_value link_instance_mock.uri = 'foo' sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = repr(album) self.assertEqual(result, 'Album(%r)' % 'foo') def test_eq(self, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) album1 = spotify.Album(self.session, sp_album=sp_album) album2 = spotify.Album(self.session, sp_album=sp_album) self.assertTrue(album1 == album2) self.assertFalse(album1 == 'foo') def test_ne(self, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) album1 = spotify.Album(self.session, sp_album=sp_album) album2 = spotify.Album(self.session, sp_album=sp_album) self.assertFalse(album1 != album2) def test_hash(self, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) album1 = spotify.Album(self.session, sp_album=sp_album) album2 = spotify.Album(self.session, sp_album=sp_album) self.assertEqual(hash(album1), hash(album2)) def test_is_loaded(self, lib_mock): lib_mock.sp_album_is_loaded.return_value = 1 sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.is_loaded lib_mock.sp_album_is_loaded.assert_called_once_with(sp_album) self.assertTrue(result) @mock.patch('spotify.utils.load') def test_load(self, load_mock, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) album.load(10) load_mock.assert_called_with(self.session, album, timeout=10) def test_is_available(self, lib_mock): lib_mock.sp_album_is_available.return_value = 1 sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.is_available lib_mock.sp_album_is_available.assert_called_once_with(sp_album) self.assertTrue(result) def test_is_available_is_none_if_unloaded(self, lib_mock): lib_mock.sp_album_is_loaded.return_value = 0 sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.is_available lib_mock.sp_album_is_loaded.assert_called_once_with(sp_album) self.assertIsNone(result) @mock.patch('spotify.artist.lib', spec=spotify.lib) def test_artist(self, artist_lib_mock, lib_mock): sp_artist = spotify.ffi.cast('sp_artist *', 43) lib_mock.sp_album_artist.return_value = sp_artist sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.artist lib_mock.sp_album_artist.assert_called_with(sp_album) self.assertEqual(artist_lib_mock.sp_artist_add_ref.call_count, 1) self.assertIsInstance(result, spotify.Artist) self.assertEqual(result._sp_artist, sp_artist) @mock.patch('spotify.artist.lib', spec=spotify.lib) def test_artist_if_unloaded(self, artist_lib_mock, lib_mock): lib_mock.sp_album_artist.return_value = spotify.ffi.NULL sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.artist lib_mock.sp_album_artist.assert_called_with(sp_album) self.assertIsNone(result) @mock.patch('spotify.Image', spec=spotify.Image) def test_cover(self, image_mock, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) sp_image_id = spotify.ffi.new('char[]', b'cover-id') lib_mock.sp_album_cover.return_value = sp_image_id sp_image = spotify.ffi.cast('sp_image *', 43) lib_mock.sp_image_create.return_value = sp_image image_mock.return_value = mock.sentinel.image image_size = spotify.ImageSize.SMALL callback = mock.Mock() result = album.cover(image_size, callback=callback) self.assertIs(result, mock.sentinel.image) lib_mock.sp_album_cover.assert_called_with( sp_album, int(image_size)) lib_mock.sp_image_create.assert_called_with( self.session._sp_session, sp_image_id) # Since we *created* the sp_image, we already have a refcount of 1 and # shouldn't increase the refcount when wrapping this sp_image in an # Image object image_mock.assert_called_with( self.session, sp_image=sp_image, add_ref=False, callback=callback) @mock.patch('spotify.Image', spec=spotify.Image) def test_cover_defaults_to_normal_size(self, image_mock, lib_mock): sp_image_id = spotify.ffi.new('char[]', b'cover-id') lib_mock.sp_album_cover.return_value = sp_image_id sp_image = spotify.ffi.cast('sp_image *', 43) lib_mock.sp_image_create.return_value = sp_image sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) album.cover() lib_mock.sp_album_cover.assert_called_with( sp_album, int(spotify.ImageSize.NORMAL)) def test_cover_is_none_if_null(self, lib_mock): lib_mock.sp_album_cover.return_value = spotify.ffi.NULL sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.cover() lib_mock.sp_album_cover.assert_called_with( sp_album, int(spotify.ImageSize.NORMAL)) self.assertIsNone(result) @mock.patch('spotify.Link', spec=spotify.Link) def test_cover_link_creates_link_to_cover(self, link_mock, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) sp_link = spotify.ffi.cast('sp_link *', 43) lib_mock.sp_link_create_from_album_cover.return_value = sp_link link_mock.return_value = mock.sentinel.link image_size = spotify.ImageSize.SMALL result = album.cover_link(image_size) lib_mock.sp_link_create_from_album_cover.assert_called_once_with( sp_album, int(image_size)) link_mock.assert_called_once_with( self.session, sp_link=sp_link, add_ref=False) self.assertEqual(result, mock.sentinel.link) @mock.patch('spotify.Link', spec=spotify.Link) def test_cover_link_defaults_to_normal_size(self, link_mock, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) sp_link = spotify.ffi.cast('sp_link *', 43) lib_mock.sp_link_create_from_album_cover.return_value = sp_link link_mock.return_value = mock.sentinel.link album.cover_link() lib_mock.sp_link_create_from_album_cover.assert_called_once_with( sp_album, int(spotify.ImageSize.NORMAL)) def test_name(self, lib_mock): lib_mock.sp_album_name.return_value = spotify.ffi.new( 'char[]', b'Foo Bar Baz') sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.name lib_mock.sp_album_name.assert_called_once_with(sp_album) self.assertEqual(result, 'Foo Bar Baz') def test_name_is_none_if_unloaded(self, lib_mock): lib_mock.sp_album_name.return_value = spotify.ffi.new('char[]', b'') sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.name lib_mock.sp_album_name.assert_called_once_with(sp_album) self.assertIsNone(result) def test_year(self, lib_mock): lib_mock.sp_album_year.return_value = 2013 sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.year lib_mock.sp_album_year.assert_called_once_with(sp_album) self.assertEqual(result, 2013) def test_year_is_none_if_unloaded(self, lib_mock): lib_mock.sp_album_is_loaded.return_value = 0 sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.year lib_mock.sp_album_is_loaded.assert_called_once_with(sp_album) self.assertIsNone(result) def test_type(self, lib_mock): lib_mock.sp_album_type.return_value = int(spotify.AlbumType.SINGLE) sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.type lib_mock.sp_album_type.assert_called_once_with(sp_album) self.assertIs(result, spotify.AlbumType.SINGLE) def test_type_is_none_if_unloaded(self, lib_mock): lib_mock.sp_album_is_loaded.return_value = 0 sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) result = album.type lib_mock.sp_album_is_loaded.assert_called_once_with(sp_album) self.assertIsNone(result) @mock.patch('spotify.Link', spec=spotify.Link) def test_link_creates_link_to_album(self, link_mock, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 42) album = spotify.Album(self.session, sp_album=sp_album) sp_link = spotify.ffi.cast('sp_link *', 43) lib_mock.sp_link_create_from_album.return_value = sp_link link_mock.return_value = mock.sentinel.link result = album.link link_mock.assert_called_once_with( self.session, sp_link=sp_link, add_ref=False) self.assertEqual(result, mock.sentinel.link) @mock.patch('spotify.album.lib', spec=spotify.lib) class AlbumBrowserTest(unittest.TestCase): def setUp(self): self.session = tests.create_session_mock() spotify._session_instance = self.session def tearDown(self): spotify._session_instance = None def test_create_without_album_or_sp_albumbrowse_fails(self, lib_mock): with self.assertRaises(AssertionError): spotify.AlbumBrowser(self.session) def test_create_from_album(self, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 43) album = spotify.Album(self.session, sp_album=sp_album) sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) lib_mock.sp_albumbrowse_create.return_value = sp_albumbrowse result = album.browse() lib_mock.sp_albumbrowse_create.assert_called_with( self.session._sp_session, sp_album, mock.ANY, mock.ANY) self.assertIsInstance(result, spotify.AlbumBrowser) albumbrowse_complete_cb = ( lib_mock.sp_albumbrowse_create.call_args[0][2]) userdata = lib_mock.sp_albumbrowse_create.call_args[0][3] self.assertFalse(result.loaded_event.is_set()) albumbrowse_complete_cb(sp_albumbrowse, userdata) self.assertTrue(result.loaded_event.is_set()) def test_create_from_album_with_callback(self, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 43) album = spotify.Album(self.session, sp_album=sp_album) sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) lib_mock.sp_albumbrowse_create.return_value = sp_albumbrowse callback = mock.Mock() result = album.browse(callback) lib_mock.sp_albumbrowse_create.assert_called_with( self.session._sp_session, sp_album, mock.ANY, mock.ANY) albumbrowse_complete_cb = ( lib_mock.sp_albumbrowse_create.call_args[0][2]) userdata = lib_mock.sp_albumbrowse_create.call_args[0][3] albumbrowse_complete_cb(sp_albumbrowse, userdata) result.loaded_event.wait(3) callback.assert_called_with(result) def test_browser_is_gone_before_callback_is_called(self, lib_mock): sp_album = spotify.ffi.cast('sp_album *', 43) album = spotify.Album(self.session, sp_album=sp_album) sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) lib_mock.sp_albumbrowse_create.return_value = sp_albumbrowse callback = mock.Mock() result = spotify.AlbumBrowser( self.session, album=album, callback=callback) loaded_event = result.loaded_event result = None # noqa tests.gc_collect() # The mock keeps the handle/userdata alive, thus this test doesn't # really test that session._callback_handles keeps the handle alive. albumbrowse_complete_cb = ( lib_mock.sp_albumbrowse_create.call_args[0][2]) userdata = lib_mock.sp_albumbrowse_create.call_args[0][3] albumbrowse_complete_cb(sp_albumbrowse, userdata) loaded_event.wait(3) self.assertEqual(callback.call_count, 1) self.assertEqual( callback.call_args[0][0]._sp_albumbrowse, sp_albumbrowse) def test_adds_ref_to_sp_albumbrowse_when_created(self, lib_mock): session = tests.create_session_mock() sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) spotify.AlbumBrowser(session, sp_albumbrowse=sp_albumbrowse) lib_mock.sp_albumbrowse_add_ref.assert_called_with(sp_albumbrowse) def test_releases_sp_albumbrowse_when_album_dies(self, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) browser = None # noqa tests.gc_collect() lib_mock.sp_albumbrowse_release.assert_called_with(sp_albumbrowse) @mock.patch('spotify.Link', spec=spotify.Link) def test_repr(self, link_mock, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) lib_mock.sp_albumbrowse_is_loaded.return_value = 1 sp_album = spotify.ffi.cast('sp_album *', 43) lib_mock.sp_albumbrowse_album.return_value = sp_album link_instance_mock = link_mock.return_value link_instance_mock.uri = 'foo' result = repr(browser) self.assertEqual(result, 'AlbumBrowser(%r)' % 'foo') def test_repr_if_unloaded(self, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) lib_mock.sp_albumbrowse_is_loaded.return_value = 0 result = repr(browser) self.assertEqual(result, 'AlbumBrowser(<not loaded>)') def test_eq(self, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser1 = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) browser2 = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) self.assertTrue(browser1 == browser2) self.assertFalse(browser1 == 'foo') def test_ne(self, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser1 = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) browser2 = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) self.assertFalse(browser1 != browser2) def test_hash(self, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser1 = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) browser2 = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) self.assertEqual(hash(browser1), hash(browser2)) def test_is_loaded(self, lib_mock): lib_mock.sp_albumbrowse_is_loaded.return_value = 1 sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) result = browser.is_loaded lib_mock.sp_albumbrowse_is_loaded.assert_called_once_with( sp_albumbrowse) self.assertTrue(result) @mock.patch('spotify.utils.load') def test_load(self, load_mock, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) browser.load(10) load_mock.assert_called_with(self.session, browser, timeout=10) def test_error(self, lib_mock): lib_mock.sp_albumbrowse_error.return_value = int( spotify.ErrorType.OTHER_PERMANENT) sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) result = browser.error lib_mock.sp_albumbrowse_error.assert_called_once_with(sp_albumbrowse) self.assertIs(result, spotify.ErrorType.OTHER_PERMANENT) def test_backend_request_duration(self, lib_mock): lib_mock.sp_albumbrowse_backend_request_duration.return_value = 137 sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) result = browser.backend_request_duration lib_mock.sp_albumbrowse_backend_request_duration.assert_called_with( sp_albumbrowse) self.assertEqual(result, 137) def test_backend_request_duration_when_not_loaded(self, lib_mock): lib_mock.sp_albumbrowse_is_loaded.return_value = 0 sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) result = browser.backend_request_duration lib_mock.sp_albumbrowse_is_loaded.assert_called_with(sp_albumbrowse) self.assertEqual( lib_mock.sp_albumbrowse_backend_request_duration.call_count, 0) self.assertIsNone(result) def test_album(self, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) sp_album = spotify.ffi.cast('sp_album *', 43) lib_mock.sp_albumbrowse_album.return_value = sp_album result = browser.album self.assertIsInstance(result, spotify.Album) self.assertEqual(result._sp_album, sp_album) def test_album_when_not_loaded(self, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) lib_mock.sp_albumbrowse_album.return_value = spotify.ffi.NULL result = browser.album lib_mock.sp_albumbrowse_album.assert_called_with(sp_albumbrowse) self.assertIsNone(result) @mock.patch('spotify.artist.lib', spec=spotify.lib) def test_artist(self, artist_lib_mock, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) sp_artist = spotify.ffi.cast('sp_artist *', 43) lib_mock.sp_albumbrowse_artist.return_value = sp_artist result = browser.artist self.assertIsInstance(result, spotify.Artist) self.assertEqual(result._sp_artist, sp_artist) def test_artist_when_not_loaded(self, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) lib_mock.sp_albumbrowse_artist.return_value = spotify.ffi.NULL result = browser.artist lib_mock.sp_albumbrowse_artist.assert_called_with(sp_albumbrowse) self.assertIsNone(result) def test_copyrights(self, lib_mock): copyright = spotify.ffi.new('char[]', b'Apple Records 1973') lib_mock.sp_albumbrowse_num_copyrights.return_value = 1 lib_mock.sp_albumbrowse_copyright.return_value = copyright sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) self.assertEqual(lib_mock.sp_albumbrowse_add_ref.call_count, 1) result = browser.copyrights self.assertEqual(lib_mock.sp_albumbrowse_add_ref.call_count, 2) self.assertEqual(len(result), 1) lib_mock.sp_albumbrowse_num_copyrights.assert_called_with( sp_albumbrowse) item = result[0] self.assertIsInstance(item, compat.text_type) self.assertEqual(item, 'Apple Records 1973') self.assertEqual(lib_mock.sp_albumbrowse_copyright.call_count, 1) lib_mock.sp_albumbrowse_copyright.assert_called_with(sp_albumbrowse, 0) def test_copyrights_if_no_copyrights(self, lib_mock): lib_mock.sp_albumbrowse_num_copyrights.return_value = 0 sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) result = browser.copyrights self.assertEqual(len(result), 0) lib_mock.sp_albumbrowse_num_copyrights.assert_called_with( sp_albumbrowse) self.assertEqual(lib_mock.sp_albumbrowse_copyright.call_count, 0) def test_copyrights_if_unloaded(self, lib_mock): lib_mock.sp_albumbrowse_is_loaded.return_value = 0 sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) result = browser.copyrights lib_mock.sp_albumbrowse_is_loaded.assert_called_with(sp_albumbrowse) self.assertEqual(len(result), 0) @mock.patch('spotify.track.lib', spec=spotify.lib) def test_tracks(self, track_lib_mock, lib_mock): sp_track = spotify.ffi.cast('sp_track *', 43) lib_mock.sp_albumbrowse_num_tracks.return_value = 1 lib_mock.sp_albumbrowse_track.return_value = sp_track sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) self.assertEqual(lib_mock.sp_albumbrowse_add_ref.call_count, 1) result = browser.tracks self.assertEqual(lib_mock.sp_albumbrowse_add_ref.call_count, 2) self.assertEqual(len(result), 1) lib_mock.sp_albumbrowse_num_tracks.assert_called_with(sp_albumbrowse) item = result[0] self.assertIsInstance(item, spotify.Track) self.assertEqual(item._sp_track, sp_track) self.assertEqual(lib_mock.sp_albumbrowse_track.call_count, 1) lib_mock.sp_albumbrowse_track.assert_called_with(sp_albumbrowse, 0) track_lib_mock.sp_track_add_ref.assert_called_with(sp_track) def test_tracks_if_no_tracks(self, lib_mock): lib_mock.sp_albumbrowse_num_tracks.return_value = 0 sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) result = browser.tracks self.assertEqual(len(result), 0) lib_mock.sp_albumbrowse_num_tracks.assert_called_with(sp_albumbrowse) self.assertEqual(lib_mock.sp_albumbrowse_track.call_count, 0) def test_tracks_if_unloaded(self, lib_mock): lib_mock.sp_albumbrowse_is_loaded.return_value = 0 sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) result = browser.tracks lib_mock.sp_albumbrowse_is_loaded.assert_called_with(sp_albumbrowse) self.assertEqual(len(result), 0) def test_review(self, lib_mock): sp_albumbrowse = spotify.ffi.cast('sp_albumbrowse *', 42) browser = spotify.AlbumBrowser( self.session, sp_albumbrowse=sp_albumbrowse) review = spotify.ffi.new('char[]', b'A nice album') lib_mock.sp_albumbrowse_review.return_value = review result = browser.review self.assertIsInstance(result, compat.text_type) self.assertEqual(result, 'A nice album') class AlbumTypeTest(unittest.TestCase): def test_has_constants(self): self.assertEqual(spotify.AlbumType.ALBUM, 0) self.assertEqual(spotify.AlbumType.SINGLE, 1)

39.411765

79

0.696828

3,547

26,800

4.922188

0.051875

0.139241

0.064952

0.077897

0.847643

0.795635

0.769517

0.726044

0.694942

0.654276

0

0.011256

0.207687

26,800

679

80

39.469809

0.810964

0.01097

0

0.650794

0

0.048421

0

0.232143

1

0.115079

false

0

0.011905

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0.132937

0

null

0

1

0

1

0

null

0

5

bfd34bc56d52821f908b1af998aa8de5581aabe0

347

py

Python

Darlington/phase1/python Basic 2/day 26 solution/qtn5.py

CodedLadiesInnovateTech/-python-challenge-solutions

430cd3eb84a2905a286819eef384ee484d8eb9e7

[ "MIT" ]

6

2020-05-23T19:53:25.000Z

2021-05-08T20:21:30.000Z

Darlington/phase1/python Basic 2/day 26 solution/qtn5.py

CodedLadiesInnovateTech/-python-challenge-solutions

430cd3eb84a2905a286819eef384ee484d8eb9e7

[ "MIT" ]

8

2020-05-14T18:53:12.000Z

2020-07-03T00:06:20.000Z

Darlington/phase1/python Basic 2/day 26 solution/qtn5.py

CodedLadiesInnovateTech/-python-challenge-solutions

430cd3eb84a2905a286819eef384ee484d8eb9e7

[ "MIT" ]

39

2020-05-10T20:55:02.000Z

2020-09-12T17:40:59.000Z

#program to check whether every even index contains an even number # and every odd index contains odd number of a given list. def odd_even_position(nums): return all(nums[i]%2==i%2 for i in range(len(nums))) print(odd_even_position([2, 1, 4, 3, 6, 7, 6, 3])) print(odd_even_position([2, 1, 4, 3, 6, 7, 6, 4])) print(odd_even_position([4, 1, 2]))

49.571429

66

0.70317

71

347

3.323944

0.464789

0.118644

0.254237

0.228814

0

0.070946

0.146974

347

7

67

49.571429

0.726351

0.354467

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0.2

false

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0.2

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0.6

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null

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1

0

null

0

1

0

1

0

5

44d75cb245c611754dd7b4e77f25c2a7f6054a2a

34

py

Python

version.py

Vodzilla/OoT-Randomizer

9b327f5508777b455884497084408c7b4f152a0f

[ "MIT" ]

null

version.py

Vodzilla/OoT-Randomizer

9b327f5508777b455884497084408c7b4f152a0f

[ "MIT" ]

null

version.py

Vodzilla/OoT-Randomizer

9b327f5508777b455884497084408c7b4f152a0f

[ "MIT" ]

null

__version__ = '6.2.76 rreal-2.2.3'

34

0.676471

8

34

2.375

0.75

0

0.225806

0.088235

34

1

34

0.387097

0

0.514286

0

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false

0

1

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null

0

1

0

1

0

1

0

null

0

5

44def8689134f67aa1b860487f12be6e042857cf

2,930

py

Python

tests/test_binaryTree.py

maxotar/datastructures

ba6c499e0bd894ff9b01557048e7a93d91774d39

[ "MIT" ]

null

tests/test_binaryTree.py

maxotar/datastructures

ba6c499e0bd894ff9b01557048e7a93d91774d39

[ "MIT" ]

null

tests/test_binaryTree.py

maxotar/datastructures

ba6c499e0bd894ff9b01557048e7a93d91774d39

[ "MIT" ]

null

from datastructures.binaryTree import BinaryTree def test_creation(): root = BinaryTree(7) assert root.data == 7 assert root.left is None assert root.right is None def test_insertion(): root = BinaryTree(0) root.insertRight(2) root.insertRight(1) assert root.right.data == 1 assert root.right.right.data == 2 def test_preorder(): root = BinaryTree(1) root.left = BinaryTree(2) root.left.left = BinaryTree(4) root.left.right = BinaryTree(5) root.right = BinaryTree(3) assert list(root.preorder()) == [1, 2, 4, 5, 3] def test_inorder(): root = BinaryTree(1) root.left = BinaryTree(2) root.left.left = BinaryTree(4) root.left.right = BinaryTree(5) root.right = BinaryTree(3) assert list(root.inorder()) == [4, 2, 5, 1, 3] def test_postorder(): root = BinaryTree(1) root.left = BinaryTree(2) root.left.left = BinaryTree(4) root.left.right = BinaryTree(5) root.right = BinaryTree(3) assert list(root.postorder()) == [4, 5, 2, 3, 1] def test_levelorder(): root = BinaryTree(1) root.left = BinaryTree(2) root.left.left = BinaryTree(4) root.left.right = BinaryTree(5) root.right = BinaryTree(3) root.right.left = BinaryTree(6) root.right.right = BinaryTree(7) assert list(root.levelorder()) == [1, 2, 3, 4, 5, 6, 7] def test_levelordernested(): root = BinaryTree(1) root.left = BinaryTree(2) root.left.left = BinaryTree(4) root.left.right = BinaryTree(5) root.right = BinaryTree(3) root.right.left = BinaryTree(6) root.right.right = BinaryTree(7) assert list(root.levelordernested()) == [[1], [2, 3], [4, 5, 6, 7]] def test_toList(): root = BinaryTree(1) root.left = BinaryTree(2) root.left.left = BinaryTree(4) root.left.right = BinaryTree(5) root.right = BinaryTree(3) root.right.left = BinaryTree(6) root.right.right = BinaryTree(7) assert root.toList() == [1, 2, 3, 4, 5, 6, 7] def test___str__(): root = BinaryTree(1) root.left = BinaryTree(2) root.left.left = BinaryTree(4) root.left.right = BinaryTree(5) root.right = BinaryTree(3) root.right.left = BinaryTree(6) root.right.right = BinaryTree(7) assert root.__str__() == str([1, 2, 3, 4, 5, 6, 7]) def test_height(): root = BinaryTree(1) root.left = BinaryTree(2) root.left.left = BinaryTree(4) root.left.right = BinaryTree(5) root.right = BinaryTree(3) root.right.left = BinaryTree(6) root.right.right = BinaryTree(7) assert root.height() == 3 # def test_remove(): # root = BinaryTree(1) # root.left = BinaryTree(2) # root.left.left = BinaryTree(4) # root.left.right = BinaryTree(5) # root.right = BinaryTree(3) # root.right.left = BinaryTree(6) # root.right.right = BinaryTree(7) # assert list(root.levelorder()) == [1, 2, 3, 4, 5, 6, 7] # root.remove(

26.636364

71

0.630375

411

2,930

4.447689

0.082725

0.122538

0.073851

0.093545

0.765864

0.739059

0

0.050196

0.218089

2,930

109

72

26.880734

0.747708

0.110922

0

0.641026

0

0.166667

1

0.128205

false

0

0.012821

0

0.141026

0

null

0

1

0

null

0

5

44ef5ab6401a4468d39f7f1e5a712810a50d5f98

2,091

py

Python

populous/advertising/urls.py

caiges/populous

d07094f9d6b2528d282ed99af0063002480bc00b

[ "BSD-3-Clause" ]

2

2016-05-09T01:17:08.000Z

2017-07-18T23:35:01.000Z

populous/advertising/urls.py

caiges/populous

d07094f9d6b2528d282ed99af0063002480bc00b

[ "BSD-3-Clause" ]

null

populous/advertising/urls.py

caiges/populous

d07094f9d6b2528d282ed99af0063002480bc00b

[ "BSD-3-Clause" ]

null

from django.conf.urls.defaults import * urlpatterns = patterns('', (r'^/?$', 'populous.advertising.views.index'), (r'^classifieds/?$', 'populous.advertising.views.classifieds_index'), (r'^classifieds/list/?$', 'django.views.generic.simple.direct_to_template', {'template': 'advertising/classifieds/list.html'}), # (r'^classifieds/categories/?$', 'populous.advertising.views.classifieds_category_list'), # (r'^classifieds/categories/(?P<slug>[\w-]+)/?$', 'populous.advertising.views.classifieds_category_detail'), # (r'^classifieds/order/activate/$', 'populous.advertising.views.activate_form'), # (r'^classifieds/order/preform/$', 'django.views.generic.simple.direct_to_template', {'template': 'advertising/classifieds/order_preform'}), # (r'^classifieds/subcategories/?$', 'populous.advertising.views.classifieds_subcategory_list'), # (r'^classifieds/subcategories/(?P<slug>[\w-]+)/?$', 'populous.advertising.views.classifieds_subcategory_detail'), # (r'^classifieds/(?P<slug>[\w-]+)/?$', 'populous.advertising.views.classifieds_detail'), # (r'^classifieds/(?P<slug>[\w-]+)/map/?$', 'populous.advertising.views.classifieds_map'), # (r'^coupons/businesses/(?P<slug>[\w-]+)/?$', 'populous.advertising.views.coupons_business'), # (r'^coupons/businesses/(?P<slug>[\w-]+)/map/?$', 'populous.advertising.views.coupons_map'), # (r'^coupons/?$', 'populous.advertising.views.coupons_list'), # (r'^coupons/(?P<slug>[\w-]+)/?$', 'populous.advertising.views.coupons_detail'), # (r'^coupons/(?P<slug>[\w-]+)/map/?$', 'populous.advertising.views.coupons_map'), # (r'^coupons/(?P<slug>[\w-]+)/print/?$', 'populous.advertising.views.coupons_print'), # (r'^graphicads/?$', 'populous.advertising.views.graphicads_list'), # (r'^graphicads/(?P<slug>[\w-]+)/?$', 'populous.advertising.views.graphicads_detail'), # (r'^textads/?$', 'populous.advertising.views.textads_list'), # (r'^textads/(?P<slug>[\w-]+)/?$', 'populous.advertising.views.textads_detail'), # (r'^textads/(?P<slug>[\w-]+)/map/?$', 'populous.advertising.views.textads_map'), )

80.423077

144

0.678623

230

2,091

6.047826

0.173913

0.273185

0.345075

0.176132

0.562904

0.457944

0.363048

0.173976

0

0.068867

2,091

26

145

80.423077

0.714432

0.824008

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0

null

1

0

1

0

1

null

0

5

78053eb08569a40eed5acef650446a7b6574c433

9,235

py

Python

alaska2/models/hpf_net.py

simphide/Kaggle-2020-Alaska2

3c1f5e8e564c9f04423beef69244fc74168f88ca

[ "MIT" ]

21

2020-08-09T11:30:16.000Z

2021-06-28T14:15:08.000Z

alaska2/models/hpf_net.py

simphide/Kaggle-2020-Alaska2

3c1f5e8e564c9f04423beef69244fc74168f88ca

[ "MIT" ]

11

2020-08-09T15:30:54.000Z

2022-02-10T07:34:39.000Z

alaska2/models/hpf_net.py

simphide/Kaggle-2020-Alaska2

3c1f5e8e564c9f04423beef69244fc74168f88ca

[ "MIT" ]

3

2020-08-09T14:29:03.000Z

2021-05-27T13:07:12.000Z

import numpy as np import torch from pytorch_toolbelt.modules import Normalize, GlobalAvgPool2d from torch import nn from alaska2.dataset import INPUT_IMAGE_KEY, OUTPUT_PRED_MODIFICATION_FLAG, OUTPUT_PRED_MODIFICATION_TYPE from alaska2.models.modules import TLU, SqrtmLayer, CovpoolLayer, TriuvecLayer from alaska2.models.srm_filter_kernel import all_normalized_hpf_list __all__ = ["HPFNet", "hpf_net_v2", "hpf_net", "hpf_b3_fixed_covpool", "hpf_b3_fixed_gap", "hpf_b3_covpool"] class HPF(nn.Module): def __init__(self): super(HPF, self).__init__() # Load 30 SRM Filters all_hpf_list_5x5 = [] for hpf_item in all_normalized_hpf_list: if hpf_item.shape[0] == 3: hpf_item = np.pad(hpf_item, pad_width=((1, 1), (1, 1)), mode="constant") all_hpf_list_5x5.append(hpf_item) hpf_weight = nn.Parameter(torch.Tensor(all_hpf_list_5x5).view(30, 1, 5, 5), requires_grad=False) self.hpf = nn.Conv2d(1, 30, kernel_size=5, padding=2, bias=False) self.hpf.weight = hpf_weight # Truncation, threshold = 3 self.tlu = TLU(3.0) def forward(self, input): output = self.hpf(input) output = self.tlu(output) return output class HPF3(nn.Module): def __init__(self, trainable_hpf=False, stride=1): super(HPF3, self).__init__() # Load 30 SRM Filters all_hpf_list_5x5 = [] for hpf_item in all_normalized_hpf_list: if hpf_item.shape[0] == 3: hpf_item = np.pad(hpf_item, pad_width=((1, 1), (1, 1)), mode="constant") all_hpf_list_5x5.append(hpf_item) features = torch.Tensor(all_hpf_list_5x5).view(30, 1, 5, 5) features = torch.cat([features, features, features], dim=1) hpf_weight = nn.Parameter(features, requires_grad=trainable_hpf) self.hpf = nn.Conv2d(3, 30, kernel_size=5, padding=2, stride=stride, bias=False) self.hpf.weight = hpf_weight # Truncation, threshold = 3 self.tlu = TLU(3.0) def forward(self, input): output = self.hpf(input) output = self.tlu(output) return output class HPFNet(nn.Module): def __init__(self, num_classes, dropout=0, pretrained=False, trainable_hpf=False): super(HPFNet, self).__init__() max_pixel_value = 255 self.rgb_bn = Normalize( [0.3914976 * max_pixel_value, 0.44266784 * max_pixel_value, 0.46043398 * max_pixel_value], [0.17819773 * max_pixel_value, 0.17319807 * max_pixel_value, 0.18128773 * max_pixel_value], ) self.group1 = HPF3(trainable_hpf=trainable_hpf) self.group2 = nn.Sequential( nn.Conv2d(30, 32, kernel_size=3, padding=1), nn.BatchNorm2d(32), nn.ReLU(), nn.Conv2d(32, 32, kernel_size=3, padding=1), nn.BatchNorm2d(32), nn.ReLU(), nn.Conv2d(32, 32, kernel_size=3, padding=1), nn.BatchNorm2d(32), nn.ReLU(), nn.Conv2d(32, 32, kernel_size=3, padding=1), nn.BatchNorm2d(32), nn.ReLU(), nn.AvgPool2d(kernel_size=3, padding=1, stride=2), ) self.group3 = nn.Sequential( nn.Conv2d(32, 32, kernel_size=3, padding=1), nn.BatchNorm2d(32), nn.ReLU(), nn.Conv2d(32, 64, kernel_size=3, padding=1), nn.BatchNorm2d(64), nn.ReLU(), nn.AvgPool2d(kernel_size=3, padding=1, stride=2), ) self.group4 = nn.Sequential( nn.Conv2d(64, 64, kernel_size=3, padding=1), nn.BatchNorm2d(64), nn.ReLU(), nn.Conv2d(64, 128, kernel_size=3, padding=1), nn.BatchNorm2d(128), nn.ReLU(), nn.AvgPool2d(kernel_size=3, padding=1, stride=2), ) self.group5 = nn.Sequential( nn.Conv2d(128, 128, kernel_size=3, padding=1), nn.BatchNorm2d(128), nn.ReLU(), nn.Conv2d(128, 256, kernel_size=3, padding=1), nn.BatchNorm2d(256), nn.ReLU(), ) self.fc1 = nn.Linear(int(256 * (256 + 1) / 2), 2) self.drop = nn.Dropout(dropout) features = int(256 * (256 + 1) / 2) self.type_classifier = nn.Linear(features, num_classes) self.flag_classifier = nn.Linear(features, 1) def forward(self, **kwargs): rgb = self.rgb_bn(kwargs[INPUT_IMAGE_KEY].float()) output = self.group1(rgb) output = self.group2(output) output = self.group3(output) output = self.group4(output) output = self.group5(output) # Global covariance pooling output = CovpoolLayer(output) output = SqrtmLayer(output, 5) output = TriuvecLayer(output) x = output.view(output.size(0), -1) return { OUTPUT_PRED_MODIFICATION_FLAG: self.flag_classifier(self.drop(x)), OUTPUT_PRED_MODIFICATION_TYPE: self.type_classifier(self.drop(x)), } @property def required_features(self): return [INPUT_IMAGE_KEY] class HPFNetCovPool(nn.Module): def __init__(self, encoder, num_classes, dropout=0, mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]): super().__init__() max_pixel_value = 255 self.rgb_bn = Normalize(np.array(mean) * max_pixel_value, np.array(std) * max_pixel_value) self.encoder = encoder self.drop = nn.Dropout(dropout) features = int(256 * (256 + 1) / 2) self.bottleneck = nn.Conv2d(encoder.num_features, 256, kernel_size=1) self.type_classifier = nn.Linear(features, num_classes) self.flag_classifier = nn.Linear(features, 1) def forward(self, **kwargs): x = self.rgb_bn(kwargs[INPUT_IMAGE_KEY]) x = self.encoder.forward_features(x) x = self.bottleneck(x) # Global covariance pooling output = CovpoolLayer(x) output = SqrtmLayer(output, 5) output = TriuvecLayer(output) x = output.view(output.size(0), -1) return { OUTPUT_PRED_MODIFICATION_TYPE: self.type_classifier(self.drop(x)), OUTPUT_PRED_MODIFICATION_FLAG: self.flag_classifier(self.drop(x)), } @property def required_features(self): return [INPUT_IMAGE_KEY] class HPFNetGAP(nn.Module): def __init__(self, encoder, num_classes, dropout=0, mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]): super().__init__() max_pixel_value = 255 self.rgb_bn = Normalize(np.array(mean) * max_pixel_value, np.array(std) * max_pixel_value) self.encoder = encoder self.drop = nn.Dropout(dropout) self.pool = GlobalAvgPool2d(flatten=True) self.type_classifier = nn.Linear(encoder.num_features, num_classes) self.flag_classifier = nn.Linear(encoder.num_features, 1) def forward(self, **kwargs): x = self.rgb_bn(kwargs[INPUT_IMAGE_KEY]) x = self.encoder.forward_features(x) x = self.pool(x) return { OUTPUT_PRED_MODIFICATION_TYPE: self.type_classifier(self.drop(x)), OUTPUT_PRED_MODIFICATION_FLAG: self.flag_classifier(self.drop(x)), } @property def required_features(self): return [INPUT_IMAGE_KEY] def hpf_net(num_classes, dropout=0, pretrained=False): return HPFNet(num_classes=num_classes, dropout=dropout, pretrained=pretrained) def hpf_b3_fixed_covpool(num_classes, dropout=0, pretrained=False): from timm.models import efficientnet encoder = efficientnet.tf_efficientnet_b3_ns(pretrained=True, drop_path_rate=0.1) encoder.conv_stem = nn.Sequential(HPF3(trainable_hpf=False, stride=2), nn.Conv2d(30, 40, kernel_size=1)) del encoder.classifier return HPFNetCovPool( encoder, num_classes=num_classes, dropout=dropout, mean=encoder.default_cfg["mean"], std=encoder.default_cfg["std"], ) def hpf_b3_covpool(num_classes, dropout=0, pretrained=False): from timm.models import efficientnet encoder = efficientnet.tf_efficientnet_b3_ns(pretrained=True, drop_path_rate=0.1) encoder.conv_stem = nn.Sequential(HPF3(trainable_hpf=True, stride=2), nn.Conv2d(30, 40, kernel_size=1)) del encoder.classifier return HPFNetCovPool( encoder, num_classes=num_classes, dropout=dropout, mean=encoder.default_cfg["mean"], std=encoder.default_cfg["std"], ) def hpf_b3_fixed_gap(num_classes, dropout=0, pretrained=False): from timm.models import efficientnet encoder = efficientnet.tf_efficientnet_b3_ns(pretrained=True, drop_path_rate=0.1) encoder.conv_stem = nn.Sequential(HPF3(trainable_hpf=False, stride=2), nn.Conv2d(30, 40, kernel_size=1)) del encoder.classifier return HPFNetGAP( encoder, num_classes=num_classes, dropout=dropout, mean=encoder.default_cfg["mean"], std=encoder.default_cfg["std"], ) def hpf_net_v2(num_classes, dropout=0, pretrained=False): return HPFNet(num_classes=num_classes, dropout=dropout, pretrained=pretrained, trainable_hpf=True)

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null

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780dde820e3f5d180e77698081bd07936c27a4ea

130

py

Python

engine/src/juliabox/plugins/parallel/__init__.py

shashi/JuliaBox

10f65b3ed1b5b2ca703a4ff2c79940cc10c66c61

[ "MIT" ]

50

2016-09-09T02:17:09.000Z

2022-03-15T17:16:20.000Z

engine/src/juliabox/plugins/parallel/__init__.py

wsshin/JuliaBox

395df7654834f9671ab132cd29c02fb05ce42c27

[ "MIT" ]

58

2016-08-29T19:19:28.000Z

2018-11-14T01:49:16.000Z

engine/src/juliabox/plugins/parallel/__init__.py

wsshin/JuliaBox

395df7654834f9671ab132cd29c02fb05ce42c27

[ "MIT" ]

24

2016-09-27T18:20:54.000Z

2022-01-02T09:37:44.000Z

__author__ = 'tan' from parallel_handler import ParallelHandler, ParallelUIModule from parallel_housekeep import ParallelHousekeep

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5

78222ea098cdb2faa83489e96534d7ffb7a593df

9,138

py

Python

dbas_export_mockup.py

hhucn/dabasco

847cf550b4f55baf21446564c908e992a69366f0

[ "MIT" ]

5

2017-08-02T16:55:10.000Z

2019-05-15T21:05:10.000Z

dbas_export_mockup.py

hhucn/dabasco

847cf550b4f55baf21446564c908e992a69366f0

[ "MIT" ]

null

dbas_export_mockup.py

hhucn/dabasco

847cf550b4f55baf21446564c908e992a69366f0

[ "MIT" ]

null

#!/usr/bin/env python3 from flask import Flask, jsonify from flask_cors import CORS app = Flask(__name__) CORS(app) # Set security headers for Web requests @app.route('/export/doj/<int:discussion>') def export_dummy_discussion(discussion): """ Return a json string with dbas export style data of an example discussion. :param discussion: discussion ID :return: json string """ nodes = [] inferences = [] undercuts = [] if discussion == 1: # Nixon Diamond example discussion nodes = [1, 2, 3] inferences = [{'id': 1, 'premises': [2], 'is_supportive': True, 'conclusion': 1}, {'id': 2, 'premises': [3], 'is_supportive': False, 'conclusion': 1}] elif discussion == 2: # Extended Nixon Diamond example discussion nodes = [1, 2, 3, 4, 5] inferences = [{'id': 1, 'premises': [2], 'is_supportive': True, 'conclusion': 1}, {'id': 2, 'premises': [3], 'is_supportive': False, 'conclusion': 1}, {'id': 3, 'premises': [4], 'is_supportive': False, 'conclusion': 2}] undercuts = [{'id': 4, 'premises': [5], 'conclusion': 2}] elif discussion == 3: # Town policy debate example discussion with 7 statements nodes = [76, 77, 78, 79, 80, 81, 82] inferences = [{'id': 65, 'premises': [77], 'is_supportive': True, 'conclusion': 76}, {'id': 66, 'premises': [78], 'is_supportive': False, 'conclusion': 76}, {'id': 67, 'premises': [79], 'is_supportive': False, 'conclusion': 76}, {'id': 68, 'premises': [80, 81], 'is_supportive': False, 'conclusion': 79}] undercuts = [{'id': 69, 'premises': [82], 'conclusion': 65}] elif discussion == 4: # Simplified town policy debate example discussion (only rebut) nodes = [76, 77, 78] inferences = [{'id': 65, 'premises': [77], 'is_supportive': True, 'conclusion': 76}, {'id': 66, 'premises': [78], 'is_supportive': False, 'conclusion': 76}] elif discussion == 5: # Town policy debate example discussion with 6 statements nodes = [76, 77, 78, 79, 80, 81] inferences = [{'id': 65, 'premises': [77], 'is_supportive': True, 'conclusion': 76}, {'id': 66, 'premises': [78], 'is_supportive': False, 'conclusion': 76}, {'id': 67, 'premises': [79, 80], 'is_supportive': False, 'conclusion': 78}] undercuts = [{'id': 68, 'premises': [81], 'conclusion': 65}] elif discussion == 6: # Simplified town policy debate example discussion (only undercut) nodes = [76, 77, 82] inferences = [{'id': 65, 'premises': [77], 'is_supportive': True, 'conclusion': 76}] undercuts = [{'id': 69, 'premises': [82], 'conclusion': 65}] elif discussion == 7: # Simplified town policy debate example discussion (only undermine) nodes = [76, 79, 80] inferences = [{'id': 67, 'premises': [79], 'is_supportive': False, 'conclusion': 76}, {'id': 68, 'premises': [80], 'is_supportive': False, 'conclusion': 79}] return jsonify({'nodes': nodes, 'inferences': inferences, 'undercuts': undercuts}) @app.route('/export/doj_user/<int:user>/<int:discussion>') def export_dummy_useropinion(user, discussion): """ Return a json string with dbas export style data of an example discussion. :param user: user ID :param discussion: discussion ID :return: json string """ marked_statements = [] marked_arguments = [] rejected_arguments = [] accepted_statements_via_click = [] rejected_statements_via_click = [] if discussion == 1: # Nixon Diamond example discussion if user == 1: accepted_statements_via_click = [2] rejected_statements_via_click = [3] elif user == 2: accepted_statements_via_click = [2, 3] rejected_statements_via_click = [] elif user == 3: accepted_statements_via_click = [1, 3] rejected_statements_via_click = [] elif discussion == 2: # Extended Nixon Diamond example discussion if user == 1: accepted_statements_via_click = [3, 4] rejected_statements_via_click = [5] if discussion == 3: # Town policy debate example discussion if user == 1: accepted_statements_via_click = [76, 77, 80, 81] rejected_statements_via_click = [78, 79, 82] elif user == 2: accepted_statements_via_click = [77, 78, 80, 81, 82] rejected_statements_via_click = [76, 79] elif user == 3: accepted_statements_via_click = [77, 78, 80, 81, 82] rejected_statements_via_click = [] elif discussion == 4: # Simplified town policy debate example discussion (only rebut) if user == 1: accepted_statements_via_click = [76, 77] rejected_statements_via_click = [] elif user == 2: accepted_statements_via_click = [78] rejected_statements_via_click = [76] elif user == 3: accepted_statements_via_click = [77] rejected_statements_via_click = [78] elif user == 4: accepted_statements_via_click = [77, 78] rejected_statements_via_click = [] elif user == 5: accepted_statements_via_click = [76, 78] rejected_statements_via_click = [] if discussion == 5: # Town policy debate example discussion with 6 statements if user == 1: accepted_statements_via_click = [77] rejected_statements_via_click = [78] elif user == 2: accepted_statements_via_click = [78] rejected_statements_via_click = [77] elif user == 3: accepted_statements_via_click = [77, 78] rejected_statements_via_click = [] elif user == 4: accepted_statements_via_click = [77, 78, 79, 80, 81] rejected_statements_via_click = [] if discussion == 6: # Simplified town policy debate example discussion (only undercut) if user == 1: accepted_statements_via_click = [77] rejected_statements_via_click = [82] elif user == 2: accepted_statements_via_click = [82] rejected_statements_via_click = [77] elif user == 3: accepted_statements_via_click = [77, 82] rejected_statements_via_click = [] elif user == 4: accepted_statements_via_click = [] rejected_statements_via_click = [77, 82] if discussion == 7: # Simplified town policy debate example discussion (only undermine) if user == 1: accepted_statements_via_click = [79] rejected_statements_via_click = [80] elif user == 2: accepted_statements_via_click = [80] rejected_statements_via_click = [79] elif user == 3: accepted_statements_via_click = [79, 80] rejected_statements_via_click = [] elif user == 4: accepted_statements_via_click = [] rejected_statements_via_click = [79, 80] return jsonify({'marked_statements': marked_statements, 'marked_arguments': marked_arguments, 'rejected_arguments': rejected_arguments, 'accepted_statements_via_click': accepted_statements_via_click, 'rejected_statements_via_click': rejected_statements_via_click}) if __name__ == '__main__': app.run(threaded=True, port=4284)

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0

null

0

1

0

null

0

5

78565da6d625c61f6fe3867f98d424696bca30d8

183

py

Python

lil_url/helpers/redis_helper.py

omprakash1989/LilUrl

c230a8aaa985ea1d9d446634237a05002a3616c4

[ "MIT" ]

null

lil_url/helpers/redis_helper.py

omprakash1989/LilUrl

c230a8aaa985ea1d9d446634237a05002a3616c4

[ "MIT" ]

null

lil_url/helpers/redis_helper.py

omprakash1989/LilUrl

c230a8aaa985ea1d9d446634237a05002a3616c4

[ "MIT" ]

null

import redis # Get redis connection. def get_redis(host='localhost', port='6379'): return redis.StrictRedis(host=host, port=port, db=2, charset="utf-8", decode_responses=True)

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null

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1

0

1

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5

785c4d15bcba68a7629cd4680f994189a1293991

106

py

Python

vim.py

RJ722/Repo-with-spaces

7efd9dcb35a760d7fd02ef88f9bdde3b26a846bb

[ "MIT" ]

null

vim.py

RJ722/Repo-with-spaces

7efd9dcb35a760d7fd02ef88f9bdde3b26a846bb

[ "MIT" ]

null

vim.py

RJ722/Repo-with-spaces

7efd9dcb35a760d7fd02ef88f9bdde3b26a846bb

[ "MIT" ]

null

# Vim has the best keybindings ever class Vim: @property def __best__(self): return True

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null

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1

0

1

0

5

7875f4086bb8b7197a2b65d49fba7f41337c60d8

19,453

py

Python

tests/program_analysis/GCC2GrFN/test_gcc_plugin_c.py

ml4ai/automates

3bb996be27e9ee9f99e931b885707dae2c2ac567

[ "Apache-2.0" ]

17

2018-12-19T16:32:38.000Z

2021-10-05T07:58:15.000Z

tests/program_analysis/GCC2GrFN/test_gcc_plugin_c.py

ml4ai/automates

3bb996be27e9ee9f99e931b885707dae2c2ac567

[ "Apache-2.0" ]

183

2018-12-20T17:03:01.000Z

2022-02-23T22:21:42.000Z

tests/program_analysis/GCC2GrFN/test_gcc_plugin_c.py

ml4ai/automates

3bb996be27e9ee9f99e931b885707dae2c2ac567

[ "Apache-2.0" ]

5

2019-01-04T22:37:49.000Z

2022-01-19T17:34:16.000Z

import pytest import subprocess import os import random import json import numpy as np from sys import platform # import automates.model_assembly.networks as networks import automates.utils.misc as misc from automates.program_analysis.CAST2GrFN.cast import CAST from automates.model_assembly.networks import GroundedFunctionNetwork from automates.program_analysis.GCC2GrFN.gcc_ast_to_cast import GCC2CAST GCC_10_BIN_DIRECTORY = "/usr/local/gcc-10.1.0/bin/" GCC_PLUGIN_IMAGE = "automates/program_analysis/gcc_plugin/plugin/ast_dump.so" GCC_TEST_DATA_DIRECTORY = "tests/data/program_analysis/GCC2GrFN" def cleanup(): for item in os.listdir("./"): if item.endswith(".o") or item.endswith("gcc_ast.json"): os.remove("./" + item) @pytest.fixture(scope="module", autouse=True) def run_before_tests(request): # Change to the plugin dir and remove the current plugin image cur_dir = os.getcwd() os.chdir("automates/program_analysis/gcc_plugin/plugin/") if os.path.exists("./ast_dump.so"): os.remove("./ast_dump.so") if platform == "linux" or platform == "linux2": # linux, run "make linux" subprocess.run(["make", "linux"], stdout=subprocess.DEVNULL) elif platform == "darwin": # OS X, run "make" subprocess.run(["make"], stdout=subprocess.DEVNULL) elif platform == "win32": raise Exception("Error: Unable to run tests on windows.") # Return to working dir os.chdir(cur_dir) assert os.path.exists( "automates/program_analysis/gcc_plugin/plugin/ast_dump.so" ), f"Error: GCC AST dump plugin does not exist at expected location: {GCC_PLUGIN_IMAGE}" @pytest.fixture(autouse=True) def run_around_tests(): # Before each test, set the seed for generating uuids to 0 for consistency # between tests and expected output misc.rd = random.Random() misc.rd.seed(0) # Run the test function yield # clean up generated files cleanup() def run_gcc_plugin_with_c_file(c_file): gpp_command = os.getenv("CUSTOM_GCC_10_PATH") if gpp_command is None: gpp_command = GCC_10_BIN_DIRECTORY + "g++-10.1" plugin_option = f"-fplugin={GCC_PLUGIN_IMAGE}" # Runs g++ with the given c file. This should create the file ast.json # with the programs ast inside of it. results = subprocess.run( [ gpp_command, plugin_option, "-c", "-x", "c++", c_file, # "-o", # "/dev/null", ], stdout=subprocess.DEVNULL, ) # Assert return code is 0 which is success assert results.returncode == 0 def evaluate_execution_results(expected_result, result): for k, v in expected_result.items(): assert k in result try: assert v == result[k] except AssertionError: raise AssertionError(f"Error in result for key {k}: {v} != {result[k]}") def test_c_simple_function_and_assignments(): run_gcc_plugin_with_c_file( f"{GCC_TEST_DATA_DIRECTORY}/simple_function_and_assignments/simple_function_and_assignments.c" ) gcc_ast_obj = json.load(open("./simple_function_and_assignments_gcc_ast.json")) cast = GCC2CAST([gcc_ast_obj]).to_cast() # # json.dump(cast.to_json_object(), open(f"{test_dir}/{test_name}--CAST.json", "w")) assert os.path.exists("./simple_function_and_assignments_gcc_ast.json") def test_all_binary_ops(): test_name = "all_binary_ops" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json, cast_source_language="c") cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = { "add": np.array([3]), "bitwise_and": np.array([0]), "bitwise_l_shift": np.array([2]), "bitwise_or": np.array([3]), "bitwise_r_shift": np.array([1]), "bitwise_xor": np.array([3]), "div": np.array([0.5]), "eq": np.array([False]), "gt": np.array([False]), "gte": np.array([False]), "lt": np.array([True]), "lte": np.array([True]), "mult": np.array([6]), "neq": np.array([True]), "remainder": np.array([2]), "sub": np.array([-1]), } evaluate_execution_results(expected_result, result) def test_all_unary_ops(): test_name = "all_unary_ops" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = { "bitwise_not": np.array([-2]), "logical_not": np.array([False]), "unary_plus": np.array([-1]), } evaluate_execution_results(expected_result, result) def test_function_call(): test_name = "function_call" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = { "x": np.array([25]), } evaluate_execution_results(expected_result, result) def test_function_call_one_variable_for_multiple_args(): test_name = "function_call_one_variable_for_multiple_args" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = { "x": np.array([25]), } evaluate_execution_results(expected_result, result) @pytest.mark.skip(reason="Need to fix trimming hanging lambdas in cast_to_air_model") def test_function_call_no_args(): test_name = "function_call_no_args" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn # TODO cannot currently execute GrFN with no starting node in root container # (This should be fixed when master is merged in?) no_starting_nodes_in_root # inputs = {} # result = grfn(inputs) # assert result == { # "x": np.array([25]), # } def test_function_call_with_literal_return(): test_name = "function_call_with_literal_return" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = { "x": np.array([5]), } evaluate_execution_results(expected_result, result) def test_function_same_func_multiple_times(): test_name = "function_same_func_multiple_times" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = { "five_squared": np.array([25]), "two_hundred": np.array([200]), "fifty": np.array([50]), } evaluate_execution_results(expected_result, result) def test_function_call_literal_args(): test_name = "function_call_literal_args" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = { "five_squared": np.array([25]), "two_hundred": np.array([200]), "fifty": np.array([50]), } evaluate_execution_results(expected_result, result) def test_function_call_expression_args(): test_name = "function_call_expression_args" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = { "r1": np.array([7000]), "r2": np.array([50]), "r3": np.array([250]), "r4": np.array([125]), } evaluate_execution_results(expected_result, result) @pytest.mark.skip(reason="Developing still") def test_function_call_with_mixed_args(): pass def test_function_call_with_complex_return(): test_name = "function_call_with_complex_return" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = {"nine": np.array([9])} evaluate_execution_results(expected_result, result) @pytest.mark.skip(reason="Need to develop a way to trim out the function") def test_function_no_args_void_return(): pass def test_function_call_nested(): test_name = "function_call_nested" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = {"onesixtyeight": np.array([168])} evaluate_execution_results(expected_result, result) @pytest.mark.skip(reason="GrFN may be incorrect") def test_if_statement(): test_name = "if_statement" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = {"x": np.array([10]), "a": np.array([3]), "b": np.array([5])} evaluate_execution_results(expected_result, result) @pytest.mark.skip(reason="GrFN may be incorrect") def test_if_else_statement(): test_name = "if_else_statement" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = {"x": np.array([5]), "a": np.array([10]), "b": np.array([5])} evaluate_execution_results(expected_result, result) @pytest.mark.skip(reason="CAST is incorrect (and so is GrFN)") def test_if_elif_statement(): test_name = "if_elif_statement" test_dir = f"{GCC_TEST_DATA_DIRECTORY}/{test_name}" run_gcc_plugin_with_c_file(f"{test_dir}/{test_name}.c") assert os.path.exists(f"./{test_name}_gcc_ast.json") gcc_ast_obj = json.load(open(f"./{test_name}_gcc_ast.json")) expected_cast_json = json.load(open(f"{test_dir}/{test_name}--CAST.json")) expected_cast = CAST.from_json_data(expected_cast_json) cast = GCC2CAST([gcc_ast_obj]).to_cast() assert expected_cast == cast expected_grfn = GroundedFunctionNetwork.from_json( f"{test_dir}/{test_name}--GrFN.json" ) grfn = cast.to_GrFN() assert expected_grfn == grfn inputs = {} result = grfn(inputs) expected_result = {"x": np.array([5]), "a": np.array([10]), "b": np.array([7])} evaluate_execution_results(expected_result, result) @pytest.mark.skip(reason="Developing still") def test_if_elif_else_statement(): pass @pytest.mark.skip(reason="Developing still") def test_nested_if_statements(): pass @pytest.mark.skip(reason="Developing still") def test_for_loop(): pass @pytest.mark.skip(reason="Developing still") def test_while_loop(): pass @pytest.mark.skip(reason="Developing still") def test_nested_loops(): pass @pytest.mark.skip(reason="Developing still") def test_nested_conditionals(): pass @pytest.mark.skip(reason="Developing still") def test_nested_function_calls_and_conditionals(): pass @pytest.mark.skip(reason="Developing still") def test_global_variable_passing(): pass @pytest.mark.skip(reason="Developing still") def test_pack_and_extract(): pass @pytest.mark.skip(reason="Developing still") def test_only_pack(): pass @pytest.mark.skip(reason="Developing still") def test_only_extract(): pass @pytest.mark.skip(reason="Developing still") def test_multiple_levels_extract_and_pack(): pass @pytest.mark.skip(reason="Developing still") def test_multiple_variables_extract_and_pack(): pass @pytest.mark.skip(reason="Developing still") def test_function_no_args_void_return_obj_update(): pass @pytest.mark.skip(reason="Developing still") def test_nested_types(): pass @pytest.mark.skip(reason="Developing still") def test_no_root_container(): pass @pytest.mark.skip(reason="Developing still") def test_array_usage(): pass @pytest.mark.skip(reason="Developing still") def test_array_iterating_length(): pass @pytest.mark.skip(reason="Developing still") def test_array_updated_in_lower_scopes(): pass @pytest.mark.skip(reason="Developing still") def test_multi_file(): pass @pytest.mark.skip(reason="Developing still") def test_source_refs(): pass ##### Model tests ###### @pytest.mark.skip(reason="Developing still") def test_pid_controller(): pass # TODO move to fortran tests # @pytest.mark.skip(reason="Developing still") # def test_stemp_soilt_for(): # pass # @pytest.mark.skip(reason="Developing still") # def test_stemp_epic_soilt_for(): # pass @pytest.mark.skip(reason="Developing still") def test_GE_simple_PI_controller(): pass @pytest.mark.skip(reason="Developing still") def test_simple_controller_bhpm(): pass

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Python

Tests/IndicesTest.py

Xen0byte/ironpython3

2e5bb6025d01ab52ea4bfbaf6fd7e0fec8ec0194

[ "Apache-2.0" ]

null

Tests/IndicesTest.py

Xen0byte/ironpython3

2e5bb6025d01ab52ea4bfbaf6fd7e0fec8ec0194

[ "Apache-2.0" ]

null

Tests/IndicesTest.py

Xen0byte/ironpython3

2e5bb6025d01ab52ea4bfbaf6fd7e0fec8ec0194

[ "Apache-2.0" ]

null

# Licensed to the .NET Foundation under one or more agreements. # The .NET Foundation licenses this file to you under the Apache 2.0 License. # See the LICENSE file in the project root for more information. # generated by generate_indicestest.py def test_indices(self): def t(i, j, k, l, r): rr = slice(i, j, k).indices(l) self.assertEqual(rr, r, "slice({i}, {j}, {k}).indices({l}) != {r}: {rr}".format(i=i, j=j, k=k, l=l, r=r, rr=rr)) t(None, None, None, 0, (0, 0, 1)) t(None, None, None, 1, (0, 1, 1)) t(None, None, None, 5, (0, 5, 1)) t(None, None, None, 10, (0, 10, 1)) t(None, None, None, 100, (0, 100, 1)) t(None, None, None, 2147483647, (0, 2147483647, 1)) t(None, None, None, 9223372036854775808, (0, 9223372036854775808, 1)) t(None, None, -5, 0, (-1, -1, -5)) t(None, None, -5, 1, (0, -1, -5)) t(None, None, -5, 5, (4, -1, -5)) t(None, None, -5, 10, (9, -1, -5)) t(None, None, -5, 100, (99, -1, -5)) t(None, None, -5, 2147483647, (2147483646, -1, -5)) t(None, None, -5, 9223372036854775808, (9223372036854775807, -1, -5)) t(None, None, -3, 0, (-1, -1, -3)) t(None, None, -3, 1, (0, -1, -3)) t(None, None, -3, 5, (4, -1, -3)) t(None, None, -3, 10, (9, -1, -3)) t(None, None, -3, 100, (99, -1, -3)) t(None, None, -3, 2147483647, (2147483646, -1, -3)) t(None, None, -3, 9223372036854775808, (9223372036854775807, -1, -3)) t(None, None, -1, 0, (-1, -1, -1)) t(None, None, -1, 1, (0, -1, -1)) t(None, None, -1, 5, (4, -1, -1)) t(None, None, -1, 10, (9, -1, -1)) t(None, None, -1, 100, (99, -1, -1)) t(None, None, -1, 2147483647, (2147483646, -1, -1)) t(None, None, -1, 9223372036854775808, (9223372036854775807, -1, -1)) t(None, None, 1, 0, (0, 0, 1)) t(None, None, 1, 1, (0, 1, 1)) t(None, None, 1, 5, (0, 5, 1)) t(None, None, 1, 10, (0, 10, 1)) t(None, None, 1, 100, (0, 100, 1)) t(None, None, 1, 2147483647, (0, 2147483647, 1)) t(None, None, 1, 9223372036854775808, (0, 9223372036854775808, 1)) t(None, None, 5, 0, (0, 0, 5)) t(None, None, 5, 1, (0, 1, 5)) t(None, None, 5, 5, (0, 5, 5)) t(None, None, 5, 10, (0, 10, 5)) t(None, None, 5, 100, (0, 100, 5)) t(None, None, 5, 2147483647, (0, 2147483647, 5)) t(None, None, 5, 9223372036854775808, (0, 9223372036854775808, 5)) t(None, None, 20, 0, (0, 0, 20)) t(None, None, 20, 1, (0, 1, 20)) t(None, None, 20, 5, (0, 5, 20)) t(None, None, 20, 10, (0, 10, 20)) t(None, None, 20, 100, (0, 100, 20)) t(None, None, 20, 2147483647, (0, 2147483647, 20)) t(None, None, 20, 9223372036854775808, (0, 9223372036854775808, 20)) t(None, None, 2147483647, 0, (0, 0, 2147483647)) t(None, None, 2147483647, 1, (0, 1, 2147483647)) t(None, None, 2147483647, 5, (0, 5, 2147483647)) t(None, None, 2147483647, 10, (0, 10, 2147483647)) t(None, None, 2147483647, 100, (0, 100, 2147483647)) t(None, None, 2147483647, 2147483647, (0, 2147483647, 2147483647)) t(None, None, 2147483647, 9223372036854775808, (0, 9223372036854775808, 2147483647)) t(None, None, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(None, None, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(None, None, 9223372036854775808, 5, (0, 5, 9223372036854775808)) t(None, None, 9223372036854775808, 10, (0, 10, 9223372036854775808)) t(None, None, 9223372036854775808, 100, (0, 100, 9223372036854775808)) t(None, None, 9223372036854775808, 2147483647, (0, 2147483647, 9223372036854775808)) t(None, None, 9223372036854775808, 9223372036854775808, (0, 9223372036854775808, 9223372036854775808)) t(None, -7, None, 0, (0, 0, 1)) t(None, -7, None, 1, (0, 0, 1)) t(None, -7, None, 5, (0, 0, 1)) t(None, -7, None, 10, (0, 3, 1)) t(None, -7, None, 100, (0, 93, 1)) t(None, -7, None, 2147483647, (0, 2147483640, 1)) t(None, -7, None, 9223372036854775808, (0, 9223372036854775801, 1)) t(None, -7, -5, 0, (-1, -1, -5)) t(None, -7, -5, 1, (0, -1, -5)) t(None, -7, -5, 5, (4, -1, -5)) t(None, -7, -5, 10, (9, 3, -5)) t(None, -7, -5, 100, (99, 93, -5)) t(None, -7, -5, 2147483647, (2147483646, 2147483640, -5)) t(None, -7, -5, 9223372036854775808, (9223372036854775807, 9223372036854775801, 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-1)) t(-7, None, -1, 10, (3, -1, -1)) t(-7, None, -1, 100, (93, -1, -1)) t(-7, None, -1, 2147483647, (2147483640, -1, -1)) t(-7, None, -1, 9223372036854775808, (9223372036854775801, -1, -1)) t(-7, None, 1, 0, (0, 0, 1)) t(-7, None, 1, 1, (0, 1, 1)) t(-7, None, 1, 5, (0, 5, 1)) t(-7, None, 1, 10, (3, 10, 1)) t(-7, None, 1, 100, (93, 100, 1)) t(-7, None, 1, 2147483647, (2147483640, 2147483647, 1)) t(-7, None, 1, 9223372036854775808, (9223372036854775801, 9223372036854775808, 1)) t(-7, None, 5, 0, (0, 0, 5)) t(-7, None, 5, 1, (0, 1, 5)) t(-7, None, 5, 5, (0, 5, 5)) t(-7, None, 5, 10, (3, 10, 5)) t(-7, None, 5, 100, (93, 100, 5)) t(-7, None, 5, 2147483647, (2147483640, 2147483647, 5)) t(-7, None, 5, 9223372036854775808, (9223372036854775801, 9223372036854775808, 5)) t(-7, None, 20, 0, (0, 0, 20)) t(-7, None, 20, 1, (0, 1, 20)) t(-7, None, 20, 5, (0, 5, 20)) t(-7, None, 20, 10, (3, 10, 20)) t(-7, None, 20, 100, (93, 100, 20)) t(-7, None, 20, 2147483647, (2147483640, 2147483647, 20)) t(-7, None, 20, 9223372036854775808, (9223372036854775801, 9223372036854775808, 20)) t(-7, None, 2147483647, 0, (0, 0, 2147483647)) t(-7, None, 2147483647, 1, (0, 1, 2147483647)) t(-7, None, 2147483647, 5, (0, 5, 2147483647)) t(-7, None, 2147483647, 10, (3, 10, 2147483647)) t(-7, None, 2147483647, 100, (93, 100, 2147483647)) t(-7, None, 2147483647, 2147483647, (2147483640, 2147483647, 2147483647)) t(-7, None, 2147483647, 9223372036854775808, (9223372036854775801, 9223372036854775808, 2147483647)) t(-7, None, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-7, None, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-7, None, 9223372036854775808, 5, (0, 5, 9223372036854775808)) t(-7, None, 9223372036854775808, 10, (3, 10, 9223372036854775808)) t(-7, None, 9223372036854775808, 100, (93, 100, 9223372036854775808)) t(-7, None, 9223372036854775808, 2147483647, (2147483640, 2147483647, 9223372036854775808)) t(-7, None, 9223372036854775808, 9223372036854775808, (9223372036854775801, 9223372036854775808, 9223372036854775808)) t(-7, -7, None, 0, (0, 0, 1)) t(-7, -7, None, 1, (0, 0, 1)) t(-7, -7, None, 5, (0, 0, 1)) t(-7, -7, None, 10, (3, 3, 1)) t(-7, -7, None, 100, (93, 93, 1)) t(-7, -7, None, 2147483647, (2147483640, 2147483640, 1)) t(-7, -7, None, 9223372036854775808, (9223372036854775801, 9223372036854775801, 1)) t(-7, -7, -5, 0, (-1, -1, -5)) t(-7, -7, -5, 1, (-1, -1, -5)) t(-7, -7, -5, 5, (-1, -1, -5)) t(-7, -7, -5, 10, (3, 3, -5)) t(-7, -7, -5, 100, (93, 93, -5)) t(-7, -7, -5, 2147483647, (2147483640, 2147483640, -5)) t(-7, -7, -5, 9223372036854775808, (9223372036854775801, 9223372036854775801, -5)) t(-7, -7, -3, 0, (-1, -1, -3)) t(-7, -7, -3, 1, (-1, -1, -3)) t(-7, -7, -3, 5, (-1, -1, -3)) t(-7, -7, -3, 10, (3, 3, -3)) t(-7, -7, -3, 100, (93, 93, -3)) t(-7, -7, -3, 2147483647, (2147483640, 2147483640, -3)) t(-7, -7, -3, 9223372036854775808, (9223372036854775801, 9223372036854775801, -3)) t(-7, -7, -1, 0, (-1, -1, -1)) t(-7, -7, -1, 1, (-1, -1, -1)) t(-7, -7, -1, 5, (-1, -1, -1)) t(-7, -7, -1, 10, (3, 3, -1)) t(-7, -7, -1, 100, (93, 93, -1)) t(-7, -7, -1, 2147483647, (2147483640, 2147483640, -1)) t(-7, -7, -1, 9223372036854775808, (9223372036854775801, 9223372036854775801, -1)) t(-7, -7, 1, 0, (0, 0, 1)) t(-7, -7, 1, 1, (0, 0, 1)) t(-7, -7, 1, 5, (0, 0, 1)) t(-7, -7, 1, 10, (3, 3, 1)) t(-7, -7, 1, 100, (93, 93, 1)) t(-7, -7, 1, 2147483647, (2147483640, 2147483640, 1)) t(-7, -7, 1, 9223372036854775808, (9223372036854775801, 9223372036854775801, 1)) t(-7, -7, 5, 0, (0, 0, 5)) t(-7, -7, 5, 1, (0, 0, 5)) t(-7, -7, 5, 5, (0, 0, 5)) t(-7, -7, 5, 10, (3, 3, 5)) t(-7, -7, 5, 100, (93, 93, 5)) t(-7, -7, 5, 2147483647, (2147483640, 2147483640, 5)) t(-7, -7, 5, 9223372036854775808, (9223372036854775801, 9223372036854775801, 5)) t(-7, -7, 20, 0, (0, 0, 20)) t(-7, -7, 20, 1, (0, 0, 20)) t(-7, -7, 20, 5, (0, 0, 20)) t(-7, -7, 20, 10, (3, 3, 20)) t(-7, -7, 20, 100, (93, 93, 20)) t(-7, -7, 20, 2147483647, (2147483640, 2147483640, 20)) t(-7, -7, 20, 9223372036854775808, (9223372036854775801, 9223372036854775801, 20)) t(-7, -7, 2147483647, 0, (0, 0, 2147483647)) t(-7, -7, 2147483647, 1, (0, 0, 2147483647)) t(-7, -7, 2147483647, 5, (0, 0, 2147483647)) t(-7, -7, 2147483647, 10, (3, 3, 2147483647)) t(-7, -7, 2147483647, 100, (93, 93, 2147483647)) t(-7, -7, 2147483647, 2147483647, (2147483640, 2147483640, 2147483647)) t(-7, -7, 2147483647, 9223372036854775808, (9223372036854775801, 9223372036854775801, 2147483647)) t(-7, -7, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-7, -7, 9223372036854775808, 1, (0, 0, 9223372036854775808)) t(-7, -7, 9223372036854775808, 5, (0, 0, 9223372036854775808)) t(-7, -7, 9223372036854775808, 10, (3, 3, 9223372036854775808)) t(-7, -7, 9223372036854775808, 100, (93, 93, 9223372036854775808)) t(-7, -7, 9223372036854775808, 2147483647, (2147483640, 2147483640, 9223372036854775808)) t(-7, -7, 9223372036854775808, 9223372036854775808, (9223372036854775801, 9223372036854775801, 9223372036854775808)) t(-7, -2, None, 0, (0, 0, 1)) t(-7, -2, None, 1, (0, 0, 1)) t(-7, -2, None, 5, (0, 3, 1)) t(-7, -2, None, 10, (3, 8, 1)) t(-7, -2, None, 100, (93, 98, 1)) t(-7, -2, None, 2147483647, (2147483640, 2147483645, 1)) t(-7, -2, None, 9223372036854775808, (9223372036854775801, 9223372036854775806, 1)) t(-7, -2, -5, 0, (-1, -1, -5)) t(-7, -2, -5, 1, (-1, -1, -5)) t(-7, -2, -5, 5, (-1, 3, -5)) t(-7, -2, -5, 10, (3, 8, -5)) t(-7, -2, -5, 100, (93, 98, -5)) t(-7, -2, -5, 2147483647, (2147483640, 2147483645, -5)) t(-7, -2, -5, 9223372036854775808, (9223372036854775801, 9223372036854775806, -5)) t(-7, -2, -3, 0, (-1, -1, -3)) t(-7, -2, -3, 1, (-1, -1, -3)) t(-7, -2, -3, 5, (-1, 3, -3)) t(-7, -2, -3, 10, (3, 8, -3)) t(-7, -2, -3, 100, (93, 98, -3)) t(-7, -2, -3, 2147483647, (2147483640, 2147483645, -3)) t(-7, -2, -3, 9223372036854775808, (9223372036854775801, 9223372036854775806, -3)) t(-7, -2, -1, 0, (-1, -1, -1)) t(-7, -2, -1, 1, (-1, -1, -1)) t(-7, -2, -1, 5, (-1, 3, -1)) t(-7, -2, -1, 10, (3, 8, -1)) t(-7, -2, -1, 100, (93, 98, -1)) t(-7, -2, -1, 2147483647, (2147483640, 2147483645, -1)) t(-7, -2, -1, 9223372036854775808, (9223372036854775801, 9223372036854775806, -1)) t(-7, -2, 1, 0, (0, 0, 1)) t(-7, -2, 1, 1, (0, 0, 1)) t(-7, -2, 1, 5, (0, 3, 1)) t(-7, -2, 1, 10, (3, 8, 1)) t(-7, -2, 1, 100, (93, 98, 1)) t(-7, -2, 1, 2147483647, (2147483640, 2147483645, 1)) t(-7, -2, 1, 9223372036854775808, (9223372036854775801, 9223372036854775806, 1)) t(-7, -2, 5, 0, (0, 0, 5)) t(-7, -2, 5, 1, (0, 0, 5)) t(-7, -2, 5, 5, (0, 3, 5)) t(-7, -2, 5, 10, (3, 8, 5)) t(-7, -2, 5, 100, (93, 98, 5)) t(-7, -2, 5, 2147483647, (2147483640, 2147483645, 5)) t(-7, -2, 5, 9223372036854775808, (9223372036854775801, 9223372036854775806, 5)) t(-7, -2, 20, 0, (0, 0, 20)) t(-7, -2, 20, 1, (0, 0, 20)) t(-7, -2, 20, 5, (0, 3, 20)) t(-7, -2, 20, 10, (3, 8, 20)) t(-7, -2, 20, 100, (93, 98, 20)) t(-7, -2, 20, 2147483647, (2147483640, 2147483645, 20)) t(-7, -2, 20, 9223372036854775808, (9223372036854775801, 9223372036854775806, 20)) t(-7, -2, 2147483647, 0, (0, 0, 2147483647)) t(-7, -2, 2147483647, 1, (0, 0, 2147483647)) t(-7, -2, 2147483647, 5, (0, 3, 2147483647)) t(-7, -2, 2147483647, 10, (3, 8, 2147483647)) t(-7, -2, 2147483647, 100, (93, 98, 2147483647)) t(-7, -2, 2147483647, 2147483647, (2147483640, 2147483645, 2147483647)) t(-7, -2, 2147483647, 9223372036854775808, (9223372036854775801, 9223372036854775806, 2147483647)) t(-7, -2, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-7, -2, 9223372036854775808, 1, (0, 0, 9223372036854775808)) t(-7, -2, 9223372036854775808, 5, (0, 3, 9223372036854775808)) t(-7, -2, 9223372036854775808, 10, (3, 8, 9223372036854775808)) t(-7, -2, 9223372036854775808, 100, (93, 98, 9223372036854775808)) t(-7, -2, 9223372036854775808, 2147483647, (2147483640, 2147483645, 9223372036854775808)) t(-7, -2, 9223372036854775808, 9223372036854775808, (9223372036854775801, 9223372036854775806, 9223372036854775808)) t(-7, 0, None, 0, (0, 0, 1)) t(-7, 0, None, 1, (0, 0, 1)) t(-7, 0, None, 5, (0, 0, 1)) t(-7, 0, None, 10, (3, 0, 1)) t(-7, 0, None, 100, (93, 0, 1)) t(-7, 0, None, 2147483647, (2147483640, 0, 1)) t(-7, 0, None, 9223372036854775808, (9223372036854775801, 0, 1)) t(-7, 0, -5, 0, (-1, -1, -5)) t(-7, 0, -5, 1, (-1, 0, -5)) t(-7, 0, -5, 5, (-1, 0, -5)) t(-7, 0, -5, 10, (3, 0, -5)) t(-7, 0, -5, 100, (93, 0, -5)) t(-7, 0, -5, 2147483647, (2147483640, 0, -5)) t(-7, 0, -5, 9223372036854775808, (9223372036854775801, 0, -5)) t(-7, 0, -3, 0, (-1, -1, -3)) t(-7, 0, -3, 1, (-1, 0, -3)) t(-7, 0, -3, 5, (-1, 0, -3)) t(-7, 0, -3, 10, (3, 0, -3)) t(-7, 0, -3, 100, (93, 0, -3)) t(-7, 0, -3, 2147483647, (2147483640, 0, -3)) t(-7, 0, -3, 9223372036854775808, (9223372036854775801, 0, -3)) t(-7, 0, -1, 0, (-1, -1, -1)) t(-7, 0, -1, 1, (-1, 0, -1)) t(-7, 0, -1, 5, (-1, 0, -1)) t(-7, 0, -1, 10, (3, 0, -1)) t(-7, 0, -1, 100, (93, 0, -1)) t(-7, 0, -1, 2147483647, (2147483640, 0, -1)) t(-7, 0, -1, 9223372036854775808, (9223372036854775801, 0, -1)) t(-7, 0, 1, 0, (0, 0, 1)) t(-7, 0, 1, 1, (0, 0, 1)) t(-7, 0, 1, 5, (0, 0, 1)) t(-7, 0, 1, 10, (3, 0, 1)) t(-7, 0, 1, 100, (93, 0, 1)) t(-7, 0, 1, 2147483647, (2147483640, 0, 1)) t(-7, 0, 1, 9223372036854775808, (9223372036854775801, 0, 1)) t(-7, 0, 5, 0, (0, 0, 5)) t(-7, 0, 5, 1, (0, 0, 5)) t(-7, 0, 5, 5, (0, 0, 5)) t(-7, 0, 5, 10, (3, 0, 5)) t(-7, 0, 5, 100, (93, 0, 5)) t(-7, 0, 5, 2147483647, (2147483640, 0, 5)) t(-7, 0, 5, 9223372036854775808, (9223372036854775801, 0, 5)) t(-7, 0, 20, 0, (0, 0, 20)) t(-7, 0, 20, 1, (0, 0, 20)) t(-7, 0, 20, 5, (0, 0, 20)) t(-7, 0, 20, 10, (3, 0, 20)) t(-7, 0, 20, 100, (93, 0, 20)) t(-7, 0, 20, 2147483647, (2147483640, 0, 20)) t(-7, 0, 20, 9223372036854775808, (9223372036854775801, 0, 20)) t(-7, 0, 2147483647, 0, (0, 0, 2147483647)) t(-7, 0, 2147483647, 1, (0, 0, 2147483647)) t(-7, 0, 2147483647, 5, (0, 0, 2147483647)) t(-7, 0, 2147483647, 10, (3, 0, 2147483647)) t(-7, 0, 2147483647, 100, (93, 0, 2147483647)) t(-7, 0, 2147483647, 2147483647, (2147483640, 0, 2147483647)) t(-7, 0, 2147483647, 9223372036854775808, (9223372036854775801, 0, 2147483647)) t(-7, 0, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-7, 0, 9223372036854775808, 1, (0, 0, 9223372036854775808)) t(-7, 0, 9223372036854775808, 5, (0, 0, 9223372036854775808)) t(-7, 0, 9223372036854775808, 10, (3, 0, 9223372036854775808)) t(-7, 0, 9223372036854775808, 100, (93, 0, 9223372036854775808)) t(-7, 0, 9223372036854775808, 2147483647, (2147483640, 0, 9223372036854775808)) t(-7, 0, 9223372036854775808, 9223372036854775808, (9223372036854775801, 0, 9223372036854775808)) t(-7, 1, None, 0, (0, 0, 1)) t(-7, 1, None, 1, (0, 1, 1)) t(-7, 1, None, 5, (0, 1, 1)) t(-7, 1, None, 10, (3, 1, 1)) t(-7, 1, None, 100, (93, 1, 1)) t(-7, 1, None, 2147483647, (2147483640, 1, 1)) t(-7, 1, None, 9223372036854775808, (9223372036854775801, 1, 1)) t(-7, 1, -5, 0, (-1, -1, -5)) t(-7, 1, -5, 1, (-1, 0, -5)) t(-7, 1, -5, 5, (-1, 1, -5)) t(-7, 1, -5, 10, (3, 1, -5)) t(-7, 1, -5, 100, (93, 1, -5)) t(-7, 1, -5, 2147483647, (2147483640, 1, -5)) t(-7, 1, -5, 9223372036854775808, (9223372036854775801, 1, -5)) t(-7, 1, -3, 0, (-1, -1, -3)) t(-7, 1, -3, 1, (-1, 0, -3)) t(-7, 1, -3, 5, (-1, 1, -3)) t(-7, 1, -3, 10, (3, 1, -3)) t(-7, 1, -3, 100, (93, 1, -3)) t(-7, 1, -3, 2147483647, (2147483640, 1, -3)) t(-7, 1, -3, 9223372036854775808, (9223372036854775801, 1, -3)) t(-7, 1, -1, 0, (-1, -1, -1)) t(-7, 1, -1, 1, (-1, 0, -1)) t(-7, 1, -1, 5, (-1, 1, -1)) t(-7, 1, -1, 10, (3, 1, -1)) t(-7, 1, -1, 100, (93, 1, -1)) t(-7, 1, -1, 2147483647, (2147483640, 1, -1)) t(-7, 1, -1, 9223372036854775808, (9223372036854775801, 1, -1)) t(-7, 1, 1, 0, (0, 0, 1)) t(-7, 1, 1, 1, (0, 1, 1)) t(-7, 1, 1, 5, (0, 1, 1)) t(-7, 1, 1, 10, (3, 1, 1)) t(-7, 1, 1, 100, (93, 1, 1)) t(-7, 1, 1, 2147483647, (2147483640, 1, 1)) t(-7, 1, 1, 9223372036854775808, (9223372036854775801, 1, 1)) t(-7, 1, 5, 0, (0, 0, 5)) t(-7, 1, 5, 1, (0, 1, 5)) t(-7, 1, 5, 5, (0, 1, 5)) t(-7, 1, 5, 10, (3, 1, 5)) t(-7, 1, 5, 100, (93, 1, 5)) t(-7, 1, 5, 2147483647, (2147483640, 1, 5)) t(-7, 1, 5, 9223372036854775808, (9223372036854775801, 1, 5)) t(-7, 1, 20, 0, (0, 0, 20)) t(-7, 1, 20, 1, (0, 1, 20)) t(-7, 1, 20, 5, (0, 1, 20)) t(-7, 1, 20, 10, (3, 1, 20)) t(-7, 1, 20, 100, (93, 1, 20)) t(-7, 1, 20, 2147483647, (2147483640, 1, 20)) t(-7, 1, 20, 9223372036854775808, (9223372036854775801, 1, 20)) t(-7, 1, 2147483647, 0, (0, 0, 2147483647)) t(-7, 1, 2147483647, 1, (0, 1, 2147483647)) t(-7, 1, 2147483647, 5, (0, 1, 2147483647)) t(-7, 1, 2147483647, 10, (3, 1, 2147483647)) t(-7, 1, 2147483647, 100, (93, 1, 2147483647)) t(-7, 1, 2147483647, 2147483647, (2147483640, 1, 2147483647)) t(-7, 1, 2147483647, 9223372036854775808, (9223372036854775801, 1, 2147483647)) t(-7, 1, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-7, 1, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-7, 1, 9223372036854775808, 5, (0, 1, 9223372036854775808)) t(-7, 1, 9223372036854775808, 10, (3, 1, 9223372036854775808)) t(-7, 1, 9223372036854775808, 100, (93, 1, 9223372036854775808)) t(-7, 1, 9223372036854775808, 2147483647, (2147483640, 1, 9223372036854775808)) t(-7, 1, 9223372036854775808, 9223372036854775808, (9223372036854775801, 1, 9223372036854775808)) t(-7, 6, None, 0, (0, 0, 1)) t(-7, 6, None, 1, (0, 1, 1)) t(-7, 6, None, 5, (0, 5, 1)) t(-7, 6, None, 10, (3, 6, 1)) t(-7, 6, None, 100, (93, 6, 1)) t(-7, 6, None, 2147483647, (2147483640, 6, 1)) t(-7, 6, None, 9223372036854775808, (9223372036854775801, 6, 1)) t(-7, 6, -5, 0, (-1, -1, -5)) t(-7, 6, -5, 1, (-1, 0, -5)) t(-7, 6, -5, 5, (-1, 4, -5)) t(-7, 6, -5, 10, (3, 6, -5)) t(-7, 6, -5, 100, (93, 6, -5)) t(-7, 6, -5, 2147483647, (2147483640, 6, -5)) t(-7, 6, -5, 9223372036854775808, (9223372036854775801, 6, -5)) t(-7, 6, -3, 0, (-1, -1, -3)) t(-7, 6, -3, 1, (-1, 0, -3)) t(-7, 6, -3, 5, (-1, 4, -3)) t(-7, 6, -3, 10, (3, 6, -3)) t(-7, 6, -3, 100, (93, 6, -3)) t(-7, 6, -3, 2147483647, (2147483640, 6, -3)) t(-7, 6, -3, 9223372036854775808, (9223372036854775801, 6, -3)) t(-7, 6, -1, 0, (-1, -1, -1)) t(-7, 6, -1, 1, (-1, 0, -1)) t(-7, 6, -1, 5, (-1, 4, -1)) t(-7, 6, -1, 10, (3, 6, -1)) t(-7, 6, -1, 100, (93, 6, -1)) t(-7, 6, -1, 2147483647, (2147483640, 6, -1)) t(-7, 6, -1, 9223372036854775808, (9223372036854775801, 6, -1)) t(-7, 6, 1, 0, (0, 0, 1)) t(-7, 6, 1, 1, (0, 1, 1)) t(-7, 6, 1, 5, (0, 5, 1)) t(-7, 6, 1, 10, (3, 6, 1)) t(-7, 6, 1, 100, (93, 6, 1)) t(-7, 6, 1, 2147483647, (2147483640, 6, 1)) t(-7, 6, 1, 9223372036854775808, (9223372036854775801, 6, 1)) t(-7, 6, 5, 0, (0, 0, 5)) t(-7, 6, 5, 1, (0, 1, 5)) t(-7, 6, 5, 5, (0, 5, 5)) t(-7, 6, 5, 10, (3, 6, 5)) t(-7, 6, 5, 100, (93, 6, 5)) t(-7, 6, 5, 2147483647, (2147483640, 6, 5)) t(-7, 6, 5, 9223372036854775808, (9223372036854775801, 6, 5)) t(-7, 6, 20, 0, (0, 0, 20)) t(-7, 6, 20, 1, (0, 1, 20)) t(-7, 6, 20, 5, (0, 5, 20)) t(-7, 6, 20, 10, (3, 6, 20)) t(-7, 6, 20, 100, (93, 6, 20)) t(-7, 6, 20, 2147483647, (2147483640, 6, 20)) t(-7, 6, 20, 9223372036854775808, (9223372036854775801, 6, 20)) t(-7, 6, 2147483647, 0, (0, 0, 2147483647)) t(-7, 6, 2147483647, 1, (0, 1, 2147483647)) t(-7, 6, 2147483647, 5, (0, 5, 2147483647)) t(-7, 6, 2147483647, 10, (3, 6, 2147483647)) t(-7, 6, 2147483647, 100, (93, 6, 2147483647)) t(-7, 6, 2147483647, 2147483647, (2147483640, 6, 2147483647)) t(-7, 6, 2147483647, 9223372036854775808, (9223372036854775801, 6, 2147483647)) t(-7, 6, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-7, 6, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-7, 6, 9223372036854775808, 5, (0, 5, 9223372036854775808)) t(-7, 6, 9223372036854775808, 10, (3, 6, 9223372036854775808)) t(-7, 6, 9223372036854775808, 100, (93, 6, 9223372036854775808)) t(-7, 6, 9223372036854775808, 2147483647, (2147483640, 6, 9223372036854775808)) t(-7, 6, 9223372036854775808, 9223372036854775808, (9223372036854775801, 6, 9223372036854775808)) t(-7, 10, None, 0, (0, 0, 1)) t(-7, 10, None, 1, (0, 1, 1)) t(-7, 10, None, 5, (0, 5, 1)) t(-7, 10, None, 10, (3, 10, 1)) t(-7, 10, None, 100, (93, 10, 1)) t(-7, 10, None, 2147483647, (2147483640, 10, 1)) t(-7, 10, None, 9223372036854775808, (9223372036854775801, 10, 1)) t(-7, 10, -5, 0, (-1, -1, -5)) t(-7, 10, -5, 1, (-1, 0, -5)) t(-7, 10, -5, 5, (-1, 4, -5)) t(-7, 10, -5, 10, (3, 9, -5)) t(-7, 10, -5, 100, (93, 10, -5)) t(-7, 10, -5, 2147483647, (2147483640, 10, -5)) t(-7, 10, -5, 9223372036854775808, (9223372036854775801, 10, -5)) t(-7, 10, -3, 0, (-1, -1, -3)) t(-7, 10, -3, 1, (-1, 0, -3)) t(-7, 10, -3, 5, (-1, 4, -3)) t(-7, 10, -3, 10, (3, 9, -3)) t(-7, 10, -3, 100, (93, 10, -3)) t(-7, 10, -3, 2147483647, (2147483640, 10, -3)) t(-7, 10, -3, 9223372036854775808, (9223372036854775801, 10, -3)) t(-7, 10, -1, 0, (-1, -1, -1)) t(-7, 10, -1, 1, (-1, 0, -1)) t(-7, 10, -1, 5, (-1, 4, -1)) t(-7, 10, -1, 10, (3, 9, -1)) t(-7, 10, -1, 100, (93, 10, -1)) t(-7, 10, -1, 2147483647, (2147483640, 10, -1)) t(-7, 10, -1, 9223372036854775808, (9223372036854775801, 10, -1)) t(-7, 10, 1, 0, (0, 0, 1)) t(-7, 10, 1, 1, (0, 1, 1)) t(-7, 10, 1, 5, (0, 5, 1)) t(-7, 10, 1, 10, (3, 10, 1)) t(-7, 10, 1, 100, (93, 10, 1)) t(-7, 10, 1, 2147483647, (2147483640, 10, 1)) t(-7, 10, 1, 9223372036854775808, (9223372036854775801, 10, 1)) t(-7, 10, 5, 0, (0, 0, 5)) t(-7, 10, 5, 1, (0, 1, 5)) t(-7, 10, 5, 5, (0, 5, 5)) t(-7, 10, 5, 10, (3, 10, 5)) t(-7, 10, 5, 100, (93, 10, 5)) t(-7, 10, 5, 2147483647, (2147483640, 10, 5)) t(-7, 10, 5, 9223372036854775808, (9223372036854775801, 10, 5)) t(-7, 10, 20, 0, (0, 0, 20)) t(-7, 10, 20, 1, (0, 1, 20)) t(-7, 10, 20, 5, (0, 5, 20)) t(-7, 10, 20, 10, (3, 10, 20)) t(-7, 10, 20, 100, (93, 10, 20)) t(-7, 10, 20, 2147483647, (2147483640, 10, 20)) t(-7, 10, 20, 9223372036854775808, (9223372036854775801, 10, 20)) t(-7, 10, 2147483647, 0, (0, 0, 2147483647)) t(-7, 10, 2147483647, 1, (0, 1, 2147483647)) t(-7, 10, 2147483647, 5, (0, 5, 2147483647)) t(-7, 10, 2147483647, 10, (3, 10, 2147483647)) t(-7, 10, 2147483647, 100, (93, 10, 2147483647)) t(-7, 10, 2147483647, 2147483647, (2147483640, 10, 2147483647)) t(-7, 10, 2147483647, 9223372036854775808, (9223372036854775801, 10, 2147483647)) t(-7, 10, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-7, 10, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-7, 10, 9223372036854775808, 5, (0, 5, 9223372036854775808)) t(-7, 10, 9223372036854775808, 10, (3, 10, 9223372036854775808)) t(-7, 10, 9223372036854775808, 100, (93, 10, 9223372036854775808)) t(-7, 10, 9223372036854775808, 2147483647, (2147483640, 10, 9223372036854775808)) t(-7, 10, 9223372036854775808, 9223372036854775808, (9223372036854775801, 10, 9223372036854775808)) t(-7, 2147483647, None, 0, (0, 0, 1)) t(-7, 2147483647, None, 1, (0, 1, 1)) t(-7, 2147483647, None, 5, (0, 5, 1)) t(-7, 2147483647, None, 10, (3, 10, 1)) t(-7, 2147483647, None, 100, (93, 100, 1)) t(-7, 2147483647, None, 2147483647, (2147483640, 2147483647, 1)) t(-7, 2147483647, None, 9223372036854775808, (9223372036854775801, 2147483647, 1)) t(-7, 2147483647, -5, 0, (-1, -1, -5)) t(-7, 2147483647, -5, 1, (-1, 0, -5)) t(-7, 2147483647, -5, 5, (-1, 4, -5)) t(-7, 2147483647, -5, 10, (3, 9, -5)) t(-7, 2147483647, -5, 100, (93, 99, -5)) t(-7, 2147483647, -5, 2147483647, (2147483640, 2147483646, -5)) t(-7, 2147483647, -5, 9223372036854775808, (9223372036854775801, 2147483647, -5)) t(-7, 2147483647, -3, 0, (-1, -1, -3)) t(-7, 2147483647, -3, 1, (-1, 0, -3)) t(-7, 2147483647, -3, 5, (-1, 4, -3)) t(-7, 2147483647, -3, 10, (3, 9, -3)) t(-7, 2147483647, -3, 100, (93, 99, -3)) t(-7, 2147483647, -3, 2147483647, (2147483640, 2147483646, -3)) t(-7, 2147483647, -3, 9223372036854775808, (9223372036854775801, 2147483647, -3)) t(-7, 2147483647, -1, 0, (-1, -1, -1)) t(-7, 2147483647, -1, 1, (-1, 0, -1)) t(-7, 2147483647, -1, 5, (-1, 4, -1)) t(-7, 2147483647, -1, 10, (3, 9, -1)) t(-7, 2147483647, -1, 100, (93, 99, -1)) t(-7, 2147483647, -1, 2147483647, (2147483640, 2147483646, -1)) t(-7, 2147483647, -1, 9223372036854775808, (9223372036854775801, 2147483647, -1)) t(-7, 2147483647, 1, 0, (0, 0, 1)) t(-7, 2147483647, 1, 1, (0, 1, 1)) t(-7, 2147483647, 1, 5, (0, 5, 1)) t(-7, 2147483647, 1, 10, (3, 10, 1)) t(-7, 2147483647, 1, 100, (93, 100, 1)) t(-7, 2147483647, 1, 2147483647, (2147483640, 2147483647, 1)) t(-7, 2147483647, 1, 9223372036854775808, (9223372036854775801, 2147483647, 1)) t(-7, 2147483647, 5, 0, (0, 0, 5)) t(-7, 2147483647, 5, 1, (0, 1, 5)) t(-7, 2147483647, 5, 5, (0, 5, 5)) t(-7, 2147483647, 5, 10, (3, 10, 5)) t(-7, 2147483647, 5, 100, (93, 100, 5)) t(-7, 2147483647, 5, 2147483647, (2147483640, 2147483647, 5)) t(-7, 2147483647, 5, 9223372036854775808, (9223372036854775801, 2147483647, 5)) t(-7, 2147483647, 20, 0, (0, 0, 20)) t(-7, 2147483647, 20, 1, (0, 1, 20)) t(-7, 2147483647, 20, 5, (0, 5, 20)) t(-7, 2147483647, 20, 10, (3, 10, 20)) t(-7, 2147483647, 20, 100, (93, 100, 20)) t(-7, 2147483647, 20, 2147483647, (2147483640, 2147483647, 20)) t(-7, 2147483647, 20, 9223372036854775808, (9223372036854775801, 2147483647, 20)) t(-7, 2147483647, 2147483647, 0, (0, 0, 2147483647)) t(-7, 2147483647, 2147483647, 1, (0, 1, 2147483647)) t(-7, 2147483647, 2147483647, 5, (0, 5, 2147483647)) t(-7, 2147483647, 2147483647, 10, (3, 10, 2147483647)) t(-7, 2147483647, 2147483647, 100, (93, 100, 2147483647)) t(-7, 2147483647, 2147483647, 2147483647, (2147483640, 2147483647, 2147483647)) t(-7, 2147483647, 2147483647, 9223372036854775808, (9223372036854775801, 2147483647, 2147483647)) t(-7, 2147483647, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-7, 2147483647, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-7, 2147483647, 9223372036854775808, 5, (0, 5, 9223372036854775808)) t(-7, 2147483647, 9223372036854775808, 10, (3, 10, 9223372036854775808)) t(-7, 2147483647, 9223372036854775808, 100, (93, 100, 9223372036854775808)) t(-7, 2147483647, 9223372036854775808, 2147483647, (2147483640, 2147483647, 9223372036854775808)) t(-7, 2147483647, 9223372036854775808, 9223372036854775808, (9223372036854775801, 2147483647, 9223372036854775808)) t(-7, 9223372036854775808, None, 0, (0, 0, 1)) t(-7, 9223372036854775808, None, 1, (0, 1, 1)) t(-7, 9223372036854775808, None, 5, (0, 5, 1)) t(-7, 9223372036854775808, None, 10, (3, 10, 1)) t(-7, 9223372036854775808, None, 100, (93, 100, 1)) t(-7, 9223372036854775808, None, 2147483647, (2147483640, 2147483647, 1)) t(-7, 9223372036854775808, None, 9223372036854775808, (9223372036854775801, 9223372036854775808, 1)) t(-7, 9223372036854775808, -5, 0, (-1, -1, -5)) t(-7, 9223372036854775808, -5, 1, (-1, 0, -5)) t(-7, 9223372036854775808, -5, 5, (-1, 4, -5)) t(-7, 9223372036854775808, -5, 10, (3, 9, -5)) t(-7, 9223372036854775808, -5, 100, (93, 99, -5)) t(-7, 9223372036854775808, -5, 2147483647, (2147483640, 2147483646, -5)) t(-7, 9223372036854775808, -5, 9223372036854775808, (9223372036854775801, 9223372036854775807, -5)) t(-7, 9223372036854775808, -3, 0, (-1, -1, -3)) t(-7, 9223372036854775808, -3, 1, (-1, 0, -3)) t(-7, 9223372036854775808, -3, 5, (-1, 4, -3)) t(-7, 9223372036854775808, -3, 10, (3, 9, -3)) t(-7, 9223372036854775808, -3, 100, (93, 99, -3)) t(-7, 9223372036854775808, -3, 2147483647, (2147483640, 2147483646, -3)) t(-7, 9223372036854775808, -3, 9223372036854775808, (9223372036854775801, 9223372036854775807, -3)) t(-7, 9223372036854775808, -1, 0, (-1, -1, -1)) t(-7, 9223372036854775808, -1, 1, (-1, 0, -1)) t(-7, 9223372036854775808, -1, 5, (-1, 4, -1)) t(-7, 9223372036854775808, -1, 10, (3, 9, -1)) t(-7, 9223372036854775808, -1, 100, (93, 99, -1)) t(-7, 9223372036854775808, -1, 2147483647, (2147483640, 2147483646, -1)) t(-7, 9223372036854775808, -1, 9223372036854775808, (9223372036854775801, 9223372036854775807, -1)) t(-7, 9223372036854775808, 1, 0, (0, 0, 1)) t(-7, 9223372036854775808, 1, 1, (0, 1, 1)) t(-7, 9223372036854775808, 1, 5, (0, 5, 1)) t(-7, 9223372036854775808, 1, 10, (3, 10, 1)) t(-7, 9223372036854775808, 1, 100, (93, 100, 1)) t(-7, 9223372036854775808, 1, 2147483647, (2147483640, 2147483647, 1)) t(-7, 9223372036854775808, 1, 9223372036854775808, (9223372036854775801, 9223372036854775808, 1)) t(-7, 9223372036854775808, 5, 0, (0, 0, 5)) t(-7, 9223372036854775808, 5, 1, (0, 1, 5)) t(-7, 9223372036854775808, 5, 5, (0, 5, 5)) t(-7, 9223372036854775808, 5, 10, (3, 10, 5)) t(-7, 9223372036854775808, 5, 100, (93, 100, 5)) t(-7, 9223372036854775808, 5, 2147483647, (2147483640, 2147483647, 5)) t(-7, 9223372036854775808, 5, 9223372036854775808, (9223372036854775801, 9223372036854775808, 5)) t(-7, 9223372036854775808, 20, 0, (0, 0, 20)) t(-7, 9223372036854775808, 20, 1, (0, 1, 20)) t(-7, 9223372036854775808, 20, 5, (0, 5, 20)) t(-7, 9223372036854775808, 20, 10, (3, 10, 20)) t(-7, 9223372036854775808, 20, 100, (93, 100, 20)) t(-7, 9223372036854775808, 20, 2147483647, (2147483640, 2147483647, 20)) t(-7, 9223372036854775808, 20, 9223372036854775808, (9223372036854775801, 9223372036854775808, 20)) t(-7, 9223372036854775808, 2147483647, 0, (0, 0, 2147483647)) t(-7, 9223372036854775808, 2147483647, 1, (0, 1, 2147483647)) t(-7, 9223372036854775808, 2147483647, 5, (0, 5, 2147483647)) t(-7, 9223372036854775808, 2147483647, 10, (3, 10, 2147483647)) t(-7, 9223372036854775808, 2147483647, 100, (93, 100, 2147483647)) t(-7, 9223372036854775808, 2147483647, 2147483647, (2147483640, 2147483647, 2147483647)) t(-7, 9223372036854775808, 2147483647, 9223372036854775808, (9223372036854775801, 9223372036854775808, 2147483647)) t(-7, 9223372036854775808, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-7, 9223372036854775808, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-7, 9223372036854775808, 9223372036854775808, 5, (0, 5, 9223372036854775808)) t(-7, 9223372036854775808, 9223372036854775808, 10, (3, 10, 9223372036854775808)) t(-7, 9223372036854775808, 9223372036854775808, 100, (93, 100, 9223372036854775808)) t(-7, 9223372036854775808, 9223372036854775808, 2147483647, (2147483640, 2147483647, 9223372036854775808)) t(-7, 9223372036854775808, 9223372036854775808, 9223372036854775808, (9223372036854775801, 9223372036854775808, 9223372036854775808)) t(-2, None, None, 0, (0, 0, 1)) t(-2, None, None, 1, (0, 1, 1)) t(-2, None, None, 5, (3, 5, 1)) t(-2, None, None, 10, (8, 10, 1)) t(-2, None, None, 100, (98, 100, 1)) t(-2, None, None, 2147483647, (2147483645, 2147483647, 1)) t(-2, None, None, 9223372036854775808, (9223372036854775806, 9223372036854775808, 1)) t(-2, None, -5, 0, (-1, -1, -5)) t(-2, None, -5, 1, (-1, -1, -5)) t(-2, None, -5, 5, (3, -1, -5)) t(-2, None, -5, 10, (8, -1, -5)) t(-2, None, -5, 100, (98, -1, -5)) t(-2, None, -5, 2147483647, (2147483645, -1, -5)) t(-2, None, -5, 9223372036854775808, (9223372036854775806, -1, -5)) t(-2, None, -3, 0, (-1, -1, -3)) t(-2, None, -3, 1, (-1, -1, -3)) t(-2, None, -3, 5, (3, -1, -3)) t(-2, None, -3, 10, (8, -1, -3)) t(-2, None, -3, 100, (98, -1, -3)) t(-2, None, -3, 2147483647, (2147483645, -1, -3)) t(-2, None, -3, 9223372036854775808, (9223372036854775806, -1, -3)) t(-2, None, -1, 0, (-1, -1, -1)) t(-2, None, -1, 1, (-1, -1, -1)) t(-2, None, -1, 5, (3, -1, -1)) t(-2, None, -1, 10, (8, -1, -1)) t(-2, None, -1, 100, (98, -1, -1)) t(-2, None, -1, 2147483647, (2147483645, -1, -1)) t(-2, None, -1, 9223372036854775808, (9223372036854775806, -1, -1)) t(-2, None, 1, 0, (0, 0, 1)) t(-2, None, 1, 1, (0, 1, 1)) t(-2, None, 1, 5, (3, 5, 1)) t(-2, None, 1, 10, (8, 10, 1)) t(-2, None, 1, 100, (98, 100, 1)) t(-2, None, 1, 2147483647, (2147483645, 2147483647, 1)) t(-2, None, 1, 9223372036854775808, (9223372036854775806, 9223372036854775808, 1)) t(-2, None, 5, 0, (0, 0, 5)) t(-2, None, 5, 1, (0, 1, 5)) t(-2, None, 5, 5, (3, 5, 5)) t(-2, None, 5, 10, (8, 10, 5)) t(-2, None, 5, 100, (98, 100, 5)) t(-2, None, 5, 2147483647, (2147483645, 2147483647, 5)) t(-2, None, 5, 9223372036854775808, (9223372036854775806, 9223372036854775808, 5)) t(-2, None, 20, 0, (0, 0, 20)) t(-2, None, 20, 1, (0, 1, 20)) t(-2, None, 20, 5, (3, 5, 20)) t(-2, None, 20, 10, (8, 10, 20)) t(-2, None, 20, 100, (98, 100, 20)) t(-2, None, 20, 2147483647, (2147483645, 2147483647, 20)) t(-2, None, 20, 9223372036854775808, (9223372036854775806, 9223372036854775808, 20)) t(-2, None, 2147483647, 0, (0, 0, 2147483647)) t(-2, None, 2147483647, 1, (0, 1, 2147483647)) t(-2, None, 2147483647, 5, (3, 5, 2147483647)) t(-2, None, 2147483647, 10, (8, 10, 2147483647)) t(-2, None, 2147483647, 100, (98, 100, 2147483647)) t(-2, None, 2147483647, 2147483647, (2147483645, 2147483647, 2147483647)) t(-2, None, 2147483647, 9223372036854775808, (9223372036854775806, 9223372036854775808, 2147483647)) t(-2, None, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-2, None, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-2, None, 9223372036854775808, 5, (3, 5, 9223372036854775808)) t(-2, None, 9223372036854775808, 10, (8, 10, 9223372036854775808)) t(-2, None, 9223372036854775808, 100, (98, 100, 9223372036854775808)) t(-2, None, 9223372036854775808, 2147483647, (2147483645, 2147483647, 9223372036854775808)) t(-2, None, 9223372036854775808, 9223372036854775808, (9223372036854775806, 9223372036854775808, 9223372036854775808)) t(-2, -7, None, 0, (0, 0, 1)) t(-2, -7, None, 1, (0, 0, 1)) t(-2, -7, None, 5, (3, 0, 1)) t(-2, -7, None, 10, (8, 3, 1)) t(-2, -7, None, 100, (98, 93, 1)) t(-2, -7, None, 2147483647, (2147483645, 2147483640, 1)) t(-2, -7, None, 9223372036854775808, (9223372036854775806, 9223372036854775801, 1)) t(-2, -7, -5, 0, (-1, -1, -5)) t(-2, -7, -5, 1, (-1, -1, -5)) t(-2, -7, -5, 5, (3, -1, -5)) t(-2, -7, -5, 10, (8, 3, -5)) t(-2, -7, -5, 100, (98, 93, -5)) t(-2, -7, -5, 2147483647, (2147483645, 2147483640, -5)) t(-2, -7, -5, 9223372036854775808, (9223372036854775806, 9223372036854775801, -5)) t(-2, -7, -3, 0, (-1, -1, -3)) t(-2, -7, -3, 1, (-1, -1, -3)) t(-2, -7, -3, 5, (3, -1, -3)) t(-2, -7, -3, 10, (8, 3, -3)) t(-2, -7, -3, 100, (98, 93, -3)) t(-2, -7, -3, 2147483647, (2147483645, 2147483640, -3)) t(-2, -7, -3, 9223372036854775808, (9223372036854775806, 9223372036854775801, -3)) t(-2, -7, -1, 0, (-1, -1, -1)) t(-2, -7, -1, 1, (-1, -1, -1)) t(-2, -7, -1, 5, (3, -1, -1)) t(-2, -7, -1, 10, (8, 3, -1)) t(-2, -7, -1, 100, (98, 93, -1)) t(-2, -7, -1, 2147483647, (2147483645, 2147483640, -1)) t(-2, -7, -1, 9223372036854775808, (9223372036854775806, 9223372036854775801, -1)) t(-2, -7, 1, 0, (0, 0, 1)) t(-2, -7, 1, 1, (0, 0, 1)) t(-2, -7, 1, 5, (3, 0, 1)) t(-2, -7, 1, 10, (8, 3, 1)) t(-2, -7, 1, 100, (98, 93, 1)) t(-2, -7, 1, 2147483647, (2147483645, 2147483640, 1)) t(-2, -7, 1, 9223372036854775808, (9223372036854775806, 9223372036854775801, 1)) t(-2, -7, 5, 0, (0, 0, 5)) t(-2, -7, 5, 1, (0, 0, 5)) t(-2, -7, 5, 5, (3, 0, 5)) t(-2, -7, 5, 10, (8, 3, 5)) t(-2, -7, 5, 100, (98, 93, 5)) t(-2, -7, 5, 2147483647, (2147483645, 2147483640, 5)) t(-2, -7, 5, 9223372036854775808, (9223372036854775806, 9223372036854775801, 5)) t(-2, -7, 20, 0, (0, 0, 20)) t(-2, -7, 20, 1, (0, 0, 20)) t(-2, -7, 20, 5, (3, 0, 20)) t(-2, -7, 20, 10, (8, 3, 20)) t(-2, -7, 20, 100, (98, 93, 20)) t(-2, -7, 20, 2147483647, (2147483645, 2147483640, 20)) t(-2, -7, 20, 9223372036854775808, (9223372036854775806, 9223372036854775801, 20)) t(-2, -7, 2147483647, 0, (0, 0, 2147483647)) t(-2, -7, 2147483647, 1, (0, 0, 2147483647)) t(-2, -7, 2147483647, 5, (3, 0, 2147483647)) t(-2, -7, 2147483647, 10, (8, 3, 2147483647)) t(-2, -7, 2147483647, 100, (98, 93, 2147483647)) t(-2, -7, 2147483647, 2147483647, (2147483645, 2147483640, 2147483647)) t(-2, -7, 2147483647, 9223372036854775808, (9223372036854775806, 9223372036854775801, 2147483647)) t(-2, -7, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-2, -7, 9223372036854775808, 1, (0, 0, 9223372036854775808)) t(-2, -7, 9223372036854775808, 5, (3, 0, 9223372036854775808)) t(-2, -7, 9223372036854775808, 10, (8, 3, 9223372036854775808)) t(-2, -7, 9223372036854775808, 100, (98, 93, 9223372036854775808)) t(-2, -7, 9223372036854775808, 2147483647, (2147483645, 2147483640, 9223372036854775808)) t(-2, -7, 9223372036854775808, 9223372036854775808, (9223372036854775806, 9223372036854775801, 9223372036854775808)) t(-2, -2, None, 0, (0, 0, 1)) t(-2, -2, None, 1, (0, 0, 1)) t(-2, -2, None, 5, (3, 3, 1)) t(-2, -2, None, 10, (8, 8, 1)) t(-2, -2, None, 100, (98, 98, 1)) t(-2, -2, None, 2147483647, (2147483645, 2147483645, 1)) t(-2, -2, None, 9223372036854775808, (9223372036854775806, 9223372036854775806, 1)) t(-2, -2, -5, 0, (-1, -1, -5)) t(-2, -2, -5, 1, (-1, -1, -5)) t(-2, -2, -5, 5, (3, 3, -5)) t(-2, -2, -5, 10, (8, 8, -5)) t(-2, -2, -5, 100, (98, 98, -5)) t(-2, -2, -5, 2147483647, (2147483645, 2147483645, -5)) t(-2, -2, -5, 9223372036854775808, (9223372036854775806, 9223372036854775806, -5)) t(-2, -2, -3, 0, (-1, -1, -3)) t(-2, -2, -3, 1, (-1, -1, -3)) t(-2, -2, -3, 5, (3, 3, -3)) t(-2, -2, -3, 10, (8, 8, -3)) t(-2, -2, -3, 100, (98, 98, -3)) t(-2, -2, -3, 2147483647, (2147483645, 2147483645, -3)) t(-2, -2, -3, 9223372036854775808, (9223372036854775806, 9223372036854775806, -3)) t(-2, -2, -1, 0, (-1, -1, -1)) t(-2, -2, -1, 1, (-1, -1, -1)) t(-2, -2, -1, 5, (3, 3, -1)) t(-2, -2, -1, 10, (8, 8, -1)) t(-2, -2, -1, 100, (98, 98, -1)) t(-2, -2, -1, 2147483647, (2147483645, 2147483645, -1)) t(-2, -2, -1, 9223372036854775808, (9223372036854775806, 9223372036854775806, -1)) t(-2, -2, 1, 0, (0, 0, 1)) t(-2, -2, 1, 1, (0, 0, 1)) t(-2, -2, 1, 5, (3, 3, 1)) t(-2, -2, 1, 10, (8, 8, 1)) t(-2, -2, 1, 100, (98, 98, 1)) t(-2, -2, 1, 2147483647, (2147483645, 2147483645, 1)) t(-2, -2, 1, 9223372036854775808, (9223372036854775806, 9223372036854775806, 1)) t(-2, -2, 5, 0, (0, 0, 5)) t(-2, -2, 5, 1, (0, 0, 5)) t(-2, -2, 5, 5, (3, 3, 5)) t(-2, -2, 5, 10, (8, 8, 5)) t(-2, -2, 5, 100, (98, 98, 5)) t(-2, -2, 5, 2147483647, (2147483645, 2147483645, 5)) t(-2, -2, 5, 9223372036854775808, (9223372036854775806, 9223372036854775806, 5)) t(-2, -2, 20, 0, (0, 0, 20)) t(-2, -2, 20, 1, (0, 0, 20)) t(-2, -2, 20, 5, (3, 3, 20)) t(-2, -2, 20, 10, (8, 8, 20)) t(-2, -2, 20, 100, (98, 98, 20)) t(-2, -2, 20, 2147483647, (2147483645, 2147483645, 20)) t(-2, -2, 20, 9223372036854775808, (9223372036854775806, 9223372036854775806, 20)) t(-2, -2, 2147483647, 0, (0, 0, 2147483647)) t(-2, -2, 2147483647, 1, (0, 0, 2147483647)) t(-2, -2, 2147483647, 5, (3, 3, 2147483647)) t(-2, -2, 2147483647, 10, (8, 8, 2147483647)) t(-2, -2, 2147483647, 100, (98, 98, 2147483647)) t(-2, -2, 2147483647, 2147483647, (2147483645, 2147483645, 2147483647)) t(-2, -2, 2147483647, 9223372036854775808, (9223372036854775806, 9223372036854775806, 2147483647)) t(-2, -2, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-2, -2, 9223372036854775808, 1, (0, 0, 9223372036854775808)) t(-2, -2, 9223372036854775808, 5, (3, 3, 9223372036854775808)) t(-2, -2, 9223372036854775808, 10, (8, 8, 9223372036854775808)) t(-2, -2, 9223372036854775808, 100, (98, 98, 9223372036854775808)) t(-2, -2, 9223372036854775808, 2147483647, (2147483645, 2147483645, 9223372036854775808)) t(-2, -2, 9223372036854775808, 9223372036854775808, (9223372036854775806, 9223372036854775806, 9223372036854775808)) t(-2, 0, None, 0, (0, 0, 1)) t(-2, 0, None, 1, (0, 0, 1)) t(-2, 0, None, 5, (3, 0, 1)) t(-2, 0, None, 10, (8, 0, 1)) t(-2, 0, None, 100, (98, 0, 1)) t(-2, 0, None, 2147483647, (2147483645, 0, 1)) t(-2, 0, None, 9223372036854775808, (9223372036854775806, 0, 1)) t(-2, 0, -5, 0, (-1, -1, -5)) t(-2, 0, -5, 1, (-1, 0, -5)) t(-2, 0, -5, 5, (3, 0, -5)) t(-2, 0, -5, 10, (8, 0, -5)) t(-2, 0, -5, 100, (98, 0, -5)) t(-2, 0, -5, 2147483647, (2147483645, 0, -5)) t(-2, 0, -5, 9223372036854775808, (9223372036854775806, 0, -5)) t(-2, 0, -3, 0, (-1, -1, -3)) t(-2, 0, -3, 1, (-1, 0, -3)) t(-2, 0, -3, 5, (3, 0, -3)) t(-2, 0, -3, 10, (8, 0, -3)) t(-2, 0, -3, 100, (98, 0, -3)) t(-2, 0, -3, 2147483647, (2147483645, 0, -3)) t(-2, 0, -3, 9223372036854775808, (9223372036854775806, 0, -3)) t(-2, 0, -1, 0, (-1, -1, -1)) t(-2, 0, -1, 1, (-1, 0, -1)) t(-2, 0, -1, 5, (3, 0, -1)) t(-2, 0, -1, 10, (8, 0, -1)) t(-2, 0, -1, 100, (98, 0, -1)) t(-2, 0, -1, 2147483647, (2147483645, 0, -1)) t(-2, 0, -1, 9223372036854775808, (9223372036854775806, 0, -1)) t(-2, 0, 1, 0, (0, 0, 1)) t(-2, 0, 1, 1, (0, 0, 1)) t(-2, 0, 1, 5, (3, 0, 1)) t(-2, 0, 1, 10, (8, 0, 1)) t(-2, 0, 1, 100, (98, 0, 1)) t(-2, 0, 1, 2147483647, (2147483645, 0, 1)) t(-2, 0, 1, 9223372036854775808, (9223372036854775806, 0, 1)) t(-2, 0, 5, 0, (0, 0, 5)) t(-2, 0, 5, 1, (0, 0, 5)) t(-2, 0, 5, 5, (3, 0, 5)) t(-2, 0, 5, 10, (8, 0, 5)) t(-2, 0, 5, 100, (98, 0, 5)) t(-2, 0, 5, 2147483647, (2147483645, 0, 5)) t(-2, 0, 5, 9223372036854775808, (9223372036854775806, 0, 5)) t(-2, 0, 20, 0, (0, 0, 20)) t(-2, 0, 20, 1, (0, 0, 20)) t(-2, 0, 20, 5, (3, 0, 20)) t(-2, 0, 20, 10, (8, 0, 20)) t(-2, 0, 20, 100, (98, 0, 20)) t(-2, 0, 20, 2147483647, (2147483645, 0, 20)) t(-2, 0, 20, 9223372036854775808, (9223372036854775806, 0, 20)) t(-2, 0, 2147483647, 0, (0, 0, 2147483647)) t(-2, 0, 2147483647, 1, (0, 0, 2147483647)) t(-2, 0, 2147483647, 5, (3, 0, 2147483647)) t(-2, 0, 2147483647, 10, (8, 0, 2147483647)) t(-2, 0, 2147483647, 100, (98, 0, 2147483647)) t(-2, 0, 2147483647, 2147483647, (2147483645, 0, 2147483647)) t(-2, 0, 2147483647, 9223372036854775808, (9223372036854775806, 0, 2147483647)) t(-2, 0, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-2, 0, 9223372036854775808, 1, (0, 0, 9223372036854775808)) t(-2, 0, 9223372036854775808, 5, (3, 0, 9223372036854775808)) t(-2, 0, 9223372036854775808, 10, (8, 0, 9223372036854775808)) t(-2, 0, 9223372036854775808, 100, (98, 0, 9223372036854775808)) t(-2, 0, 9223372036854775808, 2147483647, (2147483645, 0, 9223372036854775808)) t(-2, 0, 9223372036854775808, 9223372036854775808, (9223372036854775806, 0, 9223372036854775808)) t(-2, 1, None, 0, (0, 0, 1)) t(-2, 1, None, 1, (0, 1, 1)) t(-2, 1, None, 5, (3, 1, 1)) t(-2, 1, None, 10, (8, 1, 1)) t(-2, 1, None, 100, (98, 1, 1)) t(-2, 1, None, 2147483647, (2147483645, 1, 1)) t(-2, 1, None, 9223372036854775808, (9223372036854775806, 1, 1)) t(-2, 1, -5, 0, (-1, -1, -5)) t(-2, 1, -5, 1, (-1, 0, -5)) t(-2, 1, -5, 5, (3, 1, -5)) t(-2, 1, -5, 10, (8, 1, -5)) t(-2, 1, -5, 100, (98, 1, -5)) t(-2, 1, -5, 2147483647, (2147483645, 1, -5)) t(-2, 1, -5, 9223372036854775808, (9223372036854775806, 1, -5)) t(-2, 1, -3, 0, (-1, -1, -3)) t(-2, 1, -3, 1, (-1, 0, -3)) t(-2, 1, -3, 5, (3, 1, -3)) t(-2, 1, -3, 10, (8, 1, -3)) t(-2, 1, -3, 100, (98, 1, -3)) t(-2, 1, -3, 2147483647, (2147483645, 1, -3)) t(-2, 1, -3, 9223372036854775808, (9223372036854775806, 1, -3)) t(-2, 1, -1, 0, (-1, -1, -1)) t(-2, 1, -1, 1, (-1, 0, -1)) t(-2, 1, -1, 5, (3, 1, -1)) t(-2, 1, -1, 10, (8, 1, -1)) t(-2, 1, -1, 100, (98, 1, -1)) t(-2, 1, -1, 2147483647, (2147483645, 1, -1)) t(-2, 1, -1, 9223372036854775808, (9223372036854775806, 1, -1)) t(-2, 1, 1, 0, (0, 0, 1)) t(-2, 1, 1, 1, (0, 1, 1)) t(-2, 1, 1, 5, (3, 1, 1)) t(-2, 1, 1, 10, (8, 1, 1)) t(-2, 1, 1, 100, (98, 1, 1)) t(-2, 1, 1, 2147483647, (2147483645, 1, 1)) t(-2, 1, 1, 9223372036854775808, (9223372036854775806, 1, 1)) t(-2, 1, 5, 0, (0, 0, 5)) t(-2, 1, 5, 1, (0, 1, 5)) t(-2, 1, 5, 5, (3, 1, 5)) t(-2, 1, 5, 10, (8, 1, 5)) t(-2, 1, 5, 100, (98, 1, 5)) t(-2, 1, 5, 2147483647, (2147483645, 1, 5)) t(-2, 1, 5, 9223372036854775808, (9223372036854775806, 1, 5)) t(-2, 1, 20, 0, (0, 0, 20)) t(-2, 1, 20, 1, (0, 1, 20)) t(-2, 1, 20, 5, (3, 1, 20)) t(-2, 1, 20, 10, (8, 1, 20)) t(-2, 1, 20, 100, (98, 1, 20)) t(-2, 1, 20, 2147483647, (2147483645, 1, 20)) t(-2, 1, 20, 9223372036854775808, (9223372036854775806, 1, 20)) t(-2, 1, 2147483647, 0, (0, 0, 2147483647)) t(-2, 1, 2147483647, 1, (0, 1, 2147483647)) t(-2, 1, 2147483647, 5, (3, 1, 2147483647)) t(-2, 1, 2147483647, 10, (8, 1, 2147483647)) t(-2, 1, 2147483647, 100, (98, 1, 2147483647)) t(-2, 1, 2147483647, 2147483647, (2147483645, 1, 2147483647)) t(-2, 1, 2147483647, 9223372036854775808, (9223372036854775806, 1, 2147483647)) t(-2, 1, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-2, 1, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-2, 1, 9223372036854775808, 5, (3, 1, 9223372036854775808)) t(-2, 1, 9223372036854775808, 10, (8, 1, 9223372036854775808)) t(-2, 1, 9223372036854775808, 100, (98, 1, 9223372036854775808)) t(-2, 1, 9223372036854775808, 2147483647, (2147483645, 1, 9223372036854775808)) t(-2, 1, 9223372036854775808, 9223372036854775808, (9223372036854775806, 1, 9223372036854775808)) t(-2, 6, None, 0, (0, 0, 1)) t(-2, 6, None, 1, (0, 1, 1)) t(-2, 6, None, 5, (3, 5, 1)) t(-2, 6, None, 10, (8, 6, 1)) t(-2, 6, None, 100, (98, 6, 1)) t(-2, 6, None, 2147483647, (2147483645, 6, 1)) t(-2, 6, None, 9223372036854775808, (9223372036854775806, 6, 1)) t(-2, 6, -5, 0, (-1, -1, -5)) t(-2, 6, -5, 1, (-1, 0, -5)) t(-2, 6, -5, 5, (3, 4, -5)) t(-2, 6, -5, 10, (8, 6, -5)) t(-2, 6, -5, 100, (98, 6, -5)) t(-2, 6, -5, 2147483647, (2147483645, 6, -5)) t(-2, 6, -5, 9223372036854775808, (9223372036854775806, 6, -5)) t(-2, 6, -3, 0, (-1, -1, -3)) t(-2, 6, -3, 1, (-1, 0, -3)) t(-2, 6, -3, 5, (3, 4, -3)) t(-2, 6, -3, 10, (8, 6, -3)) t(-2, 6, -3, 100, (98, 6, -3)) t(-2, 6, -3, 2147483647, (2147483645, 6, -3)) t(-2, 6, -3, 9223372036854775808, (9223372036854775806, 6, -3)) t(-2, 6, -1, 0, (-1, -1, -1)) t(-2, 6, -1, 1, (-1, 0, -1)) t(-2, 6, -1, 5, (3, 4, -1)) t(-2, 6, -1, 10, (8, 6, -1)) t(-2, 6, -1, 100, (98, 6, -1)) t(-2, 6, -1, 2147483647, (2147483645, 6, -1)) t(-2, 6, -1, 9223372036854775808, (9223372036854775806, 6, -1)) t(-2, 6, 1, 0, (0, 0, 1)) t(-2, 6, 1, 1, (0, 1, 1)) t(-2, 6, 1, 5, (3, 5, 1)) t(-2, 6, 1, 10, (8, 6, 1)) t(-2, 6, 1, 100, (98, 6, 1)) t(-2, 6, 1, 2147483647, (2147483645, 6, 1)) t(-2, 6, 1, 9223372036854775808, (9223372036854775806, 6, 1)) t(-2, 6, 5, 0, (0, 0, 5)) t(-2, 6, 5, 1, (0, 1, 5)) t(-2, 6, 5, 5, (3, 5, 5)) t(-2, 6, 5, 10, (8, 6, 5)) t(-2, 6, 5, 100, (98, 6, 5)) t(-2, 6, 5, 2147483647, (2147483645, 6, 5)) t(-2, 6, 5, 9223372036854775808, (9223372036854775806, 6, 5)) t(-2, 6, 20, 0, (0, 0, 20)) t(-2, 6, 20, 1, (0, 1, 20)) t(-2, 6, 20, 5, (3, 5, 20)) t(-2, 6, 20, 10, (8, 6, 20)) t(-2, 6, 20, 100, (98, 6, 20)) t(-2, 6, 20, 2147483647, (2147483645, 6, 20)) t(-2, 6, 20, 9223372036854775808, (9223372036854775806, 6, 20)) t(-2, 6, 2147483647, 0, (0, 0, 2147483647)) t(-2, 6, 2147483647, 1, (0, 1, 2147483647)) t(-2, 6, 2147483647, 5, (3, 5, 2147483647)) t(-2, 6, 2147483647, 10, (8, 6, 2147483647)) t(-2, 6, 2147483647, 100, (98, 6, 2147483647)) t(-2, 6, 2147483647, 2147483647, (2147483645, 6, 2147483647)) t(-2, 6, 2147483647, 9223372036854775808, (9223372036854775806, 6, 2147483647)) t(-2, 6, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-2, 6, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-2, 6, 9223372036854775808, 5, (3, 5, 9223372036854775808)) t(-2, 6, 9223372036854775808, 10, (8, 6, 9223372036854775808)) t(-2, 6, 9223372036854775808, 100, (98, 6, 9223372036854775808)) t(-2, 6, 9223372036854775808, 2147483647, (2147483645, 6, 9223372036854775808)) t(-2, 6, 9223372036854775808, 9223372036854775808, (9223372036854775806, 6, 9223372036854775808)) t(-2, 10, None, 0, (0, 0, 1)) t(-2, 10, None, 1, (0, 1, 1)) t(-2, 10, None, 5, (3, 5, 1)) t(-2, 10, None, 10, (8, 10, 1)) t(-2, 10, None, 100, (98, 10, 1)) t(-2, 10, 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10, (8, 10, 1)) t(-2, 10, 1, 100, (98, 10, 1)) t(-2, 10, 1, 2147483647, (2147483645, 10, 1)) t(-2, 10, 1, 9223372036854775808, (9223372036854775806, 10, 1)) t(-2, 10, 5, 0, (0, 0, 5)) t(-2, 10, 5, 1, (0, 1, 5)) t(-2, 10, 5, 5, (3, 5, 5)) t(-2, 10, 5, 10, (8, 10, 5)) t(-2, 10, 5, 100, (98, 10, 5)) t(-2, 10, 5, 2147483647, (2147483645, 10, 5)) t(-2, 10, 5, 9223372036854775808, (9223372036854775806, 10, 5)) t(-2, 10, 20, 0, (0, 0, 20)) t(-2, 10, 20, 1, (0, 1, 20)) t(-2, 10, 20, 5, (3, 5, 20)) t(-2, 10, 20, 10, (8, 10, 20)) t(-2, 10, 20, 100, (98, 10, 20)) t(-2, 10, 20, 2147483647, (2147483645, 10, 20)) t(-2, 10, 20, 9223372036854775808, (9223372036854775806, 10, 20)) t(-2, 10, 2147483647, 0, (0, 0, 2147483647)) t(-2, 10, 2147483647, 1, (0, 1, 2147483647)) t(-2, 10, 2147483647, 5, (3, 5, 2147483647)) t(-2, 10, 2147483647, 10, (8, 10, 2147483647)) t(-2, 10, 2147483647, 100, (98, 10, 2147483647)) t(-2, 10, 2147483647, 2147483647, (2147483645, 10, 2147483647)) t(-2, 10, 2147483647, 9223372036854775808, (9223372036854775806, 10, 2147483647)) t(-2, 10, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(-2, 10, 9223372036854775808, 1, (0, 1, 9223372036854775808)) t(-2, 10, 9223372036854775808, 5, (3, 5, 9223372036854775808)) t(-2, 10, 9223372036854775808, 10, (8, 10, 9223372036854775808)) t(-2, 10, 9223372036854775808, 100, (98, 10, 9223372036854775808)) t(-2, 10, 9223372036854775808, 2147483647, (2147483645, 10, 9223372036854775808)) t(-2, 10, 9223372036854775808, 9223372036854775808, (9223372036854775806, 10, 9223372036854775808)) t(-2, 2147483647, None, 0, (0, 0, 1)) t(-2, 2147483647, None, 1, (0, 1, 1)) t(-2, 2147483647, None, 5, (3, 5, 1)) t(-2, 2147483647, None, 10, (8, 10, 1)) t(-2, 2147483647, None, 100, (98, 100, 1)) t(-2, 2147483647, None, 2147483647, (2147483645, 2147483647, 1)) t(-2, 2147483647, None, 9223372036854775808, (9223372036854775806, 2147483647, 1)) t(-2, 2147483647, -5, 0, (-1, -1, -5)) t(-2, 2147483647, -5, 1, (-1, 0, -5)) t(-2, 2147483647, -5, 5, (3, 4, -5)) t(-2, 2147483647, -5, 10, (8, 9, -5)) t(-2, 2147483647, -5, 100, (98, 99, -5)) t(-2, 2147483647, -5, 2147483647, (2147483645, 2147483646, -5)) t(-2, 2147483647, -5, 9223372036854775808, (9223372036854775806, 2147483647, -5)) t(-2, 2147483647, -3, 0, (-1, -1, -3)) t(-2, 2147483647, -3, 1, (-1, 0, -3)) t(-2, 2147483647, -3, 5, (3, 4, -3)) t(-2, 2147483647, -3, 10, (8, 9, -3)) t(-2, 2147483647, -3, 100, (98, 99, -3)) t(-2, 2147483647, -3, 2147483647, (2147483645, 2147483646, -3)) t(-2, 2147483647, -3, 9223372036854775808, (9223372036854775806, 2147483647, -3)) t(-2, 2147483647, -1, 0, (-1, -1, -1)) t(-2, 2147483647, -1, 1, (-1, 0, -1)) t(-2, 2147483647, -1, 5, (3, 4, -1)) t(-2, 2147483647, -1, 10, (8, 9, -1)) t(-2, 2147483647, -1, 100, (98, 99, -1)) t(-2, 2147483647, -1, 2147483647, (2147483645, 2147483646, -1)) t(-2, 2147483647, -1, 9223372036854775808, (9223372036854775806, 2147483647, -1)) t(-2, 2147483647, 1, 0, (0, 0, 1)) t(-2, 2147483647, 1, 1, (0, 1, 1)) t(-2, 2147483647, 1, 5, (3, 5, 1)) t(-2, 2147483647, 1, 10, (8, 10, 1)) t(-2, 2147483647, 1, 100, (98, 100, 1)) t(-2, 2147483647, 1, 2147483647, (2147483645, 2147483647, 1)) t(-2, 2147483647, 1, 9223372036854775808, (9223372036854775806, 2147483647, 1)) t(-2, 2147483647, 5, 0, (0, 0, 5)) t(-2, 2147483647, 5, 1, (0, 1, 5)) t(-2, 2147483647, 5, 5, (3, 5, 5)) t(-2, 2147483647, 5, 10, (8, 10, 5)) t(-2, 2147483647, 5, 100, (98, 100, 5)) t(-2, 2147483647, 5, 2147483647, (2147483645, 2147483647, 5)) t(-2, 2147483647, 5, 9223372036854775808, (9223372036854775806, 2147483647, 5)) t(-2, 2147483647, 20, 0, (0, 0, 20)) t(-2, 2147483647, 20, 1, (0, 1, 20)) t(-2, 2147483647, 20, 5, (3, 5, 20)) t(-2, 2147483647, 20, 10, (8, 10, 20)) t(-2, 2147483647, 20, 100, (98, 100, 20)) t(-2, 2147483647, 20, 2147483647, (2147483645, 2147483647, 20)) t(-2, 2147483647, 20, 9223372036854775808, (9223372036854775806, 2147483647, 20)) t(-2, 2147483647, 2147483647, 0, (0, 0, 2147483647)) t(-2, 2147483647, 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1)) t(-2, 9223372036854775808, None, 1, (0, 1, 1)) t(-2, 9223372036854775808, None, 5, (3, 5, 1)) t(-2, 9223372036854775808, None, 10, (8, 10, 1)) t(-2, 9223372036854775808, None, 100, (98, 100, 1)) t(-2, 9223372036854775808, None, 2147483647, (2147483645, 2147483647, 1)) t(-2, 9223372036854775808, None, 9223372036854775808, (9223372036854775806, 9223372036854775808, 1)) t(-2, 9223372036854775808, -5, 0, (-1, -1, -5)) t(-2, 9223372036854775808, -5, 1, (-1, 0, -5)) t(-2, 9223372036854775808, -5, 5, (3, 4, -5)) t(-2, 9223372036854775808, -5, 10, (8, 9, -5)) t(-2, 9223372036854775808, -5, 100, (98, 99, -5)) t(-2, 9223372036854775808, -5, 2147483647, (2147483645, 2147483646, -5)) t(-2, 9223372036854775808, -5, 9223372036854775808, (9223372036854775806, 9223372036854775807, -5)) t(-2, 9223372036854775808, -3, 0, (-1, -1, -3)) t(-2, 9223372036854775808, -3, 1, (-1, 0, -3)) t(-2, 9223372036854775808, -3, 5, (3, 4, -3)) t(-2, 9223372036854775808, -3, 10, (8, 9, -3)) t(-2, 9223372036854775808, 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t(2147483647, 2147483647, None, 5, (5, 5, 1)) t(2147483647, 2147483647, None, 10, (10, 10, 1)) t(2147483647, 2147483647, None, 100, (100, 100, 1)) t(2147483647, 2147483647, None, 2147483647, (2147483647, 2147483647, 1)) t(2147483647, 2147483647, None, 9223372036854775808, (2147483647, 2147483647, 1)) t(2147483647, 2147483647, -5, 0, (-1, -1, -5)) t(2147483647, 2147483647, -5, 1, (0, 0, -5)) t(2147483647, 2147483647, -5, 5, (4, 4, -5)) t(2147483647, 2147483647, -5, 10, (9, 9, -5)) t(2147483647, 2147483647, -5, 100, (99, 99, -5)) t(2147483647, 2147483647, -5, 2147483647, (2147483646, 2147483646, -5)) t(2147483647, 2147483647, -5, 9223372036854775808, (2147483647, 2147483647, -5)) t(2147483647, 2147483647, -3, 0, (-1, -1, -3)) t(2147483647, 2147483647, -3, 1, (0, 0, -3)) t(2147483647, 2147483647, -3, 5, (4, 4, -3)) t(2147483647, 2147483647, -3, 10, (9, 9, -3)) t(2147483647, 2147483647, -3, 100, (99, 99, -3)) t(2147483647, 2147483647, -3, 2147483647, (2147483646, 2147483646, -3)) t(2147483647, 2147483647, -3, 9223372036854775808, (2147483647, 2147483647, -3)) t(2147483647, 2147483647, -1, 0, (-1, -1, -1)) t(2147483647, 2147483647, -1, 1, (0, 0, -1)) t(2147483647, 2147483647, -1, 5, (4, 4, -1)) t(2147483647, 2147483647, -1, 10, (9, 9, -1)) t(2147483647, 2147483647, -1, 100, (99, 99, -1)) t(2147483647, 2147483647, -1, 2147483647, (2147483646, 2147483646, -1)) t(2147483647, 2147483647, -1, 9223372036854775808, (2147483647, 2147483647, -1)) t(2147483647, 2147483647, 1, 0, (0, 0, 1)) t(2147483647, 2147483647, 1, 1, (1, 1, 1)) t(2147483647, 2147483647, 1, 5, (5, 5, 1)) t(2147483647, 2147483647, 1, 10, (10, 10, 1)) t(2147483647, 2147483647, 1, 100, (100, 100, 1)) t(2147483647, 2147483647, 1, 2147483647, (2147483647, 2147483647, 1)) t(2147483647, 2147483647, 1, 9223372036854775808, (2147483647, 2147483647, 1)) t(2147483647, 2147483647, 5, 0, (0, 0, 5)) t(2147483647, 2147483647, 5, 1, (1, 1, 5)) t(2147483647, 2147483647, 5, 5, (5, 5, 5)) t(2147483647, 2147483647, 5, 10, (10, 10, 5)) t(2147483647, 2147483647, 5, 100, (100, 100, 5)) t(2147483647, 2147483647, 5, 2147483647, (2147483647, 2147483647, 5)) t(2147483647, 2147483647, 5, 9223372036854775808, (2147483647, 2147483647, 5)) t(2147483647, 2147483647, 20, 0, (0, 0, 20)) t(2147483647, 2147483647, 20, 1, (1, 1, 20)) t(2147483647, 2147483647, 20, 5, (5, 5, 20)) t(2147483647, 2147483647, 20, 10, (10, 10, 20)) t(2147483647, 2147483647, 20, 100, (100, 100, 20)) t(2147483647, 2147483647, 20, 2147483647, (2147483647, 2147483647, 20)) t(2147483647, 2147483647, 20, 9223372036854775808, (2147483647, 2147483647, 20)) t(2147483647, 2147483647, 2147483647, 0, (0, 0, 2147483647)) t(2147483647, 2147483647, 2147483647, 1, (1, 1, 2147483647)) t(2147483647, 2147483647, 2147483647, 5, (5, 5, 2147483647)) t(2147483647, 2147483647, 2147483647, 10, (10, 10, 2147483647)) t(2147483647, 2147483647, 2147483647, 100, (100, 100, 2147483647)) t(2147483647, 2147483647, 2147483647, 2147483647, (2147483647, 2147483647, 2147483647)) t(2147483647, 2147483647, 2147483647, 9223372036854775808, (2147483647, 2147483647, 2147483647)) t(2147483647, 2147483647, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(2147483647, 2147483647, 9223372036854775808, 1, (1, 1, 9223372036854775808)) t(2147483647, 2147483647, 9223372036854775808, 5, (5, 5, 9223372036854775808)) t(2147483647, 2147483647, 9223372036854775808, 10, (10, 10, 9223372036854775808)) t(2147483647, 2147483647, 9223372036854775808, 100, (100, 100, 9223372036854775808)) t(2147483647, 2147483647, 9223372036854775808, 2147483647, (2147483647, 2147483647, 9223372036854775808)) t(2147483647, 2147483647, 9223372036854775808, 9223372036854775808, (2147483647, 2147483647, 9223372036854775808)) t(2147483647, 9223372036854775808, None, 0, (0, 0, 1)) t(2147483647, 9223372036854775808, None, 1, (1, 1, 1)) t(2147483647, 9223372036854775808, None, 5, (5, 5, 1)) t(2147483647, 9223372036854775808, None, 10, (10, 10, 1)) t(2147483647, 9223372036854775808, None, 100, (100, 100, 1)) t(2147483647, 9223372036854775808, None, 2147483647, (2147483647, 2147483647, 1)) t(2147483647, 9223372036854775808, None, 9223372036854775808, (2147483647, 9223372036854775808, 1)) t(2147483647, 9223372036854775808, -5, 0, (-1, -1, -5)) t(2147483647, 9223372036854775808, -5, 1, (0, 0, -5)) t(2147483647, 9223372036854775808, -5, 5, (4, 4, -5)) t(2147483647, 9223372036854775808, -5, 10, (9, 9, -5)) t(2147483647, 9223372036854775808, -5, 100, (99, 99, -5)) t(2147483647, 9223372036854775808, -5, 2147483647, (2147483646, 2147483646, -5)) t(2147483647, 9223372036854775808, -5, 9223372036854775808, (2147483647, 9223372036854775807, -5)) t(2147483647, 9223372036854775808, -3, 0, (-1, -1, -3)) t(2147483647, 9223372036854775808, -3, 1, (0, 0, -3)) t(2147483647, 9223372036854775808, -3, 5, (4, 4, -3)) t(2147483647, 9223372036854775808, -3, 10, (9, 9, -3)) t(2147483647, 9223372036854775808, -3, 100, (99, 99, -3)) t(2147483647, 9223372036854775808, -3, 2147483647, (2147483646, 2147483646, 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9223372036854775808, (9223372036854775807, -1, -5)) t(9223372036854775808, None, -3, 0, (-1, -1, -3)) t(9223372036854775808, None, -3, 1, (0, -1, -3)) t(9223372036854775808, None, -3, 5, (4, -1, -3)) t(9223372036854775808, None, -3, 10, (9, -1, -3)) t(9223372036854775808, None, -3, 100, (99, -1, -3)) t(9223372036854775808, None, -3, 2147483647, (2147483646, -1, -3)) t(9223372036854775808, None, -3, 9223372036854775808, (9223372036854775807, -1, -3)) t(9223372036854775808, None, -1, 0, (-1, -1, -1)) t(9223372036854775808, None, -1, 1, (0, -1, -1)) t(9223372036854775808, None, -1, 5, (4, -1, -1)) t(9223372036854775808, None, -1, 10, (9, -1, -1)) t(9223372036854775808, None, -1, 100, (99, -1, -1)) t(9223372036854775808, None, -1, 2147483647, (2147483646, -1, -1)) t(9223372036854775808, None, -1, 9223372036854775808, (9223372036854775807, -1, -1)) t(9223372036854775808, None, 1, 0, (0, 0, 1)) t(9223372036854775808, None, 1, 1, (1, 1, 1)) t(9223372036854775808, None, 1, 5, (5, 5, 1)) 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2147483647, 2147483647, 100, (100, 100, 2147483647)) t(9223372036854775808, 2147483647, 2147483647, 2147483647, (2147483647, 2147483647, 2147483647)) t(9223372036854775808, 2147483647, 2147483647, 9223372036854775808, (9223372036854775808, 2147483647, 2147483647)) t(9223372036854775808, 2147483647, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(9223372036854775808, 2147483647, 9223372036854775808, 1, (1, 1, 9223372036854775808)) t(9223372036854775808, 2147483647, 9223372036854775808, 5, (5, 5, 9223372036854775808)) t(9223372036854775808, 2147483647, 9223372036854775808, 10, (10, 10, 9223372036854775808)) t(9223372036854775808, 2147483647, 9223372036854775808, 100, (100, 100, 9223372036854775808)) t(9223372036854775808, 2147483647, 9223372036854775808, 2147483647, (2147483647, 2147483647, 9223372036854775808)) t(9223372036854775808, 2147483647, 9223372036854775808, 9223372036854775808, (9223372036854775808, 2147483647, 9223372036854775808)) t(9223372036854775808, 9223372036854775808, None, 0, (0, 0, 1)) t(9223372036854775808, 9223372036854775808, None, 1, (1, 1, 1)) t(9223372036854775808, 9223372036854775808, None, 5, (5, 5, 1)) t(9223372036854775808, 9223372036854775808, None, 10, (10, 10, 1)) t(9223372036854775808, 9223372036854775808, None, 100, (100, 100, 1)) t(9223372036854775808, 9223372036854775808, None, 2147483647, (2147483647, 2147483647, 1)) t(9223372036854775808, 9223372036854775808, None, 9223372036854775808, (9223372036854775808, 9223372036854775808, 1)) t(9223372036854775808, 9223372036854775808, -5, 0, (-1, -1, -5)) t(9223372036854775808, 9223372036854775808, -5, 1, (0, 0, -5)) t(9223372036854775808, 9223372036854775808, -5, 5, (4, 4, -5)) t(9223372036854775808, 9223372036854775808, -5, 10, (9, 9, -5)) t(9223372036854775808, 9223372036854775808, -5, 100, (99, 99, -5)) t(9223372036854775808, 9223372036854775808, -5, 2147483647, (2147483646, 2147483646, -5)) t(9223372036854775808, 9223372036854775808, -5, 9223372036854775808, (9223372036854775807, 9223372036854775807, -5)) t(9223372036854775808, 9223372036854775808, -3, 0, (-1, -1, -3)) t(9223372036854775808, 9223372036854775808, -3, 1, (0, 0, -3)) t(9223372036854775808, 9223372036854775808, -3, 5, (4, 4, -3)) t(9223372036854775808, 9223372036854775808, -3, 10, (9, 9, -3)) t(9223372036854775808, 9223372036854775808, -3, 100, (99, 99, -3)) t(9223372036854775808, 9223372036854775808, -3, 2147483647, (2147483646, 2147483646, -3)) t(9223372036854775808, 9223372036854775808, -3, 9223372036854775808, (9223372036854775807, 9223372036854775807, -3)) t(9223372036854775808, 9223372036854775808, -1, 0, (-1, -1, -1)) t(9223372036854775808, 9223372036854775808, -1, 1, (0, 0, -1)) t(9223372036854775808, 9223372036854775808, -1, 5, (4, 4, -1)) t(9223372036854775808, 9223372036854775808, -1, 10, (9, 9, -1)) t(9223372036854775808, 9223372036854775808, -1, 100, (99, 99, -1)) t(9223372036854775808, 9223372036854775808, -1, 2147483647, (2147483646, 2147483646, -1)) t(9223372036854775808, 9223372036854775808, -1, 9223372036854775808, (9223372036854775807, 9223372036854775807, -1)) t(9223372036854775808, 9223372036854775808, 1, 0, (0, 0, 1)) t(9223372036854775808, 9223372036854775808, 1, 1, (1, 1, 1)) t(9223372036854775808, 9223372036854775808, 1, 5, (5, 5, 1)) t(9223372036854775808, 9223372036854775808, 1, 10, (10, 10, 1)) t(9223372036854775808, 9223372036854775808, 1, 100, (100, 100, 1)) t(9223372036854775808, 9223372036854775808, 1, 2147483647, (2147483647, 2147483647, 1)) t(9223372036854775808, 9223372036854775808, 1, 9223372036854775808, (9223372036854775808, 9223372036854775808, 1)) t(9223372036854775808, 9223372036854775808, 5, 0, (0, 0, 5)) t(9223372036854775808, 9223372036854775808, 5, 1, (1, 1, 5)) t(9223372036854775808, 9223372036854775808, 5, 5, (5, 5, 5)) t(9223372036854775808, 9223372036854775808, 5, 10, (10, 10, 5)) t(9223372036854775808, 9223372036854775808, 5, 100, (100, 100, 5)) t(9223372036854775808, 9223372036854775808, 5, 2147483647, (2147483647, 2147483647, 5)) t(9223372036854775808, 9223372036854775808, 5, 9223372036854775808, (9223372036854775808, 9223372036854775808, 5)) t(9223372036854775808, 9223372036854775808, 20, 0, (0, 0, 20)) t(9223372036854775808, 9223372036854775808, 20, 1, (1, 1, 20)) t(9223372036854775808, 9223372036854775808, 20, 5, (5, 5, 20)) t(9223372036854775808, 9223372036854775808, 20, 10, (10, 10, 20)) t(9223372036854775808, 9223372036854775808, 20, 100, (100, 100, 20)) t(9223372036854775808, 9223372036854775808, 20, 2147483647, (2147483647, 2147483647, 20)) t(9223372036854775808, 9223372036854775808, 20, 9223372036854775808, (9223372036854775808, 9223372036854775808, 20)) t(9223372036854775808, 9223372036854775808, 2147483647, 0, (0, 0, 2147483647)) t(9223372036854775808, 9223372036854775808, 2147483647, 1, (1, 1, 2147483647)) t(9223372036854775808, 9223372036854775808, 2147483647, 5, (5, 5, 2147483647)) t(9223372036854775808, 9223372036854775808, 2147483647, 10, (10, 10, 2147483647)) t(9223372036854775808, 9223372036854775808, 2147483647, 100, (100, 100, 2147483647)) t(9223372036854775808, 9223372036854775808, 2147483647, 2147483647, (2147483647, 2147483647, 2147483647)) t(9223372036854775808, 9223372036854775808, 2147483647, 9223372036854775808, (9223372036854775808, 9223372036854775808, 2147483647)) t(9223372036854775808, 9223372036854775808, 9223372036854775808, 0, (0, 0, 9223372036854775808)) t(9223372036854775808, 9223372036854775808, 9223372036854775808, 1, (1, 1, 9223372036854775808)) t(9223372036854775808, 9223372036854775808, 9223372036854775808, 5, (5, 5, 9223372036854775808)) t(9223372036854775808, 9223372036854775808, 9223372036854775808, 10, (10, 10, 9223372036854775808)) t(9223372036854775808, 9223372036854775808, 9223372036854775808, 100, (100, 100, 9223372036854775808)) t(9223372036854775808, 9223372036854775808, 9223372036854775808, 2147483647, (2147483647, 2147483647, 9223372036854775808)) t(9223372036854775808, 9223372036854775808, 9223372036854775808, 9223372036854775808, (9223372036854775808, 9223372036854775808, 9223372036854775808))

51.904399

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0.571341

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265,491

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0

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5,114

155

51.914548

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0.000196

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0.000392

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0

null

0

1

0

1

0

1

0

null

0

5

152e97d1307d074dead11680c6d7467fec700b22

44

py

Python

tests/__init__.py

abdulfahad66/result-service-gui

214342dd6d00f1173bfe90f8429c7d6c9947783b

[ "Apache-2.0" ]

1

2021-02-08T09:36:08.000Z

tests/__init__.py

abdulfahad66/result-service-gui

214342dd6d00f1173bfe90f8429c7d6c9947783b

[ "Apache-2.0" ]

76

2021-07-28T22:36:16.000Z

2022-03-23T22:52:54.000Z

tests/__init__.py

langrenn-sprint/sprint-webserver

065a96d102a6658e5422ea6a0be5abde4b6558e1

[ "Apache-2.0" ]

null

"""Test package. Modules: conftest """

7.333333

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0.590909

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44

6.5

1

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44

5

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null

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null

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null

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null

0

1

0

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0

null

0

1

0

5

155add187b27cdb39c94840f79b7256e718f024d

290

py

Python

tests/test_stack_trace_c.py

jamespic/profil-o-matic

9474c6bfaadd081c367ec774a9a3948baf5fa5f4

[ "MIT" ]

null

tests/test_stack_trace_c.py

jamespic/profil-o-matic

9474c6bfaadd081c367ec774a9a3948baf5fa5f4

[ "MIT" ]

null

tests/test_stack_trace_c.py

jamespic/profil-o-matic

9474c6bfaadd081c367ec774a9a3948baf5fa5f4

[ "MIT" ]

null

import unittest from .base_stack_trace_test import BaseStackTraceTest try: from profilomatic._stack_trace import generate_stack_trace class CStackTraceTest(BaseStackTraceTest, unittest.TestCase): stack_trace_fn = generate_stack_trace.__call__ except ImportError: pass

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290

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1

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false

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null

0

1

0

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0

5

1571da32dbdbe9ca7b65a67af3df29e2267a3d1b

50

py

Python

src/StatusIndia/__init__.py

sudharshanakshay/CovidStatusIndia

86e7a85c445caa00937e9f923b48d07d3c8cf529

[ "MIT" ]

null

src/StatusIndia/__init__.py

sudharshanakshay/CovidStatusIndia

86e7a85c445caa00937e9f923b48d07d3c8cf529

[ "MIT" ]

null

src/StatusIndia/__init__.py

sudharshanakshay/CovidStatusIndia

86e7a85c445caa00937e9f923b48d07d3c8cf529

[ "MIT" ]

null

from src.StatusIndia.main import IndiaWebScrapper

25

49

0.88

6

50

7.333333

1

0

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50

1

50

0.956522

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null

0

1

0

1

0

1

0

5

ec7cd1b9556121004a0227a69cd3f1e70df3e2b6

111

py

Python

datatype12.py

praveenpmin/Python

513fcde7430b03a187e2c7e58302b88645388eed

[ "MIT" ]

null

datatype12.py

praveenpmin/Python

513fcde7430b03a187e2c7e58302b88645388eed

[ "MIT" ]

null

datatype12.py

praveenpmin/Python

513fcde7430b03a187e2c7e58302b88645388eed

[ "MIT" ]

null

# Declaring a list L = [1, "a" , "string" , 1+2] print (L) L.append(6) print (L) L.pop() print (L) print (L[1])

13.875

29

0.558559

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111

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111

8

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false

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1

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null

1

0

1

0

null

0

1

0

5

ec91ded76df9d568ea1b7532fe448ad3f77879f1

65

py

Python

lieu_de_travail/views.py

ghassen3699/Site_web_Projet

20eca8ded72f4e798862dd5440000afe04892092

[ "Apache-2.0" ]

null

lieu_de_travail/views.py

ghassen3699/Site_web_Projet

20eca8ded72f4e798862dd5440000afe04892092

[ "Apache-2.0" ]

null

lieu_de_travail/views.py

ghassen3699/Site_web_Projet

20eca8ded72f4e798862dd5440000afe04892092

[ "Apache-2.0" ]

null

from django.shortcuts import render from . import forms, models

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5.777778

0.777778

0

0.153846

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3

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true

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null

0

1

0

1

0

1

0

5

ecbe30d2df03649b92d43e6e53516540265923cd

19,792

py

Python

src/modules/capsule.py

zhengzx-nlp/dynamic-nmt

65b321898c5020942d76b85701123fd272e3ae9e

[ "MIT" ]

7

2019-08-29T01:49:49.000Z

2022-02-25T05:53:13.000Z

src/modules/capsule.py

zhengzx-nlp/dynamic-nmt

65b321898c5020942d76b85701123fd272e3ae9e

[ "MIT" ]

1

2019-11-07T03:14:18.000Z

2019-11-07T03:27:08.000Z

src/modules/capsule.py

zhengzx-nlp/dynamic-nmt

65b321898c5020942d76b85701123fd272e3ae9e

[ "MIT" ]

null

# -*- coding: UTF-8 -*- # Copyright 2018, Natural Language Processing Group, Nanjing University, # # Author: Zheng Zaixiang # Contact: zhengzx@nlp.nju.edu.cn # or zhengzx.142857@gmail.com # from __future__ import absolute_import from __future__ import division from __future__ import print_function import math import torch import torch.nn as nn import torch.nn.functional as F from src.utils.logging import INFO, WARN def EM_routing_by_agreement(actn_in, votes_in, votes_in_mask, beta_u, beta_a, lbd, iterations): """ EM routing-by-agreement Args: actn_in (torch.Tensor): Activations of inputs (like bottom capsules). [batch, num_in_caps] votes_in (torch.Tensor): Voter sequence of transformed inputs. [batch, length, num_in_caps, num_out_caps, dim_out_caps] votes_in_mask (torch.Tensor): mask for input [batch, length, num_in_caps, num_out_caps] beta_u (torch.Tensor): [num_out_caps] beta_a (torch.Tensor): [num_out_caps] lbd (float): lambda iterations (int): Routing iteration Returns: (torch.Tensor): Upper capsules. [batch, length, num_out_caps, dim_out_caps] (torch.Tensor): Last routing weights. [batch, length, num_in_caps, num_out_caps] """ ln_2pi = math.log(2 * math.pi) eps = 1e-8 def _e_step(_mu, _sigma_sq, _actn_out): """ Args: _mu (torch.Tensor): Mean. [batch, length, num_out_caps, dim_out_caps] _sigma_sq (torch.Tensor): Squared sigma. [batch, length, num_out_caps, dim_out_caps] _actn_out: Activation of output capsule. [batch, length, num_out_caps] Returns: (torch.Tensor): Routing weight. [batch, length, num_in_caps, num_out_caps] """ _mu = _mu.unsqueeze(2) _sigma_sq = _sigma_sq.unsqueeze(2) + eps # [batch, length, num_in_caps, num_out_caps, dim_out_caps] _log_p_j = -1. * (votes_in - _mu) ** 2 / (2 * _sigma_sq) \ - torch.log(_sigma_sq.sqrt()) \ - 0.5 * ln_2pi # [batch, length, num_in_caps, num_out_caps] _log_ap = _log_p_j.sum(-1) + _actn_out[:, :, None, :].log() if votes_in_mask is not None: _log_ap = _log_ap.masked_fill(votes_in_mask, -1e18) _r = F.softmax(_log_ap, dim=3) return _r def _m_step(_r): """ Args: _r (torch.Tensor): Routing weight. [batch, length, num_in_caps, num_out_caps] Returns: (torch.Tensor): Mean. [batch, length, num_out_caps, dim_out_caps] (torch.Tensor): Squared sigma. [batch, length, num_out_caps, dim_out_caps] (torch.Tensor): Activation of output capsule. [batch, length, num_out_caps, dim_out_caps] """ # [batch, length, num_in_caps, num_out_caps] _actn_r = actn_in[:, None, :, None] * _r _actn_r = _actn_r / (_actn_r.sum(3, keepdim=True) + eps) # [batch, length, num_out_caps] _actn_r_sum = _actn_r.sum(2) # [batch, length, num_in_caps, num_out_caps] _r1 = _actn_r / (_actn_r_sum.unsqueeze(2) + eps) # [batch, length, num_in_caps, num_out_caps, 1] _r1 = _r1.unsqueeze(-1) # [batch, length, num_out_caps, dim_out_caps] _mu = (_r1 * votes_in).sum(2) _sigma_sq = (_r1 * ((votes_in - _mu.unsqueeze(2))**2)).sum(2) # [batch, length, num_out_caps, dim_out_caps] _cost = beta_u[None, None, :, None] + \ _sigma_sq.add(eps).sqrt().log() * _actn_r_sum.unsqueeze(-1) # [batch, length, num_out_caps] _actn_out = F.sigmoid(lbd * (beta_a[None, None, :] - _cost.sum(-1))) return _mu, _sigma_sq, _actn_out # Initialize routing weights as zeros batch, length, num_in_caps, num_out_caps, dim_out_caps = votes_in.size() r = actn_in.new_full( [batch, length, num_in_caps, num_out_caps], 1 / num_out_caps ) # routing-by-agreement for i in range(iterations): mu, sigma_sq, actn_out = _m_step(r) if i < iterations - 1: r = _e_step(mu, sigma_sq, actn_out) return mu, r class CapsuleLayer(nn.Module): def __init__(self, num_out_caps, num_in_caps, dim_in_caps, dim_out_caps, num_iterations=2, share_route_weights_for_in_caps=False): super(CapsuleLayer, self).__init__() self.num_out_caps = num_out_caps self.num_iterations = num_iterations assert num_iterations > 1, "num_iterations must at least be 1." self.share_route_weights_for_in_caps = share_route_weights_for_in_caps if share_route_weights_for_in_caps: WARN("{}: Argument 'num_in_caps' will be ignored.".format(self.__class__)) self.route_weights = nn.Parameter(0.01 * torch.randn(num_out_caps, dim_in_caps, dim_out_caps)) else: self.route_weights = nn.Parameter(0.01 * torch.randn(num_in_caps, num_out_caps, dim_in_caps, dim_out_caps)) def __repr__(self): return super().__repr__() + "\n(routing_weights): {}".format(self.route_weights.size()) @staticmethod def squash(tensor, dim=-1, eps=1e-8): squared_norm = (tensor ** 2).sum(dim=dim, keepdim=True) scale = squared_norm / (1 + squared_norm) norm = torch.sqrt(squared_norm) + eps return scale * tensor / norm def forward(self, inputs_u, inputs_mask): """ Args: inputs_u: Tensor. [batch_size, num_in_caps, dim_in_caps] inputs_mask: Tensor. [batch_size, num_in_caps] Returns: Tensor. [batch_size, num_out_caps, dim_out_caps] """ batch_size, num_in_caps, dim_in_caps = inputs_u.size() # Compute u_hat: [batch_size, num_in_caps, num_out_caps, dim_out_caps] if self.share_route_weights_for_in_caps: # priors_u_hat = (inputs_u[:, :, None, None, :] @ self.route_weights[None, None, :, :, :]).squeeze(-2) inputs_u_r = inputs_u.view(batch_size * num_in_caps, dim_in_caps) route_weight_r = self.route_weights.transpose(0, 1).reshape(dim_in_caps, -1) priors_u_hat = inputs_u_r @ route_weight_r priors_u_hat = priors_u_hat.view(batch_size, num_in_caps, self.num_out_caps, -1) else: priors_u_hat = (inputs_u[:, :, None, None, :] @ self.route_weights[None, :, :, :, :]).squeeze(-2) # Initialize logits # logits_b: [batch_size, num_in_caps, num_out_caps] logits_b = inputs_u.new_zeros(batch_size, num_in_caps, self.num_out_caps) # Routing for i in range(self.num_iterations): # probs: [batch_size, num_in_caps, num_out_caps] if inputs_mask is not None: logits_b = logits_b + inputs_mask.unsqueeze(-1) * -1e18 probs_c = F.softmax(logits_b, dim=-1) # outputs_v: [batch_size, num_out_caps, dim_out_caps] outputs_v = self.squash((probs_c.unsqueeze(-1) * priors_u_hat).sum(dim=1)) if i != self.num_iterations - 1: # delta_logits: [batch_size, num_in_caps, num_out_caps] delta_logits = (priors_u_hat * outputs_v.unsqueeze(1)).sum(dim=-1) logits_b = logits_b + delta_logits # outputs_v: [batch_size, num_out_caps, dim_out_caps] return outputs_v class ContextualCapsuleLayer(CapsuleLayer): def __init__(self, num_out_caps, num_in_caps, dim_in_caps, dim_out_caps, dim_context=None, num_iterations=2, share_route_weights_for_in_caps=False): super().__init__(num_out_caps, num_in_caps, dim_in_caps, dim_out_caps, num_iterations, share_route_weights_for_in_caps) self.linear_u_hat = nn.Linear(dim_out_caps, dim_out_caps) self.linear_v = nn.Linear(dim_out_caps, dim_out_caps) self.linear_delta = nn.Linear(dim_out_caps, 1, False) self.dim_out_caps = dim_out_caps self.contextual = dim_context is not None if self.contextual: self.linear_c = nn.Linear(dim_context, dim_out_caps, bias=False) self.reset_parameters() def reset_parameters(self): nn.init.normal_(self.linear_u_hat.weight, 0, 0.001) nn.init.normal_(self.linear_v.weight, 0, 0.001) nn.init.normal_(self.linear_delta.weight, 0, 0.001) if self.contextual: nn.init.normal_(self.linear_c.weight, 0, 0.001) def compute_delta(self, priors_u_hat, outputs_v, contexts=None): """ Args: priors_u_hat: [batch_size, num_in_caps, num_out_caps, dim_out_caps] outputs_v: [batch_size, num_out_caps, dim_out_caps] contexts: [batch_size, dim_context] Returns: Tensor. [batch_size, num_in_caps, num_out_caps] """ # [batch_size, num_in_caps, num_out_caps, dim_out_caps] u = priors_u_hat v = outputs_v[:, None, :, :] # [batch_size, num_in_caps, num_out_caps, dim_out_caps] delta = self.linear_u_hat(u) + self.linear_v(v) if self.contextual: c = contexts[:, None, None, :] delta = delta + self.linear_c(c) delta = F.tanh(delta) # [batch_size, num_in_caps, num_out_caps] delta = self.linear_delta(delta).squeeze(-1) # [batch_size, num_in_caps, num_out_caps] delta = F.tanh(delta) return delta * (self.dim_out_caps ** -0.5) def compute_delta_sequence(self, priors_u_hat, outputs_v, contexts=None): """ Args: priors_u_hat: [batch_size, num_in_caps, num_out_caps, dim_out_caps] outputs_v: [batch_size, length, num_out_caps, dim_out_caps] contexts: [batch_size, length, dim_context] Returns: Tensor. [batch_size, length, num_in_caps, num_out_caps] """ # [batch_size, length, num_in_caps, num_out_caps, dim_out_caps] u = priors_u_hat[:, None, :, :, :] v = outputs_v[:, :, None, :, :] # [batch_size, length, num_in_caps, num_out_caps, dim_out_caps] delta = self.linear_u_hat(u) + self.linear_v(v) # [batch, length, 1, 1, dim_context] c = contexts[:, :, None, None, :] # [batch, length, num_in_caps, num_out_caps, dim_out_caps] delta = delta + self.linear_c(c) delta = F.tanh(delta) # [batch_size, length, num_in_caps, num_out_caps] delta = self.linear_delta(delta).squeeze(-1) delta = F.tanh(delta) return delta * (self.dim_out_caps ** -0.5) def forward(self, inputs_u, inputs_mask, context=None): """ Args: inputs_u: Tensor. [batch_size, num_in_caps, dim_in_caps] inputs_mask: Tensor. [batch_size, num_in_caps] context: [batch_size, dim_context] Returns: Tensor. [batch_size, num_out_caps, dim_out_caps] """ batch_size, num_in_caps, dim_in_caps = inputs_u.size() # Compute u_hat: [batch_size, num_in_caps, num_out_caps, dim_out_caps] if self.share_route_weights_for_in_caps: # priors_u_hat = (inputs_u[:, :, None, None, :] @ self.route_weights[None, None, :, :, :]).squeeze(-2) inputs_u_r = inputs_u.view(batch_size * num_in_caps, dim_in_caps) route_weight_r = self.route_weights.transpose(0, 1).reshape(dim_in_caps, -1) priors_u_hat = inputs_u_r @ route_weight_r priors_u_hat = priors_u_hat.view(batch_size, num_in_caps, self.num_out_caps, -1) else: priors_u_hat = (inputs_u[:, :, None, None, :] @ self.route_weights[None, :, :, :, :]).squeeze(-2) # Initialize logits # logits_b: [batch_size, num_in_caps, num_out_caps] logits_b = inputs_u.new_zeros(batch_size, num_in_caps, self.num_out_caps) # Routing for i in range(self.num_iterations): # probs: [batch_size, num_in_caps, num_out_caps] if inputs_mask is not None: logits_b = logits_b + inputs_mask.unsqueeze(-1) * -1e18 probs_c = F.softmax(logits_b, dim=-1) # outputs_v: [batch_size, num_out_caps, dim_out_caps] outputs_v = self.squash((probs_c.unsqueeze(-1) * priors_u_hat).sum(dim=1)) if i != self.num_iterations - 1: # delta_logits: [batch_size, num_in_caps, num_out_caps] delta_logits = self.compute_delta(priors_u_hat, outputs_v, context) logits_b = logits_b + delta_logits # outputs_v: [batch_size, num_out_caps, dim_out_caps] return outputs_v, probs_c def forward_sequence(self, inputs_u, inputs_mask, context_sequence=None, cache=None): """ Args: inputs_u (torch.Tensor). [batch_size, num_in_caps, dim_in_caps] inputs_mask (torch.Tensor). [batch_size, num_in_caps] context_sequence (torch.Tensor) : [batch_size, length, dim_context] Returns: Tensor. [batch_size, length, num_out_caps, dim_out_caps] """ batch_size, num_in_caps, dim_in_caps = inputs_u.size() length = context_sequence.size(1) # Compute u_hat: [batch_size, num_in_caps, num_out_caps, dim_out_caps] if cache is not None: priors_u_hat = cache else: priors_u_hat = self.compute_caches(inputs_u) # Initialize logits # logits_b: [batch_size, length, num_in_caps, num_out_caps] logits_b = inputs_u.new_zeros(batch_size, length, num_in_caps, self.num_out_caps) # [batch, 1, num_in_caps, 1] routing_mask = inputs_mask[:, None, :, None].expand_as(logits_b) # Routing for i in range(self.num_iterations): # probs: [batch_size, length, num_in_caps, num_out_caps] if inputs_mask is not None: logits_b = logits_b.masked_fill(routing_mask, -1e18) probs_c = F.softmax(logits_b, dim=-1) # # [batch, num_out_caps, length, # _interm = probs_c.permute([0, 3, 1, 2]) @ prior_u_hat.transpose(1, 2)) # outputs_v: [batch_size, length, num_out_caps, dim_out_caps] outputs_v = self.squash((probs_c.unsqueeze(-1) * priors_u_hat.unsqueeze(1)).sum(2)) if i != self.num_iterations - 1: # delta_logits: [batch_size, length, num_in_caps, num_out_caps] delta_logits = self.compute_delta_sequence( priors_u_hat, outputs_v, context_sequence ) logits_b = logits_b + delta_logits # outputs_v: [batch_size, length, num_out_caps, dim_out_caps] return outputs_v, probs_c def compute_caches(self, inputs_u): batch_size, num_in_caps, dim_in_caps = inputs_u.size() if self.share_route_weights_for_in_caps: inputs_u_r = inputs_u.view(batch_size * num_in_caps, dim_in_caps) route_weight_r = self.route_weights.transpose(0, 1).reshape(dim_in_caps, -1) priors_u_hat = inputs_u_r @ route_weight_r priors_u_hat = priors_u_hat.view(batch_size, num_in_caps, self.num_out_caps, -1) else: priors_u_hat = (inputs_u[:, :, None, None, :] @ self.route_weights[None, :, :, :, :]).squeeze(-2) return priors_u_hat class EMContextualCapsuleLayer(nn.Module): def __init__(self, num_out_caps, num_in_caps, dim_in_caps, dim_out_caps, dim_context, lbd=1e-03, num_iterations=2, share_route_weights_for_in_caps=False): super(EMContextualCapsuleLayer, self).__init__() self.num_out_caps = num_out_caps self.num_iterations = num_iterations assert num_iterations > 1, "num_iterations must at least be 1." self.share_route_weights_for_in_caps = share_route_weights_for_in_caps if share_route_weights_for_in_caps: WARN("{}: Argument 'num_in_caps' will be ignored.".format(self.__class__)) self.route_weights = nn.Parameter( 0.01 * torch.randn(num_out_caps, dim_in_caps, dim_out_caps) ) else: self.route_weights = nn.Parameter( 0.01 * torch.randn(num_in_caps, num_out_caps, dim_in_caps, dim_out_caps) ) self.linear_u_hat = nn.Linear(dim_out_caps, dim_out_caps) self.linear_c = nn.Linear(dim_context, dim_out_caps) self.linear_vote = nn.Linear(dim_out_caps, dim_out_caps) self.linear_actn = nn.Linear(dim_in_caps, 1) self.lbd = lbd self.beta_u = nn.Parameter(torch.zeros(num_out_caps)) self.beta_a = nn.Parameter(torch.zeros(num_out_caps)) self.reset_parameters() def __repr__(self): return super().__repr__() + "\n(routing_weights): {}".format(self.route_weights.size()) def reset_parameters(self): nn.init.normal_(self.linear_u_hat.weight, 0, 0.001) nn.init.normal_(self.linear_vote.weight, 0, 0.001) nn.init.normal_(self.linear_c.weight, 0, 0.001) def compute_caches(self, inputs_u): """ Args: inputs_ud (torch.Tensor): [batch, num_in_caps, dim_in_caps] Returns: """ batch_size, num_in_caps, dim_in_caps = inputs_u.size() if self.share_route_weights_for_in_caps: inputs_u_r = inputs_u.view(batch_size * num_in_caps, dim_in_caps) route_weight_r = self.route_weights.transpose(0, 1).reshape(dim_in_caps, -1) priors_u_hat = inputs_u_r @ route_weight_r priors_u_hat = priors_u_hat.view(batch_size, num_in_caps, self.num_out_caps, -1) else: priors_u_hat = (inputs_u[:, :, None, None, :] @ self.route_weights[None, :, :, :, :]).squeeze(-2) actn = F.sigmoid(self.linear_actn(inputs_u)).squeeze(-1) # actn = inputs_u.new_ones([batch_size, num_in_caps]) return priors_u_hat, actn def forward_sequence(self, inputs_u, inputs_mask, context_sequence=None, cache=None): """ Args: inputs_u (torch.Tensor). [batch_size, num_in_caps, dim_in_caps] inputs_mask (torch.Tensor). [batch_size, num_in_caps] context_sequence (torch.Tensor) : [batch_size, length, dim_context] Returns: Tensor. [batch_size, length, num_out_caps, dim_out_caps] """ batch_size, num_in_caps, dim_in_caps = inputs_u.size() length = context_sequence.size(1) # Compute u_hat: [batch_size, num_in_caps, num_out_caps, dim_out_caps] if cache is not None: (priors_u_hat, actn_in) = cache else: priors_u_hat, actn_in = self.compute_caches(inputs_u) # Routing # [batch_size, length, num_in_caps, num_out_caps, dim_out_caps] u = self.linear_u_hat(priors_u_hat[:, None, :, :, :]) c = self.linear_c(context_sequence[:, :, None, None, :]) # [batch_size, length, num_in_caps, num_out_caps, dim_out_caps] vote_in = self.linear_vote(F.tanh(u + c)) # vote_in = F.tanh(u + c) # [batch, 1, num_in_caps, 1] routing_mask = inputs_mask[:, None, :, None].expand( batch_size, length, num_in_caps, self.num_out_caps ) mu, routing_weights = EM_routing_by_agreement( actn_in, vote_in, routing_mask, self.beta_u, self.beta_a, self.lbd, self.num_iterations ) # outputs_v: [batch_size, length, num_out_caps, dim_out_caps] return mu, routing_weights

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ece58d7abdd9805c6dc4ca3d07d6388273c83b1b

70

py

Python

src/hub/dataload/sources/reactome/__init__.py

mlebeur/mygene.info

e71ca89c2b1c546c260101286ad5419503fd6653

[ "Apache-2.0" ]

78

2017-05-26T08:38:25.000Z

2022-02-25T08:55:31.000Z

src/hub/dataload/sources/reactome/__init__.py

mlebeur/mygene.info

e71ca89c2b1c546c260101286ad5419503fd6653

[ "Apache-2.0" ]

105

2017-05-18T21:57:13.000Z

2022-03-18T21:41:47.000Z

src/hub/dataload/sources/reactome/__init__.py

mlebeur/mygene.info

e71ca89c2b1c546c260101286ad5419503fd6653

[ "Apache-2.0" ]

19

2017-06-12T18:31:54.000Z

2021-11-10T00:04:43.000Z

from .dump import ReactomeDumper from .upload import ReactomeUploader

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01ca817d0411485377d1fce11f06b109032977e1

654

py

Python

serverctl_deployd/dependencies.py

delta/serverctl_daemon

3999539da01715affc8a3471d860294184756e6f

[ "MIT" ]

2

2021-09-18T15:30:33.000Z

2021-12-23T01:50:19.000Z

serverctl_deployd/dependencies.py

delta/serverctl_daemon

3999539da01715affc8a3471d860294184756e6f

[ "MIT" ]

54

2021-09-18T12:22:38.000Z

2022-03-30T13:25:17.000Z

serverctl_deployd/dependencies.py

delta/serverctl_deployd

3999539da01715affc8a3471d860294184756e6f

[ "MIT" ]

null

""" Miscellaneous dependencies for the API. """ from functools import lru_cache import docker from docker.client import DockerClient from serverctl_deployd.config import Settings async def check_authentication() -> None: """ TODO: To be implemented """ pass # pylint: disable=unnecessary-pass async def get_docker_client() -> DockerClient: """ Get the Docker client. """ return docker.from_env() # pragma: no cover @lru_cache() def get_settings() -> Settings: """ Return settings to be used as a dependency. This is only there so that it can be overridden for tests. """ return Settings()

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1

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1

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5

17148dab62a3243caffade138c3aa6f2be47fcbb

26,338

py

Python

validation/Correlation_Analysis.py

sdomanskyi/decneo

c3b78d7cb24fbecde317850ea5068394029a7d03

[ "MIT" ]

null

validation/Correlation_Analysis.py

sdomanskyi/decneo

c3b78d7cb24fbecde317850ea5068394029a7d03

[ "MIT" ]

null

validation/Correlation_Analysis.py

sdomanskyi/decneo

c3b78d7cb24fbecde317850ea5068394029a7d03

[ "MIT" ]

null

import sys sys.path.append(".") sys.path.append("../scRegulation/") sys.path.append("/mnt/home/paterno1/anaconda3/lib/python3.7/site-packages/") #sys.path.append("/mnt/home/paterno1/anaconda3/lib/python3.7/site-packages/tables") #sys.path.append("../bin") import pandas as pd import os import numpy as np import PanglaoDBannotation as pldba import sergii_io import re from scipy import stats from scipy.spatial.distance import cdist import random import time def get_all_corr (annot_file, out_excel, out_dir, annot_dir, count_dir, gene_list1 = None, gene_list2 = None, keyword= None, column = "Cell type annotation", index_column = False, method = "pearson", m2h_file = None, log_scale = True, ignore_error = False, debug = False): #Readd in annotation data annot_df = pd.read_excel(annot_file, index_col = [0,1,2]) #get location of count files count_dir = os.path.join(count_dir,"var","www","html","SRA","SRA.final") #get annotations related to keywords if keyword != None: if type(keyword) == str: if index_column: annot_df = annot_df.loc[ annot_df.index.get_level_values(column) == keyword] else: annot_df = annot_df.loc[annot_df[column] == keyword] else: #keyword = re.compile("|".join(keyword) if index_column: annot_df = annot_df.loc[ annot_df.index.get_level_values(column).isin(keyword)] else: annot_df = annot_df.loc[annot_df[column].isin(keyword)] corr_dict = {} annot_df.to_csv("../Annot_run.csv") #read in mouse to human gene conversion if m2h_file != None: m2h = pd.read_csv(m2h_file) m2h = m2h.loc[~(m2h.index.isna() | m2h.index.duplicated(keep = "first"))] #get list of things already done processed = os.listdir(out_dir) for i in set(annot_df.index.get_level_values("SRS accession")): #extract SRA sra = pldba.getSRA(i,annot_df) #get clusters clust = set(annot_df.loc[annot_df.index.get_level_values("SRS accession")==i].index.get_level_values("Cluster index")) #get clusters and cells clust_df = pldba.extractPanglaoDBannotation(annot_dir, annot_df,sra,i,False) #skip if file already proecessd if sra + "_" + i +".csv" in processed: continue #get count file r_file = os.path.join(count_dir, '%s%s.sparse.RData.h5' % (sra, '_' + i if i!='notused' else '')) #read in count data try: count_df = sergii_io.readRDataFile(r_file)#,takeGeneSymbolOnly = True) except: sys.stderr.write("Failed to read %s"%r_file) if ignore_error: continue else: count_df = sergii_io.readRDataFile(r_file) #break #convert mouse to human if m2h_file != None and ("Mus musculus" in set(annot_df.loc[annot_df.index.get_level_values("SRS accession")==i,"Species"])): count_df.index = [ m2h.loc[m2h["MGI.symbol"] == x,"HGNC.symbol"].values[0] if x in set(m2h["MGI.symbol"]) else x for x in count_df.index] #get cells matching keyword coi = clust_df.loc[clust_df["cluster"].isin(clust)].index count_df = count_df[coi] #get correlation count_df = count_df.loc[~count_df.index.duplicated(keep = "first")] #curr_corr = get_corr(count_df,gene_list1,gene_list2,method,log_scale) try: curr_corr = get_corr(count_df,gene_list1,gene_list2,method,log_scale) except: sys.stderr.write("Failed to find correlation for %s"%r_file) if ignore_error: continue else: curr_corr = get_corr(count_df,gene_list1,gene_list1,method,log_scale) break #curr_corr.to_csv("test_curr_corr.csv") name = sra + "_" + i curr_corr.to_csv(os.path.join(out_dir,name +".csv")) """ try: for c in curr_corr.columns: if c in corr_dict: corr_dict[c] = corr_dict[c].join(curr_corr[[c]], how = "outer") corr_dict[c].columns = list(corr_dict[c])[:-1] + [name] else: corr_dict[c] = curr_corr[c] corr_dict[c].columns = [name] except: sys.stderr.write("Failed to loop through correlation %s"%f) if ignore_error: continue else: break """ #xl_file = pd.ExcelWriter(out_excel) #for k in corr_dict: # corr_dict[k].to_excel(xl_file,sheet_name = k) #xl_file.close() def get_all_diff_exp (annot_file, out_excel, out_dir, annot_dir, count_dir, gene_list1 = None, gene_list2 = None, keyword= None, column = "Cell type annotation", index_column = False, method = "pearson", m2h_file = None, log_scale = True, ignore_error = False, debug = False, reverse = True): #Readd in annotation data annot_df = pd.read_excel(annot_file, index_col = [0,1,2]) #get location of count files count_dir = os.path.join(count_dir,"var","www","html","SRA","SRA.final") #get annotations related to keywords if keyword != None: if type(keyword) == str: if index_column: annot_df = annot_df.loc[ annot_df.index.get_level_values(column) == keyword] else: annot_df = annot_df.loc[annot_df[column] == keyword] else: #keyword = re.compile("|".join(keyword) if index_column: annot_df = annot_df.loc[ annot_df.index.get_level_values(column).isin(keyword)] else: annot_df = annot_df.loc[annot_df[column].isin(keyword)] corr_dict = {} annot_df.to_csv("../Annot_run.csv") #read in mouse to human gene conversion if m2h_file != None: m2h = pd.read_csv(m2h_file) m2h = m2h.loc[~(m2h.index.isna() | m2h.index.duplicated(keep = "first"))] #get list of things already done processed = os.listdir(out_dir) vals = list(set(annot_df.index.get_level_values("SRS accession"))) if reverse: vals.reverse() for i in vals: #extract SRA sra = pldba.getSRA(i,annot_df) #get clusters clust = set(annot_df.loc[annot_df.index.get_level_values("SRS accession")==i].index.get_level_values("Cluster index")) #get clusters and cells clust_df = pldba.extractPanglaoDBannotation(annot_dir, annot_df,sra,i,False) #skip if file already proecessd if sra + "_" + i +".csv" in processed: continue #get count file r_file = os.path.join(count_dir, '%s%s.sparse.RData.h5' % (sra, '_' + i if i!='notused' else '')) #read in count data try: count_df = sergii_io.readRDataFile(r_file)#,takeGeneSymbolOnly = True) except: sys.stderr.write("Failed to read %s"%r_file) if ignore_error: continue else: count_df = sergii_io.readRDataFile(r_file) #break #convert mouse to human if m2h_file != None and ("Mus musculus" in set(annot_df.loc[annot_df.index.get_level_values("SRS accession")==i,"Species"])): count_df.index = [ m2h.loc[m2h["MGI.symbol"] == x,"HGNC.symbol"].values[0] if x in set(m2h["MGI.symbol"]) else x for x in count_df.index] #get other cells count_df = count_df.loc[~count_df.index.duplicated(keep = "first")] coi = clust_df.loc[clust_df["cluster"].isin(clust)].index other_df = count_df.loc[:,~count_df.columns.isin(coi)] #get cells matching keyword count_df = count_df[coi] #get correlation #curr_corr = get_corr(count_df,gene_list1,gene_list2,method,log_scale) try: curr_corr = get_corr(count_df,other_df,log_scale) except: sys.stderr.write("Failed to find correlation for %s"%r_file) if ignore_error: continue else: curr_corr = get_diff(count_df,other_df,log_scale) #break #curr_corr.to_csv("test_curr_corr.csv") name = sra + "_" + i curr_corr.to_csv(os.path.join(out_dir,name +".csv")) """ try: for c in curr_corr.columns: if c in corr_dict: corr_dict[c] = corr_dict[c].join(curr_corr[[c]], how = "outer") corr_dict[c].columns = list(corr_dict[c])[:-1] + [name] else: corr_dict[c] = curr_corr[c] corr_dict[c].columns = [name] except: sys.stderr.write("Failed to loop through correlation %s"%f) if ignore_error: continue else: break """ #xl_file = pd.ExcelWriter(out_excel) #for k in corr_dict: # corr_dict[k].to_excel(xl_file,sheet_name = k) #xl_file.close() def get_corr (count_df, gene_list1 = None, gene_list2 = None, method = "pearson", log_scale = True,fraction = .05): if log_scale: count_df = get_log_scale(count_df) count_df = count_df.loc[((count_df!=0).astype(int).sum(axis =1)/float(count_df.shape[1])) >fraction] count_df = count_df.fillna(0) #count_df.to_csv("count_test.txt") if gene_list1 != None: count_df = count_df.loc[count_df.index.isin(gene_list1)] if gene_list2 != None: #count_small_df = count_df.loc[count_df.index.isin(gene_list2)].T gene_list2 = set(gene_list2).intersection(count_df.index) #corr = pd.DataFrame() corr = {} corr = 1 - cdist(count_df.loc[gene_list2].values,count_df.values,metric = "correlation") #for g2 in gene_list2: #corr[g2] = [] #for g1 in count_df.index: # corr[g2].append(stats.pearsonr(count_df.loc[g1].values,count_df.loc[g2].values)[0]) #corr = pd.DataFrame(corr.values(),columns = (corr.keys()),index = count.index) corr = pd.DataFrame(corr,index = list(gene_list2),columns = count_df.index).T #count_small_df.to_csv("Test_samll_Count.csv") #count_df = count_df.T #corr = count_small_df.apply(lambda s: count_df.corrwith(s)) #print(corr.head()) if gene_list2 == None: corr = 1 - cdist(count_df.values,count_df.values,metric = "correlation") corr = pd.DataFrame(corr, count_df.index,count_df.index) #corr = count_df.T.corr(method = method) return corr def get_diff (count_df,other_df, log_scale = True, debug= False, fillna=True): ct = time.time() if fillna: count_df = count_df.fillna(0) other_df = other_df.fillna(0) if log_scale: count_df = get_log_scale(count_df) other_df = get_log_scale(other_df) if debug: sys.stderr.write("Log Scale:%f"%(ct-time.time())) ct = time.time() ind = set(count_df.index).intersection(other_df.index) count_df = count_df.loc[ind] other_df = other_df.loc[ind] #other_df.index = count_df.index #print(count_df.head().index) #print(other_df.head().index) results_df = pd.DataFrame() results_df["avg_logFC"] = (count_df.loc[ind].mean(axis=1)).fillna(0) results_df["avg_logFC"] -=(other_df.loc[ind].mean(axis=1)).fillna(0) if debug: sys.stderr.write("Mean Diff:%f"%(ct-time.time())) if debug: print("Mean Diff:%f"%(ct-time.time())) ct = time.time() ttest_res = stats.ttest_ind(count_df.fillna(0).T.values,other_df.fillna(0).T.values) if debug: sys.stderr.write("T-Test:%f"%(ct-time.time())) if debug: print("T-Test:%f"%(ct-time.time())) #print(len(ttest_res), len(ttest_res[0])) ct = time.time() results_df["T-Val"] = ttest_res[0] results_df["P-Val"] = ttest_res[1] results_df["Q-Val"] = results_df["P-Val"]*results_df.shape[0] results_df["PCT.1"] = (count_df!=0).astype(int).sum(axis=1)/float(count_df.shape[1]) results_df["PCT.2"] = (other_df!=0).astype(int).sum(axis=1)/float(other_df.shape[1]) if debug: sys.stderr.write("Other Metrics:%f"%(ct-time.time())) if debug: print("Other Metrics:%f"%(ct-time.time())) return results_df def get_log_scale(df): df = (df/df.sum(axis = 0))*10000 df = np.log1p(df) return df def merge_corr_df(dir, gene, merge_list = None): df_list = [] for f in os.listdir(dir): if merge_list != None and f not in merge_list: continue curr_df = pd.read_csv(os.path.join(dir,f), index_col = 0) if gene not in curr_df.columns: continue curr_df = curr_df[[gene]] curr_df.columns = [f.split(".")[0]] curr_df = curr_df.loc[~curr_df.index.duplicated(keep = "first")] df_list.append(curr_df) df = pd.concat(df_list, join = "outer", axis = 1) return df def merge_Many_corr_df(dir,outdir, gene_list, suffix = "", merge_list = None): df_dict = {} for f in os.listdir(dir): if merge_list != None and f not in merge_list: continue curr_df = pd.read_csv(os.path.join(dir,f), index_col = 0) for gene in gene_list: if gene not in curr_df.columns: continue curr_gene_df = curr_df[[gene]] curr_gene_df.columns = [f.split(".")[0]] curr_gene_df = curr_gene_df.loc[~curr_gene_df.index.duplicated(keep = "first")] if gene not in df_dict: df_dict[gene] = [] df_dict[gene].append(curr_gene_df) for k in df_dict: df = pd.concat(df_dict[k], join = "outer", axis = 1) df.to_csv(os.path.join(outdir,"%s_%s.csv"%(k,suffix))) #return df def extract_cells (annot_file, out_excel, out_dir, annot_dir, count_dir, gene_list1 = None, gene_list2 = None, keyword= None, column = "Cell type annotation", index_column = False, method = "pearson", m2h_file = None, log_scale = True, ignore_error = False, debug = False): #Readd in annotation data annot_df = pd.read_excel(annot_file, index_col = [0,1,2]) #get location of count files count_dir = os.path.join(count_dir,"var","www","html","SRA","SRA.final") #get annotations related to keywords if keyword != None: if type(keyword) == str: if index_column: annot_df = annot_df.loc[ annot_df.index.get_level_values(column) == keyword] else: annot_df = annot_df.loc[annot_df[column] == keyword] else: #keyword = re.compile("|".join(keyword) if index_column: annot_df = annot_df.loc[ annot_df.index.get_level_values(column).isin(keyword)] else: annot_df = annot_df.loc[annot_df[column].isin(keyword)] corr_dict = {} annot_df.to_csv("../Annot_run.csv") processed = os.listdir(out_dir) all_counts = {} for i in set(annot_df.index.get_level_values("SRS accession")): #extract SRA sra = pldba.getSRA(i,annot_df) #get clusters clust = set(annot_df.loc[annot_df.index.get_level_values("SRS accession")==i].index.get_level_values("Cluster index")) #get clusters and cells clust_df = pldba.extractPanglaoDBannotation(annot_dir, annot_df,sra,i,False) #skip if file already proecessd if sra + "_" + i +".csv" not in processed: continue coi = clust_df.loc[clust_df["cluster"].isin(clust)].index name = sra + "_" + i all_counts[name] = list(coi) all_counts = pd.DataFrame(all_counts.values(), all_counts.keys()).T all_counts.to_csv("../Endothelial_Cells.csv") def get_all_corr_hdf (hdf_expr, out_excel, out_dir, annot_dir, count_dir, gene_list1 = None, gene_list2 = None, keyword= None, column = "Cell type annotation", index_column = False, method = "pearson", m2h_file = None, log_scale = True, ignore_error = False, debug = False): #get list of things already done processed = os.listdir(out_dir) for k in ["Mus musculus", "Homo sapiens"]: curr_spec_df = pd.read_hdf(hdf_expr, key = k, index_col = 0) for i in set( curr_spec_df.columns.get_level_values("batch")): #skip if file already proecessd if i+".csv" in processed: continue try: count_df = curr_spec_df.loc[:,curr_spec_df.columns.get_level_values("batch") ==i] except: sys.stderr.write("Failed to read %s"%r_file) if ignore_error: continue else: count_df = sergii_io.readRDataFile(r_file) #break #get correlation count_df = count_df.loc[~count_df.index.duplicated(keep = "first")] #curr_corr = get_corr(count_df,gene_list1,gene_list2,method,log_scale) try: curr_corr = get_corr(count_df,gene_list1,gene_list2,method,log_scale) except: sys.stderr.write("Failed to find correlation for %s"%r_file) if ignore_error: continue else: curr_corr = get_corr(count_df,gene_list1,gene_list1,method,log_scale) break #curr_corr.to_csv("test_curr_corr.csv") name = i +"_" + k.split(" ")[0] curr_corr.to_csv(os.path.join(out_dir,name +".csv")) def get_bootstrap(col_list,n=None,itr = 100, seed = 1): cross_valid_columns=[] random.seed(seed) if n == None: n = len(col_list) for i in range(itr): rand_cols = list(col_list) cross_valid_columns.append(np.random.choice(rand_cols,n)) return cross_valid_columns def get_all_diff_exp_hdf (hdf_expr, out_excel, out_dir, annot_dir, count_dir, gene_list1 = None, gene_list2 = None, keyword= None, column = "Cell type annotation", index_column = False, method = "pearson", m2h_file = None, log_scale = True, ignore_error = False, debug = True, reverse = True ): ct = time.time() #get location of count files count_dir = os.path.join(count_dir,"var","www","html","SRA","SRA.final") if debug: sys.stderr.write("Count Dir Setup:%f"%(ct - time.time())) if debug: print("Count Dir Setup:%f"%(ct - time.time())) ct = time.time() corr_dict = {} #read in mouse to human gene conversion if m2h_file != None: m2h = pd.read_csv(m2h_file) m2h = m2h.loc[~(m2h.index.isna() | m2h.index.duplicated(keep = "first"))] #get list of things already done processed = os.listdir(out_dir) if debug: sys.stderr.write("Other Setup:%f"%(ct-time.time())) if debug: print("Other Setup:%f"%(ct-time.time())) for k in ["Mus musculus", "Homo sapiens"]: ct = time.time() curr_spec_df = pd.read_hdf(hdf_expr, key = k, index_col = 0) if debug: sys.stderr.write("Loading HDF Count:%f"%(ct-time.time())) if debug: print("Loading HDF Count:%f"%(ct-time.time())) vals = list(set(curr_spec_df.columns.get_level_values("batch"))) if reverse: vals.reverse() for i in vals: #skip if file already proecessd if i+".csv" in processed: continue try: count_df = curr_spec_df.loc[:,curr_spec_df.columns.get_level_values("batch") ==i] except: sys.stderr.write("Failed to read %s"%r_file) if ignore_error: continue else: count_df = curr_spec_df.loc[:,curr_spec_df.columns.get_level_values("batch") ==i] count_df = sergii_io.readRDataFile(r_file) break #extract SRA #sra = pldba.getSRA(i,annot_df) #get clusters #clust = set(annot_df.loc[annot_df.index.get_level_values("SRS accession")==i].index.get_level_values("Cluster index")) #get clusters and cells #clust_df = pldba.extractPanglaoDBannotation(annot_dir, annot_df,sra,i,False) #skip if file already proecessd if i +".csv" in processed: continue ct = time.time() #get count file r_file = os.path.join(count_dir, '%s.sparse.RData.h5' % (i if i!='notused' else '')) #read in count data try: other_count_df = sergii_io.readRDataFile(r_file)#,takeGeneSymbolOnly = True) except: sys.stderr.write("Failed to read %s"%r_file) if ignore_error: continue else: other_count_df = sergii_io.readRDataFile(r_file) #break if debug: sys.stderr.write("Read Other:%f"%(ct-time.time())) if debug: print("Read Other:%f"%(ct-time.time())) ct = time.time() #convert mouse to human if m2h_file != None and k == "Mus musculus": other_count_df.index = [ m2h.loc[m2h["MGI.symbol"] == x,"HGNC.symbol"].values[0] if x in set(m2h["MGI.symbol"]) else x for x in other_count_df.index] #get other cells other_count_df = other_count_df.loc[~other_count_df.index.duplicated(keep = "first")] #coi = clust_df.loc[clust_df["cluster"].isin(clust)].index other_count_df = other_count_df.loc[:,~other_count_df.columns.isin(count_df.columns)] #get cells matching keyword #count_df = count_df[coi] #get correlation #curr_corr = get_corr(count_df,gene_list1,gene_list2,method,log_scale) other_count_df = get_log_scale(other_count_df) if debug: sys.stderr.write("Fix Other:%f"%(ct-time.time())) if debug: print("Fix Other:%f"%(ct-time.time())) ct = time.time() try: curr_corr = get_diff(count_df,other_count_df,False, debug)#log_scale) except: sys.stderr.write("Failed to find correlation for %s"%r_file) if ignore_error: continue else: curr_corr = get_diff(count_df,other_count_df,log_scale) #break #if debug: print(curr_corr.head()) if debug: sys.stderr.write("Get Diff:%f"%(ct-time.time())) if debug: print("Get Diff:%f"%(ct-time.time())) #curr_corr.to_csv("test_curr_corr.csv") ct = time.time() name = i curr_corr.to_csv(os.path.join(out_dir,name +".csv")) if debug: print(os.path.join(out_dir,name +".csv")) if debug:sys.stderr.write("Saving:%f"%(ct-time.time())) if debug: print("Saving:%f"%(ct-time.time()))

36.991573

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0.77148

0.122257

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0.003865

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false

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0.026895

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0

5

17182c0441523bbbb20f1c52dcf2ffe6d34d6e1b

9,855

py

Python

openGaussBase/testcase/SQL/DDL/schema/Opengauss_Function_DDL_Schema_Case0005.py

opengauss-mirror/Yat

aef107a8304b94e5d99b4f1f36eb46755eb8919e

[ "MulanPSL-1.0" ]

null

openGaussBase/testcase/SQL/DDL/schema/Opengauss_Function_DDL_Schema_Case0005.py

opengauss-mirror/Yat

aef107a8304b94e5d99b4f1f36eb46755eb8919e

[ "MulanPSL-1.0" ]

null

openGaussBase/testcase/SQL/DDL/schema/Opengauss_Function_DDL_Schema_Case0005.py

opengauss-mirror/Yat

aef107a8304b94e5d99b4f1f36eb46755eb8919e

[ "MulanPSL-1.0" ]

null

""" Copyright (c) 2022 Huawei Technologies Co.,Ltd. openGauss is licensed under Mulan PSL v2. You can use this software according to the terms and conditions of the Mulan PSL v2. You may obtain a copy of Mulan PSL v2 at: http://license.coscl.org.cn/MulanPSL2 THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE. See the Mulan PSL v2 for more details. """ """ Case Type : 基础功能 Case Name : 修改模式用户 Description : 1.创建用户 2.使用系统用户修改 3.修改用户不是所有者，不是新用户member，没有createdb权限 4.修改用户不是所有者，不是新用户member，有createdb权限 5.修改用户不是所有者，是新用户直接member，无createdb权限 6.修改用户不是所有者，是新用户间接member，无createdb权限 7.修改用户是所有者，不是新用户member，无createdb权限 8.修改用户是所有者，是新用户直接member，无createdb权限 9.修改用户是所有者，是新用户间接member，无createdb权限 10.修改用户是所有者，是新用户直接member，有createdb权限 11.修改用户是所有者，是新用户间接member，有createdb权限 12.修改用户不是所有者，是新用户直接member，有createdb权限 13.修改用户不是所有者，是新用户间接member，有createdb权限 14.修改用户是所有者，不是新用户member，有createdb权限 Expect : 1.创建用户成功 2.创建成功 3.修改失败 4.修改失败 5.修改失败 6.修改失败 7.修改失败 8.修改失败 9.修改失败 10.修改成功 11.修改成功 12.修改失败 13.修改失败 14.修改失败 History : """ import unittest from yat.test import Node from yat.test import macro from testcase.utils.CommonSH import CommonSH from testcase.utils.Constant import Constant from testcase.utils.Logger import Logger class Ddlschema(unittest.TestCase): commonshpri = CommonSH('PrimaryDbUser') def setUp(self): self.log = Logger() self.log.info('--Opengauss_Function_DDL_Schema_Case0005.py start--') self.db_primary_db_user = Node(node='PrimaryDbUser') self.constant = Constant() self.username = 'user_case005' self.groupname = 'group_case005' self.password = macro.COMMON_PASSWD def test_schema(self): self.log.info('----------------1.创建用户-----------------') sql = f"create user {self.username} " \ f"with password '{self.password}';" \ f"create user {self.username}_1 " \ f"with password '{self.password}';" \ f"create user {self.groupname} " \ f"with password '{self.password}';" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.CREATE_ROLE_SUCCESS_MSG, result) sql = f"create user {self.groupname}_1 " \ f"with password '{self.password}' IN GROUP {self.groupname};" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.CREATE_ROLE_SUCCESS_MSG, result) sql = f"create user {self.groupname}_2 " \ f"with password '{self.password}' IN GROUP {self.groupname}_1;" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.CREATE_ROLE_SUCCESS_MSG, result) self.log.info('----------2.使用系统用户修改----------') sql = f"alter schema {self.username}_1 owner to {self.username};" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---3.修改用户不是所有者，不是新用户member，没有createdb权限---') sql = f"alter schema {self.username} owner to {self.groupname};" cmd = f"-U {self.username}_1 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---4.修改用户不是所有者，不是新用户member，有createdb权限---') sql = f"grant create on database " \ f"{self.db_primary_db_user.db_name} to {self.username}_1;" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.GRANT_SUCCESS_MSG, result) sql = f"alter schema {self.username} owner to {self.groupname};" cmd = f"-U {self.username}_1 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---5.修改用户不是所有者，是新用户直接member，无createdb权限---') sql = f"alter schema {self.username} owner to {self.groupname};" cmd = f"-U {self.groupname}_1 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---6.修改用户不是所有者，是新用户间接member，无createdb权限---') sql = f"alter schema {self.username} owner to {self.groupname};" cmd = f"-U {self.groupname}_2 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---7.修改用户是所有者，不是新用户member，无createdb权限---') sql = f"alter schema {self.username} owner to {self.groupname};" cmd = f"-U {self.username} -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---8.修改用户是所有者，是新用户直接member，无createdb权限---') sql = f"alter schema {self.groupname}_1 owner to {self.groupname};" cmd = f"-U {self.groupname}_1 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---9.修改用户是所有者，是新用户间接member，无createdb权限---') sql = f"alter schema {self.groupname}_2 owner to {self.groupname};" cmd = f"-U {self.groupname}_2 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---10.修改用户是所有者，是新用户直接member，有createdb权限---') sql = f"grant create on database {self.db_primary_db_user.db_name}" \ f" to {self.groupname}_1;" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.GRANT_SUCCESS_MSG, result) sql = f"alter schema {self.groupname}_1 owner to {self.groupname};" cmd = f"-U {self.groupname}_1 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---11.修改用户是所有者，是新用户间接member，有createdb权限---') sql = f"grant create on database {self.db_primary_db_user.db_name}" \ f" to {self.groupname}_2;" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.GRANT_SUCCESS_MSG, result) sql = f"alter schema {self.groupname}_2 owner to {self.groupname};" cmd = f"-U {self.groupname}_2 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---12.修改用户不是所有者，是新用户直接member，有createdb权限---') sql = f"grant create on database {self.db_primary_db_user.db_name}" \ f" to {self.groupname}_1;" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.GRANT_SUCCESS_MSG, result) sql = f"alter schema {self.username} owner to {self.groupname};" cmd = f"-U {self.groupname}_1 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---13.修改用户不是所有者，是新用户间接member，有createdb权限---') sql = f"grant create on database {self.db_primary_db_user.db_name}" \ f" to {self.groupname}_2;" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.GRANT_SUCCESS_MSG, result) sql = f"alter schema {self.username} owner to {self.groupname};" cmd = f"-U {self.groupname}_2 -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) self.log.info('---14.修改用户是所有者，不是新用户member，有createdb权限---') sql = f"grant create on database {self.db_primary_db_user.db_name}" \ f" to {self.username};" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.assertIn(self.constant.GRANT_SUCCESS_MSG, result) sql = f"alter schema {self.username} owner to {self.groupname};" cmd = f"-U {self.username} -W {self.password}" result = self.commonshpri.execut_db_sql(sql, cmd) self.log.info(result) self.assertNotIn(self.constant.ALTER_SCHEMA_SUCCESS_MSG, result) def tearDown(self): self.log.info('------------环境清理-----------') self.log.info('---------删除用户------') sql = f"drop user if exists {self.username} cascade;" \ f"drop user if exists {self.username}_1 cascade;" \ f"drop user if exists {self.groupname} cascade;" \ f"drop user if exists {self.groupname}_1 cascade;" \ f"drop user if exists {self.groupname}_2 cascade;" result = self.commonshpri.execut_db_sql(sql) self.log.info(result) self.log.info('--Opengauss_Function_DDL_Schema_Case0005.py finish-')

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py

Python

tests/gui_tests.py

jaredsampson/pymolprobity

879ebd4c0e64e05a0cd91da8c545023f958cb634

[ "MIT" ]

9

2016-08-29T17:39:57.000Z

2022-03-29T09:26:59.000Z

tests/gui_tests.py

jaredsampson/pymolprobity

879ebd4c0e64e05a0cd91da8c545023f958cb634

[ "MIT" ]

8

2016-11-03T19:17:47.000Z

2019-08-13T15:58:00.000Z

tests/gui_tests.py

jaredsampson/pymolprobity

879ebd4c0e64e05a0cd91da8c545023f958cb634

[ "MIT" ]

2

2017-01-19T10:36:04.000Z

2018-05-10T13:42:53.000Z

'''GUI tests for PyMOLProbity plugin.''' import mock import unittest from .context import pymolprobity import pymolprobity.gui as gui if __name__ == '__main__': unittest.main()

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1796c5d34f0b21ff6eb23b7ce9ac26a2f3bfe049

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py

Python

share.py

Architkawale18/Society-Visitor-Registration

d7838e1376225e28222cfedc0bacb4d1009d42d6

[ "Apache-2.0" ]

2

2020-03-31T12:22:41.000Z

2020-04-26T07:29:01.000Z

share.py

Architkawale18/Society-Visitor-Registration

d7838e1376225e28222cfedc0bacb4d1009d42d6

[ "Apache-2.0" ]

null

share.py

Architkawale18/Society-Visitor-Registration

d7838e1376225e28222cfedc0bacb4d1009d42d6

[ "Apache-2.0" ]

null

class SharedClass: pass

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17a3a1740cfa7f75b0f03a17620a762ead100a8c

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py

Python

shopping_list_colleague.py

fangqiangchen/git_practice

acdcdc8b3fd66ebd5b3910a8ec01988bb4e2b9d4

[ "Apache-2.0" ]

null

shopping_list_colleague.py

fangqiangchen/git_practice

acdcdc8b3fd66ebd5b3910a8ec01988bb4e2b9d4

[ "Apache-2.0" ]

null

shopping_list_colleague.py

fangqiangchen/git_practice

acdcdc8b3fd66ebd5b3910a8ec01988bb4e2b9d4

[ "Apache-2.0" ]

null

#woman dress #add test

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bd5e42ce8af85d2db6f69d7050e300c60cd3ce8c

189

py

Python

dace/transformation/__init__.py

Walon1998/dace

95ddfd3e9a5c654f0f0d66d026e0b64ec0f028a0

[ "BSD-3-Clause" ]

1

2022-03-11T13:36:34.000Z

dace/transformation/__init__.py

Walon1998/dace

95ddfd3e9a5c654f0f0d66d026e0b64ec0f028a0

[ "BSD-3-Clause" ]

null

dace/transformation/__init__.py

Walon1998/dace

95ddfd3e9a5c654f0f0d66d026e0b64ec0f028a0

[ "BSD-3-Clause" ]

null

from .transformation import (simplification_transformations, SingleStateTransformation, MultiStateTransformation, SubgraphTransformation, ExpandTransformation)

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bd9f5279f0473f499783dfd2df32f1a074721394

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py

Python

nengo_spinnaker/operators/__init__.py

SpiNNakerManchester/nengo_spinnaker

147e2b3d6c0965259d6897f177f23e5c99b184f9

[ "MIT" ]

13

2015-06-10T08:58:05.000Z

2022-03-29T08:20:14.000Z

nengo_spinnaker/operators/__init__.py

SpiNNakerManchester/nengo_spinnaker

147e2b3d6c0965259d6897f177f23e5c99b184f9

[ "MIT" ]

131

2015-04-16T15:17:12.000Z

2020-06-19T05:38:56.000Z

nengo_spinnaker/operators/__init__.py

SpiNNakerManchester/nengo_spinnaker

147e2b3d6c0965259d6897f177f23e5c99b184f9

[ "MIT" ]

7

2015-07-01T00:01:50.000Z

2018-06-28T10:12:18.000Z

from .filter import Filter from .lif import EnsembleLIF from .sdp_receiver import SDPReceiver from .sdp_transmitter import SDPTransmitter from .value_sink import ValueSink from .value_source import ValueSource

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bd9fa48fa6ba35b4e2e69d57c75c540355458e0f

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py

Python

fluiddb/util/__init__.py

fluidinfo/fluiddb

b5a8c8349f3eaf3364cc4efba4736c3e33b30d96

[ "Apache-2.0" ]

3

2021-05-10T14:41:30.000Z

2021-12-16T05:53:30.000Z

fluiddb/util/__init__.py

fluidinfo/fluiddb

b5a8c8349f3eaf3364cc4efba4736c3e33b30d96

[ "Apache-2.0" ]

null

fluiddb/util/__init__.py

fluidinfo/fluiddb

b5a8c8349f3eaf3364cc4efba4736c3e33b30d96

[ "Apache-2.0" ]

2

2018-01-24T09:03:21.000Z

2021-06-25T08:34:54.000Z

"""Logic for utilities needed by Fluidinfo."""

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py

Python

p2/components/quota/exceptions.py

BeryJu/p2

80b5c6a821f90cef73d6e8cd3c6cdb05ffa86b27

[ "MIT" ]

null

p2/components/quota/exceptions.py

BeryJu/p2

80b5c6a821f90cef73d6e8cd3c6cdb05ffa86b27

[ "MIT" ]

null

p2/components/quota/exceptions.py

BeryJu/p2

80b5c6a821f90cef73d6e8cd3c6cdb05ffa86b27

[ "MIT" ]

null

"""p2 quota exceptions""" from p2.core.exceptions import BlobException class QuotaExceededException(BlobException): """Exception raised when ACTION_BLOCK is selected."""

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bdf7e62b1eaba6dcb40b240842930efbb85e3a07

268

py

Python

smqtk_dataprovider/__init__.py

joshanderson-kw/SMQTK-Dataprovider

1ae285e65b2ae21914b0efdf90a4c9981c59853e

[ "BSD-3-Clause" ]

1

2021-03-16T15:02:12.000Z

smqtk_dataprovider/__init__.py

joshanderson-kw/SMQTK-Dataprovider

1ae285e65b2ae21914b0efdf90a4c9981c59853e

[ "BSD-3-Clause" ]

5

2021-03-10T13:58:13.000Z

2022-02-10T15:18:28.000Z

smqtk_dataprovider/__init__.py

joshanderson-kw/SMQTK-Dataprovider

1ae285e65b2ae21914b0efdf90a4c9981c59853e

[ "BSD-3-Clause" ]

2

2021-03-18T15:29:27.000Z

2021-03-29T18:43:14.000Z

from .interfaces.data_element import DataElement, from_uri # noqa: F401 from .interfaces.data_set import DataSet # noqa: F401 from .interfaces.key_value_store import KeyValueStore # noqa: F401 from .content_type_validator import ContentTypeValidator # noqa: F401

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da1dde3bb8c263bda1405c177f7d53380cd1b9b4

173

py

Python

storage/schema/query.py

trunkboy/django-multi-storage

f1627f5bb01eaae06a178c323190d2ccf6fba44f

[ "Apache-2.0" ]

null

storage/schema/query.py

trunkboy/django-multi-storage

f1627f5bb01eaae06a178c323190d2ccf6fba44f

[ "Apache-2.0" ]

4

2020-10-18T15:26:48.000Z

2020-10-20T15:57:03.000Z

storage/schema/query.py

trunkboy/django-multi-storage

f1627f5bb01eaae06a178c323190d2ccf6fba44f

[ "Apache-2.0" ]

2

2020-10-17T17:09:32.000Z

2020-10-20T13:51:39.000Z

import graphene from graphene_django.filter import DjangoFilterConnectionField from storage.schema.node import ( ImageNode ) class Query(graphene.ObjectType): pass

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e53a8627afd6a15d2ffc8c7097681c4f6d12114f

324

py

Python

portfolioplanner/Utils/__init__.py

wonkothesaint/profileplaner

98d6caf4b7205a267fb109259a7b3762b28b7c59

[ "MIT" ]

null

portfolioplanner/Utils/__init__.py

wonkothesaint/profileplaner

98d6caf4b7205a267fb109259a7b3762b28b7c59

[ "MIT" ]

null

portfolioplanner/Utils/__init__.py

wonkothesaint/profileplaner

98d6caf4b7205a267fb109259a7b3762b28b7c59

[ "MIT" ]

null

def percents_yearly_to_monthly(yearly_percent): return ((1 + yearly_percent) ** (1 / 12)) - 1 def currency_str(number, currency="ILS"): if currency == "ILS": return "₪{:,.2f}".format(number) if currency == "USD": return "${:,.2f}".format(number) return "{:,.2f} ".format(number) + currency

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0

5

e56d7e67e39b652adca8c61169e307c22fc5f577

20,233

py

Python

tests/unittests/test_collect.py

sean-hayes/zoom

eda69c64ceb69dd87d2f7a5dfdaeea52ef65c581

[ "MIT" ]

1

2017-05-11T17:24:49.000Z

tests/unittests/test_collect.py

sean-hayes/zoom

eda69c64ceb69dd87d2f7a5dfdaeea52ef65c581

[ "MIT" ]

null

tests/unittests/test_collect.py

sean-hayes/zoom

eda69c64ceb69dd87d2f7a5dfdaeea52ef65c581

[ "MIT" ]

1

2020-07-20T00:33:27.000Z

""" Test the collect module """ import logging import os import sys import unittest import difflib from decimal import Decimal from datetime import date, time, datetime import zoom # from zoom import (Entity, Fields, TextField, required, # DecimalField, url_for_page) from zoom.browse import browse from zoom.page import page from zoom.helpers import url_for_page from zoom.context import context from zoom.collect import Collection, CollectionModel from zoom.exceptions import UnauthorizedException from zoom.fields import Fields, TextField, DecimalField from zoom.users import Users from zoom.validators import required VIEW_EMPTY_LIST = """<div class="baselist"> <table> <thead><tr> <th>Name</th> <th>Address</th> <th>Salary</th> </tr></thead> <tbody> </tbody> <tr><td colspan=3>None</td></tr> </table> <div class="footer">0 people</div> </div>""" VIEW_SINGLE_RECORD_LIST = """<div class="baselist"> <table> <thead><tr> <th>Name</th> <th>Address</th> <th>Salary</th> </tr></thead> <tbody> <tr id="row-1"> <td nowrap><a href="<dz:app_url>/people/joe">Joe</a></td> <td nowrap>123 Somewhere St</td> <td nowrap>40,000</td> </tr> </tbody> </table> <div class="footer">1 person</div> </div>""" VIEW_TWO_RECORD_LIST = """<div class="baselist"> <table> <thead><tr> <th>Name</th> <th>Address</th> <th>Salary</th> </tr></thead> <tbody> <tr id="row-1"> <td nowrap><a href="<dz:app_url>/people/joe">Joe</a></td> <td nowrap>123 Somewhere St</td> <td nowrap>40,000</td> </tr> <tr id="row-2"> <td nowrap><a href="<dz:app_url>/people/sally">Sally</a></td> <td nowrap>123 Special St</td> <td nowrap>45,000</td> </tr> </tbody> </table> <div class="footer">2 people</div> </div>""" VIEW_ALL_RECORDS_LIST = """<div class="baselist"> <table> <thead><tr> <th>Name</th> <th>Address</th> <th>Salary</th> </tr></thead> <tbody> <tr id="row-1" class="light"> <td nowrap><a href="/noapp//myapp/jim">Jim</a></td> <td nowrap>123 Somewhere St</td> <td nowrap>40,000</td> </tr> <tr id="row-2" class="dark"> <td nowrap><a href="/noapp//myapp/joe">Joe</a></td> <td nowrap>123 Somewhere St</td> <td nowrap>40,000</td> </tr> <tr id="row-3" class="light"> <td nowrap><a href="/noapp//myapp/sally">Sally</a></td> <td nowrap>123 Special St</td> <td nowrap>45,000</td> </tr> </tbody> </table> <div class="footer">3 peoples</div> </div>""" VIEW_NO_JOE_LIST = """<div class="baselist"> <table> <thead><tr> <th>Name</th> <th>Address</th> <th>Salary</th> </tr></thead> <tbody> <tr id="row-1"> <td nowrap><a href="<dz:app_url>/people/sally">Sally</a></td> <td nowrap>123 Special St</td> <td nowrap>45,000</td> </tr> </tbody> </table> <div class="footer">1 person</div> </div>""" VIEW_UPDATED_JOE_LIST = """<div class="baselist"> <table> <thead><tr> <th>Name</th> <th>Address</th> <th>Salary</th> </tr></thead> <tbody> <tr id="row-1" class="light"> <td nowrap><a href="/noapp//myapp/jim">Jim</a></td> <td nowrap>123 Somewhere St</td> <td nowrap>40,000</td> </tr> <tr id="row-2" class="dark"> <td nowrap><a href="/noapp//myapp/sally">Sally</a></td> <td nowrap>123 Special St</td> <td nowrap>45,000</td> </tr> </tbody> </table> <div class="footer">2 peoples</div> </div>""" def assert_same(t1, t2): try: assert t1 == t2 except: s1 = t1.splitlines() s2 = t2.splitlines() print('\n'.join(difflib.context_diff(s1, s2))) raise class Person(CollectionModel): pass key = property(lambda self: zoom.utils.id_for(self.name)) url = property(lambda self: url_for_page('people', self.key)) # link = property(lambda self: self.name) link = property(lambda self: zoom.helpers.link_to(self.name, self.url)) #class TestPerson(CollectionRecord): pass # define the fields for the collection def person_fields(): return Fields( TextField('Name', required), TextField('Address'), DecimalField('Salary'), ) class FakeRequest(object): def __init__(self, *args, **kwargs): self.data = {} self.route = args self.__dict__.update(kwargs) def get_elapsed(self): return 0 class FakeSite(object): def __init__(self, **kwargs): self.__dict__.update(kwargs) class TestCollect(unittest.TestCase): def setUp(self): # setup the system and install our own test database # system.setup(os.path.expanduser('~')) self.db = zoom.database.setup_test() self.users = Users(self.db) self.user = self.users.first(username='admin') self.site = zoom.system.site = FakeSite( db=self.db, url='', logging=False, ) self.request = context.request = FakeRequest( '/myapp', user=self.user, site=self.site, path='/myapp', ip_address='127.0.0.1', remote_user='', host='localhost', data={}, ) # user.initialize('guest') # self.user.groups = ['managers'] # create the test collection self.collection = Collection( person_fields, name='People', model=Person, url='/myapp', store=zoom.store.EntityStore(self.db, Person) ) # so we can see our print statements self.save_stdout = sys.stdout sys.stdout = sys.stderr self.logger = logging.getLogger(__name__) def tearDown(self): # remove our test data # self.collection.store.zap() self.db.close() sys.stdout = self.save_stdout def collect(self, *route, **data): self.request.route = list(route) self.request.data = data return self.collection(route, self.request) def assert_response(self, content, *args, **kwargs): assert_same(content, self.collect(*args, **kwargs).content) def test_empty(self): self.collection.store.zap() self.assert_response(VIEW_EMPTY_LIST) def test_insert(self): self.collection.store.zap() self.assert_response(VIEW_EMPTY_LIST) insert_record_input = dict( create_button='y', name='Joe', address='123 Somewhere St', salary=Decimal('40000'), ) self.collect('new', **insert_record_input) self.logger.debug(str(self.collection.store)) self.assert_response(VIEW_SINGLE_RECORD_LIST) def test_delete(self): self.collection.store.zap() self.assert_response(VIEW_EMPTY_LIST) joe_input = dict( create_button='y', name='Joe', address='123 Somewhere St', salary=Decimal('40000'), ) self.collect('new', **joe_input) sally_input = dict( create_button='y', name='Sally', address='123 Special St', salary=Decimal('45000'), ) self.collect('new', **sally_input) self.assert_response(VIEW_TWO_RECORD_LIST) self.collect('delete', 'joe', **{'confirm': 'no'}) self.assert_response(VIEW_NO_JOE_LIST) self.collect('delete', 'sally', **{'confirm': 'no'}) self.assert_response(VIEW_EMPTY_LIST) # def test_update(self): # self.collection.store.zap() # t = self.collection() # assert_same(VIEW_EMPTY_LIST, t.content) # # joe_input = dict( # CREATE_BUTTON='y', # NAME='Joe', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # ) # t = self.collection('new', **joe_input) # # sally_input = dict( # CREATE_BUTTON='y', # NAME='Sally', # ADDRESS='123 Special St', # SALARY=Decimal('45000'), # ) # t = self.collection('new', **sally_input) # # self.collection('joe', 'edit', **dict( # SAVE_BUTTON='y', # NAME='Jim', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # )) # t = self.collection() # assert_same(VIEW_UPDATED_JOE_LIST, t.content) # # self.collection('delete', 'jim', **{'CONFIRM': 'NO'}) # t = self.collection() # assert_same(VIEW_NO_JOE_LIST, t.content) # # self.collection('delete', 'sally', **{'CONFIRM': 'NO'}) # t = self.collection() # assert_same(VIEW_EMPTY_LIST, t.content) # # def test_authorized_editors(self): # self.collection.store.zap() # t = self.collection() # assert_same(VIEW_EMPTY_LIST, t.content) # # joe_input = dict( # CREATE_BUTTON='y', # NAME='Joe', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # ) # t = self.collection('new', **joe_input) # # sally_input = dict( # CREATE_BUTTON='y', # NAME='Sally', # ADDRESS='123 Special St', # SALARY=Decimal('45000'), # ) # t = self.collection('new', **sally_input) # t = self.collection() # assert_same(VIEW_TWO_RECORD_LIST, t.content) # # # only authorized users can edit collections # user.groups = [] # with self.assertRaises(UnauthorizedException): # self.collection('joe', 'edit', **dict( # SAVE_BUTTON='y', # NAME='Jim', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # )) # t = self.collection() # assert_same(VIEW_TWO_RECORD_LIST, t.content) # # user.groups = ['managers'] # self.collection('joe', 'edit', **dict( # SAVE_BUTTON='y', # NAME='Jim', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # )) # t = self.collection() # assert_same(VIEW_UPDATED_JOE_LIST, t.content) # # user.groups = [] # with self.assertRaises(UnauthorizedException): # self.collection('delete', 'jim', **{'CONFIRM': 'NO'}) # t = self.collection() # assert_same(VIEW_UPDATED_JOE_LIST, t.content) # # user.groups = ['managers'] # self.collection('delete', 'jim', **{'CONFIRM': 'NO'}) # t = self.collection() # assert_same(VIEW_NO_JOE_LIST, t.content) # # self.collection('delete', 'sally', **{'CONFIRM': 'NO'}) # t = self.collection() # assert_same(VIEW_EMPTY_LIST, t.content) # # # def test_private(self): # # class PrivatePerson(Person): # def allows(self, user, action=None): # # def is_owner(user): # return user.user_id == self.owner_id # # def is_user(user): # return user.is_authenticated # # actions = { # 'create': is_user, # 'read': is_owner, # 'update': is_owner, # 'delete': is_owner, # } # # return actions.get(action)(user) # # #def private(rec, user, action=None): # #return rec.owner == user.user_id # # self.collection = Collection('People', person_fields, PrivatePerson, url='/myapp') # self.collection.can_edit = lambda: True # #self.collection.authorization = private # # self.collection.store.zap() # t = self.collection() # assert_same(VIEW_EMPTY_LIST, t.content) # # # user one inserts two records # joe_input = dict( # CREATE_BUTTON='y', # NAME='Jim', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # ) # t = self.collection('new', **joe_input) # # sally_input = dict( # CREATE_BUTTON='y', # NAME='Sally', # ADDRESS='123 Special St', # SALARY=Decimal('45000'), # ) # t = self.collection('new', **sally_input) # t = self.collection() # assert_same(VIEW_UPDATED_JOE_LIST, t.content) # # # user two inserts one record # user.initialize('admin') # self.collection('new', **dict( # CREATE_BUTTON='y', # NAME='Joe', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # )) # t = self.collection() # assert_same(VIEW_SINGLE_RECORD_LIST, t.content) # # # user one can still only see theirs # user.initialize('guest') # t = self.collection() # assert_same(VIEW_UPDATED_JOE_LIST, t.content) # # # user can't read records that belong to others # with self.assertRaises(UnauthorizedException): # t = self.collection('joe') # # # user can't edit records that belong to others # with self.assertRaises(UnauthorizedException): # t = self.collection('joe', 'edit') # # # user can't do delete confirmation for records that belong to others # with self.assertRaises(UnauthorizedException): # t = self.collection('joe', 'delete') # # # user can't update records that belong to others # with self.assertRaises(UnauthorizedException): # t = self.collection('joe', 'edit', **dict( # SAVE_BUTTON='y', # NAME='Andy', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # )) # # # user can't delete records that belong to others # with self.assertRaises(UnauthorizedException): # self.collection('joe', 'delete', **{'CONFIRM': 'NO'}) # # # switch back to owner and do the same operations # user.initialize('admin') # self.collection('joe') # self.collection('joe', 'edit') # self.collection('joe', 'delete') # self.collection('joe', 'edit', **dict( # SAVE_BUTTON='y', # NAME='Andy', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # )) # self.collection('andy', 'delete', **{'CONFIRM': 'NO'}) # # # user.initialize('guest') # user.groups = ['managers'] # self.collection('delete', 'jim', **{'CONFIRM': 'NO'}) # t = self.collection() # assert_same(VIEW_NO_JOE_LIST, t.content) # # self.collection('delete', 'sally', **{'CONFIRM': 'NO'}) # t = self.collection() # assert_same(VIEW_EMPTY_LIST, t.content) # # # def test_published(self): # # class PrivatePerson(Person): # def allows(self, user, action=None): # # def is_owner(user): # return user.user_id == self.owner_id # # def is_user(user): # return user.is_authenticated # # actions = { # 'create': is_user, # 'read': is_user, # 'update': is_owner, # 'delete': is_owner, # } # # return actions.get(action)(user) # # self.collection = Collection('People', person_fields, PrivatePerson, url='/myapp') # self.collection.can_edit = lambda: True # # self.collection.store.zap() # t = self.collection() # assert_same(VIEW_EMPTY_LIST, t.content) # # # user one inserts two records # user.initialize('user') # assert user.is_authenticated # user.groups = ['managers'] # # joe_input = dict( # CREATE_BUTTON='y', # NAME='Jim', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # ) # t = self.collection('new', **joe_input) # # sally_input = dict( # CREATE_BUTTON='y', # NAME='Sally', # ADDRESS='123 Special St', # SALARY=Decimal('45000'), # ) # t = self.collection('new', **sally_input) # t = self.collection() # assert_same(VIEW_UPDATED_JOE_LIST, t.content) # # # user two inserts one record # user.initialize('admin') # self.collection('new', **dict( # CREATE_BUTTON='y', # NAME='Joe', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # )) # t = self.collection() # assert_same(VIEW_ALL_RECORDS_LIST, t.content) # # # user one can also see all # user.initialize('user') # t = self.collection() # assert_same(VIEW_ALL_RECORDS_LIST, t.content) # # # guest can't read records # user.initialize('guest') # with self.assertRaises(UnauthorizedException): # t = self.collection('joe') # # # authenticated user can read records that belong to others # user.initialize('user') # t = self.collection('joe') # # # user can't edit records that belong to others # user.initialize('guest') # with self.assertRaises(UnauthorizedException): # t = self.collection('joe', 'edit') # # # user can't edit records that belong to others # user.initialize('user') # with self.assertRaises(UnauthorizedException): # t = self.collection('joe', 'edit') # # # guest can't do delete confirmation for records that belong to others # user.initialize('guest') # with self.assertRaises(UnauthorizedException): # t = self.collection('joe', 'delete') # # # user can't do delete confirmation for records that belong to others # user.initialize('user') # with self.assertRaises(UnauthorizedException): # t = self.collection('joe', 'delete') # # # user can't update records that belong to others # with self.assertRaises(UnauthorizedException): # t = self.collection('joe', 'edit', **dict( # SAVE_BUTTON='y', # NAME='Andy', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # )) # # # user can't delete records that belong to others # with self.assertRaises(UnauthorizedException): # self.collection('joe', 'delete', **{'CONFIRM': 'NO'}) # # # switch back to owner and do the same operations # user.initialize('admin') # self.collection('joe') # self.collection('joe', 'edit') # self.collection('joe', 'delete') # self.collection('joe', 'edit', **dict( # SAVE_BUTTON='y', # NAME='Andy', # ADDRESS='123 Somewhere St', # SALARY=Decimal('40000'), # )) # self.collection('andy', 'delete', **{'CONFIRM': 'NO'}) # # # guest can't delete # user.initialize('guest') # user.groups = ['managers'] # with self.assertRaises(UnauthorizedException): # self.collection('delete', 'jim', **{'CONFIRM': 'NO'}) # # # guest can't delete # with self.assertRaises(UnauthorizedException): # self.collection('delete', 'sally', **{'CONFIRM': 'NO'}) # # # non-owner can't delete # user.initialize('admin') # user.groups = ['managers'] # with self.assertRaises(UnauthorizedException): # self.collection('delete', 'jim', **{'CONFIRM': 'NO'}) # # # non-owner can't delete # with self.assertRaises(UnauthorizedException): # self.collection('delete', 'sally', **{'CONFIRM': 'NO'}) # # # owner can delete # user.initialize('user') # user.groups = ['managers'] # self.collection('delete', 'jim', **{'CONFIRM': 'NO'}) # t = self.collection() # assert_same(VIEW_NO_JOE_LIST, t.content) # # self.collection('delete', 'sally', **{'CONFIRM': 'NO'}) # t = self.collection() # assert_same(VIEW_EMPTY_LIST, t.content) #

30.37988

92

0.546731

2,239

20,233

4.831175

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0.044652

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0.74161

0.727189

0.724785

0.709346

0.708977

0

0.018636

0.297188

20,233

665

93

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0.742053

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0

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false

0.004167

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0.004167

0

null

0

1

0

null

0

5

e5d8dd753cf3ec42f424fbf2d2622715344b5504

52

py

Python

randomness_beacon/__init__.py

produit/randomness_beacon

0882772fe9b4b80b1a5b0dda19f887f5d87fb2b8

[ "BSD-2-Clause" ]

17

2015-01-18T00:46:16.000Z

2021-12-24T02:36:27.000Z

randomness_beacon/__init__.py

produit/randomness_beacon

0882772fe9b4b80b1a5b0dda19f887f5d87fb2b8

[ "BSD-2-Clause" ]

null

randomness_beacon/__init__.py

produit/randomness_beacon

0882772fe9b4b80b1a5b0dda19f887f5d87fb2b8

[ "BSD-2-Clause" ]

5

2015-09-10T01:37:15.000Z

2019-06-10T17:59:13.000Z

from beacon import Beacon, BeaconError, random_nums

26

51

0.846154

7

52

6.142857

0.857143

0

0.115385

52

1

52

0.934783

0

1

0

true

0

1

0

1

0

1

0

null

0

1

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null

0

1

0

1

0

1

0

5

e5f9f12898e992a2d676c925cd7ce7bb5b45277f

5,769

py

Python

multivar/gradient.py

HamzaBamohammed/hambam-unconstraint-optimization

f710f31883ec60d231ec6e8bf168805f7d455a98

[ "MIT" ]

4

2022-02-19T03:54:23.000Z

2022-02-25T00:03:14.000Z

multivar/gradient.py

HamzaBamohammed/hambam-unconstraint-optimization

f710f31883ec60d231ec6e8bf168805f7d455a98

[ "MIT" ]

null

multivar/gradient.py

HamzaBamohammed/hambam-unconstraint-optimization

f710f31883ec60d231ec6e8bf168805f7d455a98

[ "MIT" ]

null

import numpy as np import scipy.optimize as op import scipy.linalg as la import numdifftools as nd from matplotlib import pyplot as plt from mpl_toolkits import mplot3d from time import perf_counter #returns the minimum of a multivariable function using gradient descent def gradient_descent(f, xk, delta = 0.01, plot=False, F = None, axlim = 10): """ f: multivariable function with 1 array as parameter xk : a vector to start descent delta : precision of search plot : option to plot the results or not F : the function f expressed with 2 arrays in argument (X,Y) representing the colomns xk[0] and xk[1] for ploting issues. used only if plot == True axlim : limit of the plot 3 axis (x,y,z) """ if plot : ax = plt.axes(projection='3d') A = [] t = perf_counter() dk = nd.Gradient(f)(xk) while la.norm(dk) > delta : if plot and len(A) < 10 : A.append(xk) xt = xk phi = lambda s : f(xk - s * dk) alpha = op.newton(phi, 1) xk -= alpha * dk if plot and len(A) < 10 : A.append(xk) dk = nd.Gradient(f)(xk) if la.norm(xk - xt) < delta : break t = perf_counter() - t print("execution time: ",t) if plot : for u in A: ax.scatter(u[0], u[1], f(u), c = 'b', s = 50) ax.scatter(xk[0], xk[1], f(xk), c = 'r', s = 50,label="optimum") x = np.arange(-axlim, axlim, axlim/100) y = np.arange(-axlim, axlim, axlim/100) X, Y = np.meshgrid(x, y) Z = F(X,Y) ax.set_xlabel('x', labelpad=20) ax.set_ylabel('y', labelpad=20) ax.set_zlabel('z', labelpad=20) surf = ax.plot_surface(X, Y, Z, cmap = plt.cm.cividis) plt.legend() plt.title("optimizition with Gradient Descent") plt.show() return xk #returns the minimum of a multivariable function using conjugate gradient def conjugate_gradient(f, x, plot=False, F = None,axlim = 10): """ f: multivariable function with 1 array as parameter x : a vector to start descent plot : option to plot the results or not F : the function f expressed with 2 arrays in argument (X,Y) representing the colomns x[0] and x[1] for ploting issues. used only if plot == True axlim : limit of the plot 3 axis (x,y,z) """ if plot : ax = plt.axes(projection='3d') A = [] t = perf_counter() d = -nd.Gradient(f)(x) q = nd.Hessian(f)(x) n = len(x) for k in range(1, n): if plot and len(A) < int(n/3) : A.append(x) alpha = (d.T@d)/(d.T@q@d) x += alpha * d beta = (nd.Gradient(f)(x).T@q@d)/(d.T@q@d) d = beta * d - nd.Gradient(f)(x) t = perf_counter() - t print("execution time: ",t) if plot : for u in A: ax.scatter(u[0], u[1], f(u), c = 'b', s = 50) ax.scatter(x[0], x[1], f(x), c = 'r', s = 50,label="optimum") x = np.arange(-axlim, axlim, axlim/100) y = np.arange(-axlim, axlim, axlim/100) X, Y = np.meshgrid(x, y) Z = F(X,Y) ax.set_xlabel('x', labelpad=20) ax.set_ylabel('y', labelpad=20) ax.set_zlabel('z', labelpad=20) surf = ax.plot_surface(X, Y, Z, cmap = plt.cm.cividis) plt.legend() plt.title("optimizition with Conjugate Gradient") plt.show() return x #verifies if a function is defined positive at a point x def is_pos_def(f, x): """ f: multivariable function with 1 array as parameter x : a vector where to verify if f is definite positive """ m = nd.Hessian(f)(x) return np.all(np.linalg.eigvals(m) > 0) #returns the minimum of a multivariable function using Newton descent def newton_descent(f, x, delta = 0.01, plot=False, F = None, axlim = 10): """ f: multivariable function with 1 array as parameter x : a vector to start descent delta : precision of search plot : option to plot the results or not F : the function f expressed with 2 arrays in argument (X,Y) representing the colomns x[0] and x[1] for ploting issues. used only if plot == True axlim : limit of the plot axis (x,y,z) """ d = -la.inv(nd.Hessian(f)(x))@nd.Gradient(f)(x) m = nd.Hessian(f)(x) if la.det(m) == 0: return ValueError else : if plot : ax = plt.axes(projection='3d') A = [] t = perf_counter() while la.norm(d) > delta: if plot and len(A) < 10 : A.append(x) phi = lambda s : f(x - s * d) alpha = op.newton(phi, 1) x -= alpha * d dt = nd.Hessian(f)(x) if is_pos_def(f, x) : d = -la.inv(nd.Hessian(f)(x))@nd.Gradient(f)(x) else : u = la.eigvals(f)(x) epsilon = min(u) n = len(x) d = -la.inv((epsilon * np.identity(n) + nd.Hessian(f)(x))) @ nd.Gradient(f)(x) t = perf_counter() - t print("execution time: ",t) if plot : for u in A: ax.scatter(u[0], u[1], f(u), c = 'b', s = 50) ax.scatter(x[0], x[1], f(x), c = 'r', s = 50,label="optimum") x = np.arange(-axlim, axlim, axlim/100) y = np.arange(-axlim, axlim, axlim/100) X, Y = np.meshgrid(x, y) Z = F(X,Y) ax.set_xlabel('x', labelpad=20) ax.set_ylabel('y', labelpad=20) ax.set_zlabel('z', labelpad=20) surf = ax.plot_surface(X, Y, Z, cmap = plt.cm.cividis) plt.legend() plt.title("optimizition with Newton descent") plt.show() return x

38.718121

152

0.543248

906

5,769

3.42936

0.16777

0.015449

0.00869

0.024783

0.760219

0.704538

0.656582

0.630834

0

0.026323

0.32172

5,769

148

153

38.97973

0.767697

0

0.625

0

0.04641

0

null

0

0.0625

null

0.026786

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null

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1

0

1

0

null

0

1

0

5

e5fc6569d6941db8d29c4c65f01b5e4a1ff9b327

11,140

py

Python

grpc/rbindings/node/port/available_core/occupied_frequency_slot/nominal_central_frequency/__init__.py

lrodrin/netopeer

4d9831c3a5481d99cb26b41d02577f53ed93cee1

[ "MIT" ]

1

2018-05-09T09:56:00.000Z

grpc/rbindings/node/port/available_core/occupied_frequency_slot/nominal_central_frequency/__init__.py

lrodrin/netopeer2

4d9831c3a5481d99cb26b41d02577f53ed93cee1

[ "MIT" ]

null

grpc/rbindings/node/port/available_core/occupied_frequency_slot/nominal_central_frequency/__init__.py

lrodrin/netopeer2

4d9831c3a5481d99cb26b41d02577f53ed93cee1

[ "MIT" ]

null

# -*- coding: utf-8 -*- from collections import OrderedDict import six from pyangbind.lib.base import PybindBase from pyangbind.lib.yangtypes import YANGDynClass # PY3 support of some PY2 keywords (needs improved) if six.PY3: import builtins as __builtin__ long = int elif six.PY2: import __builtin__ class nominal_central_frequency(PybindBase): """ This class was auto-generated by the PythonClass plugin for PYANG from YANG module node-topology - based on the path /node/port/available-core/occupied-frequency-slot/nominal-central-frequency. Each member element of the container is represented as a class variable - with a specific YANG type. """ __slots__ = ('_path_helper', '_extmethods', '__grid_type', '__adjustment_granularity', '__channel_number',) _yang_name = 'nominal-central-frequency' _pybind_generated_by = 'container' def __init__(self, *args, **kwargs): self._path_helper = False self._extmethods = False self.__channel_number = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="channel-number", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True) self.__adjustment_granularity = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="adjustment-granularity", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True) self.__grid_type = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="grid-type", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True) load = kwargs.pop("load", None) if args: if len(args) > 1: raise TypeError("cannot create a YANG container with >1 argument") all_attr = True for e in self._pyangbind_elements: if not hasattr(args[0], e): all_attr = False break if not all_attr: raise ValueError("Supplied object did not have the correct attributes") for e in self._pyangbind_elements: nobj = getattr(args[0], e) if nobj._changed() is False: continue setmethod = getattr(self, "_set_%s" % e) if load is None: setmethod(getattr(args[0], e)) else: setmethod(getattr(args[0], e), load=load) def _path(self): if hasattr(self, "_parent"): return self._parent._path() + [self._yang_name] else: return [u'node', u'port', u'available-core', u'occupied-frequency-slot', u'nominal-central-frequency'] def _get_grid_type(self): """ Getter method for grid_type, mapped from YANG variable /node/port/available_core/occupied_frequency_slot/nominal_central_frequency/grid_type (string) """ return self.__grid_type def _set_grid_type(self, v, load=False): """ Setter method for grid_type, mapped from YANG variable /node/port/available_core/occupied_frequency_slot/nominal_central_frequency/grid_type (string) If this variable is read-only (config: false) in the source YANG file, then _set_grid_type is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_grid_type() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v, base=six.text_type, is_leaf=True, yang_name="grid-type", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """grid_type must be of a type compatible with string""", 'defined-type': "string", 'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="grid-type", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True)""", }) self.__grid_type = t if hasattr(self, '_set'): self._set() def _unset_grid_type(self): self.__grid_type = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="grid-type", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True) def _get_adjustment_granularity(self): """ Getter method for adjustment_granularity, mapped from YANG variable /node/port/available_core/occupied_frequency_slot/nominal_central_frequency/adjustment_granularity (string) """ return self.__adjustment_granularity def _set_adjustment_granularity(self, v, load=False): """ Setter method for adjustment_granularity, mapped from YANG variable /node/port/available_core/occupied_frequency_slot/nominal_central_frequency/adjustment_granularity (string) If this variable is read-only (config: false) in the source YANG file, then _set_adjustment_granularity is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_adjustment_granularity() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v, base=six.text_type, is_leaf=True, yang_name="adjustment-granularity", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """adjustment_granularity must be of a type compatible with string""", 'defined-type': "string", 'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="adjustment-granularity", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True)""", }) self.__adjustment_granularity = t if hasattr(self, '_set'): self._set() def _unset_adjustment_granularity(self): self.__adjustment_granularity = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="adjustment-granularity", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True) def _get_channel_number(self): """ Getter method for channel_number, mapped from YANG variable /node/port/available_core/occupied_frequency_slot/nominal_central_frequency/channel_number (string) """ return self.__channel_number def _set_channel_number(self, v, load=False): """ Setter method for channel_number, mapped from YANG variable /node/port/available_core/occupied_frequency_slot/nominal_central_frequency/channel_number (string) If this variable is read-only (config: false) in the source YANG file, then _set_channel_number is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_channel_number() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v, base=six.text_type, is_leaf=True, yang_name="channel-number", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """channel_number must be of a type compatible with string""", 'defined-type': "string", 'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="channel-number", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True)""", }) self.__channel_number = t if hasattr(self, '_set'): self._set() def _unset_channel_number(self): self.__channel_number = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="channel-number", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:node-topology', defining_module='node-topology', yang_type='string', is_config=True) grid_type = __builtin__.property(_get_grid_type, _set_grid_type) adjustment_granularity = __builtin__.property(_get_adjustment_granularity, _set_adjustment_granularity) channel_number = __builtin__.property(_get_channel_number, _set_channel_number) _pyangbind_elements = OrderedDict([('grid_type', grid_type), ('adjustment_granularity', adjustment_granularity), ('channel_number', channel_number), ])

55.979899

317

0.613824

1,226

11,140

5.279772

0.133768

0.040167

0.054071

0.027808

0.725784

0.718987

0.710644

0.701375

0.686544

0

0.001396

0.292729

11,140

198

318

56.262626

0.820155

0.185099

0

0.507463

0

0.022388

0.219512

0.084742

0

1

0.08209

false

0

0.044776

0

0.223881

0

null

0

1

0

null

0

5

f924d4d9604750ab6ae81231d93dd53e871895fa

179

py

Python

src/clickgen/writer/__init__.py

KaizIqbal/clickgen

cab0d0c005c7714cb0271809745a2dae321aa7eb

[ "MIT" ]

2

2020-06-06T03:34:29.000Z

2020-07-29T06:47:23.000Z

src/clickgen/writer/__init__.py

KaizIqbal/clickgen

cab0d0c005c7714cb0271809745a2dae321aa7eb

[ "MIT" ]

null

src/clickgen/writer/__init__.py

KaizIqbal/clickgen

cab0d0c005c7714cb0271809745a2dae321aa7eb

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from clickgen.writer.windows import to_cur, to_win from clickgen.writer.x11 import to_x11 __all__ = ["to_x11", "to_cur", "to_win"]

22.375

50

0.703911

30

179

3.866667

0.566667

0.206897

0.310345

0.172414

0

0.044872

0.128492

179

7

51

25.571429

0.698718

0.234637

0

0.133333

0

1

0

false

0

0.666667

0

0.666667

0

null

1

0

1

0

null

0

1

0

5

0058ba3732b314524e80c12acdab15d79eb5da43

216

py

Python

tests/test_scrot.py

jonringer/pyscreenshot

44cefded198b26fd162ab12c9e947704ec9dced0

[ "BSD-2-Clause" ]

416

2015-01-01T00:41:31.000Z

2022-03-31T10:15:53.000Z

tests/test_scrot.py

jonringer/pyscreenshot

44cefded198b26fd162ab12c9e947704ec9dced0

[ "BSD-2-Clause" ]

72

2015-02-23T20:12:17.000Z

2022-03-02T21:23:17.000Z

tests/test_scrot.py

jonringer/pyscreenshot

44cefded198b26fd162ab12c9e947704ec9dced0

[ "BSD-2-Clause" ]

88

2015-03-04T03:29:43.000Z

2021-10-04T06:37:00.000Z

from bt import backend_to_check, prog_check from pyscreenshot.util import use_x_display if use_x_display(): if prog_check(["scrot", "-version"]): def test_scrot(): backend_to_check("scrot")

24

43

0.694444

31

216

4.483871

0.548387

0.129496

0.201439

0.18705

0

0.199074

216

8

44

27

0.803468

0

0.083333

0

1

0.166667

true

0

0.333333

0

0.5

0

null

0

1

0

1

0

null

0

1

0

1

0

5

006ba0ac5d7fc4e1b99efdd8945123d71ef7be94

51

py

Python

torchero/models/vision/nn/__init__.py

juancruzsosa/torchero

d1440b7a9c3ab2c1d3abbb282abb9ee1ea240797

[ "MIT" ]

10

2020-07-06T13:35:26.000Z

2021-08-10T09:46:53.000Z

torchero/models/vision/nn/__init__.py

juancruzsosa/torchero

d1440b7a9c3ab2c1d3abbb282abb9ee1ea240797

[ "MIT" ]

6

2020-07-07T20:52:16.000Z

2020-07-14T04:05:02.000Z

torchero/models/vision/nn/__init__.py

juancruzsosa/torchero

d1440b7a9c3ab2c1d3abbb282abb9ee1ea240797

[ "MIT" ]

1

2021-06-28T17:56:11.000Z

from torchero.models.vision.nn.torchvision import *

51

0.843137

7

51

6.142857

1

0

0.058824

51

1

51

0.895833

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

00768a9c0a660ba7c4312c9fc74d0210b27f6886

110

py

Python

lanepathy/__init__.py

rqelibari/lanepathgenerator

49f03810f3b52fd5c71ac9f292dbef064536c8d7

[ "Apache-2.0" ]

null

lanepathy/__init__.py

rqelibari/lanepathgenerator

49f03810f3b52fd5c71ac9f292dbef064536c8d7

[ "Apache-2.0" ]

null

lanepathy/__init__.py

rqelibari/lanepathgenerator

49f03810f3b52fd5c71ac9f292dbef064536c8d7

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- import logging.config logging.config.fileConfig('logging.conf')

22

41

0.709091

15

110

5.2

0.8

0.333333

0

0.01

0.090909

110

4

42

27.5

0.77

0.381818

0

0.181818

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

007ef3fcf681e8f77e96e5a41e89d325c3231085

1,745

py

Python

Python/ProjectEuler_08.py

DaanishKS/Project-Euler-Solutions

6150a3e0327bcb15bb7b9fd808c62cf13a35f7d1

[ "MIT" ]

null

Python/ProjectEuler_08.py

DaanishKS/Project-Euler-Solutions

6150a3e0327bcb15bb7b9fd808c62cf13a35f7d1

[ "MIT" ]

null

Python/ProjectEuler_08.py

DaanishKS/Project-Euler-Solutions

6150a3e0327bcb15bb7b9fd808c62cf13a35f7d1

[ "MIT" ]

null

# Largest Product In A Series -- Solved # Solution = 23514624000 from Timer import Timer Stopwatch = Timer() Number = list('73167176531330624919225119674426574742355349194934' '96983520312774506326239578318016984801869478851843' '85861560789112949495459501737958331952853208805511' '12540698747158523863050715693290963295227443043557' '66896648950445244523161731856403098711121722383113' '62229893423380308135336276614282806444486645238749' '30358907296290491560440772390713810515859307960866' '70172427121883998797908792274921901699720888093776' '65727333001053367881220235421809751254540594752243' '52584907711670556013604839586446706324415722155397' '53697817977846174064955149290862569321978468622482' '83972241375657056057490261407972968652414535100474' '82166370484403199890008895243450658541227588666881' '16427171479924442928230863465674813919123162824586' '17866458359124566529476545682848912883142607690042' '24219022671055626321111109370544217506941658960408' '07198403850962455444362981230987879927244284909188' '84580156166097919133875499200524063689912560717606' '05886116467109405077541002256983155200055935729725' '71636269561882670428252483600823257530420752963450') Solution = 0 for i in range(0, len(Number) - 1): p = 1 for j in Number[i:i+13]: p *= int(j) if p > Solution: Solution = p print('The largest product of four adjacent digits in the series is: ', Solution) Stopwatch.stop()

43.625

81

0.711748

78

1,745

15.923077

0.679487

0.022544

0

0.768707

0.241834

1,745

39

82

44.74359

0.170068

0.034384

0

0.631391

0.59453

0

1

0

false

0

0.032258

0

0.032258

0

1

null

0

1

0

1

0

1

null

0

5

9727861837d977667b242a70b609cf093b9cc21e

26

py

Python

test2.py

takumi-lax/HiUbuntu

b930152dc09601c8094612f6996e2bccce287287

[ "MIT" ]

null

test2.py

takumi-lax/HiUbuntu

b930152dc09601c8094612f6996e2bccce287287

[ "MIT" ]

null

test2.py

takumi-lax/HiUbuntu

b930152dc09601c8094612f6996e2bccce287287

[ "MIT" ]

null

print("test") print("aaa")

13

0.653846

4

26

4.25

0.75

0

0.038462

26

2

14

13

0.68

0

0.259259

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py

Python

app/contact/__init__.py

zSelimReborn/TopFlix

236e113dd1edac2ece914cb6622562c3fafa3376

[ "Apache-2.0" ]

null

app/contact/__init__.py

zSelimReborn/TopFlix

236e113dd1edac2ece914cb6622562c3fafa3376

[ "Apache-2.0" ]

3

2020-05-18T16:34:44.000Z

2020-05-18T16:34:45.000Z

app/contact/__init__.py

zSelimReborn/TopFlix

236e113dd1edac2ece914cb6622562c3fafa3376

[ "Apache-2.0" ]

null

from flask import Blueprint bp = Blueprint('contact', __name__) from app.contact import routes

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1

0

1

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5

974fa56e4a0f717c66feb8f72ed181de1a4cb98c

1,094

py

Python

oauth_provider/responses.py

TimSC/django-oauth10a-mod

3b9786b33cbd3d2ab6de7a667f9737167b349db0

[ "BSD-3-Clause" ]

null

oauth_provider/responses.py

TimSC/django-oauth10a-mod

3b9786b33cbd3d2ab6de7a667f9737167b349db0

[ "BSD-3-Clause" ]

null

oauth_provider/responses.py

TimSC/django-oauth10a-mod

3b9786b33cbd3d2ab6de7a667f9737167b349db0

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from __future__ import print_function from django.utils.translation import ugettext as _ from django.http import HttpResponseBadRequest import oauth10a as oauth from oauth_provider.utils import send_oauth_error #INVALID_PARAMS_RESPONSE = send_oauth_error(oauth.Error(_('Invalid request parameters.'))) #INVALID_CONSUMER_RESPONSE = HttpResponseBadRequest('Invalid Consumer.') #INVALID_SCOPE_RESPONSE = send_oauth_error(oauth.Error(_('You are not allowed to access this resource.'))) #COULD_NOT_VERIFY_OAUTH_REQUEST_RESPONSE = send_oauth_error(oauth.Error(_('Could not verify OAuth request.'))) def GetInvalidParamsResponse(): return send_oauth_error(oauth.Error(_('Invalid request parameters.'))) def GetInvalidConsumerResponse(): return HttpResponseBadRequest('Invalid Consumer.') def GetInvalidScopeResponse(): return send_oauth_error(oauth.Error(_('You are not allowed to access this resource.'))) def GetCouldNotVerifyOAuthRequestResponse(): return send_oauth_error(oauth.Error(_('Could not verify OAuth request.')))

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py

Python

tests/Unit/PointwiseFunctions/GeneralRelativity/RicciScalar.py

nilsvu/spectre

1455b9a8d7e92db8ad600c66f54795c29c3052ee

[ "MIT" ]

1

2022-01-11T00:17:33.000Z

tests/Unit/PointwiseFunctions/GeneralRelativity/RicciScalar.py

nilsvu/spectre

1455b9a8d7e92db8ad600c66f54795c29c3052ee

[ "MIT" ]

null

tests/Unit/PointwiseFunctions/GeneralRelativity/RicciScalar.py

nilsvu/spectre

1455b9a8d7e92db8ad600c66f54795c29c3052ee

[ "MIT" ]

null

# Distributed under the MIT License. # See LICENSE.txt for details. import numpy as np def ricci_scalar(ricci_tensor, inverse_metric): ricci_up_down = (np.einsum("cb,ac", ricci_tensor, inverse_metric)) return np.einsum("aa", ricci_up_down)

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0

1

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1

0

5

9784a0db74e372677c3fda94745f6519e96e7736

35

py

Python

test_irsensor.py

tomekceszke/irsensor

c8ae7803af8e2ad6f6fdb6f5565ff839952731b7

[ "Apache-2.0" ]

null

test_irsensor.py

tomekceszke/irsensor

c8ae7803af8e2ad6f6fdb6f5565ff839952731b7

[ "Apache-2.0" ]

null

test_irsensor.py

tomekceszke/irsensor

c8ae7803af8e2ad6f6fdb6f5565ff839952731b7

[ "Apache-2.0" ]

null

import notifier notifier.notify()

8.75

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null

0

1

0

1

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5

97b766ec2f1f366b18d7eaeb3c08370145f33984

167

py

Python

Toca/utils/log.py

olivetree123/Toca

a4b0198046dfbf928e51db3a811bd56aa34b662d

[ "MIT" ]

null

Toca/utils/log.py

olivetree123/Toca

a4b0198046dfbf928e51db3a811bd56aa34b662d

[ "MIT" ]

null

Toca/utils/log.py

olivetree123/Toca

a4b0198046dfbf928e51db3a811bd56aa34b662d

[ "MIT" ]

null

from raven.contrib.flask import Sentry sentry = Sentry() def loginfo(msg, extra=""): # sentry.captureMessage(msg, extra=extra) print(msg, "extra = ", extra)

20.875

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null

0

1

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97bd41f82718848b6ce120362399a86729013fb5

164

py

Python

ac/accounts/admin.py

vietmx/Simple-HR-System

0873fa45d3caef7a8dcee3f2f94de0cd4071c729

[ "MIT" ]

null

ac/accounts/admin.py

vietmx/Simple-HR-System

0873fa45d3caef7a8dcee3f2f94de0cd4071c729

[ "MIT" ]

null

ac/accounts/admin.py

vietmx/Simple-HR-System

0873fa45d3caef7a8dcee3f2f94de0cd4071c729

[ "MIT" ]

null

from django.contrib import admin from .models import Employee, Department # Register your models here. admin.site.register(Employee) admin.site.register(Department)

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5

c11870fac8e15a48256cd22373b015ee3a7d1a8f

7,182

py

Python

tests/test_main.py

dekoza/poetry-version-plugin

89f9aaf02cbdc6a2a5972c07b167e78314ad153b

[ "MIT" ]

176

2021-05-27T10:18:14.000Z

2022-03-25T04:44:10.000Z

tests/test_main.py

dekoza/poetry-version-plugin

89f9aaf02cbdc6a2a5972c07b167e78314ad153b

[ "MIT" ]

19

2021-05-27T10:37:53.000Z

2022-03-25T19:21:01.000Z

tests/test_main.py

Anselmoo/poetry-version-plugin

89f9aaf02cbdc6a2a5972c07b167e78314ad153b

[ "MIT" ]

18

2021-05-28T07:07:45.000Z

2022-02-21T08:02:31.000Z

import shutil import subprocess from pathlib import Path import pkginfo testing_assets = Path(__file__).parent / "assets" plugin_source_dir = Path(__file__).parent.parent / "poetry_version_plugin" def copy_assets(source_name: str, testing_dir: Path): package_path = testing_assets / source_name shutil.copytree(package_path, testing_dir) def build_package(testing_dir: Path): result = subprocess.run( [ "coverage", "run", "--source", str(plugin_source_dir), "--parallel-mode", "-m", "poetry", "build", ], cwd=testing_dir, stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding="utf-8", ) coverage_path = list(testing_dir.glob(".coverage*"))[0] dst_coverage_path = Path(__file__).parent.parent / coverage_path.name dst_coverage_path.write_bytes(coverage_path.read_bytes()) return result def test_defaults(tmp_path: Path): testing_dir = tmp_path / "testing_package" copy_assets("no_packages", testing_dir) result = build_package(testing_dir=testing_dir) assert ( "poetry-version-plugin: Using __init__.py file at " "test_custom_version/__init__.py for dynamic version" in result.stdout ) assert ( "poetry-version-plugin: Setting package dynamic version to __version__ " "variable from __init__.py: 0.0.1" in result.stdout ) assert "Built test_custom_version-0.0.1-py3-none-any.whl" in result.stdout wheel_path = testing_dir / "dist" / "test_custom_version-0.0.1-py3-none-any.whl" info = pkginfo.get_metadata(str(wheel_path)) assert info.version == "0.0.1" def test_custom_packages(tmp_path: Path): testing_dir = tmp_path / "testing_package" copy_assets("custom_packages", testing_dir) result = build_package(testing_dir=testing_dir) assert ( "poetry-version-plugin: Using __init__.py file at custom_package/__init__.py " "for dynamic version" in result.stdout ) assert ( "poetry-version-plugin: Setting package dynamic version to __version__ " "variable from __init__.py: 0.0.2" in result.stdout ) assert "Built test_custom_version-0.0.2-py3-none-any.whl" in result.stdout wheel_path = testing_dir / "dist" / "test_custom_version-0.0.2-py3-none-any.whl" info = pkginfo.get_metadata(str(wheel_path)) assert info.version == "0.0.2" def test_variations(tmp_path: Path): testing_dir = tmp_path / "testing_package" copy_assets("variations", testing_dir) result = build_package(testing_dir=testing_dir) assert ( "poetry-version-plugin: Using __init__.py file at " "test_custom_version/__init__.py for dynamic version" in result.stdout ) assert ( "poetry-version-plugin: Setting package dynamic version to __version__ " "variable from __init__.py: 0.0.3" in result.stdout ) assert "Built test_custom_version-0.0.3-py3-none-any.whl" in result.stdout wheel_path = testing_dir / "dist" / "test_custom_version-0.0.3-py3-none-any.whl" info = pkginfo.get_metadata(str(wheel_path)) assert info.version == "0.0.3" def test_no_version_var(tmp_path: Path): testing_dir = tmp_path / "testing_package" copy_assets("no_version_var", testing_dir) result = build_package(testing_dir=testing_dir) assert ( "poetry-version-plugin: No valid __version__ variable found in __init__.py, " "cannot extract dynamic version" in result.stderr ) assert result.returncode != 0 def test_no_standard_dir(tmp_path: Path): testing_dir = tmp_path / "testing_package" copy_assets("no_standard_dir", testing_dir) result = build_package(testing_dir=testing_dir) assert "poetry-version-plugin: __init__.py file not found at" in result.stderr assert result.returncode != 0 def test_multiple_packages(tmp_path: Path): testing_dir = tmp_path / "testing_package" copy_assets("multiple_packages", testing_dir) result = build_package(testing_dir=testing_dir) assert ( "poetry-version-plugin: More than one package set, cannot extract " "dynamic version" in result.stderr ) assert result.returncode != 0 def test_no_config(tmp_path: Path): testing_dir = tmp_path / "testing_package" copy_assets("no_config", testing_dir) result = build_package(testing_dir=testing_dir) assert "Built test_custom_version-0-py3-none-any.whl" in result.stdout assert result.returncode == 0 def test_no_config_source(tmp_path: Path): testing_dir = tmp_path / "testing_package" copy_assets("no_config_source", testing_dir) result = build_package(testing_dir=testing_dir) assert ( "poetry-version-plugin: No source configuration found in " "[tool.poetry-version-plugin] in pyproject.toml, not extracting dynamic version" ) in result.stderr assert result.returncode != 0 def test_git_tag(tmp_path: Path): testing_dir = tmp_path / "testing_package" copy_assets("git_tag", testing_dir) result = result = subprocess.run( [ "git", "init", ], cwd=testing_dir, stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding="utf-8", ) assert result.returncode == 0 result = result = subprocess.run( ["git", "config", "user.email", "tester@example.com"], cwd=testing_dir, stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding="utf-8", ) assert result.returncode == 0 result = result = subprocess.run( ["git", "config", "user.name", "Tester"], cwd=testing_dir, stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding="utf-8", ) assert result.returncode == 0 result = result = subprocess.run( ["git", "add", "."], cwd=testing_dir, stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding="utf-8", ) assert result.returncode == 0 result = result = subprocess.run( ["git", "commit", "-m", "release"], cwd=testing_dir, stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding="utf-8", ) assert result.returncode == 0 result = build_package(testing_dir=testing_dir) assert "No Git tag found, not extracting dynamic version" in result.stderr assert result.returncode != 0 result = result = subprocess.run( [ "git", "tag", "0.0.9", ], cwd=testing_dir, stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding="utf-8", ) assert result.returncode == 0 result = build_package(testing_dir=testing_dir) assert ( "poetry-version-plugin: Git tag found, setting dynamic version to: 0.0.9" in result.stdout ) assert "Built test_custom_version-0.0.9-py3-none-any.whl" in result.stdout wheel_path = testing_dir / "dist" / "test_custom_version-0.0.9-py3-none-any.whl" info = pkginfo.get_metadata(str(wheel_path)) assert info.version == "0.0.9"

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0.085562

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null

0

1

0

null

0

5

c15a791ef4f30a27822389e5ec7e4741d22a3560

304

py

Python

src/explore.py

Promeos/LADOT-Street-Sweeping-Transition-Pan

eb0d224a7ba910c4bf1db78b9fdb1365de0e6945

[ "MIT" ]

1

2021-02-05T16:05:02.000Z

src/explore.py

Promeos/LADOT-Street-Sweeping-Transition-Plan

eb0d224a7ba910c4bf1db78b9fdb1365de0e6945

[ "MIT" ]

null

src/explore.py

Promeos/LADOT-Street-Sweeping-Transition-Plan

eb0d224a7ba910c4bf1db78b9fdb1365de0e6945

[ "MIT" ]

null

# Import libraries import numpy as np import pandas as pd import plotly.express as px import plotly.graph_objects as go ############################### Global Variables ######################################### ############################### Visualizations ###########################################

30.4

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0.092105

304

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1

0

1

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5

c1a7bcbb73a8d9fe223dbe46f1b93e9339624488

29

py

Python

model.py

arun14anand/practical-coding

676e8d61c0bc437895b0767529d57f1acf8ed14c

[ "MIT" ]

null

model.py

arun14anand/practical-coding

676e8d61c0bc437895b0767529d57f1acf8ed14c

[ "MIT" ]

null

model.py

arun14anand/practical-coding

676e8d61c0bc437895b0767529d57f1acf8ed14c

[ "MIT" ]

1

2021-08-07T18:36:42.000Z

# model file for you to edit

14.5

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1

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0.896552

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null

0

1

0

5

c1b1d02de8d4130edb191088fbcf394f90565160

127

py

Python

modules/liteflownet/__init__.py

adnortje/deepvideo

76d09ee8696355bc29ee57c1ef2ff61474c5ed41

[ "CC0-1.0" ]

37

2019-11-23T06:42:12.000Z

2022-01-25T16:08:28.000Z

modules/liteflownet/__init__.py

sangramch/deepvideo

16e622434b9843238b8092f94da2c58a4346788d

[ "CC0-1.0" ]

4

2020-04-11T12:36:27.000Z

2021-07-26T10:12:53.000Z

modules/liteflownet/__init__.py

sangramch/deepvideo

16e622434b9843238b8092f94da2c58a4346788d

[ "CC0-1.0" ]

9

2019-12-13T07:30:58.000Z

2020-07-15T05:32:17.000Z

# import FlowNet Loss from .eval_flow import EvalFlow from .dense_flow import DenseFlow from .flow_loss import LiteFlowNetLoss

25.4

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39

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1

0

1

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5

c1fe30a46a91a6973ce1caa5224e75111b905e2b

52

py

Python

geographical_module/models/__init__.py

CardoAI/django-geographical-module

596bbfd187022416d82bb129672afc172cf634fb

[ "MIT" ]

2

2022-02-21T11:12:11.000Z

2022-03-01T08:50:52.000Z

geographical_module/models/__init__.py

CardoAI/django-geographical-module

596bbfd187022416d82bb129672afc172cf634fb

[ "MIT" ]

null

geographical_module/models/__init__.py

CardoAI/django-geographical-module

596bbfd187022416d82bb129672afc172cf634fb

[ "MIT" ]

null

from .geography import Geography, GeographyPostcode

26

51

0.865385

5

52

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0.8

0

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52

1

52

0.957447

0

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0

null

0

1

0

1

0

1

0

5

de08f4525a57bc89d7337861c551c24c409f0be6

246

py

Python

torchflare/utils/__init__.py

Atharva-Phatak/torchflare

945f4bee73a855edd8cb19cd646731155499a27f

[ "Apache-2.0" ]

86

2021-04-23T04:55:43.000Z

2022-03-08T05:25:27.000Z

torchflare/utils/__init__.py

Neklaustares-tPtwP/torchflare

7af6b01ef7c26f0277a041619081f6df4eb1e42c

[ "Apache-2.0" ]

252

2021-04-20T21:48:10.000Z

2022-03-31T21:12:05.000Z

torchflare/utils/__init__.py

Atharva-Phatak/torchflare

945f4bee73a855edd8cb19cd646731155499a27f

[ "Apache-2.0" ]

8

2021-04-28T19:57:49.000Z

2021-08-09T02:31:35.000Z

"""Imports for utils.""" from torchflare.utils.average_meter import AverageMeter from torchflare.utils.imports_check import module_available from torchflare.utils.seeder import seed_all __all__ = ["AverageMeter", "seed_all", "module_available"]

35.142857

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1

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null

0

1

0

1

0

5

e749de1249e6f0bb0e8175a0bbd8848f930de18c

265

py

Python

dphsir/denoisers/__init__.py

Zeqiang-Lai/DPHSIR

aef3bdabeed7b900b63a2b9f0a5222458b38554a

[ "MIT" ]

3

2022-02-06T02:44:46.000Z

2022-03-09T01:37:01.000Z

dphsir/denoisers/__init__.py

Zeqiang-Lai/DPHSIR

aef3bdabeed7b900b63a2b9f0a5222458b38554a

[ "MIT" ]

null

dphsir/denoisers/__init__.py

Zeqiang-Lai/DPHSIR

aef3bdabeed7b900b63a2b9f0a5222458b38554a

[ "MIT" ]

null

from .wrapper import (TVDenoiser, FFDNet3DDenoiser, FFDNetDenoiser, IRCNNDenoiser, DRUNetDenoiser, QRNN3DDenoiser, GRUNetDenoiser, GRUNetTVDenoiser) from .composite import Augment, DeepTVDenoiser

44.166667

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16

265

10.5

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265

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e75e2dd4efef9998dac51d7a51b1dc5a1554cf4a

130

py

Python

fresh_slack/main.py

ops-utils/fresh-slack

4befa9b4f9e02877470ae61cebd7a0cc7a9c9cd4

[ "MIT" ]

1

2020-08-06T01:54:33.000Z

fresh_slack/main.py

ops-utils/fresh-slack

4befa9b4f9e02877470ae61cebd7a0cc7a9c9cd4

[ "MIT" ]

null

fresh_slack/main.py

ops-utils/fresh-slack

4befa9b4f9e02877470ae61cebd7a0cc7a9c9cd4

[ "MIT" ]

1

2020-07-06T03:56:38.000Z

from typing import Any def main(): raise Exception def lambda_handler(event: Any, context: Any) -> str: raise Exception

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e7e1d5f6e1b1a2478c7b1c02bf55b441a519fcf6

139

py

Python

Branching_Programs/gamble.py

saratkumar17mss040/Python-lab-programs

a2faa190acaaa30d92d4c801fd53fdc668c3c394

[ "MIT" ]

3

2020-08-26T15:29:18.000Z

2020-09-03T13:49:13.000Z

Branching_Programs/gamble.py

saratkumar17mss040/Python-lab-programs

a2faa190acaaa30d92d4c801fd53fdc668c3c394

[ "MIT" ]

null

Branching_Programs/gamble.py

saratkumar17mss040/Python-lab-programs

a2faa190acaaa30d92d4c801fd53fdc668c3c394

[ "MIT" ]

null

def profitable_gamble(prob, prize, pay): if prob * prize > pay: return True return False print(profitable_gamble(4,8,12))

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null

1

0

1

0

null

0

1

0

5

99b1e991ff06eb9d450d0cbc4b519773218a019b

19

py

Python

ecs_deploy/__init__.py

nahum-litvin-hs/ecs-deploy

76f9cf08aeee447871e078f4606c012a877b7baf

[ "BSD-3-Clause" ]

null

ecs_deploy/__init__.py

nahum-litvin-hs/ecs-deploy

76f9cf08aeee447871e078f4606c012a877b7baf

[ "BSD-3-Clause" ]

1

2021-04-14T07:46:13.000Z

ecs_deploy/__init__.py

hazelops/ecs-deploy

403f215901e5cb8915b22d127089fbded0e32509

[ "BSD-3-Clause" ]

1

2021-07-29T19:11:47.000Z

VERSION = '1.11.3'

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1

0

1

0

null

0

5

99f50437912bdf18ad33a8578d8673e0be01f998

141

py

Python

gpflow/utilities/__init__.py

francescodonato/GPFlow_Keras

896f2edb7a41b77f9cf4e14b040911e82d67b732

[ "Apache-2.0" ]

null

gpflow/utilities/__init__.py

francescodonato/GPFlow_Keras

896f2edb7a41b77f9cf4e14b040911e82d67b732

[ "Apache-2.0" ]

null

gpflow/utilities/__init__.py

francescodonato/GPFlow_Keras

896f2edb7a41b77f9cf4e14b040911e82d67b732

[ "Apache-2.0" ]

null

from .bijectors import * from .misc import * from .multipledispatch import Dispatcher from .traversal import * # from .ops import pca_reduce

23.5

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141

6.111111

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0

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820a8f0cc2147c9588ecef48df18872e91e2f2fb

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py

Python

src/parser/AST/block.py

ARtoriouSs/sanya-script

bb421ce0f32f99eb4f157ca91809eab37ced1630

[ "WTFPL" ]

1

2020-09-23T21:20:47.000Z

src/parser/AST/block.py

ARtoriouSs/sanya-script

bb421ce0f32f99eb4f157ca91809eab37ced1630

[ "WTFPL" ]

null

src/parser/AST/block.py

ARtoriouSs/sanya-script

bb421ce0f32f99eb4f157ca91809eab37ced1630

[ "WTFPL" ]

null

class Block: def __init__(self): self.statements = [] def add_statement(self, statement): self.statements.append(statement)

21.285714

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0.651007

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149

5.75

0.5625

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42

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false

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null

1

0

1

0

null

0

1

0

1

0

5

8215fcc8b189222347fe258beaecf49093ae86eb

577

py

Python

ghost_jukebox/__init__.py

digitaltembo/ghost-jukebox

ab39c4be5ebed1c745ae43922cdc24eae6dedd9c

[ "MIT" ]

null

ghost_jukebox/__init__.py

digitaltembo/ghost-jukebox

ab39c4be5ebed1c745ae43922cdc24eae6dedd9c

[ "MIT" ]

25

2019-03-18T03:13:08.000Z

2022-03-11T23:42:08.000Z

ghost_jukebox/__init__.py

digitaltembo/ghost-jukebox

ab39c4be5ebed1c745ae43922cdc24eae6dedd9c

[ "MIT" ]

null

from flask import Flask from ghost_jukebox import conf, security # initialize Flask app app = Flask(__name__) # Initialize Authorization basic_auth = security.basic_auth home_auth = security.home_auth # Just going to do a one user system for now, with username and password configured in environment variables users = {conf.username: conf.password} app.config['UPLOAD_FOLDER'] = conf.upload_folder import ghost_jukebox.views.home import ghost_jukebox.views.cards import ghost_jukebox.views.music_info import ghost_jukebox.views.player import ghost_jukebox.views.spotify

25.086957

108

0.82149

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577

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0.5

0.157549

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0.251641

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577

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109

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false

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null

0

1

0

null

0

1

0

1

0

5

82255785594eff45b4dcf646a727367644bf6298

202

py

Python

BullColors.py

ajmal017/bull_bot

d0b47619d841e97d68c5e25b96deb9a30db422b6

[ "MIT" ]

1

2020-11-26T00:49:30.000Z

BullColors.py

ajmal017/bull_bot

d0b47619d841e97d68c5e25b96deb9a30db422b6

[ "MIT" ]

null

BullColors.py

ajmal017/bull_bot

d0b47619d841e97d68c5e25b96deb9a30db422b6

[ "MIT" ]

null

# TODO: Just change this to CSS colors = { "text" : "#aaaaaa", "background" : "#222221", "plot_background" : "#222221", "plot_gridlines" : "#777776", "page_background" : "#222221" }

22.444444

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202

5.7

0.75

0.421053

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0

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202

9

35

22.444444

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false

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null

1

0

1

0

null

0

1

0

5

822712af2f45f754f3c144e4d7e3861f13c64241

365

bzl

Python

clang/clang.bzl

quantapix/semtools

dce8840adc86e6a9672447aace969d37e236f922

[ "MIT" ]

null

clang/clang.bzl

quantapix/semtools

dce8840adc86e6a9672447aace969d37e236f922

[ "MIT" ]

null

clang/clang.bzl

quantapix/semtools

dce8840adc86e6a9672447aace969d37e236f922

[ "MIT" ]

null

clang_env = { "ASAN_SYMBOLIZER_PATH": "/usr/local/bin/llvm-symbolizer", "CC": "/usr/local/bin/clang", "GCOV": "/dev/null", "LD_LIBRARY_PATH": "/usr/local/lib", "MSAN_SYMBOLIZER_PATH": "/usr/local/bin/llvm-symbolizer", "TSAN_SYMBOLIZER_PATH": "/usr/local/bin/llvm-symbolizer", "UBSAN_SYMBOLIZER_PATH": "/usr/local/bin/llvm-symbolizer", }

36.5

62

0.671233

48

365

4.875

0.395833

0.205128

0.25641

0.376068

0.666667

0

0.126027

365

9

63

40.555556

0.733542

0

0.726027

0.386301

0

1

0

false

0

null

1

0

1

0

1

0

null

0

5

41707b856d588bc870e01cd123b2de955c976644

33

py

Python

test/test_util/__init__.py

SirWindfield/better-exceptions

a2b920c2d48592150329b816274208cb6c8ff2c0

[ "MIT" ]

4,410

2017-03-12T11:27:56.000Z

2022-03-31T17:39:51.000Z

test/test_util/__init__.py

pralhad88/ng_exception

5d362bccf94b75d748a156e60e0ededb9dd29cbd

[ "MIT" ]

104

2017-03-22T09:29:12.000Z

2022-03-22T01:51:27.000Z

test/test_util/__init__.py

pralhad88/ng_exception

5d362bccf94b75d748a156e60e0ededb9dd29cbd

[ "MIT" ]

243

2017-03-22T09:10:42.000Z

2022-01-11T18:42:46.000Z

# DO NOT ADD AS setup.py MODULE!

16.5

32

0.69697

7

33

3.285714

1

0

0.212121

33

1

33

0.884615

0.909091

0

null

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null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

41ce1831ce9a24b4ee26f91caf9518d6e4dcb822

8,212

py

Python

metaapi/views.py

mark-barrett/RESTBroker

d9b0a3574d2970443fdf40c70ab9ceb8d72614f4

[ "MIT" ]

null

metaapi/views.py

mark-barrett/RESTBroker

d9b0a3574d2970443fdf40c70ab9ceb8d72614f4

[ "MIT" ]

null

metaapi/views.py

mark-barrett/RESTBroker

d9b0a3574d2970443fdf40c70ab9ceb8d72614f4

[ "MIT" ]

null

import json import random import string import MySQLdb from django.http import HttpResponse from django.shortcuts import render, redirect from django.views import View import MySQLdb as db from api.models import APIKey class Profiles(View): def get(self, request): conn = db.connect(host='35.241.219.62', port=3306, user='mark', password='password123', database='main', cursorclass=MySQLdb.cursors.DictCursor) cursor = conn.cursor() query = "SELECT * FROM profiles" # Get all of the tables in that database cursor.execute("SELECT * FROM profiles") response = [] for row in cursor: response.append(row) conn.close() return HttpResponse(json.dumps(response), content_type='application/json', status=200) class Posts(View): def get(self, request): conn = db.connect(host='35.241.219.62', port=3306, user='mark', password='password123', database='main', cursorclass=MySQLdb.cursors.DictCursor) cursor = conn.cursor() query = "SELECT * FROM posts" # Get all of the tables in that database cursor.execute("SELECT * FROM posts") response = [] for row in cursor: response.append(row) conn.close() return HttpResponse(json.dumps(response), content_type='application/json', status=200) class Comments(View): def get(self, request): conn = db.connect(host='35.241.219.62', port=3306, user='mark', password='password123', database='main', cursorclass=MySQLdb.cursors.DictCursor) cursor = conn.cursor() query = "SELECT * FROM comments" # Get all of the tables in that database cursor.execute("SELECT * FROM comments") response = [] for row in cursor: response.append(row) conn.close() return HttpResponse(json.dumps(response), content_type='application/json', status=200) class GenerateAPIKey(View): def get(self, request): return redirect('/') def post(self, request): try: if 'master_key' not in request.POST: response = { 'message': 'The projects master key must be sent in the master_key field to generate a new API key.' } return HttpResponse(json.dumps(response), content_type='application/json', status=403) else: # Try get the API key try: mstr_api_key = APIKey.objects.get(key=request.POST['master_key']) # We found it project = mstr_api_key.project # Generate an API key if project.type == 'private': # Now that a project has been created lets generate an API key for it. api_key_not_found = True key = '' while api_key_not_found: key = ''.join(random.choices(string.ascii_uppercase + string.digits, k=32)) key = 'rb_nrm_key_' + key try: api_key = APIKey.objects.get(key=key) except: api_key_not_found = False api_key = APIKey( key=key, user=mstr_api_key.user, project=project, master=False ) api_key.save() response = { 'api_key': api_key.key, 'message': 'Successfully generated API key.' } return HttpResponse(json.dumps(response), content_type='application/json', status=200) except Exception as e: print(e) response = { 'message': 'Cannot generate key, invalid master key.' } return HttpResponse(json.dumps(response), content_type='application/json', status=403) except Exception as e: response = { 'message': e } return HttpResponse(json.dumps(response), content_type='application/json', status=403) class RegenerateAPIKey(View): def get(self, request): return redirect('/') def post(self, request, nrm_key): try: if 'master_key' not in request.POST: response = { 'message': 'The projects master key must be sent in the master_key field to generate a new API key.' } return HttpResponse(json.dumps(response), content_type='application/json', status=403) else: # Try get the API key try: mstr_api_key = APIKey.objects.get(key=request.POST['master_key']) project = mstr_api_key.project try: api_key = APIKey.objects.get(key=nrm_key) # Now that a project has been created lets generate an API key for it. api_key_not_found = True key = '' while api_key_not_found: key = ''.join(random.choices(string.ascii_uppercase + string.digits, k=32)) # If not use the normal one key = 'rb_nrm_key_' + key try: other_api_key = APIKey.objects.get(key=key) except: api_key_not_found = False api_key.key = key api_key.save() response = { 'api_key': api_key.key, 'message': 'Successfully regenerated API Key.' } return HttpResponse(json.dumps(response), content_type='application/json', status=200) except: response = { 'message': 'The key you are trying to regenerate does not exist.' } return HttpResponse(json.dumps(response), content_type='application/json', status=403) except Exception as e: print(e) response = { 'message': 'Cannot generate key, invalid master key.' } return HttpResponse(json.dumps(response), content_type='application/json', status=403) except Exception as e: response = { 'message': e } return HttpResponse(json.dumps(response), content_type='application/json', status=403) class GetAllAPIKeys(View): def get(self, request, master_key): # Check that the master key is valid try: api_key = APIKey.objects.get(key=master_key) keys = [] api_keys_from_project = APIKey.objects.all().filter(project=api_key.project) for proj_api_key in api_keys_from_project: if 'rb_mstr_key_' not in proj_api_key.key: single_key = { 'key': proj_api_key.key, 'created_at': str(proj_api_key.created_at), } keys.append(single_key) # Return them return HttpResponse(json.dumps(keys), content_type='application/json', status=400) except Exception as e: print(e) response = { 'message': 'Cannot get API keys, invalid master key.' } return HttpResponse(json.dumps(response), content_type='application/json', status=403)

31.829457

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0.500974

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8,212

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0.094053

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0.737995

0

0.020179

0.414637

8,212

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31.953307

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0.048587

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0.631902

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false

0.018405

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0.018405

0

null

0

1

0

null

0

5

ec0ad2fcaf36cca8f8272726b06de417ea8389e0

112

py

Python

jsonWebToken/__init__.py

No9005/jwt

411e27819bb3603e3dca021775286f573562964d

[ "MIT" ]

null

jsonWebToken/__init__.py

No9005/jwt

411e27819bb3603e3dca021775286f573562964d

[ "MIT" ]

null

jsonWebToken/__init__.py

No9005/jwt

411e27819bb3603e3dca021775286f573562964d

[ "MIT" ]

null

""" Package to handle the creation of signed Json web tokens """ from .algorithmn import with_rsa, with_secret

16

45

0.767857

17

112

4.941176

0.941176

0

0.160714

112

7

45

16

0.893617

0.5

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

ec1b641e45e460febe2ddbf469c129d449b9044e

167

py

Python

DesignPatterns/FactoryPattern/SimpleFactory/autos/kia.py

Py-Himanshu-Patel/Learn-Python

47a50a934cabcce3b1cbdd4c88141a51f21d3a05

[ "MIT" ]

null

DesignPatterns/FactoryPattern/SimpleFactory/autos/kia.py

Py-Himanshu-Patel/Learn-Python

47a50a934cabcce3b1cbdd4c88141a51f21d3a05

[ "MIT" ]

null

DesignPatterns/FactoryPattern/SimpleFactory/autos/kia.py

Py-Himanshu-Patel/Learn-Python

47a50a934cabcce3b1cbdd4c88141a51f21d3a05

[ "MIT" ]

null

from .abstract_auto import AbstractAuto class Kia(AbstractAuto): def start(self): print("Kia started") def stop(self): print("Kia stopped")

16.7

39

0.646707

20

167

5.35

0.7

0.168224

0.224299

0

0.245509

167

9

40

18.555556

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0

0.131737

0

1

0.333333

false

0

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0.666667

0.333333

1

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0

1

0

1

0

null

0

1

0

1

0

5

ec57570758437ef5800c0019f0ad56a75857a8c0

56

py

Python

causallib/contrib/adversarial_balancing/__init__.py

liranszlak/causallib

2636149f6b1e307672aff638a53f8eaf2be56bc9

[ "Apache-2.0" ]

350

2019-06-19T15:56:19.000Z

2022-03-28T23:47:46.000Z

causallib/contrib/adversarial_balancing/__init__.py

daveh19/causallib

af4bd82be0a65b457bea435da70a10bb0013d4bf

[ "Apache-2.0" ]

13

2019-08-14T22:04:21.000Z

2022-03-14T07:44:12.000Z

causallib/contrib/adversarial_balancing/__init__.py

daveh19/causallib

af4bd82be0a65b457bea435da70a10bb0013d4bf

[ "Apache-2.0" ]

48

2019-11-02T16:40:56.000Z

2022-02-09T12:55:12.000Z

from .adversarial_balancing import AdversarialBalancing

28

55

0.910714

5

56

10

1

0

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56

1

56

0.961538

0

1

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true

0

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1

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1

0

null

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1

0

null

0

1

0

1

0

1

0

5

6b944265f80cc4266e27df00e25b0060e67fc0d4

42

py

Python

yard/skills/66-python/cookbook/yvhai/demo/std/ds/deque.py

paser4se/bbxyard

d09bc6efb75618b2cef047bad9c8b835043446cb

[ "Apache-2.0" ]

1

2016-03-29T02:01:58.000Z

yard/skills/66-python/cookbook/yvhai/demo/std/ds/deque.py

paser4se/bbxyard

d09bc6efb75618b2cef047bad9c8b835043446cb

[ "Apache-2.0" ]

18

2019-02-13T09:15:25.000Z

2021-12-09T21:32:13.000Z

yard/skills/66-python/cookbook/yvhai/demo/std/ds/deque.py

paser4se/bbxyard

d09bc6efb75618b2cef047bad9c8b835043446cb

[ "Apache-2.0" ]

2

2020-07-05T01:01:30.000Z

2020-07-08T22:33:06.000Z

from ..collections.deque import DequeDemo

21

41

0.833333

5

42

7

1

0

0.095238

42

1

42

0.921053

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

6bb34a6cb8d092b3904b3135ab1a8eaefcae0dab

171

py

Python

lairgpt/__init__.py

lightonai/lairgpt

7580e1339a39662b2ff636d158c36195eb7fe3fb

[ "MIT" ]

19

2021-05-04T13:54:45.000Z

2022-01-05T15:45:12.000Z

lairgpt/__init__.py

lightonai/lairgpt

7580e1339a39662b2ff636d158c36195eb7fe3fb

[ "MIT" ]

null

lairgpt/__init__.py

lightonai/lairgpt

7580e1339a39662b2ff636d158c36195eb7fe3fb

[ "MIT" ]

1

2021-05-28T15:25:12.000Z

from lairgpt.gpt_model import LairGPT from lairgpt.text_generator import TextGenerator from lairgpt.models import PAGnol lairgpt = ["LairGPT", "TextGenerator", "PAGnol"]

28.5

48

0.812865

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171

6.52381

0.47619

0.240876

0

0.105263

171

5

49

34.2

0.895425

0

0.152047

0

1

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5

6bb4b0da36388d2953013d21efd89b5fdd126248

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py

Python

blobcity/main/__init__.py

sreyan-ghosh/autoai

8351788adf3e2a126500d03a07f69525936299ac

[ "Apache-2.0" ]

1

2021-10-06T05:26:14.000Z

blobcity/main/__init__.py

sreyan-ghosh/autoai

8351788adf3e2a126500d03a07f69525936299ac

[ "Apache-2.0" ]

null

blobcity/main/__init__.py

sreyan-ghosh/autoai

8351788adf3e2a126500d03a07f69525936299ac

[ "Apache-2.0" ]

null

from .driver import * from .modelSelection import *

25.5

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5

6bc0337e95ba3ae7e285197fa8865e87d07c0248

245

py

Python

myproject/boards/pyimports.py

scaraclette/WebBoard

e35cec96589063e75fcba52898fadfa4e3f961fd

[ "MIT" ]

1

2019-12-14T20:32:17.000Z

myproject/boards/pyimports.py

scaraclette/WebBoard

e35cec96589063e75fcba52898fadfa4e3f961fd

[ "MIT" ]

5

2021-03-19T08:34:20.000Z

2022-02-10T10:15:32.000Z

myproject/boards/pyimports.py

scaraclette/WebBoard

e35cec96589063e75fcba52898fadfa4e3f961fd

[ "MIT" ]

null

from django.urls import reverse,resolve from django.test import TestCase from .views import home, board_topics, new_topic from .models import Board, Topic, Post from django.test import Client, TestCase from django.contrib.auth.models import User

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5

6bcabb66a13dc3d0049c0395fbdecbad1990bad8

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py

Python

gui/views/drawables/__init__.py

frlnx/melee

db2670453771c6d3635e97e28bb8667b14643b05

[ "CC0-1.0" ]

null

gui/views/drawables/__init__.py

frlnx/melee

db2670453771c6d3635e97e28bb8667b14643b05

[ "CC0-1.0" ]

null

gui/views/drawables/__init__.py

frlnx/melee

db2670453771c6d3635e97e28bb8667b14643b05

[ "CC0-1.0" ]

null

from .drawable import Drawable

30

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null

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0

5

6bf610a25444be6b6b8fce8862dd00faeefb8726

407

py

Python

hubspot/crm/objects/feedback_submissions/api/__init__.py

cclauss/hubspot-api-python

7c60c0f572b98c73e1f1816bf5981396a42735f6

[ "Apache-2.0" ]

117

2020-04-06T08:22:53.000Z

2022-03-18T03:41:29.000Z

hubspot/crm/objects/feedback_submissions/api/__init__.py

cclauss/hubspot-api-python

7c60c0f572b98c73e1f1816bf5981396a42735f6

[ "Apache-2.0" ]

62

2020-04-06T16:21:06.000Z

2022-03-17T16:50:44.000Z

hubspot/crm/objects/feedback_submissions/api/__init__.py

cclauss/hubspot-api-python

7c60c0f572b98c73e1f1816bf5981396a42735f6

[ "Apache-2.0" ]

45

2020-04-06T16:13:52.000Z

2022-03-30T21:33:17.000Z

from __future__ import absolute_import # flake8: noqa # import apis into api package from hubspot.crm.objects.feedback_submissions.api.associations_api import AssociationsApi from hubspot.crm.objects.feedback_submissions.api.basic_api import BasicApi from hubspot.crm.objects.feedback_submissions.api.batch_api import BatchApi from hubspot.crm.objects.feedback_submissions.api.search_api import SearchApi

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