xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

c10f80b1fa4a2bebbb5d28f85d6e88dd5d049df2

112

py

Python

start.py

quadrixm/ya

621f7c12f0bfdcca49068177cfa6e0025f3a3bae

[ "MIT" ]

22

2019-01-26T15:52:24.000Z

2021-11-11T22:24:21.000Z

start.py

quadrixm/ya

621f7c12f0bfdcca49068177cfa6e0025f3a3bae

[ "MIT" ]

1

2018-07-31T05:39:19.000Z

start.py

quadrixm/ya

621f7c12f0bfdcca49068177cfa6e0025f3a3bae

[ "MIT" ]

1

2018-07-31T05:30:02.000Z

import sys import src.main as mn if __name__ == '__main__': file_name = sys.argv[1] mn.main(file_name)

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c11ead25e4f1ab4232dafcde49692b6c9dcffe6e

3,666

py

Python

examples/drawing/draw_connector.py

xxao/pero

a7f0c84fae0b21fe120204e798bd61cdab3a125d

[ "MIT" ]

13

2019-07-15T17:51:21.000Z

2022-03-15T06:13:43.000Z

examples/drawing/draw_connector.py

xxao/pero

a7f0c84fae0b21fe120204e798bd61cdab3a125d

[ "MIT" ]

1

2021-12-29T00:46:44.000Z

2022-01-21T16:18:48.000Z

examples/drawing/draw_connector.py

xxao/pero

a7f0c84fae0b21fe120204e798bd61cdab3a125d

[ "MIT" ]

3

2020-09-27T14:31:45.000Z

2022-01-22T14:28:15.000Z

# Created byMartin.cz # Copyright (c) Martin Strohalm. All rights reserved. import pero class DrawTest(pero.Graphics): """Test case for connector arrows drawing.""" def draw(self, canvas, *args, **kwargs): """Draws the test.""" # clear canvas canvas.fill(pero.colors.White) # set properties arrow_size = 15 line_color = pero.colors.Blue start_fill_color = pero.colors.Red.opaque(0.25) end_fill_color = pero.colors.Blue.opaque(0.25) # init arrow arrow = pero.ConnectorArrow(line_color=line_color) arrow.start_head = pero.NormalHead(size=arrow_size, line_color=line_color, fill_color=start_fill_color) arrow.end_head = pero.NormalHead(size=arrow_size, line_color=line_color, fill_color=end_fill_color) # init coords x = 50 y1 = 40 y2 = 140 # draw guides canvas.line_color = pero.colors.Red canvas.draw_line(20, y1, 660, y1) canvas.draw_line(20, y2, 660, y2) # test horizontal connector arrow arrow.draw(canvas, x1=x-25, y1=y1, x2=x+25, y2=y2, orientation=pero.ORI_HORIZONTAL) x += 70 arrow.draw(canvas, x1=x+25, y1=y1, x2=x-25, y2=y2, orientation=pero.ORI_HORIZONTAL) # test vertical connector arrow x += 100 arrow.draw(canvas, x1=x-25, y1=y1, x2=x+25, y2=y2, orientation=pero.ORI_VERTICAL) x += 70 arrow.draw(canvas, x1=x+25, y1=y1, x2=x-25, y2=y2, orientation=pero.ORI_VERTICAL) # test horizontal curved connector arrow x += 100 arrow.draw(canvas, x1=x-30, y1=y1, x2=x+30, y2=y2, curve=1, orientation=pero.ORI_HORIZONTAL) x += 70 arrow.draw(canvas, x1=x+30, y1=y1, x2=x-30, y2=y2, curve=1, orientation=pero.ORI_HORIZONTAL) # test vertical curved connector arrow x += 100 arrow.draw(canvas, x1=x-25, y1=y1, x2=x+25, y2=y2, curve=1, orientation=pero.ORI_VERTICAL) x += 70 arrow.draw(canvas, x1=x+25, y1=y1, x2=x-25, y2=y2, curve=1, orientation=pero.ORI_VERTICAL) x = 50 y1 += 150 y2 += 150 # draw guides canvas.line_color = pero.colors.Red canvas.draw_line(20, y1, 660, y1) canvas.draw_line(20, y2, 660, y2) # test horizontal connector arrow arrow.draw(canvas, x1=x-20, y1=y1, x2=x+20, y2=y2, pivot=0, orientation=pero.ORI_HORIZONTAL) x += 20 arrow.draw(canvas, x1=x-20, y1=y1, x2=x+20, y2=y2, pivot=1, orientation=pero.ORI_HORIZONTAL) # test vertical connector arrow x += 100 arrow.draw(canvas, x1=x-20, y1=y1, x2=x+20, y2=y2, pivot=0, orientation=pero.ORI_VERTICAL) x += 70 arrow.draw(canvas, x1=x-20, y1=y1, x2=x+20, y2=y2, pivot=1, orientation=pero.ORI_VERTICAL) # test horizontal curved connector arrow x += 100 arrow.draw(canvas, x1=x-40, y1=y1, x2=x+40, y2=y2, pivot=0, curve=1, orientation=pero.ORI_HORIZONTAL) x += 20 arrow.draw(canvas, x1=x-40, y1=y1, x2=x+40, y2=y2, pivot=1, curve=1, orientation=pero.ORI_HORIZONTAL) # test vertical curved connector arrow x += 100 arrow.draw(canvas, x1=x-40, y1=y1, x2=x+40, y2=y2, pivot=0, curve=1, orientation=pero.ORI_VERTICAL) x += 70 arrow.draw(canvas, x1=x-40, y1=y1, x2=x+40, y2=y2, pivot=1, curve=1, orientation=pero.ORI_VERTICAL) # run test if __name__ == '__main__': pero.debug(DrawTest(), 'show', "Connector Arrows", 680, 330)

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py

Python

loguniform/__init__.py

j-faria/LogUniform

caed56d92eed0bd9398c11eb88ce2476077a6ffa

[ "MIT" ]

1

2021-07-09T01:49:33.000Z

loguniform/__init__.py

j-faria/LogUniform

caed56d92eed0bd9398c11eb88ce2476077a6ffa

[ "MIT" ]

2

2018-05-25T13:43:13.000Z

2021-05-14T17:18:11.000Z

loguniform/__init__.py

j-faria/LogUniform

caed56d92eed0bd9398c11eb88ce2476077a6ffa

[ "MIT" ]

null

from .LogUniform import LogUniform, ModifiedLogUniform

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py

Python

null/__init__.py

SilverStrange/NullChecker

ac70724b3d55fc845d207ee22524e3544b5b6f0b

[ "MIT" ]

null

null/__init__.py

SilverStrange/NullChecker

ac70724b3d55fc845d207ee22524e3544b5b6f0b

[ "MIT" ]

null

null/__init__.py

SilverStrange/NullChecker

ac70724b3d55fc845d207ee22524e3544b5b6f0b

[ "MIT" ]

null

from .file import File from .scan import scan, create_workers from .config import create_default_config, read_config from .options import parse_args from .defaults import Default

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c13e50e4836dc71e4a9e1be518e0fe6c77db793f

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py

Python

Test/game/graphic/render.py

twodulls/pythonsample

f576f79be75d96df61e26ef79a0e36a6feedfec1

[ "Apache-2.0" ]

null

Test/game/graphic/render.py

twodulls/pythonsample

f576f79be75d96df61e26ef79a0e36a6feedfec1

[ "Apache-2.0" ]

null

Test/game/graphic/render.py

twodulls/pythonsample

f576f79be75d96df61e26ef79a0e36a6feedfec1

[ "Apache-2.0" ]

null

from ..sound.echo import echo_test def render_test(): print("render") echo_test()

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py

Python

context_propagation_python/context.py

AminoApps/context-propagation-python

ddde90d468c43e669c0c0a325e0127d9a755e1a6

[ "Apache-2.0" ]

null

context_propagation_python/context.py

AminoApps/context-propagation-python

ddde90d468c43e669c0c0a325e0127d9a755e1a6

[ "Apache-2.0" ]

null

context_propagation_python/context.py

AminoApps/context-propagation-python

ddde90d468c43e669c0c0a325e0127d9a755e1a6

[ "Apache-2.0" ]

1

2020-01-21T09:13:39.000Z

from context_propagation_python.constants import THREAD_LOCAL_CONTEXT def set_context(carrier): THREAD_LOCAL_CONTEXT.context = carrier def get_context(): if hasattr(THREAD_LOCAL_CONTEXT, 'context'): return {k: v for k, v in THREAD_LOCAL_CONTEXT.context.items()} else: return dict()

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c1787daaed1c52ecc5ced43e836b3b1f95392a0c

21

py

Python

ctrl/__init__.py

sirhcsenots/ctrl

86e960b9948aa6a78f3eea9f7571ebb868e4ee06

[ "MIT" ]

null

ctrl/__init__.py

sirhcsenots/ctrl

86e960b9948aa6a78f3eea9f7571ebb868e4ee06

[ "MIT" ]

null

ctrl/__init__.py

sirhcsenots/ctrl

86e960b9948aa6a78f3eea9f7571ebb868e4ee06

[ "MIT" ]

null

# Control Everything

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5

c1a027700785bdf5ee7c151b0e15f48a00bdca19

305

py

Python

capstone/capapi/tests/test_documents.py

truthiswill/capstone

61b17611ebee17a5f5e4f64ae4ccaa67ac357478

[ "MIT" ]

null

capstone/capapi/tests/test_documents.py

truthiswill/capstone

61b17611ebee17a5f5e4f64ae4ccaa67ac357478

[ "MIT" ]

4

2021-09-02T20:54:31.000Z

2022-02-27T14:04:06.000Z

capstone/capapi/tests/test_documents.py

whitemike889/capstone

61b17611ebee17a5f5e4f64ae4ccaa67ac357478

[ "MIT" ]

null

import pytest from capdb.models import CaseMetadata @pytest.mark.django_db def test_case_document_full_cite(client, whitelisted_case_document, ingest_metadata): case = CaseMetadata.objects.get(name=whitelisted_case_document.name) assert case.full_cite() == whitelisted_case_document.full_cite()

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c1a4aae6d2e94b66399d559e3876300c990bf459

214

py

Python

nighres/laminar/__init__.py

jennydaman/nighres

9ced74e61db02261e4753a69b03f4479bfdc26b6

[ "Apache-2.0" ]

null

nighres/laminar/__init__.py

jennydaman/nighres

9ced74e61db02261e4753a69b03f4479bfdc26b6

[ "Apache-2.0" ]

null

nighres/laminar/__init__.py

jennydaman/nighres

9ced74e61db02261e4753a69b03f4479bfdc26b6

[ "Apache-2.0" ]

null

from nighres.laminar.volumetric_layering import volumetric_layering from nighres.laminar.profile_sampling import profile_sampling from nighres.laminar.laminar_iterative_smoothing import laminar_iterative_smoothing

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c1ec953bd09bba5f0eae1471c670435dfda84e69

775

py

Python

scripts/template.py

calmisential/SkeNetch

c014b9d2caa0a3a9809b437c957cea3b73af685d

[ "Apache-2.0" ]

1

2021-12-14T07:26:28.000Z

scripts/template.py

calmisential/SkeNetch

c014b9d2caa0a3a9809b437c957cea3b73af685d

[ "Apache-2.0" ]

null

scripts/template.py

calmisential/SkeNetch

c014b9d2caa0a3a9809b437c957cea3b73af685d

[ "Apache-2.0" ]

1

2021-12-14T07:26:30.000Z

from abc import ABCMeta, abstractmethod class ITrainer(metaclass=ABCMeta): @abstractmethod def _set_model(self, *args, **kwargs): pass @abstractmethod def _set_train_dataloader(self, *args, **kwargs): pass @abstractmethod def _set_optimizer(self, *args, **kwargs): pass @abstractmethod def _set_lr_scheduler(self, *args, **kwargs): pass @abstractmethod def load(self, *args, **kwargs): pass @abstractmethod def _save(self, *args, **kwargs): pass @abstractmethod def train(self, *args, **kwargs): pass @abstractmethod def test(self, *args, **kwargs): pass @abstractmethod def forward_pipeline(self, *args, **kwargs): pass

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c1f4b3171e1ece7d1f469fa18639ac8dd4caf4f3

324

py

Python

plx_gpib_ethernet/__init__.py

snhobbs/prologix-gpib-ethernet

1cf5f673447d16bdcb359ef46258333f38b8a37f

[ "MIT" ]

23

2017-02-27T02:09:45.000Z

2022-03-30T11:17:10.000Z

plx_gpib_ethernet/__init__.py

snhobbs/prologix-gpib-ethernet

1cf5f673447d16bdcb359ef46258333f38b8a37f

[ "MIT" ]

5

2017-09-27T13:41:15.000Z

2021-03-07T09:13:14.000Z

plx_gpib_ethernet/__init__.py

snhobbs/prologix-gpib-ethernet

1cf5f673447d16bdcb359ef46258333f38b8a37f

[ "MIT" ]

9

2017-12-14T10:27:54.000Z

2021-01-05T03:20:52.000Z

from .plx_gpib_ethernet import PrologixGPIBEthernet from .plx_gpib_ethernet_device import PrologixGPIBEthernetDevice from .version import __version__ __all__ = ['plx_gpib_ethernet', 'plx_gpib_ethernet_device', 'PrologixGPIBEthernet', 'PrologixGPIBEthernetDevice', '__version__']

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c1fa7c697472265c7b1596a261fd7f91163fbc94

134

py

Python

feature-demos/slicing.py

t4d-classes/python_03152021

41c0e688a895d6986422dfd0b60b38f356414f31

[ "MIT" ]

null

feature-demos/slicing.py

t4d-classes/python_03152021

41c0e688a895d6986422dfd0b60b38f356414f31

[ "MIT" ]

null

feature-demos/slicing.py

t4d-classes/python_03152021

41c0e688a895d6986422dfd0b60b38f356414f31

[ "MIT" ]

null

letters = [chr(num) for num in range(65, 91)] # print(letters) print(letters[-10:-3]) print(letters[10:-5:2]) # print(letters[8])

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de0fbb592d2d631109d3deed89407743c4053fba

233

py

Python

pirates/battle/DefenseRepeaterCannon.py

Willy5s/Pirates-Online-Rewritten

7434cf98d9b7c837d57c181e5dabd02ddf98acb7

[ "BSD-3-Clause" ]

81

2018-04-08T18:14:24.000Z

2022-01-11T07:22:15.000Z

pirates/battle/DefenseRepeaterCannon.py

Willy5s/Pirates-Online-Rewritten

7434cf98d9b7c837d57c181e5dabd02ddf98acb7

[ "BSD-3-Clause" ]

4

2018-09-13T20:41:22.000Z

2022-01-08T06:57:00.000Z

pirates/battle/DefenseRepeaterCannon.py

Willy5s/Pirates-Online-Rewritten

7434cf98d9b7c837d57c181e5dabd02ddf98acb7

[ "BSD-3-Clause" ]

26

2018-05-26T12:49:27.000Z

2021-09-11T09:11:59.000Z

from pandac.PandaModules import * from pirates.battle.DefenseCannon import DefenseCannon class DefenseRepeaterCannon(DefenseCannon): def __init__(self, cr, shipCannon=False): DefenseCannon.__init__(self, cr, shipCannon)

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py

Python

api/__init__.py

yydcnjjw/anki-jp-tools

ddebd98f5c6f8b1a91020f558fc2ae7644739fd6

[ "Apache-2.0" ]

null

api/__init__.py

yydcnjjw/anki-jp-tools

ddebd98f5c6f8b1a91020f558fc2ae7644739fd6

[ "Apache-2.0" ]

null

api/__init__.py

yydcnjjw/anki-jp-tools

ddebd98f5c6f8b1a91020f558fc2ae7644739fd6

[ "Apache-2.0" ]

null

from .api import api_call

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a9c3380e9a153fdb6811f8cac8c9022929b1d78b

28,171

py

Python

calliope/backend/pyomo/constraints/group.py

guidogz/Calliope_guido

148ee39c3671e55ad3a1a2da216ee23112d16abf

[ "Apache-2.0" ]

null

calliope/backend/pyomo/constraints/group.py

guidogz/Calliope_guido

148ee39c3671e55ad3a1a2da216ee23112d16abf

[ "Apache-2.0" ]

null

calliope/backend/pyomo/constraints/group.py

guidogz/Calliope_guido

148ee39c3671e55ad3a1a2da216ee23112d16abf

[ "Apache-2.0" ]

null

""" Copyright (C) 2013-2019 Calliope contributors listed in AUTHORS. Licensed under the Apache 2.0 License (see LICENSE file). group.py ~~~~~~~~ Group constraints. """ import logging import numpy as np import pyomo.core as po # pylint: disable=import-error from calliope.backend.pyomo.util import loc_tech_is_in, get_param logger = logging.getLogger(__name__) ORDER = 20 # order in which to invoke constraints relative to other constraint files def return_noconstraint(*args): logger.debug('group constraint returned NoConstraint: {}'.format(','.join(args))) return po.Constraint.NoConstraint def load_constraints(backend_model): model_data_dict = backend_model.__calliope_model_data['data'] for sense in ['min', 'max', 'equals']: if 'group_energy_cap_share_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_energy_cap_share_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_energy_cap_share_{}'.format(sense)), [sense], rule=energy_cap_share_constraint_rule ) ) if 'group_energy_cap_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_energy_cap_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_energy_cap_{}'.format(sense)), [sense], rule=energy_cap_constraint_rule ) ) if 'group_resource_area_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_resource_area_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_resource_area_{}'.format(sense)), [sense], rule=resource_area_constraint_rule ) ) if 'group_carrier_prod_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_carrier_prod_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_carrier_prod_{}'.format(sense)), backend_model.carriers, [sense], rule=carrier_prod_constraint_rule ) ) if 'group_demand_share_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_demand_share_{}_constraint'.format(sense), po.Constraint(getattr(backend_model, 'group_names_demand_share_{}'.format(sense)), backend_model.carriers, [sense], rule=demand_share_constraint_rule) ) if 'group_demand_share_per_timestep_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_demand_share_per_timestep_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_demand_share_per_timestep_{}'.format(sense)), backend_model.carriers, backend_model.timesteps, [sense], rule=demand_share_per_timestep_constraint_rule ) ) if 'group_carrier_prod_share_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_carrier_prod_share_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_carrier_prod_share_{}'.format(sense)), backend_model.carriers, [sense], rule=carrier_prod_share_constraint_rule ) ) if 'group_carrier_prod_share_per_timestep_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_carrier_prod_share_per_timestep_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_carrier_prod_share_per_timestep_{}'.format(sense)), backend_model.carriers, backend_model.timesteps, [sense], rule=carrier_prod_share_per_timestep_constraint_rule ) ) if 'group_net_import_share_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_net_import_share_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_net_import_share_{}'.format(sense)), backend_model.carriers, [sense], rule=net_import_share_constraint_rule ) ) if 'group_cost_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_cost_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_cost_{}'.format(sense)), backend_model.costs, [sense], rule=cost_cap_constraint_rule ) ) if 'group_cost_var_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_cost_var_{}_constraint'.format(sense), po.Constraint(getattr(backend_model, 'group_names_cost_var_{}'.format(sense)), backend_model.costs, [sense], rule=cost_var_cap_constraint_rule) ) if 'group_cost_investment_{}'.format(sense) in model_data_dict: setattr( backend_model, 'group_cost_investment_{}_constraint'.format(sense), po.Constraint( getattr(backend_model, 'group_names_cost_investment_{}'.format(sense)), backend_model.costs, [sense], rule=cost_investment_cap_constraint_rule ) ) if 'group_demand_share_per_timestep_decision' in model_data_dict: backend_model.group_demand_share_per_timestep_decision_main_constraint = po.Constraint( backend_model.group_names_demand_share_per_timestep_decision, backend_model.carriers, backend_model.techs, backend_model.timesteps, rule=demand_share_per_timestep_decision_main_constraint_rule ) backend_model.group_demand_share_per_timestep_decision_sum_constraint = po.Constraint( backend_model.group_names_demand_share_per_timestep_decision, backend_model.carriers, rule=demand_share_per_timestep_decision_sum_constraint_rule ) def equalizer(lhs, rhs, sign): if sign == 'max': return lhs <= rhs elif sign == 'min': return lhs >= rhs elif sign == 'equals': return lhs == rhs else: raise ValueError('Invalid sign: {}'.format(sign)) def get_demand_share_lhs_and_rhs_loc_tech_carriers(backend_model, group_name, carrier): """ Returns ------- (lhs_loc_tech_carriers, rhs_loc_tech_carriers): lhs are the supply technologies, rhs are the demand technologies """ lhs_loc_techs = getattr( backend_model, 'group_constraint_loc_techs_{}'.format(group_name) ) lhs_locs = set(loc_tech.split('::')[0] for loc_tech in lhs_loc_techs) lhs_loc_tech_carriers = [ i for i in backend_model.loc_tech_carriers_prod if i.rsplit('::', 1)[0] in lhs_loc_techs and i.split('::')[-1] == carrier ] rhs_loc_tech_carriers = [ i for i in backend_model.loc_tech_carriers_demand if i.split('::')[0] in lhs_locs and i.split('::')[-1] == carrier ] return (lhs_loc_tech_carriers, rhs_loc_tech_carriers) def demand_share_constraint_rule(backend_model, group_name, carrier, what): """ Enforces shares of demand of a carrier to be met by the given groups of technologies at the given locations, on average over the entire model period. The share is relative to ``demand`` technologies only. .. container:: scrolling-wrapper .. math:: \\sum_{loc::tech::carrier \\in given\\_group, timestep \\in timesteps} carrier_{prod}(loc::tech::carrier, timestep) \\leq share \\times \\sum_{loc::tech:carrier \\in loc\\_techs\\_demand \\in given\\_locations, timestep\\in timesteps} carrier_{con}(loc::tech::carrier, timestep) """ share = get_param(backend_model, 'group_demand_share_{}'.format(what), (carrier, group_name)) if share is None: return return_noconstraint('demand_share', group_name) else: lhs_loc_tech_carriers, rhs_loc_tech_carriers = get_demand_share_lhs_and_rhs_loc_tech_carriers( backend_model, group_name, carrier ) lhs = sum( backend_model.carrier_prod[loc_tech_carrier, timestep] for loc_tech_carrier in lhs_loc_tech_carriers for timestep in backend_model.timesteps ) rhs = share * -1 * sum( backend_model.carrier_con[loc_tech_carrier, timestep] for loc_tech_carrier in rhs_loc_tech_carriers for timestep in backend_model.timesteps ) return equalizer(lhs, rhs, what) def demand_share_per_timestep_constraint_rule(backend_model, group_name, carrier, timestep, what): """ Enforces shares of demand of a carrier to be met by the given groups of technologies at the given locations, in each timestep. The share is relative to ``demand`` technologies only. .. container:: scrolling-wrapper .. math:: \\sum_{loc::tech::carrier \\in given\\_group} carrier_{prod}(loc::tech::carrier, timestep) \\leq share \\times \\sum_{loc::tech:carrier \\in loc\\_techs\\_demand \\in given\\_locations} carrier_{con}(loc::tech::carrier, timestep) for timestep \\in timesteps """ share = get_param(backend_model, 'group_demand_share_per_timestep_{}'.format(what), (carrier, group_name)) if share is None: return return_noconstraint('demand_share_per_timestep', group_name) else: lhs_loc_tech_carriers, rhs_loc_tech_carriers = get_demand_share_lhs_and_rhs_loc_tech_carriers( backend_model, group_name, carrier ) lhs = sum( backend_model.carrier_prod[loc_tech_carrier, timestep] for loc_tech_carrier in lhs_loc_tech_carriers ) rhs = share * -1 * sum( backend_model.carrier_con[loc_tech_carrier, timestep] for loc_tech_carrier in rhs_loc_tech_carriers ) return equalizer(lhs, rhs, what) def demand_share_per_timestep_decision_main_constraint_rule(backend_model, group_name, carrier, tech, timestep): """ Allows the model to decide on how a fraction demand for a carrier is met by the given groups, which will all have the same share in each timestep. The share is relative to the actual demand from ``demand`` technologies only. The main constraint enforces that the shares are the same in each timestep. .. container:: scrolling-wrapper .. math:: \\sum_{loc::tech::carrier \\in given\\_group} carrier_{prod}(loc::tech::carrier, timestep) = \\sum_{loc::tech::carrier \\in given\\_group} required\\_resource(loc::tech::carrier, timestep) \\times \\sum_{loc::tech::carrier \\in given\\_group} demand\\_share\\_per\\_timestep\\_decision(loc::tech::carrier) \\forall timestep \\in timesteps \\forall tech \\in techs """ share_of_carrier_demand = get_param(backend_model, 'group_demand_share_per_timestep_decision', (carrier, group_name)) if share_of_carrier_demand is None: return return_noconstraint('demand_share_per_timestep_decision_main', group_name) else: # lhs are the supply technologies, rhs are the demand technologies lhs_loc_tech_carriers, rhs_loc_tech_carriers = get_demand_share_lhs_and_rhs_loc_tech_carriers( backend_model, group_name, carrier ) # Filter the supply loc_tech_carriers by the current tech lhs_loc_tech_carriers = [i for i in lhs_loc_tech_carriers if '::{}::'.format(tech) in i] # Only techs that are in the given group are considered if len(lhs_loc_tech_carriers) == 0: return return_noconstraint('demand_share_per_timestep_decision_main', group_name) lhs = sum( backend_model.carrier_prod[loc_tech_carrier, timestep] for loc_tech_carrier in lhs_loc_tech_carriers ) rhs = -1 * sum( backend_model.required_resource[rhs_loc_tech_carrier.rsplit('::', 1)[0], timestep] for rhs_loc_tech_carrier in rhs_loc_tech_carriers ) * sum( backend_model.demand_share_per_timestep_decision[lhs_loc_tech_carrier] for lhs_loc_tech_carrier in lhs_loc_tech_carriers ) return equalizer(lhs, rhs, 'equals') def demand_share_per_timestep_decision_sum_constraint_rule(backend_model, group_name, carrier): """ Allows the model to decide on how a fraction of demand for a carrier is met by the given groups, which will all have the same share in each timestep. The share is relative to the actual demand from ``demand`` technologies only. The sum constraint ensures that all decision shares add up to the share of carrier demand specified in the constraint. This constraint is only applied if the share of carrier demand has been set to a not-None value. .. container:: scrolling-wrapper .. math:: share = \\sum_{loc::tech::carrier \\in given\\_group} demand\\_share\\_per\\_timestep\\_decision(loc::tech::carrier) """ share_of_carrier_demand = get_param(backend_model, 'group_demand_share_per_timestep_decision', (carrier, group_name)) # If inf was given that means that we don't limit the total share if share_of_carrier_demand is None or np.isinf(share_of_carrier_demand): return return_noconstraint('demand_share_per_timestep_decision_sum', group_name) else: lhs_loc_tech_carriers, _ = get_demand_share_lhs_and_rhs_loc_tech_carriers( backend_model, group_name, carrier ) return share_of_carrier_demand == sum( backend_model.demand_share_per_timestep_decision[loc_tech_carrier] for loc_tech_carrier in lhs_loc_tech_carriers ) def get_carrier_prod_share_lhs_and_rhs_loc_techs(backend_model, group_name): lhs_loc_techs = getattr( backend_model, 'group_constraint_loc_techs_{}'.format(group_name) ) lhs_locs = [loc_tech.split('::')[0] for loc_tech in lhs_loc_techs] rhs_loc_techs = [ i for i in backend_model.loc_techs_supply_conversion_all if i.split('::')[0] in lhs_locs ] return (lhs_loc_techs, rhs_loc_techs) def carrier_prod_share_constraint_rule(backend_model, constraint_group, carrier, what): """ Enforces shares of carrier_prod for groups of technologies and locations, on average over the entire model period. The share is relative to ``supply`` and ``supply_plus`` technologies only. .. container:: scrolling-wrapper .. math:: \\sum_{loc::tech::carrier \\in given\\_group, timestep \\in timesteps} carrier_{prod}(loc::tech::carrier, timestep) \\leq share \\times \\sum_{loc::tech:carrier \\in loc\\_tech\\_carriers\\_supply\\_all \\in given\\_locations, timestep\\in timesteps} carrier_{prod}(loc::tech::carrier, timestep) """ share = get_param(backend_model, 'group_carrier_prod_share_{}'.format(what), (carrier, constraint_group)) if share is None: return return_noconstraint('supply_share', constraint_group) else: lhs_loc_techs, rhs_loc_techs = get_carrier_prod_share_lhs_and_rhs_loc_techs( backend_model, constraint_group ) lhs = sum( backend_model.carrier_prod[loc_tech + '::' + carrier, timestep] for loc_tech in lhs_loc_techs for timestep in backend_model.timesteps ) rhs = share * sum( backend_model.carrier_prod[loc_tech + '::' + carrier, timestep] for loc_tech in rhs_loc_techs for timestep in backend_model.timesteps ) return equalizer(lhs, rhs, what) def carrier_prod_share_per_timestep_constraint_rule(backend_model, constraint_group, carrier, timestep, what): """ Enforces shares of carrier_prod for groups of technologies and locations, in each timestep. The share is relative to ``supply`` and ``supply_plus`` technologies only. .. container:: scrolling-wrapper .. math:: \\sum_{loc::tech::carrier \\in given\\_group} carrier_{prod}(loc::tech::carrier, timestep) \\leq share \\times \\sum_{loc::tech:carrier \\in loc\\_tech\\_carriers\\_supply\\_all \\in given\\_locations} carrier_{prod}(loc::tech::carrier, timestep) for timestep \\in timesteps """ share = get_param(backend_model, 'group_carrier_prod_share_per_timestep_{}'.format(what), (carrier, constraint_group)) if share is None: return return_noconstraint('carrier_prod_share_per_timestep', constraint_group) else: lhs_loc_techs, rhs_loc_techs = get_carrier_prod_share_lhs_and_rhs_loc_techs( backend_model, constraint_group ) lhs = sum( backend_model.carrier_prod[loc_tech + '::' + carrier, timestep] for loc_tech in lhs_loc_techs ) rhs = share * sum( backend_model.carrier_prod[loc_tech + '::' + carrier, timestep] for loc_tech in rhs_loc_techs ) return equalizer(lhs, rhs, what) def net_import_share_constraint_rule(backend_model, constraint_group, carrier, what): """ Enforces demand shares of net imports from transmission technologies for groups of locations, on average over the entire model period. Transmission within the group are ignored. The share is relative to ``demand`` technologies only. .. container:: scrolling-wrapper .. math:: \\sum_{loc::tech::carrier \\in loc\\_tech\\_carriers\\_transmission \\in given\\_locations, timestep \\in timesteps} carrier_{prod}(loc::tech::carrier, timestep) + \\sum_{loc::tech::carrier \\in loc\\_tech\\_carriers\\_transmission \\in given\\_locations, timestep \\in timesteps} carrier_{con}(loc::tech::carrier, timestep) \\leq share \\times \\sum_{loc::tech:carrier \\in loc\\_tech\\_demand \\in given\\_locations, timestep\\in timesteps} carrier_{con}(loc::tech::carrier, timestep) """ share = get_param(backend_model, 'group_net_import_share_{}'.format(what), (carrier, constraint_group)) if share.value is None: return return_noconstraint('net_import_share', constraint_group) else: trans_loc_tech = getattr( backend_model, 'group_constraint_loc_techs_{}'.format(constraint_group) ) locs = set(loc_tech.split('::')[0] for loc_tech in trans_loc_tech) trans_loc_tech = filter(lambda loc_tec: loc_tec.split(":")[-1] not in locs, trans_loc_tech) demand_loc_tech = [ i for i in backend_model.loc_tech_carriers_demand if i.split('::')[0] in locs ] lhs = sum( (backend_model.carrier_prod[loc_tech + '::' + carrier, timestep] + backend_model.carrier_con[loc_tech + '::' + carrier, timestep]) for loc_tech in trans_loc_tech for timestep in backend_model.timesteps ) rhs = - share * sum( backend_model.carrier_con[loc_tech, timestep] for loc_tech in demand_loc_tech for timestep in backend_model.timesteps ) return equalizer(lhs, rhs, what) def carrier_prod_constraint_rule(backend_model, constraint_group, carrier, what): """ Enforces carrier_prod for groups of technologies and locations, as a sum over the entire model period. .. container:: scrolling-wrapper .. math:: \\sum_{loc::tech::carrier \\in given\\_group, timestep \\in timesteps} carrier_{prod}(loc::tech::carrier, timestep) \\leq supply_max """ limit = get_param(backend_model, 'group_carrier_prod_{}'.format(what), (carrier, constraint_group)) if limit is None: return return_noconstraint('carrier_prod', constraint_group) else: # We won't actually use the rhs techs lhs_loc_techs, rhs_loc_techs = get_carrier_prod_share_lhs_and_rhs_loc_techs( backend_model, constraint_group ) lhs = sum( backend_model.carrier_prod[loc_tech + '::' + carrier, timestep] for loc_tech in lhs_loc_techs for timestep in backend_model.timesteps if loc_tech + '::' + carrier in backend_model.loc_tech_carriers_prod ) return equalizer(lhs, limit, what) def energy_cap_share_constraint_rule(backend_model, constraint_group, what): """ Enforces shares of energy_cap for groups of technologies and locations. The share is relative to ``supply`` and ``supply_plus`` technologies only. .. container:: scrolling-wrapper .. math:: \\sum_{loc::tech \\in given\\_group} energy_{cap}(loc::tech) \\leq share \\times \\sum_{loc::tech \\in loc\\_tech\\_supply\\_all \\in given\\_locations} energy_{cap}(loc::tech) """ share = get_param(backend_model, 'group_energy_cap_share_{}'.format(what), (constraint_group)) if share is None: return return_noconstraint('energy_cap_share', constraint_group) else: lhs_loc_techs = getattr( backend_model, 'group_constraint_loc_techs_{}'.format(constraint_group) ) lhs_locs = [loc_tech.split('::')[0] for loc_tech in lhs_loc_techs] rhs_loc_techs = [ i for i in backend_model.loc_techs_supply_conversion_all if i.split('::')[0] in lhs_locs ] lhs = sum( backend_model.energy_cap[loc_tech] for loc_tech in lhs_loc_techs ) rhs = share * sum( backend_model.energy_cap[loc_tech] for loc_tech in rhs_loc_techs ) return equalizer(lhs, rhs, what) def energy_cap_constraint_rule(backend_model, constraint_group, what): """ Enforce upper and lower bounds for energy_cap of energy_cap for groups of technologies and locations. .. container:: scrolling-wrapper .. math:: \\sum_{loc::tech \\in given\\_group} energy_{cap}(loc::tech) \\leq energy\\_cap\\_max\\\\ \\sum_{loc::tech \\in given\\_group} energy_{cap}(loc::tech) \\geq energy\\_cap\\_min """ threshold = get_param(backend_model, 'group_energy_cap_{}'.format(what), (constraint_group)) if threshold is None: return return_noconstraint('energy_cap', constraint_group) else: lhs_loc_techs = getattr( backend_model, 'group_constraint_loc_techs_{}'.format(constraint_group) ) # Transmission techs only contribute half their capacity in each direction lhs = [] for loc_tech in lhs_loc_techs: if loc_tech_is_in(backend_model, loc_tech, 'loc_techs_transmission'): weight = 0.5 else: weight = 1 lhs.append(weight * backend_model.energy_cap[loc_tech]) rhs = threshold return equalizer(sum(lhs), rhs, what) def cost_cap_constraint_rule(backend_model, group_name, cost, what): """ Limit cost for a specific cost class to a certain value, i.e. Ɛ-constrained costs, for groups of technologies and locations. .. container:: scrolling-wrapper .. math:: \\sum{loc::tech \\in loc\\_techs_{group\\_name}, timestep \\in timesteps} \\boldsymbol{cost}(cost, loc::tech, timestep) \\begin{cases} \\leq cost\\_max(cost) \\geq cost\\_min(cost) = cost\\_equals(cost) \\end{cases} """ cost_cap = get_param(backend_model, 'group_cost_{}'.format(what), (cost, group_name)) if cost_cap is None: return return_noconstraint('cost_cap', group_name) else: loc_techs = [i for i in getattr( backend_model, 'group_constraint_loc_techs_{}'.format(group_name) ) if i in backend_model.loc_techs_cost] sum_cost = sum(backend_model.cost[cost, loc_tech] for loc_tech in loc_techs) return equalizer(sum_cost, cost_cap, what) def cost_investment_cap_constraint_rule(backend_model, group_name, cost, what): """ Limit investment costs specific to a cost class to a certain value, i.e. Ɛ-constrained costs, for groups of technologies and locations. .. container:: scrolling-wrapper .. math:: \\sum{loc::tech \\in loc\\_techs_{group\\_name}, timestep \\in timesteps} \\boldsymbol{cost\\_{investment}}(cost, loc::tech, timestep) \\begin{cases} \\leq cost\\_investment\\_max(cost) \\geq cost\\_investment\\_min(cost) = cost\\_investment\\_equals(cost) \\end{cases} """ cost_cap = get_param(backend_model, 'group_cost_investment_{}'.format(what), (cost, group_name)) if cost_cap is None: return return_noconstraint('cost_investment_cap', group_name) else: loc_techs = [i for i in getattr( backend_model, 'group_constraint_loc_techs_{}'.format(group_name) ) if i in backend_model.loc_techs_investment_cost] sum_cost = sum(backend_model.cost_investment[cost, loc_tech] for loc_tech in loc_techs) return equalizer(sum_cost, cost_cap, what) def cost_var_cap_constraint_rule(backend_model, group_name, cost, what): """ Limit variable costs specific to a cost class to a certain value, i.e. Ɛ-constrained costs, for groups of technologies and locations. .. container:: scrolling-wrapper .. math:: \\sum{loc::tech \\in loc\\_techs_{group\\_name}, timestep \\in timesteps} \\boldsymbol{cost\\_{var}}(cost, loc::tech, timestep) \\begin{cases} \\leq cost\\_var\\_max(cost) \\geq cost\\_var\\_min(cost) = cost\\_var\\_equals(cost) \\end{cases} """ cost_cap = get_param(backend_model, 'group_cost_var_{}'.format(what), (cost, group_name)) if cost_cap is None: return return_noconstraint('cost_var_cap', group_name) else: loc_techs = [i for i in getattr( backend_model, 'group_constraint_loc_techs_{}'.format(group_name) ) if i in backend_model.loc_techs_om_cost] sum_cost = sum( backend_model.cost_var[cost, loc_tech, timestep] for loc_tech in loc_techs for timestep in backend_model.timesteps ) return equalizer(sum_cost, cost_cap, what) def resource_area_constraint_rule(backend_model, constraint_group, what): """ Enforce upper and lower bounds of resource_area for groups of technologies and locations. .. container:: scrolling-wrapper .. math:: \\boldsymbol{resource_{area}}(loc::tech) \\leq group\\_resource\\_area\\_max\\\\ \\boldsymbol{resource_{area}}(loc::tech) \\geq group\\_resource\\_area\\_min """ threshold = get_param(backend_model, 'group_resource_area_{}'.format(what), (constraint_group)) if threshold is None: return return_noconstraint('resource_area', constraint_group) else: lhs_loc_techs = getattr( backend_model, 'group_constraint_loc_techs_{}'.format(constraint_group) ) lhs = sum( backend_model.resource_area[loc_tech] for loc_tech in lhs_loc_techs ) rhs = threshold return equalizer(lhs, rhs, what)

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Python

python/dgl/_ffi/_ctypes/__init__.py

ketyi/dgl

a1b859c29b63a673c148d13231a49504740e0e01

[ "Apache-2.0" ]

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2018-12-08T22:11:31.000Z

2022-03-31T13:04:33.000Z

python/dgl/_ffi/_ctypes/__init__.py

ketyi/dgl

a1b859c29b63a673c148d13231a49504740e0e01

[ "Apache-2.0" ]

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2022-03-31T21:16:27.000Z

python/dgl/_ffi/_ctypes/__init__.py

ketyi/dgl

a1b859c29b63a673c148d13231a49504740e0e01

[ "Apache-2.0" ]

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2022-03-31T13:07:41.000Z

"""ctypes specific implementation of FFI"""

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Python

src/custom_shapes.py

charleswilmot/Contrastive_DPG

e63f3251ea2501ca8416a0c57d12fff9df4ef039

[ "BSD-2-Clause" ]

null

src/custom_shapes.py

charleswilmot/Contrastive_DPG

e63f3251ea2501ca8416a0c57d12fff9df4ef039

[ "BSD-2-Clause" ]

null

src/custom_shapes.py

charleswilmot/Contrastive_DPG

e63f3251ea2501ca8416a0c57d12fff9df4ef039

[ "BSD-2-Clause" ]

null

import pyrep from pyrep.objects import Shape, Dummy, Object from pyrep.robots.arms.arm import Arm from pyrep.const import ObjectType class StatefulObject(Dummy): def __init__(self, name_or_handle, pyrep): super().__init__(name_or_handle) self._pyrep = pyrep def get_state(self): funcname = "getState@{}".format(self.get_name()) ints, floats, strings, bytes = self._pyrep.script_call(funcname, pyrep.const.sim.sim_scripttype_childscript) if not ints: raise ValueError( "Script return value incorect ({})".format(self.get_name()) ) return ints[0] def set_state(self, on): funcname = "setState@{}".format(self.get_name()) ints, floats, strings, bytes = self._pyrep.script_call( funcname, pyrep.const.sim.sim_scripttype_childscript, ints=[int(on)] ) if not ints: raise ValueError( "Script return value incorect ({})".format(self.get_name()) ) return ints[0] def set_goal(self, on): funcname = "setGoal@{}".format(self.get_name()) ints, floats, strings, bytes = self._pyrep.script_call( funcname, pyrep.const.sim.sim_scripttype_childscript, ints=[int(on)] ) if not ints: raise ValueError( "Script return value incorect ({})".format(self.get_name()) ) return ints[0] class TapShape(StatefulObject): def __init__(self, name_or_handle, pyrep): super().__init__(name_or_handle, pyrep) proximity_sensors = self.get_objects_in_tree( object_type=ObjectType.PROXIMITY_SENSOR ) self.proximity_sensor_0 = next( s for s in proximity_sensors if s.get_name().startswith("proximity_sensor_0") ) self.proximity_sensor_1 = next( s for s in proximity_sensors if s.get_name().startswith("proximity_sensor_1") ) self.joint = self.get_objects_in_tree( object_type=ObjectType.JOINT )[0] class ButtonShape(StatefulObject): def __init__(self, name_or_handle, pyrep): super().__init__(name_or_handle, pyrep) self.proximity_sensor = self.get_objects_in_tree( object_type=ObjectType.PROXIMITY_SENSOR )[0] class LeverShape(StatefulObject): def __init__(self, name_or_handle, pyrep): super().__init__(name_or_handle, pyrep) proximity_sensors = self.get_objects_in_tree( object_type=ObjectType.PROXIMITY_SENSOR ) self.proximity_sensor_0 = next( s for s in proximity_sensors if s.get_name().startswith("proximity_sensor_0") ) self.proximity_sensor_1 = next( s for s in proximity_sensors if s.get_name().startswith("proximity_sensor_1") ) self.joint = self.get_objects_in_tree( object_type=ObjectType.JOINT )[0] class Kuka(Arm): def __init__(self, name_or_handle): if type(name_or_handle) is int: name = Object.get_object_name(name_or_handle) else: name = name_or_handle super().__init__(count=0, name=name, num_joints=7)

32.90099

116

0.614505

394

3,323

4.829949

0.180203

0.037835

0.07567

0.062533

0.785602

0.773516

0

0.006765

0.288294

3,323

100

117

33.23

0.797886

0

0.586207

0

0.061089

0

1

0.091954

false

0

0.045977

0

0.229885

0

null

0

1

0

null

0

5

e7cad18636fc98345e1722c27da275915f3865e8

164

py

Python

codewars/7kyu/doha22/shortest_word/shortest_word.py

doha22/Training_one

0cd7cf86c7da0f6175834146296b763d1841766b

[ "MIT" ]

null

codewars/7kyu/doha22/shortest_word/shortest_word.py

doha22/Training_one

0cd7cf86c7da0f6175834146296b763d1841766b

[ "MIT" ]

2

2019-01-22T10:53:42.000Z

2019-01-31T08:02:48.000Z

codewars/7kyu/doha22/shortest_word/shortest_word.py

doha22/Training_one

0cd7cf86c7da0f6175834146296b763d1841766b

[ "MIT" ]

13

2019-01-22T10:37:42.000Z

2019-01-25T13:30:43.000Z

def find_short(s): # your code here m = min(s.split(), key = len) l = len(m) return l def find_short2(s): return min(len(x) for x in s.split())

20.5

41

0.573171

31

164

2.967742

0.580645

0.152174

0

0.008403

0.27439

164

8

41

20.5

0.764706

0.085366

0

0.125

0

1

0.333333

false

0

0.166667

0.666667

0

null

0

1

0

null

0

1

0

1

0

1

0

5

99e153c82ab038ba5f02bba579b5c82772dca0bd

148

py

Python

trialpage.py

Glenn-Po/LearningPython

96b12999d13b55216a3da6cf6b9248a8e86cbe0b

[ "Apache-2.0" ]

null

trialpage.py

Glenn-Po/LearningPython

96b12999d13b55216a3da6cf6b9248a8e86cbe0b

[ "Apache-2.0" ]

null

trialpage.py

Glenn-Po/LearningPython

96b12999d13b55216a3da6cf6b9248a8e86cbe0b

[ "Apache-2.0" ]

null

'''from enum import Enum class Color(Enum): red = 1 green = 2 blue = 3 print(Color.red) print(Color(1)) print(Color['red']) '''

10.571429

24

0.567568

22

148

3.818182

0.545455

0.357143

0.309524

0

0.036697

0.263514

148

13

25

11.384615

0.733945

0.932432

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

1

0

1

0

null

0

1

0

5

823812aefc7ef7a844b1b42375eaa424e4546d55

43

py

Python

src/includes/python/bin.py

vmchale/project-init

722b36504c554814c3cdfe374810d789527ad872

[ "BSD-3-Clause" ]

121

2017-05-01T12:48:29.000Z

2022-03-23T02:08:01.000Z

src/includes/python/bin.py

vmchale/project-init

722b36504c554814c3cdfe374810d789527ad872

[ "BSD-3-Clause" ]

11

2017-05-01T08:54:50.000Z

2020-04-02T06:22:12.000Z

src/includes/python/bin.py

vmchale/project-init

722b36504c554814c3cdfe374810d789527ad872

[ "BSD-3-Clause" ]

12

2017-05-01T12:49:38.000Z

2022-01-27T20:24:35.000Z

#!/usr/bin/env python import {{ project }}

14.333333

21

0.651163

6

43

4.666667

1

0

0.139535

43

2

22

21.5

0.756757

0.465116

0

null

0

1

null

0

1

0

null

0

1

0

null

0

1

0

1

0

5

41641dd92e35cc6c411f54800f89c260674a6fbd

90

py

Python

python_perl_storable/__init__.py

darviarush/python-perl-storable

5757664c5adedfbe73fd592d5270692a7f02f136

[ "MIT" ]

null

python_perl_storable/__init__.py

darviarush/python-perl-storable

5757664c5adedfbe73fd592d5270692a7f02f136

[ "MIT" ]

null

python_perl_storable/__init__.py

darviarush/python-perl-storable

5757664c5adedfbe73fd592d5270692a7f02f136

[ "MIT" ]

null

from .thaw import thaw from .freeze import freeze from .perl import freeze_perl, thaw_perl

30

40

0.822222

15

90

4.8

0.333333

0

0.133333

90

3

40

30

0.923077

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

419502f7e70ebe37d2e9dc43deab17d098696dbe

58

py

Python

atcoder/abc/abc004_b.py

knuu/competitive-programming

16bc68fdaedd6f96ae24310d697585ca8836ab6e

[ "MIT" ]

1

2018-11-12T15:18:55.000Z

atcoder/abc/abc004_b.py

knuu/competitive-programming

16bc68fdaedd6f96ae24310d697585ca8836ab6e

[ "MIT" ]

null

atcoder/abc/abc004_b.py

knuu/competitive-programming

16bc68fdaedd6f96ae24310d697585ca8836ab6e

[ "MIT" ]

null

print('\n'.join([input()[::-1] for _ in range(4)][::-1]))

29

57

0.5

10

58

2.8

0.9

0

0.056604

0.086207

58

1

58

0.471698

0

0.034483

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

41a2b17a7a55854954ce305f1b6d4bc40b78b910

23

py

Python

rama_master.py

mmayar/Clase-Ciencia-de-los-Datos

28ad34663ef25a3ab7ce528b50b19159581e7d35

[ "MIT" ]

null

rama_master.py

mmayar/Clase-Ciencia-de-los-Datos

28ad34663ef25a3ab7ce528b50b19159581e7d35

[ "MIT" ]

null

rama_master.py

mmayar/Clase-Ciencia-de-los-Datos

28ad34663ef25a3ab7ce528b50b19159581e7d35

[ "MIT" ]

null

print("Hallo an alle")

11.5

22

0.695652

4

23

4

1

0

0.130435

23

1

23

0.8

0

0.565217

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

68bd9d0fda3baf8dd7058ae47f699979d789341a

4,196

py

Python

baseline/unet/unet_model.py

Hwihuni/Deep-Model-Watermarking

73ea2286ace0aac3d55f6056da38ea2bc38ed00d

[ "MIT" ]

null

baseline/unet/unet_model.py

Hwihuni/Deep-Model-Watermarking

73ea2286ace0aac3d55f6056da38ea2bc38ed00d

[ "MIT" ]

null

baseline/unet/unet_model.py

Hwihuni/Deep-Model-Watermarking

73ea2286ace0aac3d55f6056da38ea2bc38ed00d

[ "MIT" ]

null

""" Full assembly of the parts to form the complete network """ import torch.nn.functional as F import math from .unet_parts import * class UNet(nn.Module): def __init__(self, n_channels, n_classes, bilinear=True): super(UNet, self).__init__() self.n_channels = n_channels self.n_classes = n_classes self.bilinear = bilinear self.inc = DoubleConv(self.n_channels, 64) self.down1 = Down(64, 128) self.down2 = Down(128, 256) self.down3 = Down(256, 512) factor = 2 if bilinear else 1 self.down4 = Down(512, 1024 // factor, 1024) self.up1 = Up(1024, 512 // factor, bilinear) self.up2 = Up(512, 256 // factor, bilinear) self.up3 = Up(256, 128 // factor, bilinear) self.up4 = Up(128, 64, bilinear) self.outc = OutConv(64, self.n_classes) def forward(self, x): x1 = self.inc(x) x2 = self.down1(x1) x3 = self.down2(x2) x4 = self.down3(x3) x5 = self.down4(x4) x6 = self.up1(x5, x4) x7 = self.up2(x6, x3) x8 = self.up3(x7, x2) # x9 = self.up4(x8, x1) logits = self.outc(x9) return logits class Fc(nn.Module): def __init__(self,n_channels, n_classes): super(Fc, self).__init__() self.n_channels2 = n_channels self.n_classes2 = n_classes self.fc1 = Conv_1D(self.n_channels2, 160) self.fc2 = Conv_1D(160, 240) self.fc3 = Conv_1D(240+self.n_channels2, 320) self.fc4 = Conv_1D(320, 360) self.fc5 = Conv_1D(360+self.n_channels2, 480) self.fc6 = Conv_1D(480, 520) self.fc7 = Conv_1D(520+self.n_channels2, 600) self.outfc = Conv_1D(600, self.n_classes2) def forward(self, x_mid): x21 = self.fc1(x_mid) x22 = torch.cat([x_mid,self.fc2(x21)], dim=1) x23 = self.fc3(x22) x24 = torch.cat([x_mid,self.fc4(x23)], dim=1) x25 = self.fc5(x24) x26 = torch.cat([x_mid,self.fc6(x25)], dim=1) x27 = self.fc7(x26) logits = self.outfc(x27) return logits class Model_int(nn.Module): def __init__(self, n_channels, n_classes, bilinear=True): super(Model_int, self).__init__() self.n_channels1 = 1 self.n_classes1 = 1 self.n_channels2 = 3 self.n_classes2 = 1 self.bilinear = bilinear self.inc = DoubleConv(self.n_channels1, 64) self.down1 = Down(64, 128) self.down2 = Down(128, 256) self.down3 = Down(256, 512) factor = 2 if bilinear else 1 self.down4 = Down(512, 1024 // factor, 1024) self.up1 = Up(1024, 512 // factor, bilinear) self.up2 = Up(512, 256 // factor, bilinear) self.up3 = Up(256, 128 // factor, bilinear) self.up4 = Up(128, 64, bilinear) self.outc = OutConv(64, self.n_classes1) self.pool = nn.AvgPool2d(3) self.intep = nn.Upsample(scale_factor=3) self.fc1 = Conv_1D(self.n_channels2, 160) self.fc2 = Conv_1D(160, 240) self.fc3 = Conv_1D(240+self.n_channels2, 320) self.fc4 = Conv_1D(320, 360) self.fc5 = Conv_1D(360+self.n_channels2, 480) self.fc6 = Conv_1D(480, 520) self.fc7 = Conv_1D(520+self.n_channels2, 600) self.outfc = Conv_1D(600, self.n_classes2) def forward(self, xin): x = xin[:,1:2,:,:]/(1e-12+xin[:,0:1,:,:]) x1 = self.inc(x) x2 = self.down1(x1) x3 = self.down2(x2) x4 = self.down3(x3) x5 = self.down4(x4) x6 = self.up1(x5, x4) x7 = self.up2(x6, x3) x8 = self.up3(x7, x2) # x9 = self.up4(x8, x1) #mid = self.intep(self.pool(self.outc(x9))) mid = self.outc(x9) x_mid = torch.cat([mid, xin], dim=1) x21 = self.fc1(x_mid) x22 = torch.cat([x_mid,self.fc2(x21)], dim=1) x23 = self.fc3(x22) x24 = torch.cat([x_mid,self.fc4(x23)], dim=1) x25 = self.fc5(x24) x26 = torch.cat([x_mid,self.fc6(x25)], dim=1) x27 = self.fc7(x26) logits = torch.cat([mid, self.outfc(x27)], dim=1) return logits

33.03937

63

0.565062

626

4,196

3.65016

0.175719

0.054705

0.061269

0.03151

0.748359

0.740481

0.70372

0.687965

0

0.141117

0.295758

4,196

126

64

33.301587

0.632149

0.023594

0

0.688679

0

1

0.056604

false

0

0.028302

0

0.141509

0

null

0

1

0

null

0

5

ec13f693c464363c80dac6e1e9bb81473a79b180

36

py

Python

Python/mol.py

abdalrhmanyasser/Abdalrhman_Rep

e0fc3caa2cc04e92f591ccd7934586986d194000

[ "CC0-1.0" ]

null

Python/mol.py

abdalrhmanyasser/Abdalrhman_Rep

e0fc3caa2cc04e92f591ccd7934586986d194000

[ "CC0-1.0" ]

null

Python/mol.py

abdalrhmanyasser/Abdalrhman_Rep

e0fc3caa2cc04e92f591ccd7934586986d194000

[ "CC0-1.0" ]

null

from molWeight import * findweight()

18

23

0.805556

4

36

7.25

1

0

0.111111

36

2

24

18

0.90625

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

6b7ed0bd2e983164eb376218da1fde2970942777

131

py

Python

src/prefect/tasks/mixpanel/__init__.py

suryatmodulus/prefect

e4ac9f6aa831140c7fba0397f3e5e0884b1b9e42

[ "Apache-2.0" ]

3

2021-11-09T10:46:58.000Z

2022-03-11T04:22:35.000Z

src/prefect/tasks/mixpanel/__init__.py

suryatmodulus/prefect

e4ac9f6aa831140c7fba0397f3e5e0884b1b9e42

[ "Apache-2.0" ]

8

2021-10-11T16:42:59.000Z

2022-03-31T08:42:24.000Z

src/prefect/tasks/mixpanel/__init__.py

suryatmodulus/prefect

e4ac9f6aa831140c7fba0397f3e5e0884b1b9e42

[ "Apache-2.0" ]

1

2022-03-11T04:22:40.000Z

""" This module contains a collection of tasks to interact with Mixpanel APIs. """ from .mixpanel_tasks import MixpanelExportTask

21.833333

74

0.793893

17

131

6.058824

0.882353

0

0.145038

131

5

75

26.2

0.919643

0.564886

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

6b908bf60af6792e0e100ec508ff8a0b34531cfd

242

py

Python

db/query.py

muellerzr/capstone-2021

a7f0c4de902735aece018d7c2ffedccc1995d51a

[ "Apache-2.0" ]

null

db/query.py

muellerzr/capstone-2021

a7f0c4de902735aece018d7c2ffedccc1995d51a

[ "Apache-2.0" ]

1

2021-11-30T00:03:22.000Z

db/query.py

muellerzr/capstone-2021

a7f0c4de902735aece018d7c2ffedccc1995d51a

[ "Apache-2.0" ]

null

from pymongo import MongoClient client = MongoClient('mongodb+srv://<username>:<password>@cluster0.27gwi.mongodb.net/Cluster0?retryWrites=true&w=majority') db=client.credentials #fivestar = db.reviews.find_one({'rating': 5}) #print(fivestar)

40.333333

123

0.785124

31

242

6.096774

0.806452

0

0.021834

0.053719

242

6

124

40.333333

0.803493

0.247934

0

0.333333

0.546961

0

1

0

false

0.333333

0

0.333333

0

null

0

1

0

1

0

1

null

0

1

0

5

6b9e02f9211409f10e7764f30ef7c7bc74bf73e2

682

py

Python

openweathermap_client/exceptions.py

Nobatek/openweathermap-client

07cd28fa7930e3d595d1946236c9b00851eb8bfa

[ "MIT" ]

null

openweathermap_client/exceptions.py

Nobatek/openweathermap-client

07cd28fa7930e3d595d1946236c9b00851eb8bfa

[ "MIT" ]

null

openweathermap_client/exceptions.py

Nobatek/openweathermap-client

07cd28fa7930e3d595d1946236c9b00851eb8bfa

[ "MIT" ]

null

"""OpenWeatherMap API client exceptions.""" from marshmallow import ValidationError class OpenWeatherMapClientError(Exception): """Generic OpenWeatherMap API client exception.""" class OWMClientKeyNotDefinedError(OpenWeatherMapClientError): """OpenWeatherMap API key not defined error.""" class OWMClientUnknownServiceNameError(OpenWeatherMapClientError): """OpenWeatherMap API service unknown error.""" class OWMClientAccessLimitationError(OpenWeatherMapClientError): """OpenWeatherMap API service access limitation error.""" class OWMClientValidationError(OpenWeatherMapClientError, ValidationError): """OpenWeatherMap API data validation error."""

28.416667

75

0.802053

51

682

10.72549

0.509804

0.186472

0.230347

0.179159

0

0.112903

682

23

76

29.652174

0.904132

0.381232

0

1

0

true

0

0.166667

0

1

0

1

null

0

1

0

null

0

1

0

1

0

5

6bd330ecd62ce882e921fe42445422e3cafc9446

24

py

Python

auto_torrenting.py

c-okelly/small_jobs

316114c983e789ff932abaf933b5938e313befb3

[ "MIT" ]

null

auto_torrenting.py

c-okelly/small_jobs

316114c983e789ff932abaf933b5938e313befb3

[ "MIT" ]

null

auto_torrenting.py

c-okelly/small_jobs

316114c983e789ff932abaf933b5938e313befb3

[ "MIT" ]

null

# Author Conor O'Kelly

8

22

0.708333

4

24

4.25

1

0

0.208333

24

2

23

12

0.894737

0.833333

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

d40aefb01dffe34973a1f115edb7b5c079b5d477

57

py

Python

caiman_napari/__init__.py

kushalkolar/caiman-napari-prototype

e9434d513f0454fd84c1dc0987d4c0658a2dfda4

[ "Apache-2.0" ]

null

caiman_napari/__init__.py

kushalkolar/caiman-napari-prototype

e9434d513f0454fd84c1dc0987d4c0658a2dfda4

[ "Apache-2.0" ]

null

caiman_napari/__init__.py

kushalkolar/caiman-napari-prototype

e9434d513f0454fd84c1dc0987d4c0658a2dfda4

[ "Apache-2.0" ]

1

2021-12-03T21:22:08.000Z

from .cnmf import napari_experimental_provide_dock_widget

57

0.929825

8

57

6.125

1

0

0.052632

57

1

57

0.907407

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

d46cea1160fabf2e3539d5eba8408300d75f0ebc

150

py

Python

tests/web_platform/CSS2/positioning/test_right_applies_to.py

jonboland/colosseum

cbf974be54fd7f6fddbe7285704cfaf7a866c5c5

[ "BSD-3-Clause" ]

71

2015-04-13T09:44:14.000Z

2019-03-24T01:03:02.000Z

tests/web_platform/CSS2/positioning/test_right_applies_to.py

jonboland/colosseum

cbf974be54fd7f6fddbe7285704cfaf7a866c5c5

[ "BSD-3-Clause" ]

35

2019-05-06T15:26:09.000Z

2022-03-28T06:30:33.000Z

tests/web_platform/CSS2/positioning/test_right_applies_to.py

jonboland/colosseum

cbf974be54fd7f6fddbe7285704cfaf7a866c5c5

[ "BSD-3-Clause" ]

139

2015-05-30T18:37:43.000Z

2019-03-27T17:14:05.000Z

from tests.utils import W3CTestCase class TestRightAppliesTo(W3CTestCase): vars().update(W3CTestCase.find_tests(__file__, 'right-applies-to-'))

25

72

0.786667

17

150

6.647059

0.823529

0

0.022059

0.093333

150

5

73

30

0.808824

0

0.113333

0

1

0

true

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

d480434187d2d4965e1d9a7be83e957a7e829b31

100

py

Python

acm_icpc/2018_2019_KNU_DzaDza/1_4/F.py

mstrechen/cp

ffac439840a71f70580a0ef197e47479e167a0eb

[ "MIT" ]

null

acm_icpc/2018_2019_KNU_DzaDza/1_4/F.py

mstrechen/cp

ffac439840a71f70580a0ef197e47479e167a0eb

[ "MIT" ]

null

acm_icpc/2018_2019_KNU_DzaDza/1_4/F.py

mstrechen/cp

ffac439840a71f70580a0ef197e47479e167a0eb

[ "MIT" ]

null

a = input().split(' ') n = int(a[0]) k = int(a[1]) print(2 ** (4 * n + k + 1) + 2 ** (4 * n))

16.666667

43

0.36

20

100

1.8

0.55

0.222222

0.166667

0

0.101449

0.31

100

5

44

20

0.42029

0

0.010526

0

1

0

false

0

0.25

1

0

1

null

1

0

1

0

1

0

null

0

5

cf579f861cc9d7beae973d53a1a8c919d94e3c59

78

py

Python

db_create.py

Don-1/info3180-project3-4

5a361e91a3c48498eea464312fb12d39bfa190c9

[ "MIT" ]

null

db_create.py

Don-1/info3180-project3-4

5a361e91a3c48498eea464312fb12d39bfa190c9

[ "MIT" ]

null

db_create.py

Don-1/info3180-project3-4

5a361e91a3c48498eea464312fb12d39bfa190c9

[ "MIT" ]

null

from config import SQLALCHEMY_DATABASE_URI from app import db db.create_all()

19.5

42

0.846154

13

78

4.846154

0.769231

0

0.115385

78

4

43

19.5

0.913043

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

cf829f2a0769af24ffc63064db6a6bdc86a1f38a

116

py

Python

solutions/908.smallest-range-i.241983759.ac.py

satu0king/Leetcode-Solutions

2edff60d76c2898d912197044f6284efeeb34119

[ "MIT" ]

78

2020-10-22T11:31:53.000Z

2022-02-22T13:27:49.000Z

solutions/908.smallest-range-i.241983759.ac.py

satu0king/Leetcode-Solutions

2edff60d76c2898d912197044f6284efeeb34119

[ "MIT" ]

null

solutions/908.smallest-range-i.241983759.ac.py

satu0king/Leetcode-Solutions

2edff60d76c2898d912197044f6284efeeb34119

[ "MIT" ]

26

2020-10-23T15:10:44.000Z

2021-11-07T16:13:50.000Z

class Solution(object): def smallestRangeI(self, A, K): return max(0, max(A) - min(A) - 2 * K)

23.2

46

0.534483

17

116

3.647059

0.764706

0

0.025

0.310345

116

4

47

29

0.75

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

d8783061dcd132ff7ce4c566ed60236c58199386

87

py

Python

Hackerrank-Solutions/Hackerrank-Python-Solutions/Numpy/Shape and Reshape.py

HetDaftary/Competitive-Coding-Solutions

a683fa11895410c6eef07b1a68054f3e90aa596b

[ "MIT" ]

null

Hackerrank-Solutions/Hackerrank-Python-Solutions/Numpy/Shape and Reshape.py

HetDaftary/Competitive-Coding-Solutions

a683fa11895410c6eef07b1a68054f3e90aa596b

[ "MIT" ]

null

Hackerrank-Solutions/Hackerrank-Python-Solutions/Numpy/Shape and Reshape.py

HetDaftary/Competitive-Coding-Solutions

a683fa11895410c6eef07b1a68054f3e90aa596b

[ "MIT" ]

null

import numpy as np print(np.reshape(list(map(int, input().strip().split())), (3, 3)))

29

66

0.643678

15

87

3.733333

0.866667

0

0.025641

0.103448

87

3

66

29

0.692308

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

d89d90e5483c3e450210df4df77773036f4c9016

19,881

py

Python

data/transcoder_evaluation_gfg/python/UNIQUE_CELLS_BINARY_MATRIX.py

mxl1n/CodeGen

e5101dd5c5e9c3720c70c80f78b18f13e118335a

[ "MIT" ]

241

2021-07-20T08:35:20.000Z

2022-03-31T02:39:08.000Z

data/transcoder_evaluation_gfg/python/UNIQUE_CELLS_BINARY_MATRIX.py

mxl1n/CodeGen

e5101dd5c5e9c3720c70c80f78b18f13e118335a

[ "MIT" ]

49

2021-07-22T23:18:42.000Z

2022-03-24T09:15:26.000Z

data/transcoder_evaluation_gfg/python/UNIQUE_CELLS_BINARY_MATRIX.py

mxl1n/CodeGen

e5101dd5c5e9c3720c70c80f78b18f13e118335a

[ "MIT" ]

71

2021-07-21T05:17:52.000Z

2022-03-29T23:49:28.000Z

# Copyright (c) 2019-present, Facebook, Inc. # All rights reserved. # # This source code is licensed under the license found in the # LICENSE file in the root directory of this source tree. # def f_gold ( mat , n , m ) : rowsum = [ 0 ] * n ; colsum = [ 0 ] * m ; for i in range ( n ) : for j in range ( m ) : if ( mat [ i ] [ j ] != 0 ) : rowsum [ i ] += 1 ; colsum [ j ] += 1 ; uniquecount = 0 ; for i in range ( n ) : for j in range ( m ) : if ( mat [ i ] [ j ] != 0 and rowsum [ i ] == 1 and colsum [ j ] == 1 ) : uniquecount += 1 ; return uniquecount ; #TOFILL if __name__ == '__main__': param = [ ([[0, 1, 0, 0], [0, 0, 1, 0], [1, 0, 0, 1]] ,3,4,), ([[0, 1, 0, 0], [0, 0, 1, 0], [1, 0, 0, 1]] ,2,2,), ([[0, 1, 0, 0], [0, 0, 1, 1], [1, 0, 1, 1]] ,3,4,), ([[0, 1, 0, 0], [0, 0, 1, 0], [1, 1, 0, 1]] ,3,4,), ([[1, 1, 1, 1], [0, 0, 1, 0], [1, 0, 0, 1]] ,3,3,), ([[0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 72, 33, 13, 43, 21, 83, 34, 30, 20, 82, 85, 36], [7, 69, 9, 45, 18, 47, 1, 78, 72, 53, 37, 20, 95, 71, 58, 41, 38, 44, 15, 35, 81, 27, 21, 40, 44, 90, 44, 5, 97, 49], [69, 92, 21, 8, 66, 37, 14, 34, 60, 61, 46, 21, 91, 18, 61, 69, 34, 82, 54, 99, 90, 29, 41, 92, 70, 90, 58, 82, 30, 33], [63, 96, 90, 86, 34, 49, 12, 22, 85, 24, 56, 25, 66, 1, 74, 34, 5, 17, 1, 78, 21, 6, 75, 39, 59, 20, 84, 85, 64, 24], [41, 90, 67, 38, 38, 28, 10, 24, 62, 52, 71, 87, 87, 24, 95, 50, 86, 91, 38, 69, 18, 72, 99, 49, 17, 76, 86, 53, 6, 94], [66, 5, 2, 62, 99, 5, 31, 81, 63, 91, 95, 74, 76, 18, 77, 57, 72, 99, 62, 4, 62, 46, 71, 21, 60, 45, 79, 98, 22, 65], [6, 65, 83, 27, 10, 55, 78, 34, 41, 32, 67, 51, 80, 39, 97, 5, 58, 99, 17, 23, 90, 46, 7, 62, 7, 15, 30, 20, 67, 86], [54, 50, 71, 95, 49, 50, 3, 64, 46, 81, 22, 52, 37, 60, 67, 48, 30, 88, 97, 43, 10, 71, 80, 96, 2, 72, 79, 67, 84, 98], [46, 41, 4, 87, 8, 10, 5, 74, 90, 80, 59, 58, 23, 61, 17, 28, 18, 52, 58, 41, 75, 98, 79, 1, 97, 73, 17, 79, 4, 46], [70, 6, 83, 23, 94, 1, 73, 61, 22, 65, 57, 36, 25, 16, 26, 92, 5, 22, 14, 73, 78, 80, 94, 96, 70, 17, 1, 18, 75, 11], [92, 12, 34, 80, 74, 8, 90, 42, 14, 51, 9, 83, 98, 38, 29, 29, 28, 88, 92, 76, 83, 6, 2, 53, 31, 37, 56, 93, 40, 12], [55, 97, 57, 45, 25, 42, 18, 30, 18, 7, 79, 30, 5, 69, 33, 6, 48, 4, 13, 26, 49, 20, 32, 96, 65, 89, 89, 53, 65, 3], [21, 43, 25, 85, 67, 93, 35, 86, 23, 13, 98, 23, 63, 99, 83, 15, 79, 26, 67, 81, 94, 61, 28, 34, 16, 43, 11, 24, 87, 25], [77, 19, 34, 66, 72, 5, 75, 66, 54, 96, 24, 76, 80, 51, 24, 50, 54, 17, 96, 84, 35, 30, 47, 42, 22, 31, 51, 37, 88, 88], [13, 89, 31, 14, 84, 39, 92, 89, 38, 75, 18, 39, 83, 67, 41, 46, 49, 27, 23, 35, 13, 26, 78, 35, 41, 6, 72, 52, 53, 79], [8, 47, 80, 93, 64, 34, 29, 35, 48, 74, 65, 69, 67, 14, 46, 27, 46, 29, 1, 82, 3, 26, 21, 24, 45, 84, 29, 18, 3, 51], [97, 18, 37, 63, 85, 19, 23, 84, 55, 24, 83, 26, 97, 96, 54, 99, 89, 33, 88, 57, 9, 64, 75, 85, 59, 81, 16, 5, 44, 46], [10, 77, 58, 70, 64, 80, 70, 93, 60, 25, 87, 11, 93, 85, 63, 26, 41, 53, 75, 24, 81, 73, 72, 94, 7, 87, 73, 83, 64, 72], [46, 78, 51, 92, 99, 71, 6, 30, 16, 57, 65, 61, 17, 63, 7, 35, 69, 91, 30, 44, 99, 80, 6, 80, 56, 8, 84, 95, 20, 73], [30, 62, 77, 26, 66, 61, 61, 45, 46, 24, 77, 16, 82, 16, 66, 1, 74, 25, 14, 81, 82, 7, 21, 93, 91, 49, 4, 12, 22, 34], [26, 28, 19, 31, 14, 87, 81, 23, 81, 8, 38, 10, 30, 7, 2, 22, 5, 67, 73, 69, 56, 20, 93, 70, 68, 57, 21, 17, 79, 27], [39, 83, 67, 92, 86, 70, 95, 69, 13, 98, 50, 10, 56, 44, 28, 85, 37, 36, 56, 92, 77, 57, 36, 1, 43, 9, 84, 81, 67, 32], [99, 70, 58, 52, 70, 89, 28, 65, 40, 80, 20, 88, 79, 10, 76, 62, 37, 99, 60, 91, 77, 94, 67, 52, 35, 62, 12, 29, 30, 22], [81, 53, 91, 22, 60, 49, 49, 7, 46, 11, 16, 54, 57, 36, 51, 22, 37, 3, 35, 38, 55, 41, 38, 88, 34, 99, 11, 79, 14, 81], [21, 28, 86, 60, 34, 65, 87, 96, 4, 56, 70, 80, 10, 35, 88, 10, 76, 63, 97, 91, 25, 74, 89, 32, 56, 26, 68, 73, 27, 73], [90, 11, 53, 32, 59, 30, 9, 11, 87, 17, 96, 11, 57, 86, 50, 96, 73, 81, 53, 89, 80, 97, 66, 43, 39, 42, 76, 34, 25, 78], [9, 94, 12, 10, 88, 34, 76, 26, 96, 35, 77, 83, 56, 77, 56, 86, 48, 23, 65, 8, 98, 13, 49, 10, 3, 28, 27, 85, 11, 88], [12, 7, 42, 96, 10, 61, 64, 28, 26, 93, 91, 52, 74, 4, 22, 10, 4, 7, 63, 87, 67, 88, 30, 76, 21, 48, 17, 67, 79, 96], [9, 40, 86, 96, 59, 69, 41, 68, 48, 61, 5, 7, 75, 6, 29, 51, 81, 28, 57, 63, 38, 83, 49, 12, 45, 83, 97, 45, 5, 65], [35, 35, 31, 36, 40, 99, 40, 61, 12, 82, 92, 13, 30, 40, 17, 73, 22, 56, 62, 57, 15, 93, 54, 16, 84, 89, 24, 80, 80, 25]],1,28,), ([[0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14, 45, 59, 40, 83, 46, 59, 89, 37, 82, 68, 65, 97, 28, 41, 83, 97, 15, 87, 93, 39, 78, 94, 66, 77, 28, 31, 12, 13, 3], [63, 29, 64, 94, 76, 85, 66, 50, 80, 96, 92, 73, 17, 56, 83, 7, 36, 40, 1, 42, 36, 39, 1, 88, 63, 74, 75, 86, 56, 31, 1, 41, 11, 6, 51, 64, 81, 78, 96, 20, 4, 39, 47, 22, 93, 42, 77, 79], [35, 25, 3, 51, 12, 14, 40, 32, 50, 68, 29, 31, 96, 24, 11, 30, 19, 36, 6, 2, 19, 46, 40, 18, 36, 46, 56, 52, 54, 56, 20, 1, 23, 38, 20, 4, 69, 6, 63, 90, 1, 63, 79, 80, 87, 86, 54, 69], [43, 5, 70, 66, 10, 36, 35, 45, 23, 62, 47, 16, 37, 42, 35, 40, 16, 69, 11, 51, 93, 75, 80, 89, 50, 67, 67, 65, 12, 7, 43, 46, 96, 22, 76, 6, 38, 39, 60, 85, 62, 92, 96, 27, 49, 15, 33, 96], [46, 98, 71, 13, 53, 39, 50, 70, 60, 9, 4, 94, 92, 21, 12, 77, 50, 13, 52, 91, 92, 82, 80, 21, 55, 10, 78, 92, 29, 11, 30, 40, 91, 49, 3, 1, 32, 39, 85, 2, 74, 31, 18, 7, 5, 29, 68, 46], [56, 3, 13, 67, 72, 50, 4, 42, 99, 76, 24, 19, 99, 82, 40, 34, 89, 7, 75, 38, 19, 99, 45, 20, 91, 95, 89, 2, 93, 37, 31, 42, 6, 85, 97, 9, 74, 86, 95, 53, 11, 83, 76, 16, 13, 38, 13, 15], [18, 16, 41, 50, 69, 91, 66, 41, 27, 59, 65, 14, 35, 23, 22, 27, 50, 25, 98, 54, 49, 91, 99, 85, 3, 25, 68, 57, 15, 67, 11, 92, 3, 18, 53, 9, 79, 72, 40, 56, 14, 61, 13, 47, 74, 94, 5, 86], [99, 5, 12, 35, 85, 26, 1, 10, 38, 24, 95, 47, 87, 85, 2, 95, 2, 30, 25, 83, 62, 1, 92, 63, 84, 59, 54, 69, 55, 94, 87, 42, 91, 53, 65, 9, 71, 51, 90, 16, 53, 70, 62, 37, 61, 57, 45, 76], [88, 17, 2, 95, 37, 54, 42, 29, 65, 78, 40, 11, 58, 96, 20, 66, 31, 5, 96, 50, 9, 41, 10, 53, 49, 26, 67, 36, 23, 94, 39, 59, 23, 23, 43, 25, 84, 60, 33, 33, 65, 47, 33, 38, 24, 73, 95, 49], [92, 87, 30, 82, 58, 90, 97, 59, 16, 93, 16, 33, 39, 46, 38, 23, 26, 49, 81, 24, 83, 42, 27, 2, 8, 79, 41, 13, 91, 22, 47, 47, 65, 69, 29, 79, 30, 46, 6, 6, 87, 52, 5, 86, 41, 20, 20, 39], [30, 48, 81, 60, 23, 60, 50, 13, 74, 38, 39, 68, 19, 52, 41, 92, 27, 23, 19, 80, 35, 5, 88, 5, 93, 6, 41, 41, 54, 44, 48, 37, 93, 56, 33, 91, 35, 6, 46, 74, 36, 44, 7, 7, 29, 80, 65, 60], [35, 57, 29, 38, 77, 12, 87, 80, 58, 78, 80, 6, 36, 52, 88, 27, 25, 40, 36, 60, 29, 95, 3, 13, 68, 11, 48, 79, 60, 2, 79, 70, 13, 35, 51, 56, 40, 77, 59, 12, 16, 53, 41, 20, 40, 61, 77, 34], [19, 45, 91, 29, 19, 56, 27, 2, 40, 65, 78, 8, 27, 97, 95, 30, 25, 49, 56, 65, 31, 99, 60, 85, 34, 17, 73, 29, 72, 83, 6, 88, 6, 3, 95, 31, 76, 52, 8, 90, 26, 15, 77, 56, 86, 62, 13, 46], [54, 9, 88, 3, 23, 12, 41, 44, 58, 11, 19, 59, 73, 37, 10, 73, 33, 77, 20, 44, 75, 93, 13, 63, 14, 73, 54, 42, 38, 83, 72, 82, 98, 36, 9, 80, 5, 15, 24, 64, 48, 43, 39, 25, 80, 86, 80, 97], [5, 60, 7, 18, 6, 12, 33, 98, 21, 58, 82, 78, 42, 94, 46, 3, 57, 53, 62, 13, 51, 19, 59, 62, 37, 77, 15, 90, 70, 91, 12, 89, 50, 47, 16, 16, 67, 34, 88, 46, 87, 64, 94, 49, 21, 53, 62, 81], [54, 82, 3, 53, 12, 80, 38, 78, 91, 18, 84, 35, 81, 84, 70, 90, 71, 76, 17, 21, 70, 47, 37, 89, 54, 15, 11, 9, 68, 3, 13, 96, 6, 1, 5, 66, 86, 96, 41, 50, 7, 21, 81, 53, 20, 65, 32, 96], [84, 74, 6, 41, 33, 74, 25, 24, 95, 93, 12, 37, 50, 9, 93, 67, 4, 54, 85, 6, 66, 37, 84, 45, 97, 14, 84, 43, 66, 7, 55, 37, 76, 16, 17, 95, 71, 90, 1, 2, 95, 84, 33, 13, 65, 51, 33, 3], [60, 83, 44, 96, 5, 47, 43, 47, 6, 60, 36, 37, 77, 76, 6, 30, 92, 10, 28, 6, 73, 24, 52, 82, 68, 45, 87, 27, 68, 13, 75, 75, 19, 33, 78, 13, 7, 33, 32, 45, 56, 72, 46, 98, 19, 34, 63, 70], [54, 55, 50, 65, 45, 30, 79, 73, 61, 93, 59, 2, 30, 46, 68, 19, 84, 5, 73, 84, 57, 63, 52, 59, 60, 80, 84, 20, 90, 33, 12, 21, 56, 23, 20, 87, 49, 47, 70, 45, 76, 35, 72, 27, 80, 47, 32, 29], [71, 80, 53, 93, 56, 89, 43, 4, 64, 91, 87, 23, 60, 30, 43, 88, 48, 80, 7, 87, 31, 19, 52, 68, 6, 83, 60, 91, 93, 12, 38, 13, 28, 5, 46, 46, 81, 27, 26, 62, 68, 72, 90, 97, 12, 77, 85, 52], [37, 25, 39, 67, 19, 71, 81, 77, 24, 51, 45, 8, 72, 45, 2, 30, 67, 45, 26, 17, 38, 67, 57, 33, 94, 79, 72, 94, 64, 23, 12, 8, 73, 72, 38, 33, 48, 97, 45, 75, 23, 43, 25, 15, 10, 20, 16, 99], [98, 85, 57, 46, 1, 25, 56, 46, 59, 62, 78, 61, 83, 8, 41, 15, 44, 82, 1, 97, 65, 34, 4, 81, 2, 39, 54, 10, 42, 45, 26, 27, 39, 25, 29, 82, 22, 90, 60, 90, 52, 85, 21, 8, 66, 98, 76, 18], [81, 15, 3, 85, 83, 59, 55, 32, 11, 82, 53, 29, 67, 4, 92, 9, 57, 38, 7, 65, 35, 47, 34, 63, 9, 90, 72, 19, 26, 46, 56, 10, 43, 30, 40, 55, 58, 31, 72, 47, 77, 37, 94, 57, 79, 57, 99, 3], [29, 88, 45, 87, 73, 2, 15, 96, 18, 29, 40, 3, 97, 58, 71, 94, 91, 38, 29, 31, 65, 43, 27, 27, 93, 69, 3, 29, 13, 97, 60, 84, 67, 70, 81, 47, 68, 97, 33, 6, 64, 78, 71, 70, 51, 67, 22, 72], [24, 77, 77, 65, 53, 41, 32, 69, 71, 45, 32, 28, 97, 14, 13, 93, 50, 40, 1, 47, 91, 30, 34, 46, 1, 34, 59, 7, 65, 42, 82, 99, 19, 13, 23, 66, 3, 86, 36, 49, 72, 87, 72, 57, 89, 99, 64, 11], [41, 6, 45, 81, 57, 82, 33, 61, 18, 7, 29, 69, 16, 95, 69, 74, 29, 29, 16, 4, 65, 72, 92, 1, 92, 3, 64, 66, 89, 57, 75, 18, 39, 84, 81, 7, 55, 17, 68, 36, 94, 1, 35, 76, 17, 80, 28, 32], [55, 35, 19, 93, 93, 80, 4, 21, 44, 62, 1, 83, 51, 90, 76, 17, 37, 92, 36, 29, 69, 3, 15, 67, 77, 69, 21, 23, 47, 86, 34, 41, 90, 47, 31, 35, 7, 45, 57, 96, 22, 70, 21, 49, 47, 27, 10, 86], [44, 51, 18, 68, 99, 38, 36, 60, 68, 74, 96, 74, 45, 74, 75, 9, 13, 57, 82, 57, 37, 47, 11, 28, 6, 33, 14, 47, 29, 15, 56, 69, 86, 31, 19, 18, 58, 70, 73, 30, 95, 35, 17, 16, 97, 68, 95, 33], [36, 11, 60, 4, 63, 5, 64, 85, 77, 4, 35, 26, 26, 19, 37, 11, 66, 31, 18, 75, 44, 16, 58, 2, 59, 96, 48, 86, 36, 8, 36, 25, 40, 95, 4, 43, 74, 27, 38, 81, 38, 64, 89, 17, 13, 85, 79, 24], [7, 64, 63, 22, 53, 74, 97, 12, 72, 22, 39, 47, 64, 44, 16, 59, 34, 46, 80, 78, 70, 55, 74, 24, 27, 73, 16, 2, 31, 63, 47, 19, 56, 11, 86, 93, 95, 8, 74, 6, 31, 99, 50, 29, 21, 41, 69, 69], [88, 79, 56, 28, 34, 56, 77, 55, 44, 32, 86, 29, 3, 69, 11, 48, 53, 56, 53, 26, 9, 75, 65, 56, 28, 23, 31, 66, 61, 82, 16, 59, 81, 48, 17, 35, 95, 99, 59, 88, 41, 37, 30, 82, 91, 16, 84, 47], [28, 21, 41, 45, 97, 73, 64, 88, 13, 94, 43, 97, 58, 88, 20, 63, 1, 23, 33, 57, 81, 54, 66, 95, 31, 54, 16, 37, 7, 1, 94, 18, 42, 39, 26, 75, 65, 57, 69, 86, 77, 17, 7, 71, 12, 38, 87, 48], [55, 54, 72, 15, 30, 55, 73, 21, 60, 78, 8, 47, 36, 73, 26, 84, 70, 34, 60, 23, 97, 85, 41, 90, 69, 55, 73, 45, 61, 33, 89, 52, 81, 19, 75, 8, 70, 6, 72, 57, 88, 60, 19, 52, 41, 91, 84, 88], [38, 69, 16, 39, 97, 74, 51, 5, 83, 62, 41, 85, 67, 59, 92, 19, 80, 62, 53, 66, 8, 46, 12, 88, 65, 82, 23, 39, 60, 27, 57, 44, 70, 28, 23, 34, 25, 11, 48, 65, 10, 73, 26, 10, 18, 60, 73, 45], [26, 9, 36, 15, 24, 40, 2, 4, 95, 20, 39, 45, 26, 60, 69, 68, 86, 70, 31, 69, 7, 69, 4, 91, 73, 37, 2, 49, 83, 17, 17, 40, 51, 88, 77, 28, 46, 78, 87, 87, 74, 49, 17, 27, 62, 11, 83, 44], [91, 36, 16, 60, 87, 97, 52, 22, 78, 77, 86, 71, 38, 65, 51, 97, 86, 23, 15, 79, 31, 28, 67, 42, 25, 33, 97, 23, 92, 53, 16, 37, 5, 11, 12, 21, 18, 14, 33, 21, 26, 89, 25, 35, 63, 20, 63, 66], [12, 32, 97, 48, 95, 97, 59, 20, 37, 40, 61, 56, 14, 36, 76, 90, 34, 6, 46, 77, 22, 99, 83, 23, 64, 96, 44, 11, 68, 61, 76, 56, 51, 63, 30, 10, 88, 23, 1, 48, 4, 28, 44, 67, 2, 58, 6, 42], [17, 37, 44, 23, 40, 85, 44, 31, 76, 93, 13, 90, 97, 98, 20, 47, 10, 65, 52, 63, 29, 54, 86, 50, 65, 44, 8, 9, 23, 84, 34, 16, 86, 62, 87, 65, 78, 52, 23, 38, 40, 8, 32, 40, 66, 48, 13, 27], [46, 71, 3, 85, 61, 72, 65, 17, 26, 29, 72, 38, 51, 43, 72, 8, 25, 55, 45, 91, 86, 67, 57, 49, 54, 47, 64, 24, 62, 33, 99, 40, 29, 8, 75, 16, 33, 64, 11, 29, 49, 88, 66, 5, 88, 53, 44, 7], [95, 94, 70, 69, 79, 27, 99, 54, 73, 23, 58, 17, 87, 46, 47, 93, 59, 45, 62, 54, 75, 13, 12, 2, 42, 54, 11, 78, 22, 85, 49, 37, 36, 89, 49, 58, 3, 66, 91, 33, 18, 48, 75, 71, 37, 50, 36, 27], [22, 31, 40, 54, 64, 70, 53, 54, 54, 97, 71, 6, 64, 54, 65, 46, 42, 93, 75, 92, 56, 40, 15, 30, 23, 12, 92, 95, 30, 16, 30, 68, 33, 57, 97, 28, 85, 79, 26, 14, 57, 15, 66, 16, 37, 11, 11, 33], [2, 33, 63, 3, 84, 33, 26, 34, 78, 52, 93, 66, 72, 27, 72, 71, 75, 94, 49, 47, 21, 21, 71, 84, 61, 14, 20, 5, 31, 62, 12, 56, 56, 12, 66, 26, 68, 30, 98, 20, 66, 35, 79, 51, 14, 55, 36, 53], [54, 63, 94, 58, 27, 2, 85, 78, 91, 85, 23, 35, 62, 72, 59, 76, 64, 92, 41, 33, 97, 9, 79, 74, 49, 2, 3, 23, 74, 19, 18, 35, 54, 60, 9, 95, 94, 52, 50, 12, 17, 91, 85, 49, 48, 27, 14, 55], [13, 3, 64, 88, 96, 72, 99, 23, 80, 73, 39, 58, 18, 54, 31, 64, 42, 37, 98, 70, 78, 88, 97, 42, 83, 29, 70, 3, 18, 85, 29, 52, 42, 52, 36, 95, 8, 96, 80, 86, 2, 51, 15, 17, 13, 54, 99, 25], [74, 75, 33, 78, 98, 22, 44, 4, 26, 1, 10, 2, 29, 25, 87, 94, 60, 89, 13, 40, 34, 35, 79, 39, 42, 84, 86, 25, 14, 83, 86, 87, 1, 39, 30, 5, 94, 71, 62, 77, 31, 7, 29, 51, 89, 77, 79, 51], [94, 71, 69, 14, 94, 23, 80, 88, 43, 56, 21, 30, 76, 40, 94, 22, 2, 23, 87, 86, 62, 30, 27, 98, 75, 93, 37, 70, 16, 20, 74, 46, 74, 25, 59, 86, 32, 17, 90, 80, 10, 17, 2, 66, 29, 4, 30, 61], [58, 76, 34, 78, 24, 88, 82, 25, 89, 25, 92, 30, 55, 89, 24, 39, 77, 2, 34, 16, 48, 24, 50, 2, 93, 39, 81, 59, 23, 12, 77, 69, 15, 60, 64, 2, 70, 64, 36, 87, 13, 2, 5, 40, 80, 64, 39, 35], [57, 41, 45, 34, 19, 90, 42, 17, 35, 76, 35, 6, 52, 74, 43, 23, 83, 43, 53, 72, 73, 67, 97, 66, 34, 35, 82, 27, 27, 64, 39, 60, 81, 73, 96, 23, 78, 11, 4, 51, 38, 51, 48, 80, 36, 25, 5, 74]],1,32,), ([[0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], [69, 62, 79, 46, 48, 38, 61, 81, 17, 48, 33, 18, 36, 54, 3, 89, 99, 20], [31, 21, 34, 57, 37, 1, 57, 55, 31, 23, 75, 48, 20, 7, 99, 2, 97, 40], [24, 74, 9, 43, 97, 51, 85, 78, 50, 87, 76, 22, 92, 91, 10, 82, 88, 67], [4, 30, 85, 22, 92, 73, 41, 16, 56, 69, 14, 52, 14, 47, 16, 43, 68, 37], [14, 41, 87, 73, 24, 75, 92, 19, 83, 12, 47, 98, 12, 3, 30, 58, 46, 51], [99, 15, 43, 22, 9, 92, 93, 39, 81, 68, 57, 68, 7, 2, 54, 37, 74, 82], [28, 59, 46, 63, 35, 99, 94, 85, 58, 89, 13, 71, 6, 84, 45, 5, 38, 44], [25, 82, 88, 15, 72, 77, 39, 48, 52, 60, 89, 23, 69, 52, 86, 22, 25, 55], [64, 65, 4, 52, 32, 53, 26, 79, 35, 91, 14, 34, 60, 25, 54, 27, 21, 48], [35, 52, 70, 99, 26, 15, 5, 90, 33, 25, 81, 52, 44, 20, 56, 66, 8, 83], [64, 29, 48, 19, 9, 72, 15, 98, 68, 63, 91, 38, 47, 13, 96, 99, 46, 36], [10, 55, 23, 23, 68, 44, 5, 4, 30, 52, 97, 13, 18, 32, 33, 58, 62, 71], [14, 14, 10, 59, 39, 46, 18, 19, 37, 3, 55, 7, 71, 52, 54, 38, 63, 64], [6, 74, 52, 44, 36, 37, 64, 48, 27, 65, 1, 48, 85, 37, 92, 49, 55, 39], [36, 66, 66, 68, 2, 65, 18, 41, 98, 91, 39, 26, 75, 3, 49, 28, 16, 99], [22, 80, 97, 77, 49, 28, 16, 64, 60, 66, 26, 42, 92, 3, 21, 32, 70, 69], [24, 65, 23, 80, 8, 45, 89, 11, 57, 12, 72, 10, 63, 35, 38, 21, 51, 18]],10,12,), ([[0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 19, 2, 93, 66, 82, 36, 56], [21, 97, 63, 2, 74, 15, 62, 12, 3, 4, 9, 46, 42, 74, 31, 37, 11, 61, 27, 46, 70, 94, 43, 99, 45], [18, 50, 6, 13, 12, 7, 14, 73, 99, 47, 7, 39, 56, 85, 19, 27, 61, 66, 52, 56, 14, 33, 12, 85, 94], [86, 66, 93, 24, 96, 45, 76, 55, 71, 53, 66, 19, 51, 82, 98, 66, 45, 40, 83, 6, 51, 41, 47, 17, 23], [40, 73, 37, 85, 58, 21, 27, 11, 39, 94, 63, 28, 84, 47, 47, 4, 61, 18, 50, 93, 36, 91, 1, 35, 5], [6, 60, 5, 32, 39, 95, 40, 42, 74, 95, 8, 91, 29, 60, 78, 23, 4, 34, 38, 61, 27, 83, 31, 3, 93], [77, 27, 43, 60, 96, 46, 37, 67, 6, 59, 3, 77, 11, 27, 2, 64, 44, 76, 55, 40, 76, 23, 64, 95, 57], [10, 35, 6, 89, 95, 54, 94, 79, 67, 82, 56, 81, 60, 14, 46, 16, 27, 37, 97, 61, 20, 25, 50, 58, 78], [37, 5, 54, 37, 74, 10, 9, 78, 33, 93, 24, 70, 57, 26, 39, 44, 64, 48, 67, 48, 40, 46, 96, 90, 3], [76, 14, 83, 4, 12, 99, 23, 3, 3, 42, 80, 77, 19, 28, 38, 9, 56, 17, 7, 72, 76, 54, 28, 66, 28], [25, 91, 99, 79, 49, 48, 99, 47, 62, 33, 42, 87, 27, 8, 62, 38, 4, 54, 48, 69, 16, 61, 18, 45, 18], [8, 29, 21, 54, 91, 47, 66, 68, 48, 76, 80, 89, 23, 17, 61, 52, 42, 51, 1, 21, 57, 36, 2, 23, 60], [59, 66, 43, 59, 74, 73, 93, 90, 36, 60, 93, 4, 21, 97, 95, 92, 97, 4, 4, 33, 14, 9, 88, 64, 62], [89, 7, 92, 5, 13, 2, 84, 12, 91, 7, 34, 21, 60, 82, 10, 38, 58, 56, 44, 85, 80, 64, 20, 50, 54], [46, 40, 24, 85, 58, 31, 50, 10, 84, 14, 19, 30, 57, 16, 22, 54, 84, 70, 43, 97, 19, 5, 71, 98, 20], [15, 38, 1, 5, 98, 54, 85, 61, 78, 17, 76, 27, 70, 25, 91, 45, 2, 22, 96, 54, 17, 61, 66, 26, 56], [33, 1, 40, 43, 44, 62, 36, 56, 39, 89, 13, 39, 12, 21, 87, 18, 13, 19, 35, 46, 57, 34, 62, 56, 1], [57, 86, 28, 4, 71, 75, 76, 40, 53, 39, 35, 98, 82, 10, 51, 64, 79, 59, 26, 3, 77, 98, 17, 65, 78], [1, 88, 57, 11, 67, 77, 55, 86, 41, 59, 30, 25, 71, 64, 89, 25, 66, 34, 55, 58, 86, 54, 1, 18, 16], [56, 74, 31, 48, 77, 34, 34, 60, 76, 37, 40, 17, 41, 56, 54, 79, 13, 46, 72, 17, 11, 40, 46, 65, 32], [52, 10, 59, 15, 3, 9, 8, 74, 8, 16, 11, 23, 56, 56, 22, 18, 39, 3, 8, 5, 91, 5, 19, 81, 61], [46, 18, 61, 60, 2, 50, 63, 71, 49, 80, 71, 18, 90, 93, 16, 46, 94, 25, 8, 64, 14, 22, 78, 91, 35], [51, 76, 43, 85, 75, 3, 73, 55, 19, 42, 61, 23, 80, 4, 96, 65, 4, 59, 90, 91, 80, 30, 33, 80, 33], [20, 95, 48, 27, 32, 86, 27, 25, 66, 87, 12, 46, 48, 85, 75, 85, 37, 4, 90, 84, 61, 71, 47, 91, 47], [17, 32, 10, 50, 75, 59, 18, 66, 35, 6, 3, 71, 35, 77, 66, 66, 51, 72, 73, 34, 39, 95, 93, 49, 47]],15,17,), ([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 95, 83, 85, 49, 74], [4, 62, 18, 60, 64, 20, 52, 36, 62, 48, 96, 57, 57, 91, 41, 88, 93, 53, 88, 62, 29, 39, 82], [10, 61, 56, 9, 50, 75, 12, 2, 90, 73, 17, 35, 46, 67, 70, 87, 35, 79, 72, 96, 34, 11, 3], [93, 10, 82, 82, 12, 91, 51, 83, 97, 89, 59, 2, 2, 5, 22, 33, 69, 28, 58, 14, 50, 74, 41], [15, 74, 68, 43, 55, 49, 18, 81, 95, 97, 25, 12, 55, 47, 85, 81, 84, 93, 67, 71, 64, 60, 97], [90, 84, 43, 37, 32, 99, 85, 52, 53, 56, 72, 2, 48, 16, 91, 36, 10, 92, 81, 89, 79, 18, 92], [2, 40, 42, 95, 95, 25, 1, 82, 16, 42, 37, 37, 71, 6, 78, 22, 95, 74, 46, 40, 54, 46, 36], [41, 98, 67, 23, 43, 61, 17, 93, 65, 3, 78, 75, 30, 21, 16, 62, 60, 9, 66, 26, 67, 15, 12], [19, 14, 15, 87, 11, 63, 43, 67, 43, 1, 4, 85, 25, 84, 74, 82, 97, 53, 35, 25, 3, 51, 50], [13, 35, 89, 55, 18, 51, 30, 40, 30, 58, 88, 90, 65, 97, 72, 12, 8, 75, 78, 18, 65, 85, 10], [37, 29, 46, 88, 44, 36, 18, 79, 32, 20, 34, 73, 41, 98, 35, 57, 27, 18, 21, 18, 27, 95, 28], [97, 15, 45, 47, 36, 19, 99, 96, 45, 57, 76, 29, 98, 16, 22, 72, 55, 12, 98, 16, 55, 47, 73], [27, 99, 11, 83, 95, 15, 53, 91, 33, 71, 87, 22, 65, 58, 27, 75, 12, 60, 85, 72, 77, 33, 66], [9, 77, 26, 45, 55, 52, 9, 79, 7, 57, 57, 37, 73, 78, 30, 51, 47, 84, 54, 23, 79, 58, 56], [31, 68, 89, 62, 83, 60, 37, 34, 1, 41, 95, 44, 35, 27, 21, 72, 82, 23, 41, 93, 80, 50, 74], [81, 22, 40, 2, 42, 30, 44, 83, 10, 84, 63, 24, 6, 45, 18, 16, 40, 16, 79, 70, 97, 13, 68], [96, 50, 29, 58, 7, 97, 5, 40, 4, 7, 80, 37, 75, 59, 50, 69, 29, 55, 89, 67, 96, 30, 20], [94, 67, 61, 44, 56, 79, 60, 41, 78, 40, 50, 10, 17, 15, 93, 53, 98, 99, 73, 51, 81, 66, 26], [38, 92, 30, 55, 9, 92, 16, 24, 86, 20, 62, 52, 78, 52, 43, 96, 10, 66, 71, 65, 15, 75, 84], [50, 41, 60, 33, 52, 38, 84, 64, 10, 96, 50, 63, 59, 12, 58, 89, 9, 49, 61, 81, 78, 88, 51], [45, 67, 80, 18, 61, 50, 14, 10, 74, 6, 3, 86, 2, 76, 1, 52, 13, 32, 25, 38, 5, 18, 10], [53, 83, 34, 30, 32, 11, 86, 30, 1, 6, 78, 56, 67, 58, 79, 95, 19, 61, 62, 86, 71, 91, 35], [43, 5, 46, 35, 87, 36, 4, 61, 2, 35, 46, 4, 60, 48, 4, 70, 51, 17, 4, 86, 57, 85, 76]],17,22,) ] n_success = 0 for i, parameters_set in enumerate(param): if f_filled(*parameters_set) == f_gold(*parameters_set): n_success+=1 print("#Results: %i, %i" % (n_success, len(param)))

382.326923

9,101

0.473719

4,889

19,881

1.922888

0.03109

0.018934

0.022657

0.025104

0.022232

0.021806

0.021062

0.020849

0.01936

0

0.61077

0.26211

19,881

52

9,102

382.326923

0.030061

0.009305

0

0.285714

0

0.001219

0

1

0.02381

false

0

0.047619

0.02381

0

1

null

0

1

0

1

0

null

0

5

d8a41006ae613f092c2493be67fa94572854ab3b

92

py

Python

froide/foisite/admin.py

manonthemat/froide

698c49935eaf2e922f3c9f6a46af0fd545ccbbbb

[ "MIT" ]

198

2016-12-03T22:42:55.000Z

2022-03-25T15:08:36.000Z

froide/foisite/admin.py

manonthemat/froide

698c49935eaf2e922f3c9f6a46af0fd545ccbbbb

[ "MIT" ]

264

2016-11-30T18:53:17.000Z

2022-03-17T11:34:18.000Z

froide/foisite/admin.py

ashmpace/question-mtl

5ce1289cd6db0e629aa138d2dee235d9a4c4546b

[ "MIT" ]

42

2016-12-22T04:08:27.000Z

2022-02-26T08:30:38.000Z

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

15.333333

32

0.815217

13

92

5.769231

0.692308

0

0.119565

92

5

33

18.4

0.925926

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

d8b4ee6c6b8979ab9fa1955a0f045727106c7104

36

py

Python

login.py

ManiaShark/project

6f5e8e320b1538bad226424984fff51b6e74f596

[ "MIT" ]

1

2018-09-12T01:05:17.000Z

login.py

ManiaShark/project

6f5e8e320b1538bad226424984fff51b6e74f596

[ "MIT" ]

null

login.py

ManiaShark/project

6f5e8e320b1538bad226424984fff51b6e74f596

[ "MIT" ]

1

2018-09-12T11:02:26.000Z

num = 1 num2 = 33333 num3 = 333333

7.2

13

0.638889

6

36

3.833333

1

0

0.538462

0.277778

36

4

14

9

0.346154

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

5

d8e33f74acbf4800ef30401dd24af5ca23b7058c

3,000

py

Python

Sticky-Notes/tests/test_outputs/getFileName.py

v2thegreat/sticky-notes

e79dd10b8fb88e0195ac1ca90d6b8dcb0f56e002

[ "Apache-2.0" ]

null

Sticky-Notes/tests/test_outputs/getFileName.py

v2thegreat/sticky-notes

e79dd10b8fb88e0195ac1ca90d6b8dcb0f56e002

[ "Apache-2.0" ]

null

Sticky-Notes/tests/test_outputs/getFileName.py

v2thegreat/sticky-notes

e79dd10b8fb88e0195ac1ca90d6b8dcb0f56e002

[ "Apache-2.0" ]

null

expected_outputs = ['Note-0.md', 'Note-0.HTML', 'Note-1.md', 'Note-1.HTML', 'Note-2.md', 'Note-2.HTML', 'Note-3.md', 'Note-3.HTML', 'Note-4.md', 'Note-4.HTML', 'Note-5.md', 'Note-5.HTML', 'Note-6.md', 'Note-6.HTML', 'Note-7.md', 'Note-7.HTML', 'Note-8.md', 'Note-8.HTML', 'Note-9.md', 'Note-9.HTML', 'Note-10.md', 'Note-10.HTML', 'Note-11.md', 'Note-11.HTML', 'Note-12.md', 'Note-12.HTML', 'Note-13.md', 'Note-13.HTML', 'Note-14.md', 'Note-14.HTML', 'Note-15.md', 'Note-15.HTML', 'Note-16.md', 'Note-16.HTML', 'Note-17.md', 'Note-17.HTML', 'Note-18.md', 'Note-18.HTML', 'Note-19.md', 'Note-19.HTML', 'Note-20.md', 'Note-20.HTML', 'Note-21.md', 'Note-21.HTML', 'Note-22.md', 'Note-22.HTML', 'Note-23.md', 'Note-23.HTML', 'Note-24.md', 'Note-24.HTML', 'Note-25.md', 'Note-25.HTML', 'Note-26.md', 'Note-26.HTML', 'Note-27.md', 'Note-27.HTML', 'Note-28.md', 'Note-28.HTML', 'Note-29.md', 'Note-29.HTML', 'Note-30.md', 'Note-30.HTML', 'Note-31.md', 'Note-31.HTML', 'Note-32.md', 'Note-32.HTML', 'Note-33.md', 'Note-33.HTML', 'Note-34.md', 'Note-34.HTML', 'Note-35.md', 'Note-35.HTML', 'Note-36.md', 'Note-36.HTML', 'Note-37.md', 'Note-37.HTML', 'Note-38.md', 'Note-38.HTML', 'Note-39.md', 'Note-39.HTML', 'Note-40.md', 'Note-40.HTML', 'Note-41.md', 'Note-41.HTML', 'Note-42.md', 'Note-42.HTML', 'Note-43.md', 'Note-43.HTML', 'Note-44.md', 'Note-44.HTML', 'Note-45.md', 'Note-45.HTML', 'Note-46.md', 'Note-46.HTML', 'Note-47.md', 'Note-47.HTML', 'Note-48.md', 'Note-48.HTML', 'Note-49.md', 'Note-49.HTML', 'Note-50.md', 'Note-50.HTML', 'Note-51.md', 'Note-51.HTML', 'Note-52.md', 'Note-52.HTML', 'Note-53.md', 'Note-53.HTML', 'Note-54.md', 'Note-54.HTML', 'Note-55.md', 'Note-55.HTML', 'Note-56.md', 'Note-56.HTML', 'Note-57.md', 'Note-57.HTML', 'Note-58.md', 'Note-58.HTML', 'Note-59.md', 'Note-59.HTML', 'Note-60.md', 'Note-60.HTML', 'Note-61.md', 'Note-61.HTML', 'Note-62.md', 'Note-62.HTML', 'Note-63.md', 'Note-63.HTML', 'Note-64.md', 'Note-64.HTML', 'Note-65.md', 'Note-65.HTML', 'Note-66.md', 'Note-66.HTML', 'Note-67.md', 'Note-67.HTML', 'Note-68.md', 'Note-68.HTML', 'Note-69.md', 'Note-69.HTML', 'Note-70.md', 'Note-70.HTML', 'Note-71.md', 'Note-71.HTML', 'Note-72.md', 'Note-72.HTML', 'Note-73.md', 'Note-73.HTML', 'Note-74.md', 'Note-74.HTML', 'Note-75.md', 'Note-75.HTML', 'Note-76.md', 'Note-76.HTML', 'Note-77.md', 'Note-77.HTML', 'Note-78.md', 'Note-78.HTML', 'Note-79.md', 'Note-79.HTML', 'Note-80.md', 'Note-80.HTML', 'Note-81.md', 'Note-81.HTML', 'Note-82.md', 'Note-82.HTML', 'Note-83.md', 'Note-83.HTML', 'Note-84.md', 'Note-84.HTML', 'Note-85.md', 'Note-85.HTML', 'Note-86.md', 'Note-86.HTML', 'Note-87.md', 'Note-87.HTML', 'Note-88.md', 'Note-88.HTML', 'Note-89.md', 'Note-89.HTML', 'Note-90.md', 'Note-90.HTML', 'Note-91.md', 'Note-91.HTML', 'Note-92.md', 'Note-92.HTML', 'Note-93.md', 'Note-93.HTML', 'Note-94.md', 'Note-94.HTML', 'Note-95.md', 'Note-95.HTML', 'Note-96.md', 'Note-96.HTML', 'Note-97.md', 'Note-97.HTML', 'Note-98.md', 'Note-98.HTML', 'Note-99.md', 'Note-99.HTML']

1,500

2,999

0.598667

602

3,000

2.981728

0.174419

0.334262

0

0.135811

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0

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null

1

0

1

0

1

0

null

0

5

d8ee5f8d9b3a85a50d156261bb8a4ea705b11351

115

py

Python

fiction_segmentation/data/test_split_overflow.py

aklagoo/fiction_segmentation

c14d5c380f800a632bc9f3199e69e6b25413e086

[ "MIT" ]

null

fiction_segmentation/data/test_split_overflow.py

aklagoo/fiction_segmentation

c14d5c380f800a632bc9f3199e69e6b25413e086

[ "MIT" ]

null

fiction_segmentation/data/test_split_overflow.py

aklagoo/fiction_segmentation

c14d5c380f800a632bc9f3199e69e6b25413e086

[ "MIT" ]

null

from unittest import TestCase class TestSplit_overflow(TestCase): def test_uniformity(self, x): pass

16.428571

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115

5.857143

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0.208696

115

6

36

19.166667

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false

0.25

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null

0

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1

0

1

0

5

d8fe60cb7b72d3e5b63d2e4e57e12e4214168725

24

py

Python

app/classes/missing.py

fossabot/Starboard-2

798e2d04995ae7d920e76708b9ea8fae6f4af319

[ "MIT" ]

null

app/classes/missing.py

fossabot/Starboard-2

798e2d04995ae7d920e76708b9ea8fae6f4af319

[ "MIT" ]

null

app/classes/missing.py

fossabot/Starboard-2

798e2d04995ae7d920e76708b9ea8fae6f4af319

[ "MIT" ]

null

class Missing: pass

8

14

0.666667

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24

5.333333

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0

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24

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15

12

0.941176

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true

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1

0

null

0

1

0

null

0

1

0

5

2b25ed291a003b5f379cf6ba31308ce499cb34a2

424

py

Python

ch18/pymui_v2.py

rauhaanrizvi/code

018270126c3549ec586165ee7b054ecb4fcb3bb8

[ "0BSD" ]

10

2021-05-07T08:31:57.000Z

2022-03-06T11:16:23.000Z

ch18/pymui_v2.py

rauhaanrizvi/code

018270126c3549ec586165ee7b054ecb4fcb3bb8

[ "0BSD" ]

null

ch18/pymui_v2.py

rauhaanrizvi/code

018270126c3549ec586165ee7b054ecb4fcb3bb8

[ "0BSD" ]

4

2021-08-23T08:48:36.000Z

2022-03-13T04:00:04.000Z

# Basic MUI components Button = require('@material-ui/core/Button')['default'] List = require('@material-ui/core/List')['default'] ListItem = require('@material-ui/core/ListItem')['default'] Typography = require('@material-ui/core/Typography')['default'] Input = require('@material-ui/core/Input')['default'] InputLabel = require('@material-ui/core/InputLabel')['default'] Box = require('@material-ui/core/Box')['default']

42.4

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0.721698

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424

5.884615

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0.388889

0.480392

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0.061321

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64

47.111111

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1

0

1

0

1

null

0

5

2b3940a57b9b855605a3d04e880237d3e9088f16

70

py

Python

settings.py

rtre84/Flask-Restplus-Swagger-Postgres

5289fa26c89f30297eba2868a581906f76cf724b

[ "MIT" ]

1

2020-09-17T12:11:35.000Z

settings.py

rtre84/Flask-Restplus-Swagger-Postgres

5289fa26c89f30297eba2868a581906f76cf724b

[ "MIT" ]

null

settings.py

rtre84/Flask-Restplus-Swagger-Postgres

5289fa26c89f30297eba2868a581906f76cf724b

[ "MIT" ]

null

# DB_URI = 'sqlite:///./main.db' DB_URI = 'postgres://localhost/mydb'

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70

4.3

0.7

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0.1

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1

0

null

1

0

1

0

1

null

0

5

2b3be92ebdc406b9f0984b35ac3c573766beccb5

83

py

Python

manipulaHTML_start.py

lucasiqueira86/Python

becabacbf9a55405ffafda50df7e8a02aedc3051

[ "MIT" ]

null

manipulaHTML_start.py

lucasiqueira86/Python

becabacbf9a55405ffafda50df7e8a02aedc3051

[ "MIT" ]

null

manipulaHTML_start.py

lucasiqueira86/Python

becabacbf9a55405ffafda50df7e8a02aedc3051

[ "MIT" ]

null

# # Exemplo de processamento e parse de HTML # from html.parser import HTMLParser

16.6

42

0.771084

12

83

5.333333

0.833333

0

0.180723

83

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43

20.75

0.941176

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1

0

null

0

1

0

1

0

1

0

5

2b40ed1fb10bb9082962ab805b1faee855b0b57e

310

py

Python

Mycoffee/accounts/views.py

AbderrhmanAbdellatif/MyCoffee

01563ccd1881caea605391fb813b7d0f2f59be02

[ "MIT" ]

null

Mycoffee/accounts/views.py

AbderrhmanAbdellatif/MyCoffee

01563ccd1881caea605391fb813b7d0f2f59be02

[ "MIT" ]

null

Mycoffee/accounts/views.py

AbderrhmanAbdellatif/MyCoffee

01563ccd1881caea605391fb813b7d0f2f59be02

[ "MIT" ]

null

from django.http import request from django.shortcuts import render # Create your views here. def signin(request): return render(request,'accounts/signin.html') def signup(request): return render(request,'accounts/signup.html') def profile(request): return render(request,'accounts/profile.html')

28.181818

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310

5.804878

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0.163866

0.239496

0.327731

0.428571

0

0.122581

310

11

50

28.181818

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0

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0.073427

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0

1

0

null

0

1

0

1

0

5

2b48a65242018f8f0b0cb6a6bc4910557c1f169e

2,034

py

Python

lightningtrace/transformations.py

GeomaticsResearch/lightningtrace

3d1c0a799dfa78a39fdbd0700e22b8709f641a33

[ "MIT" ]

5

2017-02-12T01:16:42.000Z

2019-01-06T16:48:08.000Z

lightningtrace/transformations.py

GeomaticsResearch/lightningtrace

3d1c0a799dfa78a39fdbd0700e22b8709f641a33

[ "MIT" ]

1

2018-04-10T21:27:45.000Z

2019-02-14T00:15:08.000Z

lightningtrace/transformations.py

GeomaticsResearch/lightningtrace

3d1c0a799dfa78a39fdbd0700e22b8709f641a33

[ "MIT" ]

null

import numpy as np def world_to_pixel_coords(affine, coords): """Convert a set of coordinates from world to pixel coordinates. :param affine: The rasterio affine object :param coords: World coordinates you want to translate to pixel coordinates """ # Convert to numpy array coords = np.array(coords) if coords.shape[0] <= 0 or coords.shape[1] < 2: raise ValueError("Shape of coords is incorrect. Please make sure you have X, Y, optional Z format") # Affine transformations between raster and world coordinates. # See https://github.com/sgillies/affine # See https://github.com/mapbox/rasterio/blob/master/docs/windowed-rw.rst # See http://www.perrygeo.com/python-affine-transforms.html # affine = Convert from pixel coordinates to world coordinates reverse_affine = ~affine # reverse_affine = Convert from world coordinates to pixel coordinates coords[:, 0:2] = np.apply_along_axis(lambda x: reverse_affine*(x[0], x[1]), axis=1, arr=coords) return coords def pixel_to_world_coords(affine, pixel_coords): """Convert a set of coordinates from pixel to world coordinates. :param affine: The rasterio affine object :param pixel_coords: Pixel coordinates (col, row) you want to translate to world coordinates """ coords = np.array(pixel_coords) if coords.shape[0] <= 0 or coords.shape[1] < 2: raise ValueError("Shape of pixel_coords is incorrect. Please make sure you have X, Y, optional Z format") # Affine transformations between raster and world coordinates. # See https://github.com/sgillies/affine # See https://github.com/mapbox/rasterio/blob/master/docs/windowed-rw.rst # See http://www.perrygeo.com/python-affine-transforms.html # affine = Convert from pixel coordinates to world coordinates reverse_affine = ~affine # reverse_affine = Convert from world coordinates to pixel coordinates coords[:, 0:2] = np.apply_along_axis(lambda x: affine*(x[0], x[1]), axis=1, arr=coords) return coords

48.428571

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0

null

0

1

0

1

0

null

0

5

2b6f56601504428d404ef21c2c065e37bf422b79

86

py

Python

account_setings.py

NurgaliyevS/Crypto_bot_telegram

cf8545d3079a9c5de98b4564bf6bf5d3c02a28ad

[ "MIT" ]

2

2022-03-20T02:49:08.000Z

2022-03-31T15:26:03.000Z

settings.py

NurgaliyevS/Crypto_Telegram_Bot_Buy_Coins

5b13d65c68d1c0c5ce5737ffc197b5b226689802

[ "MIT" ]

null

settings.py

NurgaliyevS/Crypto_Telegram_Bot_Buy_Coins

5b13d65c68d1c0c5ce5737ffc197b5b226689802

[ "MIT" ]

null

from dotenv import load_dotenv load_dotenv() # take environment variables from .env.

28.666667

54

0.802326

12

86

5.583333

0.666667

0.298507

0

0.139535

86

3

54

28.666667

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1

0

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1

0

1

0

null

0

1

0

1

0

5

99416782c8e0b909961f70c2f4bdc7554e54b060

68

py

Python

minerutils/__init__.py

EPICLab/miner-utils

802d614ea39eb6f35797d2033717f1b953a6825f

[ "MIT" ]

2

2020-09-22T00:05:20.000Z

2022-03-18T02:34:18.000Z

minerutils/__init__.py

EPICLab/miner-utils

802d614ea39eb6f35797d2033717f1b953a6825f

[ "MIT" ]

1

2020-10-01T21:23:21.000Z

2020-10-02T18:26:56.000Z

minerutils/__init__.py

EPICLab/miner-utils

802d614ea39eb6f35797d2033717f1b953a6825f

[ "MIT" ]

null

from .auth import MinerWithAuthentication from .github import GitHub

34

41

0.867647

8

68

7.375

0.625

0

0.102941

68

2

42

34

0.967213

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true

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1

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1

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1

0

null

0

1

0

1

0

1

0

5

996b6eadca01ee00a408b771a3d547d847157f5e

276

py

Python

{{cookiecutter.project_shortname}}/{{cookiecutter.package_name}}/__init__.py

slint/cookiecutter-invenio-datamodel

edf16c5830db9d6e73dd9f133fc3cd1ce29a0d71

[ "MIT" ]

null

{{cookiecutter.project_shortname}}/{{cookiecutter.package_name}}/__init__.py

slint/cookiecutter-invenio-datamodel

edf16c5830db9d6e73dd9f133fc3cd1ce29a0d71

[ "MIT" ]

null

{{cookiecutter.project_shortname}}/{{cookiecutter.package_name}}/__init__.py

slint/cookiecutter-invenio-datamodel

edf16c5830db9d6e73dd9f133fc3cd1ce29a0d71

[ "MIT" ]

null

{% include 'misc/header.py' %} """{{ cookiecutter.description }}""" from __future__ import absolute_import, print_function from .ext import {{ cookiecutter.extension_class }} from .version import __version__ __all__ = ('__version__', '{{ cookiecutter.extension_class }}')

25.090909

63

0.73913

28

276

6.571429

0.607143

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0.282609

0

0.115942

276

10

64

27.6

0.754098

0

0.245833

0.116667

0

null

0

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null

0.2

1

0

null

1

0

null

0

1

0

1

0

5

997bd596b360bb4e957def706805050c29e6a2e0

79

py

Python

desafios/des048.py

Ericssm96/python

764d0d704be685db9e993c4b74d3df78da12cc6f

[ "MIT" ]

null

desafios/des048.py

Ericssm96/python

764d0d704be685db9e993c4b74d3df78da12cc6f

[ "MIT" ]

null

desafios/des048.py

Ericssm96/python

764d0d704be685db9e993c4b74d3df78da12cc6f

[ "MIT" ]

null

s = 0 for c in range(0, 501): if c % 2 != 0 and c % 3 == 0: s += c

15.8

33

0.379747

18

79

1.666667

0.611111

0

0.204545

0.443038

79

4

34

19.75

0.477273

0

1

0

false

0

1

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1

null

0

1

0

1

0

1

0

null

0

5

9983217e23f84635b737ee96a0fc27810089ff8f

68

py

Python

chat/controllers/__init__.py

liuwill-projects/flask-server-scaffold

e75e3667053b6584a41aaba563d0a34f4db8fc1c

[ "MIT" ]

1

2017-04-27T09:44:35.000Z

chat/controllers/__init__.py

liuwill-projects/flask-server-scaffold

e75e3667053b6584a41aaba563d0a34f4db8fc1c

[ "MIT" ]

null

chat/controllers/__init__.py

liuwill-projects/flask-server-scaffold

e75e3667053b6584a41aaba563d0a34f4db8fc1c

[ "MIT" ]

null

from flask import Flask, jsonify from chat.utils.jsonp import jsonp

22.666667

34

0.823529

11

68

5.090909

0.636364

0

0.132353

68

2

35

34

0.949153

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

41df7e93d1b07022234bc59a3194a82463a794db

80

py

Python

creepy/__init__.py

itesoro/reepyc

38523ed0de784fa293c3f22af6d01712f0aa38c8

[ "MIT" ]

1

2022-02-11T22:05:36.000Z

creepy/__init__.py

itesoro/reepyc

38523ed0de784fa293c3f22af6d01712f0aa38c8

[ "MIT" ]

15

2020-11-24T09:22:28.000Z

2021-11-10T17:54:32.000Z

creepy/__init__.py

itesoro/reepyc

38523ed0de784fa293c3f22af6d01712f0aa38c8

[ "MIT" ]

null

from .query import connect, unproxy from .copy import copy from .app import app

20

35

0.7875

13

80

4.846154

0.538462

0

0.1625

80

3

36

26.666667

0.940299

0

1

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true

0

1

0

1

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1

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1

0

null

0

1

0

1

0

1

0

5

41f225bad3fd07b95061fd54f8a0cfa152e50218

254

py

Python

manage.py

amalchuk/readable

ce5397039516299a105ed975d79d9e62d0fe747f

[ "MIT" ]

null

manage.py

amalchuk/readable

ce5397039516299a105ed975d79d9e62d0fe747f

[ "MIT" ]

null

manage.py

amalchuk/readable

ce5397039516299a105ed975d79d9e62d0fe747f

[ "MIT" ]

null

#!/usr/bin/env python from os import environ if __name__ == "__main__": environ.setdefault("DJANGO_SETTINGS_MODULE", "readable.settings.development") from django.core.management import execute_from_command_line execute_from_command_line()

25.4

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0.779528

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254

5.6875

0.6875

0.120879

0.197802

0.241758

0

0.125984

254

9

82

28.222222

0.81982

0.07874

0

0.253219

0.218884

0

1

0

true

0

0.4

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0.4

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null

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1

0

1

0

null

0

1

0

1

0

5

5106badfed7ceee8bf0550d5ebdd7953c15c52ab

97

py

Python

Codeforces/669/gen.py

Mindjolt2406/Competitive-Programming

d000d98bf7005ee4fb809bcea2f110e4c4793b80

[ "MIT" ]

2

2018-12-11T14:37:24.000Z

2022-01-23T18:11:54.000Z

Codeforces/669/gen.py

Mindjolt2406/Competitive-Programming

d000d98bf7005ee4fb809bcea2f110e4c4793b80

[ "MIT" ]

null

Codeforces/669/gen.py

Mindjolt2406/Competitive-Programming

d000d98bf7005ee4fb809bcea2f110e4c4793b80

[ "MIT" ]

null

from random import * n = randint(5,10) print n for i in range(n): print randint(1,10), print ""

16.166667

22

0.670103

19

97

3.421053

0.684211

0.215385

0

0.075949

0.185567

97

6

23

16.166667

0.746835

0

null

0

0.166667

null

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

5

511c4b0f0051cca6d3e9d4723359af3604198075

242

py

Python

extraction_tool/constants.py

ohadlevy/homebridge-palgate-opener

1dc2c4e00a7dc969221db6f571a75d2d4088a7a0

[ "MIT" ]

13

2020-10-24T22:17:31.000Z

2022-03-04T22:31:23.000Z

extraction_tool/constants.py

ohadlevy/homebridge-palgate-opener

1dc2c4e00a7dc969221db6f571a75d2d4088a7a0

[ "MIT" ]

7

2021-01-24T11:23:24.000Z

2022-02-27T13:19:28.000Z

extraction_tool/constants.py

ohadlevy/homebridge-palgate-opener

1dc2c4e00a7dc969221db6f571a75d2d4088a7a0

[ "MIT" ]

4

2020-10-24T22:17:42.000Z

2022-01-20T08:01:31.000Z

SMS_ADDR = "https://api1.pal-es.com/v1/bt/verify/972{}/start/sms/" SMS_TOKEN = "GDN5-F8KG5-GNYSD45-KGBXRW843-SDFN4" VALIDATE_ADDR = "https://api1.pal-es.com/v1/bt/verify/972{}/code/{}/" DEVICE_ADDR = "https://api1.pal-es.com/v1/bt/devices/"

48.4

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0.706612

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242

3.97619

0.52381

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0.233533

0.287425

0.556886

0.407186

0

0.091703

0.053719

242

4

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60.5

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null

0

1

0

1

0

1

0

null

0

5

512969a9d62c413ba64061dc9a182ad677f3a2ad

264

py

Python

thirdparty/statistic.py

bopopescu/redis-ctl

16ae59b6dfe3d62ecb59951bd81395c370b005ef

[ "MIT" ]

109

2015-02-11T03:06:09.000Z

2017-06-06T09:48:00.000Z

thirdparty/statistic.py

bopopescu/redis-ctl

16ae59b6dfe3d62ecb59951bd81395c370b005ef

[ "MIT" ]

14

2015-04-10T02:09:21.000Z

2017-04-24T00:22:18.000Z

thirdparty/statistic.py

bopopescu/redis-ctl

16ae59b6dfe3d62ecb59951bd81395c370b005ef

[ "MIT" ]

53

2015-03-13T15:34:34.000Z

2017-05-05T22:31:49.000Z

class Base(object): def __str__(self): return 'Unimplemented Statistic Service' def write_points(self, name, fields): raise NotImplementedError() def query(self, name, fields, span, end, interval): raise NotImplementedError()

26.4

55

0.674242

28

264

6.178571

0.714286

0.092486

0.16185

0

0.231061

264

9

56

29.333333

0.852217

0

0.285714

0

0.117424

0

1

0.428571

false

0

0.142857

0.714286

0

1

0

null

0

1

0

null

0

1

0

1

0

5

5135b10c191bf7b9cc9a6a8eac047d3870110b02

186

py

Python

pythonDesafios/aula10.py

mateusdev7/desafios-python

6160ddc84548c7af7f5775f9acabe58238f83008

[ "MIT" ]

null

pythonDesafios/aula10.py

mateusdev7/desafios-python

6160ddc84548c7af7f5775f9acabe58238f83008

[ "MIT" ]

null

pythonDesafios/aula10.py

mateusdev7/desafios-python

6160ddc84548c7af7f5775f9acabe58238f83008

[ "MIT" ]

null

# Condições tempo = int(input('Quantos anos tem seu carro?\n>')) if tempo <= 3: print('Seu carro está novo') else: print('Seu carro está velhinho...') print('Fim do programa.')

20.666667

52

0.650538

28

186

4.321429

0.714286

0.198347

0.214876

0.280992

0

0.006579

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186

8

53

23.25

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0

false

0

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null

0

1

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1

0

null

0

1

0

5

51515643097b406b77e71f83643bb04a5b1b38ed

115

py

Python

pyinterfaces/convenience/record.py

OaklandPeters/pyinterfaces

c60efaad92e8d2e1ec25df718dfb43f034a083bb

[ "MIT" ]

null

pyinterfaces/convenience/record.py

OaklandPeters/pyinterfaces

c60efaad92e8d2e1ec25df718dfb43f034a083bb

[ "MIT" ]

null

pyinterfaces/convenience/record.py

OaklandPeters/pyinterfaces

c60efaad92e8d2e1ec25df718dfb43f034a083bb

[ "MIT" ]

null

""" These are the interfaces from the package itemize/. Todo: add dependency on itemize, and import them here. """

23

54

0.73913

17

115

5

0.882353

0

0.165217

115

4

55

28.75

0.885417

0.921739

0

null

0

null

0

null

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0.25

null

1

null

true

0

null

1

0

null

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1

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1

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null

0

1

0

1

0

5

516495aeea8fc8f01a72d4b5e6c869fcb616427e

6,481

py

Python

stage/configuration/test_amazon_s3_destination.py

anubandhan/datacollector-tests

301c024c66d68353735256b262b681dd05ba16cc

[ "Apache-2.0" ]

null

stage/configuration/test_amazon_s3_destination.py

anubandhan/datacollector-tests

301c024c66d68353735256b262b681dd05ba16cc

[ "Apache-2.0" ]

1

2019-04-24T11:06:38.000Z

stage/configuration/test_amazon_s3_destination.py

anubandhan/datacollector-tests

301c024c66d68353735256b262b681dd05ba16cc

[ "Apache-2.0" ]

2

2019-05-24T06:34:37.000Z

2020-03-30T11:48:18.000Z

import pytest from streamsets.testframework.decorators import stub @stub def test_access_key_id(sdc_builder, sdc_executor): pass @stub @pytest.mark.parametrize('stage_attributes', [{'server_side_encryption_option': 'KMS', 'use_server_side_encryption': True}]) def test_aws_kms_key_arn(sdc_builder, sdc_executor, stage_attributes): pass @stub def test_bucket(sdc_builder, sdc_executor): pass @stub def test_common_prefix(sdc_builder, sdc_executor): pass @stub @pytest.mark.parametrize('stage_attributes', [{'compress_with_gzip': False}, {'compress_with_gzip': True}]) def test_compress_with_gzip(sdc_builder, sdc_executor, stage_attributes): pass @stub def test_connection_timeout(sdc_builder, sdc_executor): pass @stub @pytest.mark.parametrize('stage_attributes', [{'server_side_encryption_option': 'CUSTOMER', 'use_server_side_encryption': True}]) def test_customer_encryption_key(sdc_builder, sdc_executor, stage_attributes): pass @stub @pytest.mark.parametrize('stage_attributes', [{'server_side_encryption_option': 'CUSTOMER', 'use_server_side_encryption': True}]) def test_customer_encryption_key_md5(sdc_builder, sdc_executor, stage_attributes): pass @stub def test_data_time_zone(sdc_builder, sdc_executor): pass @stub def test_delimiter(sdc_builder, sdc_executor): pass @stub @pytest.mark.parametrize('stage_attributes', [{'server_side_encryption_option': 'KMS', 'use_server_side_encryption': True}]) def test_encryption_context(sdc_builder, sdc_executor, stage_attributes): pass @stub @pytest.mark.parametrize('stage_attributes', [{'region': 'OTHER'}]) def test_endpoint(sdc_builder, sdc_executor, stage_attributes): pass @stub def test_minimum_upload_part_size(sdc_builder, sdc_executor): pass @stub def test_multipart_upload_threshold(sdc_builder, sdc_executor): pass @stub def test_object_name_prefix(sdc_builder, sdc_executor): pass @stub def test_object_name_suffix(sdc_builder, sdc_executor): pass @stub @pytest.mark.parametrize('stage_attributes', [{'on_record_error': 'DISCARD'}, {'on_record_error': 'STOP_PIPELINE'}, {'on_record_error': 'TO_ERROR'}]) def test_on_record_error(sdc_builder, sdc_executor, stage_attributes): pass @stub def test_partition_prefix(sdc_builder, sdc_executor): pass @stub def test_preconditions(sdc_builder, sdc_executor): pass @stub @pytest.mark.parametrize('stage_attributes', [{'use_proxy': True}]) def test_proxy_host(sdc_builder, sdc_executor, stage_attributes): pass @stub @pytest.mark.parametrize('stage_attributes', [{'use_proxy': True}]) def test_proxy_password(sdc_builder, sdc_executor, stage_attributes): pass @stub @pytest.mark.parametrize('stage_attributes', [{'use_proxy': True}]) def test_proxy_port(sdc_builder, sdc_executor, stage_attributes): pass @stub @pytest.mark.parametrize('stage_attributes', [{'use_proxy': True}]) def test_proxy_user(sdc_builder, sdc_executor, stage_attributes): pass @stub @pytest.mark.parametrize('stage_attributes', [{'region': 'AP_NORTHEAST_1'}, {'region': 'AP_NORTHEAST_2'}, {'region': 'AP_NORTHEAST_3'}, {'region': 'AP_SOUTHEAST_1'}, {'region': 'AP_SOUTHEAST_2'}, {'region': 'AP_SOUTH_1'}, {'region': 'CA_CENTRAL_1'}, {'region': 'CN_NORTHWEST_1'}, {'region': 'CN_NORTH_1'}, {'region': 'EU_CENTRAL_1'}, {'region': 'EU_WEST_1'}, {'region': 'EU_WEST_2'}, {'region': 'EU_WEST_3'}, {'region': 'OTHER'}, {'region': 'SA_EAST_1'}, {'region': 'US_EAST_1'}, {'region': 'US_EAST_2'}, {'region': 'US_GOV_WEST_1'}, {'region': 'US_WEST_1'}, {'region': 'US_WEST_2'}]) def test_region(sdc_builder, sdc_executor, stage_attributes): pass @stub def test_required_fields(sdc_builder, sdc_executor): pass @stub def test_retry_count(sdc_builder, sdc_executor): pass @stub def test_secret_access_key(sdc_builder, sdc_executor): pass @stub @pytest.mark.parametrize('stage_attributes', [{'server_side_encryption_option': 'CUSTOMER', 'use_server_side_encryption': True}, {'server_side_encryption_option': 'KMS', 'use_server_side_encryption': True}, {'server_side_encryption_option': 'NONE', 'use_server_side_encryption': True}, {'server_side_encryption_option': 'S3', 'use_server_side_encryption': True}]) def test_server_side_encryption_option(sdc_builder, sdc_executor, stage_attributes): pass @stub def test_socket_timeout(sdc_builder, sdc_executor): pass @stub def test_thread_pool_size_for_parallel_uploads(sdc_builder, sdc_executor): pass @stub def test_time_basis(sdc_builder, sdc_executor): pass @stub @pytest.mark.parametrize('stage_attributes', [{'use_proxy': False}, {'use_proxy': True}]) def test_use_proxy(sdc_builder, sdc_executor, stage_attributes): pass @stub @pytest.mark.parametrize('stage_attributes', [{'use_server_side_encryption': False}, {'use_server_side_encryption': True}]) def test_use_server_side_encryption(sdc_builder, sdc_executor, stage_attributes): pass

29.729358

107

0.584632

672

6,481

5.205357

0.153274

0.066038

0.122642

0.198113

0.759863

0.736421

0.699828

0.627787

0.591481

0

0.004715

0.31276

6,481

217

108

29.866359

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0

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0

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false

0.228188

0.013423

0

0.234899

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null

0

1

0

1

0

null

0

1

0

1

0

5

5ad25bcf361868f1573ce15be23883e97a4be338

83

py

Python

src/moderate/endianness/solutions/python/solution.py

rdtsc/codeeval-solutions

d5c06baf89125e9e9f4b163ee57e5a8f7e73e717

[ "MIT" ]

null

src/moderate/endianness/solutions/python/solution.py

rdtsc/codeeval-solutions

d5c06baf89125e9e9f4b163ee57e5a8f7e73e717

[ "MIT" ]

null

src/moderate/endianness/solutions/python/solution.py

rdtsc/codeeval-solutions

d5c06baf89125e9e9f4b163ee57e5a8f7e73e717

[ "MIT" ]

null

#!/usr/bin/env python3 import sys print(sys.byteorder.title(), 'Endian', sep='')

13.833333

46

0.674699

12

83

4.666667

0.916667

0

0.013514

0.108434

83

5

47

16.6

0.743243

0.253012

0

0.098361

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

5afc70df7ddecda1d227e407ffd0daf35b4c8077

74

py

Python

tests/invalid/type_enum.py

anthem-ai/fhir-types

42348655fb3a9b3f131b911d6bc0782da8c14ce4

[ "Apache-2.0" ]

2

2022-02-03T00:51:30.000Z

2022-02-03T18:42:43.000Z

tests/invalid/type_enum.py

anthem-ai/fhir-types

42348655fb3a9b3f131b911d6bc0782da8c14ce4

[ "Apache-2.0" ]

null

tests/invalid/type_enum.py

anthem-ai/fhir-types

42348655fb3a9b3f131b911d6bc0782da8c14ce4

[ "Apache-2.0" ]

null

from fhir_types import FHIR_Patient p: FHIR_Patient = {"gender": "mail"}

18.5

36

0.743243

11

74

4.727273

0.727273

0.423077

0

0.135135

74

3

37

24.666667

0.8125

0

0.135135

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

5aff4b608618ed1aa9318dbfab951aa942848689

176

py

Python

settings/django_settings/cfg_prod.py

thitta/Someone.tw-Blog

b38669877f269006fcbeb5544ec3054acfef5128

[ "Apache-2.0" ]

3

2019-05-04T01:30:40.000Z

2019-10-15T03:21:29.000Z

settings/django_settings/cfg_prod.py

thitta/Someone.tw-Blog

b38669877f269006fcbeb5544ec3054acfef5128

[ "Apache-2.0" ]

8

2020-02-12T00:09:35.000Z

2022-02-10T08:40:10.000Z

settings/django_settings/cfg_prod.py

thitta/Someone.tw-Blog

b38669877f269006fcbeb5544ec3054acfef5128

[ "Apache-2.0" ]

null

DEBUG = False ALLOWED_HOSTS = ["someone.tw", "blog.someone.tw", "www.someone.tw", "128.199.149.10"] STATIC_URL = 'https://storage.googleapis.com/blog-someone-tw-static/site/'

35.2

85

0.715909

27

176

4.592593

0.703704

0.290323

0.209677

0

0.067485

0.073864

176

4

86

44

0.693252

0

0.636364

0

1

0

false

0

1

0

null

1

0

1

0

1

0

null

0

5

852115df3213ad90cf9b078d620a244ed9ae7ed0

32

py

Python

resizeright/__init__.py

alexhagen/ResizeRight

0ba9eaac7e7a73b639180ba23d98adce48c1ec57

[ "MIT" ]

null

resizeright/__init__.py

alexhagen/ResizeRight

0ba9eaac7e7a73b639180ba23d98adce48c1ec57

[ "MIT" ]

null

resizeright/__init__.py

alexhagen/ResizeRight

0ba9eaac7e7a73b639180ba23d98adce48c1ec57

[ "MIT" ]

null

from .resize_right import resize

32

0.875

5

32

5.4

0.8

0

0.09375

32

1

32

0.931034

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

517442ed0c4dd697a07e82ffa940f98ff6002947

127

py

Python

03.Complete Python Developer - Zero to Mastery - AN/04.Advanced Python Functional Programming/map.py

ptyadana/python-dojo

98c7234b84f0afea99a091c7198342d66bbdff5b

[ "MIT" ]

3

2020-06-01T04:17:18.000Z

2020-12-18T03:05:55.000Z

03.Complete Python Developer - Zero to Mastery - AN/04.Advanced Python Functional Programming/map.py

ptyadana/python-dojo

98c7234b84f0afea99a091c7198342d66bbdff5b

[ "MIT" ]

1

2020-04-25T08:01:59.000Z

03.Complete Python Developer - Zero to Mastery - AN/04.Advanced Python Functional Programming/map.py

ptyadana/python-dojo

98c7234b84f0afea99a091c7198342d66bbdff5b

[ "MIT" ]

7

2020-04-26T10:02:36.000Z

2021-06-08T05:12:46.000Z

#map def multiply_by_two(item): return item*2 my_list = [1,2,3] print(my_list) print(list(map(multiply_by_two, my_list)))

15.875

42

0.724409

25

127

3.4

0.52

0.211765

0.305882

0

0.036036

0.125984

127

7

43

18.142857

0.72973

0.023622

0

1

0.2

false

0

0.2

0.4

1

0

null

1

0

1

0

null

0

1

0

5

518bd21174229fbc45b75642d1272497dae68adf

74

py

Python

byconeer/lib/__init__.py

sofiapfund/bycon

d7993eaf99cfce46f3025718ab3aa3c0f812badd

[ "CC0-1.0" ]

null

byconeer/lib/__init__.py

sofiapfund/bycon

d7993eaf99cfce46f3025718ab3aa3c0f812badd

[ "CC0-1.0" ]

1

2021-03-18T12:17:59.000Z

2021-03-18T12:19:24.000Z

byconeer/lib/__init__.py

sofiapfund/bycon

d7993eaf99cfce46f3025718ab3aa3c0f812badd

[ "CC0-1.0" ]

null

# __init__.py from .table_tools import * from .publication_utils import *

18.5

32

0.783784

10

74

5.2

0.8

0

0.135135

74

3

33

24.666667

0.8125

0.148649

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

51ab65493b66211277baa7db6b16138562290d3c

389

py

Python

moka/numeric.py

zhengpingzhou/pymoka

7ad4ee3eb97e656ade7b31ff4400db633854712a

[ "MIT" ]

2

2020-09-13T08:15:47.000Z

2021-02-19T07:29:44.000Z

moka/numeric.py

zhengpingzhou/pymoka

7ad4ee3eb97e656ade7b31ff4400db633854712a

[ "MIT" ]

null

moka/numeric.py

zhengpingzhou/pymoka

7ad4ee3eb97e656ade7b31ff4400db633854712a

[ "MIT" ]

null

import random import numpy.linalg as LA def normalize(value, value_min, value_max): """Map value from [value_min, value_max] to [-1, 1]""" return 2 * ((value - value_min) / (value_max - value_min)) - 1 def unnormalize(value, value_min, value_max): """Map value from [-1, 1] to [value_min, value_max]""" return ((value + 1) / 2.0 * (value_max - value_min) + value_min)

27.785714

68

0.652956

62

389

3.870968

0.306452

0.266667

0.325

0.333333

0.3625

0.275

0

0.028662

0.192802

389

13

69

29.923077

0.735669

0.249357

0

1

0.333333

false

0

0.333333

0

1

0

null

1

0

null

0

1

0

1

0

5

51c86b84d59feefc6bd773989dfabe205923f9bf

120

py

Python

questionnaire/__init__.py

cjz25/cquestionnaire

961c508d463a8d9d50c8485fa65c4a9d3a56e5fa

[ "MIT" ]

null

questionnaire/__init__.py

cjz25/cquestionnaire

961c508d463a8d9d50c8485fa65c4a9d3a56e5fa

[ "MIT" ]

null

questionnaire/__init__.py

cjz25/cquestionnaire

961c508d463a8d9d50c8485fa65c4a9d3a56e5fa

[ "MIT" ]

1

2021-10-15T12:51:01.000Z

class Sequence: def __init__(self, old_seq, new_seq): self.old_seq = old_seq self.new_seq = new_seq

24

41

0.65

19

120

3.578947

0.421053

0.264706

0.294118

0

0.266667

120

4

42

30

0.772727

0

1

0.25

false

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

51cb168625fc743eca63cdf8bb5092c8a2551b37

103

py

Python

examples/simple/test_simple.py

kuss/pytest-convey

46ec70721e7403d43465f11795da09053e5a963e

[ "MIT" ]

7

2019-08-16T06:30:12.000Z

2021-02-09T22:45:27.000Z

examples/simple/test_simple.py

kuss/pytest-board

46ec70721e7403d43465f11795da09053e5a963e

[ "MIT" ]

1

2021-10-15T11:08:15.000Z

examples/simple/test_simple.py

kuss/pytest-convey

46ec70721e7403d43465f11795da09053e5a963e

[ "MIT" ]

null

def test_pass(): assert True def test_fail(): assert False def test_exception(): x = 1/0

11.444444

21

0.631068

16

103

3.875

0.6875

0.33871

0

0.026316

0.262136

103

8

22

12.875

0.789474

0

0.333333

1

0.5

false

0.166667

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

51f92a2c6513baddca3c660fe1f56cdcee61c54a

373

py

Python

test_covid_news_handling.py

RhianMackintosh/ECM1400-Coursework

d579f843a08725e0ab593f715f3a5eceeb73f6ec

[ "BSD-4-Clause-UC" ]

null

test_covid_news_handling.py

RhianMackintosh/ECM1400-Coursework

d579f843a08725e0ab593f715f3a5eceeb73f6ec

[ "BSD-4-Clause-UC" ]

null

test_covid_news_handling.py

RhianMackintosh/ECM1400-Coursework

d579f843a08725e0ab593f715f3a5eceeb73f6ec

[ "BSD-4-Clause-UC" ]

null

from covid_news_handling import * """ This module provides tests for the functions in the covid_news_handling module """ def test_news_API_request(): assert news_API_request() == news_API_request("Covid COVID-19 coronavirus"), "Test failed: default covid terms" assert isinstance(list, news_API_request()), "Test failed: list returned from news request"

37.3

116

0.756032

52

373

5.173077

0.5

0.104089

0.208178

0

0.006369

0.158177

373

9

117

41.444444

0.850318

0

0.366906

0

0.5

1

0.25

true

0

0.25

0

0.5

0

null

0

1

0

1

0

null

0

1

0

1

0

5

cfc21b2b6383464ee2d24b1e11f37268e134aa55

306

py

Python

IOMC/EventVertexGenerators/python/VtxSmearedRealistic5TeVPA2016Collision_cfi.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

852

2015-01-11T21:03:51.000Z

2022-03-25T21:14:00.000Z

IOMC/EventVertexGenerators/python/VtxSmearedRealistic5TeVPA2016Collision_cfi.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

30,371

2015-01-02T00:14:40.000Z

2022-03-31T23:26:05.000Z

IOMC/EventVertexGenerators/python/VtxSmearedRealistic5TeVPA2016Collision_cfi.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

3,240

2015-01-02T05:53:18.000Z

2022-03-31T17:24:21.000Z

import FWCore.ParameterSet.Config as cms from IOMC.EventVertexGenerators.VtxSmearedParameters_cfi import Realistic5TeVPACollision2016VtxSmearingParameters,VtxSmearedCommon VtxSmeared = cms.EDProducer("BetafuncEvtVtxGenerator", Realistic5TeVPACollision2016VtxSmearingParameters, VtxSmearedCommon )

38.25

130

0.882353

20

306

13.45

0.8

0.483271

0

0.035336

0.075163

306

7

131

43.714286

0.915194

0

0.075163

0

1

0

false

0

0.333333

0

0.333333

0

1

0

1

null

1

0

1

0

null

0

1

0

5

5c713b2eff972a9ff68ddaba928a8edc4cf17d08

220

py

Python

app/v2/inbound_sms/__init__.py

tlwr/notifications-api

88a6b7729edb9be41ce3e7c027f1452b7b6d00d2

[ "MIT" ]

10

2020-05-04T14:11:06.000Z

2022-02-22T19:06:36.000Z

app/v2/inbound_sms/__init__.py

tlwr/notifications-api

88a6b7729edb9be41ce3e7c027f1452b7b6d00d2

[ "MIT" ]

554

2020-05-07T21:56:24.000Z

2022-03-31T23:04:51.000Z

app/v2/inbound_sms/__init__.py

tlwr/notifications-api

88a6b7729edb9be41ce3e7c027f1452b7b6d00d2

[ "MIT" ]

4

2020-08-27T16:43:29.000Z

2021-02-17T22:17:27.000Z

from flask import Blueprint from app.v2.errors import register_errors v2_inbound_sms_blueprint = Blueprint("v2_inbound_sms", __name__, url_prefix='/v2/received-text-messages') register_errors(v2_inbound_sms_blueprint)

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py

Python

scanpy/queries/__init__.py

mkmkryu/scanpy2

f3db32a142dc31c1b628380db1c969a6d0b9dc3a

[ "BSD-3-Clause" ]

1,171

2017-01-17T14:01:02.000Z

2022-03-31T23:02:57.000Z

scanpy/queries/__init__.py

mkmkryu/scanpy2

f3db32a142dc31c1b628380db1c969a6d0b9dc3a

[ "BSD-3-Clause" ]

1,946

2017-01-22T10:19:04.000Z

2022-03-31T17:13:03.000Z

scanpy/queries/__init__.py

mkmkryu/scanpy2

f3db32a142dc31c1b628380db1c969a6d0b9dc3a

[ "BSD-3-Clause" ]

499

2017-01-21T11:39:29.000Z

2022-03-23T13:57:35.000Z

from ._queries import ( biomart_annotations, gene_coordinates, mitochondrial_genes, ) # Biomart queries from ._queries import enrich # gprofiler queries

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py

Python

starspace/data.py

chanzuckerberg/spatial-warehouse

ce5ac5345af02ec7d2c58153fd01ab5499574a45

[ "MIT" ]

6

2019-10-16T15:36:54.000Z

2021-01-12T16:56:23.000Z

starspace/data.py

chanzuckerberg/spatial-warehouse

ce5ac5345af02ec7d2c58153fd01ab5499574a45

[ "MIT" ]

5

2019-10-07T20:02:50.000Z

2020-03-11T03:49:22.000Z

starspace/data.py

chanzuckerberg/spatial-warehouse

ce5ac5345af02ec7d2c58153fd01ab5499574a45

[ "MIT" ]

2

2020-02-25T17:06:34.000Z

2021-11-09T19:28:54.000Z

from .classes import Matrix, Spots, Regions # TODO add more data to s3, add to this module. class osmFISH: @staticmethod def matrix(): url = ("s3://starspace.data/formatted/osmfish_codeluppi_2018_nat-methods_somatosensory-cortex/" "osmfish-codeluppi-2018-nat-methods-somatosensory-cortex.matrix.zarr/") return Matrix.load_zarr(url) @staticmethod def spots(): url = ("s3://starspace.data/formatted/osmfish_codeluppi_2018_nat-methods_somatosensory-cortex/" "osmfish-codeluppi-2018-nat-methods-somatosensory-cortex.spots.zarr/") return Spots.load_zarr(url) @staticmethod def regions(): url = ("s3://starspace.data/formatted/osmfish_codeluppi_2018_nat-methods_somatosensory-cortex/" "osmfish-codeluppi-2018-nat-methods-somatosensory-cortex.regions.zarr/") return Regions.load_zarr(url)

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py

Python

metacrypt/__init__.py

analyticsdept/py-cli-decrypt

7a867957368ce99775ff3e3074a80b85d7a96ae5

[ "MIT" ]

null

metacrypt/__init__.py

analyticsdept/py-cli-decrypt

7a867957368ce99775ff3e3074a80b85d7a96ae5

[ "MIT" ]

null

metacrypt/__init__.py

analyticsdept/py-cli-decrypt

7a867957368ce99775ff3e3074a80b85d7a96ae5

[ "MIT" ]

null

from .metacrypt import MetaCrypt

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269

py

Python

skbeam/core/tests/utils.py

mrakitin/scikit-beam

89fe81486431b72df4dc497564867b9b3a26ee26

[ "BSD-3-Clause" ]

71

2016-01-04T22:32:27.000Z

2022-03-25T07:57:54.000Z

skbeam/core/tests/utils.py

mrakitin/scikit-beam

89fe81486431b72df4dc497564867b9b3a26ee26

[ "BSD-3-Clause" ]

288

2015-12-09T23:40:31.000Z

2021-02-02T00:32:00.000Z

skbeam/core/tests/utils.py

mrakitin/scikit-beam

89fe81486431b72df4dc497564867b9b3a26ee26

[ "BSD-3-Clause" ]

53

2015-12-10T14:35:17.000Z

2021-06-24T13:36:00.000Z

from __future__ import print_function, absolute_import, division import numpy as np def parabola_gen(x, center, height, width): return width * (x-center)**2 + height def gauss_gen(x, center, height, width): return height * np.exp(-((x-center) / width)**2)

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7a8fb22d5ba96d5a17babfb8cd0a6394cfffba97

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py

Python

models/UPCC/__init__.py

TD21forever/QoS-Predcition-Algorithm-library

f4503462887d719a39c9ccddd6cc55546e783fd5

[ "MIT" ]

2

2022-02-08T08:19:59.000Z

2022-02-17T01:42:54.000Z

models/UPCC/__init__.py

TD21forever/QoS-Predcition-Algorithm-library

f4503462887d719a39c9ccddd6cc55546e783fd5

[ "MIT" ]

null

models/UPCC/__init__.py

TD21forever/QoS-Predcition-Algorithm-library

f4503462887d719a39c9ccddd6cc55546e783fd5

[ "MIT" ]

null

from .model import UPCCModel

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1

0

5

7a99cf29c8b32fb953166fbbcd9d8b70f80366ba

577

py

Python

pymoo/rand/impl/numpy_random_generator.py

yashvesikar/pymoo

8ce725671d95df580654568fa9bc0e53268aff5d

[ "MIT" ]

null

pymoo/rand/impl/numpy_random_generator.py

yashvesikar/pymoo

8ce725671d95df580654568fa9bc0e53268aff5d

[ "MIT" ]

null

pymoo/rand/impl/numpy_random_generator.py

yashvesikar/pymoo

8ce725671d95df580654568fa9bc0e53268aff5d

[ "MIT" ]

null

import numpy as np from pymoo.rand.random_generator import RandomGenerator class NumpyRandomGenerator(RandomGenerator): def seed(self, x): np.random.seed(x) def rand(self, size=None): if size is None: return np.random.random() elif isinstance(size, int): return np.random.random(size) else: return np.random.random((size[0], size[1])) def randint(self, low, high, size=None): return np.random.randint(low, high, size) def perm(self, n): return np.random.permutation(n)

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7aba5d2dfd4f66bd15f5cf87af550886b48f2d7c

158

py

Python

trillian/helpers.py

projectsbyif/trillian-demo-python-api-client

5ab5de705cffe27d4ef0c23b46d0eeb40dac7f46

[ "Apache-2.0" ]

null

trillian/helpers.py

projectsbyif/trillian-demo-python-api-client

5ab5de705cffe27d4ef0c23b46d0eeb40dac7f46

[ "Apache-2.0" ]

null

trillian/helpers.py

projectsbyif/trillian-demo-python-api-client

5ab5de705cffe27d4ef0c23b46d0eeb40dac7f46

[ "Apache-2.0" ]

1

2019-04-01T02:15:18.000Z

import base64 def to_b64(binary): return base64.b64encode(binary).decode('ascii') def from_b64(base64_text): return base64.b64decode(base64_text)

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8fa7524ec5e06301c03cb2a6ee1c9f90b63d7c7a

149

py

Python

br2gm/constants.py

vpavlin/br2gm

7e9c5f293e119a263402728ad0f45149cfdcfa17

[ "MIT" ]

1

2015-04-14T07:49:05.000Z

br2gm/constants.py

vpavlin/br2gm

7e9c5f293e119a263402728ad0f45149cfdcfa17

[ "MIT" ]

null

br2gm/constants.py

vpavlin/br2gm

7e9c5f293e119a263402728ad0f45149cfdcfa17

[ "MIT" ]

null

#!/usr/bin/env python from os.path import expanduser, join DEFAULT_CREDS_NAME=".br2gm_auth" DEFAULT_CREDS=join(expanduser("~"), DEFAULT_CREDS_NAME)

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891182127b6b9c6d2cc9d4603f145f19203dc00d

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py

Python

packetsniffer/sniffer.py

malgulam/100ProjectsOfCode

95026b15d858a6e97dfd847c5ec576bbc260ff61

[ "MIT" ]

8

2020-12-13T16:15:34.000Z

2021-11-13T22:45:28.000Z

packetsniffer/sniffer.py

malgulam/100ProjectsOfCode

95026b15d858a6e97dfd847c5ec576bbc260ff61

[ "MIT" ]

1

2021-06-02T03:42:39.000Z

packetsniffer/sniffer.py

malgulam/100ProjectsOfCode

95026b15d858a6e97dfd847c5ec576bbc260ff61

[ "MIT" ]

1

2020-12-14T20:01:14.000Z

#!/usr/bin/python3 #imports import socket import struct import binascii #platform module to check the system type #import os import platform platform_ = str(platform.system()).lower() #for packet interface, we'll use PF_PACKET for linux and #AF_INET for window if 'linux' or 'x' in platform_: s = socket.socket(socket.PF_PACKET, socket.SOCK_RAW, socket.htons(0x0800)) #recvfrom to receive packets...using 2048(from tutorials(seems to be the best guess!)) while True: packet = s.recvfrom(2048) #ripping ethernet header eth_header = packet[0][0:14] #unpacking the header with the struct method eth_header = struct.unpack("!6s6s2s", eth_header) print(f'DESTINATION MAC: {binascii.hexlify(eth_header[0])} Source MAC:{binascii.hexlify(eth_header[1])} TYPE: {binascii.hexlify(eth_header[2])}') ipheader = packet[0][14:34] ip_header = struct.unpack("!12s4s4s", ipheader) print(f'SOURCE IP:{socket.inet_ntoa(ip_header[1])} DESTINATION IP:{socket.inet_ntoa(ip_header[2])}') elif 'windows' or 'win' in platform: s = socket.socket(socket.AF_INET, socket.SOCK_RAW, socket.htons(0x0800)) #recvfrom to receive packets...using 2048(from tutorials(seems to be the best guess!)) while True: packet = s.recvfrom(2048) #ripping ethernet header eth_header = packet[0][0:14] #unpacking the header with the struct method eth_header = struct.unpack("!6s6s2s", eth_header) print(f'DESTINATION MAC: {binascii.hexlify(eth_header[0])} Source MAC:{binascii.hexlify(eth_header[1])} TYPE: {binascii.hexlify(eth_header[2])}') ipheader = packet[0][14:34] ip_header = struct.unpack("!12s4s4s", ipheader) print(f'SOURCE IP:{socket.inet_ntoa(ip_header[1])} DESTINATION IP:{socket.inet_ntoa(ip_header[2])}') else: print('Unknown platform!Modify script!')

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py

Python

pyobjconfig/__init__.py

wwoods/pyobjconfig

7a47e72643c8e8d2c6e5824caf6630f2eb96270b

[ "MIT" ]

null

pyobjconfig/__init__.py

wwoods/pyobjconfig

7a47e72643c8e8d2c6e5824caf6630f2eb96270b

[ "MIT" ]

2

2022-03-08T16:34:28.000Z

2022-03-08T18:09:22.000Z

pyobjconfig/__init__.py

wwoods/pyobjconfig

7a47e72643c8e8d2c6e5824caf6630f2eb96270b

[ "MIT" ]

null

from .common import ConfigurableObject, ConfigurableSwitch from pydantic import BaseModel as PydanticBaseModel

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8f42bf2b59b1704061a939bfe6a1aafe18882b5b

186

py

Python

authentication/admin.py

jjlorenzo/django_multitenant

ad1c111fc1246380ee1001e4b04d9469599b9518

[ "MIT" ]

null

authentication/admin.py

jjlorenzo/django_multitenant

ad1c111fc1246380ee1001e4b04d9469599b9518

[ "MIT" ]

null

authentication/admin.py

jjlorenzo/django_multitenant

ad1c111fc1246380ee1001e4b04d9469599b9518

[ "MIT" ]

1

2020-09-11T20:43:36.000Z

from __future__ import absolute_import from .models import Practice from .models import User from django.contrib import admin admin.site.register(Practice) admin.site.register(User)

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8f61bb2bb8d71085a10db639d8d03d9ccda1c654

160

py

Python

app/main/errors.py

rickmutua/news-app

2568bdf79ee03c22c54afaa70fdd3970eb6a7772

[ "MIT" ]

null

app/main/errors.py

rickmutua/news-app

2568bdf79ee03c22c54afaa70fdd3970eb6a7772

[ "MIT" ]

null

app/main/errors.py

rickmutua/news-app

2568bdf79ee03c22c54afaa70fdd3970eb6a7772

[ "MIT" ]

null

from flask import render_template from . import main @main.app_errorhandler(404) def four_0w_four(error): return render_template('four0wfour.html'), 404

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8f6c1f2f9c232a0621261b7669e12ff4269c0463

206

py

Python

src/main.py

trilader/frischluft-firmware

c24bed143db4af991a4626e5faab35878e68504a

[ "Apache-2.0" ]

7

2021-05-26T20:26:36.000Z

2021-06-05T17:17:24.000Z

src/main.py

trilader/frischluft-firmware

c24bed143db4af991a4626e5faab35878e68504a

[ "Apache-2.0" ]

4

2021-05-28T13:39:28.000Z

2021-06-27T20:48:47.000Z

src/main.py

trilader/frischluft-firmware

c24bed143db4af991a4626e5faab35878e68504a

[ "Apache-2.0" ]

2

2021-05-28T15:01:28.000Z

2021-05-28T16:11:05.000Z

# Early 2021 # Author metachris # Part of frischluft.works # Filename: main.py # Purpose: .mpy migration after we ran out of memory # License Details found @ /LICENSE file in this repository import start

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py

Python

code/python/filters.py

funked1/pieper_md

bd541dc9cec86b795abafd0648ae0114c3d20a91

[ "MIT" ]

null

code/python/filters.py

funked1/pieper_md

bd541dc9cec86b795abafd0648ae0114c3d20a91

[ "MIT" ]

3

2020-04-26T18:48:48.000Z

2020-04-26T18:52:40.000Z

code/python/filters.py

funked1/pieper_md

bd541dc9cec86b795abafd0648ae0114c3d20a91

[ "MIT" ]

null

from scipy import signal import numpy as np from scipy.signal import kaiserord, lfilter, firwin, freqz from pylab import figure, clf, plot, xlabel, ylabel, xlim, ylim, title, grid, axes, show import matplotlib.pyplot as plt def lpf_40(fs): width = 5.0 / fs ripple_db = 60 N, beta = kaiserord(ripple_db, width) cutoff_hz = 40 taps = firwin(N, cutoff_hz, window=('kaiser', beta), pass_zero='lowpass', fs=fs) #-------------------------------------------------------------------------- # Plot magnitude response of the filter #-------------------------------------------------------------------------- """ freq, h = signal.freqz(taps, 1, fs=fs) h_db = 20 * np.log10(abs(h)) fig, ax = plt.subplots() ax.plot(freq, h_db, color='green') ax.set_title('40 Hz Lowpass Filter Frequency Response', fontsize='15', fontweight='bold') ax.set_ylabel('Amplitude (dB)', fontsize='15', fontweight='bold') ax.set_xlabel('Frequency (Hz)', fontsize='15', fontweight='bold') ax.tick_params(axis='both', which='major', labelsize="15") ax.set_xlim([0, 100]) ax.grid() plt.show() """ return taps def notch_50(fs): f0 = 50.0 # Frequency to be removed Q = 30.0 zeros, poles = signal.iirnotch(f0, Q, fs) #-------------------------------------------------------------------------- # Plot magnitude response of the filter #-------------------------------------------------------------------------- """ freq, h = signal.freqz(zeros, poles, fs=fs) # frequency response h_db = 20 * np.log10(abs(h)) fig, ax = plt.subplots() ax.plot(freq, h_db, color='green') ax.set_title('50 Hz Notch Filter Frequency Response', fontsize='15', fontweight='bold') ax.set_ylabel('Amplitude (dB)', fontsize='15', fontweight='bold') ax.set_xlabel('Frequency (Hz)', fontsize='15', fontweight='bold') ax.tick_params(axis='both', which='major', labelsize="15") ax.set_xlim([0, 100]) ax.set_ylim([-25, 10]) ax.grid() plt.show() """ return [zeros, poles] def notch_60(fs): f0 = 60.0 # Frequency to be removed Q = 30.0 zeros, poles = signal.iirnotch(f0, Q, fs) #-------------------------------------------------------------------------- # Plot magnitude response of the filter #-------------------------------------------------------------------------- """ freq, h = signal.freqz(zeros, poles, fs=fs) # frequency response h_db = 20 * np.log10(abs(h)) fig, ax = plt.subplots() ax.plot(freq, h_db, color='green') ax.set_title('60 Hz Notch Filter Frequency Response', fontsize='15', fontweight='bold') ax.set_ylabel('Amplitude (dB)', fontsize='15', fontweight='bold') ax.set_xlabel('Frequency (Hz)', fontsize='15', fontweight='bold') ax.tick_params(axis='both', which='major', labelsize="15") ax.set_xlim([0, 100]) ax.set_ylim([-25, 10]) ax.grid() plt.show() """ return [zeros, poles]

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56c2e9fdc3793ab3711cbba5f07a0175346bc477

164

py

Python

tdml/dataframe/dataframe.py

zechengz/tdml

af60d35b7b62259e414edaa0a45fb2d3563b0430

[ "MIT" ]

2

2020-08-08T00:36:23.000Z

2021-06-21T19:51:30.000Z

tdml/dataframe/dataframe.py

zechengz/tdml

af60d35b7b62259e414edaa0a45fb2d3563b0430

[ "MIT" ]

null

tdml/dataframe/dataframe.py

zechengz/tdml

af60d35b7b62259e414edaa0a45fb2d3563b0430

[ "MIT" ]

1

2020-10-06T19:40:41.000Z

def toPandas(df): """ Transform the dataframe into the Pandas dataframe. Args: df: Dataframe in specified package. Returns: A Pandas dataframe. """ pass

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py

Python

aries_cloudagent/vc/tests/dids/did_example_489398593.py

kuraakhilesh8230/aries-cloudagent-python

ee384d1330f6a50ff45a507392ce54f92900f23a

[ "Apache-2.0" ]

247

2019-07-02T21:10:21.000Z

2022-03-30T13:55:33.000Z

aries_cloudagent/vc/tests/dids/did_example_489398593.py

kuraakhilesh8230/aries-cloudagent-python

ee384d1330f6a50ff45a507392ce54f92900f23a

[ "Apache-2.0" ]

1,462

2019-07-02T20:57:30.000Z

2022-03-31T23:13:35.000Z

aries_cloudagent/vc/tests/dids/did_example_489398593.py

kuraakhilesh8230/aries-cloudagent-python

ee384d1330f6a50ff45a507392ce54f92900f23a

[ "Apache-2.0" ]

377

2019-06-20T21:01:31.000Z

2022-03-30T08:27:53.000Z

DID_EXAMPLE_48939859 = { "@context": "https://www.w3.org/ns/did/v1", "id": "did:example:489398593", "assertionMethod": [ { "id": "did:example:489398593#test", "type": "Bls12381G2Key2020", "controller": "did:example:489398593", "publicKeyBase58": "oqpWYKaZD9M1Kbe94BVXpr8WTdFBNZyKv48cziTiQUeuhm7sBhCABMyYG4kcMrseC68YTFFgyhiNeBKjzdKk9MiRWuLv5H4FFujQsQK2KTAtzU8qTBiZqBHMmnLF4PL7Ytu", } ], }

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1

null

0

5

712e715e7339b903c6a7a5f4bf3b643795f3ea90

103

py

Python

website/about/admin.py

phayv/open_project

2ab2b87683ea120f6f7baa734df9a6920716232b

[ "BSD-3-Clause" ]

null

website/about/admin.py

phayv/open_project

2ab2b87683ea120f6f7baa734df9a6920716232b

[ "BSD-3-Clause" ]

14

2020-03-24T15:57:26.000Z

2022-03-11T23:26:57.000Z

website/about/admin.py

phayv/open_project

2ab2b87683ea120f6f7baa734df9a6920716232b

[ "BSD-3-Clause" ]

1

2018-08-01T02:17:01.000Z

from django.contrib import admin from about.models import UserProfile admin.site.register(UserProfile)

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true

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854090c93e71c710dec79c570953ac1fb920dcdc

55

py

Python

nni/algorithms/hpo/ppo_tuner/__init__.py

dutxubo/nni

c16f4e1c89b54b8b80661ef0072433d255ad2d24

[ "MIT" ]

9,680

2019-05-07T01:42:30.000Z

2022-03-31T16:48:33.000Z

nni/algorithms/hpo/ppo_tuner/__init__.py

dutxubo/nni

c16f4e1c89b54b8b80661ef0072433d255ad2d24

[ "MIT" ]

1,957

2019-05-06T21:44:21.000Z

2022-03-31T09:21:53.000Z

nni/algorithms/hpo/ppo_tuner/__init__.py

dutxubo/nni

c16f4e1c89b54b8b80661ef0072433d255ad2d24

[ "MIT" ]

1,571

2019-05-07T06:42:55.000Z

2022-03-31T03:19:24.000Z

from .ppo_tuner import PPOTuner, PPOClassArgsValidator

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55

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0.090909

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1

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1

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5

856f899f63bdd9e468bb0c9913661ad5a365256b

23

py

Python

Chapter 04/ch4_3_14.py

bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE

f6a4194684515495d00aa38347a725dd08f39a0c

[ "MIT" ]

null

Chapter 04/ch4_3_14.py

bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE

f6a4194684515495d00aa38347a725dd08f39a0c

[ "MIT" ]

null

Chapter 04/ch4_3_14.py

bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE

f6a4194684515495d00aa38347a725dd08f39a0c

[ "MIT" ]

null

print(bool(3.14)) #True

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187

py

Python

boost_adaptbx/tests/tst_rational_truediv.py

rimmartin/cctbx_project

644090f9432d9afc22cfb542fc3ab78ca8e15e5d

[ "BSD-3-Clause-LBNL" ]

null

boost_adaptbx/tests/tst_rational_truediv.py

rimmartin/cctbx_project

644090f9432d9afc22cfb542fc3ab78ca8e15e5d

[ "BSD-3-Clause-LBNL" ]

null

boost_adaptbx/tests/tst_rational_truediv.py

rimmartin/cctbx_project

644090f9432d9afc22cfb542fc3ab78ca8e15e5d

[ "BSD-3-Clause-LBNL" ]

null

from __future__ import division import libtbx.load_env import os execfile(libtbx.env.under_dist("boost_adaptbx", os.path.join("tests", "tst_rational.py")))

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1

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1

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5

a48edac983626719434d0d83f572375c318cf9c9

12,399

py

Python

evology/research/icml/asym_analysis_scholl.py

aymericvie/evology

8f00d94dee7208be5a5bdd0375a9d6ced25097f4

[ "Apache-2.0" ]

null

evology/research/icml/asym_analysis_scholl.py

aymericvie/evology

8f00d94dee7208be5a5bdd0375a9d6ced25097f4

[ "Apache-2.0" ]

2

2022-01-10T02:10:56.000Z

2022-01-14T03:41:42.000Z

evology/research/icml/asym_analysis_scholl.py

aymericvie/evology

8f00d94dee7208be5a5bdd0375a9d6ced25097f4

[ "Apache-2.0" ]

null

import pandas as pd import matplotlib.pyplot as plt import seaborn as sns import numpy as np from scipy.ndimage.filters import gaussian_filter import ternary import numpy as np from ternary.helpers import simplex_iterator from matplotlib.colors import ListedColormap sns.set(font_scale=1) scale = 25 fontsize = 18 data = pd.read_csv( "/Users/aymericvie/Documents/GitHub/evology/evology/research/icml/data/asym_dis_scholl.csv" ) # Removing the sum 0 or sum nan runs does not seem necessary data_group = data.groupby( ["WS_VI_initial", "WS_TF_initial", "WS_NT_initial"], as_index=False ).mean() def generate_random_heatmap_data(scale): tf_ws = dict() vi_ws = dict() nt_ws = dict() attractor = dict() l = 0 for (i, j, k) in simplex_iterator(scale): nt_ws[(i, j)] = data_group.loc[l, "WS_NT_final"] vi_ws[(i, j)] = data_group.loc[l, "WS_VI_final"] tf_ws[(i, j)] = data_group.loc[l, "WS_TF_final"] if data_group.loc[l, "WS_TF_final"] >= 90: attractor[(i, j)] = 0 elif data_group.loc[l, "WS_TF_final"] > 10: attractor[(i, j)] = 1 else: attractor[(i, j)] = 2 l += 1 return nt_ws, vi_ws, tf_ws, attractor nt_r, vi_r, tf_r, attractor = generate_random_heatmap_data(scale) figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(nt_r, style='triangular') tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('NT final wealth share', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/WS_NT_scholl.png',dpi=300) #plt.show() figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(vi_r, style='triangular') tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('VI final wealth share', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/WS_VI_scholl.png',dpi=300) #plt.show() figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(tf_r, style='triangular') tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('TF final wealth share', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/WS_TF_scholl.png',dpi=300) #plt.show() cmap = plt.get_cmap('inferno', 3) cmap = ListedColormap(['red', 'grey', 'blue']) figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(attractor, style='triangular',cmap=cmap, colorbar=False) tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('Basins of attraction', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/basins_scholl.png',dpi=300) #plt.show() def gen_data(scale): gens = dict() l = 0 for (i, j, k) in simplex_iterator(scale): gens[(i, j)] = data_group.loc[l, "Gen"] l += 1 return gens """ Density/diffusion plot for generations """ gens = gen_data(scale) figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(gens, style='triangular') tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('Max generations', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/generations_scholl.png',dpi=300) #plt.show() # Difference in returns # Result: regions with early extinctions correspond to high difference in returns; # these are regions that are by nature imbalanced and pushing to the boundary. def gen_data(scale): gens = dict() l = 0 for (i, j, k) in simplex_iterator(scale): gens[(i, j)] = data_group.loc[l, "AvgDiffReturns"] if data_group.loc[l, "AvgDiffReturns"] > 10: gens[(i, j)] = 10 l += 1 return gens gens = gen_data(scale) figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(gens, style='triangular') tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('Avg diff returns', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/diff_returns_scholl.png',dpi=300) #plt.show() def gen_data(scale): gens = dict() l = 0 for (i, j, k) in simplex_iterator(scale): gens[(i, j)] = data_group.loc[l, "AvgDiffReturns"] if data_group.loc[l, "AvgDiffReturns"] > 1: gens[(i, j)] = 1 l += 1 return gens gens = gen_data(scale) figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(gens, style='triangular') tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('Avg diff returns', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/diff_returns_scholl2.png',dpi=300) #plt.show() def PathPoints(data): points = [] for i in range(len(data["WS_NT_final"])): x = (data.loc[i, "WS_VI_final"] / 100) * scale y = (data.loc[i, "WS_TF_final"] / 100) * scale z = (data.loc[i, "WS_NT_final"] / 100) * scale points.append((x, y, z)) return points points = PathPoints(data) # origin = [((100/3, 100/3, 100/3))] figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.gridlines(color="gray", multiple=10) tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.bottom_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.scatter(points, marker='D', color='red', label="Simulations") tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.get_axes().axis('off') tax.set_title('Scatterplot', fontsize=fontsize) plt.legend(loc='upper right', fontsize=fontsize) plt.tight_layout() tax._redraw_labels() plt.savefig('figures/scatterplot_scholl.png',dpi=300) # plt.show() """ density """ def PathPoints(df): points = [] N = len(df) for i in range(N): x = int((df.loc[i, "WS_VI_final"] / 100) * scale) y = int((df.loc[i, "WS_TF_final"] / 100) * scale) z = int((df.loc[i, "WS_NT_final"] / 100) * scale) points.append((x, y, z)) return points points = PathPoints(data) def DensityData(points, scale): density = dict() total_count = (scale + 1) * (scale + 2) / 2 sum_count = 0 total_enum = 0 for (i, j, k) in simplex_iterator(scale): count = 0 total_enum += 1 for point in points: if i == point[0] and j == point[1]: count += 1 density[(i, j)] = (count / total_count) / 10 sum_count += density[(i, j)] return density # scale = 24 # to remove the artifact attractor scale = 25 #cant set scale more than the experiment setting (25) density = DensityData(points, scale) figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(density, style="triangular", cmap="Reds", vmin=0, vmax=0.15) tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks=ticks, axis="blr", linewidth=1, multiple=10) tax.bottom_axis_label("VI Final Wealth Share (%)", fontsize=fontsize) tax.left_axis_label("NT Final Wealth Share (%)", fontsize=fontsize) tax.right_axis_label("TF Final Wealth Share (%)", fontsize=fontsize) tax.get_axes().axis("off") tax.set_title("Wealth asymptotic distributions density", fontsize=fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig("figures/density_scholl.png", dpi=300) #plt.show() #### SUBSTRATEGIES def gen_data(scale): tf = dict() vi = dict() nt = dict() l = 0 for (i, j, k) in simplex_iterator(scale): nt[(i, j)] = data_group.loc[l, "Mean_NT"] vi[(i, j)] = data_group.loc[l, "Mean_VI"] tf[(i, j)] = data_group.loc[l, "Mean_TF"] l += 1 return nt, vi, tf nt, vi, tf = gen_data(scale) figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(nt, style='triangular') tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('NT substrategy', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/nt_substrat_scholl.png',dpi=300) #plt.show() figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(vi, style='triangular') tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('VI substrategy', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/vi_substrat_scholl.png',dpi=300) #plt.show() figure, tax = ternary.figure(scale=scale) figure.set_size_inches(10, 8) tax.heatmap(tf, style='triangular') tax.boundary() tax.clear_matplotlib_ticks() ticks = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] tax.ticks(ticks = ticks, axis='blr', linewidth=1, multiple=10) tax.bottom_axis_label("NT Initial Wealth Share (%)", fontsize = fontsize) tax.left_axis_label("VI Initial Wealth Share (%)", fontsize = fontsize) tax.right_axis_label("TF Initial Wealth Share (%)", fontsize = fontsize) tax.get_axes().axis('off') tax.set_title('TF substrategy', fontsize = fontsize) tax._redraw_labels() plt.tight_layout() plt.savefig('figures/tf_substrat_scholl.png',dpi=300) #plt.show()

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a4988b6c33c555ef3041d4b7eff578ccdab16908

157

py

Python

wrappers/serial/simulation/surface.py

ska-telescope/algorithm-reference-library

1b2c8d6079249202864abf8c60cdea40f0f123cb

[ "Apache-2.0" ]

22

2016-12-14T11:20:07.000Z

2021-08-13T15:23:41.000Z

wrappers/serial/simulation/surface.py

ska-telescope/algorithm-reference-library

1b2c8d6079249202864abf8c60cdea40f0f123cb

[ "Apache-2.0" ]

30

2017-06-27T09:15:38.000Z

2020-09-11T18:16:37.000Z

wrappers/arlexecute/simulation/surface.py

SKA-ScienceDataProcessor/algorithm-reference-library

1b2c8d6079249202864abf8c60cdea40f0f123cb

[ "Apache-2.0" ]

20

2017-07-02T03:45:49.000Z

2019-12-11T17:19:01.000Z

""" Functions for ionospheric modelling: see SDP memo 97 """ from processing_components.simulation.surface import simulate_gaintable_from_voltage_patterns

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8efc6ccb02b93a85de313d9fae0522d63fee59b4

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py

Python

BobuxServer/bobuxserver/websockets/serverlogic.py

ItsMajestiX/Bobux

63b079727faba2e4e342dce7df45315977690584

[ "MIT" ]

null

BobuxServer/bobuxserver/websockets/serverlogic.py

ItsMajestiX/Bobux

63b079727faba2e4e342dce7df45315977690584

[ "MIT" ]

1

2021-07-29T17:52:25.000Z

BobuxServer/bobuxserver/websockets/serverlogic.py

ItsMajestiX/Bobux

63b079727faba2e4e342dce7df45315977690584

[ "MIT" ]

null

import websockets import json async def processCommand(message, path): pass

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5

f15837d12be1c9944d2217d63a329e0b31d116ad

635

py

Python

app/main/errors.py

Z-Tool/ztool-backhend

7d332dcdc088723fe33707d2679d6704ebcb9095

[ "MIT" ]

3

2017-02-16T06:50:12.000Z

2017-02-16T07:39:21.000Z

app/main/errors.py

Z-Tool/ztool-backhend

7d332dcdc088723fe33707d2679d6704ebcb9095

[ "MIT" ]

null

app/main/errors.py

Z-Tool/ztool-backhend

7d332dcdc088723fe33707d2679d6704ebcb9095

[ "MIT" ]

2

2017-02-16T07:40:06.000Z

2020-09-01T06:08:57.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- from flask import jsonify from . import main @main.app_errorhandler(400) def bad_request(e): return jsonify({'error': '403 bad request'}), 400 @main.app_errorhandler(401) def unauthorized(e): return jsonify({'error': '401 unauthorized'}), 401 @main.app_errorhandler(403) def forbidden(e): return jsonify({'error': '403 forbidden'}), 403 @main.app_errorhandler(404) def page_not_found(e): return jsonify({'error': '404 page not found'}), 404 @main.app_errorhandler(500) def internal_server_error(e): return jsonify({'error': '500 internal server error'}), 500

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f16352c6d05c7eeaba0c03e2929d4bc4bc0c921b

648

py

Python

tests/datasets/context.py

doruktiktiklar/sadedegel

3362c4b6bf07c34634313b9eafe52e6817efec60

[ "MIT" ]

null

tests/datasets/context.py

doruktiktiklar/sadedegel

3362c4b6bf07c34634313b9eafe52e6817efec60

[ "MIT" ]

null

tests/datasets/context.py

doruktiktiklar/sadedegel

3362c4b6bf07c34634313b9eafe52e6817efec60

[ "MIT" ]

null

import sys from pathlib import Path sys.path.insert(0, (Path(__file__) / '..' / '..').absolute()) from sadedegel.dataset import load_raw_corpus, load_sentence_corpus,load_annotated_corpus # noqa # pylint: disable=unused-import, wrong-import-position from sadedegel.dataset.extended import load_extended_metadata, load_extended_sents_corpus, load_extended_raw_corpus # noqa # pylint: disable=unused-import, wrong-import-position from sadedegel.dataset import util # noqa # pylint: disable=unused-import, wrong-import-position from sadedegel.dataset import file_paths, CorpusTypeEnum # noqa # pylint: disable=unused-import, wrong-import-position

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74b6f038aa40842d5f102393dc915957c5479f9b

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py

Python

src/nagiosql/api/tests.py

strategist922/NagiosQL-API

ebaaf99d2d1da7f04d6337ae37193cdbb2d6c2b9

[ "BSD-3-Clause" ]

null

src/nagiosql/api/tests.py

strategist922/NagiosQL-API

ebaaf99d2d1da7f04d6337ae37193cdbb2d6c2b9

[ "BSD-3-Clause" ]

null

src/nagiosql/api/tests.py

strategist922/NagiosQL-API

ebaaf99d2d1da7f04d6337ae37193cdbb2d6c2b9

[ "BSD-3-Clause" ]

1

2021-07-13T04:42:06.000Z

# Copyright 2012 NagiosQL-API authors. All rights reserved. # Use of this source code is governed by a BSD-style # license that can be found in the LICENSE file. from nagiosql.api.test_service import * from nagiosql.api.test_host import *

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5

74e08417815e4834e807ad7d225fe6cdc71bf0c9

58

py

Python

cmdparserkhv/__init__.py

khvorov45/CmdParser

5eb7a109826cf4d95f791367af44219f5ebd4ff2

[ "MIT" ]

null

cmdparserkhv/__init__.py

khvorov45/CmdParser

5eb7a109826cf4d95f791367af44219f5ebd4ff2

[ "MIT" ]

null

cmdparserkhv/__init__.py

khvorov45/CmdParser

5eb7a109826cf4d95f791367af44219f5ebd4ff2

[ "MIT" ]

null

# pylint: skip-file from .parser import CmdParser, Cmdent

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5

74fbad25ec881f43e888d45c6b1f59bc1cdb0cae

209

py

Python

nni/retiarii/__init__.py

jgard1/COS598D_Assignment3

0ac4b02c8572d3e5757b79b42a83407e55204a04

[ "MIT" ]

1

2021-03-08T19:21:00.000Z

nni/retiarii/__init__.py

jgard1/COS598D_Assignment3

0ac4b02c8572d3e5757b79b42a83407e55204a04

[ "MIT" ]

8

2021-08-31T23:35:05.000Z

2022-03-24T10:45:36.000Z

nni/retiarii/__init__.py

rushtehrani/nni

f897829772b8146e0e13ba92b6a51f8fa8227ac5

[ "MIT" ]

2

2021-03-23T17:43:00.000Z

2022-01-18T18:14:17.000Z

from .operation import Operation from .graph import * from .execution import * from .mutator import * from .serializer import basic_unit, json_dump, json_dumps, json_load, json_loads, serialize, serialize_cls

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2d152cd9a33ee73b0c31fbdedfa2cba8117ee576

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py

Python

flask_app/routes/admin.py

m01seenko/flask-boilerplate

20aebeb19782cb76f06e366d2fb2107cc1c3ac6d

[ "MIT" ]

null

flask_app/routes/admin.py

m01seenko/flask-boilerplate

20aebeb19782cb76f06e366d2fb2107cc1c3ac6d

[ "MIT" ]

null

flask_app/routes/admin.py

m01seenko/flask-boilerplate

20aebeb19782cb76f06e366d2fb2107cc1c3ac6d

[ "MIT" ]

null

import http from flask import Blueprint admin_blueprint = Blueprint("admin", __name__, url_prefix="/admin") @admin_blueprint.route("/", methods=["GET"]) @admin_blueprint.route("/index", methods=["GET"]) def index(): return "Forbidden", http.HTTPStatus.FORBIDDEN

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