xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

ee3ec35eef83893b482fd99438300cc57dac0b64

327

py

Python

decorators/decorators.py

shreshthgandhi/data_structures_py3

ecc76250a756a8f044c5d8eac7d387aeebdb0a1a

[ "MIT" ]

null

decorators/decorators.py

shreshthgandhi/data_structures_py3

ecc76250a756a8f044c5d8eac7d387aeebdb0a1a

[ "MIT" ]

null

decorators/decorators.py

shreshthgandhi/data_structures_py3

ecc76250a756a8f044c5d8eac7d387aeebdb0a1a

[ "MIT" ]

null

# Inner Functions def parent(num): def first_child(): return "First Child" def second_child(): return "Second Child" if num == 1: # Return a reference to the inner function first_child return first_child else: return second_child first = parent(1) second = parent(2)

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c9e797c404302762bfe030a6d2c4a2dfba732d76

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py

Python

hackupc/env/lib/python3.5/site-packages/belt/__init__.py

IKholopov/HackUPC2017

4da409766b54e5eb5ea4a7e4d87646f00ea4c728

[ "Apache-2.0" ]

1

2017-03-05T01:43:57.000Z

hackupc/env/lib/python3.5/site-packages/belt/__init__.py

IKholopov/HackUPC2017

4da409766b54e5eb5ea4a7e4d87646f00ea4c728

[ "Apache-2.0" ]

null

hackupc/env/lib/python3.5/site-packages/belt/__init__.py

IKholopov/HackUPC2017

4da409766b54e5eb5ea4a7e4d87646f00ea4c728

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- from django import get_version VERSION = (1, 0, 0, 'alpha', 2) __version__ = get_version(VERSION)

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py

Python

satellite/publisher/base.py

briancline/torque-satellite

41add02c7c99ed0520d33ace2287a32497fbad79

[ "MIT" ]

10

2015-07-23T22:04:50.000Z

2021-09-18T03:18:19.000Z

satellite/publisher/base.py

briancline/torque-satellite

41add02c7c99ed0520d33ace2287a32497fbad79

[ "MIT" ]

null

satellite/publisher/base.py

briancline/torque-satellite

41add02c7c99ed0520d33ace2287a32497fbad79

[ "MIT" ]

3

2015-08-12T05:16:32.000Z

2019-10-22T21:05:36.000Z

class Publisher(object): def publish(self, payload): raise NotImplemented def read(self, buffer): raise NotImplemented

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4e9158aa1341a5539d4e2a2b19590c935815f77b

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py

Python

s3imageservice/views/__init__.py

The-Politico/django-s3-image-service

da8afd36b82c031ed09d881e7b3de013061e9ccd

[ "MIT" ]

7

2018-07-23T16:35:07.000Z

2021-12-22T16:42:08.000Z

s3imageservice/views/__init__.py

The-Politico/django-s3-image-service

da8afd36b82c031ed09d881e7b3de013061e9ccd

[ "MIT" ]

13

2019-01-07T22:42:30.000Z

2022-02-27T10:53:02.000Z

s3imageservice/views/__init__.py

The-Politico/django-s3-image-service

da8afd36b82c031ed09d881e7b3de013061e9ccd

[ "MIT" ]

2

2020-07-27T02:25:59.000Z

2020-10-17T20:54:22.000Z

# flake8: noqa from .image_service import ImageService

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4e94bd79644320a348fceb9f0424a977cb4c6d47

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py

Python

pyout/tests/conftest.py

vsoch/pyout

f4247e563b89a01ee8b3e167e1e75dd01b2f2632

[ "MIT" ]

2

2020-01-29T13:42:02.000Z

2020-05-13T02:26:50.000Z

pyout/tests/conftest.py

vsoch/pyout

f4247e563b89a01ee8b3e167e1e75dd01b2f2632

[ "MIT" ]

132

2017-12-19T18:15:18.000Z

2022-02-03T20:28:19.000Z

pyout/tests/conftest.py

kyleam/pyout

9f5bbf2cab6b131365c1cc282fcae81f01f0b18f

[ "MIT" ]

3

2017-12-19T20:57:25.000Z

2020-05-12T22:56:21.000Z

import pytest pytest.register_assert_rewrite("pyout.tests.utils")

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4ed576c6bf56f05033e598b0851b705298bb13c2

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py

Python

simple_playgrounds/playgrounds/collection/test/__init__.py

Asjidkalam/simple-playgrounds

72ec42987a33175103191fa9722e0e002f889954

[ "MIT" ]

null

simple_playgrounds/playgrounds/collection/test/__init__.py

Asjidkalam/simple-playgrounds

72ec42987a33175103191fa9722e0e002f889954

[ "MIT" ]

1

2021-02-19T20:55:05.000Z

simple_playgrounds/playgrounds/collection/test/__init__.py

Asjidkalam/simple-playgrounds

72ec42987a33175103191fa9722e0e002f889954

[ "MIT" ]

1

2021-02-19T20:46:00.000Z

from .test_scene_elements import *

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14c35fd9059bedf6993aab69ab499b326ab028dc

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py

Python

agent/bot.py

latticetower/dr-derks-mutants

5c3ab86137ecb478a3013985172d160568a86b13

[ "MIT" ]

1

2021-02-02T14:19:51.000Z

agent/bot.py

latticetower/dr-derks-mutants

5c3ab86137ecb478a3013985172d160568a86b13

[ "MIT" ]

null

agent/bot.py

latticetower/dr-derks-mutants

5c3ab86137ecb478a3013985172d160568a86b13

[ "MIT" ]

1

2021-04-08T15:47:25.000Z

import numpy as np from agent.dqn_bot import DerkPlayer # change this if necessary

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14f216b35f5ff93e6112da62c8fde12148039af4

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py

Python

auth/tests/unit/auth_test.py

JensMadsen/gcloud-aio

0edf1f167a1f89470ff81a73ccf841c454e7bd0d

[ "MIT" ]

null

auth/tests/unit/auth_test.py

JensMadsen/gcloud-aio

0edf1f167a1f89470ff81a73ccf841c454e7bd0d

[ "MIT" ]

null

auth/tests/unit/auth_test.py

JensMadsen/gcloud-aio

0edf1f167a1f89470ff81a73ccf841c454e7bd0d

[ "MIT" ]

null

import gcloud.aio.auth.auth as auth # pylint: disable=unused-import def test_importable(): assert True

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14f42004f063281395aa8bd1d8811913698555a8

36

py

Python

tests/factories/__init__.py

MetaGenScope/metagenscope-server

609cd57c626c857c8efde8237a1f22f4d1e6065d

[ "MIT" ]

null

tests/factories/__init__.py

MetaGenScope/metagenscope-server

609cd57c626c857c8efde8237a1f22f4d1e6065d

[ "MIT" ]

35

2019-12-09T19:29:10.000Z

2020-02-02T19:06:53.000Z

tests/factories/__init__.py

MetaGenScope/metagenscope-server

609cd57c626c857c8efde8237a1f22f4d1e6065d

[ "MIT" ]

null

"""Factories for use in testing."""

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5

11804cd1f37401dcaae4dd3460e83233d58149c0

51

py

Python

storecompressfiles/__init__.py

raman77768/storecompressfiles

98b2fa45b05c714bc74b3876b7ca226b664cb2a7

[ "MIT" ]

null

storecompressfiles/__init__.py

raman77768/storecompressfiles

98b2fa45b05c714bc74b3876b7ca226b664cb2a7

[ "MIT" ]

null

storecompressfiles/__init__.py

raman77768/storecompressfiles

98b2fa45b05c714bc74b3876b7ca226b664cb2a7

[ "MIT" ]

null

from storecompressfiles.class1 import encode,decode

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5

11aa989741dc1259f922836d0b3fb1400de8794a

222

py

Python

robotframework-ls/src/robotframework_debug_adapter/global_vars.py

GLMeece/robotframework-lsp

dc9c807c4a192d252df1d05a1c5d16f8c1f24086

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

null

robotframework-ls/src/robotframework_debug_adapter/global_vars.py

GLMeece/robotframework-lsp

dc9c807c4a192d252df1d05a1c5d16f8c1f24086

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

null

robotframework-ls/src/robotframework_debug_adapter/global_vars.py

GLMeece/robotframework-lsp

dc9c807c4a192d252df1d05a1c5d16f8c1f24086

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

null

_robot_target_comm = None def set_global_robot_target_comm(robot_target_comm): global _robot_target_comm _robot_target_comm = robot_target_comm def get_global_robot_target_comm(): return _robot_target_comm

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5

11bad291f77b7d0e1cf59ebbf9465e2402dd0553

178

py

Python

dataxmissionprotocol/ports/queue/__init__.py

RobinBobin/data-transmission-protocol

b53f2157437eb59d53270b3acab3a325f7dfad28

[ "MIT" ]

null

dataxmissionprotocol/ports/queue/__init__.py

RobinBobin/data-transmission-protocol

b53f2157437eb59d53270b3acab3a325f7dfad28

[ "MIT" ]

null

dataxmissionprotocol/ports/queue/__init__.py

RobinBobin/data-transmission-protocol

b53f2157437eb59d53270b3acab3a325f7dfad28

[ "MIT" ]

null

from .connectionestablished import ConnectionEstablished from .connectionlost import ConnectionLost from .datareceived import DataReceived from .processerror import ProcessError

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5

f502dddba7691b1cfe893374a63990b121c49b3f

562

py

Python

test.py

kylelrichards11/DSPipeline

94fc7a8438748c6390a3dfc1fac231225595cc4f

[ "MIT" ]

null

test.py

kylelrichards11/DSPipeline

94fc7a8438748c6390a3dfc1fac231225595cc4f

[ "MIT" ]

null

test.py

kylelrichards11/DSPipeline

94fc7a8438748c6390a3dfc1fac231225595cc4f

[ "MIT" ]

null

################################################################################################ # TESTING ################################################################################################ # External Imports import unittest # Internal Imports from tests.data_augmentation_tests import * from tests.data_manager_tests import * from tests.data_transformation_tests import * from tests.ds_pipeline_tests import * from tests.feature_selection_tests import * from tests.outlier_detection_tests import * if __name__ == "__main__": unittest.main()

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true

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5

ee9baa0db67a3437c4af95acc0482332b70a222a

62

py

Python

malaya_speech/train/model/speechsplitformer/__init__.py

ishine/malaya-speech

fd34afc7107af1656dff4b3201fa51dda54fde18

[ "MIT" ]

111

2020-08-31T04:58:54.000Z

2022-03-29T15:44:18.000Z

malaya_speech/train/model/speechsplitformer/__init__.py

ishine/malaya-speech

fd34afc7107af1656dff4b3201fa51dda54fde18

[ "MIT" ]

14

2020-12-16T07:27:22.000Z

2022-03-15T17:39:01.000Z

malaya_speech/train/model/speechsplitformer/__init__.py

ishine/malaya-speech

fd34afc7107af1656dff4b3201fa51dda54fde18

[ "MIT" ]

29

2021-02-09T08:57:15.000Z

2022-03-12T14:09:19.000Z

from .model import Model, Model_F0 # from . import inference

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eeb9a99700caba0909497e2fe085176a414d0982

620

py

Python

src/main/python/cafebabepy/wsgi/__init__.py

cafebabepy/cafebabepy-wsgi

606cd2eff89900d7ead56577ba3685571d482343

[ "BSD-3-Clause" ]

null

src/main/python/cafebabepy/wsgi/__init__.py

cafebabepy/cafebabepy-wsgi

606cd2eff89900d7ead56577ba3685571d482343

[ "BSD-3-Clause" ]

null

src/main/python/cafebabepy/wsgi/__init__.py

cafebabepy/cafebabepy-wsgi

606cd2eff89900d7ead56577ba3685571d482343

[ "BSD-3-Clause" ]

null

class Server: def __init__(self): self._status = None self._response_headers = [] def start_response(self, status, response_headers, exc_info=None): self._status = status; self._response_headers = response_headers @property def status(self): return self._status @status.setter def status(self, status): self.status = self._status @property def response_headers(self): return self._response_headers @response_headers.setter def response_headers(self, response_headers): self._response_headers = response_headers

24.8

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eef2a3769f6d2eb04c1fcd17f53c28c1a2489c51

497

py

Python

prescient/plugins/__init__.py

iSoron/Prescient

a3c1d7c5840893ff43dca48c40dc90f083292d26

[ "BSD-3-Clause" ]

1

2021-10-14T20:39:50.000Z

prescient/plugins/__init__.py

iSoron/Prescient

a3c1d7c5840893ff43dca48c40dc90f083292d26

[ "BSD-3-Clause" ]

null

prescient/plugins/__init__.py

iSoron/Prescient

a3c1d7c5840893ff43dca48c40dc90f083292d26

[ "BSD-3-Clause" ]

null

from __future__ import annotations from typing import TYPE_CHECKING if TYPE_CHECKING: from .internal import PluginCallbackManager def get_active_plugin_manager() -> PluginCallbackManager: ''' Get the active plugin manager, creating one if necessary ''' from . import internal if internal.active_plugin_manager is None: internal.active_plugin_manager = internal.PluginCallbackManager() return internal.active_plugin_manager from .plugin_registration import *

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013a9615d4588f3127b452c97ede42c8a0196a46

140

py

Python

nrp_experiment/blackboard_create_dataset/all_neurons_monitor.py

imbyjuli/blackboard-tensorflow-nrp

93fb4b5ba18e5e3c55526670160ee3ec21626e43

[ "Apache-2.0" ]

null

nrp_experiment/blackboard_create_dataset/all_neurons_monitor.py

imbyjuli/blackboard-tensorflow-nrp

93fb4b5ba18e5e3c55526670160ee3ec21626e43

[ "Apache-2.0" ]

null

nrp_experiment/blackboard_create_dataset/all_neurons_monitor.py

imbyjuli/blackboard-tensorflow-nrp

93fb4b5ba18e5e3c55526670160ee3ec21626e43

[ "Apache-2.0" ]

null

# Imported Python Transfer Function @nrp.NeuronMonitor(nrp.brain.record, nrp.spike_recorder) def all_neurons_monitor(t): return True ##

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014dca31971055c7072bd9fd3f1257bce909cbce

502

py

Python

venv/Lib/site-packages/tensorflow/_api/v2/profiler/experimental/__init__.py

rexliu3/StockTradingBotCloud

46b732b9c05f73bc0e856a3c4a16854b6d12e18e

[ "MIT" ]

null

venv/Lib/site-packages/tensorflow/_api/v2/profiler/experimental/__init__.py

rexliu3/StockTradingBotCloud

46b732b9c05f73bc0e856a3c4a16854b6d12e18e

[ "MIT" ]

null

venv/Lib/site-packages/tensorflow/_api/v2/profiler/experimental/__init__.py

rexliu3/StockTradingBotCloud

46b732b9c05f73bc0e856a3c4a16854b6d12e18e

[ "MIT" ]

1

2020-06-28T11:47:47.000Z

# This file is MACHINE GENERATED! Do not edit. # Generated by: tensorflow/python/tools/api/generator/create_python_api.py script. """Public API for tf.profiler.experimental namespace. """ from __future__ import print_function as _print_function import sys as _sys from . import client from . import server from tensorflow.python.profiler.profiler_v2 import Profile from tensorflow.python.profiler.profiler_v2 import start from tensorflow.python.profiler.profiler_v2 import stop del _print_function

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0166b02fbb603487d18aa4d6ae2a3379caa92ac4

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py

Python

driver/drivers/__init__.py

MITIBMxGraph/SALIENT_artifact

d89c185b2dd4f5389086b434d36c42aab096560e

[ "Apache-2.0" ]

6

2022-02-15T16:27:43.000Z

2022-03-31T18:51:22.000Z

driver/drivers/__init__.py

MITIBMxGraph/SALIENT_artifact

d89c185b2dd4f5389086b434d36c42aab096560e

[ "Apache-2.0" ]

null

driver/drivers/__init__.py

MITIBMxGraph/SALIENT_artifact

d89c185b2dd4f5389086b434d36c42aab096560e

[ "Apache-2.0" ]

null

from .base import BaseDriver from .ddp import DDPDriver from .singleproc import SingleProcDriver

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1

0

1

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5

0168fc744a8e703ecafe4f3d477219e4a7217728

35

py

Python

props/proposition_structure/__init__.py

DeltaF1/props

25ddd9cf7c583c545217f190acbf8309d1ecdb2a

[ "MIT" ]

null

props/proposition_structure/__init__.py

DeltaF1/props

25ddd9cf7c583c545217f190acbf8309d1ecdb2a

[ "MIT" ]

null

props/proposition_structure/__init__.py

DeltaF1/props

25ddd9cf7c583c545217f190acbf8309d1ecdb2a

[ "MIT" ]

null

from . import proposition_structure

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null

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1

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5

0187b90681cf5a5a40d77e952950a7aceb324034

119

py

Python

Python/8 kyu/5 Without Numbers!!/solution.py

Hsins/CodeWars

7e7b912fdd0647c0af381d8b566408e383ea5df8

[ "MIT" ]

1

2020-01-09T21:47:56.000Z

Python/8 kyu/5 Without Numbers!!/solution.py

Hsins/CodeWars

7e7b912fdd0647c0af381d8b566408e383ea5df8

[ "MIT" ]

1

2020-01-20T12:39:03.000Z

Python/8 kyu/5 Without Numbers!!/solution.py

Hsins/CodeWars

7e7b912fdd0647c0af381d8b566408e383ea5df8

[ "MIT" ]

null

# [8 kyu] 5 Without Numbers!! # # Author: Hsins # Date: 2019/11/28 def unusual_five(): return len(" ")

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6d6c7add60f44cb0c0cc466351c7f4a89445b661

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py

Python

api/tacticalrmm/agents/permissions.py

rfost52/tacticalrmm

44dd59fa3f530e7cf6730ef44606fa869c8cd222

[ "MIT" ]

903

2019-10-22T22:56:42.000Z

2022-03-18T14:15:54.000Z

api/tacticalrmm/agents/permissions.py

rfost52/tacticalrmm

44dd59fa3f530e7cf6730ef44606fa869c8cd222

[ "MIT" ]

720

2019-12-07T08:11:26.000Z

2022-03-17T21:47:04.000Z

api/tacticalrmm/agents/permissions.py

rfost52/tacticalrmm

44dd59fa3f530e7cf6730ef44606fa869c8cd222

[ "MIT" ]

231

2020-02-11T14:14:21.000Z

2022-03-16T21:23:10.000Z

from rest_framework import permissions from tacticalrmm.permissions import _has_perm class MeshPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_use_mesh") class UninstallPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_uninstall_agents") class UpdateAgentPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_update_agents") class EditAgentPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_edit_agent") class ManageProcPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_manage_procs") class EvtLogPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_view_eventlogs") class SendCMDPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_send_cmd") class RebootAgentPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_reboot_agents") class InstallAgentPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_install_agents") class RunScriptPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_run_scripts") class ManageNotesPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_manage_notes") class RunBulkPerms(permissions.BasePermission): def has_permission(self, r, view): return _has_perm(r, "can_run_bulk")

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null

0

1

0

1

0

5

6d97b5cbc2329b0fb1d92325528e425adb1390f1

103

py

Python

src/sirt6/exceptions.py

rshtirmer/sirt6-src

0c4279571d4fbb73a0ecb56409df8fe3d652eee0

[ "MIT" ]

null

src/sirt6/exceptions.py

rshtirmer/sirt6-src

0c4279571d4fbb73a0ecb56409df8fe3d652eee0

[ "MIT" ]

null

src/sirt6/exceptions.py

rshtirmer/sirt6-src

0c4279571d4fbb73a0ecb56409df8fe3d652eee0

[ "MIT" ]

1

2020-07-15T04:44:15.000Z

class Sirt6BaseException(Exception): pass class InvalidLayoutError(Sirt6BaseException): pass

14.714286

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0.786408

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0.022989

0.15534

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0.5

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1

null

0

1

0

null

0

1

0

5

6dd177944e4c2854e5bfce0fb5b51c8fb79480f7

76

py

Python

SlackBotProject/SlackBotApp/services/index.py

CKVB/Slack-Bot

1f59736b726fa792d76e19b2846b63d52582b3b8

[ "MIT" ]

null

SlackBotProject/SlackBotApp/services/index.py

CKVB/Slack-Bot

1f59736b726fa792d76e19b2846b63d52582b3b8

[ "MIT" ]

null

SlackBotProject/SlackBotApp/services/index.py

CKVB/Slack-Bot

1f59736b726fa792d76e19b2846b63d52582b3b8

[ "MIT" ]

null

def index(): return { "message": "healthy & running" }, 200

15.2

38

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76

5.428571

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0.06

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76

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39

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null

0

1

0

null

0

1

0

1

0

5

096bb842e6406a85816c87582fd0328e6172c87d

87

py

Python

bearicade_ansible/roles/bear/add_user/files/totp_generate.py

alexantoniades/bearicade

34c4d9c1817dfba753f148451a3ccd9ef45b2e39

[ "MIT" ]

4

2020-03-08T12:14:43.000Z

2021-07-31T09:56:47.000Z

bearicade_ansible/roles/bear/add_user/files/totp_generate.py

alexantoniades/bearicade

34c4d9c1817dfba753f148451a3ccd9ef45b2e39

[ "MIT" ]

2

2020-03-07T15:56:05.000Z

2020-03-14T14:08:08.000Z

bearicade_ansible/roles/bear/add_user/files/totp_generate.py

alexantoniades/bearicade

34c4d9c1817dfba753f148451a3ccd9ef45b2e39

[ "MIT" ]

1

2021-12-22T13:30:17.000Z

#!/usr/bin/env python import sys import pyotp sys.stdout.write(pyotp.random_base32(32))

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null

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0

1

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1

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5

09b8c69ae286cd19de5d6ac64af3fd0c344fbfe2

3,250

py

Python

api/ops/tests/test_anomalyDetection.py

LeiSoft/CueObserve

cc5254df7d0cb817a8b3ec427f5cb54a1d420f7e

[ "Apache-2.0" ]

149

2021-07-16T13:37:30.000Z

2022-03-21T10:13:15.000Z

api/ops/tests/test_anomalyDetection.py

LeiSoft/CueObserve

cc5254df7d0cb817a8b3ec427f5cb54a1d420f7e

[ "Apache-2.0" ]

61

2021-07-15T06:39:05.000Z

2021-12-27T06:58:10.000Z

api/ops/tests/test_anomalyDetection.py

LeiSoft/CueObserve

cc5254df7d0cb817a8b3ec427f5cb54a1d420f7e

[ "Apache-2.0" ]

22

2021-07-19T07:20:49.000Z

2022-03-21T10:13:16.000Z

import pytest from unittest import mock from ops.tasks.detection.core.anomalyDetection import anomalyService from anomaly.models import Anomaly from pandas import Timestamp from mixer.backend.django import mixer import pandas as pd @pytest.mark.django_db(transaction=True) def test_createAnomalyService(client, mocker): fakedata = [{'ds': Timestamp('2021-06-01 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-02 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-03 00:00:00+0000', tz='UTC'), 'y': 0.0}, {'ds': Timestamp('2021-06-04 00:00:00+0000', tz='UTC'), 'y': 0.0}, {'ds': Timestamp('2021-06-05 00:00:00+0000', tz='UTC'), 'y': 4.0}, {'ds': Timestamp('2021-06-06 00:00:00+0000', tz='UTC'), 'y': 0.0}, {'ds': Timestamp('2021-06-07 00:00:00+0000', tz='UTC'), 'y': 4.0}, {'ds': Timestamp('2021-06-08 00:00:00+0000', tz='UTC'), 'y': 0.0}, {'ds': Timestamp('2021-06-09 00:00:00+0000', tz='UTC'), 'y': 2.0}, {'ds': Timestamp('2021-06-10 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-11 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-12 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-13 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-14 00:00:00+0000', tz='UTC'), 'y': 2.0}, {'ds': Timestamp('2021-06-15 00:00:00+0000', tz='UTC'), 'y': 0.0}, {'ds': Timestamp('2021-06-16 00:00:00+0000', tz='UTC'), 'y': 2.0}, {'ds': Timestamp('2021-06-17 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-18 00:00:00+0000', tz='UTC'), 'y': 2.0}, {'ds': Timestamp('2021-06-19 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-20 00:00:00+0000', tz='UTC'), 'y': 2.0}, {'ds': Timestamp('2021-06-21 00:00:00+0000', tz='UTC'), 'y': 4.0}, {'ds': Timestamp('2021-06-22 00:00:00+0000', tz='UTC'), 'y': 3.0}, {'ds': Timestamp('2021-06-23 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-24 00:00:00+0000', tz='UTC'), 'y': 0.0}, {'ds': Timestamp('2021-06-25 00:00:00+0000', tz='UTC'), 'y': 3.0}, {'ds': Timestamp('2021-06-26 00:00:00+0000', tz='UTC'), 'y': 3.0}, {'ds': Timestamp('2021-06-27 00:00:00+0000', tz='UTC'), 'y': 1.0}, {'ds': Timestamp('2021-06-28 00:00:00+0000', tz='UTC'), 'y': 0.0}, {'ds': Timestamp('2021-06-29 00:00:00+0000', tz='UTC'), 'y': 0.0}, {'ds': Timestamp('2021-06-30 00:00:00+0000', tz='UTC'), 'y': 0.0}] dts = mixer.blend("anomaly.Dataset", granularity="day") anomDef = mixer.blend("anomaly.AnomalyDefinition", dataset=dts, periodicTask=None) dimValObj = { "dimVal": "xkcd", "anomalyId": 1, "contriPercent": 12 } anomalyDefProps = { "granularity": "day", "highOrLow": "" } result = anomalyService(dimValObj, fakedata, anomalyDefProps, "Prophet", {}) assert result["success"] assert not result["published"]

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null

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5

09cb6494ebcb8ed36c71d1375aed115161b66bfc

66

py

Python

graphgallery/nn/models/semisupervised/__init__.py

Sharpiless/GraphGallery

5e8895cc2ca2fc06a31bfc58bc3b7a52e1ceddd0

[ "MIT" ]

1

2020-11-22T10:14:58.000Z

graphgallery/nn/models/semisupervised/__init__.py

mengliu1998/GraphGallery

025ac09e883f3e1e1b02000e086830c935884a6e

[ "MIT" ]

null

graphgallery/nn/models/semisupervised/__init__.py

mengliu1998/GraphGallery

025ac09e883f3e1e1b02000e086830c935884a6e

[ "MIT" ]

1

2020-11-22T10:14:59.000Z

from graphgallery.nn.models.semisupervised.experimental import *

22

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66

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0.918033

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null

0

1

0

1

0

1

0

5

09e71397bb24d57fb0ecf96573abf08b3f7f6fd5

48

py

Python

mazeGenerator/__init__.py

Charl86/Maze-Generator

9f8ea0d7d0dd6aad2b7a048959267b473a75fbb6

[ "MIT" ]

null

mazeGenerator/__init__.py

Charl86/Maze-Generator

9f8ea0d7d0dd6aad2b7a048959267b473a75fbb6

[ "MIT" ]

null

mazeGenerator/__init__.py

Charl86/Maze-Generator

9f8ea0d7d0dd6aad2b7a048959267b473a75fbb6

[ "MIT" ]

null

from mazeGenerator.app import App app = App()

9.6

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5

61d4807c88ce0829d1d75975281c57750ebd9795

1,487

py

Python

CTFShow/easyrsa5.py

Don2025/CTFwriteUp

41e0a5bf87a1a02dd1548e621853c145ff64cedb

[ "MIT" ]

2

2022-03-20T02:27:59.000Z

2022-03-20T02:28:02.000Z

CTFShow/easyrsa5.py

Don2025/CTFwriteUp

41e0a5bf87a1a02dd1548e621853c145ff64cedb

[ "MIT" ]

null

CTFShow/easyrsa5.py

Don2025/CTFwriteUp

41e0a5bf87a1a02dd1548e621853c145ff64cedb

[ "MIT" ]

null

from gmpy2 import * import binascii e = mpz(284100478693161642327695712452505468891794410301906465434604643365855064101922252698327584524956955373553355814138784402605517536436009073372339264422522610010012877243630454889127160056358637599704871937659443985644871453345576728414422489075791739731547285138648307770775155312545928721094602949588237119345) n = mpz(468459887279781789188886188573017406548524570309663876064881031936564733341508945283407498306248145591559137207097347130203582813352382018491852922849186827279111555223982032271701972642438224730082216672110316142528108239708171781850491578433309964093293907697072741538649347894863899103340030347858867705231) c = mpz(350429162418561525458539070186062788413426454598897326594935655762503536409897624028778814302849485850451243934994919418665502401195173255808119461832488053305530748068788500746791135053620550583421369214031040191188956888321397450005528879987036183922578645840167009612661903399312419253694928377398939392827) p = mpz(18489327396055733397216193236128138397765028288613793035021305599301380136673327250408422592244732819005905679957567952974717041052102175277835219391448987) q = mpz(25336772790324258952117622504537139442881120269760383961991795601846585772802865528712760553670210656524156997774484665833049279421936394718949688217533213) phi_n = (p-1)*(q-1) d = invert(e, phi_n) m = powmod(c, d, n) # m = c^d%n flag = binascii.unhexlify(hex(m)[2:]).decode('utf-8') print(flag) # flag{very_biiiiig_e}

114.384615

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5

61d73625cefcaf30bc83add9d195fd8d719fa0c1

198

py

Python

Recycled/Interface/Configurable.py

lifg2000/StockAnalysisSystem

b0bef50f5c1a9565e1a1f953fedbe7821601147c

[ "Apache-2.0" ]

138

2018-01-03T03:32:49.000Z

2022-03-12T02:57:46.000Z

Recycled/Interface/Configurable.py

lifg2000/StockAnalysisSystem

b0bef50f5c1a9565e1a1f953fedbe7821601147c

[ "Apache-2.0" ]

9

2018-01-01T03:16:24.000Z

2021-05-27T09:57:24.000Z

Recycled/Interface/Configurable.py

lifg2000/StockAnalysisSystem

b0bef50f5c1a9565e1a1f953fedbe7821601147c

[ "Apache-2.0" ]

50

2019-08-05T01:02:30.000Z

2022-03-07T00:52:14.000Z

class Configurable: def __init__(self): pass def function_support(self, function: str) -> bool: pass def parameter_template(self, function: str) -> dict: pass

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null

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1

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1

0

5

61f7d206629004912c10e8b66b954629f066d1b7

160

py

Python

python/cuxfilter/sampledata/__init__.py

rnyak/cuxfilter

626e45af3b8a0f2e37bc5cdbe6d2da618141f995

[ "Apache-2.0" ]

201

2018-12-21T18:32:40.000Z

2022-03-22T11:50:29.000Z

python/cuxfilter/sampledata/__init__.py

rnyak/cuxfilter

626e45af3b8a0f2e37bc5cdbe6d2da618141f995

[ "Apache-2.0" ]

258

2018-12-27T07:37:50.000Z

2022-03-31T20:01:32.000Z

python/cuxfilter/sampledata/__init__.py

rnyak/cuxfilter

626e45af3b8a0f2e37bc5cdbe6d2da618141f995

[ "Apache-2.0" ]

51

2019-01-10T19:03:09.000Z

2022-03-08T01:37:11.000Z

from .random_signals import df as signals_data from .unemployment_data_from_bokeh import df as unemployment_data from .download_datasets import datasets_check

32

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py

Python

sedfitter/sed/tests/test_cube.py

KainRasleafar/sedfitter

4f0e9e46f7903a853166835bb74857cc15eef219

[ "BSD-2-Clause" ]

15

2015-07-04T02:00:30.000Z

2021-05-13T09:03:10.000Z

sedfitter/sed/tests/test_cube.py

KainRasleafar/sedfitter

4f0e9e46f7903a853166835bb74857cc15eef219

[ "BSD-2-Clause" ]

45

2015-04-27T20:19:22.000Z

2022-01-28T06:24:31.000Z

sedfitter/sed/tests/test_cube.py

KainRasleafar/sedfitter

4f0e9e46f7903a853166835bb74857cc15eef219

[ "BSD-2-Clause" ]

19

2015-04-21T15:32:04.000Z

2022-03-02T21:53:46.000Z

import numpy as np from astropy import units as u from ..cube import SEDCube def test_roundrip(tmpdir): n_models = 30 n_ap = 3 n_wav = 10 s = SEDCube() s.names = ['name_{0:02d}'.format(i) for i in range(n_models)] s.apertures = np.linspace(10, 100, n_ap) * u.au s.wav = np.linspace(0.01, 5000, n_wav)[::-1] * u.micron s.distance = 1. * u.kpc s.val = np.random.random((n_models, n_ap, n_wav)) * u.mJy s.unc = np.random.random((n_models, n_ap, n_wav)) * u.mJy temp_file = tmpdir.join('test_roundtrip_sedcube').strpath s.write(temp_file) s2 = SEDCube.read(temp_file) assert s == s2 def test_roundrip_missing_optional(tmpdir): n_models = 30 n_wav = 10 s = SEDCube() s.names = ['name_{0:02d}'.format(i) for i in range(n_models)] s.wav = np.linspace(0.01, 5000, n_wav)[::-1] * u.micron s.distance = 1. * u.kpc s.val = np.random.random((n_models, 1, n_wav)) * u.mJy temp_file = tmpdir.join('test_roundtrip_sedcube').strpath s.write(temp_file) s2 = SEDCube.read(temp_file) assert s == s2

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Python

code/abc045_a_04.py

KoyanagiHitoshi/AtCoder

731892543769b5df15254e1f32b756190378d292

[ "MIT" ]

3

2019-08-16T16:55:48.000Z

2021-04-11T10:21:40.000Z

code/abc045_a_04.py

KoyanagiHitoshi/AtCoder

731892543769b5df15254e1f32b756190378d292

[ "MIT" ]

null

code/abc045_a_04.py

KoyanagiHitoshi/AtCoder

731892543769b5df15254e1f32b756190378d292

[ "MIT" ]

null

a,b,h=[int(input()) for i in range(3)] print((a+b)*h//2)

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5

3a1bafc4a3cc9e583674c56bf5eae2144ef257d1

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py

Python

pyml/get_theta.py

gitter-badger/PyML

4554a6944767f3c5576dc07d320ab6726b115f2d

[ "MIT" ]

null

pyml/get_theta.py

gitter-badger/PyML

4554a6944767f3c5576dc07d320ab6726b115f2d

[ "MIT" ]

null

pyml/get_theta.py

gitter-badger/PyML

4554a6944767f3c5576dc07d320ab6726b115f2d

[ "MIT" ]

null

import numpy as np def get_theta(x, y): theta = ((x.T * x).I) * x.T * y; return theta

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160

py

Python

src/envs/__init__.py

napnel/UoA-thesis-s1260099

dce954b8795c24dc8fbbacb8b7ebdfe101fc01c6

[ "Apache-2.0" ]

null

src/envs/__init__.py

napnel/UoA-thesis-s1260099

dce954b8795c24dc8fbbacb8b7ebdfe101fc01c6

[ "Apache-2.0" ]

null

src/envs/__init__.py

napnel/UoA-thesis-s1260099

dce954b8795c24dc8fbbacb8b7ebdfe101fc01c6

[ "Apache-2.0" ]

null

from ray.tune.registry import register_env from src.envs.environment import TradingEnv register_env("TradingEnv", lambda env_config: TradingEnv(**env_config))

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3a2bda56481bd53f969c094c49a4d5d9c6d004d5

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py

Python

chroma_core/migrations/0030_purge_state.py

intel-hpdd/-intel-manager-for-lustre

f8a6f61205b42cc62f4bbcb8d81214ad4f215cd6

[ "MIT" ]

52

2018-09-13T03:26:23.000Z

2022-03-25T16:51:37.000Z

chroma_core/migrations/0030_purge_state.py

intel-hpdd/-intel-manager-for-lustre

f8a6f61205b42cc62f4bbcb8d81214ad4f215cd6

[ "MIT" ]

1,264

2018-06-15T19:50:57.000Z

2022-03-28T08:19:04.000Z

chroma_core/migrations/0030_purge_state.py

whamcloud/intel-manager-for-lustre

f8a6f61205b42cc62f4bbcb8d81214ad4f215cd6

[ "MIT" ]

27

2018-06-18T08:51:59.000Z

2022-03-16T15:35:34.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.11.23 on 2020-11-16 21:25 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ("chroma_core", "0029_remove_managedtarget_fields"), ] operations = [ migrations.RemoveField( model_name="configuretargetjob", name="job_ptr", ), migrations.RemoveField( model_name="configuretargetjob", name="target", ), migrations.RemoveField( model_name="failbacktargetjob", name="job_ptr", ), migrations.RemoveField( model_name="failbacktargetjob", name="target", ), migrations.RemoveField( model_name="formattargetjob", name="job_ptr", ), migrations.RemoveField( model_name="formattargetjob", name="target", ), migrations.RemoveField( model_name="registertargetjob", name="job_ptr", ), migrations.RemoveField( model_name="registertargetjob", name="target", ), migrations.RemoveField( model_name="removeconfiguredtargetjob", name="job_ptr", ), migrations.RemoveField( model_name="removeconfiguredtargetjob", name="target", ), migrations.RemoveField( model_name="removetargetjob", name="job_ptr", ), migrations.RemoveField( model_name="removetargetjob", name="target", ), migrations.RemoveField( model_name="removefilesystemjob", name="filesystem", ), migrations.RemoveField( model_name="removefilesystemjob", name="job_ptr", ), migrations.RemoveField( model_name="updatenidsjob", name="job_ptr", ), migrations.RemoveField( model_name="updatedevicesjob", name="job_ptr", ), migrations.DeleteModel( name="TargetFailoverAlert", ), migrations.DeleteModel( name="ConfigureTargetJob", ), migrations.DeleteModel( name="FailbackTargetJob", ), migrations.DeleteModel( name="FormatTargetJob", ), migrations.DeleteModel( name="RegisterTargetJob", ), migrations.DeleteModel( name="RemoveConfiguredTargetJob", ), migrations.DeleteModel( name="RemoveTargetJob", ), migrations.DeleteModel( name="RemoveFilesystemJob", ), migrations.DeleteModel( name="UpdateNidsJob", ), migrations.DeleteModel( name="UpdateDevicesJob", ), ]

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28ff53fdb066eeb5cdf296b57fa544f75fe5d914

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py

Python

src/callable_journal/__init__.py

nathan5280/callable-journal

d815f2e029b3af53f9631b6a7672c0faec16be0e

[ "MIT" ]

1

2020-10-21T20:56:35.000Z

src/callable_journal/__init__.py

nathan5280/callable-journal

d815f2e029b3af53f9631b6a7672c0faec16be0e

[ "MIT" ]

null

src/callable_journal/__init__.py

nathan5280/callable-journal

d815f2e029b3af53f9631b6a7672c0faec16be0e

[ "MIT" ]

null

from .journal import journal, journal_init from .param_arg_mapper import COPY_ALL_ARGS, DROP_RESULT

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py

Python

docs/bayes_window_book/_build/jupyter_execute/neurons_example/monster.py

mmyros/bayes_window_examples

b19efd85abe76395a155f5452d291f2550ace343

[ "MIT" ]

null

docs/bayes_window_book/_build/jupyter_execute/neurons_example/monster.py

mmyros/bayes_window_examples

b19efd85abe76395a155f5452d291f2550ace343

[ "MIT" ]

null

docs/bayes_window_book/_build/jupyter_execute/neurons_example/monster.py

mmyros/bayes_window_examples

b19efd85abe76395a155f5452d291f2550ace343

[ "MIT" ]

null

#!/usr/bin/env python # coding: utf-8 # # Neurons example, pt. 2: large datasets # In[1]: import numpyro from bayes_window import models, fake_spikes_explore, BayesWindow, BayesConditions, BayesRegression from bayes_window.generative_models import generate_fake_spikes import numpy as np from importlib import reload import altair as alt alt.data_transformers.disable_max_rows() try: alt.renderers.enable('altair_saver', fmts=['png']) except Exception: pass # In[2]: df, df_monster, index_cols, firing_rates = generate_fake_spikes(n_trials=20, n_neurons=6, n_mice=3, dur=5, mouse_response_slope=40, overall_stim_response_strength=5) # ## Step by step # ### 1. Firing rate # In[ ]: bw1 = BayesConditions(df=df_monster, y='isi',treatment='stim', condition=['neuron_x_mouse','i_trial'], group='mouse') bw1.fit(dist_y='gamma'); # bw.plot_model_quality() # ### 2. Regression # In[ ]: bw2 = BayesRegression(df=bw1.posterior['mu_per_condition'], y='center interval', treatment='stim', condition=['neuron_x_mouse'], group='mouse') bw2.fit(model=models.model_hierarchical, do_make_change='subtract', dist_y='student', robust_slopes=False, add_group_intercept=False, add_group_slope=False, fold_change_index_cols=('stim', 'mouse', 'neuron_x_mouse')) bw2.plot_model_quality() # In[ ]: bw2.chart # ## Each neuron separately via SVI # ### 1. Firing rate # In[ ]: from tqdm import tqdm gb='neuron_x_mouse' step1_res=[] for i, df_m_n in tqdm(df_monster.groupby(gb)): bw1 = BayesConditions(df_m_n, y='isi',treatment='stim', condition=['i_trial'], group='mouse' ).fit(dist_y='gamma', # fit_fn=fitting.fit_svi ) posterior=bw1.posterior['mu_per_condition'].copy() posterior[gb] = i step1_res.append(posterior) # ### 2. Regression # TODO add sigma to step 2 inputs # # In[ ]: import pandas as pd bw2 = BayesRegression(pd.concat(step1_res), y='center interval', treatment='stim', condition=['neuron_x_mouse'], group='mouse', detail='i_trial') bw2.fit(model=models.model_hierarchical, do_make_change='subtract', dist_y='student', robust_slopes=False, add_group_intercept=False, add_group_slope=False) bw2.chart # ## NUTS 1-step GLM # In[ ]: # Gamma GLM bw = BayesRegression(df_monster, y='isi', treatment='stim', condition=['neuron', 'mouse'], group='mouse') bw.fit(model=models.model_hierarchical, progress_bar=True, do_make_change='subtract', dist_y='gamma', robust_slopes=False, add_group_intercept=False, add_group_slope=False, fold_change_index_cols=('stim', 'mouse', 'neuron','neuron_x_mouse')) bw.plot_model_quality() # In[ ]: import altair as alt alt.data_transformers.disable_max_rows() bw.plot(x='neuron', color='mouse', independent_axes=True, finalize=True) bw.facet(column='mouse',width=200,height=200).display() # ## NUTS student # In[ ]: bw = BayesRegression(df=df_monster, y='isi', treatment='stim', condition=['neuron', 'mouse'], group='mouse') bw.fit(model=models.model_hierarchical, progress_bar=True, do_make_change='subtract', dist_y='student', robust_slopes=False, add_group_intercept=False, add_group_slope=False, fold_change_index_cols=('stim', 'mouse', 'neuron','neuron_x_mouse')) bw.plot_model_quality() # In[ ]: bw.plot(x='neuron', color='mouse', independent_axes=True, finalize=True) bw.facet(column='mouse',width=200,height=200).display() # In[ ]: bw = BayesRegression(df_monster, y='isi', treatment='stim', condition='neuron_x_mouse', group='mouse') bw.fit(model=models.model_hierarchical, do_make_change='subtract', progress_bar=True, dist_y='student', use_gpu=True, num_chains=1, num_warmup=500, add_group_slope=True, add_group_intercept=False, fold_change_index_cols=('stim', 'mouse', 'neuron','neuron_x_mouse')) bw.plot(x='neuron', color='mouse', independent_axes=True, finalize=True) bw.facet(column='mouse',width=200,height=200).display() #bw.explore_models(use_gpu=True) # ## NUTS Lognormal # In[ ]: bw = BayesRegression(df=df_monster, y='isi', treatment='stim', condition=['neuron', 'mouse'], group='mouse') bw.fit(model=models.model_hierarchical, do_make_change='subtract', progress_bar=True, use_gpu=True, num_chains=1, n_draws=1500, num_warmup=1500, dist_y='lognormal', add_group_slope=True, add_group_intercept=True, fold_change_index_cols=('stim', 'mouse', 'neuron')) bw.plot(x='neuron', color='mouse', independent_axes=True, finalize=True) bw.facet(column='mouse',width=200,height=200).display() # In[ ]: bw.explore_models(add_group_slope=True) # ## BarkerMH # In[ ]: get_ipython().run_cell_magic('time', '', "from bayes_window import fitting\n\nfrom importlib import reload\nreload(fitting)\n\nbw = BayesRegression(df=df_monster, y='isi', treatment='stim', condition=['neuron', 'mouse'], group='mouse')\nbw.fit(model=models.model_hierarchical, do_make_change='subtract',\n sampler=numpyro.infer.BarkerMH,\n# progress_bar=True,\n use_gpu=False, num_chains=1, n_draws=5000, num_warmup=3000,\n dist_y='student',\n add_group_slope=True, add_group_intercept=True,\n fold_change_index_cols=('stim', 'mouse', 'neuron'),\n fit_method=fitting.fit_numpyro,\n )\n\nbw.plot(x='neuron', color='mouse', independent_axes=True, finalize=True)\n\n\nbw.facet(column='mouse',width=200,height=200).display()") # ## Fit using SVI # In[ ]: get_ipython().run_cell_magic('time', '', "from bayes_window import fitting\nbw = BayesRegression(df=df_monster, y='isi', treatment='stim', condition=['neuron', 'mouse'], group='mouse')\nbw.fit(model=models.model_hierarchical, do_make_change='subtract',\n n_draws=5000,\n dist_y='gamma',\n add_group_slope=True, add_group_intercept=False,\n fold_change_index_cols=('stim', 'mouse', 'neuron'),\n fit_method=fitting.fit_svi,\n )\n\nbw.plot(x='neuron', color='mouse', independent_axes=True, finalize=True)\n\n\nbw.facet(column='mouse',width=200,height=200).display()") # In[ ]: get_ipython().run_cell_magic('time', '', "from bayes_window import fitting\nimport numpyro\nfrom importlib import reload\nreload(fitting)\nbw = BayesRegression(df=df_monster, y='isi', treatment='stim', condition=['neuron', 'mouse'], group='mouse')\nbw.fit(model=models.model_hierarchical, do_make_change='subtract',\n\n autoguide=numpyro.infer.autoguide.AutoLaplaceApproximation,\n optim=numpyro.optim.Adam(step_size=0.0005),\n loss=numpyro.infer.Trace_ELBO(),\n dist_y='lognormal',\n add_group_slope=True, add_group_intercept=True,\n fold_change_index_cols=('stim', 'mouse', 'neuron'),\n fit_method=fitting.fit_svi,\n\n n_draws=int(1e5),\n num_warmup=int(1e5),\n )\n\nbw.plot(x='neuron', color='mouse', independent_axes=True, finalize=True)\n\n\nbw.facet(column='mouse',width=200,height=200).display()") # In[ ]: get_ipython().run_cell_magic('time', '', "from bayes_window import fitting\nimport numpyro\n#numpyro.enable_validation(False)\nbw = BayesRegression(df=df_monster, y='isi', treatment='stim', condition=['neuron', 'mouse'], group='mouse')\nbw.fit(model=models.model_hierarchical, do_make_change='subtract',\n #use_gpu=True,\n autoguide=numpyro.infer.autoguide.AutoLaplaceApproximation,\n optim=numpyro.optim.Adam(1),\n loss=numpyro.infer.Trace_ELBO(),\n dist_y='lognormal',\n add_group_slope=True, add_group_intercept=False,\n fold_change_index_cols=('stim', 'mouse', 'neuron'),\n fit_method=fitting.fit_svi,\n #progress_bar=False,\n n_draws=int(1e5),\n num_warmup=int(1e5),\n )\n\nbw.plot(x='neuron', color='mouse', independent_axes=True, finalize=True)\n\n\nbw.facet(column='mouse',width=200,height=200).display()") # Pretty model # In[ ]: reload(models) bw = BayesRegression(df=df, y='isi', treatment='stim', condition=['neuron', 'mouse'], group='mouse') bw.fit(model=models.reparam_model(models.model_hierarchical_for_render), do_make_change='subtract', progress_bar=True, use_gpu=False, num_chains=1, n_draws=1500, num_warmup=1500, dist_y='normal', add_group_slope=True, add_group_intercept=True, fold_change_index_cols=('stim', 'mouse', 'neuron')) bw.plot(x='neuron', color='mouse', independent_axes=True, finalize=True) bw.facet(column='mouse',width=200,height=200).display() # In[ ]: #!pip install git+https://github.com/pyro-ppl/numpyro.git from numpyro.contrib.render import render_model reload(models) render_model(models.model_hierarchical_for_render, model_args=(1, 1, 1, 1, 'gamma', True, True), render_distributions=True) # In[ ]: #!pip install git+https://github.com/pyro-ppl/numpyro.git from numpyro.contrib.render import render_model reload(models) render_model(models.model_hierarchical_for_render, model_args=(1, 1, 1, 1, 'gamma', True, False), render_distributions=True) # In[ ]: #!pip install git+https://github.com/pyro-ppl/numpyro.git from numpyro.contrib.render import render_model reload(models) render_model(models.model_hier_stim_one_codition, model_args=(1, 1, 1, 'gamma', ), render_distributions=True) # ## Two-step # ## Packaged version 1 # Separate levels # In[3]: # bw = BayesRegression(df=df_monster, y='isi',treatment='stim', condition=['neuron_x_mouse'], # group='mouse', detail='i_trial') # bw=bw.fit_twostep_by_group(dist_y_step_one='gamma', dist_y='student') # bw.chart # ## Packaged version 2 # No grouping in first step # In[3]: # bw = BayesRegression(df=df_monster, y='isi',treatment='stim', condition=['neuron_x_mouse'], group='mouse', detail='i_trial') # bw=bw.fit_twostep(dist_y_step_one='gamma', dist_y='student') # In[ ]: # bw.chart

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3a6b6bece59d9972e7c2ff0d724f157d0210e7b0

108

py

Python

python/rain/client/rpc.py

aimof/rain

86b77666e1310888ad483c7976c2c99f3d5bfeaa

[ "MIT" ]

709

2018-03-02T14:34:30.000Z

2022-03-26T13:21:21.000Z

python/rain/client/rpc.py

aimof/rain

86b77666e1310888ad483c7976c2c99f3d5bfeaa

[ "MIT" ]

49

2018-03-03T14:35:27.000Z

2022-03-08T23:38:22.000Z

python/rain/client/rpc.py

aimof/rain

86b77666e1310888ad483c7976c2c99f3d5bfeaa

[ "MIT" ]

56

2018-02-28T14:00:12.000Z

2022-03-08T01:04:04.000Z

from ..common.fs import load_capnp common = load_capnp("common.capnp") server = load_capnp("server.capnp")

21.6

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py

Python

ntou/kobe/admin.py

asas1asas200/ntou2.0

7f5f7ae6d09c998081c5621c77b65a5c85939284

[ "MIT" ]

3

2020-03-20T02:25:46.000Z

2020-07-19T06:18:27.000Z

ntou/kobe/admin.py

asas1asas200/ntou2.0

7f5f7ae6d09c998081c5621c77b65a5c85939284

[ "MIT" ]

16

2020-03-16T08:10:25.000Z

2022-01-13T02:21:50.000Z

ntou/kobe/admin.py

asas1asas200/ntou2.0

7f5f7ae6d09c998081c5621c77b65a5c85939284

[ "MIT" ]

1

2020-03-15T14:05:00.000Z

from django.contrib import admin from .models import KobePost, registrationReviewer admin.site.register(KobePost) admin.site.register(registrationReviewer)

26.166667

50

0.853503

18

157

7.444444

0.555556

0.134328

0.253731

0

0.076433

157

5

51

31.4

0.924138

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

3a911e783b88cb494290e1d4707d645526aea83c

203

py

Python

src/PyMud/command/command_executor.py

NichCritic/pymud

583ec16f5a75dc7b45146564b39851291dc07b6c

[ "MIT" ]

null

src/PyMud/command/command_executor.py

NichCritic/pymud

583ec16f5a75dc7b45146564b39851291dc07b6c

[ "MIT" ]

null

src/PyMud/command/command_executor.py

NichCritic/pymud

583ec16f5a75dc7b45146564b39851291dc07b6c

[ "MIT" ]

null

''' Created on 2013-11-18 @author: Nich ''' class CommandExecutor(object): def execute(self, command_package): command, args = command_package command(**args)

15.615385

39

0.586207

21

203

5.571429

0.761905

0.239316

0.358974

0.42735

0

0.056338

0.300493

203

13

40

15.615385

0.767606

0.17734

0

1

0.25

false

0

0.5

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1

0

null

1

0

null

0

1

0

5

3ac1678ab07f651e542f62e12e0e4a039ae13072

125

py

Python

animalsay/__main__.py

gloriamacia/animal_say

e3730a2cbc66f783ab8d51a6f3b06a7db1f1cc0f

[ "MIT" ]

3

2020-12-27T10:20:28.000Z

2021-03-18T18:38:20.000Z

animalsay/__main__.py

gloriamacia/animal_say

e3730a2cbc66f783ab8d51a6f3b06a7db1f1cc0f

[ "MIT" ]

null

animalsay/__main__.py

gloriamacia/animal_say

e3730a2cbc66f783ab8d51a6f3b06a7db1f1cc0f

[ "MIT" ]

null

import sys from animalsay.utils import say if __name__ == "__main__": say(sys.argv[1] ,' '.join(sys.argv[2:]))

15.625

45

0.616

18

125

3.833333

0.722222

0.202899

0

0.020408

0.216

125

7

46

17.857143

0.683673

0

0.077586

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

3acbdad8c71e7fe9dae438f128d8c24e4a72430d

51,480

py

Python

openprocurement/auction/texas/tests/unit/test_auction.py

OrysiaDrabych/openprocurement.auction.texas

7174da79f524acfa70a2d1015166bef8d44ff799

[ "Apache-2.0" ]

null

openprocurement/auction/texas/tests/unit/test_auction.py

OrysiaDrabych/openprocurement.auction.texas

7174da79f524acfa70a2d1015166bef8d44ff799

[ "Apache-2.0" ]

null

openprocurement/auction/texas/tests/unit/test_auction.py

OrysiaDrabych/openprocurement.auction.texas

7174da79f524acfa70a2d1015166bef8d44ff799

[ "Apache-2.0" ]

4

2018-09-03T15:15:43.000Z

2018-11-02T17:14:07.000Z

import unittest import mock from copy import deepcopy from datetime import datetime, timedelta from openprocurement.auction.texas.auction import Auction from openprocurement.auction.worker_core.constants import TIMEZONE from openprocurement.auction.texas.constants import ( MULTILINGUAL_FIELDS, ADDITIONAL_LANGUAGES, DEADLINE_HOUR, ROUND_DURATION, DEFAULT_AUCTION_TYPE, SANDBOX_AUCTION_DURATION ) class MutableMagicMock(mock.MagicMock): def _mock_call(_mock_self, *args, **kwargs): return super(MutableMagicMock, _mock_self)._mock_call(*deepcopy(args), **deepcopy(kwargs)) class AuctionInitSetup(unittest.TestCase): def setUp(self): self.tender_id = '1' * 32 patch_get_gsm = mock.patch( 'openprocurement.auction.texas.auction.getGlobalSiteManager' ) mock_get_gsm = patch_get_gsm.start() mock_gsm = mock.MagicMock() mock_get_gsm.return_value = mock_gsm self.auction = Auction(self.tender_id) patch_get_gsm.stop() self.mock_db = mock.MagicMock() self.mock_datasource = mock.MagicMock() self.mock_job_service = mock.MagicMock() self.mock_end_auction_event = mock.MagicMock() self.mock_context = { '_end_auction_event': self.mock_end_auction_event, 'auction_doc_id': self.tender_id, 'deadline': 'deadline', 'worker_defaults': { 'deadline': { 'deadline_time': {'hour': DEADLINE_HOUR} } } } self.auction.database = self.mock_db self.auction.datasource = self.mock_datasource self.auction.context = self.mock_context self.auction.job_service = self.mock_job_service self.auction._end_auction_event = self.mock_end_auction_event self.patch_utils = mock.patch( 'openprocurement.auction.texas.auction.utils', ) self.mocked_utils = self.patch_utils.start() self.patch_logger = mock.patch( 'openprocurement.auction.texas.auction.LOGGER' ) self.mocked_logger = self.patch_logger.start() def tearDown(self): self.patch_utils.stop() self.patch_logger.stop() class TestScheduleAuction(AuctionInitSetup): def setUp(self): super(TestScheduleAuction, self).setUp() self.auction.start_auction = mock.MagicMock() self.auction.startDate = 'startDate' self.patch_scheduler = mock.patch( 'openprocurement.auction.texas.auction.SCHEDULER' ) self.mocked_scheduler = self.patch_scheduler.start() self.patch_run_server = mock.patch( 'openprocurement.auction.texas.auction.run_server' ) self.mocked_run_server = self.patch_run_server.start() self.mocked_run_server.return_value = 'server' self.patch_synchronize_auction_info = mock.patch.object( self.auction, 'synchronize_auction_info' ) self.mocked_synchronize_auction_info = self.patch_synchronize_auction_info.start() self.auction.bids_mapping = {'bids': 'mapping'} self.auction._auction_data = {'auction': 'data'} self.auction.bidders_data = {'bidders': 'data'} def tearDown(self): super(TestScheduleAuction, self).tearDown() self.patch_scheduler.stop() self.patch_run_server.stop() self.patch_synchronize_auction_info.stop() def test_auction_schedule(self): auction_document = { 'stages': [ { 'start': datetime.now().isoformat() }, { 'start': datetime.now().isoformat() } ], } self.mock_db.get_auction_document.return_value = auction_document self.mocked_utils.update_auction_document.return_value.__enter__.return_value = auction_document convert_datetime_results = [ datetime.now(), datetime.now(), datetime.now(), ] self.mocked_utils.convert_datetime.side_effect = iter(convert_datetime_results) auction_protocol = {'auction': 'protocol'} self.mocked_utils.prepare_auction_protocol.return_value = auction_protocol self.auction.schedule_auction() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.auction.context['auction_doc_id']) self.assertEqual(self.mocked_utils.update_auction_document.call_count, 1) self.mocked_utils.update_auction_document.assert_called_with(self.auction.context, self.auction.database) self.assertEqual(self.auction.context['auction_document'], auction_document) self.assertEqual(self.auction.context['auction_data'], self.auction._auction_data) self.assertEqual(self.auction.context['bidders_data'], self.auction.bidders_data) self.assertEqual(self.auction.context['bids_mapping'], self.auction.bids_mapping) self.assertEqual(self.auction.context['auction_protocol'], auction_protocol) self.assertEqual(self.mocked_scheduler.add_job.call_count, 1) self.mocked_scheduler.add_job.assert_called_with( self.auction.start_auction, 'date', run_date=convert_datetime_results[0], name='Start of Auction', id='auction:start' ) self.assertEqual(self.auction.job_service.add_pause_job.call_count, 1) self.auction.job_service.add_pause_job.assert_called_with(convert_datetime_results[1]) self.assertEqual(self.auction.job_service.add_ending_main_round_job.call_count, 1) self.auction.job_service.add_ending_main_round_job.assert_called_with( convert_datetime_results[2] + timedelta(seconds=ROUND_DURATION) ) self.mocked_utils.convert_datetime.assert_called_with( auction_document['stages'][1]['start'] ) self.assertEqual(self.mocked_run_server.call_count, 1) self.mocked_run_server.assert_called_with(self.auction, None, self.mocked_logger) self.assertEqual(self.auction.context['server'], 'server') class TestCancelAuction(AuctionInitSetup): def setUp(self): super(TestCancelAuction, self).setUp() self.patch_datetime = mock.patch('openprocurement.auction.texas.auction.datetime') self.mock_datetime = self.patch_datetime.start() self.mock_now = mock.MagicMock() self.isoformat_mock = mock.MagicMock() self.isormat_date = 'isoformat_date' self.isoformat_mock.isoformat.return_value = self.isormat_date self.mock_now.return_value = self.isoformat_mock self.mock_datetime.now = self.mock_now def tearDown(self): super(TestCancelAuction, self).tearDown() self.patch_datetime.stop() def test_cancellation_if_auction_doc_exist(self): auction_document = { 'current_stage': 1 } self.mock_db.get_auction_document.return_value = auction_document self.mocked_utils.update_auction_document.return_value.__enter__.return_value = auction_document self.auction.cancel_auction() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.auction.context['auction_doc_id']) self.assertEqual(self.mocked_utils.update_auction_document.call_count, 1) self.mocked_utils.update_auction_document.assert_called_with(self.auction.context, self.auction.database) self.assertEqual(self.mock_datetime.now.call_count, 1) self.mock_datetime.now.assert_called_with(TIMEZONE) self.assertEqual(auction_document['current_stage'], -100) self.assertEqual(auction_document['endDate'], self.isormat_date) def test_cancellation_if_auction_doc_not_exist(self): self.mock_db.get_auction_document.return_value = None self.auction.cancel_auction() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.auction.context['auction_doc_id']) self.assertEqual(self.mocked_utils.update_auction_document.call_count, 0) self.assertEqual(self.mock_datetime.now.call_count, 0) class TestRescheduleAuction(AuctionInitSetup): def test_reschedule_if_auction_doc_exist(self): auction_document = { 'current_stage': 1 } self.mock_db.get_auction_document.return_value = auction_document self.mocked_utils.update_auction_document.return_value.__enter__.return_value = auction_document self.auction.reschedule_auction() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.auction.context['auction_doc_id']) self.assertEqual(self.mocked_utils.update_auction_document.call_count, 1) self.mocked_utils.update_auction_document.assert_called_with(self.auction.context, self.auction.database) self.assertEqual(auction_document['current_stage'], -101) def test_reschedule_if_auction_doc_not_exist(self): self.mock_db.get_auction_document.return_value = None self.auction.reschedule_auction() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.auction.context['auction_doc_id']) self.assertEqual(self.mocked_utils.update_auction_document.call_count, 0) class TestStartAuction(AuctionInitSetup): def setUp(self): super(TestStartAuction, self).setUp() self.patch_synchronize_auction_info = mock.patch.object( self.auction, 'synchronize_auction_info' ) self.mocked_synchronize_auction_info = self.patch_synchronize_auction_info.start() self.patch_prepare_initial_bids = mock.patch.object( self.auction, '_prepare_initial_bids' ) self.mocked_prepare_initial_bids = self.patch_prepare_initial_bids.start() self.auction.auction_protocol = { 'timeline': { 'auction_start': { 'time': '' } } } self.patch_datetime = mock.patch('openprocurement.auction.texas.auction.datetime') self.mock_datetime = self.patch_datetime.start() self.mock_now = mock.MagicMock() self.isoformat_mock = mock.MagicMock() self.isormat_date = 'isoformat_date' self.isoformat_mock.isoformat.return_value = self.isormat_date self.mock_now.return_value = self.isoformat_mock self.mock_datetime.now = self.mock_now self.auction.context['server_actions'] = 'server_actions' def tearDown(self): super(TestStartAuction, self).tearDown() self.patch_prepare_initial_bids.stop() self.patch_synchronize_auction_info.stop() def test_start_auction(self): auction_document = { 'current_stage': -1 } self.mock_db.get_auction_document.return_value = auction_document self.mocked_utils.update_auction_document.return_value.__enter__.return_value = auction_document self.auction.start_auction() self.assertEqual(auction_document['current_stage'], 0) self.assertEqual(self.mocked_utils.lock_server.call_count, 1) self.mocked_utils.lock_server.assert_called_with(self.auction.context['server_actions']) self.assertEqual(self.mocked_utils.update_auction_document.call_count, 1) self.mocked_utils.update_auction_document.assert_called_with(self.auction.context, self.auction.database) class TestPostAnnounce(AuctionInitSetup): def test_post_announce(self): auction_document = { 'current_stage': 1 } self.mock_db.get_auction_document.return_value = auction_document auction_from_ds = {'auction': 'from_datasource'} self.mock_datasource.get_data.return_value = auction_from_ds self.mocked_utils.update_auction_document.return_value.__enter__.return_value = auction_document bids_info = 'bids info' self.mocked_utils.get_bids.return_value = bids_info self.auction.post_announce() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.auction.context['auction_doc_id']) self.assertEqual(self.mocked_utils.get_bids.call_count, 1) self.mocked_utils.get_bids.assert_called_with(auction_from_ds) self.assertEqual(self.mock_datasource.get_data.call_count, 1) self.mock_datasource.get_data.assert_called_with(with_credentials=True) self.assertEqual(self.mocked_utils.update_auction_document.call_count, 1) self.mocked_utils.update_auction_document.assert_called_with(self.auction.context, self.auction.database) self.assertEqual(self.mocked_utils.open_bidders_name.call_count, 1) self.mocked_utils.open_bidders_name.assert_called_with(auction_document, bids_info) class TestPrepareAuctionDocument(AuctionInitSetup): def setUp(self): super(TestPrepareAuctionDocument, self).setUp() self.start_date = 'startDate' self.auction.startDate = self.start_date self.auction.worker_defaults['sandbox_mode'] = False self.auction.debug = False self.auction_data = {'auction': 'data'} self.auction._auction_data = self.auction_data self.patch_synchronize_auction_info = mock.patch.object( self.auction, 'synchronize_auction_info' ) self.mocked_synchronize_auction_info = self.patch_synchronize_auction_info.start() self.mocked_prepare_auction_document_data = MutableMagicMock() self.auction._prepare_auction_document_data = self.mocked_prepare_auction_document_data self.patch_reschedule = mock.patch.object( self.auction, 'reschedule_auction' ) self.mocked_reschedule = self.patch_reschedule.start() self.prepared_stages = ['pause', 'main'] self.mocked_utils.prepare_auction_stages.return_value = self.prepared_stages def tearDown(self): super(TestPrepareAuctionDocument, self).tearDown() self.patch_synchronize_auction_info.stop() self.patch_reschedule.stop() def test_if_public_document(self): public_document = { '_rev': '111' } self.mock_db.get_auction_document.return_value = public_document auction_document = deepcopy(public_document) self.auction.prepare_auction_document() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.mock_context['auction_doc_id']) self.assertEqual(self.mocked_synchronize_auction_info.call_count, 1) self.mocked_synchronize_auction_info.assert_called_with(prepare=True) self.assertEqual(self.mocked_prepare_auction_document_data.call_count, 1) self.mocked_prepare_auction_document_data.assert_called_with(auction_document) self.assertEqual(self.mocked_utils.prepare_auction_stages.call_count, 1) self.mocked_utils.prepare_auction_stages.assert_called_with(self.start_date, auction_document, self.mock_context['deadline']) self.assertEqual(self.mocked_utils.set_absolute_deadline.call_count, 1) self.mocked_utils.set_absolute_deadline.assert_called_with(self.mock_context, self.start_date) self.assertEqual(self.mocked_utils.set_relative_deadline.call_count, 0) auction_document['stages'] = self.prepared_stages self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with( auction_document, self.mock_context['auction_doc_id'] ) self.assertEqual(self.mock_datasource.set_participation_urls.call_count, 1) self.mock_datasource.set_participation_urls.assert_called_with( self.auction_data ) self.assertEqual(self.mocked_reschedule.call_count, 0) def test_if_no_public_document(self): public_document = {} self.mock_db.get_auction_document.return_value = public_document auction_document = {} self.auction.prepare_auction_document() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.mock_context['auction_doc_id']) self.assertEqual(self.mocked_synchronize_auction_info.call_count, 1) self.mocked_synchronize_auction_info.assert_called_with(prepare=True) self.assertEqual(self.mocked_prepare_auction_document_data.call_count, 1) self.mocked_prepare_auction_document_data.assert_called_with(auction_document) self.assertEqual(self.mocked_utils.prepare_auction_stages.call_count, 1) self.mocked_utils.prepare_auction_stages.assert_called_with(self.start_date, auction_document, self.mock_context['deadline']) self.assertEqual(self.mocked_utils.set_absolute_deadline.call_count, 1) self.mocked_utils.set_absolute_deadline.assert_called_with(self.mock_context, self.start_date) self.assertEqual(self.mocked_utils.set_relative_deadline.call_count, 0) auction_document['stages'] = self.prepared_stages self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with( auction_document, self.mock_context['auction_doc_id'] ) self.assertEqual(self.mock_datasource.set_participation_urls.call_count, 1) self.mock_datasource.set_participation_urls.assert_called_with( self.auction_data ) self.assertEqual(self.mocked_reschedule.call_count, 0) def test_if_debug(self): self.auction.debug = True public_document = { '_rev': '111' } self.mock_db.get_auction_document.return_value = public_document auction_document = deepcopy(public_document) auction_document['mode'] = 'test' auction_document['test_auction_data'] = self.auction_data self.auction.prepare_auction_document() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.mock_context['auction_doc_id']) self.assertEqual(self.mocked_synchronize_auction_info.call_count, 1) self.mocked_synchronize_auction_info.assert_called_with(prepare=True) self.assertEqual(self.mocked_prepare_auction_document_data.call_count, 1) self.mocked_prepare_auction_document_data.assert_called_with(auction_document) self.assertEqual(self.mocked_utils.prepare_auction_stages.call_count, 1) self.mocked_utils.prepare_auction_stages.assert_called_with(self.start_date, auction_document, self.mock_context['deadline']) self.assertEqual(self.mocked_utils.set_absolute_deadline.call_count, 1) self.mocked_utils.set_absolute_deadline.assert_called_with(self.mock_context, self.start_date) self.assertEqual(self.mocked_utils.set_relative_deadline.call_count, 0) auction_document['stages'] = self.prepared_stages self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with( auction_document, self.mock_context['auction_doc_id'] ) self.assertEqual(self.mock_datasource.set_participation_urls.call_count, 1) self.mock_datasource.set_participation_urls.assert_called_with( self.auction_data ) self.assertEqual(self.mocked_reschedule.call_count, 0) def test_if_no_debug(self): self.auction.debug = False public_document = { '_rev': '111' } self.mock_db.get_auction_document.return_value = public_document auction_document = deepcopy(public_document) self.auction.prepare_auction_document() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.mock_context['auction_doc_id']) self.assertEqual(self.mocked_synchronize_auction_info.call_count, 1) self.mocked_synchronize_auction_info.assert_called_with(prepare=True) self.assertEqual(self.mocked_prepare_auction_document_data.call_count, 1) self.mocked_prepare_auction_document_data.assert_called_with(auction_document) self.assertEqual(self.mocked_utils.prepare_auction_stages.call_count, 1) self.mocked_utils.prepare_auction_stages.assert_called_with(self.start_date, auction_document, self.mock_context['deadline']) self.assertEqual(self.mocked_utils.set_absolute_deadline.call_count, 1) self.mocked_utils.set_absolute_deadline.assert_called_with(self.mock_context, self.start_date) self.assertEqual(self.mocked_utils.set_relative_deadline.call_count, 0) auction_document['stages'] = self.prepared_stages self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with( auction_document, self.mock_context['auction_doc_id'] ) self.assertEqual(self.mock_datasource.set_participation_urls.call_count, 1) self.mock_datasource.set_participation_urls.assert_called_with( self.auction_data ) self.assertEqual(self.mocked_reschedule.call_count, 0) def test_if_sandbox(self): self.auction.worker_defaults['sandbox_mode'] = True public_document = { '_rev': '111' } self.mock_db.get_auction_document.return_value = public_document auction_document = deepcopy(public_document) self.auction.prepare_auction_document() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.mock_context['auction_doc_id']) self.assertEqual(self.mocked_synchronize_auction_info.call_count, 1) self.mocked_synchronize_auction_info.assert_called_with(prepare=True) self.assertEqual(self.mocked_prepare_auction_document_data.call_count, 1) self.mocked_prepare_auction_document_data.assert_called_with(auction_document) self.assertEqual(self.mocked_utils.prepare_auction_stages.call_count, 1) self.mocked_utils.prepare_auction_stages.assert_called_with( self.start_date, auction_document, self.mock_context['deadline'], fast_forward=True ) self.assertEqual(self.mocked_utils.set_absolute_deadline.call_count, 1) self.mocked_utils.set_absolute_deadline.assert_called_with(self.mock_context, self.start_date) self.assertEqual(self.mocked_utils.set_relative_deadline.call_count, 0) auction_document['stages'] = self.prepared_stages self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with( auction_document, self.mock_context['auction_doc_id'] ) self.assertEqual(self.mock_datasource.set_participation_urls.call_count, 1) self.mock_datasource.set_participation_urls.assert_called_with( self.auction_data ) self.assertEqual(self.mocked_reschedule.call_count, 0) def test_if_no_sandbox(self): self.auction.worker_defaults['sandbox_mode'] = False public_document = { '_rev': '111' } self.mock_db.get_auction_document.return_value = public_document auction_document = deepcopy(public_document) self.auction.prepare_auction_document() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.mock_context['auction_doc_id']) self.assertEqual(self.mocked_synchronize_auction_info.call_count, 1) self.mocked_synchronize_auction_info.assert_called_with(prepare=True) self.assertEqual(self.mocked_prepare_auction_document_data.call_count, 1) self.mocked_prepare_auction_document_data.assert_called_with(auction_document) self.assertEqual(self.mocked_utils.prepare_auction_stages.call_count, 1) self.mocked_utils.prepare_auction_stages.assert_called_with(self.start_date, auction_document, self.mock_context['deadline']) self.assertEqual(self.mocked_utils.set_absolute_deadline.call_count, 1) self.mocked_utils.set_absolute_deadline.assert_called_with(self.mock_context, self.start_date) self.assertEqual(self.mocked_utils.set_relative_deadline.call_count, 0) auction_document['stages'] = self.prepared_stages self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with( auction_document, self.mock_context['auction_doc_id'] ) self.assertEqual(self.mock_datasource.set_participation_urls.call_count, 1) self.mock_datasource.set_participation_urls.assert_called_with( self.auction_data ) self.assertEqual(self.mocked_reschedule.call_count, 0) def test_if_main_round(self): self.mocked_utils.prepare_auction_stages.return_value = self.prepared_stages public_document = { '_rev': '111' } self.mock_db.get_auction_document.return_value = public_document auction_document = deepcopy(public_document) self.auction.prepare_auction_document() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.mock_context['auction_doc_id']) self.assertEqual(self.mocked_synchronize_auction_info.call_count, 1) self.mocked_synchronize_auction_info.assert_called_with(prepare=True) self.assertEqual(self.mocked_prepare_auction_document_data.call_count, 1) self.mocked_prepare_auction_document_data.assert_called_with(auction_document) self.assertEqual(self.mocked_utils.prepare_auction_stages.call_count, 1) self.mocked_utils.prepare_auction_stages.assert_called_with(self.start_date, auction_document, self.mock_context['deadline']) self.assertEqual(self.mocked_utils.set_absolute_deadline.call_count, 1) self.mocked_utils.set_absolute_deadline.assert_called_with(self.mock_context, self.start_date) self.assertEqual(self.mocked_utils.set_relative_deadline.call_count, 0) auction_document['stages'] = self.prepared_stages self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with( auction_document, self.mock_context['auction_doc_id'] ) self.assertEqual(self.mock_datasource.set_participation_urls.call_count, 1) self.mock_datasource.set_participation_urls.assert_called_with( self.auction_data ) self.assertEqual(self.mocked_reschedule.call_count, 0) def test_if_no_main_round(self): prepared_stages = [self.prepared_stages[0], {}] self.mocked_utils.prepare_auction_stages.return_value = prepared_stages public_document = { '_rev': '111' } self.mock_db.get_auction_document.return_value = public_document auction_document = deepcopy(public_document) self.auction.prepare_auction_document() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.mock_context['auction_doc_id']) self.assertEqual(self.mocked_synchronize_auction_info.call_count, 1) self.mocked_synchronize_auction_info.assert_called_with(prepare=True) self.assertEqual(self.mocked_prepare_auction_document_data.call_count, 1) self.mocked_prepare_auction_document_data.assert_called_with(auction_document) self.assertEqual(self.mocked_utils.prepare_auction_stages.call_count, 1) self.mocked_utils.prepare_auction_stages.assert_called_with(self.start_date, auction_document, self.mock_context['deadline']) self.assertEqual(self.mocked_utils.set_absolute_deadline.call_count, 1) self.mocked_utils.set_absolute_deadline.assert_called_with(self.mock_context, self.start_date) self.assertEqual(self.mocked_utils.set_relative_deadline.call_count, 0) auction_document['stages'] = prepared_stages self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with( auction_document, self.mock_context['auction_doc_id'] ) self.assertEqual(self.mock_datasource.set_participation_urls.call_count, 0) self.assertEqual(self.mocked_reschedule.call_count, 1) def test_if_mod_test_and_smd(self): self.auction.worker_defaults['sandbox_mode'] = True public_document = { '_rev': '111' } self.auction._auction_data = { 'data': { 'mode': 'test', 'submissionMethodDetails': 'quick', } } self.mock_db.get_auction_document.return_value = public_document auction_document = deepcopy(public_document) auction_document.update({'submissionMethodDetails': 'quick'}) self.auction.prepare_auction_document() self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.mock_context['auction_doc_id']) self.assertEqual(self.mocked_synchronize_auction_info.call_count, 1) self.mocked_synchronize_auction_info.assert_called_with(prepare=True) self.assertEqual(self.mocked_prepare_auction_document_data.call_count, 1) self.mocked_prepare_auction_document_data.assert_called_with(auction_document) self.assertEqual(self.mocked_utils.prepare_auction_stages.call_count, 1) self.mocked_utils.prepare_auction_stages.assert_called_with( self.start_date, auction_document, self.mock_context['deadline'], fast_forward=True ) self.assertEqual(self.mocked_utils.set_absolute_deadline.call_count, 0) self.assertEqual(self.mocked_utils.set_relative_deadline.call_count, 1) self.mocked_utils.set_relative_deadline.assert_called_with( self.mock_context, self.start_date, SANDBOX_AUCTION_DURATION ) auction_document['stages'] = self.prepared_stages self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with( auction_document, self.mock_context['auction_doc_id'] ) self.assertEqual(self.mock_datasource.set_participation_urls.call_count, 1) self.mock_datasource.set_participation_urls.assert_called_with( self.auction._auction_data ) self.assertEqual(self.mocked_reschedule.call_count, 0) class TestPrepareInitialBids(AuctionInitSetup): def setUp(self): super(TestPrepareInitialBids, self).setUp() self.start_date = 'startDate' self.auction.startDate = self.start_date self.bids_mapping = { 'id_1': 'bid_1', 'id_2': 'bid_2' } self.auction.bids_mapping = deepcopy(self.bids_mapping) self.auction.auction_protocol = { 'timeline': { 'auction_start': { 'initial_bids': [] } } } self.patch_sorting_start_bids_by_amount = mock.patch( 'openprocurement.auction.texas.auction.sorting_start_bids_by_amount' ) self.resulted_stages = ['1_stage', '2_stage'] self.mocked_utils.prepare_results_stage.side_effect = self.resulted_stages def tearDown(self): super(TestPrepareInitialBids, self).tearDown() self.patch_sorting_start_bids_by_amount.stop() def test_prepare_initial_bids(self): auction_document = { 'value': {'amount': 10000}, 'initial_bids': [] } bidders_data = [ { 'id': 'id_1', 'date': 'date_1', 'value': {'amount': 1000}, 'owner': 'owner_1', 'bidNumber': 1, }, { 'id': 'id_2', 'date': 'date_2', 'value': {'amount': 2000}, 'owner': 'owner_2', 'bidNumber': 2 } ] self.auction.bidders_data = deepcopy(bidders_data) self.mocked_sorting_start_bids_by_amount = self.patch_sorting_start_bids_by_amount.start() self.mocked_sorting_start_bids_by_amount.return_value = deepcopy(bidders_data) auction_protocol = { 'timeline': { 'auction_start': { 'initial_bids': [ { 'bidder': bidders_data[0]['id'], 'date': bidders_data[0]['date'], 'amount': auction_document['value']['amount'], 'bid_number': self.bids_mapping[bidders_data[0]['id']] }, { 'bidder': bidders_data[1]['id'], 'date': bidders_data[1]['date'], 'amount': auction_document['value']['amount'], 'bid_number': self.bids_mapping[bidders_data[1]['id']] } ] } } } self.auction._prepare_initial_bids(auction_document) self.assertEqual(self.mocked_sorting_start_bids_by_amount.call_count, 1) self.mocked_sorting_start_bids_by_amount.assert_called_with(bidders_data) self.assertEqual(self.mocked_utils.prepare_results_stage.call_count, 2) self.mocked_utils.prepare_results_stage.assert_called_with( bidder_id=bidders_data[1]['id'], time=bidders_data[1]['date'], bidder_name=self.bids_mapping[bidders_data[1]['id']], amount=auction_document['value']['amount'] ) self.assertEqual(auction_document['initial_bids'], self.resulted_stages) self.assertEqual(self.mock_context['auction_protocol'], auction_protocol) # def test_prepare_initial_bids_without_date(self): # auction_document = { # 'value': {'amount': 10000}, # 'initial_bids': [] # } # # bidders_data = [ # { # 'id': 'id_1', # 'value': {'amount': 1000}, # 'owner': 'owner_1' # }, # { # 'id': 'id_2', # 'value': {'amount': 2000}, # 'owner': 'owner_2' # } # ] # self.auction.bidders_data = deepcopy(bidders_data) # # self.mocked_sorting_start_bids_by_amount = self.patch_sorting_start_bids_by_amount.start() # self.mocked_sorting_start_bids_by_amount.return_value = deepcopy(bidders_data) # # auction_protocol = { # 'timeline': { # 'auction_start': { # 'initial_bids': [ # { # 'bidder': bidders_data[0]['id'], # 'date': self.start_date, # 'amount': auction_document['value']['amount'], # 'bid_number': self.bids_mapping[bidders_data[0]['id']] # }, # { # 'bidder': bidders_data[1]['id'], # 'date': self.start_date, # 'amount': auction_document['value']['amount'], # 'bid_number': self.bids_mapping[bidders_data[1]['id']] # } # ] # } # } # } # # self.auction._prepare_initial_bids(auction_document) # # self.assertEqual(self.mocked_sorting_start_bids_by_amount.call_count, 1) # self.mocked_sorting_start_bids_by_amount.assert_called_with(bidders_data) # # self.assertEqual(self.mocked_utils.prepare_results_stage.call_count, 2) # self.mocked_utils.prepare_results_stage.assert_called_with( # bidder_id=bidders_data[1]['id'], # time=self.start_date, # bidder_name=self.bids_mapping[bidders_data[1]['id']], # amount=auction_document['value']['amount'] # ) # # self.assertEqual(auction_document['initial_bids'], self.resulted_stages) # self.assertEqual(self.mock_context['auction_protocol'], auction_protocol) class TestPrepareAuctionDocumentData(AuctionInitSetup): def setUp(self): super(TestPrepareAuctionDocumentData, self).setUp() self.auction_data = { 'data': { 'auctionID': 'auction-id', 'procurementMethodType': 'landlease', 'procuringEntity': {'some': 'entity'}, 'items': ['item1', 'item2'], 'value': {'amount': 1000}, 'minimalStep': {'amount': 100}, 'title': 'Title', 'description': 'Description', 'title_en': 'Translated title' } } self.auction.worker_defaults['resource_api_version'] = '1' self.auction._auction_data = deepcopy(self.auction_data) def test_prepare_auction_document_data(self): auction_document = {} expected_result = { "_id": self.mock_context['auction_doc_id'], "stages": [], "auctionID": self.auction_data["data"].get("auctionID", ""), "procurementMethodType": self.auction_data["data"].get( "procurementMethodType", "texas"), "TENDERS_API_VERSION": self.auction.worker_defaults['resource_api_version'], "current_stage": -1, "results": [], "initial_bids": [], "procuringEntity": self.auction_data["data"]['procuringEntity'], "items": self.auction_data["data"]["items"], "value": self.auction_data["data"]["value"], "minimalStep": self.auction_data["data"]["minimalStep"], "initial_value": self.auction_data["data"]["value"]["amount"], "auction_type": DEFAULT_AUCTION_TYPE, "title": self.auction_data["data"]["title"], "title_en": self.auction_data["data"]["title_en"], "description": self.auction_data["data"]["description"] } self.auction._prepare_auction_document_data(auction_document) self.assertEqual(auction_document, expected_result) class TestSynchronizeAuctionInfo(AuctionInitSetup): def setUp(self): super(TestSynchronizeAuctionInfo, self).setUp() self.patch_set_auction_data = mock.patch.object( self.auction, '_set_auction_data' ) self.mocked_set_auction_data = self.patch_set_auction_data.start() self.patch_set_start_date = mock.patch.object( self.auction, '_set_start_date' ) self.mocked_set_start_date = self.patch_set_start_date.start() self.patch_set_bidders_data = mock.patch.object( self.auction, '_set_bidders_data' ) self.mocked_set_bidders_data = self.patch_set_bidders_data.start() self.patch_set_mapping = mock.patch.object( self.auction, '_set_mapping' ) self.mocked_set_mapping = self.patch_set_mapping.start() def test_synchronize_auction_info(self): self.auction.synchronize_auction_info() self.assertEqual(self.mocked_set_auction_data.call_count, 1) self.mocked_set_auction_data.assert_called_with(False) self.assertEqual(self.mocked_set_start_date.call_count, 1) self.assertEqual(self.mocked_set_bidders_data.call_count, 1) self.assertEqual(self.mocked_set_mapping.call_count, 1) class TestSetAuctionData(AuctionInitSetup): def setUp(self): super(TestSetAuctionData, self).setUp() self.patch_generate_request_id = mock.patch( 'openprocurement.auction.texas.auction.generate_request_id' ) self.mocked_generate_request_id = self.patch_generate_request_id.start() self.mocked_generate_request_id.return_value = 'generated_request_id' self.start_date = 'converted_datetime' self.mocked_utils.convert_datetime.return_value = self.start_date self.patch_sys = mock.patch( 'openprocurement.auction.texas.auction.sys' ) self.mock_sys = self.patch_sys.start() def tearDown(self): super(TestSetAuctionData, self).tearDown() self.patch_generate_request_id.stop() self.patch_sys.stop() def test_with_prepare(self): get_data = [ {'data': {'auctionPeriod': {'startDate': 'startDate'}}}, {'data': {'second': 'data'}} ] self.mock_datasource.get_data.side_effect = iter(get_data) self.mock_db.get_auction_document.return_value = {'some': 'data'} expected_auction_data = {} expected_auction_data.update(get_data[0]) expected_auction_data['data'].update(get_data[1]['data']) self.auction._set_auction_data(True) self.assertEqual(self.mock_datasource.get_data.call_count, 2) self.mock_datasource.get_data.assert_called_with(public=False) self.assertEqual(self.auction._auction_data, expected_auction_data) self.assertEqual(self.auction.startDate, self.start_date) self.assertEqual(self.mock_end_auction_event.set.call_count, 0) self.assertEqual(self.mocked_utils.convert_datetime.call_count, 1) self.mocked_utils.convert_datetime.assert_called_with(expected_auction_data['data']['auctionPeriod']['startDate']) self.assertEqual(self.mock_db.get_auction_document.call_count, 0) self.assertEqual(self.mock_db.save_auction_document.call_count, 0) self.assertEqual(self.mock_sys.exit.call_count, 0) def test_without_prepare(self): get_data = [ {'data': {'auctionPeriod': {'startDate': 'startDate'}}}, ] self.mock_datasource.get_data.side_effect = iter(get_data) self.mock_db.get_auction_document.return_value = {'some': 'data'} expected_auction_data = get_data[0] self.auction._set_auction_data(False) self.assertEqual(self.mock_datasource.get_data.call_count, 1) self.mock_datasource.get_data.assert_called_with(public=False) self.assertEqual(self.auction._auction_data, expected_auction_data) self.assertEqual(self.auction.startDate, self.start_date) self.assertEqual(self.mock_end_auction_event.set.call_count, 0) self.assertEqual(self.mocked_utils.convert_datetime.call_count, 1) self.mocked_utils.convert_datetime.assert_called_with(expected_auction_data['data']['auctionPeriod']['startDate']) self.assertEqual(self.mock_db.get_auction_document.call_count, 0) self.assertEqual(self.mock_db.save_auction_document.call_count, 0) self.assertEqual(self.mock_sys.exit.call_count, 0) def test_with_auction_data(self): get_data = [ {'data': {'auctionPeriod': {'startDate': 'startDate'}}}, ] self.mock_datasource.get_data.side_effect = iter(get_data) self.mock_db.get_auction_document.return_value = {'some': 'data'} expected_auction_data = get_data[0] self.auction._set_auction_data(False) self.assertEqual(self.mock_datasource.get_data.call_count, 1) self.mock_datasource.get_data.assert_called_with(public=False) self.assertEqual(self.auction._auction_data, expected_auction_data) self.assertEqual(self.auction.startDate, self.start_date) self.assertEqual(self.mock_end_auction_event.set.call_count, 0) self.assertEqual(self.mocked_utils.convert_datetime.call_count, 1) self.mocked_utils.convert_datetime.assert_called_with(expected_auction_data['data']['auctionPeriod']['startDate']) self.assertEqual(self.mock_db.get_auction_document.call_count, 0) self.assertEqual(self.mock_db.save_auction_document.call_count, 0) self.assertEqual(self.mock_sys.exit.call_count, 0) def test_without_auction_data(self): self.mock_datasource.get_data.return_value = {} auction_document = {'some': 'data'} self.mock_db.get_auction_document.return_value = auction_document self.auction.startDate = None expected_auction_data = {'data': {}} self.auction._set_auction_data(False) self.assertEqual(self.mock_datasource.get_data.call_count, 1) self.mock_datasource.get_data.assert_called_with(public=False) self.assertEqual(self.auction._auction_data, expected_auction_data) self.assertEqual(self.auction.startDate, None) self.assertEqual(self.mock_end_auction_event.set.call_count, 0) self.assertEqual(self.mocked_utils.convert_datetime.call_count, 0) self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.tender_id) expected_call = deepcopy(auction_document) expected_call['current_stage'] = -100 self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with(expected_call, self.tender_id) self.assertEqual(self.mock_sys.exit.call_count, 0) def test_with_auction_document(self): self.mock_datasource.get_data.return_value = {} auction_document = {'some': 'data'} self.mock_db.get_auction_document.return_value = auction_document self.auction.startDate = None expected_auction_data = {'data': {}} self.auction._set_auction_data(False) self.assertEqual(self.mock_datasource.get_data.call_count, 1) self.mock_datasource.get_data.assert_called_with(public=False) self.assertEqual(self.auction._auction_data, expected_auction_data) self.assertEqual(self.auction.startDate, None) self.assertEqual(self.mock_end_auction_event.set.call_count, 0) self.assertEqual(self.mocked_utils.convert_datetime.call_count, 0) self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.tender_id) expected_call = deepcopy(auction_document) expected_call['current_stage'] = -100 self.assertEqual(self.mock_db.save_auction_document.call_count, 1) self.mock_db.save_auction_document.assert_called_with(expected_call, self.tender_id) self.assertEqual(self.mock_sys.exit.call_count, 0) def test_without_auction_document(self): self.mock_datasource.get_data.return_value = {} self.mock_db.get_auction_document.return_value = {} self.auction.startDate = None expected_auction_data = {'data': {}} self.auction._set_auction_data(False) self.assertEqual(self.mock_datasource.get_data.call_count, 1) self.mock_datasource.get_data.assert_called_with(public=False) self.assertEqual(self.auction._auction_data, expected_auction_data) self.assertEqual(self.auction.startDate, None) self.assertEqual(self.mock_end_auction_event.set.call_count, 1) self.assertEqual(self.mocked_utils.convert_datetime.call_count, 0) self.assertEqual(self.mock_db.get_auction_document.call_count, 1) self.mock_db.get_auction_document.assert_called_with(self.tender_id) self.assertEqual(self.mock_db.save_auction_document.call_count, 0) self.assertEqual(self.mock_sys.exit.call_count, 1) self.mock_sys.exit.assert_called_with(1) class TestSetStartDate(AuctionInitSetup): def setUp(self): super(TestSetStartDate, self).setUp() self.auction.worker_defaults['sandbox_mode'] = False self.auction._auction_data = { 'data': { 'auctionPeriod': { 'startDate': 'startDate' } } } self.converted_time = datetime.now() self.mocked_utils.convert_datetime.return_value = self.converted_time def test_start_date(self): self.auction._set_start_date() self.assertEqual(self.auction.startDate, self.converted_time) class TestBiddersData(AuctionInitSetup): def setUp(self): super(TestBiddersData, self).setUp() self.prepared_bids = [ { 'id': 'id_1', 'date': 'date_1', 'value': 'value_1', 'owner': 'owner_1', 'bidNumber': '1' }, { 'id': 'id_2', 'date': 'date_2', 'value': 'value_2', 'owner': 'owner_2', 'status': 'active', }, { 'id': 'id_3', 'date': 'date_3', 'value': 'value_3', 'owner': 'owner_3', 'status': 'invalid' } ] self.auction._auction_data = { 'data': {'bids': self.prepared_bids} } def test_bidders_data(self): expected_result = deepcopy(self.prepared_bids[:2]) del expected_result[1]['status'] expected_result[1]['bidNumber'] = None self.auction._set_bidders_data() self.assertEqual(self.auction.bidders_data, expected_result) class TestSetMapping(AuctionInitSetup): def setUp(self): super(TestSetMapping, self).setUp() self.prepared_bids = [ { 'id': 'id_1', 'date': 'date_1', 'value': 'value_1', 'owner': 'owner_1' }, { 'id': 'id_2', 'date': 'date_2', 'value': 'value_2', 'owner': 'owner_2', } ] self.auction.bidders_data = self.prepared_bids self.auction.bids_mapping = {} def test_set_mapping(self): expected_result = { 'id_1': 1, 'id_2': 2 } self.auction._set_mapping() self.assertEqual(self.auction.bids_mapping, expected_result) def suite(): suite = unittest.TestSuite() suite.addTest(unittest.makeSuite(TestScheduleAuction)) return suite

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null

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5

3ad0e34800309dd164ea7a1081ccf63f7f937ba8

59

py

Python

tests/test_basic.py

ld1106282791/image-ema-2019-project

399af7b9bbf33c21eb4f64e01fd2405b01f77234

[ "MIT" ]

null

tests/test_basic.py

ld1106282791/image-ema-2019-project

399af7b9bbf33c21eb4f64e01fd2405b01f77234

[ "MIT" ]

null

tests/test_basic.py

ld1106282791/image-ema-2019-project

399af7b9bbf33c21eb4f64e01fd2405b01f77234

[ "MIT" ]

null

""" Code unit-tests go here. """ import image_ema_project

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5

c93756239c9361a65511ed00923a693cd42c0f03

202

py

Python

end_signal.py

AlxndrMlk/dataScienceHelpers

5da8426817d84f8790e0dfc5479240fa4f328d8f

[ "MIT" ]

null

end_signal.py

AlxndrMlk/dataScienceHelpers

5da8426817d84f8790e0dfc5479240fa4f328d8f

[ "MIT" ]

null

end_signal.py

AlxndrMlk/dataScienceHelpers

5da8426817d84f8790e0dfc5479240fa4f328d8f

[ "MIT" ]

null

def end_signal(): # Hey, computer, let me know when you're done! :) # NOTE: This only works for Windows winsound.Beep(440, 100) time.sleep(.05) winsound.Beep(660, 100)

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c95cfee18bc3a2cbb786458ab6133cf20929e210

164

py

Python

t.py

alfredcs/marketTrend

3a6afa04a3cb21f7d624a0169da6a733eaa7ab22

[ "MIT" ]

null

t.py

alfredcs/marketTrend

3a6afa04a3cb21f7d624a0169da6a733eaa7ab22

[ "MIT" ]

null

t.py

alfredcs/marketTrend

3a6afa04a3cb21f7d624a0169da6a733eaa7ab22

[ "MIT" ]

null

import json data = [] with open('t.json') as f: for line in f: #data.append(json.loads(line)) print(json.loads(line)) print("-------")

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null

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5

c971319c656c4d0b85584935b930349274b5136b

82

py

Python

robovat/envs/__init__.py

leobxpan/robovat

0d360c34c677cf018c4daab0b8e758943ae1d2c1

[ "MIT" ]

62

2020-04-08T11:26:24.000Z

2021-09-06T02:45:53.000Z

robovat/envs/__init__.py

leobxpan/robovat

0d360c34c677cf018c4daab0b8e758943ae1d2c1

[ "MIT" ]

7

2020-04-12T13:10:10.000Z

2022-03-12T00:15:03.000Z

robovat/envs/__init__.py

leobxpan/robovat

0d360c34c677cf018c4daab0b8e758943ae1d2c1

[ "MIT" ]

17

2020-04-12T17:37:01.000Z

2021-09-07T01:51:46.000Z

from .grasp.grasp_4dof_env import Grasp4DofEnv from .push.push_env import PushEnv

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null

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5

c981a949ff43c4399bc53c05d58e42fe12793ae2

37

py

Python

bye.py

blahu/pynet-course2

a11ba8545a67c97fa9f781b3971cb58fa1f79830

[ "Apache-2.0" ]

null

bye.py

blahu/pynet-course2

a11ba8545a67c97fa9f781b3971cb58fa1f79830

[ "Apache-2.0" ]

null

bye.py

blahu/pynet-course2

a11ba8545a67c97fa9f781b3971cb58fa1f79830

[ "Apache-2.0" ]

null

#!/usr/bin/env python print ("bye!)

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1

0

5

a377b6c3a5ad6f2f60846f15b6c6aca9c38a185c

216

py

Python

EHESTPRAC/admin.py

TIJMacLean/FlyMyPlane

3e3f069b37482456857146383e3c5d8bbcdfdb0e

[ "Apache-2.0" ]

null

EHESTPRAC/admin.py

TIJMacLean/FlyMyPlane

3e3f069b37482456857146383e3c5d8bbcdfdb0e

[ "Apache-2.0" ]

null

EHESTPRAC/admin.py

TIJMacLean/FlyMyPlane

3e3f069b37482456857146383e3c5d8bbcdfdb0e

[ "Apache-2.0" ]

null

from django.contrib import admin # Register your models here. from .models import Question, Choices, FlightCategories admin.site.register(Question) admin.site.register(Choices) admin.site.register(FlightCategories)

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null

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5

a38f97bd381eb1276ebdd07068150eb18f14545b

71

py

Python

icevision/models/mmseg/models/deeplabv3/backbones/__init__.py

lgvaz/mantisshrimp2

743cb7df0dae7eb1331fc2bb66fc9ca09db496cd

[ "Apache-2.0" ]

17

2020-07-31T22:09:07.000Z

2020-08-30T11:18:36.000Z

icevision/models/mmseg/models/deeplabv3/backbones/__init__.py

Borda/icevision

743cb7df0dae7eb1331fc2bb66fc9ca09db496cd

[ "Apache-2.0" ]

115

2020-08-01T09:19:54.000Z

2020-09-04T18:51:28.000Z

icevision/models/mmseg/models/deeplabv3/backbones/__init__.py

lgvaz/mantisshrimp2

743cb7df0dae7eb1331fc2bb66fc9ca09db496cd

[ "Apache-2.0" ]

1

2020-08-25T06:04:34.000Z

from icevision.models.mmseg.models.deeplabv3.backbones.resnet import *

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a397102beaf9efdef7f450f1dd065e24125829c7

36

py

Python

hdash/__init__.py

inodb/hdash

829ffbe856af17876343bc81f577fa7ee2118784

[ "MIT" ]

null

hdash/__init__.py

inodb/hdash

829ffbe856af17876343bc81f577fa7ee2118784

[ "MIT" ]

2

2021-05-24T17:15:45.000Z

2022-03-09T21:44:32.000Z

hdash/__init__.py

inodb/hdash

829ffbe856af17876343bc81f577fa7ee2118784

[ "MIT" ]

1

2021-11-16T23:15:47.000Z

"""HTAN Dashboard and Validator."""

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0

1

0

null

0

1

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5

6e6a89452213e705deaad278cdd52d110d8a954a

501

py

Python

61.py

thaisNY/OtavioMiranda_PY

a381fbd6a3fef5c118f3f1a8064adb9f4ad09477

[ "MIT" ]

null

61.py

thaisNY/OtavioMiranda_PY

a381fbd6a3fef5c118f3f1a8064adb9f4ad09477

[ "MIT" ]

null

61.py

thaisNY/OtavioMiranda_PY

a381fbd6a3fef5c118f3f1a8064adb9f4ad09477

[ "MIT" ]

null

t1 = 1, print(type(t1)) t2 = 1, 2, 3 print(t2) #<class 'tuple'> #(1, 2, 3) #truplas sao iteraveis e fatiaveis t3 = 1,2, 'Thais', 4, 5 t4 = 6, 7, 8, 9, 10 t5 = t3 + t4 print(t5) #(1, 2, 'Thais', 4, 5, 6, 7, 8, 9, 10) n1,n2,n3,n4,*n_outros,n10 = t5 print(n1, n2, n3,n4) print(*n_outros) print(n10) #1 2 Thais 4 #5 6 7 8 9 #10 n1 = 'oi', print(n1*10) #('oi', 'oi', 'oi', 'oi', 'oi', 'oi', 'oi', 'oi', 'oi', 'oi') t6 = (1,2,3,4) t6 = list(t6) t6[2] = 300 t6 = tuple(t6) print(t6) #(1, 2, 300, 4)

13.184211

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5

6e9873f74e7ddb34233125bf6ccd2a2f1587278d

203

py

Python

queick/__init__.py

jmriego/queick

24dcdb2a62ac1ebe8e10b3997aea909b674e704c

[ "MIT" ]

23

2020-11-08T03:41:14.000Z

2022-03-05T15:41:28.000Z

queick/__init__.py

jmriego/queick

24dcdb2a62ac1ebe8e10b3997aea909b674e704c

[ "MIT" ]

1

2021-07-22T21:58:32.000Z

2021-08-10T10:42:13.000Z

queick/__init__.py

jmriego/queick

24dcdb2a62ac1ebe8e10b3997aea909b674e704c

[ "MIT" ]

2

2021-04-28T11:53:05.000Z

2021-12-07T21:37:10.000Z

from .worker import Worker from .queue_manager import QueueManager from .constants import RETRY_TYPE from .job_queue import JobQueue from .exceptions import * from .scheduling_time import SchedulingTime

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5

6e9eaa5fc7f8c33d29ef1925ba3024a4e1085311

6,550

py

Python

401.binary-watch.py

windard/leeeeee

0107a5f95746592ca4fe78d2b5875cf65b1910e7

[ "MIT" ]

null

401.binary-watch.py

windard/leeeeee

0107a5f95746592ca4fe78d2b5875cf65b1910e7

[ "MIT" ]

null

401.binary-watch.py

windard/leeeeee

0107a5f95746592ca4fe78d2b5875cf65b1910e7

[ "MIT" ]

null

# # @lc app=leetcode id=401 lang=python # # [401] Binary Watch # # https://leetcode.com/problems/binary-watch/description/ # # algorithms # Easy (45.07%) # Total Accepted: 61.8K # Total Submissions: 136.8K # Testcase Example: '0' # # A binary watch has 4 LEDs on the top which represent the hours (0-11), and # the 6 LEDs on the bottom represent the minutes (0-59). # Each LED represents a zero or one, with the least significant bit on the # right. # # For example, the above binary watch reads "3:25". # # Given a non-negative integer n which represents the number of LEDs that are # currently on, return all possible times the watch could represent. # # Example: # Input: n = 1Return: ["1:00", "2:00", "4:00", "8:00", "0:01", "0:02", "0:04", # "0:08", "0:16", "0:32"] # # # Note: # # The order of output does not matter. # The hour must not contain a leading zero, for example "01:00" is not valid, # it should be "1:00". # The minute must be consist of two digits and may contain a leading zero, for # example "10:2" is not valid, it should be "10:02". # # # TIME_MAP = { 0: ["0:00"], 1: ["1:00", "2:00", "4:00", "8:00", "0:01", "0:02", "0:04", "0:08", "0:16", "0:32"], 2: ["0:03","0:05","0:06","0:09","0:10","0:12","0:17","0:18","0:20","0:24","0:33","0:34","0:36","0:40","0:48","1:01","1:02","1:04","1:08","1:16","1:32","2:01","2:02","2:04","2:08","2:16","2:32","3:00","4:01","4:02","4:04","4:08","4:16","4:32","5:00","6:00","8:01","8:02","8:04","8:08","8:16","8:32","9:00","10:00"], 3: ["0:07","0:11","0:13","0:14","0:19","0:21","0:22","0:25","0:26","0:28","0:35","0:37","0:38","0:41","0:42","0:44","0:49","0:50","0:52","0:56","1:03","1:05","1:06","1:09","1:10","1:12","1:17","1:18","1:20","1:24","1:33","1:34","1:36","1:40","1:48","2:03","2:05","2:06","2:09","2:10","2:12","2:17","2:18","2:20","2:24","2:33","2:34","2:36","2:40","2:48","3:01","3:02","3:04","3:08","3:16","3:32","4:03","4:05","4:06","4:09","4:10","4:12","4:17","4:18","4:20","4:24","4:33","4:34","4:36","4:40","4:48","5:01","5:02","5:04","5:08","5:16","5:32","6:01","6:02","6:04","6:08","6:16","6:32","7:00","8:03","8:05","8:06","8:09","8:10","8:12","8:17","8:18","8:20","8:24","8:33","8:34","8:36","8:40","8:48","9:01","9:02","9:04","9:08","9:16","9:32","10:01","10:02","10:04","10:08","10:16","10:32","11:00"], 4: ["0:15","0:23","0:27","0:29","0:30","0:39","0:43","0:45","0:46","0:51","0:53","0:54","0:57","0:58","1:07","1:11","1:13","1:14","1:19","1:21","1:22","1:25","1:26","1:28","1:35","1:37","1:38","1:41","1:42","1:44","1:49","1:50","1:52","1:56","2:07","2:11","2:13","2:14","2:19","2:21","2:22","2:25","2:26","2:28","2:35","2:37","2:38","2:41","2:42","2:44","2:49","2:50","2:52","2:56","3:03","3:05","3:06","3:09","3:10","3:12","3:17","3:18","3:20","3:24","3:33","3:34","3:36","3:40","3:48","4:07","4:11","4:13","4:14","4:19","4:21","4:22","4:25","4:26","4:28","4:35","4:37","4:38","4:41","4:42","4:44","4:49","4:50","4:52","4:56","5:03","5:05","5:06","5:09","5:10","5:12","5:17","5:18","5:20","5:24","5:33","5:34","5:36","5:40","5:48","6:03","6:05","6:06","6:09","6:10","6:12","6:17","6:18","6:20","6:24","6:33","6:34","6:36","6:40","6:48","7:01","7:02","7:04","7:08","7:16","7:32","8:07","8:11","8:13","8:14","8:19","8:21","8:22","8:25","8:26","8:28","8:35","8:37","8:38","8:41","8:42","8:44","8:49","8:50","8:52","8:56","9:03","9:05","9:06","9:09","9:10","9:12","9:17","9:18","9:20","9:24","9:33","9:34","9:36","9:40","9:48","10:03","10:05","10:06","10:09","10:10","10:12","10:17","10:18","10:20","10:24","10:33","10:34","10:36","10:40","10:48","11:01","11:02","11:04","11:08","11:16","11:32"], 5: ["0:31","0:47","0:55","0:59","1:15","1:23","1:27","1:29","1:30","1:39","1:43","1:45","1:46","1:51","1:53","1:54","1:57","1:58","2:15","2:23","2:27","2:29","2:30","2:39","2:43","2:45","2:46","2:51","2:53","2:54","2:57","2:58","3:07","3:11","3:13","3:14","3:19","3:21","3:22","3:25","3:26","3:28","3:35","3:37","3:38","3:41","3:42","3:44","3:49","3:50","3:52","3:56","4:15","4:23","4:27","4:29","4:30","4:39","4:43","4:45","4:46","4:51","4:53","4:54","4:57","4:58","5:07","5:11","5:13","5:14","5:19","5:21","5:22","5:25","5:26","5:28","5:35","5:37","5:38","5:41","5:42","5:44","5:49","5:50","5:52","5:56","6:07","6:11","6:13","6:14","6:19","6:21","6:22","6:25","6:26","6:28","6:35","6:37","6:38","6:41","6:42","6:44","6:49","6:50","6:52","6:56","7:03","7:05","7:06","7:09","7:10","7:12","7:17","7:18","7:20","7:24","7:33","7:34","7:36","7:40","7:48","8:15","8:23","8:27","8:29","8:30","8:39","8:43","8:45","8:46","8:51","8:53","8:54","8:57","8:58","9:07","9:11","9:13","9:14","9:19","9:21","9:22","9:25","9:26","9:28","9:35","9:37","9:38","9:41","9:42","9:44","9:49","9:50","9:52","9:56","10:07","10:11","10:13","10:14","10:19","10:21","10:22","10:25","10:26","10:28","10:35","10:37","10:38","10:41","10:42","10:44","10:49","10:50","10:52","10:56","11:03","11:05","11:06","11:09","11:10","11:12","11:17","11:18","11:20","11:24","11:33","11:34","11:36","11:40","11:48"], 6: ["1:31","1:47","1:55","1:59","2:31","2:47","2:55","2:59","3:15","3:23","3:27","3:29","3:30","3:39","3:43","3:45","3:46","3:51","3:53","3:54","3:57","3:58","4:31","4:47","4:55","4:59","5:15","5:23","5:27","5:29","5:30","5:39","5:43","5:45","5:46","5:51","5:53","5:54","5:57","5:58","6:15","6:23","6:27","6:29","6:30","6:39","6:43","6:45","6:46","6:51","6:53","6:54","6:57","6:58","7:07","7:11","7:13","7:14","7:19","7:21","7:22","7:25","7:26","7:28","7:35","7:37","7:38","7:41","7:42","7:44","7:49","7:50","7:52","7:56","8:31","8:47","8:55","8:59","9:15","9:23","9:27","9:29","9:30","9:39","9:43","9:45","9:46","9:51","9:53","9:54","9:57","9:58","10:15","10:23","10:27","10:29","10:30","10:39","10:43","10:45","10:46","10:51","10:53","10:54","10:57","10:58","11:07","11:11","11:13","11:14","11:19","11:21","11:22","11:25","11:26","11:28","11:35","11:37","11:38","11:41","11:42","11:44","11:49","11:50","11:52","11:56"], 7: ["3:31","3:47","3:55","3:59","5:31","5:47","5:55","5:59","6:31","6:47","6:55","6:59","7:15","7:23","7:27","7:29","7:30","7:39","7:43","7:45","7:46","7:51","7:53","7:54","7:57","7:58","9:31","9:47","9:55","9:59","10:31","10:47","10:55","10:59","11:15","11:23","11:27","11:29","11:30","11:39","11:43","11:45","11:46","11:51","11:53","11:54","11:57","11:58"], 8: ["7:31","7:47","7:55","7:59","11:31","11:47","11:55","11:59"], 9: [], 10: ["0:00"], } class Solution(object): def readBinaryWatch(self, num): """ :type num: int :rtype: List[str] """ return TIME_MAP.get(num, [])

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py

Python

model_free/Actor_Critic/a3c.py

sherlockHSY/Reinforcement_learning_with_pytorch

90c4f302b588bbf8be7962aaaa7f61c0234fb8d9

[ "MIT" ]

6

2021-11-15T05:32:36.000Z

2022-03-22T08:38:07.000Z

model_free/Actor_Critic/a3c.py

sherlockHSY/Reinforcement_learning_with_pytorch

90c4f302b588bbf8be7962aaaa7f61c0234fb8d9

[ "MIT" ]

null

model_free/Actor_Critic/a3c.py

sherlockHSY/Reinforcement_learning_with_pytorch

90c4f302b588bbf8be7962aaaa7f61c0234fb8d9

[ "MIT" ]

null

"""to do"""

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py

Python

github_test.py

spiolynn/github_test

ab170afe0fa5eeaa1edd4393f2c4dd1f877f11ef

[ "MIT" ]

null

github_test.py

spiolynn/github_test

ab170afe0fa5eeaa1edd4393f2c4dd1f877f11ef

[ "MIT" ]

null

github_test.py

spiolynn/github_test

ab170afe0fa5eeaa1edd4393f2c4dd1f877f11ef

[ "MIT" ]

null

import os print('this is my first github project')

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6e437fc8920f7c43b17e97ff74b18337f113493a

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py

Python

python/combilelist.py

waytai/open

00fc6891a8fe8e7dc84067ebea8e69895e14e912

[ "BSD-2-Clause" ]

null

python/combilelist.py

waytai/open

00fc6891a8fe8e7dc84067ebea8e69895e14e912

[ "BSD-2-Clause" ]

null

python/combilelist.py

waytai/open

00fc6891a8fe8e7dc84067ebea8e69895e14e912

[ "BSD-2-Clause" ]

null

#两个列表[1,5,7,9]和[2,2,6,8]合并为[1,2,2,3,6,7,8,9] a = [1,5,7,9] b = [3] a.extend(b) print(a)

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2836c5e1628968b8cb8cb9940f6114523b42742d

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py

Python

contrib/pylightning/lightning/__init__.py

mosqueiro/lightning

793a25a0e5ee0c3c80d1403d556a4a013ee233fd

[ "MIT" ]

1

2021-07-25T11:39:24.000Z

contrib/pylightning/lightning/__init__.py

mosqueiro/lightning

793a25a0e5ee0c3c80d1403d556a4a013ee233fd

[ "MIT" ]

null

contrib/pylightning/lightning/__init__.py

mosqueiro/lightning

793a25a0e5ee0c3c80d1403d556a4a013ee233fd

[ "MIT" ]

1

2021-03-26T13:28:40.000Z

from pyln.client import LightningRpc, RpcError, Millisatoshi, __version__, Plugin, monkey_patch

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py

Python

clustering_benchmark/__init__.py

yjxiong/clustering-benchmark

7c040a3fac264b13a64a0c8d8e1cbdec79777bc6

[ "MIT" ]

1

2021-07-02T11:07:18.000Z

clustering_benchmark/__init__.py

yjxiong/clustering-benchmark

7c040a3fac264b13a64a0c8d8e1cbdec79777bc6

[ "MIT" ]

null

clustering_benchmark/__init__.py

yjxiong/clustering-benchmark

7c040a3fac264b13a64a0c8d8e1cbdec79777bc6

[ "MIT" ]

null

from .benchmark import ClusteringBenchmark

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5

285c132f7ae7409ae1bef9d3f50e7a9837786110

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py

Python

doc/groktut/a_second_view/src/sample/app.py

zopefoundation/groktoolkit

6d295997510139b0588b2401d5f54fca8234a15e

[ "ZPL-2.1" ]

2

2015-12-05T05:46:55.000Z

2017-07-03T17:39:32.000Z

doc/groktut/a_second_view/src/sample/app.py

zopefoundation/groktoolkit

6d295997510139b0588b2401d5f54fca8234a15e

[ "ZPL-2.1" ]

7

2017-07-06T15:07:31.000Z

2021-04-20T14:38:21.000Z

doc/groktut/a_second_view/src/sample/app.py

zopefoundation/groktoolkit

6d295997510139b0588b2401d5f54fca8234a15e

[ "ZPL-2.1" ]

2

2016-03-20T18:03:15.000Z

2018-01-11T04:33:40.000Z

import grok class Sample(grok.Application, grok.Container): pass class Index(grok.View): pass class Bye(grok.View): pass

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5

285e0441deca05fdbdf515eda39508df9ec31a6b

59

py

Python

mamba/component/mamba_tmtc/__init__.py

ismaelJimenez/mamba_server

e6e2343291a0df24f226bde0d13e5bfa74cc3650

[ "MIT" ]

null

mamba/component/mamba_tmtc/__init__.py

ismaelJimenez/mamba_server

e6e2343291a0df24f226bde0d13e5bfa74cc3650

[ "MIT" ]

null

mamba/component/mamba_tmtc/__init__.py

ismaelJimenez/mamba_server

e6e2343291a0df24f226bde0d13e5bfa74cc3650

[ "MIT" ]

null

from .tcp_single_port_server import TcpSingleSocketServer

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0

5

2889992ee854c7b07389e5efaa3e1e2aa38e326c

3,896

py

Python

test/test_turistas_entrantes_aena_controller.py

SergioCMDev/Busines-Inteligence-applied-to-tourism

61834a46fce22453e94b7bbdf8d4ecdcf128285a

[ "Apache-2.0" ]

null

test/test_turistas_entrantes_aena_controller.py

SergioCMDev/Busines-Inteligence-applied-to-tourism

61834a46fce22453e94b7bbdf8d4ecdcf128285a

[ "Apache-2.0" ]

null

test/test_turistas_entrantes_aena_controller.py

SergioCMDev/Busines-Inteligence-applied-to-tourism

61834a46fce22453e94b7bbdf8d4ecdcf128285a

[ "Apache-2.0" ]

null

# coding: utf-8 from __future__ import absolute_import from . import BaseTestCase from six import BytesIO from flask import json class TestTuristasEntrantesAenaController(BaseTestCase): """ TuristasEntrantesAenaController integration test stubs """ def test_obtener_cantidad_ciudad_rango_anios(self): """ Test case for obtener_cantidad_ciudad_rango_anios Obtiene la cantidad de personas que van hacia una ciudad durante un rango de años """ query_string = [('CiudadDestino', 'Valencia'), ('AnioInicio', 2009), ('AnioFin', 2015)] response = self.client.open('/server/Aena/TuristasEntrantes/ObtenerCantidadCiudadRangoAnios/{PaisDestino}'.format(PaisDestino='PaisDestino_example'), method='GET', query_string=query_string) self.assert200(response, "Response body is : " + response.data.decode('utf-8')) def test_obtener_cantidad_entrantes_rango_anios(self): """ Test case for obtener_cantidad_entrantes_rango_anios Dado un pais destino obtiene la cantidad de personas que viajan hacia el organizado por años """ query_string = [('AnioInicio', 2009), ('AnioFin', 2015)] response = self.client.open('/server/Aena/TuristasEntrantes/ObtenerCantidadEntrantesRangoAnios/{PaisDestino}'.format(PaisDestino='PaisDestino_example'), method='GET', query_string=query_string) self.assert200(response, "Response body is : " + response.data.decode('utf-8')) def test_obtener_cantidad_origen_rango_anios(self): """ Test case for obtener_cantidad_origen_rango_anios Dado un pais destino obtiene la cantidad de personas que viajan hacia el y sus localizaciones organizado por años """ query_string = [('AnioInicio', 2009), ('AnioFin', 2015)] response = self.client.open('/server/Aena/TuristasEntrantes/ObtenerCantidadOrigenRangoAnios/{PaisDestino}'.format(PaisDestino='PaisDestino_example'), method='GET', query_string=query_string) self.assert200(response, "Response body is : " + response.data.decode('utf-8')) def test_obtener_cantidad_origen_rango_anios_meses(self): """ Test case for obtener_cantidad_origen_rango_anios_meses Dado un pais destino obtiene la cantidad de personas que viajan hacia el y sus localizaciones organizado por años y meses """ query_string = [('AnioInicio', 2009), ('AnioFin', 2015)] response = self.client.open('/server/Aena/TuristasEntrantes/ObtenerCantidadOrigenRangoAniosMeses/{PaisDestino}'.format(PaisDestino='PaisDestino_example'), method='GET', query_string=query_string) self.assert200(response, "Response body is : " + response.data.decode('utf-8')) def test_obtener_cantidad_rango_anios_meses(self): """ Test case for obtener_cantidad_rango_anios_meses Dado un pais destino obtiene la cantidad de personas que viajan hacia el organizado por años y meses """ query_string = [('AnioInicio', 2009), ('AnioFin', 2015)] response = self.client.open('/server/Aena/TuristasEntrantes/ObtenerCantidadRangoAniosMeses/{PaisDestino}'.format(PaisDestino='PaisDestino_example'), method='GET', query_string=query_string) self.assert200(response, "Response body is : " + response.data.decode('utf-8')) if __name__ == '__main__': import unittest unittest.main()

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null

0

1

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null

0

5

955683e2938a01b26ba923e051f56854e6b365a8

36

py

Python

tests/__init__.py

rec/dedupe

315bc8f6859e284f95ea3b6cb06564508ca8006d

[ "MIT" ]

2

2019-05-26T15:09:38.000Z

2019-06-15T10:18:44.000Z

tests/__init__.py

rec/dedupe

315bc8f6859e284f95ea3b6cb06564508ca8006d

[ "MIT" ]

null

tests/__init__.py

rec/dedupe

315bc8f6859e284f95ea3b6cb06564508ca8006d

[ "MIT" ]

null

"""Unit test package for dedupe."""

18

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4.8

1

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36

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null

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0

null

0

null

1

null

true

0

null

1

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null

0

1

0

1

0

null

0

1

0

5

9567beb26c392b4cc1258d8eca19548e71d9a80a

209

py

Python

worksim/team.py

RealLucasMeyer/working_sim

ab9eff09186cd672a1d8a6e4bbef4932eba95d1a

[ "MIT" ]

null

worksim/team.py

RealLucasMeyer/working_sim

ab9eff09186cd672a1d8a6e4bbef4932eba95d1a

[ "MIT" ]

null

worksim/team.py

RealLucasMeyer/working_sim

ab9eff09186cd672a1d8a6e4bbef4932eba95d1a

[ "MIT" ]

null

class Team: def __init__(self): self.workers = [] # list of Worker objects def hire(self, worker): self.workers.append(worker) def fire(self, pos): self.workers.pop(pos)

20.9

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0.598086

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null

0

1

0

1

0

5

958af78eb54d002dacf8556ad6b0393a7d3dc5e8

152

py

Python

semester4/oop/lab1/ukrnet_news/bot/__init__.py

no1sebomb/University-Labs

1da5e7486f0b8a6119c077945aba8c89cdfc2e50

[ "WTFPL" ]

null

semester4/oop/lab1/ukrnet_news/bot/__init__.py

no1sebomb/University-Labs

1da5e7486f0b8a6119c077945aba8c89cdfc2e50

[ "WTFPL" ]

null

semester4/oop/lab1/ukrnet_news/bot/__init__.py

no1sebomb/University-Labs

1da5e7486f0b8a6119c077945aba8c89cdfc2e50

[ "WTFPL" ]

1

2020-11-01T23:54:52.000Z

# coding=utf-8 """ This subpackage defines bot and it's tools used for scraping news """ from .bot import UkrnetNewsBot from .refresh import refresher

19

65

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0

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null

0

1

0

1

0

1

0

5

9599b63092c58d31a4d07b85caebf974af15fc62

29

py

Python

app.py

borisaavedra/twiquest

7d006ce09fd50a1ca971bac502f85208465bb63f

[ "MIT" ]

null

app.py

borisaavedra/twiquest

7d006ce09fd50a1ca971bac502f85208465bb63f

[ "MIT" ]

null

app.py

borisaavedra/twiquest

7d006ce09fd50a1ca971bac502f85208465bb63f

[ "MIT" ]

null

from app import app, api, bom

29

0.758621

6

29

3.666667

0.833333

0

0.172414

29

1

29

0.916667

0

1

0

true

0

1

0

1

0

1

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null

0

1

0

null

0

1

0

1

0

5

c25c17aeb53df4c39deb52c047889eccd67200b7

63

py

Python

armmminng.py

Prasanna-icefire/Army_Surviallence_Droverot

391d85fe3e51a1a15ed14091c6638a5a05e1fe4b

[ "MIT" ]

null

armmminng.py

Prasanna-icefire/Army_Surviallence_Droverot

391d85fe3e51a1a15ed14091c6638a5a05e1fe4b

[ "MIT" ]

null

armmminng.py

Prasanna-icefire/Army_Surviallence_Droverot

391d85fe3e51a1a15ed14091c6638a5a05e1fe4b

[ "MIT" ]

null

import os os.system("python socking.py & python armcontrol.py")

31.5

53

0.777778

10

63

4.9

0.7

0

0.095238

63

2

53

31.5

0.859649

0

0.625

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

c2a85d47de5d0dbb9b92b7e775dd1800badead83

44

py

Python

tests/test_storage_meta.py

nicoddemus/aioworkers

4ab85064844dc28141833d1348989d8c891f3d7d

[ "Apache-2.0" ]

45

2017-04-26T23:50:30.000Z

2021-12-29T03:21:06.000Z

tests/test_storage_meta.py

nicoddemus/aioworkers

4ab85064844dc28141833d1348989d8c891f3d7d

[ "Apache-2.0" ]

63

2017-08-01T10:35:45.000Z

2022-03-01T18:07:49.000Z

tests/test_storage_meta.py

nicoddemus/aioworkers

4ab85064844dc28141833d1348989d8c891f3d7d

[ "Apache-2.0" ]

6

2017-10-19T08:21:23.000Z

2021-12-29T03:25:32.000Z

from aioworkers.storage import meta # noqa

22

43

0.795455

6

44

5.833333

1

0

0.159091

44

1

44

0.945946

0.090909

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

c2e7141f142bc89da35623e377a16bf6d173c823

66

py

Python

software/reach_master/build/lib.linux-x86_64-2.7/reachmaster/test/test_config.py

luzgool/ReachMaster

e7ef5087fb4e5c55e0b680fc00391f2f8cdc5367

[ "BSD-3-Clause-LBNL" ]

2

2020-09-19T21:04:59.000Z

2021-07-27T15:57:49.000Z

software/reach_master/build/lib.linux-x86_64-2.7/reachmaster/test/test_config.py

luzgool/ReachMaster

e7ef5087fb4e5c55e0b680fc00391f2f8cdc5367

[ "BSD-3-Clause-LBNL" ]

1

2021-02-16T21:53:00.000Z

software/reach_master/build/lib.linux-x86_64-2.7/reachmaster/test/test_config.py

luzgool/ReachMaster

e7ef5087fb4e5c55e0b680fc00391f2f8cdc5367

[ "BSD-3-Clause-LBNL" ]

4

2020-02-08T22:41:35.000Z

2021-09-10T20:33:00.000Z

import unittest2 from .. import config print("config imported!")

16.5

26

0.757576

8

66

6.25

0.75

0

0.017544

0.136364

66

4

26

16.5

0.859649

0

0.238806

0

1

0

true

0

1

0

1

0.333333

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

c2ff62baa7debdfc358167d65e82b68fa6a1b77a

909

py

Python

functionblocks/blockgen.py

BookOwl/functionblocks

611b34c527b392f1338660f515e5f4a6f719b72d

[ "MIT" ]

4

2016-04-05T16:24:50.000Z

2021-05-08T00:07:38.000Z

functionblocks/blockgen.py

BookOwl/functionblocks

611b34c527b392f1338660f515e5f4a6f719b72d

[ "MIT" ]

2

2016-04-05T15:40:00.000Z

2020-02-12T23:05:48.000Z

functionblocks/blockgen.py

BookOwl/functionblocks

611b34c527b392f1338660f515e5f4a6f719b72d

[ "MIT" ]

null

# blockgen.py # Functions for generating Scratch JSON def procedure(name, args, atomic, body): argnames, argtypes = zip(*args) return [0, 0, [["procDef", name + " " + " ".join(argtypes), list(argnames), [""]*len(argnames), atomic], body]] def getparam(name): return ["getparam", name, "r"] def listappend(listname, val): return ["append:toList:", val, listname] def join(val1, val2): return ["concatenate:with:", val1, val2] def setvar(varname, value): return ["setVar:to:", varname, value] def add(arg1, arg2): return ["+", arg1, arg2] def sub(arg1, arg2): return ["-", arg1, arg2] def mul(arg1, arg2): return ["*", arg1, arg2] def div(arg1, arg2): return ["\/", arg1, arg2] def eq(arg1, arg2): return ["=", arg1, arg2] def gt(arg1, arg2): return [">", arg1, arg2] def join(arg1, arg2): return ["concatenate:with:", arg1, arg2]

28.40625

102

0.60286

115

909

4.765217

0.391304

0.20438

0.178832

0.19708

0.273723

0

0.047157

0.206821

909

31

103

29.322581

0.712899

0.053905

0

0.096963

0

1

0.444444

false

0

0.407407

0.888889

0

null

1

0

1

0

null

0

1

0

1

0

5

6c171b7e5ebd515548dbf4e757117791325eafcb

64

py

Python

src/config/__init__.py

thijsmie/tantalus

6e9777068f9c8ef7f74dc77f1ce4c44dbf682015

[ "MIT" ]

3

2017-09-13T12:21:41.000Z

2021-03-22T16:44:17.000Z

src/config/__init__.py

thijsmie/tantalus

6e9777068f9c8ef7f74dc77f1ce4c44dbf682015

[ "MIT" ]

12

2017-09-18T09:27:37.000Z

2021-12-16T09:46:36.000Z

src/config/__init__.py

thijsmie/tantalus

6e9777068f9c8ef7f74dc77f1ce4c44dbf682015

[ "MIT" ]

1

2017-10-20T15:18:01.000Z

from .mutable import config from .static import get_flask_config

32

36

0.859375

10

64

5.3

0.7

0

0.109375

64

2

36

32

0.929825

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

6c3007831236dc8898a444f2e13beb214a1cb012

250

py

Python

tests/data_context/fixtures/plugins/my_custom_v3_api_datasource.py

victorcouste/great_expectations

9ee46d83feb87e13c769e2ae35b899b3f18d73a4

[ "Apache-2.0" ]

6,451

2017-09-11T16:32:53.000Z

2022-03-31T23:27:49.000Z

tests/data_context/fixtures/plugins/my_custom_v3_api_datasource.py

victorcouste/great_expectations

9ee46d83feb87e13c769e2ae35b899b3f18d73a4

[ "Apache-2.0" ]

3,892

2017-09-08T18:57:50.000Z

2022-03-31T23:15:20.000Z

tests/data_context/fixtures/plugins/my_custom_v3_api_datasource.py

victorcouste/great_expectations

9ee46d83feb87e13c769e2ae35b899b3f18d73a4

[ "Apache-2.0" ]

1,023

2017-09-08T15:22:05.000Z

2022-03-31T21:17:08.000Z

from great_expectations.datasource import Datasource class MyCustomV3ApiDatasource(Datasource): """ This class is used only for testing. E.g. ensuring appropriate usage stats messaging when using plugin functionality. """ pass

22.727273

84

0.748

28

250

6.642857

0.892857

0

0.004975

0.196

250

10

85

25

0.920398

0.468

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

null

0

1

0

1

0

5

6c3076e49d5d6a6bbf49facaa8dcfd24b921c809

20

py

Python

tict/__init__.py

glaslos/tict

d1aaef41946428d1bcf4dc29a64e693f4f5a1412

[ "MIT" ]

null

tict/__init__.py

glaslos/tict

d1aaef41946428d1bcf4dc29a64e693f4f5a1412

[ "MIT" ]

1

2016-10-09T12:09:01.000Z

2016-10-09T18:29:41.000Z

tict/__init__.py

glaslos/tict

d1aaef41946428d1bcf4dc29a64e693f4f5a1412

[ "MIT" ]

null

from .tict import *

10

19

0.7

3

20

4.666667

1

0

0.2

20

1

20

0.875

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

6c36fdba6d0297baa1cee72fa746a98679446d8a

4,942

py

Python

cv/resume/migrations/0001_initial.py

Trianglium/artist-cv

5a742a3998ba8778b2b6ddde2c3f88ff3cc85124

[ "MIT" ]

2

2022-01-29T00:45:58.000Z

2022-01-30T22:05:18.000Z

cv/resume/migrations/0001_initial.py

Trianglium/artist-cv

5a742a3998ba8778b2b6ddde2c3f88ff3cc85124

[ "MIT" ]

14

2022-01-30T17:58:46.000Z

2022-02-23T14:42:10.000Z

cv/resume/migrations/0001_initial.py

Trianglium/artist-cv

5a742a3998ba8778b2b6ddde2c3f88ff3cc85124

[ "MIT" ]

null

# Generated by Django 4.0.1 on 2022-02-18 01:33 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations = [ migrations.CreateModel( name='Educational', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('institution', models.CharField(max_length=155, null=True)), ('start_date', models.DateTimeField(auto_now=True)), ('end_date', models.DateTimeField(auto_now=True)), ('overview', models.TextField(null=True)), ('highlights', models.TextField(null=True)), ('location', models.TextField(null=True)), ('credential', models.CharField(max_length=255, null=True)), ('secondary_credentials', models.TextField(max_length=500, null=True)), ('url', models.URLField(max_length=500, null=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Interpersonal', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(help_text='What do you call this skill? What do you type in to google, to find information about this skill?', max_length=155, null=True)), ('proficiency_level', models.CharField(choices=[('N', 'Novice'), ('P', 'Proficient'), ('E', 'Expert')], default='P', help_text="This field will NOT be public. It's solely for sorting skills (desc) from most proficient to least proficient as to emphasize the skills that you are most comfortable interviewing in.", max_length=1)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Professional', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('institution', models.CharField(max_length=155, null=True)), ('start_date', models.DateTimeField(auto_now=True)), ('end_date', models.DateTimeField(auto_now=True)), ('overview', models.TextField(null=True)), ('highlights', models.TextField(null=True)), ('location', models.TextField(null=True)), ('title', models.CharField(max_length=255)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Technical', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(help_text='What do you call this skill? What do you type in to google, to find information about this skill?', max_length=155, null=True)), ('proficiency_level', models.CharField(choices=[('N', 'Novice'), ('P', 'Proficient'), ('E', 'Expert')], default='P', help_text="This field will NOT be public. It's solely for sorting skills (desc) from most proficient to least proficient as to emphasize the skills that you are most comfortable interviewing in.", max_length=1)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Volunteer', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('institution', models.CharField(max_length=155, null=True)), ('start_date', models.DateTimeField(auto_now=True)), ('end_date', models.DateTimeField(auto_now=True)), ('overview', models.TextField(null=True)), ('highlights', models.TextField(null=True)), ('location', models.TextField(null=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='ProfessionalProfile', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('objective', models.TextField(null=True)), ('resume_summary', models.TextField(null=True)), ('public_email', models.TextField(null=True)), ('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='resume', to=settings.AUTH_USER_MODEL)), ], ), ]

49.919192

345

0.577904

505

4,942

5.542574

0.253465

0.057163

0.081458

0.098607

0.780279

0.749553

0.733476

0.698464

0

0.012482

0.286726

4,942

98

346

50.428571

0.78156

0.009106

0

0.681319

1

0.043956

0.212462

0.00429

0

1

0

false

0

0.032967

0

0.076923

0

null

0

1

0

1

0

1

0

null

0

5

6c626d01b0f4734bf13e4d15ae1cccdeb917508d

51

py

Python

py/src/PL/chunks/__init__.py

jdstmporter/midifiles

4149f8d59d1279f282c4c617a107adcf06abd89b

[ "MIT" ]

4

2021-05-10T22:43:08.000Z

2021-09-21T05:48:59.000Z

py/src/PL/chunks/__init__.py

jdstmporter/midifiles

4149f8d59d1279f282c4c617a107adcf06abd89b

[ "MIT" ]

3

2021-07-29T22:06:41.000Z

2021-09-29T01:52:10.000Z

py/src/PL/chunks/__init__.py

jdstmporter/midifiles

4149f8d59d1279f282c4c617a107adcf06abd89b

[ "MIT" ]

1

2021-09-29T00:36:26.000Z

from .track import Track from .header import Header

25.5

26

0.823529

8

51

5.25

0.5

0

0.137255

51

2

26

25.5

0.954545

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

6c652822f801493365898655fe1fc5c5c87c54b4

412

py

Python

2020-06-month-long-challenge/day08.py

jkbockstael/leetcode

8ef5c907fb153c37dc97f6524493ceca2044ea38

[ "Unlicense" ]

null

2020-06-month-long-challenge/day08.py

jkbockstael/leetcode

8ef5c907fb153c37dc97f6524493ceca2044ea38

[ "Unlicense" ]

null

2020-06-month-long-challenge/day08.py

jkbockstael/leetcode

8ef5c907fb153c37dc97f6524493ceca2044ea38

[ "Unlicense" ]

null

#!/usr/bin/env python3 # Day 8: Power of Two # # Given an integer, write a function to determine if it is a power of two. class Solution: def isPowerOfTwo(self, n: int) -> bool: return n > 0 and (n & (n - 1)) == 0 # Tests assert Solution().isPowerOfTwo(1) == True assert Solution().isPowerOfTwo(16) == True assert Solution().isPowerOfTwo(218) == False assert Solution().isPowerOfTwo(-16) == False

25.75

74

0.669903

61

412

4.52459

0.622951

0.202899

0.376812

0.217391

0

0.038922

0.18932

412

15

75

27.466667

0.787425

0.291262

0

0.571429

1

0.142857

false

0

0.142857

0.428571

0

null

1

0

null

0

1

0

1

0

5

6666c8c365c462513b64714c2de6b4cfbef148d5

272

py

Python

src/environement/TexasHoldemLimit/strategy/all_strategy.py

noeRls/opponent-exploitation

989217afffcca7b13d6bb177bbca59f42e308a25

[ "MIT" ]

null

src/environement/TexasHoldemLimit/strategy/all_strategy.py

noeRls/opponent-exploitation

989217afffcca7b13d6bb177bbca59f42e308a25

[ "MIT" ]

null

src/environement/TexasHoldemLimit/strategy/all_strategy.py

noeRls/opponent-exploitation

989217afffcca7b13d6bb177bbca59f42e308a25

[ "MIT" ]

1

2021-10-20T17:28:19.000Z

from src.environement.strategys.random import RandomStrategy from src.environement.strategys.equilibrium import EquilibriumStrategy from ...Strategy import Strategy from typing import List ALL_TEXAS_HOLDEM_STRATEGY: List[Strategy] = [EquilibriumStrategy, RandomStrategy]

38.857143

81

0.860294

30

272

7.7

0.5

0.060606

0.164502

0.242424

0

0.080882

272

6

82

45.333333

0.924

0

1

0

true

0

0.8

0

0.8

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

5

66e1eaace01219ee8fec34ab6094fcdc18aebb4b

53

py

Python

main.py

Loniks/AntiVirus

693e4c930d6011f23e1011b034ceecdf609b1259

[ "MIT" ]

null

main.py

Loniks/AntiVirus

693e4c930d6011f23e1011b034ceecdf609b1259

[ "MIT" ]

null

main.py

Loniks/AntiVirus

693e4c930d6011f23e1011b034ceecdf609b1259

[ "MIT" ]

1

2021-06-19T14:03:56.000Z

from antivirus.ml import build_model build_model()

10.6

36

0.811321

8

53

5.125

0.75

0.487805

0

0.132075

53

4

37

13.25

0.891304

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

66ea13ae6bdece3a51734719ff08996b0b9a4fb1

334

py

Python

entsoe_client/Parsers/Entsoe_Document_Parser.py

DarioHett/entsoe-client

bb424fa54966d3be49daa1edb9e0fd40ed00ac15

[ "MIT" ]

1

2021-10-03T18:11:57.000Z

entsoe_client/Parsers/Entsoe_Document_Parser.py

DarioHett/entsoe-client

bb424fa54966d3be49daa1edb9e0fd40ed00ac15

[ "MIT" ]

1

2021-11-08T16:54:10.000Z

entsoe_client/Parsers/Entsoe_Document_Parser.py

DarioHett/entsoe-client

bb424fa54966d3be49daa1edb9e0fd40ed00ac15

[ "MIT" ]

1

2021-12-04T21:24:53.000Z

from abc import ABC, abstractmethod class Entsoe_Document_Parser(ABC): def __init__(self): self.objectified_input_xml = None def set_objectified_input_xml(self, objectified_input_xml): self.objectified_input_xml = objectified_input_xml @classmethod @abstractmethod def parse(cls): pass

22.266667

63

0.727545

40

334

5.65

0.5

0.353982

0.420354

0.30531

0.287611

0

0.212575

334

14

64

23.857143

0.859316

0

1

0.3

false

0.1

0

0.5

0

null

1

0

null

0

1

0

1

0

5

dd03ddc466daadc0943f0872e311bb0c8b53b0f5

250

py

Python

printer.py

oliver-cloud/SudokuSolver

65e9c26c36faf910f1bd97a2f712ccfa3265f1ee

[ "MIT" ]

null

printer.py

oliver-cloud/SudokuSolver

65e9c26c36faf910f1bd97a2f712ccfa3265f1ee

[ "MIT" ]

null

printer.py

oliver-cloud/SudokuSolver

65e9c26c36faf910f1bd97a2f712ccfa3265f1ee

[ "MIT" ]

null

def sudoku_printer(array): for i in range(len(array)): #print(i % 3 == 2) if (i % 3) != 0 or i == 0: print("%s %s %s|%s %s %s|%s %s %s|" % tuple(array[i])) else: print("-" * 18) print("%s %s %s|%s %s %s|%s %s %s|" % tuple(array[i]))

25

57

0.476

50

250

2.36

0.38

0.271186

0.355932

0.40678

0.423729

0

0.036842

0.24

250

9

58

27.777778

0.584211

0.068

0

0.285714

0

0.237069

0

1

0.142857

false

0

0.142857

0.571429

0

null

1

0

1

0

null

0

1

0

5

dd5fc3129ee9d7c4db289fe408d2aeb7c54f3445

276

py

Python

src/StduyTest/study_keras_cnn.py

hello-sea/DeepLearning_ObjectDetection

8d0c10921917032d57a0157c874e86b18a755a41

[ "MIT" ]

25

2019-04-05T01:22:53.000Z

2021-11-07T13:38:21.000Z

src/StduyTest/study_keras_cnn.py

hello-sea/DeepLearning_ObjectRecognition

8d0c10921917032d57a0157c874e86b18a755a41

[ "MIT" ]

1

2019-09-22T13:35:33.000Z

2021-11-01T03:42:54.000Z

src/StduyTest/study_keras_cnn.py

hello-sea/DeepLearning_ObjectDetection

8d0c10921917032d57a0157c874e86b18a755a41

[ "MIT" ]

9

2019-05-05T02:44:51.000Z

2020-10-27T08:19:22.000Z

# -*- coding: utf-8 -*- from keras.datasets import mnist from keras.models import Sequential from keras.layers import Dense, Dropout, Activation, Flatten from keras.layers import Convolution2D, MaxPooling2D from keras.utils import np_utils from keras import backend as K

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5

dd89a11acb088e569e91bfd91c849fee1edbf38c

12,679

py

Python

weather_forecast/weathercrawl1.py

smcoder123/Web_crawler-without-the-use-of-browser-automation-

e2b01c0755de0f44a02aa48dd51c06b8ff639836

[ "MIT" ]

null

weather_forecast/weathercrawl1.py

smcoder123/Web_crawler-without-the-use-of-browser-automation-

e2b01c0755de0f44a02aa48dd51c06b8ff639836

[ "MIT" ]

null

weather_forecast/weathercrawl1.py

smcoder123/Web_crawler-without-the-use-of-browser-automation-

e2b01c0755de0f44a02aa48dd51c06b8ff639836

[ "MIT" ]

null

#!/usr/bin/env python from bs4 import BeautifulSoup import requests from datetime import date import pandas as pd url = 'https://weather.com/en-IN/' api_key="d522aa97197fd864d36b418f39ebb323" #obtained from the source code itself. date_def= date.today() #default date choice_def="today" #default type of forecast place=input("Enter place in details ie place:") date=input("Enter date in yyyy-mm-dd :") print("Enter type of forecast you want :") print("1.Today") print("2.Hourly") print("2.5-day") print("3.10-day") print("4.Weekend") choice=input("Enter the type of weather forecasting : ") if date=="": date=date_def if choice=="": choice=choice_def if choice=="Today" or choice=="today": choice_enter=choice elif choice=="Hourly" or choice=="hourly": choice_entered=choice elif choice=="5-day" or choice=="5 day": choice_entered=choice elif choice=="10-day" or choice=="10 day": choice_entered=choice elif choice=="Weekend" or choice=="weekend": choice_entered=choice elif choice=="Monthly" or choice=="monthly": choice_entered=choice #obtaining the coordinates of the place rr= requests.get("https://api.weather.com/v3/location/search?query="+ str(place)+"&locationType=city&language=en-IN&format=json&apiKey="+api_key) info_place=rr.json() def today(info): print("The current weather of " + str(info_place["location"]["address"][0]) + " is :-") print(" Co-ordinate - latitude :" + str(info_place["location"]["latitude"][0])+ " longitude :" + str(info_place["location"]["longitude"][0])) print(" Temperature :" + str(info["vt1observation"]["temperature"])+" deg C " +str(info["vt1observation"]["phrase"])+ " as of "+str(info["vt1observation"]["observationTime"])) print(" Feels like "+str(info["vt1observation"]["feelsLike"]) + " deg C" ) print(" Dew point :"+str(info["vt1observation"]["dewPoint"])+ " deg") print(" Humidity :" +str(info["vt1observation"]["humidity"])+" %") print(" UV Index " +str(info["vt1observation"]["uvIndex"]) +" out of 10 which is "+str(info["vt1observation"]["uvDescription"])) print(" Wind :"+ str(info["vt1observation"]["windDirCompass"])+" " + str(info["vt1observation"]["windSpeed"])+ " km/hr") print(" Visibility :"+str(info["vt1observation"]["visibility"])+ " km") print(" Pressure: "+str(info["vt1observation"]["altimeter"])+"mb "+ str(info["vt1observation"]["barometerTrend"])) def day5(info): print("Co-ordinate - latitude :" + str(info_place["location"]["latitude"][0])+ " longitude :" + str(info_place["location"]["longitude"][0])) print("Weather of "+str(info_place["location"]["address"][0])+" for the next 5 days are :-") for i in range(0,5): print(str(i+1)+"- "+info["vt1dailyForecast"]["dayOfWeek"][i]) print(" Description : Day- "+str(info["vt1dailyForecast"]["day"]["phrase"][i])+" ,Night- "+str(info["vt1dailyForecast"]["night"]["phrase"][i])) print(" Temperature : Max- "+str(info["vt1dailyForecast"]["day"]["temperature"][i])+" deg C, Min- "+str(info["vt1dailyForecast"]["night"]["temperature"][i])+ " deg C") print(" Precipitation : Day- "+str(info["vt1dailyForecast"]["day"]["precipPct"][i])+"% " +str(info["vt1dailyForecast"]["day"]["precipType"][i]) + " Night- "+str(info["vt1dailyForecast"]["night"]["precipPct"][i])+"% "+str(info["vt1dailyForecast"]["day"]["precipType"][i])) print(" Wind : Day- "+ str(info["vt1dailyForecast"]["day"]["windDirCompass"][i]) +str(info["vt1dailyForecast"]["day"]["windSpeed"][i])+" km/hr ,Night- "+ str(info["vt1dailyForecast"]["day"]["windDirCompass"][i]) +str(info["vt1dailyForecast"]["night"]["windSpeed"][i])+" km/hr") print(" Humidity : Day- "+str(info["vt1dailyForecast"]["day"]["humidityPct"][i])+" % ,Night- "+str(info["vt1dailyForecast"]["night"]["humidityPct"][i])+" %") print(" UV Index : Day- "+str(info["vt1dailyForecast"]["day"]["uvIndex"][i])+" out of 10 ,Night- "+str(info["vt1dailyForecast"]["night"]["uvIndex"][i])+" out of 10") print(" Sunrise : "+str(info["vt1dailyForecast"]["sunrise"][i])) print(" SunSet : "+str(info["vt1dailyForecast"]["sunset"][i])) print(" Moon Phase : "+str(info["vt1dailyForecast"]["moonPhrase"][i])) print(" Moonrise : "+str(info["vt1dailyForecast"]["moonrise"][i])) print(" MoonSet : "+str(info["vt1dailyForecast"]["moonset"][i])) print(" ") def day10(info): print("Co-ordinate - latitude :" + str(info_place["location"]["latitude"][0])+ " longitude :" + str(info_place["location"]["longitude"][0])) print("Weather of "+str(info_place["location"]["address"][0])+" for the next 10 days are :-") for i in range(0,10): print(str(i+1)+"- "+info["vt1dailyForecast"]["dayOfWeek"][i]) print(" Description : Day- "+str(info["vt1dailyForecast"]["day"]["phrase"][i])+" ,Night- "+str(info["vt1dailyForecast"]["night"]["phrase"][i])) print(" Temperature : Max- "+str(info["vt1dailyForecast"]["day"]["temperature"][i])+" deg C, Min- "+str(info["vt1dailyForecast"]["night"]["temperature"][i])+ " deg C") print(" Precipitation : Day- "+str(info["vt1dailyForecast"]["day"]["precipPct"][i])+"% " +str(info["vt1dailyForecast"]["day"]["precipType"][i]) + " Night- "+str(info["vt1dailyForecast"]["night"]["precipPct"][i])+"% "+str(info["vt1dailyForecast"]["day"]["precipType"][i])) print(" Wind : Day- "+ str(info["vt1dailyForecast"]["day"]["windDirCompass"][i]) +str(info["vt1dailyForecast"]["day"]["windSpeed"][i])+" km/hr ,Night- "+ str(info["vt1dailyForecast"]["day"]["windDirCompass"][i]) +str(info["vt1dailyForecast"]["night"]["windSpeed"][i])+" km/hr") print(" Humidity : Day- "+str(info["vt1dailyForecast"]["day"]["humidityPct"][i])+" % ,Night- "+str(info["vt1dailyForecast"]["night"]["humidityPct"][i])+" %") print(" UV Index : Day- "+str(info["vt1dailyForecast"]["day"]["uvIndex"][i])+" out of 10 ,Night- "+str(info["vt1dailyForecast"]["night"]["uvIndex"][i])+" out of 10") print(" Sunrise : "+str(info["vt1dailyForecast"]["sunrise"][i])) print(" SunSet : "+str(info["vt1dailyForecast"]["sunset"][i])) print(" Moon Phase : "+str(info["vt1dailyForecast"]["moonPhrase"][i])) print(" Moonrise : "+str(info["vt1dailyForecast"]["moonrise"][i])) print(" MoonSet : "+str(info["vt1dailyForecast"]["moonset"][i])) print(" ") def hourbyhour(info): url="https://weather.com/en-IN/weather/hourbyhour/l/"+str(info_place["location"]["placeId"][0]) rr=requests.get(url) soup=BeautifulSoup(rr.text,'html.parser') table=soup.find('table',classname="twc-table") table_rows=table.find_all('tr') h=[''] l =[] for th in soup.find_all('th'): h.append(th.text) for tr in table_rows: td = tr.find_all('td') row = [tr.text for tr in td] l.append(row) l.remove([]) df=pd.DataFrame(data=l,columns=h) print(df) def weekend(info): print("Co-ordinate - latitude :" + str(info_place["location"]["latitude"][0])+ " longitude :" + str(info_place["location"]["longitude"][0])) print("Weather of "+str(info_place["location"]["address"][0])+" for the next 2 weekends are :-") j=0 for i in range(0,15): if info["vt1dailyForecast"]["dayOfWeek"][i]=="Saturday": j+=1 print(str(j)+"- "+ info["vt1dailyForecast"]["dayOfWeek"][i]) print(" Description : Day- "+str(info["vt1dailyForecast"]["day"]["phrase"][i])+" ,Night- "+str(info["vt1dailyForecast"]["night"]["phrase"][i])) print(" Temperature : Max- "+str(info["vt1dailyForecast"]["day"]["temperature"][i])+" deg C, Min- "+str(info["vt1dailyForecast"]["night"]["temperature"][i])+ " deg C") print(" Precipitation : Day- "+str(info["vt1dailyForecast"]["day"]["precipPct"][i])+"% " +str(info["vt1dailyForecast"]["day"]["precipType"][i]) + " Night- "+str(info["vt1dailyForecast"]["night"]["precipPct"][i])+"% "+str(info["vt1dailyForecast"]["day"]["precipType"][i])) print(" Wind : Day- "+ str(info["vt1dailyForecast"]["day"]["windDirCompass"][i]) +str(info["vt1dailyForecast"]["day"]["windSpeed"][i])+" km/hr ,Night- "+ str(info["vt1dailyForecast"]["day"]["windDirCompass"][i]) +str(info["vt1dailyForecast"]["night"]["windSpeed"][i])+" km/hr") print(" Humidity : Day- "+str(info["vt1dailyForecast"]["day"]["humidityPct"][i])+" % ,Night- "+str(info["vt1dailyForecast"]["night"]["humidityPct"][i])+" %") print(" UV Index : Day- "+str(info["vt1dailyForecast"]["day"]["uvIndex"][i])+" out of 10 ,Night- "+str(info["vt1dailyForecast"]["night"]["uvIndex"][i])+" out of 10") print(" Sunrise : "+str(info["vt1dailyForecast"]["sunrise"][i])) print(" SunSet : "+str(info["vt1dailyForecast"]["sunset"][i])) print(" Moon Phase : "+str(info["vt1dailyForecast"]["moonPhrase"][i])) print(" Moonrise : "+str(info["vt1dailyForecast"]["moonrise"][i])) print(" MoonSet : "+str(info["vt1dailyForecast"]["moonset"][i])) print(" ") elif info["vt1dailyForecast"]["dayOfWeek"][i]=="Sunday": j+=1 print(str(j)+"- "+ info["vt1dailyForecast"]["dayOfWeek"][i]) print(" Description : Day- "+str(info["vt1dailyForecast"]["day"]["phrase"][i])+" ,Night- "+str(info["vt1dailyForecast"]["night"]["phrase"][i])) print(" Temperature : Max- "+str(info["vt1dailyForecast"]["day"]["temperature"][i])+" deg C, Min- "+str(info["vt1dailyForecast"]["night"]["temperature"][i])+ " deg C") print(" Precipitation : Day- "+str(info["vt1dailyForecast"]["day"]["precipPct"][i])+"% " +str(info["vt1dailyForecast"]["day"]["precipType"][i]) + " Night- "+str(info["vt1dailyForecast"]["night"]["precipPct"][i])+"% "+str(info["vt1dailyForecast"]["day"]["precipType"][i])) print(" Wind : Day- "+ str(info["vt1dailyForecast"]["day"]["windDirCompass"][i]) +str(info["vt1dailyForecast"]["day"]["windSpeed"][i])+" km/hr ,Night- "+ str(info["vt1dailyForecast"]["day"]["windDirCompass"][i]) +str(info["vt1dailyForecast"]["night"]["windSpeed"][i])+" km/hr") print(" Humidity : Day- "+str(info["vt1dailyForecast"]["day"]["humidityPct"][i])+" % ,Night- "+str(info["vt1dailyForecast"]["night"]["humidityPct"][i])+" %") print(" UV Index : Day- "+str(info["vt1dailyForecast"]["day"]["uvIndex"][i])+" out of 10 ,Night- "+str(info["vt1dailyForecast"]["night"]["uvIndex"][i])+" out of 10") print(" Sunrise : "+str(info["vt1dailyForecast"]["sunrise"][i])) print(" SunSet : "+str(info["vt1dailyForecast"]["sunset"][i])) print(" Moon Phase : "+str(info["vt1dailyForecast"]["moonPhrase"][i])) print(" Moonrise : "+str(info["vt1dailyForecast"]["moonrise"][i])) print(" MoonSet : "+str(info["vt1dailyForecast"]["moonset"][i])) print(" ") if __name__=="__main__": if choice=="Today" or choice=="today": resp= requests.get("https://api.weather.com/v2/turbo/vt1observation?apiKey="+api_key+"&format=json&geocode=" +str(info_place["location"]["latitude"][0]) + "," + str(info_place["location"]["longitude"][0]) + "&language=en-IN&units=m") info=resp.json() today(info) elif choice=='hourly' or choice=='Hourly': hourbyhour(info_place) else : response=requests.get("https://api.weather.com/v2/turbo/vt1dailyForecast?apiKey="+api_key+"&format=json&geocode=" +str(info_place["location"]["latitude"][0]) + "," + str(info_place["location"]["longitude"][0]) + "&language=en-IN&units=m") info=response.json() if choice=="5-day" or choice=="5 day": day5(info) elif choice=="10-day" or choice=="10 day": day10(info) elif choice=="weekend" or choice=="Weekend": weekend(info) #################################################################################################

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5

dd9796696e94a57d14b0367bb290bd171f9f9b29

57

py

Python

utility/__init__.py

Xianchao-Xu/PyFEM

f8341c3aa65ad3230ff8b9a5bafc39e801cd6bc3

[ "MIT" ]

null

utility/__init__.py

Xianchao-Xu/PyFEM

f8341c3aa65ad3230ff8b9a5bafc39e801cd6bc3

[ "MIT" ]

null

utility/__init__.py

Xianchao-Xu/PyFEM

f8341c3aa65ad3230ff8b9a5bafc39e801cd6bc3

[ "MIT" ]

1

2021-12-27T15:29:20.000Z

# coding: utf-8 # author: xuxc from .FileParser import *

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dd99dcb93b342f184ab378acd46a89742e55aaab

14,776

py

Python

bin/fss-exp7-pp.py

ptgrogan/fss-ofs

425d065c18841f27d3465261b5f4abe9a209367d

[ "Apache-2.0" ]

null

bin/fss-exp7-pp.py

ptgrogan/fss-ofs

425d065c18841f27d3465261b5f4abe9a209367d

[ "Apache-2.0" ]

null

bin/fss-exp7-pp.py

ptgrogan/fss-ofs

425d065c18841f27d3465261b5f4abe9a209367d

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ Copyright 2015 Paul T. Grogan Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import csv import re import numpy as np import matplotlib.pyplot as plt id = np.array([]) run = np.array([]) cost = np.array([]) exp_value = np.array([]) min_value = np.array([]) max_value = np.array([]) std_err = np.array([]) oisl = np.array([], dtype=np.bool_) pisl = np.array([], dtype=np.bool_) osgl = np.array([], dtype=np.bool_) players = np.array([]) player = np.array([]) stations = np.array([]) satellites = np.array([]) totalCost = np.array([]) totalExpValue = np.array([]) totalStdErr = np.array([]) with open('data-exp.csv','rb') as csvfile: reader = csv.reader(csvfile, delimiter=',') reader.next() # skip header counter = 0 for row in reader: counter+=1 # if int(row[1])==0 and int(row[2])==1:# and row[3]=='false': run = np.append(run, row[0]) id = np.append(id, counter) players = np.append(players, int(row[1])) player = np.append(player, int(row[2])) satellites = np.append(satellites, int(row[3])) stations = np.append(stations, int(row[4])) pisl = np.append(pisl, 'pISL' in row[0]) oisl = np.append(oisl, 'oISL' in row[0]) osgl = np.append(osgl, 'oSGL' in row[0]) cost = np.append(cost, float(row[6])) min_value = np.append(min_value, float(row[7])) max_value = np.append(max_value, float(row[8])) exp_value = np.append(exp_value, float(row[10])) std_err = np.append(std_err, float(row[12])) totalCost = np.append(totalCost, float(row[13])) totalExpValue = np.append(totalExpValue, float(row[14])) totalStdErr = np.append(totalStdErr, float(row[15])) #exp_value = exp_value - cost #totalExpValue = totalExpValue - totalCost plt.rcParams.update({'axes.labelsize':8, 'font.size':8, 'font.family':'Times New Roman', 'legend.fontsize':8, 'xtick.labelsize':8, 'ytick.labelsize':8}) def pareto(id, cost, exp_value, std_err): p_id = np.array([]) p_cost = np.array([]) p_value = np.array([]) p_exp = np.array([]) for i in range(0,np.size(cost)): if exp_value[i] > 0 and np.sum(np.logical_and(cost<=cost[i], exp_value-1.96*std_err>exp_value[i]+1.96*std_err[i])) == 0: p_id = np.append(p_id, id[i]) p_cost = np.append(p_cost, cost[i]) p_value = np.append(p_value, exp_value[i]) if np.sum(np.logical_and(cost<=cost[i], exp_value>exp_value[i])) == 0: p_exp = np.append(p_exp, True) else: p_exp = np.append(p_exp, False) return p_id, p_cost, p_value, p_exp def tradespaceIndependent(label, id, cost, exp_value, std_err, run, pisl, oisl, osgl): plt.clf() plt.errorbar(cost[np.logical_and.reduce((pisl==False,oisl==False,osgl==False))], exp_value[np.logical_and.reduce((pisl==False,oisl==False,osgl==False))], yerr=1.96*std_err[np.logical_and.reduce((pisl==False,oisl==False,osgl==False))], fmt='none',color='k',ecolor='k', alpha=0.3) plt.errorbar(cost[np.logical_and.reduce((pisl==True,oisl==False,osgl==False))], exp_value[np.logical_and.reduce((pisl==True,oisl==False,osgl==False))], yerr=1.96*std_err[np.logical_and.reduce((pisl==True,oisl==False,osgl==False))], fmt='none',color='b',ecolor='b', alpha=0.3) plt.plot(cost[np.logical_and.reduce((pisl==False,oisl==False,osgl==False))], exp_value[np.logical_and.reduce((pisl==False,oisl==False,osgl==False))], ls='', marker='.',mec='none',color='k', alpha=0.3) plt.plot(cost[np.logical_and.reduce((pisl==True,oisl==False,osgl==False))], exp_value[np.logical_and.reduce((pisl==True,oisl==False,osgl==False))], ls='', marker='.',mec='none',color='b', alpha=0.3) P_id, P_cost, P_value, P_exp = pareto(id, cost, exp_value, std_err) p_id, p_cost, p_value, p_exp = pareto( id[np.logical_and.reduce((pisl==False,oisl==False,osgl==False))], cost[np.logical_and.reduce((pisl==False,oisl==False,osgl==False))], exp_value[np.logical_and.reduce((pisl==False,oisl==False,osgl==False))], std_err[np.logical_and.reduce((pisl==False,oisl==False,osgl==False))]) #plt.plot(p_cost[p_exp==True],p_value[p_exp==True],'.-k', alpha=0.3) for i in np.intersect1d(P_id[P_exp==True],p_id[p_exp==True]): plt.annotate('%0d'%i, xy=(p_cost[p_id==i], p_value[p_id==i]), xytext=(-5,4), textcoords='offset points', size=8, color='k') p_id, p_cost, p_value, p_exp = pareto( id[np.logical_and.reduce((pisl==True,oisl==False,osgl==False))], cost[np.logical_and.reduce((pisl==True,oisl==False,osgl==False))], exp_value[np.logical_and.reduce((pisl==True,oisl==False,osgl==False))], std_err[np.logical_and.reduce((pisl==True,oisl==False,osgl==False))]) #plt.plot(p_cost[p_exp==True],p_value[p_exp==True],'.-b', alpha=0.3) for i in np.intersect1d(P_id[P_exp==True],p_id[p_exp==True]): plt.annotate('%0d'%i, xy=(p_cost[p_id==i], p_value[p_id==i]), xytext=(-5,4), textcoords='offset points', size=8, color='b') plt.plot(P_cost[P_exp==True],P_value[P_exp==True],ls='--',color=[.3,.3,.3]) plt.xlabel('Initial Cost ($\S$)') plt.ylabel('24-turn Expected Revenue ($\S$)') plt.xlim([1000, 4000]) plt.ylim([0, 12000]) plt.legend(['pSGL','pSGL and pISL'],loc='upper left') plt.grid() plt.gcf().set_size_inches(6.5, 3.5) plt.savefig(label+'-exp-ts.png', bbox_inches='tight', dpi=300) def tradespaceCentralized(label, id, cost, exp_value, std_err, run, pisl, oisl, osgl): plt.clf() plt.errorbar(cost[np.logical_and.reduce((pisl==False,oisl==True,osgl==False))], exp_value[np.logical_and.reduce((pisl==False,oisl==True,osgl==False))], yerr=1.96*std_err[np.logical_and.reduce((pisl==False,oisl==True,osgl==False))], fmt='none',color='g',ecolor='g', alpha=0.3) plt.errorbar(cost[np.logical_and.reduce((pisl==False,oisl==False,osgl==True))], exp_value[np.logical_and.reduce((pisl==False,oisl==False,osgl==True))], yerr=1.96*std_err[np.logical_and.reduce((pisl==False,oisl==False,osgl==True))], fmt='none',color='r',ecolor='r', alpha=0.3) plt.errorbar(cost[np.logical_and.reduce((pisl==True,oisl==False,osgl==True))], exp_value[np.logical_and.reduce((pisl==True,oisl==False,osgl==True))], yerr=1.96*std_err[np.logical_and.reduce((pisl==True,oisl==False,osgl==True))], fmt='none',color='m',ecolor='m', alpha=0.3) plt.errorbar(cost[np.logical_and.reduce((pisl==False,oisl==True,osgl==True))], exp_value[np.logical_and.reduce((pisl==False,oisl==True,osgl==True))], yerr=1.96*std_err[np.logical_and.reduce((pisl==False,oisl==True,osgl==True))], fmt='none',color='y',ecolor='y', alpha=0.3) plt.plot(cost[np.logical_and.reduce((pisl==False,oisl==True,osgl==False))], exp_value[np.logical_and.reduce((pisl==False,oisl==True,osgl==False))], ls='', marker='.',mec='none',color='g', alpha=0.3) plt.plot(cost[np.logical_and.reduce((pisl==False,oisl==False,osgl==True))], exp_value[np.logical_and.reduce((pisl==False,oisl==False,osgl==True))], ls='', marker='.',mec='none',color='r', alpha=0.3) plt.plot(cost[np.logical_and.reduce((pisl==True,oisl==False,osgl==True))], exp_value[np.logical_and.reduce((pisl==True,oisl==False,osgl==True))], ls='', marker='.',mec='none',color='m', alpha=0.3) plt.plot(cost[np.logical_and.reduce((pisl==False,oisl==True,osgl==True))], exp_value[np.logical_and.reduce((pisl==False,oisl==True,osgl==True))], ls='', marker='.',mec='none',color='y', alpha=0.3) P_id, P_cost, P_value, P_exp = pareto(id, cost, exp_value, std_err) p_id, p_cost, p_value, p_exp = pareto( id[np.logical_and.reduce((pisl==False,oisl==True,osgl==False))], cost[np.logical_and.reduce((pisl==False,oisl==True,osgl==False))], exp_value[np.logical_and.reduce((pisl==False,oisl==True,osgl==False))], std_err[np.logical_and.reduce((pisl==False,oisl==True,osgl==False))]) #plt.plot(p_cost[p_exp==True],p_value[p_exp==True],'.-g', alpha=0.3) for i in np.intersect1d(P_id[P_exp==True],p_id[p_exp==True]): plt.annotate('%0d'%i, xy=(p_cost[p_id==i], p_value[p_id==i]), xytext=(-5,4), textcoords='offset points', size=8, color='g') p_id, p_cost, p_value, p_exp = pareto( id[np.logical_and.reduce((pisl==False,oisl==False,osgl==True))], cost[np.logical_and.reduce((pisl==False,oisl==False,osgl==True))], exp_value[np.logical_and.reduce((pisl==False,oisl==False,osgl==True))], std_err[np.logical_and.reduce((pisl==False,oisl==False,osgl==True))]) #plt.plot(p_cost[p_exp==True],p_value[p_exp==True],'.-r', alpha=0.3) for i in np.intersect1d(P_id[P_exp==True],p_id[p_exp==True]): plt.annotate('%0d'%i, xy=(p_cost[p_id==i], p_value[p_id==i]), xytext=(-5,4), textcoords='offset points', size=8, color='r') p_id, p_cost, p_value, p_exp = pareto( id[np.logical_and.reduce((pisl==True,oisl==False,osgl==True))], cost[np.logical_and.reduce((pisl==True,oisl==False,osgl==True))], exp_value[np.logical_and.reduce((pisl==True,oisl==False,osgl==True))], std_err[np.logical_and.reduce((pisl==True,oisl==False,osgl==True))]) #plt.plot(p_cost[p_exp==True],p_value[p_exp==True],'.-m', alpha=0.3) for i in np.intersect1d(P_id[P_exp==True],p_id[p_exp==True]): plt.annotate('%0d'%i, xy=(p_cost[p_id==i], p_value[p_id==i]), xytext=(-5,4), textcoords='offset points', size=8, color='m') p_id, p_cost, p_value, p_exp = pareto( id[np.logical_and.reduce((pisl==False,oisl==True,osgl==True))], cost[np.logical_and.reduce((pisl==False,oisl==True,osgl==True))], exp_value[np.logical_and.reduce((pisl==False,oisl==True,osgl==True))], std_err[np.logical_and.reduce((pisl==False,oisl==True,osgl==True))]) #plt.plot(p_cost[p_exp==True],p_value[p_exp==True],'.-y', alpha=0.3) for i in np.intersect1d(P_id[P_exp==True],p_id[p_exp==True]): plt.annotate('%0d'%i, xy=(p_cost[p_id==i], p_value[p_id==i]), xytext=(-5,4), textcoords='offset points', size=8, color='y') plt.plot(P_cost[P_exp==True],P_value[P_exp==True],ls='--',color=[.3,.3,.3]) plt.xlabel('Initial Cost ($\S$)') plt.ylabel('24-turn Expected Revenue ($\S$)') plt.xlim([1000, 4000]) plt.ylim([0, 12000]) plt.legend(['pSGL and oISL', 'oSGL', 'oSGL and pISL', 'oSGL and oISL'],loc='upper left') plt.grid() plt.gcf().set_size_inches(6.5, 3.5) plt.savefig(label+'-exp-ts.png', bbox_inches='tight', dpi=300) independent = np.logical_and.reduce((players==2,player==0,oisl==False,osgl==False)) centralized = np.logical_and.reduce((players==2,player==0,np.logical_or(oisl,osgl))) if np.size(id[independent]) > 0: tradespaceIndependent('2i', id[independent], totalCost[independent]/2, totalExpValue[independent]/2, totalStdErr[independent]/2, run[independent], pisl[independent], oisl[independent], osgl[independent]) if np.size(id[centralized]) > 0: tradespaceCentralized('2c', id[centralized], totalCost[centralized]/2, totalExpValue[centralized]/2, totalStdErr[centralized]/2, run[centralized], pisl[centralized], oisl[centralized], osgl[centralized]) i_id, i_cost, i_value, i_exp = pareto(id[independent], totalCost[independent]/2, totalExpValue[independent]/2, totalStdErr[independent]/2) c_id, c_cost, c_value, c_exp = pareto(id[centralized], totalCost[centralized]/2, totalExpValue[centralized]/2, totalStdErr[centralized]/2) x_value = np.array([]) for i in c_id: m = re.search('^(1.* 1.GroundSta@SUR1)', run[i]) if m: query = m.group(1).replace('oSGL','pSGL').replace('oISL','pISL') for design in run[independent]: if query in design: x_value = np.append(x_value, totalExpValue[np.logical_and(run==design,player==0)]/2) x = np.linspace(max(np.amin(i_cost[i_exp==True]), np.amin(c_cost[c_exp==True])), max(np.amax(i_cost[i_exp==True]), np.amax(c_cost[c_exp==True]))) plt.clf() plt.fill_between(x, np.interp(x, i_cost[i_exp==True],i_value[i_exp==True]), np.interp(x, c_cost[c_exp==True], c_value[c_exp==True]), color='none', hatch='/', edgecolor=[.3,.3,.3,.5], linewidth=0.0) plt.fill_between(x, np.interp(x, c_cost[c_exp==True],x_value[c_exp==True]), np.interp(x, i_cost[i_exp==True], i_value[i_exp==True]), color='none', hatch='\\', edgecolor=[1,.3,.3,.5], linewidth=0.0) plt.plot(i_cost[i_exp==True], i_value[i_exp==True], '-k') plt.plot(c_cost[c_exp==True], c_value[c_exp==True], '--k') plt.plot(c_cost[c_exp==True], x_value[c_exp==True], '--r') plt.annotate('Upside Potential of FSS Success', xy=(2600, 7500), size=8, color='k') plt.annotate('Downside Risk of FSS Failure', xy=(2125, 3000), xytext=(2375,2250), textcoords='data', arrowprops=dict(arrowstyle='->',connectionstyle='arc3',ec='r'), size=8, color='r') plt.xlabel('Initial Cost ($\S$)') plt.ylabel('24-turn Expected Revenue ($\S$)') plt.xlim([1000, 4000]) plt.ylim([0, 12000]) plt.legend(['Independent Pareto Front ($V_i$)','Centralized Pareto Front, FSS Success ($V_c$)','Centralized Pareto Front, FSS Failure ($V_x$)'],loc='upper left') plt.grid() plt.gcf().set_size_inches(6.5, 3.5) plt.savefig('2-exp.png', bbox_inches='tight', dpi=300) plt.clf() plt.fill_between(x, np.interp(x, i_cost[i_exp==True],i_value[i_exp==True]-i_cost[i_exp==True]), np.interp(x, c_cost[c_exp==True], c_value[c_exp==True]-c_cost[c_exp==True]), color='none', hatch='/', edgecolor=[.3,.3,.3,.5], linewidth=0.0) plt.fill_between(x, np.interp(x, c_cost[c_exp==True],x_value[c_exp==True]-c_cost[c_exp==True]), np.interp(x, i_cost[i_exp==True], i_value[i_exp==True]-i_cost[i_exp==True]), color='none', hatch='\\', edgecolor=[1,.3,.3,.5], linewidth=0.0) plt.plot(i_cost[i_exp==True], i_value[i_exp==True]-i_cost[i_exp==True], '-k') plt.plot(c_cost[c_exp==True], c_value[c_exp==True]-c_cost[c_exp==True], '--k') plt.plot(c_cost[c_exp==True], x_value[c_exp==True]-c_cost[c_exp==True], '--r') plt.annotate('Upside Potential of FSS Success', xy=(2600, 4500), size=8, color='k') plt.annotate('Downside Risk of FSS Failure', xy=(2300, 1500), xytext=(2600,500), textcoords='data', arrowprops=dict(arrowstyle='->',connectionstyle='arc3',ec='r'), size=8, color='r') plt.xlabel('Initial Cost ($\S$)') plt.ylabel('24-turn Expected Net Value ($\S$)') plt.xlim([1000, 4000]) plt.ylim([-2000, 10000]) plt.legend(['Independent Pareto Front ($V_i$)','Centralized Pareto Front, FSS Success ($V_c$)','Centralized Pareto Front, FSS Failure ($V_x$)'],loc='upper left') plt.grid() plt.gcf().set_size_inches(6.5, 3.5) plt.savefig('2-exp-env.png', bbox_inches='tight', dpi=300)

46.465409

162

0.676841

2,560

14,776

3.763281

0.100781

0.049408

0.07349

0.104629

0.740918

0.726593

0.715175

0.703654

0.694935

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0

0.025734

0.100568

14,776

318

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46.465409

0.699172

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null

0

null

0

1

0

1

0

null

0

1

0

5

06bc512a4ca26dbb79ec2daef02f9c14ce8e06f4

300

py

Python

parqser/saver/base_saver.py

ARQtty/parqser

2f4f9505544d718dc818d1d9177ac1394bfbb352

[ "MIT" ]

null

parqser/saver/base_saver.py

ARQtty/parqser

2f4f9505544d718dc818d1d9177ac1394bfbb352

[ "MIT" ]

19

2021-07-22T11:18:17.000Z

2021-08-20T10:12:17.000Z

parqser/saver/base_saver.py

ARQtty/parqser

2f4f9505544d718dc818d1d9177ac1394bfbb352

[ "MIT" ]

1

2021-07-29T11:56:03.000Z

from typing import List, Dict, Any class BaseSaver: def __init__(self, *args, **kwargs): raise NotImplemented def save(self, params: Dict[str, Any]) -> None: raise NotImplemented def save_batch(self, params: List[Dict[str, Any]]) -> None: raise NotImplemented

23.076923

63

0.65

37

300

5.135135

0.540541

0.3

0.231579

0.273684

0.347368

0

0.24

300

12

64

25

0.833333

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0.375

0

1

0.375

false

0

0.125

0

0.625

0

null

1

0

null

0

1

0

1

0

5

06bfad8d82209d503201d9dfccf0b90d0fd29d26

104

py

Python

beacon_aug/external/DiffJPEG/modules/__init__.py

adobe-research/beacon-aug

9b891e99edd74a0ee88809e0b16a157e5fa90cf0

[ "MIT" ]

11

2021-09-22T20:08:59.000Z

2022-02-16T22:34:09.000Z

beacon_aug/external/DiffJPEG/modules/__init__.py

adobe-research/beacon-aug

9b891e99edd74a0ee88809e0b16a157e5fa90cf0

[ "MIT" ]

null

beacon_aug/external/DiffJPEG/modules/__init__.py

adobe-research/beacon-aug

9b891e99edd74a0ee88809e0b16a157e5fa90cf0

[ "MIT" ]

null

from .. import utils from .compression import compress_jpeg from .decompression import decompress_jpeg

20.8

42

0.836538

13

104

6.538462

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0.125

104

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1

0

null

0

1

0

1

0

1

0

5

06d77cda4b651066d97509314428ccfe157e8ec2

96,489

py

Python

img_rc.py

Tac213/PyChakura2.7

ff95c1b170a4d51b589a249716d43eadbd1e8acf

[ "MIT" ]

null

img_rc.py

Tac213/PyChakura2.7

ff95c1b170a4d51b589a249716d43eadbd1e8acf

[ "MIT" ]

null

img_rc.py

Tac213/PyChakura2.7

ff95c1b170a4d51b589a249716d43eadbd1e8acf

[ "MIT" ]

null

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0

1

0

1

0

1

0

null

1

0

5

6604842e33301cd50793ab12680393923a777bf8

1,212

py

Python

__Training__/Python - 30 Days of Code - HackerRank/12. 2D Arrays.py

JUD210/Study-Note

2add9db3f11d99370f49878f0c19e9caa60d2d02

[ "MIT" ]

null

__Training__/Python - 30 Days of Code - HackerRank/12. 2D Arrays.py

JUD210/Study-Note

2add9db3f11d99370f49878f0c19e9caa60d2d02

[ "MIT" ]

null

__Training__/Python - 30 Days of Code - HackerRank/12. 2D Arrays.py

JUD210/Study-Note

2add9db3f11d99370f49878f0c19e9caa60d2d02

[ "MIT" ]

null

# https://www.hackerrank.com/challenges/30-2d-arrays/problem # Inputs standard_input = """1 1 1 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0 0 2 4 4 0 0 0 0 2 0 0 0 0 1 2 4 0""" import math import os import random import re import sys arr = [] for i in range(6): arr.append(list(map(int, input().rstrip().split()))) # 1 1 1 0 0 0 # 0 1 0 0 0 0 # 1 1 1 0 0 0 # 0 0 2 4 4 0 # 0 0 0 2 0 0 # 0 0 1 2 4 0 def sum_hourglass(arr, x, y): result = 0 blank = [(x, y + 1), (x + 2, y + 1)] for ty in range(y, y + 3): for tx in range(x, x + 3): if (tx, ty) not in blank: result += arr[ty][tx] return result sum_results = [] for y in range(len(arr) - 2): for x in range(len(arr[y]) - 2): sum_results.append(sum_hourglass(arr, x, y)) print(max(sum_results)) # 19 # Reference # # 1 1 1 1 1 0 1 0 0 0 0 0 # 1 0 0 0 # 1 1 1 1 1 0 1 0 0 0 0 0 # # 0 1 0 1 0 0 0 0 0 0 0 0 # 1 1 0 0 # 0 0 2 0 2 4 2 4 4 4 4 0 # # 1 1 1 1 1 0 1 0 0 0 0 0 # 0 2 4 4 # 0 0 0 0 0 2 0 2 0 2 0 0 # # 0 0 2 0 2 4 2 4 4 4 4 0 # 0 0 2 0 # 0 0 1 0 1 2 1 2 4 2 4 0

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null

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5

662a994566e7ad4b2f62a33ab8c56e0cdfc67072

12,683

py

Python

test_all.py

blakefren/PasswordAsAService

f1d9e28e91c80807bfee67756cf7f408c467a71e

[ "MIT" ]

null

test_all.py

blakefren/PasswordAsAService

f1d9e28e91c80807bfee67756cf7f408c467a71e

[ "MIT" ]

null

test_all.py

blakefren/PasswordAsAService

f1d9e28e91c80807bfee67756cf7f408c467a71e

[ "MIT" ]

null

""" This script performs unit testing for PasswordAsAService web API. It is intended to run with the included /etc/passwd and /etc/group files. This does not read the passwd and group files to check the data, it only validates that the data was returned in the correct format, edge cases, etc. """ import sys import os from flask import Flask, request import unittest import json from itertools import combinations from service import app # Adjust these to test with other user/group. dummy_user = 0 dummy_group = 0 user_cols = ['name', 'uid', 'gid', 'comment', 'home', 'shell'] group_cols = ['name', 'gid', 'member'] group_cols_output = ['name', 'gid', 'members'] class TestService(unittest.TestCase): def test_users_all(self): # Test all users status code. self.test_app = app.test_client() response = self.test_app.get('/users') self.assertEqual(response.status_code, 200) '''with app.test_client() as client: # Testing query URL. response = client.get('/users') print(request.url) print(response.status_code)''' def test_users_all_data(self): # Check all users data. self.test_app = app.test_client() response = self.test_app.get('/users') json_vals = self.valid_json(response.data) # JSON return is invalid. if json_vals is None: self.assertTrue(False) # Test the valid JSON. else: # Make sure we have users. self.assertTrue(len(json_vals) > 0) # Check for all user columns in returned data. self.valid_user_data(json_vals, False) def test_users_single(self): # Test single user status code. self.test_app = app.test_client() response = self.test_app.get('/users/' + str(dummy_user)) # dummy user. self.assertEqual(response.status_code, 200) response = self.test_app.get('/users/1000000') # non-existent user. self.assertEqual(response.status_code, 404) response = self.test_app.get('/users/asdf') # non-integer uid. self.assertEqual(response.status_code, 404) def test_users_single_data(self): # Test single user data. self.test_app = app.test_client() response = self.test_app.get('/users/' + str(dummy_user)) # dummy group. json_vals = self.valid_json(response.data) # JSON return is invalid. if json_vals is None: self.assertTrue(False) # Test the valid JSON. else: # Make sure we have a user. self.assertTrue(len(json_vals) > 1) # Check for all user columns in returned data. self.valid_user_data(json_vals, True) def test_users_query(self): # Test users query status code. self.test_app = app.test_client() dummy_dict = { 'name': '', 'uid': 1000000, 'gid': 1000000, 'comment': '', 'home': '', 'shell': '' } # Get all combinations of querystring args. combos = [] for i in range(len(user_cols)+1): for item in combinations(user_cols, i): temp = {} for param in list(item): temp[param] = dummy_dict[param] combos.append(temp) # Iterate through all combinations of querystring args. for item in combos: response = self.test_app.get('/users/query', query_string=item) self.assertEqual(response.status_code, 200) # Run query with non-supported arg. response = self.test_app.get('/users/query', query_string={'asdf': 'fdsa'}) self.assertEqual(response.status_code, 200) def test_users_query_data(self): # Test users query data. self.test_app = app.test_client() dummy_dict = { 'name': 'root', 'uid': 0, 'gid': 0, 'comment': 'System Operator', 'home': '/', 'shell': '/bin/ksh' } # Get all combinations of querystring args. combos = [] for i in range(len(user_cols) + 1): for item in combinations(user_cols, i): temp = {} for param in list(item): temp[param] = dummy_dict[param] combos.append(temp) # Iterate through all combinations of querystring args. for item in combos: response = self.test_app.get('/users/query', query_string=item) # Test for valid JSON. json_vals = self.valid_json(response.data) # JSON return is invalid. if json_vals is None: self.assertTrue(False) # Test the valid JSON. else: # No need to validate if we have a user. # Some queries may not return any users. # Check for all user columns in returned data. self.valid_user_data(json_vals, False) # Run query with non-supported arg. response = self.test_app.get('/users/query', query_string={'asdf': 'fdsa'}) json_vals = self.valid_json(response.data) if json_vals is None: self.assertTrue(False) else: # No need to validate if we have a user. # Some queries may not return any users. # Check for all user columns in returned data. self.valid_user_data(json_vals, False) def test_users_groups(self): # Test user group status code. self.test_app = app.test_client() response = self.test_app.get('/users/' + str(dummy_user) + '/groups') # dummy user. self.assertEqual(response.status_code, 200) response = self.test_app.get('/users/1000000/groups') # non-existent user. self.assertEqual(response.status_code, 404) response = self.test_app.get('/users/asdf/groups') # non-integer uid. self.assertEqual(response.status_code, 404) def test_users_groups_data(self): # Test user group data. self.test_app = app.test_client() response = self.test_app.get('/users/' + str(dummy_user) + '/groups') # dummy user. json_vals = self.valid_json(response.data) # JSON return is invalid. if json_vals is None: self.assertTrue(False) # Test the valid JSON. else: # No need to validate if we have a group. # Some users may not be in any groups. # Check for all group columns in returned data. self.valid_group_data(json_vals, False) def test_groups_all(self): # Test all groups status code. self.test_app = app.test_client() response = self.test_app.get('/groups') self.assertEqual(response.status_code, 200) def test_groups_all_data(self): # Check all groups data. self.test_app = app.test_client() response = self.test_app.get('/groups') json_vals = self.valid_json(response.data) # JSON return is invalid. if json_vals is None: self.assertTrue(False) # Test the valid JSON. else: # Make sure we have groups. self.assertTrue(len(json_vals) > 0) # Check for all group columns in returned data. self.valid_group_data(json_vals, False) def test_groups_single(self): # Test single group status code. self.test_app = app.test_client() response = self.test_app.get('/groups/' + str(dummy_group)) # dummy group. self.assertEqual(response.status_code, 200) response = self.test_app.get('/groups/1000000') # non-existent group. self.assertEqual(response.status_code, 404) response = self.test_app.get('/groups/asdf') # non-integer gid. self.assertEqual(response.status_code, 404) def test_groups_single_data(self): # Test single group data. self.test_app = app.test_client() response = self.test_app.get('/groups/' + str(dummy_group)) # dummy group. json_vals = self.valid_json(response.data) # JSON return is invalid. if json_vals is None: self.assertTrue(False) # Test the valid JSON. else: # Make sure we have a group. self.assertTrue(len(json_vals) > 1) # Check for all group columns in returned data. self.valid_group_data(json_vals, True) def test_groups_query(self): # Test groups query status code. self.test_app = app.test_client() dummy_dict = { 'name': '', 'gid': 1000000, 'member': '' } # Get all combinations of querystring args. combos = [] for i in range(len(group_cols) + 1): for item in combinations(group_cols, i): temp = {} for param in list(item): temp[param] = dummy_dict[param] combos.append(temp) # Iterate through all combinations of querystring args. for item in combos: response = self.test_app.get('/groups/query', query_string=item) self.assertEqual(response.status_code, 200) # Run query with non-supported arg. response = self.test_app.get('/groups/query', query_string={'asdf': 'fdsa'}) self.assertEqual(response.status_code, 200) def test_groups_query_data(self): # Test groups query data. self.test_app = app.test_client() dummy_dict = { 'name': 'bin', 'gid': 2, 'member': ['root', 'daemon'] } # Get all combinations of querystring args. combos = [] for i in range(len(group_cols) + 1): for item in combinations(group_cols, i): for j in range(1, len(dummy_dict['member'])+1): # Adding to get all member combos. for jtem in combinations(dummy_dict['member'], j): # Adding to get all member combos. temp = {} for param in list(item): if param == 'member': temp[param] = list(jtem) else: temp[param] = dummy_dict[param] if temp not in combos: combos.append(temp) # Iterate through all combinations of querystring args. for item in combos: response = self.test_app.get('/groups/query', query_string=item) # Test for valid JSON. json_vals = self.valid_json(response.data) # JSON return is invalid. if json_vals is None: self.assertTrue(False) # Test the valid JSON. else: # No need to validate if we have a group. # Some queries may not return any groups. # Check for all groups columns in returned data. self.valid_group_data(json_vals, False) # Run query with non-supported arg. response = self.test_app.get('/groups/query', query_string={'name': 'root', 'asdf': 'fdsa'}) json_vals = self.valid_json(response.data) if json_vals is None: self.assertTrue(False) else: # No need to validate if we have a group. # Some queries may not return any groups. # Check for all groups columns in returned data. self.valid_group_data(json_vals, False) # Methods below are called by testing methods above. def valid_json(self, data): # Tests for valid json. valid_json_flag = False json_vals = None try: json_vals = json.loads(data) valid_json_flag = True except ValueError: pass self.assertTrue(valid_json_flag) return json_vals def valid_user_data(self, data, single_user): # Checks user data. if single_user: self.assertEqual(list(data.keys()), user_cols) else: for user in data: self.assertEqual(list(user.keys()), user_cols) def valid_group_data(self, data, single_group): # Checks group data. if single_group: self.assertEqual(list(data.keys()), group_cols_output) else: for group in data: self.assertEqual(list(group.keys()), group_cols_output)

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663730af842263cb477d764653c45960d8a1cfd4

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py

Python

scripts/field/go40000.py

Snewmy/swordie

ae01ed4ec0eb20a18730e8cd209eea0b84a8dd17

[ "MIT" ]

2

2020-08-25T06:55:19.000Z

2021-03-15T14:37:34.000Z

scripts/field/go40000.py

Snewmy/swordie

ae01ed4ec0eb20a18730e8cd209eea0b84a8dd17

[ "MIT" ]

null

scripts/field/go40000.py

Snewmy/swordie

ae01ed4ec0eb20a18730e8cd209eea0b84a8dd17

[ "MIT" ]

3

2020-08-25T06:55:25.000Z

2020-12-01T13:07:43.000Z

# Inside Small Forest sm.showEffect("Map/Effect.img/maplemap/enter/40000")

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b0b21d2a66100be3ed02fc9826ceea07c9b2910e

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py

Python

syzygy/exceptions.py

charettes/django-syzygy

2258bd9ce2f1b415e40e5b0c2652b478c460eb9d

[ "MIT" ]

8

2021-01-27T03:34:44.000Z

2022-02-21T22:40:20.000Z

syzygy/exceptions.py

charettes/django-syzygy

2258bd9ce2f1b415e40e5b0c2652b478c460eb9d

[ "MIT" ]

7

2020-04-21T03:11:59.000Z

2021-09-30T05:47:38.000Z

syzygy/exceptions.py

charettes/django-syzygy

2258bd9ce2f1b415e40e5b0c2652b478c460eb9d

[ "MIT" ]

null

class AmbiguousStage(ValueError): pass class AmbiguousPlan(ValueError): pass

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b0c04f2d924a821b28aeabbce76ee335bbd123cf

68

py

Python

use_functions.py

aeverall/learn-py-packaging

7d180affcb18933bf3fb3293ae0a5cf7701f1757

[ "MIT" ]

null

use_functions.py

aeverall/learn-py-packaging

7d180affcb18933bf3fb3293ae0a5cf7701f1757

[ "MIT" ]

null

use_functions.py

aeverall/learn-py-packaging

7d180affcb18933bf3fb3293ae0a5cf7701f1757

[ "MIT" ]

null

from learn_py_packaging.toy_module import power print(power(3, 4))

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9fe85e92f80e765c51bfb236b32a5a5f56c629c6

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py

Python

gtrending/__init__.py

berrybretch/gtrending

d3e4f6c15935258ab4c7635fd8ebcb10b0ff4a74

[ "MIT" ]

null

gtrending/__init__.py

berrybretch/gtrending

d3e4f6c15935258ab4c7635fd8ebcb10b0ff4a74

[ "MIT" ]

null

gtrending/__init__.py

berrybretch/gtrending

d3e4f6c15935258ab4c7635fd8ebcb10b0ff4a74

[ "MIT" ]

null

from .fetch import fetch_repos, fetch_developers, languages_list, spoken_languages_list

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b01ebf4c531ed32ae84cf690d2d513d8bf2a6028

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py

Python

field_ops/__init__.py

dbstein/field_ops

70359a1be37d911b879746e5c61d6d10da1c0f3b

[ "Apache-2.0" ]

null

field_ops/__init__.py

dbstein/field_ops

70359a1be37d911b879746e5c61d6d10da1c0f3b

[ "Apache-2.0" ]

null

field_ops/__init__.py

dbstein/field_ops

70359a1be37d911b879746e5c61d6d10da1c0f3b

[ "Apache-2.0" ]

null

from .core import Engine from .core2 import Engine as Engine2 from .core2 import Expression from .core2 import _cos as cos from .core2 import _sin as sin from .core2 import _tan as tan from .core2 import _arccos as arccos from .core2 import _arcsin as arcsin from .core2 import _arctan as arctan from .core2 import _arctan2 as arctan2 from .core2 import _cosh as cosh from .core2 import _sinh as sinh from .core2 import _tanh as tanh from .core2 import _arccosh as arccosh from .core2 import _arcsinh as arcsinh from .core2 import _arctanh as arctanh from .core2 import _log as log from .core2 import _log10 as log10 from .core2 import _log1p as log1p from .core2 import _exp as exp from .core2 import _expm1 as expm1 from .core2 import _sqrt as sqrt from .core2 import _abs as abs from .core2 import _conj as conj from .core2 import _real as real from .core2 import _imag as imag from .core2 import _complex as complex from .core2 import _sum as sum from .core2 import _prod as prod from .core2 import _pi as pi from .core2 import _e as e

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b030da43dc42841002bb50973452c9fe9d1956f0

196

py

Python

snowflake/__init__.py

vd2org/snowflake

7e1744f66582af998720f542cb3317c0e5586204

[ "MIT" ]

8

2021-07-18T14:30:33.000Z

2022-01-15T02:52:53.000Z

snowflake/__init__.py

vd2org/snowflake

7e1744f66582af998720f542cb3317c0e5586204

[ "MIT" ]

null

snowflake/__init__.py

vd2org/snowflake

7e1744f66582af998720f542cb3317c0e5586204

[ "MIT" ]

1

2021-12-05T14:24:15.000Z

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5

b038fe867227efd341221ac324e9fa6056af7e5e

261

py

Python

overhave/test_execution/__init__.py

TinkoffCreditSystems/overhave

b0ab705ef5c5c5a65fa0b14b173b64fd7310e187

[ "Apache-2.0" ]

33

2021-02-01T15:49:37.000Z

2021-12-20T00:44:43.000Z

overhave/test_execution/__init__.py

TinkoffCreditSystems/overhave

b0ab705ef5c5c5a65fa0b14b173b64fd7310e187

[ "Apache-2.0" ]

46

2021-02-03T12:56:52.000Z

2021-12-19T18:50:27.000Z

overhave/test_execution/__init__.py

TinkoffCreditSystems/overhave

b0ab705ef5c5c5a65fa0b14b173b64fd7310e187

[ "Apache-2.0" ]

1

2021-12-07T09:02:44.000Z

# flake8: noqa from .executor import ITestExecutor, TestExecutor from .objects import BddStepModel, StepTypeName from .settings import OverhaveProjectSettings, OverhaveTestSettings from .step_collector import StepCollector from .test_runner import PytestRunner

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5

b05be82bf24c6561d3b88ed6ff3eef25b7607f7b

62

py

Python

Python Programs/MaximumEdgeofTriangle.py

Chibi-Shem/Hacktoberfest2020-Expert

324843464aec039e130e85a16e74b76d310f1497

[ "MIT" ]

77

2020-10-01T10:06:59.000Z

2021-11-08T08:57:18.000Z

Python Programs/MaximumEdgeofTriangle.py

Chibi-Shem/Hacktoberfest2020-Expert

324843464aec039e130e85a16e74b76d310f1497

[ "MIT" ]

46

2020-09-27T04:55:36.000Z

2021-05-14T18:49:06.000Z

Python Programs/MaximumEdgeofTriangle.py

Chibi-Shem/Hacktoberfest2020-Expert

324843464aec039e130e85a16e74b76d310f1497

[ "MIT" ]

327

2020-09-26T17:06:03.000Z

2021-10-09T06:04:39.000Z

def next_edge(side1, side2): return (side1 + side2) - 1

15.5

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c6624c818cb77811a3cb4cecc8538c97489d4abf

550

py

Python

tests/test_groups.py

dapfa/python-limitlessled

75a4236ac438634a6d93dcf096d180f6a54ba08d

[ "MIT" ]

34

2015-11-27T21:55:21.000Z

2021-09-09T21:31:28.000Z

tests/test_groups.py

dapfa/python-limitlessled

75a4236ac438634a6d93dcf096d180f6a54ba08d

[ "MIT" ]

40

2015-12-01T19:00:16.000Z

2021-09-10T14:59:46.000Z

tests/test_groups.py

dapfa/python-limitlessled

75a4236ac438634a6d93dcf096d180f6a54ba08d

[ "MIT" ]

25

2015-11-30T21:22:16.000Z

2021-09-09T17:19:05.000Z

import unittest from limitlessled.bridge import Bridge from limitlessled.group.white import WhiteGroup, WHITE from limitlessled.group.rgbw import RgbwGroup, RGBW from limitlessled.group.rgbww import RgbwwGroup, RGBWW # TODO: mock socket class TestWhiteGroup(unittest.TestCase): def setUp(self): self.bridge = Bridge('localhost', 9999, version=5) def test_brightness(self): pass def test_temperature(self): pass def test_transition(self): pass def tearDown(self): self.bridge.close()

22

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24

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1

0

1

0

1

0

5

c66b6549d3067fa8b35c586f5ab3252ee2749330

816

py

Python

tests/_bundles/vendor_bundle/commands.py

achiang/flask-unchained

12788a6e618904a25ff2b571eb05ff1dc8f1840f

[ "MIT" ]

69

2018-10-10T01:59:11.000Z

2022-03-29T17:29:30.000Z

tests/_bundles/vendor_bundle/commands.py

achiang/flask-unchained

12788a6e618904a25ff2b571eb05ff1dc8f1840f

[ "MIT" ]

18

2018-11-17T12:42:02.000Z

2021-05-22T18:45:27.000Z

tests/_bundles/vendor_bundle/commands.py

achiang/flask-unchained

12788a6e618904a25ff2b571eb05ff1dc8f1840f

[ "MIT" ]

7

2018-10-12T16:20:25.000Z

2021-10-06T12:18:21.000Z

from flask_unchained.cli import cli, click @cli.command() def vendor_top_level(): """vendor_bundle docstring""" click.echo('vendor_bundle') # this group will have its baz command overridden @cli.group() def foo_group(): """vendor_bundle docstring""" @foo_group.command() def bar(): """vendor_bundle docstring""" click.echo('vendor_bundle') @foo_group.command() def baz(): """vendor_bundle docstring""" click.echo('vendor_bundle') # this group should get overridden by the myapp bundle @cli.group() def goo_group(): """vendor_bundle docstring""" @goo_group.command() def gar(): """vendor_bundle docstring""" click.echo('vendor_bundle') @goo_group.command() def gaz(): """the overridden group should not contain this command""" click.echo('vendor_bundle')

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5

c67e47e222a165fbade5e9aa1226730719bf3ccc

185

py

Python

docs/settings.py

lsaffre/north

3c928a0d061550130d7ce0a8e415ba505eee8a01

[ "BSD-2-Clause" ]

null

docs/settings.py

lsaffre/north

3c928a0d061550130d7ce0a8e415ba505eee8a01

[ "BSD-2-Clause" ]

null

docs/settings.py

lsaffre/north

3c928a0d061550130d7ce0a8e415ba505eee8a01

[ "BSD-2-Clause" ]

null

# pro-forma settings file. from north import Site #~ SITE = Site(__file__,globals(),no_local=True) SITE = Site(globals(),no_local=True) SECRET_KEY = "20227" # see :djangoticket:`20227`

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