xszheng2020/the_stack_dedup_python_hits_2 · Datasets at Hugging Face

d20d55a6b8812037e181c5378cc8a4a6ae82572d

285

py

Python

project/write_matrix.py

felixzheng02/pypkpd

9e7f41aa7e33ba50cec3482f14e7be08a4bc23e7

[ "MIT" ]

9

2021-06-17T08:11:31.000Z

2021-06-22T08:05:27.000Z

project/write_matrix.py

Caiya-Zhang/pypkpd

9e7f41aa7e33ba50cec3482f14e7be08a4bc23e7

[ "MIT" ]

null

project/write_matrix.py

Caiya-Zhang/pypkpd

9e7f41aa7e33ba50cec3482f14e7be08a4bc23e7

[ "MIT" ]

2

2021-06-18T07:16:08.000Z

2021-09-25T04:43:28.000Z

""" Function written to match MATLAB function Author: Caiya Zhang, Yuchen Zheng """ import numpy as np from project.fprintf import fprintf def write_matrix(f, x: np.ndarray): for i in range(0, x.shape[0]): fprintf(f,"%6e",x[i, :]) fprintf(f,"\n") return

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null

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1

0

2

d22e53fa5b707e5ff25bad39c2e1688da76babc2

1,330

py

Python

setup.py

VivumLab/py_cui

e3f185102d469b9c758f6d7ad53b6bcfc27e0f3d

[ "BSD-3-Clause" ]

654

2020-02-22T00:02:14.000Z

2022-03-29T23:10:31.000Z

setup.py

VivumLab/py_cui

e3f185102d469b9c758f6d7ad53b6bcfc27e0f3d

[ "BSD-3-Clause" ]

133

2020-01-28T15:41:05.000Z

2022-03-22T19:05:38.000Z

setup.py

VivumLab/py_cui

e3f185102d469b9c758f6d7ad53b6bcfc27e0f3d

[ "BSD-3-Clause" ]

68

2020-02-22T01:43:09.000Z

2022-02-22T18:01:43.000Z

import setuptools from sys import platform # Use README for long description with open('README.md', 'r') as readme_fp: long_description = readme_fp.read() with open('requirements.txt', 'r') as req_fp: required_libs = req_fp.readlines() # py_cui setup setuptools.setup( name='py_cui', description='A widget and grid based framework for building command line user interfaces in python.', long_description=long_description, long_description_content_type='text/markdown', version='0.1.4', author='Jakub Wlodek', author_email='jwlodek.dev@gmail.com', license='BSD (3-clause)', packages=setuptools.find_packages(exclude=['docs','tests', 'examples', 'venv']), install_requires=required_libs, url='https://github.com/jwlodek/py_cui', classifiers=[ 'Development Status :: 3 - Alpha', 'Intended Audience :: Developers', 'Programming Language :: Python :: 3.2', 'Programming Language :: Python :: 3.3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', ], keywords='cui cli commandline user-interface ui', python_requires='>=3.6', )

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d234dc73aa6cfe8b677814a5964de2e921ddf21e

1,327

py

Python

oop.py

vuksamardzic/basic-py

356766f895660376530a4734d751cea281d1920e

[ "MIT" ]

null

oop.py

vuksamardzic/basic-py

356766f895660376530a4734d751cea281d1920e

[ "MIT" ]

null

oop.py

vuksamardzic/basic-py

356766f895660376530a4734d751cea281d1920e

[ "MIT" ]

null

# Classes & Objects class Person: # __ means private __name = '' __email = '' def __init__(self, name, email): self.__name = name self.__email = email def set_name(self, name): self.__name = name def get_name(self): return self.__name def set_email(self, email): self.__email = email def get_email(self): return self.__email def to_string(self): return '{} can be contacted at {}'.format(self.__name, self.__email) person = Person('vuk samardžić', 'samardzic.vuk@gmail.com') # person.set_name('vuk') # person.set_email('samardzic.vuk@gmail.com') # print(person.get_name(), person.get_email()) # print(person.to_string()) class Customer(Person): __balance = 0 def __init__(self, name, email, balance): super().__init__(name, email) self.__balance = balance def set_balance(self, balance): self.__balance = balance def get_balance(self): return self.__balance def to_string(self): return '{} has the balance of {} and can be contacted at {}'.format(self.get_name(), self.__balance, self.get_email()) customer = Customer('John Doe', 'jdoe@gmail.com', 100) print(customer.to_string())

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2

d23eddf080fd748ffcca83d21face5169d137711

1,166

py

Python

apps/user/migrations/0002_auto_20200131_2116.py

phdevs1/CyberCaffe

bee989a6d8d59205ee2645e986b4b0f16d00bf05

[ "Apache-2.0" ]

null

apps/user/migrations/0002_auto_20200131_2116.py

phdevs1/CyberCaffe

bee989a6d8d59205ee2645e986b4b0f16d00bf05

[ "Apache-2.0" ]

7

2021-03-19T08:39:34.000Z

2022-03-12T00:15:38.000Z

apps/user/migrations/0002_auto_20200131_2116.py

pioh123/CyberCaffe

bee989a6d8d59205ee2645e986b4b0f16d00bf05

[ "Apache-2.0" ]

null

# Generated by Django 2.2.9 on 2020-01-31 21:16 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('user', '0001_initial'), ] operations = [ migrations.AlterModelOptions( name='user', options={'ordering': ['first_name'], 'verbose_name': 'Cliente', 'verbose_name_plural': 'Clientes'}, ), migrations.AlterField( model_name='user', name='first_name', field=models.CharField(max_length=30, verbose_name='Nombres'), ), migrations.AlterField( model_name='user', name='last_name', field=models.CharField(blank=True, max_length=30, null=True, verbose_name='Apellidos'), ), migrations.AlterField( model_name='user', name='money', field=models.FloatField(blank=True, null=True, verbose_name='Saldo'), ), migrations.AlterField( model_name='user', name='phone', field=models.CharField(blank=True, max_length=30, null=True, verbose_name='Telefono'), ), ]

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d243b100883faf50e90a2ee1d67172b43fbf7f7c

272

py

Python

wafhelpers/rtems_trace.py

fakecoinbase/ntpsecslashntpsec

6f72d3bfb0614b24219e69d990d3701393eb92ae

[ "CC-BY-4.0", "BSD-2-Clause", "NTP", "MIT", "BSD-3-Clause" ]

201

2015-11-16T16:57:58.000Z

2022-03-21T01:01:34.000Z

wafhelpers/rtems_trace.py

fakecoinbase/ntpsecslashntpsec

6f72d3bfb0614b24219e69d990d3701393eb92ae

[ "CC-BY-4.0", "BSD-2-Clause", "NTP", "MIT", "BSD-3-Clause" ]

4

2019-03-20T21:49:34.000Z

2021-12-30T18:08:56.000Z

wafhelpers/rtems_trace.py

fakecoinbase/ntpsecslashntpsec

6f72d3bfb0614b24219e69d990d3701393eb92ae

[ "CC-BY-4.0", "BSD-2-Clause", "NTP", "MIT", "BSD-3-Clause" ]

40

2016-05-25T05:25:51.000Z

2021-12-30T17:40:00.000Z

from waflib.TaskGen import feature, after_method @feature("rtems_trace") @after_method('apply_link') def rtems_trace(self): if self.env.RTEMS_TEST_ENABLE: self.link_task.env.LINK_CC = self.env.BIN_RTEMS_TLD \ + self.env.RTEMS_TEST_FLAGS + ['--']

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1

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null

0

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d252e4772aedc4e852e116819c2a601f7290f948

1,276

py

Python

HD/Dovapp/views.py

xiaojie96528/Dove

514200432c6fa9158feea1fe5527d6f291c20ddc

[ "Unlicense" ]

null

HD/Dovapp/views.py

xiaojie96528/Dove

514200432c6fa9158feea1fe5527d6f291c20ddc

[ "Unlicense" ]

null

HD/Dovapp/views.py

xiaojie96528/Dove

514200432c6fa9158feea1fe5527d6f291c20ddc

[ "Unlicense" ]

null

from django.shortcuts import render from Dovapp.models import * from rest_framework import viewsets from Dovapp.serializers import * from django.contrib.auth import authenticate,login,logout from django.contrib.auth.decorators import login_required from django.http import JsonResponse import json class ProjectViewSet(viewsets.ModelViewSet): """ get: Return all projects. post: Create a new project. """ queryset = Project.objects.all() serializer_class = ProjectSerializer def login_acc(request): if request.method=="POST": username = request.POST.get("username") password = request.POST.get("password") try: user = authenticate(username=username,password=password) except Exception as e: user=None print(e) if user is not None: login(request,user) data = {"msg": "登录成功", "data": user.username,"code":"200"} return JsonResponse(data,safe=False) else: data = {"msg": "用户名或密码错误1","data": "xm"} return JsonResponse(data,safe=False) def logout_acc(request): logout(request) data = {"msg": "退出成功", "data": "", "code": "200"} return JsonResponse(data,safe=False)

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d254b436bc6cddd56e9b89d311860bb0e5dc2b6a

790

py

Python

com.systemincloud.examples.tasks.pythontask/src/test/py/tasks/params/Parameters.py

systemincloud/sic-examples

b82d5d672f515b1deb5ddb35c5a93c003e03c030

[ "Apache-2.0" ]

null

com.systemincloud.examples.tasks.pythontask/src/test/py/tasks/params/Parameters.py

systemincloud/sic-examples

b82d5d672f515b1deb5ddb35c5a93c003e03c030

[ "Apache-2.0" ]

15

2015-01-08T20:28:19.000Z

2016-07-20T07:19:15.000Z

com.systemincloud.examples.tasks.pythontask/src/test/py/tasks/params/Parameters.py

systemincloud/sic-examples

b82d5d672f515b1deb5ddb35c5a93c003e03c030

[ "Apache-2.0" ]

null

from sicpythontask.PythonTaskInfo import PythonTaskInfo from sicpythontask.PythonTask import PythonTask from sicpythontask.SicParameter import SicParameter from sicpythontask.InputPort import InputPort from sicpythontask.OutputPort import OutputPort from sicpythontask.data.Int32 import Int32 @PythonTaskInfo @SicParameter(name="M") @SicParameter(name="N", default_value="5") class Parameters(PythonTask): def __init_ports__(self): self.in_ = InputPort(name="in", data_type=Int32) self.out = OutputPort(name="out", data_type=Int32) def runner_start(self): self.n = int(self.get_parameter('N')) self.m = int(self.get_parameter('M')) def execute(self, grp): self.out.put_data(Int32(self.in_.get_data(Int32).values[0]*self.n + self.m))

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d25532d0801b35285335d7d62daaa54571c4a971

2,697

py

Python

wagtailnest/utils.py

ionata/wagtailnest

da903db0967e6f3b87db7213c9d94c0ec98048f5

[ "BSD-3-Clause" ]

1

2018-04-11T23:47:33.000Z

wagtailnest/utils.py

ionata/wagtailnest

da903db0967e6f3b87db7213c9d94c0ec98048f5

[ "BSD-3-Clause" ]

12

2017-07-18T01:52:06.000Z

2021-09-08T00:15:37.000Z

wagtailnest/utils.py

ionata/wagtailnest

da903db0967e6f3b87db7213c9d94c0ec98048f5

[ "BSD-3-Clause" ]

1

2017-05-05T06:18:44.000Z

from functools import wraps from dj_core.utils import as_absolute from django.conf import settings from django.urls import reverse from rest_framework.settings import perform_import from wagtail.core.blocks import RichTextBlock from wagtail.core.models import Site, UserPagePermissionsProxy from wagtail.images.formats import get_image_formats def get_site(): site = Site.objects.filter(pk=settings.SITE_ID).first() if site is None: site = Site.objects.filter( hostname=settings.DJCORE.URL.hostname).first() return site or Site.objects.first() def _clean_rel_url(rel_url): return '/{}/'.format(rel_url.strip('/')).replace('//', '/') def get_root_relative_url(url_path): """Remove the root page slug from the URL path""" return _clean_rel_url('/'.join(url_path.split('/')[2:])) def get_url_path(root_relative_url): """Add the root page slug to the URL path""" return _clean_rel_url('/'.join( [get_site().root_page.url_path.strip('/')] + [s for s in root_relative_url.split('/') if s != ''])) def publishable_pages(user, qs=None): publishable = UserPagePermissionsProxy(user).publishable_pages() if qs is None: return publishable return qs.filter(id__in=publishable.values_list('pk', flat=True)) def can_publish(user, page): return page.pk in publishable_pages(user).values_list('pk', flat=True) def generate_image_url(image, filter_spec): """From an Image, get a URL.""" from wagtail.images.views.serve import generate_signature signature = generate_signature(image.id, filter_spec) name = 'wagtailimages_serve' url = reverse(name, args=(signature, image.id, filter_spec)) return as_absolute(url) def get_image_filter_spec(profile_name): profiles = {x.name: x for x in get_image_formats()} return getattr(profiles.get(profile_name, None), 'filter_spec', 'original') def richtext_to_python(value): """Convert a RichText rendered string back into RichText.""" if isinstance(value, str): return str(RichTextBlock().to_python(value)) return value def serialize_video_url(video_url): from wagtailnest.serializers import EmbedSerializer return EmbedSerializer.for_url(video_url) def import_setting(name, default=None): value = perform_import(settings.WAGTAILNEST.get(name, None), name) return default if value is None else value def nonraw_signal_handler(signal_handler): """Decorator that turns off signal handlers when loading fixture data.""" @wraps(signal_handler) def wrapper(*args, **kwargs): if kwargs.get('raw'): return signal_handler(*args, **kwargs) return wrapper

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d266cfc02c86def010526f635a28263a0737b8ff

552

py

Python

django_quicky/context_processors.py

sametmax/django-quicky

2a87dbdcc6db400aff5a9119533bd3784fc4afb4

[ "Zlib" ]

149

2015-01-02T19:48:47.000Z

2022-02-18T15:43:34.000Z

django_quicky/context_processors.py

keshapps/django-quicky

2a87dbdcc6db400aff5a9119533bd3784fc4afb4

[ "Zlib" ]

3

2015-01-28T18:44:42.000Z

2017-05-23T18:50:02.000Z

django_quicky/context_processors.py

keshapps/django-quicky

2a87dbdcc6db400aff5a9119533bd3784fc4afb4

[ "Zlib" ]

11

2015-01-05T19:22:16.000Z

2021-01-25T13:06:20.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- # vim: ai ts=4 sts=4 et sw=4 nu from django.views.debug import get_safe_settings class SafeSettings(object): """ Map attributes to values in the safe settings dict """ def __init__(self): self._settings = get_safe_settings() def __getattr__(self, name): try: return self._settings[name.upper()] except KeyError: raise AttributeError settings_obj = SafeSettings() def settings(request): return {'settings': settings_obj}

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d27223323c43244be904aa993d9b2e5796b576a0

1,644

py

Python

mpcereform/reform.py

michaelgfalk/mpce-database-reform

097738b103a969489a25d2ae3ce5c704ec6e1dbd

[ "MIT" ]

1

2019-07-02T01:36:47.000Z

mpcereform/reform.py

michaelgfalk/mpce-database-reform

097738b103a969489a25d2ae3ce5c704ec6e1dbd

[ "MIT" ]

null

mpcereform/reform.py

michaelgfalk/mpce-database-reform

097738b103a969489a25d2ae3ce5c704ec6e1dbd

[ "MIT" ]

1

2019-08-14T06:12:59.000Z

"""Command for reshaping existing 'manuscripts' database, and porting it to the new structure""" import sys import argparse from mpcereform.core import LocalDB def main(): """Main entry point for the script""" # Define argument parser parser = argparse.ArgumentParser(description='Build the MPCE database from raw data.') parser.add_argument('-u', '--user', type=str, help='username for your MySQL/MariaDB server', default='root') parser.add_argument('-p', '--password', type=str, help='password for your MySQL/MariaDB server', default=None) parser.add_argument('-hst', '--host', type=str, help='hostname for your MySQL/MariaDB server (defaults to localhost)', default='127.0.0.1') args = parser.parse_args() arg_dict = vars(args) # Start connection, build schema if necessary print('\nDATABASE CONNECTION') print('======================\n') db = LocalDB(**arg_dict) #pylint:disable=invalid-name; # Run import methods print('\nENTITY IMPORT') print('======================\n') db.import_works() db.import_editions() db.import_places() print('\nEVENT IMPORT') print('======================\n') db.import_stn() db.import_new_tables() db.import_data_spreadsheets() print('\nRESOLVING AGENT DATA') print('======================\n') db.resolve_agents() print('\nADDING ADDITIONAL STRUCTURE TO DATABASE') print('======================\n') db.create_triggers() db.summarise() if __name__ == '__main__': sys.exit(main())

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null

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2

962a58eb1d233b2ad02abd3e67afb5e8981e9407

172

py

Python

spectrify/__init__.py

grantatspothero/spectrify

b32910bf2d6b5c0d34578715d4ff2af0cea572d3

[ "MIT" ]

null

spectrify/__init__.py

grantatspothero/spectrify

b32910bf2d6b5c0d34578715d4ff2af0cea572d3

[ "MIT" ]

null

spectrify/__init__.py

grantatspothero/spectrify

b32910bf2d6b5c0d34578715d4ff2af0cea572d3

[ "MIT" ]

null

# -*- coding: utf-8 -*- """Top-level package for Spectrify.""" __author__ = """The Narrativ Company, Inc.""" __email__ = 'engineering@narrativ.com' __version__ = '1.0.1'

21.5

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7

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9641a6590cc0a7f2c2cf6df11e4a2c3ac8c4a6c3

1,666

py

Python

openquake/hazardlib/scalerel/peer.py

gfzriesgos/shakyground-lfs

2caf67cc32e6800286eded2df1efb05973ccf41b

[ "BSD-3-Clause" ]

1

2019-08-01T00:28:24.000Z

openquake/hazardlib/scalerel/peer.py

gfzriesgos/shakyground-lfs

2caf67cc32e6800286eded2df1efb05973ccf41b

[ "BSD-3-Clause" ]

4

2018-08-31T14:14:35.000Z

2021-10-11T12:53:13.000Z

openquake/hazardlib/scalerel/peer.py

gfzriesgos/shakyground-lfs

2caf67cc32e6800286eded2df1efb05973ccf41b

[ "BSD-3-Clause" ]

3

2018-08-31T14:11:00.000Z

2019-07-17T10:06:02.000Z

# -*- coding: utf-8 -*- # vim: tabstop=4 shiftwidth=4 softtabstop=4 # # Copyright (C) 2012-2018 GEM Foundation # # OpenQuake is free software: you can redistribute it and/or modify it # under the terms of the GNU Affero General Public License as published # by the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # OpenQuake is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Affero General Public License for more details. # # You should have received a copy of the GNU Affero General Public License # along with OpenQuake. If not, see <http://www.gnu.org/licenses/>. """ Module :mod:`openquake.hazardlib.scalerel.peer` implements :class:`PeerMSR`. """ from openquake.hazardlib.scalerel.base import BaseMSRSigma from openquake.baselib.slots import with_slots @with_slots class PeerMSR(BaseMSRSigma): """ Magnitude-Scaling Relationship defined for PEER PSHA test cases. See "Verification of Probabilistic Seismic Hazard Analysis Computer Programs", Patricia Thomas and Ivan Wong, PEER Report 2010/106, May 2010. """ _slots_ = [] def get_median_area(self, mag, rake): """ Calculates median area as ``10 ** (mag - 4)``. Rake is ignored. """ return 10 ** (mag - 4.0) def get_std_dev_area(self, mag, rake): """ Standard deviation for PeerMSR. Mag and rake are ignored. >>> peer = PeerMSR() >>> 0.25 == peer.get_std_dev_area(4.0, 50) True """ return 0.25

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0.031634

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0.214286

1,666

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null

0

null

0

1

0

1

0

2

96487499ba079f0859d79d5c4ffe39f18b10e29a

431

py

Python

sympy/polys/domains/characteristiczero.py

msgoff/sympy

1e7daef7514902f5e89718fa957b7b36c6669a10

[ "BSD-3-Clause" ]

null

sympy/polys/domains/characteristiczero.py

msgoff/sympy

1e7daef7514902f5e89718fa957b7b36c6669a10

[ "BSD-3-Clause" ]

null

sympy/polys/domains/characteristiczero.py

msgoff/sympy

1e7daef7514902f5e89718fa957b7b36c6669a10

[ "BSD-3-Clause" ]

null

"""Implementation of :class:`CharacteristicZero` class. """ from __future__ import print_function, division from sympy.polys.domains.domain import Domain from sympy.utilities import public @public class CharacteristicZero(Domain): """Domain that has infinite number of elements. """ has_CharacteristicZero = True def characteristic(self): """Return the characteristic of this domain. """ return 0

23.944444

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0.733179

48

431

6.458333

0.604167

0.148387

0

0.002825

0.178654

431

17

60

25.352941

0.872881

0.327146

0

1

0.125

false

0

0.375

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0.875

0.125

0

null

0

null

0

1

0

1

0

2

9657189fa10a1d0b806ca88143156feeda494c67

1,211

py

Python

src/ingest-pipeline/md/data_file_types/__init__.py

AustinHartman/ingest-pipeline

788d9310792c9396a38650deda3dad11483b368c

[ "MIT" ]

6

2020-02-18T19:09:59.000Z

2021-10-07T20:38:46.000Z

src/ingest-pipeline/md/data_file_types/__init__.py

AustinHartman/ingest-pipeline

788d9310792c9396a38650deda3dad11483b368c

[ "MIT" ]

324

2020-02-06T22:08:50.000Z

2022-03-24T20:44:33.000Z

src/ingest-pipeline/md/data_file_types/__init__.py

AustinHartman/ingest-pipeline

788d9310792c9396a38650deda3dad11483b368c

[ "MIT" ]

2

2020-07-20T14:43:49.000Z

2021-10-29T18:24:36.000Z

from .ignore_metadata_file import IgnoreMetadataFile from .yaml_metadata_file import YamlMetadataFile from .json_metadata_file import JSONMetadataFile from .false_json_metadata_file import FalseJSONMetadataFile from .txt_tform_metadata_file import TxtTformMetadataFile from .txt_wordlist_metadata_file import TxtWordListMetadataFile from .mtx_tform_metadata_file import MtxTformMetadataFile #from .czi_metadata_file import CZIMetadataFile from .ome_tiff_metadata_file import OMETiffMetadataFile from .scn_tiff_metadata_file import ScnTiffMetadataFile from .imzml_metadata_file import ImzMLMetadataFile from .fastq_metadata_file import FASTQMetadataFile from .csv_metadata_file import CSVMetadataFile from .tsv_metadata_file import TSVMetadataFile from .metadatatsv_metadata_file import MetadataTSVMetadataFile __all__ = ["IgnoreMetadataFile", "YamlMetadataFile", "JSONMetadataFile", "TxtTformMetadataFile", "MtxTformMetadataFile", #"CZIMetadataFile", "OMETiffMetadataFile", "ScnTiffMetadataFile", "ImzMLMetadataFile", "FASTQMetadataFile", "FalseJSONMetadataFile", "TxtWordListMetadataFile", "CSVMetadataFile", "TSVMetadataFile", "MetadataTSVMetadataFile"]

55.045455

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0.83815

112

1,211

8.705357

0.330357

0.184615

0.276923

0.045128

0

0.109001

1,211

21

84

57.666667

0.903614

0.052849

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0.058515

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false

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null

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null

0

1

0

2

965942653ae1d738b4c43d1e78e32e417acd5007

182

py

Python

app/views/__test__/test_foo.py

alexjravila/JogoBaixoWebAPI

3e0e2d746000c600d105f973eba690ee6590db93

[ "MIT" ]

null

app/views/__test__/test_foo.py

alexjravila/JogoBaixoWebAPI

3e0e2d746000c600d105f973eba690ee6590db93

[ "MIT" ]

null

app/views/__test__/test_foo.py

alexjravila/JogoBaixoWebAPI

3e0e2d746000c600d105f973eba690ee6590db93

[ "MIT" ]

null

from http import HTTPStatus def test_foo_get_all_should_be_ok(client): expectedResult = [] response = client.get("/api/foo") assert response.status_code == HTTPStatus.OK

30.333333

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0.747253

25

182

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0.153846

182

6

48

30.333333

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0.2

1

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0.2

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1

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null

0

1

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null

0

2

96699696e3c59556aa5e6cb9f65ef4981c4e2135

234

py

Python

code/List/sample.py

jumploop/30-seconds-of-python

bfcc5a35d9bd0bba67e81de5715dba21e1ba43be

[ "CC0-1.0" ]

null

code/List/sample.py

jumploop/30-seconds-of-python

bfcc5a35d9bd0bba67e81de5715dba21e1ba43be

[ "CC0-1.0" ]

null

code/List/sample.py

jumploop/30-seconds-of-python

bfcc5a35d9bd0bba67e81de5715dba21e1ba43be

[ "CC0-1.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ 功能实现：从列表中返回一个随机元素。解读：使用random.choice()从lst中获取一个随机元素 """ from random import choice def sample(lst): return choice(lst) # Examples print(sample([3, 7, 9, 11])) # output: # 9

11.142857

30

0.641026

32

234

4.6875

0.84375

0

0.036082

0.17094

234

20

31

11.7

0.737113

0.495727

0

1

0.25

false

0

0.25

0.75

0.25

0

null

0

null

0

1

0

1

0

2

9671c2b3c051b1808d5ef9fe526b6e9c32a9b462

314

py

Python

elliptic_integral_approximation.py

BIDS-numpy/presentation-uofm-2020

8ffd67167f212273bad8c8ed0171259a90e62909

[ "BSD-3-Clause" ]

5

2019-12-19T23:27:52.000Z

2020-01-30T19:38:09.000Z

elliptic_integral_approximation.py

Dimbinantenaina/presentation-AIMS-2020

55a97b8a46613d220219ea4be2182ce3c01f5579

[ "BSD-3-Clause" ]

8

2020-01-11T07:43:54.000Z

2020-02-04T22:58:39.000Z

elliptic_integral_approximation.py

Dimbinantenaina/presentation-AIMS-2020

55a97b8a46613d220219ea4be2182ce3c01f5579

[ "BSD-3-Clause" ]

6

2020-04-30T16:24:15.000Z

2020-05-02T09:11:08.000Z

import numpy as np def schlawin(x): a1 = 0.44325141463 a2 = 0.06260601220 a3 = 0.04757383546 a4 = 0.01736506451 b1 = 0.24998368310 b2 = 0.09200180037 b3 = 0.04069697526 b4 = 0.00526449639 return 1 + x*(a1 + x*(a2 + x*(a3 + x*a4))) + x*(b1 + x*(b2 + x*(b3 + x*b4)))*np.log(1/x)

24.153846

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3.339623

0.509434

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0

0.497817

0.270701

314

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0.275109

0

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0.090909

0

0.272727

0

null

0

1

0

1

0

null

0

2

968cb5c2efa92fd0d1cd2bd70ffcfae507ec19df

21,295

py

Python

src/rocommand/ro_annotation.py

A-Mazurek/ro-manager

e49b6025b89594e036fdb2b56c8b871717b3b620

[ "MIT-0", "MIT" ]

11

2015-01-19T04:21:58.000Z

2019-02-21T11:54:45.000Z

src/rocommand/ro_annotation.py

A-Mazurek/ro-manager

e49b6025b89594e036fdb2b56c8b871717b3b620

[ "MIT-0", "MIT" ]

1

2016-10-18T14:35:36.000Z

2016-10-25T19:12:05.000Z

src/rocommand/ro_annotation.py

A-Mazurek/ro-manager

e49b6025b89594e036fdb2b56c8b871717b3b620

[ "MIT-0", "MIT" ]

7

2015-03-04T17:22:00.000Z

2022-03-14T15:55:23.000Z

# ro_annotation.py """ Research Object annotation read, write, decode functions """ __author__ = "Graham Klyne (GK@ACM.ORG)" __copyright__ = "Copyright 2011-2013, University of Oxford" __license__ = "MIT (http://opensource.org/licenses/MIT)" import sys import os import os.path import datetime import logging import re import urlparse log = logging.getLogger(__name__) import rdflib #from rdflib.namespace import RDF, RDFS #from rdflib import URIRef, Namespace, BNode #from rdflib import Literal import ro_settings import ro_manifest from ro_namespaces import RDF, RDFS, RO, AO, ORE, DCTERMS, ROTERMS from ro_uriutils import resolveUri, resolveFileAsUri from ro_prefixes import prefix_dict # Default list of annotation types annotationTypes = ( [ { "name": "type", "prefix": "dcterms", "localName": "type", "type": "string" , "baseUri": DCTERMS.baseUri, "fullUri": DCTERMS.type , "label": "Type" , "description": "Word or brief phrase describing type of Research Object component" } , { "name": "keywords", "prefix": "dcterms", "localName": "subject", "type": "termlist" , "baseUri": DCTERMS.baseUri, "fullUri": DCTERMS.subject , "label": "Keywords" , "description": "List of key words or phrases associated with a Research Object component" } , { "name": "description", "prefix": "dcterms", "localName": "description", "type": "text" , "baseUri": DCTERMS.baseUri, "fullUri": DCTERMS.description , "label": "Description" , "description": "Extended description of Research Object component" } , { "name": "format", "prefix": "dcterms", "localName": "format", "type": "string" , "baseUri": DCTERMS.baseUri, "fullUri": DCTERMS.format , "label": "Data format" , "description": "String indicating the data format of a Research Object component" } , { "name": "note", "prefix": "dcterms", "localName": "note", "type": "text" , "baseUri": ROTERMS.baseUri, "fullUri": ROTERMS.note , "label": "Note" , "description": "String indicating some information about a Research Object component" } , { "name": "title", "prefix": "dcterms", "localName": "title", "type": "string" , "baseUri": DCTERMS.baseUri, "fullUri": DCTERMS.title , "label": "Title" , "description": "Title of Research Object component" } , { "name": "created", "prefix": "dcterms", "localName": "created", "type": "datetime" , "baseUri": DCTERMS.baseUri, "fullUri": DCTERMS.created , "label": "Creation time" , "description": "Date and time that Research Object component was created" } , { "name": "rdf:type", "prefix": "rdf", "localName": "type", "type": "resource" , "baseUri": RDF.baseUri, "fullUri": RDF.type , "label": "RDF type" , "description": "RDF type of the annotated object" } , { "name": "rdfs:seeAlso", "prefix": "rdfs", "localName": "seeAlso", "type": "resource" , "baseUri": RDFS.baseUri, "fullUri": RDFS.seeAlso , "label": "See also" , "description": "Related resource with further information" } ]) # Default list of annotation prefixes annotationPrefixes = prefix_dict.copy() annotationPrefixes.update({'ex': "http://example.org/ro/annotation#"}) # Annotation support functions def getResourceNameString(ro_config, rname, base=None): """ Returns a string value corresoponding to a URI indicated by the supplied parameter. Relative references are assumed to be paths relative to the supplied base URI or, if no rbase is supplied, relative to the current directory. """ rsplit = rname.split(":") if len(rsplit) == 2: # Try to interpret name as CURIE for rpref in ro_config["annotationPrefixes"]: if rsplit[0] == rpref: rname = ro_config["annotationPrefixes"][rpref]+rsplit[1] if urlparse.urlsplit(rname).scheme == "": if base: rname = resolveUri(rname, base) else: rname = resolveFileAsUri(rname) return rname def getAnnotationByName(ro_config, aname, defaultType="string"): """ Given an attribute name from the command line, returns attribute predicate and type URIs as a URIRef node and attribute value type """ predicate = aname valtype = defaultType for atype in ro_config["annotationTypes"]: # Try to interpret attribute name as predefined name if atype["name"] == aname: predicate = atype["fullUri"] valtype = atype["type"] break else: predicate = getResourceNameString(ro_config, aname, base=ROTERMS.defaultBase+"#") predicate = rdflib.URIRef(predicate) return (predicate, valtype) def getAnnotationByUri(ro_config, auri, defaultType="string"): """ Given an attribute URI from the manifest graph, returns an attribute name and type tuple for displaying an attribute """ # Look for predefined name for atype in ro_config["annotationTypes"]: if str(atype["fullUri"]) == str(auri): return (atype["name"], atype["type"]) # Look for CURIE match for (pref,puri) in ro_config["annotationPrefixes"].iteritems(): if auri.startswith(puri): return (pref+":"+auri[len(puri):], defaultType) # return full URI in angle brackets return ("<"+str(auri)+">", defaultType) def getAnnotationNameByUri(ro_config, uri): """ Given an attribute URI from the manifest graph, returns an attribute name for displaying an attribute """ return getAnnotationByUri(ro_config, uri)[0] def makeAnnotationFilename(rodir, afile): #log.debug("makeAnnotationFilename: %s, %s"%(rodir, afile)) return os.path.join(os.path.abspath(rodir), ro_settings.MANIFEST_DIR+"/", afile) def makeComponentFilename(rodir, rofile): log.debug("makeComponentFilename: %s, %s"%(rodir, rofile)) return os.path.join(rodir, rofile) def readAnnotationBody(rodir, annotationfile): """ Read annotation body from indicated file, return RDF Graph of annotation values. """ log.debug("readAnnotationBody: %s, %s"%(rodir, annotationfile)) annotationfilename = makeComponentFilename(rodir, annotationfile) if not os.path.exists(annotationfilename): return None annotationformat = "xml" # Look at file extension to figure format if re.search("\.(ttl|n3)$", annotationfile): annotationformat="n3" rdfGraph = rdflib.Graph() rdfGraph.parse(annotationfilename, format=annotationformat) return rdfGraph def createAnnotationGraphBody(ro_config, ro_dir, rofile, anngraph): """ Create a new annotation body for a single resource in a research object, based on a supplied graph value. Existing annotations for the same resource are not touched; if an annotation is being added or replaced, it is the calling program'sresponsibility to update the manifest to reference the active annotations. A new name is allocated for the created annotation, graph which is returned as the result of this function. ro_config is the research object manager configuration, supplied as a dictionary ro_dir is the research object root directory rofile is the name of the Research Object component to be annotated, possibly relative to the RO root directory. anngraph is an annotation graph that is to be saved. Returns the name of the annotation body created relative to the RO manifest and metadata directory. """ # Determine name for annotation body log.debug("createAnnotationGraphBody: %s, %s"%(ro_dir, rofile)) annotation_filename = None name_index = 0 name_suffix = os.path.basename(rofile) if name_suffix in [".",""]: name_suffix = os.path.basename(os.path.normpath(ro_dir)) today = datetime.date.today() while annotation_filename == None: name_index += 1 name = ("Ann-%04d%02d%02d-%04d-%s.rdf"% (today.year, today.month, today.day, name_index, name_suffix)) if not os.path.exists(makeAnnotationFilename(ro_dir, name)): annotation_filename = name # Create annotation body file log.debug("createAnnotationGraphBody: %s"%(annotation_filename)) anngraph.serialize(destination=makeAnnotationFilename(ro_dir, annotation_filename), format='xml', base=ro_manifest.getRoUri(ro_dir), xml_base="..") return annotation_filename def createAnnotationBody(ro_config, ro_dir, rofile, attrdict, defaultType="string"): """ Create a new annotation body for a single resource in a research object. Existing annotations for the same resource are not touched; if an annotation is being added or replaced, it is the calling program'sresponsibility to update the manifest to reference the active annotations. A new name is allocated for the created annotation, which is returned as the result of this function. ro_config is the research object manager configuration, supplied as a dictionary ro_dir is the research object root directory rofile is the name of the Research Object component to be annotated, possibly relative to the RO root directory. attrdict is a dictionary of attributes to be saved inthe annotation body. Dictionary keys are attribute names that can be resolved via getAnnotationByName. Returns the name of the annotation body created relative to the RO manifest and metadata directory. """ # Assemble data for annotation anngraph = rdflib.Graph() s = ro_manifest.getComponentUri(ro_dir, rofile) for k in attrdict: (p,t) = getAnnotationByName(ro_config, k, defaultType) anngraph.add((s, p, makeAnnotationValue(ro_config, attrdict[k],t))) # Write graph and return filename return createAnnotationGraphBody(ro_config, ro_dir, rofile, anngraph) def _addAnnotationBodyToRoGraph(ro_graph, ro_dir, rofile, annfile): """ Add a new annotation body to an RO graph ro_graph graph to which annotation is added ro_dir is the research object directory rofile is the research object file being annotated annfile is the base file name of the annotation body to be added """ # <ore:aggregates> # <ro:AggregatedAnnotation> # <ro:annotatesAggregatedResource rdf:resource="data/UserRequirements-astro.ods" /> # <ao:body rdf:resource=".ro/(annotation).rdf" /> # </ro:AggregatedAnnotation> # </ore:aggregates> ann = rdflib.BNode() ro_graph.add((ann, RDF.type, RO.AggregatedAnnotation)) ro_graph.add((ann, RO.annotatesAggregatedResource, ro_manifest.getComponentUri(ro_dir, rofile))) ro_graph.add((ann, AO.body, ro_manifest.getComponentUri(ro_dir, ro_settings.MANIFEST_DIR+"/"+annfile))) ro_graph.add((ro_manifest.getComponentUri(ro_dir, "."), ORE.aggregates, ann)) return def _removeAnnotationBodyFromRoGraph(ro_graph, annbody): """ Remove references to an annotation body from an RO graph ro_graph graph from which annotation is removed annbody is the the annotation body node to be removed """ ro_graph.remove((annbody, None, None )) ro_graph.remove((None, ORE.aggregates, annbody)) return def _addSimpleAnnotation(ro_config, ro_dir, rofile, attrname, attrvalue): """ Add a simple annotation to a file in a research object. ro_config is the research object manager configuration, supplied as a dictionary ro_dir is the research object root directory rofile names the file or resource to be annotated, possibly relative to the RO. attrname names the attribute in a form recognized by getAnnotationByName attrvalue is a value to be associated with the attribute """ annfile = createAnnotationBody(ro_config, ro_dir, rofile, { attrname: attrvalue} ) ro_graph = ro_manifest.readManifestGraph(ro_dir) _addAnnotationBodyToRoGraph(ro_graph, ro_dir, rofile, annfile) ro_manifest.writeManifestGraph(ro_dir, ro_graph) return def _removeSimpleAnnotation(ro_config, ro_dir, rofile, attrname, attrvalue): """ Remove a simple annotation or multiple matching annotations a research object. ro_config is the research object manager configuration, supplied as a dictionary ro_dir is the research object root directory rofile names the annotated file or resource, possibly relative to the RO. attrname names the attribute in a form recognized by getAnnotationByName attrvalue is the attribute value to be deleted, or Nomne to delete all vaues """ log.debug("removeSimpleAnnotation: ro_dir %s, rofile %s, attrname %s, attrvalue %s"% (ro_dir, rofile, attrname, attrvalue)) # Enumerate annotations # For each: # if annotation is only one in graph then: # remove aggregated annotation # else: # create new annotation graph witj annotation removed # update aggregated annotation ro_graph = ro_manifest.readManifestGraph(ro_dir) subject = ro_manifest.getComponentUri(ro_dir, rofile) (predicate,valtype) = getAnnotationByName(ro_config, attrname) val = attrvalue and makeAnnotationValue(ro_config, attrvalue, valtype) #@@TODO refactor common code with getRoAnnotations, etc. add_annotations = [] remove_annotations = [] for ann_node in ro_graph.subjects(predicate=RO.annotatesAggregatedResource, object=subject): ann_uri = ro_graph.value(subject=ann_node, predicate=AO.body) ann_graph = readAnnotationBody(ro_dir, ro_manifest.getComponentUriRel(ro_dir, ann_uri)) if (subject, predicate, val) in ann_graph: ann_graph.remove((subject, predicate, val)) if (subject, None, None) in ann_graph: # Triples remain in annotation body: write new body and update RO graph ann_name = createAnnotationGraphBody(ro_config, ro_dir, rofile, ann_graph) remove_annotations.append(ann_node) add_annotations.append(ann_name) else: # Remove annotation from RO graph remove_annotations.append(ann_node) # Update RO graph if needed if add_annotations or remove_annotations: for a in remove_annotations: _removeAnnotationBodyFromRoGraph(ro_graph, a) for a in add_annotations: _addAnnotationBodyToRoGraph(ro_graph, ro_dir, rofile, a) ro_manifest.writeManifestGraph(ro_dir, ro_graph) return def _replaceSimpleAnnotation(ro_config, ro_dir, rofile, attrname, attrvalue): """ Replace a simple annotation in a research object. ro_config is the research object manager configuration, supplied as a dictionary ro_dir is the research object root directory rofile names the file or resource to be annotated, possibly relative to the RO. attrname names the attribute in a form recognized by getAnnotationByName attrvalue is a new value to be associated with the attribute """ ro_graph = ro_manifest.readManifestGraph(ro_dir) subject = ro_manifest.getComponentUri(ro_dir, rofile) (predicate,valtype) = getAnnotationByName(ro_config, attrname) log.debug("Replace annotation: subject %s, predicate %s, value %s"%(repr(subject), repr(predicate), repr(attrvalue))) ro_graph.remove((subject, predicate, None)) ro_graph.add((subject, predicate, makeAnnotationValue(ro_config, attrvalue, valtype))) ro_manifest.writeManifestGraph(ro_dir, ro_graph) return def _getAnnotationValues(ro_config, ro_dir, rofile, attrname): """ Returns iterator over annotation values for given subject and attribute """ log.debug("getAnnotationValues: ro_dir %s, rofile %s, attrname %s"%(ro_dir, rofile, attrname)) ro_graph = ro_manifest.readManifestGraph(ro_dir) subject = ro_manifest.getComponentUri(ro_dir, rofile) (predicate,valtype) = getAnnotationByName(ro_config, attrname) #@@TODO refactor common code with getRoAnnotations, etc. for ann_node in ro_graph.subjects(predicate=RO.annotatesAggregatedResource, object=subject): ann_uri = ro_graph.value(subject=ann_node, predicate=AO.body) ann_graph = readAnnotationBody(ro_dir, ro_manifest.getComponentUriRel(ro_dir, ann_uri)) for v in ann_graph.objects(subject=subject, predicate=predicate): #log.debug("Triple: %s %s %s"%(subject,p,v)) yield v return def _getRoAnnotations(ro_dir): """ Returns iterator over annotations applied to the RO as an entity. Each value returned by the iterator is a (subject,predicate,object) triple. """ ro_graph = ro_manifest.readManifestGraph(ro_dir) subject = ro_manifest.getRoUri(ro_dir) log.debug("getRoAnnotations %s"%str(subject)) for ann_node in ro_graph.subjects(predicate=RO.annotatesAggregatedResource, object=subject): ann_uri = ro_graph.value(subject=ann_node, predicate=AO.body) ann_graph = readAnnotationBody(ro_dir, ro_manifest.getComponentUriRel(ro_dir, ann_uri)) if ann_graph: for (p, v) in ann_graph.predicate_objects(subject=subject): #log.debug("Triple: %s %s %s"%(subject,p,v)) yield (subject, p, v) return def _getFileAnnotations(ro_dir, rofile): """ Returns iterator over annotations applied to a specified component in the RO Each value returned by the iterator is a (subject,predicate,object) triple. """ log.debug("getFileAnnotations: ro_dir %s, rofile %s"%(ro_dir, rofile)) ro_graph = ro_manifest.readManifestGraph(ro_dir) subject = ro_manifest.getComponentUri(ro_dir, rofile) log.debug("getFileAnnotations: %s"%str(subject)) #@@TODO refactor common code with getRoAnnotations, etc. for ann_node in ro_graph.subjects(predicate=RO.annotatesAggregatedResource, object=subject): ann_uri = ro_graph.value(subject=ann_node, predicate=AO.body) ann_graph = readAnnotationBody(ro_dir, ro_manifest.getComponentUriRel(ro_dir, ann_uri)) if ann_graph: for (p, v) in ann_graph.predicate_objects(subject=subject): #log.debug("Triple: %s %s %s"%(subject,p,v)) yield (subject, p, v) return def getAllAnnotations(ro_dir): """ Returns iterator over all annotations associated with the RO Each value returned by the iterator is a (subject,predicate,object) triple. """ log.debug("getAllAnnotations %s"%str(ro_dir)) ro_graph = ro_manifest.readManifestGraph(ro_dir) #@@TODO refactor common code with getRoAnnotations, etc. for (ann_node, subject) in ro_graph.subject_objects(predicate=RO.annotatesAggregatedResource): ann_uri = ro_graph.value(subject=ann_node, predicate=AO.body) log.debug("- ann_uri %s"%(str(ann_uri))) ann_graph = readAnnotationBody(ro_dir, ro_manifest.getComponentUriRel(ro_dir, ann_uri)) if ann_graph == None: log.debug("No annotation graph: ann_uri: "+str(ann_uri)) else: for (p, v) in ann_graph.predicate_objects(subject=subject): #log.debug("Triple: %s %s %s"%(subject,p,v)) yield (subject, p, v) return def makeAnnotationValue(ro_config, aval, atype): """ atype is one of "string", "resurce", ... Returns a graph node for the supplied type and value """ #@@TODO: construct appropriately typed RDF literals if atype == "resource": return rdflib.URIRef(getResourceNameString(ro_config, aval)) if atype == "string": return rdflib.Literal(aval) if atype == "text": return rdflib.Literal(aval) if atype == "datetime": return rdflib.Literal(aval) return rdflib.Literal(aval) def formatAnnotationValue(aval, atype): """ atype is one of "string", "resurce", ... """ #@@TODO: deal with appropriately typed RDF literals if atype == "resource" or isinstance(aval,rdflib.URIRef): return '<' + str(aval) + '>' if atype == "string": return '"' + unicode(aval).encode('utf-8').replace('"', '\\"') + '"' if atype == "text": # multiline return '"""' + unicode(aval).encode('utf-8') + '"""' if atype == "datetime": return '"' + str(aval) + '"' return str(aval) def showAnnotations(ro_config, ro_dir, annotations, outstr): sname_prev = None for (asubj,apred,aval) in annotations: # log.debug("Annotations: asubj %s, apred %s, aval %s"% # (repr(asubj), repr(apred), repr(aval))) if apred != ORE.aggregates: (aname, atype) = getAnnotationByUri(ro_config, apred) sname = ro_manifest.getComponentUriRel(ro_dir, str(asubj)) log.debug("Annotations: sname %s, aname %s"%(sname, aname)) if sname == "": sname = ro_manifest.getRoUri(ro_dir) if sname != sname_prev: print "\n<"+str(sname)+">" sname_prev = sname outstr.write(" %s %s\n"%(aname, formatAnnotationValue(aval, atype))) return # End.

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0.680723

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5.518044

0.143966

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0.017792

0.016034

0.473418

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0.367018

0.310056

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null

0

null

0

1

0

1

0

2

969ffef1a03d4a66cdc882e7038aa21225221acf

5,508

py

Python

arxiv/integration/meta.py

ibnesayeed/arxiv-base

9f49302370272792a0afc78debd039d249844c6c

[ "MIT" ]

23

2019-01-10T22:01:18.000Z

2022-02-02T10:28:25.000Z

arxiv/integration/meta.py

ibnesayeed/arxiv-base

9f49302370272792a0afc78debd039d249844c6c

[ "MIT" ]

57

2018-12-17T16:45:38.000Z

2021-12-14T14:20:58.000Z

arxiv/integration/meta.py

cul-it/arxiv-base-ui

a5beadf44c24f72e21313299bfafc1ffb9d28ac7

[ "MIT" ]

5

2019-01-10T22:01:28.000Z

2021-11-05T12:25:31.000Z

"""Meta tools for integrations.""" import inspect from typing import Any class MetaIntegration(type): """ Metaclass for context-bound integrations. The purpose of this metaclass is to simplify writing integrations that need to attach to the application or request context. A typical pattern when using an integration's method is to first check for an instance of the integration on the current context, and then call the method on that instance. In practice, this means either performing the context check every time the method is used (yuck) or implementing module-level functions that wrap the integration class instance methods, and check the context when called (also yuck). Here's an example of what life was like back then: .. code-block:: python class FileManagementService(object): '''Encapsulates a connection with the file management service.''' def __init__(self, *args, **kwargs) -> None: ... def get_upload_status(self, upload_id: int) -> Upload: ... def init_app(app: object = None) -> None: '''Set default configuration params for an application instance.''' config = get_application_config(app) config.setdefault('FILE_MANAGER_ENDPOINT', 'https://arxiv.org/') config.setdefault('FILE_MANAGER_VERIFY', True) def get_session(app: object = None) -> FileManagementService: '''Get a new session with the file management endpoint.''' config = get_application_config(app) endpoint = config.get('FILE_MANAGER_ENDPOINT', 'https://arxiv.org/') verify_cert = config.get('FILE_MANAGER_VERIFY', True) return FileManagementService(endpoint, verify_cert=verify_cert) def current_session() -> FileManagementService: '''Get/create :class:`.FileManagementService` for this context.''' g = get_application_global() if not g: return get_session() elif 'filemanager' not in g: g.filemanager = get_session() # type: ignore return g.filemanager # type: ignore @wraps(FileManagementService.get_upload_status) def get_upload_status(upload_id: int) -> Upload: '''See :meth:`FileManagementService.get_upload_status`.''' return current_session().get_upload_status(upload_id) and then when you want to use it: .. code-block:: python from my.cool.services import filemanager filemanager.get_upload_status(59192) A better way ------------ Classes that use this metaclass are expected to implement a classmethod called ``current_session()`` that returns an instance of the class, similar to the example above. That method is responsible for getting the correct instance for the context. The net effect is that instance methods will be exposed as if they were class methods; behind the scenes, this metaclass will call ``current_session()`` and obtain the bound method from the returned instance. So you can do something like: .. code-block:: python class FileManagementService(metaclass=MetaIntegration): '''Encapsulates a connection with the file management service.''' def __init__(self, *args, **kwargs) -> None: ... def get_upload_status(self, upload_id: int) -> Upload: ... @classmethod def init_app(cls, app: object = None) -> None: '''Set default configuration params for an application instance.''' config = get_application_config(app) config.setdefault('FILE_MANAGER_ENDPOINT', 'https://arxiv.org/') config.setdefault('FILE_MANAGER_VERIFY', True) @classmethod def get_session(cls, app: object = None) -> 'FileManagementService': '''Get a new session with the file management endpoint.''' config = get_application_config(app) endpoint = config.get('FILE_MANAGER_ENDPOINT', 'https://arxiv.org/') verify_cert = config.get('FILE_MANAGER_VERIFY', True) return cls(endpoint, verify_cert=verify_cert) @classmethod def current_session(cls) -> 'FileManagementService': '''Get/create :class:`.FileManagementService` for this context.''' g = get_application_global() if not g: return cls.get_session() elif 'filemanager' not in g: g.filemanager = cls.get_session() # type: ignore return g.filemanager # type: ignore and then use it like: .. code-block:: python from my.cool.services.filemanager import FileManager FileManager.get_upload_status(59192) An even better way ------------------ The example above was only a marginal improvement. What would be better is not having to write any of those classmethods at all. For an example of what that looks like, see :class:`.api.service.HTTPIntegration`. """ def __getattribute__(self, key: str) -> Any: """Get the attribute from the instance bound to the current context.""" obj = super(MetaIntegration, self).__getattribute__(key) if inspect.isfunction(obj): return getattr(self.current_session(), key) return obj

37.216216

83

0.640523

640

5,508

5.38125

0.282813

0.020906

0.034843

0.02439

0.503484

0.450058

0.40302

0.350174

0

0.002489

0.270697

5,508

147

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37.469388

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0.871097

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0.125

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0

null

0

1

0

null

0

1

0

2

96ae59476203e369d22f45505c454269f030c9e1

1,168

py

Python

tests/repositories/test_integration_class.py

racelandshop/integration

424057dcad30f20ed0276aec07d28b48b2b187be

[ "MIT" ]

null

tests/repositories/test_integration_class.py

racelandshop/integration

424057dcad30f20ed0276aec07d28b48b2b187be

[ "MIT" ]

null

tests/repositories/test_integration_class.py

racelandshop/integration

424057dcad30f20ed0276aec07d28b48b2b187be

[ "MIT" ]

null

import pytest from custom_components.racelandshop.helpers.classes.exceptions import RacelandshopException @pytest.mark.asyncio async def test_async_post_installation(repository_integration, racelandshop): await repository_integration.async_post_installation() repository_integration.data.config_flow = True repository_integration.data.first_install = True racelandshop.hass.data["custom_components"] = {} await repository_integration.async_post_installation() @pytest.mark.asyncio async def test_async_post_registration(repository_integration): await repository_integration.async_post_registration() @pytest.mark.asyncio async def test_reload_custom_components(repository_integration, racelandshop): racelandshop.hass.data["custom_components"] = {} await repository_integration.reload_custom_components() @pytest.mark.asyncio async def test_validate_repository(repository_integration): with pytest.raises(RacelandshopException): await repository_integration.validate_repository() @pytest.mark.asyncio async def test_update_repository(repository_integration): await repository_integration.update_repository()

32.444444

91

0.832192

126

1,168

7.388889

0.261905

0.293233

0.167562

0.118153

0.549946

0.38131

0.214823

0

0.097603

1,168

35

92

33.371429

0.883302

0

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0

0.02911

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1

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true

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0

0.086957

0

null

1

0

null

0

1

0

2

96b89c05cc470150ee90158676e7c8b15141bf97

1,999

py

Python

custom-scorer/retrieve_and_rank_scorer/scorer_exception.py

al7e/answer-retrieval

bbca5f1511e855046000618777ce8392ef00e2f5

[ "Apache-2.0" ]

39

2016-07-18T15:32:02.000Z

2017-10-05T17:33:11.000Z

custom-scorer/retrieve_and_rank_scorer/scorer_exception.py

al7e/answer-retrieval

bbca5f1511e855046000618777ce8392ef00e2f5

[ "Apache-2.0" ]

27

2016-07-18T22:09:46.000Z

2017-08-04T08:37:38.000Z

custom-scorer/retrieve_and_rank_scorer/scorer_exception.py

al7e/answer-retrieval

bbca5f1511e855046000618777ce8392ef00e2f5

[ "Apache-2.0" ]

64

2016-07-18T14:56:47.000Z

2017-12-07T08:55:04.000Z

# Copyright 2016 IBM 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. class ScorerConfigurationException(Exception): """ Define exceptions to be used by various services. ScorerConfigurationException: Raised if a Scorer is improperly configured ScorerRuntimeException: Raised if a Scorer has a runtime error """ def __init__(self, message): """ Wrapper exception for configuration issues. Should be raised if: 1) Inputs to the constructor of a scorer are bad, 2) Invariant to scorer is violated etc. """ super(ScorerConfigurationException, self).__init__(message) # endclass ScorerConfigurationException class ScorerRuntimeException(Exception): def __init__(self, message): """ Wrapper exception for general runtime issues for a scorer. Should be raised if: 1) Input to an api method (likely .score) is invalid 2) Unforeseen problems prevent properly scoring a query, document, query/document pair """ super(ScorerRuntimeException, self).__init__(message) # endclass ScorerRuntimeException class ScorerTimeoutException(ScorerRuntimeException): def __init__(self, message, args, kwargs): """ Should be raised if a scorer times out """ super(ScorerTimeoutException, self).__init__(message) self._args = args self._kwargs = kwargs #endclass ScorerTimeoutException

39.196078

102

0.705853

236

1,999

5.868644

0.512712

0.043321

0.019495

0.032491

0.077978

0.05343

0

0.007792

0.229615

1,999

50

103

39.98

0.891558

0.637819

0

0.181818

0

1

0.272727

false

0

0.545455

0

null

0

null

0

1

0

1

0

2

96c22e564b0b34f67d76208eb69779ca5fad5e51

150

py

Python

curso-python/exercicios/exercicio-010.py

thiagoAlexandre3/cursos-auto-didata

2afb4f4bfe4a5622f2b5a9a5adbdc7e495ddf772

[ "MIT" ]

null

curso-python/exercicios/exercicio-010.py

thiagoAlexandre3/cursos-auto-didata

2afb4f4bfe4a5622f2b5a9a5adbdc7e495ddf772

[ "MIT" ]

null

curso-python/exercicios/exercicio-010.py

thiagoAlexandre3/cursos-auto-didata

2afb4f4bfe4a5622f2b5a9a5adbdc7e495ddf772

[ "MIT" ]

null

reais = float(input('Quantos reais você tem? R$ ')); dolar = reais * 5.81; print('Você tem {:.2f}R$ e pode comprar {:.2f}US$.'.format(reais, dolar));

37.5

74

0.633333

25

150

3.8

0.68

0.147368

0

0.03876

0.14

150

3

75

50

0.697674

0

0.466667

0

1

0

false

0

0.333333

1

0

null

0

1

0

null

0

2

73690bddedd826c29466aebe00b0e97e5a07f812

2,977

py

Python

script/python/devopstest.py

ibmcuijunluke/software-automation

9bc9ad78f1095983b6b46671482091489088cb15

[ "Apache-2.0" ]

2

2017-04-14T03:40:55.000Z

2018-04-25T11:12:51.000Z

script/python/devopstest.py

ibmcuijunluke/software-automation

9bc9ad78f1095983b6b46671482091489088cb15

[ "Apache-2.0" ]

null

script/python/devopstest.py

ibmcuijunluke/software-automation

9bc9ad78f1095983b6b46671482091489088cb15

[ "Apache-2.0" ]

1

2018-04-25T11:12:51.000Z

#!/usr/bin/python #-*-coding:UTF-8 -*- ''' Created on 20170407 @author: cui.jun@thoughtworks.cn ''' import sys,os,time #from tw_devops import zipfileutils print ("start deploy tomcat war and static zip package now ......."); tomcatwebapphome="/opt/apache-tomcat-8.0.41/webapps" webappswar="/opt/apache-tomcat-8.0.41/webapps/jw-interfaceapi.war" sourceunzip="/opt/apache-tomcat-8.0.41/webapps/jw-interfaceapi" targetjavawar="/opt/javawars"; tomcathome="/opt/apache-tomcat-8.0.41" zipfiledirfile = '/opt/javawars/html5demo.zip' warfiledirfile = '/opt/javawars/jw-interfaceapi.war' ngnixTargetDir="/opt/ngnixdir" current_date=time.strftime('%Y-%m-%d') current_datetime=time.strftime('%Y%m%d%H%M%S') #step 1 # print os.path.isfile(ngnix_zipfile_path) #check our env ngnixzipfile and tomcatwar packages if exist if os.path.isfile(zipfiledirfile): message = 'OK, the "%s" file exists.',current_datetime pass else: message = "Sorry, I cannot find the %s filee. ,pls create it" raise Exception("Sorry, I cannot find the file. %s ") #sys.exit() print "the message is ",message if os.path.isfile(warfiledirfile): message = 'OK, the "%s" file exists.',current_datetime pass else: message = "Sorry, I cannot find the %s file. ,pls create it" raise Exception("Sorry, I cannot find the s% file. %s ") #sys.exit() print "the message is ",message if os.path.isdir(ngnixTargetDir): message = 'OK, the "%s" ngnixfile dir exists.',current_datetime pass else: message = "Sorry, I cannot find the ngnixfile dir ,pls create it ." raise Exception("Sorry, I cannot find the ngnixfile dir. %s ") #sys.exit() print "the message is ",message #ngnixzipdir = 'html5-map.zip' # r = zipfilezipfileutilsfile(filename) #step 2 unzip zip file to ngnix dir and restart ngnix import zipfile import os #python2.7 zipfile libary has error, so i use python call shell. #os.listdir(r'E:\\apache-tomcat-8.0.41\\webapps\\') os.system("cp -f %s/html5demo.zip %s/" %(targetjavawar,ngnixTargetDir)); #os.system("cd %s" %(targetjavawar)) os.system("unzip -o -d %s %s" %(ngnixTargetDir,zipfiledirfile)) #os.system("/usr/nginx/sbin/nginx -t") #os.system("/usr/local/nginx/sbin/nginx -s reload") #/usr/nginx/sbin/nginx -t #/usr/local/nginx/sbin/nginx -s reload #step 3 restart tomcat new war print "start application server......begin............." kill_cmd="kill `ps -ef | grep tomcat | awk '{print $2,$8}' | grep 'java$'| awk '{print $1}'`"; os.system(kill_cmd); time.sleep(3); # os.system("rm -rf "); # time.sleep(3); os.system("rm -rf %s" %(webappswar)); os.system("rm -rf %s" %(sourceunzip)); os.system("cp -rf %s %s/" %(targetjavawar,tomcatwebapphome)); # time.sleep(3); os.system("%s/bin/startup.sh &" %(tomcathome)); #time.sleep(3); #Msg='-'*30+time.strftime('%Y-%m-%d %H:%M:%S')+'-'*30+'\n' #print " the time is ".Msg #time.sleep(2); print "start application server......end............."

32.714286

96

0.674169

445

2,977

4.48764

0.330337

0.044066

0.036054

0.048072

0.426139

0.384577

0.363545

0.284927

0.250876

0.210816

0

0.019201

0.142761

2,977

90

97

33.077778

0.763323

0.276789

0

0.23913

0

0.021739

0.482809

0.134625

0

null

0.065217

null

0.152174

0

null

0

null

0

1

0

1

0

2

736954c7128a50d71fe3df09fedd5e97a151c0f1

220

py

Python

djangoBlog/apps/config/urls.py

blackmonkey121/blog

938f104d3360c5f7562a2fd5a7d2f2e77c4695c0

[ "BSD-3-Clause" ]

4

2019-07-20T02:04:11.000Z

2020-05-02T06:15:22.000Z

djangoBlog/apps/config/urls.py

blackmonkey121/blog

938f104d3360c5f7562a2fd5a7d2f2e77c4695c0

[ "BSD-3-Clause" ]

8

2020-05-03T09:01:14.000Z

2022-01-13T02:13:14.000Z

djangoBlog/apps/config/urls.py

blackmonkey121/blog

938f104d3360c5f7562a2fd5a7d2f2e77c4695c0

[ "BSD-3-Clause" ]

null

#!usr/bin/env python3 # -*- coding: utf-8 -*- __author__ = "Monkey" from django.urls import path from ..config.views import FavoriteView urlpatterns = [ path('favorite/', FavoriteView.as_view(), name='favorite'), ]

22

63

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220

5.481481

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0

0.010526

0.136364

220

10

64

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7372f311335c86c86acbc9ebc4dc0e6b1e969875

240

py

Python

graphite_feeder/handler/event/appliance/sound/player/fade_out/volume.py

majamassarini/automate-graphite-feeder

0f17f99bbdaab86e10e0b7d424d055ff44fc4ca0

[ "MIT" ]

null

graphite_feeder/handler/event/appliance/sound/player/fade_out/volume.py

majamassarini/automate-graphite-feeder

0f17f99bbdaab86e10e0b7d424d055ff44fc4ca0

[ "MIT" ]

null

graphite_feeder/handler/event/appliance/sound/player/fade_out/volume.py

majamassarini/automate-graphite-feeder

0f17f99bbdaab86e10e0b7d424d055ff44fc4ca0

[ "MIT" ]

null

import home from graphite_feeder.handler.event.appliance.sound.player.volume import ( Handler as Parent, ) class Handler(Parent): KLASS = home.appliance.sound.player.event.fade_out.volume.Event TITLE = "Fade out volume (%)"

20

73

0.7375

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240

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0.5625

0.16

0.228571

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0.154167

240

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null

0

1

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null

0

1

0

2

7378d4aa72c88b68bc97ef203cf2c74074ba032f

747

py

Python

packages/pyright-internal/src/tests/samples/paramInference1.py

Jasha10/pyright

0ce0cfa10fe7faa41071a2cc417bb449cf8276fe

[ "MIT" ]

3,934

2019-03-22T09:26:41.000Z

2019-05-06T21:03:08.000Z

packages/pyright-internal/src/tests/samples/paramInference1.py

Jasha10/pyright

0ce0cfa10fe7faa41071a2cc417bb449cf8276fe

[ "MIT" ]

107

2019-03-24T04:09:37.000Z

2019-05-06T17:00:04.000Z

packages/pyright-internal/src/tests/samples/paramInference1.py

Jasha10/pyright

0ce0cfa10fe7faa41071a2cc417bb449cf8276fe

[ "MIT" ]

119

2019-03-23T10:48:04.000Z

2019-05-06T08:57:56.000Z

# This sample tests the logic that infers parameter types based on # default argument values or annotated base class methods. class Parent: def func1(self, a: int, b: str) -> float: ... class Child(Parent): def func1(self, a, b): reveal_type(self, expected_text="Self@Child") reveal_type(a, expected_text="int") reveal_type(b, expected_text="str") return a def func2(a, b=0, c=None): reveal_type(a, expected_text="Unknown") reveal_type(b, expected_text="int") reveal_type(c, expected_text="Unknown | None") def func3(a=(1, 2), b=[1,2], c={1: 2}): reveal_type(a, expected_text="Unknown") reveal_type(b, expected_text="Unknown") reveal_type(c, expected_text="Unknown")

26.678571

66

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747

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0.12

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0

null

0

1

0

null

0

1

0

2

7381e501735df140d94d4a45a5c60c1de5725216

790

py

Python

config/hooks/tk-multi-publish2/python/tk_multi_publish2/__init__.py

JoanAzpeitia/lp_sg

e0ee79555e419dd2ae3a5f31e5515b3f40b22a62

[ "MIT" ]

null

config/hooks/tk-multi-publish2/python/tk_multi_publish2/__init__.py

JoanAzpeitia/lp_sg

e0ee79555e419dd2ae3a5f31e5515b3f40b22a62

[ "MIT" ]

null

config/hooks/tk-multi-publish2/python/tk_multi_publish2/__init__.py

JoanAzpeitia/lp_sg

e0ee79555e419dd2ae3a5f31e5515b3f40b22a62

[ "MIT" ]

1

2020-02-15T10:42:56.000Z

# Copyright (c) 2017 Shotgun Software Inc. # # CONFIDENTIAL AND PROPRIETARY # # This work is provided "AS IS" and subject to the Shotgun Pipeline Toolkit # Source Code License included in this distribution package. See LICENSE. # By accessing, using, copying or modifying this work you indicate your # agreement to the Shotgun Pipeline Toolkit Source Code License. All rights # not expressly granted therein are reserved by Shotgun Software Inc. from sgtk.platform.qt import QtCore, QtGui import util def show_dialog(app): """ Show the main dialog ui :param app: The parent App """ # defer imports so that the app works gracefully in batch modes from .dialog import AppDialog # start ui app.engine.show_dialog("Shotgun Publish", app, AppDialog)

27.241379

76

0.737975

112

790

5.1875

0.651786

0.051635

0.061962

0.068847

0.151463

0

0.006369

0.205063

790

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null

0

null

0

1

0

1

0

2

73a3c87ffd5f26a101fd0f8dc6cc0997de70b24c

488

py

Python

atcoder/arc098/c.py

Ashindustry007/competitive-programming

2eabd3975c029d235abb7854569593d334acae2f

[ "WTFPL" ]

506

2018-08-22T10:30:38.000Z

2022-03-31T10:01:49.000Z

atcoder/arc098/c.py

Ashindustry007/competitive-programming

2eabd3975c029d235abb7854569593d334acae2f

[ "WTFPL" ]

13

2019-08-07T18:31:18.000Z

2020-12-15T21:54:41.000Z

atcoder/arc098/c.py

Ashindustry007/competitive-programming

2eabd3975c029d235abb7854569593d334acae2f

[ "WTFPL" ]

234

2018-08-06T17:11:41.000Z

2022-03-26T10:56:42.000Z

#!/usr/bin/env python3 # https://arc098.contest.atcoder.jp/tasks/arc098_a n = int(input()) s = input() a = [0] * n if s[0] == 'W': a[0] = 1 for i in range(1, n): c = s[i] if c == 'E': a[i] = a[i - 1] else: a[i] = a[i - 1] + 1 b = [0] * n if s[n - 1] == 'E': b[n - 1] = 1 for i in range(n - 2, -1, -1): c = s[i] if c == 'W': b[i] = b[i + 1] else: b[i] = b[i + 1] + 1 m = n for i in range(n): m = min(m, a[i] + b[i]) print(m - 1)

19.52

50

0.403689

106

488

1.849057

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0.091837

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0.352041

0

0.080997

0.342213

488

24

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20.333333

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0

1

null

0

1

0

null

0

2

73b72fbb308f8fd4a86c4a19d3cc88d7dc9cbdb7

405

py

Python

MyPythonDemos2018/SimpleDemos/a05_classmethod.py

zcatt/MyDemos2018

a332fdf94170663ba7a530cedc28418159a1c29a

[ "MIT" ]

null

MyPythonDemos2018/SimpleDemos/a05_classmethod.py

zcatt/MyDemos2018

a332fdf94170663ba7a530cedc28418159a1c29a

[ "MIT" ]

null

MyPythonDemos2018/SimpleDemos/a05_classmethod.py

zcatt/MyDemos2018

a332fdf94170663ba7a530cedc28418159a1c29a

[ "MIT" ]

null

#!/usr/bin/python3 # -*- coding: utf-8 -*- """ class C: @classmethod def f(cls, arg1, arg2, ...): ... 类方法传入的第一个参数不是instance的self，而是类cls. """ class C: @classmethod def createC(cls, value): obj= cls(value) return obj def __init__(self, value): self.v= value def output(self): print("value= {0:d}".format(self.v)) c = C.createC(3) c.output()

16.2

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405

4.269231

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0.18018

0

0.020067

0.261728

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24

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null

0

1

0

null

0

1

0

2

73bdf2c124efa5c0ddad9b7c311bbec5c90bc4d5

4,304

py

Python

src/meteringpoints_shared/models.py

Energy-Track-and-Trace/ett-meteringpoints

75f5a10a55b1ee450e53986db1bf70a23ea82a3f

[ "Apache-2.0" ]

null

src/meteringpoints_shared/models.py

Energy-Track-and-Trace/ett-meteringpoints

75f5a10a55b1ee450e53986db1bf70a23ea82a3f

[ "Apache-2.0" ]

null

src/meteringpoints_shared/models.py

Energy-Track-and-Trace/ett-meteringpoints

75f5a10a55b1ee450e53986db1bf70a23ea82a3f

[ "Apache-2.0" ]

null

import sqlalchemy as sa from enum import Enum from typing import List, Optional from dataclasses import dataclass, field from sqlalchemy.orm import relationship from origin.serialize import Serializable from origin.models.tech import TechnologyType from origin.models.common import ResultOrdering from origin.models.meteringpoints import MeteringPointType from .db import db # -- Common models ----------------------------------------------------------- @dataclass class MeteringPointFilters(Serializable): """ Filters for querying MeteringPoints. """ gsrn: Optional[List[str]] = field(default=None) type: Optional[MeteringPointType] = field(default=None) sector: Optional[List[str]] = field(default=None) class MeteringPointOrderingKeys(Enum): """ Keys to order MeteringPoints by when querying. """ gsrn = 'gsrn' type = 'type' sector = 'sector' MeteringPointOrdering = ResultOrdering[MeteringPointOrderingKeys] # -- Database models --------------------------------------------------------- class DbMeteringPoint(db.ModelBase): """ SQL representation of a MeteringPoint. """ __tablename__ = 'meteringpoint' __table_args__ = ( sa.PrimaryKeyConstraint('gsrn'), sa.UniqueConstraint('gsrn'), ) gsrn = sa.Column(sa.String(), index=True, nullable=False) sector = sa.Column(sa.String(), index=True) type = sa.Column(sa.Enum(MeteringPointType), index=True) # -- Relationships ------------------------------------------------------- address = relationship( 'DbMeteringPointAddress', primaryjoin='foreign(DbMeteringPoint.gsrn) == DbMeteringPointAddress.gsrn', # noqa: E501 uselist=False, viewonly=True, lazy='joined', ) # TODO Rewrite this? technology = relationship( 'DbTechnology', primaryjoin='foreign(DbMeteringPoint.gsrn) == DbMeteringPointTechnology.gsrn', # noqa: E501 secondary='meteringpoint_technology', secondaryjoin=( 'and_(' 'foreign(DbMeteringPointTechnology.tech_code) == DbTechnology.tech_code,' # noqa: E501 'foreign(DbMeteringPointTechnology.fuel_code) == DbTechnology.fuel_code' # noqa: E501 ')' ), uselist=False, viewonly=True, lazy='joined', ) class DbMeteringPointAddress(db.ModelBase): """ SQL representation of a (physical) address for a MeteringPoint. """ __tablename__ = 'meteringpoint_address' __table_args__ = ( sa.PrimaryKeyConstraint('gsrn'), sa.UniqueConstraint('gsrn'), ) gsrn = sa.Column(sa.String(), index=True, nullable=False) street_code = sa.Column(sa.String()) street_name = sa.Column(sa.String()) building_number = sa.Column(sa.String()) floor_id = sa.Column(sa.String()) room_id = sa.Column(sa.String()) post_code = sa.Column(sa.String()) city_name = sa.Column(sa.String()) city_sub_division_name = sa.Column(sa.String()) municipality_code = sa.Column(sa.String()) location_description = sa.Column(sa.String()) class DbMeteringPointTechnology(db.ModelBase): """ SQL representation of technology codes for a MeteringPoint. """ __tablename__ = 'meteringpoint_technology' __table_args__ = ( sa.PrimaryKeyConstraint('gsrn'), sa.UniqueConstraint('gsrn'), ) gsrn = sa.Column(sa.String(), index=True, nullable=False) tech_code = sa.Column(sa.String()) fuel_code = sa.Column(sa.String()) class DbMeteringPointDelegate(db.ModelBase): """ TODO """ __tablename__ = 'meteringpoint_delegate' __table_args__ = ( sa.PrimaryKeyConstraint('gsrn', 'subject'), ) gsrn = sa.Column(sa.String(), index=True, nullable=False) subject = sa.Column(sa.String()) class DbTechnology(db.ModelBase): """ SQL representation of a Technology. """ __tablename__ = 'technology' __table_args__ = ( sa.PrimaryKeyConstraint('tech_code', 'fuel_code'), sa.UniqueConstraint('tech_code', 'fuel_code'), ) fuel_code = sa.Column(sa.String()) tech_code = sa.Column(sa.String()) # TODO Use String instead of Enum (forward compatibility) type = sa.Column(sa.Enum(TechnologyType))

28.693333

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0.643123

423

4,304

6.368794

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0.081663

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0.202602

4,304

149

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0

null

0

null

0

1

0

1

0

2

73e84c9135bab7ac7be004011cc3b757ccc4b119

4,168

py

Python

reference-architecture/day2ops/scripts/ocp36-sat6.py

rafael-sales/openshift-ansible-contrib

627c8b1856699cf25c7adca074f26ff899ddd4fd

[ "Apache-2.0" ]

null

reference-architecture/day2ops/scripts/ocp36-sat6.py

rafael-sales/openshift-ansible-contrib

627c8b1856699cf25c7adca074f26ff899ddd4fd

[ "Apache-2.0" ]

null

reference-architecture/day2ops/scripts/ocp36-sat6.py

rafael-sales/openshift-ansible-contrib

627c8b1856699cf25c7adca074f26ff899ddd4fd

[ "Apache-2.0" ]

1

2019-09-22T19:10:41.000Z

#!/usr/bin/env python # vim: sw=4 ts=4 et import os, argparse, socket, getpass, subprocess class ocpSat6(object): __name__ = 'ocpSat6' openshift3Images=[] def __init__(self, load=True): if load: self._parseCli() self._loadImageList() self._addData() self._syncData() def _loadImageList(self): cmd='curl -s https://registry.access.redhat.com/v1/search?q="openshift3" | python -mjson.tool | grep ".name.:" | cut -d: -f2 | sed -e "s/ "//g"" -e "s/,"//g"" | grep -E \'(ose-haproxy-router|registry-console|ose-deployer|ose-pod|ose-docker-registry)\'' result = subprocess.check_output(cmd, shell=True) lines = result.splitlines() for line in lines: nl = line.replace('"', '') self.openshift3Images.append(nl) def _parseCli(self): parser = argparse.ArgumentParser(description='Add all OCP images for disconnected installation to satellite 6', add_help=True) parser.add_argument('--orgid', action='store', default='1',help='Satellite organization ID to create new product for OCP images in') parser.add_argument('--productname', action='store', default='ocp36',help='Satellite product name to use to create OCP images') parser.add_argument('--username', action='store', default='admin', help='Satellite 6 username for hammer CLI') parser.add_argument('--password', action='store', help='Satellite 6 Password for hammer CLI') parser.add_argument('--no_confirm', action='store_true', help='Do not ask for confirmation') self.args = parser.parse_args() if not self.args.password: self.args.password = getpass.getpass(prompt='Please enter the password to use for the admin account in hammer CLI: ') def _syncData(self): if not self.args.no_confirm: print "Sync repo data? (This may take a while)" go = raw_input("Continue? y/n:\n") if 'y' not in go: exit(0) cmd="hammer --username %s --password %s product synchronize --name %s --organization-id %s" % (self.args.username, self.args.password, self.args.productname, self.args.orgid) os.system(cmd) def _addData(self): if not self.args.no_confirm: print "Adding OCP images to org ID: %s with the product name: %s" % (self.args.orgid, self.args.productname) go = raw_input("Continue? y/n:\n") if 'y' not in go: exit(0) print "Adding product with name: %s" % self.args.productname cmd="hammer --username %s --password %s product create --name %s --organization-id %s" % (self.args.username, self.args.password, self.args.productname, self.args.orgid) os.system(cmd) print "Adding openshift3 images" for image in self.openshift3Images: cmd='hammer --username %s --password %s repository create --name %s --organization-id %s --content-type docker --url "https://registry.access.redhat.com" --docker-upstream-name %s --product %s' % (self.args.username, self.args.password, image, self.args.orgid, image, self.args.productname ) os.system(cmd) print "The following vars should exist in your OpenShift install playbook" cmd="hammer --username %s --password %s organization list" % (self.args.username, self.args.password) result = subprocess.check_output(cmd, shell=True) lines = result.splitlines() for line in lines: if self.args.orgid in line: orgLabel = line.split("|")[2].lower() hostname = socket.getfqdn() oreg_url = "%s-%s-openshift3_ose-${component}:${version}" % ( orgLabel, self.args.productname ) print "oreg_url: %s" % ( oreg_url.replace(" ", "")) print 'openshift_disable_check: "docker_image_availability"' print 'openshift_docker_insecure_registries: "%s:5000"' % hostname print 'openshift_docker_additional_registries: "%s:5000"' % hostname print "openshift_examples_modify_imagestreams: True" if __name__ == '__main__': ocpSat6()

48.465116

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0.799253

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null

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null

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null

0

null

0

1

0

1

0

2

fb417c8637a28bbf828561b30c84658f308e31f8

892

py

Python

quaternary_FOM_stackedtern_demo.py

johnmgregoire/PythonCompositionPlots

e105c575463b7d4512d9aac18c7330d1a0dc2c14

[ "BSD-3-Clause" ]

4

2018-03-05T09:34:49.000Z

2022-02-01T15:33:54.000Z

quaternary_FOM_stackedtern_demo.py

johnmgregoire/PythonCompositionPlots

e105c575463b7d4512d9aac18c7330d1a0dc2c14

[ "BSD-3-Clause" ]

null

quaternary_FOM_stackedtern_demo.py

johnmgregoire/PythonCompositionPlots

e105c575463b7d4512d9aac18c7330d1a0dc2c14

[ "BSD-3-Clause" ]

2

2016-01-24T19:09:21.000Z

2019-10-11T12:43:07.000Z

import matplotlib.cm as cm import numpy import pylab import operator, copy, os from myternaryutility import TernaryPlot from myquaternaryutility import QuaternaryPlot from quaternary_FOM_stackedtern import * axl, stpl=make10ternaxes() gridi=30 comps_10full=[(a*1./gridi, b*1./gridi, c*1./gridi, (gridi-a-b-c)*1./gridi) for a in numpy.arange(0,1+gridi) for b in numpy.arange(0,1+gridi-a) for c in numpy.arange(0,1+gridi-a-b)] comps_10full=list(set(comps_10full)) print len(comps_10full) #plotpoints_cmyk comps_10full=numpy.array(comps_10full) pylab.figure() stpquat=QuaternaryPlot(111) cols=stpquat.rgb_comp(comps_10full) stpquat.scatter(comps_10full, c=cols, s=20, edgecolors='none') scatter_10axes(comps_10full, cols, stpl, s=20, edgecolors='none') stpquat.label() pylab.savefig('stackedtern_quat.png') pylab.figure(axl[0].figure.number) pylab.savefig('stackedtern.png') pylab.show()

27.875

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0.784753

143

892

4.79021

0.398601

0.144526

0.056934

0.061314

0.090511

0.061314

0

0.05122

0.080717

892

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null

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null

0

null

0

1

0

1

0

2

fb53099647d1f5af1a16d37c6eb0d5b68a9badc9

191

py

Python

app/data/mysql_cfg.py

cyy0523xc/fastapi-start

3cc6e0165cc32895b48f4864e12a14b08f42a1e2

[ "Apache-2.0" ]

9

2021-08-16T03:44:54.000Z

2022-03-31T08:54:10.000Z

app/data/mysql_cfg.py

cyy0523xc/fastapi-start

3cc6e0165cc32895b48f4864e12a14b08f42a1e2

[ "Apache-2.0" ]

2

2021-08-18T14:01:09.000Z

2021-11-05T06:46:11.000Z

app/data/mysql_cfg.py

cyy0523xc/fastapi-start

3cc6e0165cc32895b48f4864e12a14b08f42a1e2

[ "Apache-2.0" ]

3

2021-06-08T02:29:09.000Z

2022-02-25T01:34:05.000Z

# MYSQL数据库配置 # 通常在不同环境下配置是不一样的，根据实际情况进行修改 MYSQL_CFG = { 'HOST': '172.17.0.1', 'PORT': 3306, 'USERNAME': 'username', 'PASSWORD': 'password', 'DATABASE': 'database_name' }

17.363636

31

0.60733

19

191

6

0.842105

0

0.072368

0.204188

191

10

32

19.1

0.677632

0.193717

0

0.473333

0

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false

0.142857

0

1

0

null

0

null

0

1

0

2

fb57d9f989a9d8ee0bc2a1d294116b7862ea2de2

7,214

py

Python

model.py

titee15017/CarND-Behavioral-Cloning-P3

3eee75bcda92519a1f94547ac1a9256e5e3c6a7f

[ "MIT" ]

null

model.py

titee15017/CarND-Behavioral-Cloning-P3

3eee75bcda92519a1f94547ac1a9256e5e3c6a7f

[ "MIT" ]

null

model.py

titee15017/CarND-Behavioral-Cloning-P3

3eee75bcda92519a1f94547ac1a9256e5e3c6a7f

[ "MIT" ]

null

import csv import cv2 import numpy as np images = [] measurements = [] correction = 0.2 corrections = [0, correction, -correction] print('start processing data') print('1st data, normal lap') lines = [] with open('data/driving_log.csv') as csvfile: reader = csv.reader(csvfile) for line in reader: lines.append(line) for i in range(1,len(lines)): # drop most of 0 angle, so model will not be train on a lot of 0 if ((float(lines[i][3]) == 0.0) and (np.random.rand(1)[0] > 0.90) or (float(lines[i][3]) != 0.0)): for j in range(3): source_path = lines[i][j] filename = source_path.split('/')[-1] current_path = 'data/IMG/' + filename image = cv2.imread(current_path) measurement = float(lines[i][3]) + corrections[j] images.append(image) measurements.append(measurement) image_flipped = np.fliplr(image) measurement_flipped = -measurement images.append(image_flipped) measurements.append(measurement_flipped) print('2nd data, prevent off road') lines = [] with open('data_off_road_1/driving_log.csv') as csvfile: reader = csv.reader(csvfile) for line in reader: lines.append(line) for i in range(1,len(lines)): # drop most of 0 angle, so model will not be train on a lot of 0 if ((float(lines[i][3]) == 0.0) and (np.random.rand(1)[0] > 0.90) or (float(lines[i][3]) != 0.0)): for j in range(3): source_path = lines[i][j] filename = source_path.split('/')[-1] current_path = 'data_off_road_1/IMG/' + filename image = cv2.imread(current_path) measurement = float(lines[i][3]) + corrections[j] images.append(image) measurements.append(measurement) image_flipped = np.fliplr(image) measurement_flipped = -measurement images.append(image_flipped) measurements.append(measurement_flipped) print('3th data, prevent off road') lines = [] with open('data_off_road_2/driving_log.csv') as csvfile: reader = csv.reader(csvfile) for line in reader: lines.append(line) for i in range(1,len(lines)): # drop most of 0 angle, so model will not be train on a lot of 0 if ((float(lines[i][3]) == 0.0) and (np.random.rand(1)[0] > 0.90) or (float(lines[i][3]) != 0.0)): for j in range(3): source_path = lines[i][j] filename = source_path.split('/')[-1] current_path = 'data_off_road_2/IMG/' + filename image = cv2.imread(current_path) measurement = float(lines[i][3]) + corrections[j] images.append(image) measurements.append(measurement) image_flipped = np.fliplr(image) measurement_flipped = -measurement images.append(image_flipped) measurements.append(measurement_flipped) print('4th data, recovering') lines = [] with open('data_recovering/driving_log.csv') as csvfile: reader = csv.reader(csvfile) for line in reader: lines.append(line) for i in range(1,len(lines)): # remove angle between -1 to 1, prevent influence to center lane data set if ((float(lines[i][3]) > 1.0) or (float(lines[i][3]) < -1.0)): for j in range(3): source_path = lines[i][j] filename = source_path.split('/')[-1] current_path = 'data_recovering/IMG/' + filename image = cv2.imread(current_path) measurement = float(lines[i][3]) + corrections[j] images.append(image) measurements.append(measurement) image_flipped = np.fliplr(image) measurement_flipped = -measurement images.append(image_flipped) measurements.append(measurement_flipped) print('done processing data') print('start trainning') X_train = np.array(images) y_train = np.array(measurements) from keras.models import Sequential from keras.layers import Flatten, Dense, Lambda, Cropping2D, Dropout from keras.layers.convolutional import Convolution2D from keras.layers.pooling import MaxPooling2D model = Sequential() # Normalize model.add(Lambda(lambda x: x / 255.0 - 0.5, input_shape=(160,320,3))) # Crop, input shape (160, 320, 3), output shape (60, 320, 3) model.add(Cropping2D(cropping=((70,26),(0,0)))) # Convolution layer 1, input shape (64, 320, 3), filtter shape (3, 3, 8), output shape (64, 320, 8) model.add(Convolution2D(8, 3, strides=1, activation="relu", padding="same")) # MaxPooling, input shape (64, 320, 8), output shape (32, 160, 8) model.add(MaxPooling2D(pool_size=(2, 2))) # Convolution layer 2, input shape (32, 160, 8), filtter shape (3, 3, 16), output shape (32, 160, 16) model.add(Convolution2D(16, 3, strides=1, activation="relu", padding="same")) # MaxPooling, input shape (32, 160, 16), output shape (16, 80, 16) model.add(MaxPooling2D(pool_size=(2, 2))) # Convolution layer 3, input shape (16, 80, 16), filtter shape (3, 3, 32), output shape (16, 80, 32) model.add(Convolution2D(32, 3, strides=1, activation="relu", padding="same")) # Convolution layer 4, input shape (16, 80, 32), filtter shape (3, 3, 32), output shape (16, 80, 32) model.add(Convolution2D(32, 3, strides=1, activation="relu", padding="same")) # MaxPooling, input shape (16, 80, 32), output shape (8, 40, 32) model.add(MaxPooling2D(pool_size=(2, 2))) # Convolution layer 5, input shape (8, 40, 32), filtter shape (3, 3, 64), output shape (8, 40, 64) model.add(Convolution2D(64, 3, strides=1, activation="relu", padding="same")) # Convolution layer 6, input shape (8, 40, 64), filtter shape (3, 3, 64), output shape (8, 40, 64) model.add(Convolution2D(64, 3, strides=1, activation="relu", padding="same")) # MaxPooling, input shape (8, 40, 64), output shape (4, 20, 64) model.add(MaxPooling2D(pool_size=(2, 2))) # Convolution layer 7, input shape (4, 20, 64), filtter shape (3, 3, 64), output shape (4, 20, 64) model.add(Convolution2D(64, 3, strides=1, activation="relu", padding="same")) # Convolution layer 8, input shape (4, 20, 64), filtter shape (3, 3, 64), output shape (4, 20, 64) model.add(Convolution2D(64, 3, strides=1, activation="relu", padding="same")) # MaxPooling, input shape (4, 20, 64), output shape (2, 10, 64) model.add(MaxPooling2D(pool_size=(2, 2))) # Flatten, input shape (2, 10, 64), output shape (1280) model.add(Flatten()) # Fully connected layer 9, input shape (1280), output shape (1280) model.add(Dense(1280)) # Dropout rate 50% model.add(Dropout(0.5)) # Fully connected layer 10, input shape (1280), output shape (1280) model.add(Dense(640)) # Dropout rate 50% model.add(Dropout(0.5)) # Fully connected layer 11, input shape (1000), output shape (1) model.add(Dense(1)) # Compute loss by mean squared error, Optimize by adam model.compile(loss='mse', optimizer='adam') # Split training/validation by 80/20, shuffle data, number of epoch is 10 model.fit(X_train, y_train, validation_split=0.2, shuffle=True, nb_epoch=10) print('done trainning') print('save model') model.save('model.h5')

37.968421

102

0.64153

1,046

7,214

4.365201

0.159656

0.036794

0.028909

0.031537

0.726675

0.70346

0.697547

0.686159

0.62396

0

0.073322

0.215414

7,214

189

103

38.169312

0.733392

0.254505

0

0.650407

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0.081713

0.01739

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1

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false

0

0.056911

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0.056911

0.073171

0

null

0

1

0

1

0

null

0

2

fb6bd21508d4eb474f730a7550657d5737bd35b1

105

py

Python

inputCleaner/inputCleaner.py

ChristopherMichael-Stokes/AdventOfCode2021

871883c3e8b98c4f229429c2aab5beee5ec70f85

[ "BSD-2-Clause" ]

null

inputCleaner/inputCleaner.py

ChristopherMichael-Stokes/AdventOfCode2021

871883c3e8b98c4f229429c2aab5beee5ec70f85

[ "BSD-2-Clause" ]

null

inputCleaner/inputCleaner.py

ChristopherMichael-Stokes/AdventOfCode2021

871883c3e8b98c4f229429c2aab5beee5ec70f85

[ "BSD-2-Clause" ]

null

import os with open('./input.txt', 'r') as f: data = f.readlines() print(''.join(data).__repr__())

15

35

0.6

16

105

3.6875

0.875

0

0.161905

105

6

36

17.5

0.670455

0

0.114286

0

1

0

false

0

0.25

0

0.25

1

0

null

0

1

0

null

0

2

fb6f0b8f0f841779ddf08babd88330bb9c34aeee

1,275

py

Python

exercises/reverse_number.py

R0bertWell/interview_questions

f8a65a842dfe03ac28c865bb8370422ff2071137

[ "MIT" ]

null

exercises/reverse_number.py

R0bertWell/interview_questions

f8a65a842dfe03ac28c865bb8370422ff2071137

[ "MIT" ]

null

exercises/reverse_number.py

R0bertWell/interview_questions

f8a65a842dfe03ac28c865bb8370422ff2071137

[ "MIT" ]

null

def reverse_num(x: int) -> int : if x == 0: return 0 else: num_temp = str(x) tam = len(num_temp) num_zeros = 0 if num_temp[0] == "-": if num_temp[tam - 1] == "0": dici = {"0": 0} for value in num_temp[:1:-1]: if value in dici: dici[value] += 1 num_zeros += 1 else: break num_temp = num_temp[tam-num_zeros:0:-1] x = (int(num_temp)) * -1 else: num_temp = num_temp[:0:-1] x = (int(num_temp)) * -1 else: if num_temp[tam - 1] == "0": dici = {"0": 0} for value in num_temp[::-1]: if value in dici: dici[value] += 1 num_zeros += 1 else: break num_temp = num_temp[tam-num_zeros::-1] x = (int(num_temp)) else: x = int(num_temp[::-1]) if x > (2 ** 31 - 1) or x < (-2 ** 31): return 0 else: return x if __name__ == "__main__": print(reverse_num(65090))

30.357143

55

0.359216

148

1,275

2.878378

0.182432

0.279343

0.093897

0.103286

0.631455

0.575117

0.49061

0

0.065359

0.52

1,275

42

56

30.357143

0.630719

0

0.575

0

0.010188

0

1

0.025

false

0

0.1

0.025

0

null

1

0

1

0

null

0

2

fba0ad79b9f393dc2c78c71f0640de95743488c4

2,673

py

Python

backend/app/literature/routers/reference_manual_term_tag_router.py

alliance-genome/agr_literature_service_demo

48cd3a3797f96ef94e6d40d2c94e379bfc48914f

[ "MIT" ]

null

backend/app/literature/routers/reference_manual_term_tag_router.py

alliance-genome/agr_literature_service_demo

48cd3a3797f96ef94e6d40d2c94e379bfc48914f

[ "MIT" ]

null

backend/app/literature/routers/reference_manual_term_tag_router.py

alliance-genome/agr_literature_service_demo

48cd3a3797f96ef94e6d40d2c94e379bfc48914f

[ "MIT" ]

null

from sqlalchemy.orm import Session from fastapi import APIRouter from fastapi import Depends from fastapi import status from fastapi import Response from fastapi import Security from fastapi_okta import OktaUser from literature import database from literature.user import set_global_user_id from literature.schemas import ReferenceManualTermTagSchemaShow from literature.schemas import ReferenceManualTermTagSchemaPost from literature.schemas import ReferenceManualTermTagSchemaPatch from literature.schemas import ResponseMessageSchema from literature.crud import reference_manual_term_tag_crud from literature.routers.authentication import auth router = APIRouter( prefix="/reference_manual_term_tag", tags=['Reference Manual Term Tag'] ) get_db = database.get_db @router.post('/', status_code=status.HTTP_201_CREATED, response_model=str) def create(request: ReferenceManualTermTagSchemaPost, user: OktaUser = Security(auth.get_user), db: Session = Depends(get_db)): set_global_user_id(db, user.id) return reference_manual_term_tag_crud.create(db, request) @router.delete('/{reference_manual_term_tag_id}', status_code=status.HTTP_204_NO_CONTENT) def destroy(reference_manual_term_tag_id: int, user: OktaUser = Security(auth.get_user), db: Session = Depends(get_db)): set_global_user_id(db, user.id) reference_manual_term_tag_crud.destroy(db, reference_manual_term_tag_id) return Response(status_code=status.HTTP_204_NO_CONTENT) @router.patch('/{reference_manual_term_tag_id}', status_code=status.HTTP_202_ACCEPTED, response_model=ResponseMessageSchema) async def patch(reference_manual_term_tag_id: int, request: ReferenceManualTermTagSchemaPatch, user: OktaUser = Security(auth.get_user), db: Session = Depends(get_db)): set_global_user_id(db, user.id) patch = request.dict(exclude_unset=True) return reference_manual_term_tag_crud.patch(db, reference_manual_term_tag_id, patch) @router.get('/{reference_manual_term_tag_id}', response_model=ReferenceManualTermTagSchemaShow, status_code=200) def show(reference_manual_term_tag_id: int, db: Session = Depends(get_db)): return reference_manual_term_tag_crud.show(db, reference_manual_term_tag_id) @router.get('/{reference_manual_term_tag_id}/versions', status_code=200) def show(reference_manual_term_tag_id: int, db: Session = Depends(get_db)): return reference_manual_term_tag_crud.show_changesets(db, reference_manual_term_tag_id)

33.4125

91

0.75982

339

2,673

5.640118

0.19469

0.156904

0.198745

0.230126

0.478556

0.45136

0.330021

0.27249

0.226464

0

0.00809

0.167602

2,673

79

92

33.835443

0.851236

0

0.263158

0

0.069211

0.059484

0

1

0.070175

false

0

0.263158

0.035088

0.421053

0

null

0

1

0

null

0

2

fba237db49b2b835cdcad396506066991e50a95b

2,087

py

Python

backend/app/apps/authentication/views.py

Hesbon5600/hotel-recommender

f0048bdc25e212b218ded8413977242429ff4b90

[ "MIT" ]

null

backend/app/apps/authentication/views.py

Hesbon5600/hotel-recommender

f0048bdc25e212b218ded8413977242429ff4b90

[ "MIT" ]

1

2021-04-08T20:07:39.000Z

backend/app/apps/authentication/views.py

Hesbon5600/hotel-recommender

f0048bdc25e212b218ded8413977242429ff4b90

[ "MIT" ]

null

from django.views.generic import CreateView, FormView from django.conf import settings from django.shortcuts import render, redirect, reverse from django.urls import reverse_lazy from django.contrib.auth import authenticate, login, logout from django.contrib import messages from django.core.mail import send_mail from .models import User from .forms import UserSignupForm, UserLoginForm class UserRegistrationCreateView(FormView): """ Create user api view """ model = User form_class = UserSignupForm template_name = 'authentication/signup.html' def post(self, request): """ Overide the default post() """ form = self.form_class(request.POST) if not form.is_valid(): return render(request, self.template_name, {"form": form}) data = { "first_name": form.cleaned_data['first_name'], "last_name": form.cleaned_data['last_name'], "password": form.cleaned_data['password'], "email": form.cleaned_data['email'], } User.objects.create_user(**data) return redirect(reverse('authentication:login')) class UserLoginCreateView(FormView): """ Create user api view """ model = User form_class = UserLoginForm template_name = 'authentication/login.html' success_url = reverse_lazy("hotels:list-hotels") def post(self, request): """ Overide the default post() # """ form = self.form_class(request.POST) email = request.POST['username'] password = request.POST['password'] user = authenticate(request, email=email, password=password) if user and user.is_active: login(request, user) return super(UserLoginCreateView, self).form_valid(form) messages.success( request, 'This email and password combination is invalid', extra_tags='red') return render(request, self.template_name, {"form": form}) def logout_view(request): logout(request) return redirect('authentication:login')

31.621212

88

0.659799

233

2,087

5.798283

0.321888

0.051813

0.044412

0.031088

0.226499

0.162842

0.099186

0

0.235745

2,087

65

89

32.107692

0.847022

0.046478

0

0.181818

0

0.128594

0.02666

0

1

0.068182

false

0.090909

0.204545

0

0.590909

0

null

0

null

0

1

0

1

0

2

fba5400c53eb75375a556ae72c212f65831ee73d

911

py

Python

com/banma/test/test5.py

liuyangyang2015/PythonDemo

a72c009a31ff833dd12405bb97e688ae91ceda6c

[ "MIT" ]

null

com/banma/test/test5.py

liuyangyang2015/PythonDemo

a72c009a31ff833dd12405bb97e688ae91ceda6c

[ "MIT" ]

null

com/banma/test/test5.py

liuyangyang2015/PythonDemo

a72c009a31ff833dd12405bb97e688ae91ceda6c

[ "MIT" ]

null

# class Chain(object): # # def __init__(self, path=''): # self._path = path # # def __getattr__(self, path): # return Chain('%s/%s' % (self._path, path)) # # def __str__(self): # return self._path # # __repr__ = __str__ # # print(Chain().status.user.timeline.list) # # from enum import Enum, unique # # @unique # class Weekday(Enum): # Sun = 0 # Sun的value被设定为0 # Mon = 1 # Tue = 2 # Wed = 8 # Thu = 4 # Fri = 5 # Sat = 6 # # print(Weekday(8)) # import os # # print('Process (%s) start...' % os.getpid()) # # Only works on Unix/Linux/Mac: # pid = os.fork() # if pid == 0: # print('I am child process (%s) and my parent is %s.' % (os.getpid(), os.getppid())) # else: # print('I (%s) just created a child process (%s).' % (os.getpid(), pid)) from datetime import datetime now = datetime.now() # 获取当前datetime print(now) print(type(now))

20.704545

89

0.566411

123

911

4.00813

0.536585

0.081136

0.048682

0.060852

0

0.014599

0.248079

911

44

90

20.704545

0.705109

0.824369

0

1

0

false

0

0.25

0

0.25

0.5

0

null

0

1

0

null

0

1

0

2

fbaf7f34961e663b79853166a225057d6daf59f0

208

py

Python

client/__init__.py

eresende-nuodb/nuodb-client

5252b4c98a2d8084d5cb677a5d72f298dd0071fc

[ "BSD-3-Clause" ]

null

client/__init__.py

eresende-nuodb/nuodb-client

5252b4c98a2d8084d5cb677a5d72f298dd0071fc

[ "BSD-3-Clause" ]

null

client/__init__.py

eresende-nuodb/nuodb-client

5252b4c98a2d8084d5cb677a5d72f298dd0071fc

[ "BSD-3-Clause" ]

null

__author__ = "NuoDB, Inc." __copyright__ = "(C) Copyright NuoDB, Inc. 2019" __license__ = "MIT" __version__ = "1.0" __maintainer__ = "NuoDB Drivers" __email__ = "drivers@nuodb.com" __status__ = "Production"

26

49

0.721154

23

208

5.304348

0.73913

0.131148

0

0.033333

0.134615

208

7

50

29.714286

0.644444

0

0.423077

0

1

0

false

0

1

0

null

0

1

0

null

0

2

fbb7b04900c9d443524f381064d8ef36a2d29641

845

py

Python

myuw/views/api/directory.py

timtim17/myuw

d59702a8095daf049d7e57cbb1f7f2a5bebc69af

[ "Apache-2.0" ]

null

myuw/views/api/directory.py

timtim17/myuw

d59702a8095daf049d7e57cbb1f7f2a5bebc69af

[ "Apache-2.0" ]

null

myuw/views/api/directory.py

timtim17/myuw

d59702a8095daf049d7e57cbb1f7f2a5bebc69af

[ "Apache-2.0" ]

null

# Copyright 2022 UW-IT, University of Washington # SPDX-License-Identifier: Apache-2.0 import traceback import logging from myuw.dao.pws import get_person_of_current_user from myuw.views.error import handle_exception from myuw.logger.timer import Timer from myuw.logger.logresp import log_api_call from myuw.views.api import ProtectedAPI logger = logging.getLogger(__name__) class MyDirectoryInfo(ProtectedAPI): def get(self, request, *args, **kwargs): """ GET returns 200 with PWS entry for the current user """ timer = Timer() try: resp = get_person_of_current_user(request).json_data() log_api_call(timer, request, "Get MyDirectoryInfo") return self.json_response(resp) except Exception: return handle_exception(logger, timer, traceback)

31.296296

66

0.711243

109

845

5.330275

0.522936

0.068847

0.037866

0.061962

0.075732

0

0.013514

0.211834

845

26

67

32.5

0.858859

0.159763

0

0.027737

0

1

0.058824

false

0

0.411765

0

0.647059

0

null

0

null

0

1

0

1

0

2

fbbdd9d2a51684c774767be1b8e4fff0c5b342a9

1,332

py

Python

solvebio/resource/__init__.py

PolinaBevad/solvebio-python

f6c736baa01b5a868a385cb0baf8f9dc2007cec3

[ "MIT" ]

null

solvebio/resource/__init__.py

PolinaBevad/solvebio-python

f6c736baa01b5a868a385cb0baf8f9dc2007cec3

[ "MIT" ]

null

solvebio/resource/__init__.py

PolinaBevad/solvebio-python

f6c736baa01b5a868a385cb0baf8f9dc2007cec3

[ "MIT" ]

null

from __future__ import absolute_import from .apiresource import ListObject from .user import User from .dataset import Dataset from .datasetfield import DatasetField from .datasetimport import DatasetImport from .datasetexport import DatasetExport from .datasetcommit import DatasetCommit from .datasetmigration import DatasetMigration from .datasettemplate import DatasetTemplate from .vault_sync_task import VaultSyncTask from .object_copy_task import ObjectCopyTask from .manifest import Manifest from .object import Object from .vault import Vault from .task import Task from .beacon import Beacon from .beaconset import BeaconSet from .application import Application from .group import Group from .savedquery import SavedQuery types = { 'Application': Application, 'Beacon': Beacon, 'BeaconSet': BeaconSet, 'Dataset': Dataset, 'DatasetImport': DatasetImport, 'DatasetExport': DatasetExport, 'DatasetCommit': DatasetCommit, 'DatasetMigration': DatasetMigration, 'DatasetTemplate': DatasetTemplate, 'DatasetField': DatasetField, 'Group': Group, 'Manifest': Manifest, 'Object': Object, 'ObjectCopyTask': ObjectCopyTask, 'ECSTask': Task, 'VaultSyncTask': VaultSyncTask, 'User': User, 'Vault': Vault, 'list': ListObject, 'SavedQuery': SavedQuery, }

28.340426

46

0.764264

130

1,332

7.761538

0.230769

0.029732

0

0.158408

1,332

46

47

28.956522

0.900089

0

0.143393

0

1

0

false

0

0.511628

0

0.511628

0

null

0

null

0

1

0

1

0

2

fbbeebc4cf13457f9cc2193dd2ff394cca86f7f7

1,679

py

Python

stubs.min/System/ComponentModel/__init___parts/CurrentChangedEventManager.py

ricardyn/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

1

2021-02-02T13:39:16.000Z

stubs.min/System/ComponentModel/__init___parts/CurrentChangedEventManager.py

hdm-dt-fb/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

null

stubs.min/System/ComponentModel/__init___parts/CurrentChangedEventManager.py

hdm-dt-fb/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

null

class CurrentChangedEventManager(WeakEventManager): """ Provides a System.Windows.WeakEventManager implementation so that you can use the "weak event listener" pattern to attach listeners for the System.ComponentModel.ICollectionView.CurrentChanged event. """ @staticmethod def AddHandler(source,handler): """ AddHandler(source: ICollectionView,handler: EventHandler[EventArgs]) """ pass @staticmethod def AddListener(source,listener): """ AddListener(source: ICollectionView,listener: IWeakEventListener) Adds the specified listener to the System.ComponentModel.ICollectionView.CurrentChanged event of the specified source. source: The object with the event. listener: The object to add as a listener. """ pass @staticmethod def RemoveHandler(source,handler): """ RemoveHandler(source: ICollectionView,handler: EventHandler[EventArgs]) """ pass @staticmethod def RemoveListener(source,listener): """ RemoveListener(source: ICollectionView,listener: IWeakEventListener) Removes the specified listener from the System.ComponentModel.ICollectionView.CurrentChanged event of the specified source. source: The object with the event. listener: The listener to remove. """ pass ReadLock=property(lambda self: object(),lambda self,v: None,lambda self: None) """Establishes a read-lock on the underlying data table,and returns an System.IDisposable. """ WriteLock=property(lambda self: object(),lambda self,v: None,lambda self: None) """Establishes a write-lock on the underlying data table,and returns an System.IDisposable. """

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null

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0

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fbc319e8d1b7e3923c4c6a288f7bd866f0ee7778

10,915

py

Python

release/stubs.min/System/Drawing/__init___parts/Color.py

htlcnn/ironpython-stubs

780d829e2104b2789d5f4d6f32b0ec9f2930ca03

[ "MIT" ]

182

2017-06-27T02:26:15.000Z

2022-03-30T18:53:43.000Z

release/stubs.min/System/Drawing/__init___parts/Color.py

htlcnn/ironpython-stubs

780d829e2104b2789d5f4d6f32b0ec9f2930ca03

[ "MIT" ]

28

2017-06-27T13:38:23.000Z

2022-03-15T11:19:44.000Z

release/stubs.min/System/Drawing/__init___parts/Color.py

htlcnn/ironpython-stubs

780d829e2104b2789d5f4d6f32b0ec9f2930ca03

[ "MIT" ]

67

2017-06-28T09:43:59.000Z

2022-03-20T21:17:10.000Z

class Color(object): """ Represents an ARGB (alpha,red,green,blue) color. """ def Equals(self,obj): """ Equals(self: Color,obj: object) -> bool Tests whether the specified object is a System.Drawing.Color structure and is equivalent to this System.Drawing.Color structure. obj: The object to test. Returns: true if obj is a System.Drawing.Color structure equivalent to this System.Drawing.Color structure; otherwise,false. """ pass @staticmethod def FromArgb(*__args): """ FromArgb(alpha: int,baseColor: Color) -> Color Creates a System.Drawing.Color structure from the specified System.Drawing.Color structure,but with the new specified alpha value. Although this method allows a 32-bit value to be passed for the alpha value,the value is limited to 8 bits. alpha: The alpha value for the new System.Drawing.Color. Valid values are 0 through 255. baseColor: The System.Drawing.Color from which to create the new System.Drawing.Color. Returns: The System.Drawing.Color that this method creates. FromArgb(red: int,green: int,blue: int) -> Color Creates a System.Drawing.Color structure from the specified 8-bit color values (red,green,and blue). The alpha value is implicitly 255 (fully opaque). Although this method allows a 32-bit value to be passed for each color component,the value of each component is limited to 8 bits. red: The red component value for the new System.Drawing.Color. Valid values are 0 through 255. green: The green component value for the new System.Drawing.Color. Valid values are 0 through 255. blue: The blue component value for the new System.Drawing.Color. Valid values are 0 through 255. Returns: The System.Drawing.Color that this method creates. FromArgb(argb: int) -> Color Creates a System.Drawing.Color structure from a 32-bit ARGB value. argb: A value specifying the 32-bit ARGB value. Returns: The System.Drawing.Color structure that this method creates. FromArgb(alpha: int,red: int,green: int,blue: int) -> Color Creates a System.Drawing.Color structure from the four ARGB component (alpha,red,green,and blue) values. Although this method allows a 32-bit value to be passed for each component,the value of each component is limited to 8 bits. alpha: The alpha component. Valid values are 0 through 255. red: The red component. Valid values are 0 through 255. green: The green component. Valid values are 0 through 255. blue: The blue component. Valid values are 0 through 255. Returns: The System.Drawing.Color that this method creates. """ pass @staticmethod def FromKnownColor(color): """ FromKnownColor(color: KnownColor) -> Color Creates a System.Drawing.Color structure from the specified predefined color. color: An element of the System.Drawing.KnownColor enumeration. Returns: The System.Drawing.Color that this method creates. """ pass @staticmethod def FromName(name): """ FromName(name: str) -> Color Creates a System.Drawing.Color structure from the specified name of a predefined color. name: A string that is the name of a predefined color. Valid names are the same as the names of the elements of the System.Drawing.KnownColor enumeration. Returns: The System.Drawing.Color that this method creates. """ pass def GetBrightness(self): """ GetBrightness(self: Color) -> Single Gets the hue-saturation-brightness (HSB) brightness value for this System.Drawing.Color structure. Returns: The brightness of this System.Drawing.Color. The brightness ranges from 0.0 through 1.0,where 0.0 represents black and 1.0 represents white. """ pass def GetHashCode(self): """ GetHashCode(self: Color) -> int Returns a hash code for this System.Drawing.Color structure. Returns: An integer value that specifies the hash code for this System.Drawing.Color. """ pass def GetHue(self): """ GetHue(self: Color) -> Single Gets the hue-saturation-brightness (HSB) hue value,in degrees,for this System.Drawing.Color structure. Returns: The hue,in degrees,of this System.Drawing.Color. The hue is measured in degrees,ranging from 0.0 through 360.0,in HSB color space. """ pass def GetSaturation(self): """ GetSaturation(self: Color) -> Single Gets the hue-saturation-brightness (HSB) saturation value for this System.Drawing.Color structure. Returns: The saturation of this System.Drawing.Color. The saturation ranges from 0.0 through 1.0,where 0.0 is grayscale and 1.0 is the most saturated. """ pass def ToArgb(self): """ ToArgb(self: Color) -> int Gets the 32-bit ARGB value of this System.Drawing.Color structure. Returns: The 32-bit ARGB value of this System.Drawing.Color. """ pass def ToKnownColor(self): """ ToKnownColor(self: Color) -> KnownColor Gets the System.Drawing.KnownColor value of this System.Drawing.Color structure. Returns: An element of the System.Drawing.KnownColor enumeration,if the System.Drawing.Color is created from a predefined color by using either the System.Drawing.Color.FromName(System.String) method or the System.Drawing.Color.FromKnownColor(System.Drawing.KnownColor) method; otherwise,0. """ pass def ToString(self): """ ToString(self: Color) -> str Converts this System.Drawing.Color structure to a human-readable string. Returns: A string that is the name of this System.Drawing.Color,if the System.Drawing.Color is created from a predefined color by using either the System.Drawing.Color.FromName(System.String) method or the System.Drawing.Color.FromKnownColor(System.Drawing.KnownColor) method; otherwise,a string that consists of the ARGB component names and their values. """ pass def __eq__(self,*args): """ x.__eq__(y) <==> x==y """ pass def __ne__(self,*args): pass A=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the alpha component value of this System.Drawing.Color structure. Get: A(self: Color) -> Byte """ B=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the blue component value of this System.Drawing.Color structure. Get: B(self: Color) -> Byte """ G=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the green component value of this System.Drawing.Color structure. Get: G(self: Color) -> Byte """ IsEmpty=property(lambda self: object(),lambda self,v: None,lambda self: None) """Specifies whether this System.Drawing.Color structure is uninitialized. Get: IsEmpty(self: Color) -> bool """ IsKnownColor=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets a value indicating whether this System.Drawing.Color structure is a predefined color. Predefined colors are represented by the elements of the System.Drawing.KnownColor enumeration. Get: IsKnownColor(self: Color) -> bool """ IsNamedColor=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets a value indicating whether this System.Drawing.Color structure is a named color or a member of the System.Drawing.KnownColor enumeration. Get: IsNamedColor(self: Color) -> bool """ IsSystemColor=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets a value indicating whether this System.Drawing.Color structure is a system color. A system color is a color that is used in a Windows display element. System colors are represented by elements of the System.Drawing.KnownColor enumeration. Get: IsSystemColor(self: Color) -> bool """ Name=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the name of this System.Drawing.Color. Get: Name(self: Color) -> str """ R=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the red component value of this System.Drawing.Color structure. Get: R(self: Color) -> Byte """ AliceBlue=None AntiqueWhite=None Aqua=None Aquamarine=None Azure=None Beige=None Bisque=None Black=None BlanchedAlmond=None Blue=None BlueViolet=None Brown=None BurlyWood=None CadetBlue=None Chartreuse=None Chocolate=None Coral=None CornflowerBlue=None Cornsilk=None Crimson=None Cyan=None DarkBlue=None DarkCyan=None DarkGoldenrod=None DarkGray=None DarkGreen=None DarkKhaki=None DarkMagenta=None DarkOliveGreen=None DarkOrange=None DarkOrchid=None DarkRed=None DarkSalmon=None DarkSeaGreen=None DarkSlateBlue=None DarkSlateGray=None DarkTurquoise=None DarkViolet=None DeepPink=None DeepSkyBlue=None DimGray=None DodgerBlue=None Empty=None Firebrick=None FloralWhite=None ForestGreen=None Fuchsia=None Gainsboro=None GhostWhite=None Gold=None Goldenrod=None Gray=None Green=None GreenYellow=None Honeydew=None HotPink=None IndianRed=None Indigo=None Ivory=None Khaki=None Lavender=None LavenderBlush=None LawnGreen=None LemonChiffon=None LightBlue=None LightCoral=None LightCyan=None LightGoldenrodYellow=None LightGray=None LightGreen=None LightPink=None LightSalmon=None LightSeaGreen=None LightSkyBlue=None LightSlateGray=None LightSteelBlue=None LightYellow=None Lime=None LimeGreen=None Linen=None Magenta=None Maroon=None MediumAquamarine=None MediumBlue=None MediumOrchid=None MediumPurple=None MediumSeaGreen=None MediumSlateBlue=None MediumSpringGreen=None MediumTurquoise=None MediumVioletRed=None MidnightBlue=None MintCream=None MistyRose=None Moccasin=None NavajoWhite=None Navy=None OldLace=None Olive=None OliveDrab=None Orange=None OrangeRed=None Orchid=None PaleGoldenrod=None PaleGreen=None PaleTurquoise=None PaleVioletRed=None PapayaWhip=None PeachPuff=None Peru=None Pink=None Plum=None PowderBlue=None Purple=None Red=None RosyBrown=None RoyalBlue=None SaddleBrown=None Salmon=None SandyBrown=None SeaGreen=None SeaShell=None Sienna=None Silver=None SkyBlue=None SlateBlue=None SlateGray=None Snow=None SpringGreen=None SteelBlue=None Tan=None Teal=None Thistle=None Tomato=None Transparent=None Turquoise=None Violet=None Wheat=None White=None WhiteSmoke=None Yellow=None YellowGreen=None

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0.331122

0

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10,915

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false

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null

0

null

0

1

0

1

0

2

fbc6b16f9486d5e2e81bdbf62103b2a53aef5bf6

20,581

py

Python

modules/s3/s3cfg.py

flavour/lacity

fd1f1cccdcea64d07143b29d4f88996e3af35c4b

[ "MIT" ]

null

modules/s3/s3cfg.py

flavour/lacity

fd1f1cccdcea64d07143b29d4f88996e3af35c4b

[ "MIT" ]

null

modules/s3/s3cfg.py

flavour/lacity

fd1f1cccdcea64d07143b29d4f88996e3af35c4b

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Deployment Settings @requires: U{B{I{gluon}} <http://web2py.com>} @author: Dominic König <dominic[at]aidiq.com> @copyright: 2009-2011 (c) Sahana Software Foundation @license: MIT Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ __all__ = ["S3Config"] from gluon import HTTP, current from gluon.storage import Storage from gluon.contrib.simplejson.ordered_dict import OrderedDict class S3Config(Storage): """ Deployment Settings Helper Class """ def __init__(self): self.auth = Storage() self.base = Storage() self.database = Storage() self.frontpage = Storage() self.frontpage.rss = [] self.fin = Storage() self.gis = Storage() self.mail = Storage() self.twitter = Storage() self.L10n = Storage() self.options = Storage() self.osm = Storage() self.security = Storage() self.aaa = Storage() self.ui = Storage() self.req = Storage() self.inv = Storage() self.hrm = Storage() self.save_search = Storage() T = current.T # These are copied from modules/s3/s3aaa.py self.aaa.acl = Storage(CREATE = 0x0001, READ = 0x0002, UPDATE = 0x0004, DELETE = 0x0008, ALL = 0x000F # CREATE | READ | UPDATE | DELETE ) self.CURRENCIES = { "USD" :T("United States Dollars"), "EUR" :T("Euros"), "GBP" :T("Great British Pounds") } # ----------------------------------------------------------------------------- # Auth settings def get_auth_hmac_key(self): return self.auth.get("hmac_key", "akeytochange") def get_auth_openid(self): return self.auth.get("openid", False) def get_auth_registration_requires_verification(self): return self.auth.get("registration_requires_verification", False) def get_auth_registration_requires_approval(self): return self.auth.get("registration_requires_approval", False) def get_auth_registration_requests_mobile_phone(self): return self.auth.get("registration_requests_mobile_phone", False) def get_auth_registration_mobile_phone_mandatory(self): " Make the selection of Mobile Phone Mandatory during registration " return self.auth.get("registration_mobile_phone_mandatory", False) def get_auth_registration_requests_organisation(self): " Have the registration form request the Organisation " return self.auth.get("registration_requests_organisation", False) def get_auth_registration_organisation_mandatory(self): " Make the selection of Organisation Mandatory during registration " return self.auth.get("registration_organisation_mandatory", False) def get_auth_registration_organisation_hidden(self): " Hide the Organisation field in the registration form unless an email is entered which isn't whitelisted " return self.auth.get("registration_organisation_hidden", False) def get_auth_registration_volunteer(self): " Redirect the newly-registered user to their volunteer details page " return self.auth.get("registration_volunteer", False) def get_auth_always_notify_approver(self): return self.auth.get("always_notify_approver", False) # @ToDo: Deprecate def get_aaa_default_uacl(self): return self.aaa.get("default_uacl", self.aaa.acl.READ) def get_aaa_default_oacl(self): return self.aaa.get("default_oacl", self.aaa.acl.READ | self.aaa.acl.UPDATE) def get_security_archive_not_delete(self): return self.security.get("archive_not_delete", True) def get_security_audit_read(self): return self.security.get("audit_read", False) def get_security_audit_write(self): return self.security.get("audit_write", False) def get_security_policy(self): " Default is Simple Security Policy " return self.security.get("policy", 1) def get_security_map(self): return self.security.get("map", False) def get_security_self_registration(self): return self.security.get("self_registration", True) # ----------------------------------------------------------------------------- # Base settings def get_system_name(self): return self.base.get("system_name", current.T("Sahana Eden Humanitarian Management Platform")) def get_system_name_short(self): return self.base.get("system_name_short", self.get_system_name()) def get_paper_size(self): return self.base.get("paper_size", "A4") def get_base_debug(self): return self.base.get("debug", False) def get_base_migrate(self): return self.base.get("migrate", True) def get_base_prepopulate(self): return self.base.get("prepopulate", 1) def get_base_public_url(self): return self.base.get("public_url", "http://127.0.0.1:8000") def get_base_cdn(self): return self.base.get("cdn", False) # ----------------------------------------------------------------------------- # Database settings def get_database_type(self): return self.database.get("db_type", "sqlite") def get_database_string(self): db_type = self.database.get("db_type", "sqlite") pool_size = self.database.get("pool_size", 0) if (db_type == "sqlite"): db_string = "sqlite://storage.db" elif (db_type == "mysql"): db_string = "mysql://%s:%s@%s:%s/%s" % \ (self.database.get("username", "sahana"), self.database.get("password", "password"), self.database.get("host", "localhost"), self.database.get("port", None) or "3306", self.database.get("database", "sahana")) elif (db_type == "postgres"): db_string = "postgres://%s:%s@%s:%s/%s" % \ (self.database.get("username", "sahana"), self.database.get("password", "password"), self.database.get("host", "localhost"), self.database.get("port", None) or "5432", self.database.get("database", "sahana")) else: raise HTTP(501, body="Database type '%s' not recognised - please correct file models/000_config.py." % db_type) if pool_size: return (db_string, pool_size) else: return db_string # ----------------------------------------------------------------------------- # Finance settings # @ToDo: Make these customisable per User/Facility def get_fin_currencies(self): return self.fin.get("currencies", self.CURRENCIES) def get_fin_currency_default(self): return self.fin.get("currency_default", "USD") def get_fin_currency_readable(self): return self.fin.get("currency_readable", True) def get_fin_currency_writable(self): return self.fin.get("currency_writable", True) # ----------------------------------------------------------------------------- # GIS (Map) Settings # No defaults are needed for gis_config deployment settings -- initial # defaults come either from the table itself or are added to the site # config when it is created. This does not include defaults for the # hierarchy labels as that is defined separately in 000_config. def get_gis_default_config_values(self): return self.gis.get("default_config_values", Storage()) def get_gis_default_location_hierarchy(self): location_hierarchy = self.gis.get("location_hierarchy", None) if not location_hierarchy: location_hierarchy = OrderedDict([ ("L0", current.T("Country")), ("L1", current.T("Province")), ("L2", current.T("District")), ("L3", current.T("Town")), ("L4", current.T("Village")), #("L5", current.T("Neighbourhood")), ]) return location_hierarchy # These fields in gis_config are references to other tables. Rather than # hard code an id, default via the name. def get_gis_default_symbology(self): return self.gis.get("default_symbology", "US") def get_gis_default_projection(self): return self.gis.get("default_projection", "Spherical Mercator") def get_gis_default_marker(self): return self.gis.get("default_marker", "marker_red") def get_gis_max_allowed_hierarchy_level(self): # If the site's default hierarchy is deeper than the specified maximum, # adjust the limit so the entire default hierarchy will be shown in a # config update form. (At this point, we cannot also limit this to the # depth available in the gis_config table as the database is not # available. See max_allowed_level_num in s3gis GIS.) limit = current.response.s3.gis.adjusted_max_allowed_hierarchy_level if not limit: limit = max(self.gis.get("max_allowed_hierarchy_level", "L4"), self.get_gis_default_location_hierarchy().keys()[-1]) current.response.s3.gis.adjusted_max_allowed_hierarchy_level = limit return limit def get_gis_building_name(self): " Display Building Name when selecting Locations " return self.gis.get("building_name", True) def get_gis_latlon_selector(self): " Display a Lat/Lon boxes when selecting Locations " return self.gis.get("latlon_selector", True) def get_gis_map_selector(self): " Display a Map-based tool to select Locations " return self.gis.get("map_selector", True) def get_gis_menu(self): """ Should we display a menu of GIS configurations? - set to False to not show the menu (default) - set to the label to use for the menu to enable it e.g. T("Events") or T("Regions") """ return self.gis.get("menu", False) def get_gis_display_l0(self): return self.gis.get("display_L0", False) def get_gis_display_l1(self): return self.gis.get("display_L1", True) def get_gis_duplicate_features(self): return self.gis.get("duplicate_features", False) def get_gis_edit_lx(self): " Edit Hierarchy Locations " return self.gis.get("edit_Lx", True) def get_gis_edit_group(self): " Edit Location Groups " return self.gis.get("edit_GR", False) def get_gis_marker_max_height(self): return self.gis.get("marker_max_height", 35) def get_gis_marker_max_width(self): return self.gis.get("marker_max_width", 30) def get_gis_mouse_position(self): return self.gis.get("mouse_position", "normal") def get_gis_print_service(self): return self.gis.get("print_service", "") def get_gis_geoserver_url(self): return self.gis.get("geoserver_url", "") def get_gis_geoserver_username(self): return self.gis.get("geoserver_username", "admin") def get_gis_geoserver_password(self): return self.gis.get("geoserver_password", "password") def get_gis_spatialdb(self): return self.gis.get("spatialdb", False) # OpenStreetMap settings def get_osm_oauth_consumer_key(self): return self.osm.get("oauth_consumer_key", "") def get_osm_oauth_consumer_secret(self): return self.osm.get("oauth_consumer_secret", "") # ----------------------------------------------------------------------------- # L10N Settings def get_L10n_default_country_code(self): return self.L10n.get("default_country_code", 1) def get_L10n_default_language(self): return self.L10n.get("default_language", "en") def get_L10n_display_toolbar(self): return self.L10n.get("display_toolbar", True) def get_L10n_languages(self): return self.L10n.get("languages", { "en":current.T("English") }) def get_L10n_religions(self): T = current.T return self.L10n.get("religions", { "none":T("None"), "other":T("Other") }) def get_L10n_date_format(self): T = current.T return self.L10n.get("date_format", T("%Y-%m-%d")) def get_L10n_time_format(self): T = current.T return self.L10n.get("time_format", T("%H:%M:%S")) def get_L10n_datetime_format(self): T = current.T return self.L10n.get("datetime_format", T("%Y-%m-%d %H:%M:%S")) def get_L10n_utc_offset(self): return self.L10n.get("utc_offset", "UTC +0000") def get_L10n_mandatory_lastname(self): return self.L10n.get("mandatory_lastname", False) # ----------------------------------------------------------------------------- # Messaging # ----------------------------------------------------------------------------- # Mail settings def get_mail_server(self): return self.mail.get("server", "127.0.0.1:25") def get_mail_server_login(self): return self.mail.get("login", False) def get_mail_server_tls(self): """ Does the Mail Server use TLS? - default Debian is False - GMail is True """ return self.mail.get("tls", False) def get_mail_sender(self): return self.mail.get("sender", "sahana@your.org") def get_mail_approver(self): return self.mail.get("approver", "useradmin@your.org") def get_mail_limit(self): """ A daily limit to the number of messages which can be sent """ return self.mail.get("limit", None) # Twitter settings def get_twitter_oauth_consumer_key(self): return self.twitter.get("oauth_consumer_key", "") def get_twitter_oauth_consumer_secret(self): return self.twitter.get("oauth_consumer_secret", "") # ----------------------------------------------------------------------------- # PDF settings def get_paper_size(self): return self.base.get("paper_size", "A4") def get_pdf_logo(self): return self.ui.get("pdf_logo", None) # Optical Character Recognition (OCR) def get_pdf_excluded_fields(self, resourcename): excluded_fields_dict = { "hms_hospital" : [ "hrm_human_resource", ], "pr_group" : [ "pr_group_membership", ], } excluded_fields =\ excluded_fields_dict.get(resourcename, []) return excluded_fields # ----------------------------------------------------------------------------- # Options def get_terms_of_service(self): return self.options.get("terms_of_service", False) def get_options_support_requests(self): return self.options.get("support_requests", False) # ----------------------------------------------------------------------------- # UI/Workflow Settings def get_ui_navigate_away_confirm(self): return self.ui.get("navigate_away_confirm", True) def get_ui_confirm(self): """ For Delete actions Workaround for this Bug in Selenium with FF4: http://code.google.com/p/selenium/issues/detail?id=1604 """ return self.ui.get("confirm", True) def get_ui_autocomplete(self): """ Currently Unused """ return self.ui.get("autocomplete", False) def get_ui_update_label(self): return self.ui.get("update_label", current.T("Open")) def get_ui_cluster(self): """ UN-style deployment? """ return self.ui.get("cluster", False) def get_ui_camp(self): """ 'Camp' instead of 'Shelter'? """ return self.ui.get("camp", False) def get_ui_label_mobile_phone(self): """ Label for the Mobile Phone field e.g. 'Cell Phone' """ T = current.T label = self.ui.get("label_mobile_phone", T("Mobile Phone")) # May need this form for Web Setup #return T(label) return label def get_ui_label_postcode(self): """ Label for the Postcode field e.g. 'ZIP Code' """ T = current.T label = self.ui.get("label_postcode", T("Postcode")) # May need this form for Web Setup #return T(label) return label # ----------------------------------------------------------------------------- # Modules # ----------------------------------------------------------------------------- # Request Settings def get_req_type_inv_label(self): return self.req.get("type_inv_label", current.T("Inventory Items")) def get_req_type_hrm_label(self): return self.req.get("type_hrm_label", current.T("People")) def get_req_status_writable(self): """ Whether Request Status should be manually editable """ return self.req.get("status_writable", True) def get_req_quantities_writable(self): """ Whether Item Quantities should be manually editable """ return self.req.get("quantities_writable", False) def get_req_skill_quantities_writable(self): """ Whether People Quantities should be manually editable """ return self.req.get("skill_quantities_writable", False) def get_req_multiple_req_items(self): return self.req.get("multiple_req_items", True) def get_req_show_quantity_transit(self): return self.req.get("show_quantity_transit", True) def get_req_use_commit(self): return self.req.get("use_commit", True) def get_req_req_crud_strings(self, type = None): return self.req.get("req_crud_strings") and \ self.req.req_crud_strings.get(type, None) def get_req_webeoc_is_master(self): return self.req.get("webeoc_is_master", True) # ----------------------------------------------------------------------------- # Inventory Management Setting def get_inv_collapse_tabs(self): return self.inv.get("collapse_tabs", True) def get_inv_shipment_name(self): """ Get the name of Shipments - currently supported options are: * shipment * order """ return self.inv.get("shipment_name", "shipment") # ----------------------------------------------------------------------------- # Human Resource Management def get_hrm_email_required(self): return self.hrm.get("email_required", True) # Save Search and Subscription def get_save_search_widget(self): return self.save_search.get("widget", True) # ----------------------------------------------------------------------------- # Active modules list def has_module(self, module_name): if not self.modules: # Provide a minimal list of core modules _modules = [ "admin", # Admin "gis", # GIS "pr", # Person Registry "org" # Organization Registry ] else: _modules = self.modules return module_name in _modules

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null

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null

0

1

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1

0

2

fbda1644f2552e19e5d19991b8502432f589b88d

555

py

Python

ejercicios/basico/suma_entre_dos_numeros.py

carlosviveros/Soluciones

115f4fa929c7854ca497e4c994352adc64565456

[ "MIT" ]

1

2022-02-02T04:44:56.000Z

ejercicios/basico/suma_entre_dos_numeros.py

leugimkm/Soluciones

d71601c8d9b5e86e926f48d9e49462af8a956b6d

[ "MIT" ]

null

ejercicios/basico/suma_entre_dos_numeros.py

leugimkm/Soluciones

d71601c8d9b5e86e926f48d9e49462af8a956b6d

[ "MIT" ]

null

"""AyudaEnPython: https://www.facebook.com/groups/ayudapython Escribe un programa que solicite dos números enteros al usuario y muestre por pantalla la suma de todos los números enteros que hay entre los dos números (ambos números incluidos). Ejemplo: Introduce el número de inicio: 4 Introduce el número de fin: 8 El resusltado es: 30 """ inicio = int(input("Introduce el número de inicio: ")) fin = int(input("Introduce el número de fin: ")) if inicio > fin: inicio, fin = fin, inicio print(f"El resusltado es: {sum(range(inicio, fin + 1))}")

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83754c383c9d8616fa873063f2aefba1b4b85aa1

508

py

Python

dataloader/create_data_loader.py

WiktorSa/Music-Generation-with-LSTM-and-.wav-files

37b713b5e6193788a7710cc0fac4134efb74fa62

[ "MIT" ]

1

2022-03-09T20:13:57.000Z

dataloader/create_data_loader.py

WiktorSa/Music-Generation-with-LSTM-and-.wav-files

37b713b5e6193788a7710cc0fac4134efb74fa62

[ "MIT" ]

1

2021-10-01T16:20:06.000Z

2021-10-01T17:25:30.000Z

dataloader/create_data_loader.py

WiktorSa/Music-Generation-with-LSTM-and-.wav-files

37b713b5e6193788a7710cc0fac4134efb74fa62

[ "MIT" ]

null

import numpy as np from torch.utils.data import DataLoader from dataloader.music_dataset import MusicDataset def get_data_loader(x: np.ndarray, y: np.ndarray, batch_size: int) -> DataLoader: """ Generate a DataLoader from a given data :param x: input sequences :param y: output sequences :param batch_size: batch size :return: DataLoader """ dataset = MusicDataset(x, y) dataloader = DataLoader(dataset, batch_size, shuffle=True, drop_last=True) return dataloader

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0.1

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18

82

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null

0

null

0

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8387f80c01d3857d9c86fea346c1dfb0c8183f4b

586

py

Python

paw2018/nflgames/migrations/0003_auto_20180830_1438.py

mdcollins80/PAW-api

ba40ec77301ac0c84a8ad95481323031b398168b

[ "MIT" ]

null

paw2018/nflgames/migrations/0003_auto_20180830_1438.py

mdcollins80/PAW-api

ba40ec77301ac0c84a8ad95481323031b398168b

[ "MIT" ]

null

paw2018/nflgames/migrations/0003_auto_20180830_1438.py

mdcollins80/PAW-api

ba40ec77301ac0c84a8ad95481323031b398168b

[ "MIT" ]

null

# Generated by Django 2.0.8 on 2018-08-30 18:38 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('nflgames', '0002_auto_20180830_1436'), ] operations = [ migrations.AlterField( model_name='game', name='away_team_score', field=models.SmallIntegerField(blank=True, null=True), ), migrations.AlterField( model_name='game', name='home_team_score', field=models.SmallIntegerField(blank=True, null=True), ), ]

24.416667

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586

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1

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null

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2

8397b03e82838d41b9922244369430b1cf00de3f

1,086

py

Python

operators/get_pillow.py

BlenderAddonsArchive/material-combiner-addon

8103f17bddf0153df9c6211c7269c0524858a70c

[ "MIT" ]

null

operators/get_pillow.py

BlenderAddonsArchive/material-combiner-addon

8103f17bddf0153df9c6211c7269c0524858a70c

[ "MIT" ]

null

operators/get_pillow.py

BlenderAddonsArchive/material-combiner-addon

8103f17bddf0153df9c6211c7269c0524858a70c

[ "MIT" ]

null

import os import sys from subprocess import call import bpy from .. import globs class InstallPIL(bpy.types.Operator): bl_idname = 'smc.get_pillow' bl_label = 'Install PIL' bl_description = 'Click to install Pillow. This could take a while and might require you to start Blender as admin' def execute(self, context): python_executable = bpy.app.binary_path_python if bpy.app.version < (3, 0, 0) else sys.executable try: import pip try: from PIL import Image, ImageChops except ImportError: call([python_executable, '-m', 'pip', 'install', 'Pillow', '--user', '--upgrade'], shell=True) except ImportError: call([python_executable, os.path.join(os.path.dirname(os.path.abspath(__file__)), 'get_pip.py'), '--user'], shell=True) call([python_executable, '-m', 'pip', 'install', 'Pillow', '--user', '--upgrade'], shell=True) globs.smc_pi = True self.report({'INFO'}, 'Installation complete') return {'FINISHED'}

36.2

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839dbe4891e64b4c1d88f3e8ad00c5e89d4fa29c

2,867

py

Python

src/django_prefetch_utils/descriptors/annotation.py

roverdotcom/django-prefetch-utils

f901cb2159b3e95f44baf18812d5bbb7c52afd97

[ "BSD-3-Clause" ]

1

2019-09-26T10:32:47.000Z

src/django_prefetch_utils/descriptors/annotation.py

roverdotcom/django-prefetch-utils

f901cb2159b3e95f44baf18812d5bbb7c52afd97

[ "BSD-3-Clause" ]

1

2019-07-23T09:25:06.000Z

src/django_prefetch_utils/descriptors/annotation.py

roverdotcom/django-prefetch-utils

f901cb2159b3e95f44baf18812d5bbb7c52afd97

[ "BSD-3-Clause" ]

1

2021-12-22T14:38:20.000Z

from django.utils.functional import cached_property from .base import GenericPrefetchRelatedDescriptor from .base import GenericSinglePrefetchRelatedDescriptorMixin class AnnotationDescriptor(GenericSinglePrefetchRelatedDescriptorMixin, GenericPrefetchRelatedDescriptor): """ This descriptor behaves like an annotated value would appear on a model. It lets you turn an annotation into a prefetch at the cost of an additional query:: >>> class Author(models.Model): ... book_count = AnnotationDescriptor(Count('books')) ... authors.models.Author >>> author = Author.objects.get(name="Jane") >>> author.book_count 11 >>> author = Author.objects.prefetch_related('book_count').get(name="Jane") >>> author.book_count # no queries done 11 It works by storing a ``values_list`` tuple containing the annotated value on :attr:`cache_name` on the object. """ def __init__(self, annotation): self.annotation = annotation def get_prefetch_model_class(self): """ Returns the model class of the objects that are prefetched by this descriptor. :returns: subclass of :class:`django.db.models.model` """ return self.model @cached_property def cache_name(self): """ Returns the name of the attribute where we will cache the annotated value. We are overriding ``cache_name`` from :class:`GenericPrefetchRelatedDescriptor` so that we can just return the annotated value from :attr:`__get__`. :rtype: str """ return "_prefetched_{}".format(self.name) def __get__(self, obj, type=None): if obj is None: return self # Perform the query if we haven't already fetched the annotated value if not self.is_cached(obj): annotation_value = super().__get__(obj, type) setattr(obj, self.cache_name, annotation_value) return getattr(obj, self.cache_name)[1] def filter_queryset_for_instances(self, queryset, instances): """ Returns *queryset* filtered to the objects which are related to *instances*. :param list instances: instances of the class on which this descriptor is found :param QuerySet queryset: the queryset to filter for *instances* :rtype: :class:`django.db.models.QuerySet` """ queryset = ( queryset.filter(pk__in=[obj.pk for obj in instances]) .annotate(**{self.name: self.annotation}) .values_list("pk", self.name) ) return queryset def get_join_value_for_instance(self, instance): return instance.pk def get_join_value_for_related_obj(self, annotation_value): return annotation_value[0]

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2,867

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null

0

null

0

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1

0

2

83a0c082bc6603eb00250798f4a9293fb5b6a9f7

1,391

py

Python

Chapter_3/Chapter_3_1_4_1.py

flytian/python_machinelearning

004707c3e66429f102272a7da97e532255cca293

[ "Apache-2.0" ]

null

Chapter_3/Chapter_3_1_4_1.py

flytian/python_machinelearning

004707c3e66429f102272a7da97e532255cca293

[ "Apache-2.0" ]

null

Chapter_3/Chapter_3_1_4_1.py

flytian/python_machinelearning

004707c3e66429f102272a7da97e532255cca293

[ "Apache-2.0" ]

null

# coding:utf-8 # 从sklearn.datasets中导入20类新闻文本抓取器。 from sklearn.datasets import fetch_20newsgroups # 导入numpy，并且重命名为np。 import numpy as np # 使用新闻抓取器从互联网上下载所有数据，并且存储在变量news中。 news = fetch_20newsgroups(subset='all') # 从sklearn.cross_validation导入train_test_split用来分割数据。 from sklearn.cross_validation import train_test_split # 对前3000条新闻文本进行数据分割，25%文本用于未来测试。 X_train, X_test, y_train, y_test = train_test_split(news.data[:3000], news.target[:3000], test_size=0.25, random_state=33) # 导入支持向量机（分类）模型。 from sklearn.svm import SVC # 导入TfidfVectorizer文本抽取器。 from sklearn.feature_extraction.text import TfidfVectorizer # 导入Pipeline。 from sklearn.pipeline import Pipeline # 使用Pipeline 简化系统搭建流程，将文本抽取与分类器模型串联起来。 clf = Pipeline([('vect', TfidfVectorizer(stop_words='english', analyzer='word')), ('svc', SVC())]) # 这里需要试验的2个超参数的的个数分别是4、3， svc__gamma的参数共有10^-2, 10^-1... 。这样我们一共有12种的超参数组合，12个不同参数下的模型。 parameters = {'svc__gamma': np.logspace(-2, 1, 4), 'svc__C': np.logspace(-1, 1, 3)} # 从sklearn.grid_search中导入网格搜索模块GridSearchCV。 from sklearn.grid_search import GridSearchCV # 将12组参数组合以及初始化的Pipline包括3折交叉验证的要求全部告知GridSearchCV。请大家务必注意refit=True这样一个设定。 gs = GridSearchCV(clf, parameters, verbose=2, refit=True, cv=3) # 执行单线程网格搜索。 % time_ = gs.fit(X_train, y_train) gs.best_params_, gs.best_score_ # 输出最佳模型在测试集上的准确性。 print gs.score(X_test, y_test)

32.348837

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168

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6.095238

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0.064453

0.027344

0

0.041017

0.123652

1,391

42

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null

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null

0

1

0

1

0

2

83a99a6012b085a99fc3b809de934d3e8644c29e

821

py

Python

tests/test_micloud.py

ekorsanov01/micloud

65b78cc55510baa8d5d7cf4556ab5fbdf3464095

[ "MIT" ]

3

2021-01-08T15:16:33.000Z

2021-03-04T18:06:17.000Z

tests/test_micloud.py

starkillerOG/micloud

6d9c886a9c2a58f5a7711a410fd53be5386db694

[ "MIT" ]

null

tests/test_micloud.py

starkillerOG/micloud

6d9c886a9c2a58f5a7711a410fd53be5386db694

[ "MIT" ]

null

import unittest import logging import os, json from micloud import MiCloud from tests.configuration import setup_testing_environment setup_testing_environment() class TestMiCloud(unittest.TestCase): """def test_login_success(self): mc = MiCloud(os.getenv("USERNAME"), os.getenv("PASSWORD")) f = open("tests.txt", "w") f.write("Now the file has more content!") f.close() self.assertTrue(mc.login())""" def test_get_devices(self): mc = MiCloud(os.getenv("USERNAME"), os.getenv("PASSWORD")) self.assertTrue(mc.login()) self.assertIsNotNone(mc.get_token()) res = mc.get_devices(save=True) self.assertIsNotNone(res) self.assertTrue(type(res)==list) if __name__ == '__main__': unittest.main()

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0.4375

0

null

0

null

0

1

0

2

83aa7a6b82a233ee798bc220c22027904429169d

1,281

py

Python

admin_sso/openid/models.py

allink/django-admin-sso

04935aa31fa701ad1dd62c0aa1b9625235b555ad

[ "BSD-3-Clause" ]

17

2015-03-30T09:37:33.000Z

2022-03-11T08:36:26.000Z

admin_sso/openid/models.py

allink/django-admin-sso

04935aa31fa701ad1dd62c0aa1b9625235b555ad

[ "BSD-3-Clause" ]

6

2015-03-06T10:55:04.000Z

2021-03-24T10:10:44.000Z

admin_sso/openid/models.py

allink/django-admin-sso

04935aa31fa701ad1dd62c0aa1b9625235b555ad

[ "BSD-3-Clause" ]

4

2015-06-25T07:32:59.000Z

2019-07-24T08:35:09.000Z

from django.db import models from django.utils.timezone import now from django.utils.translation import ugettext_lazy as _ from admin_sso import settings class OpenIDUser(models.Model): claimed_id = models.TextField(max_length=2047) email = models.EmailField() fullname = models.CharField(max_length=255) user = models.ForeignKey(settings.AUTH_USER_MODEL) last_login = models.DateTimeField(_('last login'), default=now) class Meta: verbose_name = _('OpenIDUser') verbose_name_plural = _('OpenIDUsers') app_label = 'admin_sso' def __unicode__(self): return self.claimed_id def update_last_login(self): self.last_login = now() self.save() class Nonce(models.Model): server_url = models.CharField(max_length=2047) timestamp = models.IntegerField() salt = models.CharField(max_length=40) class Meta: app_label = 'admin_sso' class Association(models.Model): server_url = models.CharField(max_length=2047) handle = models.CharField(max_length=255) secret = models.CharField(max_length=255) issued = models.IntegerField() lifetime = models.IntegerField() assoc_type = models.CharField(max_length=64) class Meta: app_label = 'admin_sso'

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0

null

0

1

0

null

0

1

0

2

83b21bfd3e88588a1f804872b03450864e71b9ce

253

py

Python

PythonLearning/Design and Analysis of Algorithms/week2/Q2_4.py

JimouChen/python-application

b7b16506a17e2c304d1c5fabd6385e96be211c56

[ "Apache-2.0" ]

1

2020-08-09T12:47:27.000Z

PythonLearning/Design and Analysis of Algorithms/week2/Q2_4.py

JimouChen/Python_Application

b7b16506a17e2c304d1c5fabd6385e96be211c56

[ "Apache-2.0" ]

null

PythonLearning/Design and Analysis of Algorithms/week2/Q2_4.py

JimouChen/Python_Application

b7b16506a17e2c304d1c5fabd6385e96be211c56

[ "Apache-2.0" ]

null

""" # @Time : 2020/9/17 # @Author : Jimou Chen """ def T(n): if n == 1: return 4 elif n > 1: return 3 * T(n - 1) def T(n): if n == 1: return 1 elif n > 1: return 2 * T(n // 3) + n print(T(5))

11

32

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22

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11.5

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false

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0

null

0

1

0

null

0

1

0

2

83b3ae52b6957745430684a86578513982143650

2,601

py

Python

test/test_bilayer_class_auto.py

aravindhk/Vides

65d9ea9764ddf5f6ef40e869bd31387d0e3e378f

[ "BSD-4-Clause" ]

2

2021-11-03T17:24:24.000Z

2021-12-02T06:06:50.000Z

test/test_bilayer_class_auto.py

aravindhk/Vides

65d9ea9764ddf5f6ef40e869bd31387d0e3e378f

[ "BSD-4-Clause" ]

null

test/test_bilayer_class_auto.py

aravindhk/Vides

65d9ea9764ddf5f6ef40e869bd31387d0e3e378f

[ "BSD-4-Clause" ]

null

#!/usr/bin/python from NanoTCAD_ViDES import * ########################### #FIRST TEST ########################### BG=bilayer_graphene(10); BG.dE=1e-3; BG.eta=1e-5; BG.kmax=12.5958; BG.kmin=5.39722; BG.dk=(BG.kmax-BG.kmin)/32.0; #-0.2 BG.Eupper = 0.633527 BG.Elower = -0.433527 BG.Phi=-0.2*ones(size(BG.Phi)); BG.charge_T(); plot(BG.charge*0.144*sqrt(3)*1e-9); hold a=loadtxt("carica.-0.2"); print(max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))); plot(a,'o') show() if (max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))<1e-5): string="PASSED" else: string="NOT PASSED" ########################### #SECOND TEST ########################### BG=bilayer_graphene(10); BG.dE=1e-3; BG.eta=1e-5; BG.kmax=12.5958; BG.kmin=5.39722; BG.dk=(BG.kmax-BG.kmin)/32.0; #0.5 BG.Eupper = 0.258527 BG.Elower = -0.933527 BG.Phi=0.5*ones(size(BG.Phi)); BG.charge_T(); plot(BG.charge*0.144*sqrt(3)*1e-9); hold a=loadtxt("carica.0.5"); #print max(abs(a-BG.charge*0.144*sqrt(3)*1e-9)) plot(a,'o') show() if (max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))<1e-5): string2="PASSED" else: string2="NOT PASSED" print(max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))) ########################### # THIRD TEST ########################### BG=bilayer_graphene(10); BG.dE=1e-3; BG.eta=1e-8; BG.kmax=12.5958; BG.kmin=5.39722; BG.dk=(BG.kmax-BG.kmin)/32.0; #lin BG.Eupper = 0.433527 BG.Elower = -0.530727 BG.Phi=BG.y*1e-2; BG.charge_T(); plot(BG.charge*0.144*sqrt(3)*1e-9); hold a=loadtxt("carica.lin"); plot(a,'o') show() print(max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))) if (max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))<5e-5): string3="PASSED" else: string3="NOT PASSED" print(max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))) #show() ########################### # FOURTH TEST ########################### BG=bilayer_graphene(10); BG.dE=1e-3; BG.eta=1e-5; BG.kmax=12.5958; BG.kmin=5.39722; BG.dk=(BG.kmax-BG.kmin)/32.0; #plusminus BG.Eupper = 0.533527 BG.Elower = -0.533527 i=linspace(0,size(BG.Phi)-1,size(BG.Phi)) i_even=nonzero((i%2)==0); i_odd=nonzero((i%2)==1); BG.Phi[i_even]=-0.1; BG.Phi[i_odd]=0.1; BG.Ei=-BG.Phi; BG.charge_T(); plot(BG.charge*0.144*sqrt(3)*1e-9); hold a=loadtxt("carica.plusminus"); plot(a,'o') show() print(max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))) if (max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))<5e-5): string4="PASSED" else: string4="NOT PASSED" print(max(abs(a-BG.charge*0.144*sqrt(3)*1e-9))) fp=open("bilayer_test","w"); string5="TEST on bilayer \n Test 1: %s \n Test 2: %s \n Test 3: %s \n Test 4: %s \n" %(string,string2,string3,string4); fp.write(string5); fp.close() #show()

17.815068

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0.590927

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2,601

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2,601

145

120

17.937931

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0

null

0

1

0

null

0

1

0

2

83baccd90e553fca59c4116ef6b652786e64cf56

1,814

py

Python

utilities/generator.py

RogerGee/php-git2

ec8092016e379c79ba0ab3304e684c9a074b218c

[ "MIT" ]

2

2019-05-13T12:31:15.000Z

2021-07-12T13:50:15.000Z

utilities/generator.py

RogerGee/php-git2

ec8092016e379c79ba0ab3304e684c9a074b218c

[ "MIT" ]

null

utilities/generator.py

RogerGee/php-git2

ec8092016e379c79ba0ab3304e684c9a074b218c

[ "MIT" ]

null

#!/usr/bin/env python # # generator.py # # Use this script to generate templates for a set of function bindings. Pipe the # function names, one per line, to this program. It first generates the template # declarations and then generates the function entry macro. import re import sys def genFunc(func): print ("static constexpr auto ZIF_{} = zif_php_git2_function<\n" \ + " php_git2::func_wrapper<\n" \ + "\n" \ + " >::func<{}>,\n" \ + " php_git2::local_pack<\n" \ + "\n" \ + " >,\n" \ + " -1,\n" \ + " php_git2::sequence<>,\n" \ + " php_git2::sequence<>,\n" \ + " php_git2::sequence<>\n" \ + " >;\n").format(func.upper(),func) def genFreeFunc(func,section): print ("static constexpr auto ZIF_{} = zif_php_git2_function_free<\n" \ " php_git2::local_pack<\n" \ " php_git2::php_resource_cleanup<php_git2::php_{}>\n" \ " >\n" \ " >;\n").format(func.upper(),section) def genDefine(func,trailing = True): print " PHP_GIT2_FE({},ZIF_{},NULL){}".format(func,func.upper()," \\" if trailing else "") def genDoc(func): print "{}()".format(func) names = [] while True: line = sys.stdin.readline() if len(line) == 0: break func = re.search("[^\s]+",line) if func is None: print "error: bad input: '{}'".format(line) name = func.group(0) names.append(name) match = re.search("(.*)_free$",name) if match: genFreeFunc(name,match.group(1)) else: genFunc(name) print "#define GIT___FE \\" for i in range(len(names)): genDefine(names[i], i + 1 < len(names)) print "" print "-"*40 print "[git_]" print "-"*40 for name in names: genDoc(name)

27.074627

97

0.551819

230

1,814

4.217391

0.395652

0.079381

0.057732

0.049485

0.214433

0.180412

0.143299

0

0.015129

0.271224

1,814

66

98

27.484848

0.718608

0.137266

0

0.122449

1

0

0.330552

0.173941

0

null

0

0.040816

null

0.204082

0

null

0

1

0

null

0

1

0

2

83c6d674a547b24f4e6713ae599c43f3801f2901

519

py

Python

ebl/dictionary/web/bootstrap.py

ElectronicBabylonianLiterature/dictionary

5977a57314cf57f94f75cd12520f178b1d6a6555

[ "MIT" ]

null

ebl/dictionary/web/bootstrap.py

ElectronicBabylonianLiterature/dictionary

5977a57314cf57f94f75cd12520f178b1d6a6555

[ "MIT" ]

null

ebl/dictionary/web/bootstrap.py

ElectronicBabylonianLiterature/dictionary

5977a57314cf57f94f75cd12520f178b1d6a6555

[ "MIT" ]

null

import falcon from ebl.context import Context from ebl.dictionary.application.dictionary import Dictionary from ebl.dictionary.web.word_search import WordSearch from ebl.dictionary.web.words import WordsResource def create_dictionary_routes(api: falcon.App, context: Context): dictionary = Dictionary(context.word_repository, context.changelog) words = WordsResource(dictionary) word_search = WordSearch(dictionary) api.add_route("/words", word_search) api.add_route("/words/{object_id}", words)

34.6

71

0.795761

65

519

6.215385

0.369231

0.069307

0.126238

0.09901

0

0.115607

519

14

72

37.071429

0.880174

0

0.046243

0

1

0.090909

false

0

0.454545

0

0.545455

0

null

0

null

0

1

0

1

0

2

83d35e8b67f7fe3524402d845a60b2ed832f68d2

500

py

Python

hsir/__init__.py

WenjieZ/wuhan-pneumonia

3d26955daa2deedec57cdd3effb3118531bbea7f

[ "BSD-3-Clause" ]

6

2020-01-26T07:33:41.000Z

2020-02-25T22:15:43.000Z

hsir/__init__.py

WenjieZ/wuhan-pneumonia

3d26955daa2deedec57cdd3effb3118531bbea7f

[ "BSD-3-Clause" ]

2

2020-02-17T16:12:50.000Z

2020-02-29T21:31:17.000Z

hsir/__init__.py

WenjieZ/wuhan-pneumonia

3d26955daa2deedec57cdd3effb3118531bbea7f

[ "BSD-3-Clause" ]

1

2020-03-07T00:13:05.000Z

from .utils import * from .law import * from .norm import * from .empirical import * from .sir import * from .sirq import * from .sirt import * from .sirqt import * __all__ = ['Id', 'JumpProcess', 'Law', 'Bin', 'Poi', 'Gau', 'variation1', 'variation2', 'elastic_net', 'Region', 'Epidemic', 'Sample', 'Confirmed', 'Resisted', 'SIR', 'InferSIR', 'SIRQ', 'InferSIRQ', 'SIRt', 'InferSIRt', 'SIRQt', 'InferSIRQt', ]

25

67

0.538

48

500

5.5

0.604167

0.265152

0

0.00565

0.292

500

19

68

26.315789

0.740113

0

0.29

0

1

0

false

0

0.470588

0

0.470588

0

null

1

0

null

0

1

0

2

83d3986613ac445839d15243517f52ee08b5825b

239

py

Python

dagger/dag_creator/airflow/utils/utils.py

jorgetagle/dagger

dafcfb9df904e512f050aefdacf6581c571bac23

[ "MIT" ]

5

2020-09-09T11:44:49.000Z

2021-12-31T14:07:00.000Z

dagger/dag_creator/airflow/utils/utils.py

jorgetagle/dagger

dafcfb9df904e512f050aefdacf6581c571bac23

[ "MIT" ]

null

dagger/dag_creator/airflow/utils/utils.py

jorgetagle/dagger

dafcfb9df904e512f050aefdacf6581c571bac23

[ "MIT" ]

3

2021-08-31T10:14:42.000Z

2022-02-28T17:03:39.000Z

from pathlib import Path def get_sql_queries(path): sql_queries = {} for query_file in Path(path).glob("*.sql"): with open(query_file, "r") as f: sql_queries[query_file.stem] = f.read() return sql_queries

23.9

51

0.640167

36

239

4.027778

0.583333

0.275862

0

0.238494

239

9

52

26.555556

0.796703

0

0.025105

0

1

0.142857

false

0

0.142857

0

0.428571

0

null

1

0

1

0

null

0

2

83d4347102f8d7fc0cdbbc3324f10dea48926a95

7,983

py

Python

pyaz/network/watcher/connection_monitor/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

null

pyaz/network/watcher/connection_monitor/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

null

pyaz/network/watcher/connection_monitor/__init__.py

py-az-cli/py-az-cli

9a7dc44e360c096a5a2f15595353e9dad88a9792

[ "MIT" ]

1

2022-02-03T09:12:01.000Z

from .... pyaz_utils import _call_az from . import endpoint, output, test_configuration, test_group def create(name, dest_address=None, dest_port=None, dest_resource=None, do_not_start=None, endpoint_dest_address=None, endpoint_dest_coverage_level=None, endpoint_dest_name=None, endpoint_dest_resource_id=None, endpoint_dest_type=None, endpoint_source_address=None, endpoint_source_coverage_level=None, endpoint_source_name=None, endpoint_source_resource_id=None, endpoint_source_type=None, frequency=None, http_method=None, http_path=None, http_port=None, http_valid_status_codes=None, https_prefer=None, icmp_disable_trace_route=None, location=None, monitoring_interval=None, notes=None, output_type=None, preferred_ip_version=None, protocol=None, resource_group=None, source_port=None, source_resource=None, tags=None, tcp_disable_trace_route=None, tcp_port=None, tcp_port_behavior=None, test_config_name=None, test_group_disable=None, test_group_name=None, threshold_failed_percent=None, threshold_round_trip_time=None, workspace_ids=None): ''' Create a connection monitor. Required Parameters: - name -- Connection monitor name. Optional Parameters: - dest_address -- The IP address or URI at which to receive traffic. - dest_port -- Port number on which to receive traffic. - dest_resource -- Name of ID of the resource to receive traffic. Currently only Virtual Machines are supported. - do_not_start -- Create the connection monitor but do not start it immediately. - endpoint_dest_address -- Address of the destination of connection monitor endpoint (IP or domain name) - endpoint_dest_coverage_level -- Test coverage for the endpoint - endpoint_dest_name -- The name of the destination of connection monitor endpoint. If you are creating a V2 Connection Monitor, it's required - endpoint_dest_resource_id -- Resource ID of the destination of connection monitor endpoint - endpoint_dest_type -- The endpoint type - endpoint_source_address -- Address of the source of connection monitor endpoint (IP or domain name) - endpoint_source_coverage_level -- Test coverage for the endpoint - endpoint_source_name -- The name of the source of connection monitor endpoint. If you are creating a V2 Connection Monitor, it's required - endpoint_source_resource_id -- Resource ID of the source of connection monitor endpoint. If endpoint is intended to used as source, this option is required. - endpoint_source_type -- The endpoint type - frequency -- The frequency of test evaluation, in seconds - http_method -- The HTTP method to use - http_path -- The path component of the URI. For instance, "/dir1/dir2" - http_port -- The port to connect to - http_valid_status_codes -- Space-separated list of HTTP status codes to consider successful. For instance, "2xx 301-304 418" - https_prefer -- Value indicating whether HTTPS is preferred over HTTP in cases where the choice is not explicit - icmp_disable_trace_route -- Value indicating whether path evaluation with trace route should be disabled. false is default. - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`. - monitoring_interval -- Monitoring interval in seconds. - notes -- Optional notes to be associated with the connection monitor - output_type -- Connection monitor output destination type. Currently, only "Workspace" is supported - preferred_ip_version -- The preferred IP version to use in test evaluation. The connection monitor may choose to use a different version depending on other parameters - protocol -- The protocol to use in test evaluation - resource_group -- Name of resource group. You can configure the default group using `az configure --defaults group=<name>` - source_port -- Port number from which to originate traffic. - source_resource -- Name or ID of the resource from which to originate traffic. Currently only Virtual Machines are supported. - tags -- space-separated tags: key[=value] [key[=value] ...]. Use '' to clear existing tags. - tcp_disable_trace_route -- Value indicating whether path evaluation with trace route should be disabled. false is default. - tcp_port -- The port to connect to - tcp_port_behavior -- Destination port behavior - test_config_name -- The name of the connection monitor test configuration. If you are creating a V2 Connection Monitor, it's required - test_group_disable -- Value indicating whether test group is disabled. false is default. - test_group_name -- The name of the connection monitor test group - threshold_failed_percent -- The maximum percentage of failed checks permitted for a test to evaluate as successful - threshold_round_trip_time -- The maximum round-trip time in milliseconds permitted for a test to evaluate as successful - workspace_ids -- Space-separated list of ids of log analytics workspace ''' return _call_az("az network watcher connection-monitor create", locals()) def delete(location, name, resource_group=None): ''' Delete a connection monitor for the given region. Required Parameters: - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`. - name -- Connection monitor name. Optional Parameters: - resource_group -- ==SUPPRESS== ''' return _call_az("az network watcher connection-monitor delete", locals()) def show(location, name, resource_group=None): ''' Shows a connection monitor by name. Required Parameters: - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`. - name -- Connection monitor name. Optional Parameters: - resource_group -- ==SUPPRESS== ''' return _call_az("az network watcher connection-monitor show", locals()) def stop(location, name, resource_group=None): ''' Stop the specified connection monitor. Required Parameters: - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`. - name -- Connection monitor name. Optional Parameters: - resource_group -- ==SUPPRESS== ''' return _call_az("az network watcher connection-monitor stop", locals()) def start(location, name, resource_group=None): ''' Start the specified connection monitor. Required Parameters: - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`. - name -- Connection monitor name. Optional Parameters: - resource_group -- ==SUPPRESS== ''' return _call_az("az network watcher connection-monitor start", locals()) def query(location, name, resource_group=None): ''' Query a snapshot of the most recent connection state of a connection monitor. Required Parameters: - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`. - name -- Connection monitor name. Optional Parameters: - resource_group -- ==SUPPRESS== ''' return _call_az("az network watcher connection-monitor query", locals()) def list(location, resource_group=None): ''' List connection monitors for the given region. Required Parameters: - location -- Location. Values from: `az account list-locations`. You can configure the default location using `az configure --defaults location=<location>`. Optional Parameters: - resource_group -- ==SUPPRESS== ''' return _call_az("az network watcher connection-monitor list", locals())

57.431655

944

0.749217

1,060

7,983

5.492453

0.166038

0.099279

0.020611

0.024734

0.551872

0.488664

0.46685

0.435933

0.37719

0.360357

0

0.002271

0.172742

7,983

138

945

57.847826

0.879316

0.711011

0

0.156904

0

1

0.4375

false

0

0.125

0

1

0

null

0

null

0

1

0

1

0

2

83df9264ba2ce4b89fcbdd158f066fbadf85c82d

8,703

py

Python

airmozilla/manage/tests/test_event_hit_stats.py

anurag90x/airmozilla

c758fb86695e16891e45dc24a2cf1406c54f2686

[ "BSD-3-Clause" ]

null

airmozilla/manage/tests/test_event_hit_stats.py

anurag90x/airmozilla

c758fb86695e16891e45dc24a2cf1406c54f2686

[ "BSD-3-Clause" ]

null

airmozilla/manage/tests/test_event_hit_stats.py

anurag90x/airmozilla

c758fb86695e16891e45dc24a2cf1406c54f2686

[ "BSD-3-Clause" ]

null

import datetime from cStringIO import StringIO from nose.tools import eq_, ok_ import mock from django.utils import timezone from django.test import TestCase from airmozilla.manage import event_hit_stats from airmozilla.main.models import Event, EventHitStats, Template SAMPLE_STATISTICS_XML = ( '<?xml version="1.0"?>' '<Response><Message/><MessageCode/><Success><StatsInfo><StatsTable>' '<cols><col>Class</col><col>Vendor</col><col>Model</col>' '<col>Platform</col><col>OS</col><col>Browser</col><col>Browser Ver</col>' '<col>Hits</col></cols><rows><row><col>Desktop</col><col></col><col></col>' '<col></col><col>Apple</col><col>Firefox</col><col>21.0</col><col>5</col>' '</row><row><col>Desktop</col><col></col><col></col><col></col>' '<col>Apple</col><col>Firefox</col><col>20.0</col><col>2</col></row>' '</rows></StatsTable><Others>0</Others><TotalHits>%s</TotalHits>' '</StatsInfo></Success></Response>' ) def non_signal_save(obj, **kwargs): obj.__class__.objects.filter(pk=obj.pk).update(**kwargs) class EventHitStatsTestCase(TestCase): fixtures = ['airmozilla/manage/tests/main_testdata.json'] @mock.patch('urllib2.urlopen') def test_update(self, p_urlopen): calls = [] def mocked_urlopen(request): calls.append(1) assert 'abc123' in request.data return StringIO((SAMPLE_STATISTICS_XML % (10,)).strip()) p_urlopen.side_effect = mocked_urlopen assert not EventHitStats.objects.count() assert Event.objects.all() assert Event.objects.archived().all() eq_(event_hit_stats.update(), 0) assert not EventHitStats.objects.count() vidly_template = Template.objects.create(name='Vid.ly Template') event, = Event.objects.archived().all() event.template = vidly_template event.template_environment = {'tag': 'abc123'} event.save() eq_(event_hit_stats.update(), 1) assert EventHitStats.objects.count() stat, = EventHitStats.objects.all() eq_(stat.event, event) eq_(stat.total_hits, 10) eq_(stat.shortcode, 'abc123') eq_(len(calls), 1) # do it again and nothing should happen eq_(event_hit_stats.update(), 0) eq_(len(calls), 1) # let's pretend the event is half an hour old now = timezone.now() half_hour_ago = now - datetime.timedelta(minutes=30) # event.update(modified=event.modified - half_hour_ago) # non_signal_save(event, modified=half_hour_ago) eq_(event_hit_stats.update(), 0) eq_(len(calls), 1) # ...because the EventHitStats was modified too recently non_signal_save(stat, modified=half_hour_ago) non_signal_save(event, modified=half_hour_ago) eq_(event_hit_stats.update(), 0) eq_(len(calls), 1) # it needs to be at least one hour old hour_ago = now - datetime.timedelta(minutes=60, seconds=1) non_signal_save(stat, modified=hour_ago) non_signal_save(event, modified=hour_ago) eq_(event_hit_stats.update(), 1) eq_(len(calls), 2) # a second time, nothing should happen eq_(event_hit_stats.update(), 0) eq_(len(calls), 2) # let's pretend it's even older day_ago = now - datetime.timedelta(hours=24, seconds=1) non_signal_save(stat, modified=day_ago) non_signal_save(event, modified=day_ago) eq_(event_hit_stats.update(), 1) eq_(len(calls), 3) # second time, nothing should happen eq_(event_hit_stats.update(), 0) eq_(len(calls), 3) # even older still week_ago = now - datetime.timedelta(days=7, seconds=1) non_signal_save(stat, modified=week_ago) non_signal_save(event, modified=week_ago) eq_(event_hit_stats.update(), 1) eq_(len(calls), 4) # second time, nothing should happen eq_(event_hit_stats.update(), 0) eq_(len(calls), 4) @mock.patch('airmozilla.manage.event_hit_stats.logging') @mock.patch('urllib2.urlopen') def test_first_update_with_errors(self, p_urlopen, mock_logging): def mocked_urlopen(request): raise IOError('foo') p_urlopen.side_effect = mocked_urlopen vidly_template = Template.objects.create(name='Vid.ly Template') event, = Event.objects.archived().all() event.template = vidly_template event.template_environment = {'tag': ''} event.save() eq_(event_hit_stats.update(), 0) mock_logging.warn.assert_called_with( 'Event %r does not have a Vid.ly tag', event.title ) event.template_environment = {'tag': 'abc123'} event.save() self.assertRaises( IOError, event_hit_stats.update ) eq_(event_hit_stats.update(swallow_errors=True), 0) mock_logging.error.assert_called_with( 'Unable to download statistics for %r (tag: %s)', event.title, 'abc123' ) @mock.patch('urllib2.urlopen') def test_update_new_tag(self, p_urlopen): def mocked_urlopen(request): assert 'xyz987' in request.data return StringIO((SAMPLE_STATISTICS_XML % (10,)).strip()) p_urlopen.side_effect = mocked_urlopen vidly_template = Template.objects.create(name='Vid.ly Template') event, = Event.objects.archived().all() event.template = vidly_template event.template_environment = {'tag': 'abc123'} event.save() stat = EventHitStats.objects.create( event=event, shortcode='abc123', total_hits=5, ) event.template_environment = {'tag': 'xyz987'} event.save() # set them back two days now = timezone.now() days_ago = now - datetime.timedelta(hours=24 * 2, seconds=1) non_signal_save(stat, modified=days_ago) non_signal_save( event, modified=days_ago + datetime.timedelta(seconds=1) ) eq_(event_hit_stats.update(), 1) stat = EventHitStats.objects.get(pk=stat.pk) eq_(stat.total_hits, 10) eq_(stat.shortcode, 'xyz987') @mock.patch('urllib2.urlopen') def test_update_removed_tag(self, p_urlopen): def mocked_urlopen(request): assert 'xyz987' in request.data return StringIO((SAMPLE_STATISTICS_XML % (10,)).strip()) p_urlopen.side_effect = mocked_urlopen vidly_template = Template.objects.create(name='Vid.ly Template') event, = Event.objects.archived().all() event.template = vidly_template event.template_environment = {'tag': 'abc123'} event.save() stat = EventHitStats.objects.create( event=event, shortcode='abc123', total_hits=5, ) event.template_environment = {'foo': 'bar'} event.save() # set them back two days now = timezone.now() days_ago = now - datetime.timedelta(hours=24 * 2, seconds=1) non_signal_save(stat, modified=days_ago) non_signal_save( event, modified=days_ago + datetime.timedelta(seconds=1) ) eq_(event_hit_stats.update(), 0) ok_(not EventHitStats.objects.all().count()) @mock.patch('airmozilla.manage.event_hit_stats.logging') @mock.patch('urllib2.urlopen') def test_update_with_errors(self, p_urlopen, mock_logging): def mocked_urlopen(request): raise IOError('boo!') p_urlopen.side_effect = mocked_urlopen vidly_template = Template.objects.create(name='Vid.ly Template') event, = Event.objects.archived().all() event.template = vidly_template event.template_environment = {'tag': 'abc123'} event.save() stat = EventHitStats.objects.create( event=event, shortcode='abc123', total_hits=5, ) # set them back two days now = timezone.now() days_ago = now - datetime.timedelta(hours=24 * 2, seconds=1) non_signal_save(stat, modified=days_ago) non_signal_save( event, modified=days_ago + datetime.timedelta(seconds=1) ) self.assertRaises( IOError, event_hit_stats.update ) eq_(event_hit_stats.update(swallow_errors=True), 0) mock_logging.error.assert_called_with( 'Unable to download statistics for %r (tag: %s)', event.title, 'abc123' )

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83e450fcc4a3f50dd35481308fb48db2f167bb8f

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py

Python

envs/real/robot.py

cww97/visual-language-grasping

f96404c9997ef55ede07293ce319ca19a39ae5ec

[ "BSD-2-Clause" ]

3

2020-05-08T11:14:21.000Z

2021-07-09T15:30:01.000Z

envs/real/robot.py

cww97/visual-language-grasping

f96404c9997ef55ede07293ce319ca19a39ae5ec

[ "BSD-2-Clause" ]

4

2020-03-10T13:24:43.000Z

2021-07-13T06:09:03.000Z

envs/real/robot.py

cww97/visual-language-grasping

f96404c9997ef55ede07293ce319ca19a39ae5ec

[ "BSD-2-Clause" ]

1

2021-04-23T01:38:46.000Z

import socket import struct import time import numpy as np import utils from .camera import Camera from ..robot import Robot as BaseRobot class RealRobot(BaseRobot): def __init__(self, tcp_host_ip, tcp_port, rtc_host_ip, rtc_port, workspace_limits): BaseRobot.__init__(self, workspace_limits) # Connect to robot client self.tcp_host_ip = tcp_host_ip self.tcp_port = tcp_port # self.tcp_socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) # Connect as real-time client to parse state data self.rtc_host_ip = rtc_host_ip self.rtc_port = rtc_port # Default home joint configuration # self.home_joint_config = [-np.pi, -np.pi/2, np.pi/2, -np.pi/2, -np.pi/2, 0] self.home_joint_config = [-(180.0 / 360.0) * 2 * np.pi, -(84.2 / 360.0) * 2 * np.pi, (112.8 / 360.0) * 2 * np.pi, -(119.7 / 360.0) * 2 * np.pi, -(90.0 / 360.0) * 2 * np.pi, 0.0] # Default joint speed configuration self.joint_acc = 8 # Safe: 1.4 self.joint_vel = 3 # Safe: 1.05 # Joint tolerance for blocking calls self.joint_tolerance = 0.01 # Default tool speed configuration self.tool_acc = 1.2 # Safe: 0.5 self.tool_vel = 0.25 # Safe: 0.2 # Tool pose tolerance for blocking calls self.tool_pose_tolerance = [0.002, 0.002, 0.002, 0.01, 0.01, 0.01] # Move robot to home pose self.close_gripper() self.go_home() # Fetch RGB-D data from RealSense camera self.camera = Camera() self.cam_intrinsics = self.camera.intrinsics # Load camera pose (from running calibrate.py), intrinsics and depth scale self.cam_pose = np.loadtxt('real/camera_pose.txt', delimiter=' ') self.cam_depth_scale = np.loadtxt('real/camera_depth_scale.txt', delimiter=' ') def get_camera_data(self): # Get color and depth image from ROS service color_img, depth_img = self.camera.get_data() # color_img = self.camera.color_data.copy() # depth_img = self.camera.depth_data.copy() return color_img, depth_img @staticmethod def parse_tcp_state_data(state_data, subpackage): # Read package header data_bytes = bytearray() data_bytes.extend(state_data) data_length = struct.unpack("!i", data_bytes[0:4])[0] robot_message_type = data_bytes[4] assert (robot_message_type == 16) byte_idx = 5 # Parse sub-packages subpackage_types = {'joint_data': 1, 'cartesian_info': 4, 'force_mode_data': 7, 'tool_data': 2} while byte_idx < data_length: # package_length = int.from_bytes(data_bytes[byte_idx:(byte_idx+4)], byteorder='big', signed=False) package_length = struct.unpack("!i", data_bytes[byte_idx:(byte_idx + 4)])[0] byte_idx += 4 package_idx = data_bytes[byte_idx] if package_idx == subpackage_types[subpackage]: byte_idx += 1 break byte_idx += package_length - 4 def parse_joint_data(data_bytes, byte_idx): actual_joint_positions = [0, 0, 0, 0, 0, 0] target_joint_positions = [0, 0, 0, 0, 0, 0] for joint_idx in range(6): actual_joint_positions[joint_idx] = struct.unpack('!d', data_bytes[(byte_idx + 0):(byte_idx + 8)])[0] target_joint_positions[joint_idx] = struct.unpack('!d', data_bytes[(byte_idx + 8):(byte_idx + 16)])[0] byte_idx += 41 return actual_joint_positions def parse_cartesian_info(data_bytes, byte_idx): actual_tool_pose = [0, 0, 0, 0, 0, 0] for pose_value_idx in range(6): actual_tool_pose[pose_value_idx] = struct.unpack('!d', data_bytes[(byte_idx + 0):(byte_idx + 8)])[0] byte_idx += 8 return actual_tool_pose def parse_tool_data(data_bytes, byte_idx): byte_idx += 2 tool_analog_input2 = struct.unpack('!d', data_bytes[(byte_idx + 0):(byte_idx + 8)])[0] return tool_analog_input2 parse_functions = {'joint_data': parse_joint_data, 'cartesian_info': parse_cartesian_info, 'tool_data': parse_tool_data} return parse_functions[subpackage](data_bytes, byte_idx) def parse_rtc_state_data(self, state_data): # Read package header data_bytes = bytearray() data_bytes.extend(state_data) data_length = struct.unpack("!i", data_bytes[0:4])[0] assert (data_length == 812) byte_idx = 4 + 8 + 8 * 48 + 24 + 120 TCP_forces = [0, 0, 0, 0, 0, 0] for joint_idx in range(6): TCP_forces[joint_idx] = struct.unpack('!d', data_bytes[(byte_idx + 0):(byte_idx + 8)])[0] byte_idx += 8 return TCP_forces def get_instruction(self): raise NotImplementedError() def close_gripper(self, _async=False): self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "set_digital_out(8,True)\n" self.tcp_socket.send(str.encode(tcp_command)) self.tcp_socket.close() if _async: gripper_fully_closed = True else: time.sleep(1.5) gripper_fully_closed = self.check_grasp() return gripper_fully_closed def open_gripper(self, _async=False): self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "set_digital_out(8,False)\n" self.tcp_socket.send(str.encode(tcp_command)) self.tcp_socket.close() if not _async: time.sleep(1.5) def get_state(self): self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) state_data = self.tcp_socket.recv(2048) self.tcp_socket.close() return state_data def move_to(self, tool_position, tool_orientation): self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "movel(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0)\n" % (tool_position[0], tool_position[1], tool_position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.tool_acc, self.tool_vel) self.tcp_socket.send(str.encode(tcp_command)) # Block until robot reaches target tool position tcp_state_data = self.tcp_socket.recv(2048) actual_tool_pose = self.parse_tcp_state_data(tcp_state_data, 'cartesian_info') while not all([np.abs(actual_tool_pose[j] - tool_position[j]) < self.tool_pose_tolerance[j] for j in range(3)]): # [min(np.abs(actual_tool_pose[j] - tool_orientation[j-3]), np.abs(np.abs(actual_tool_pose[j] - tool_orientation[j-3]) - np.pi*2)) < self.tool_pose_tolerance[j] for j in range(3,6)] # print([np.abs(actual_tool_pose[j] - tool_position[j]) for j in range(3)] + [min(np.abs(actual_tool_pose[j] - tool_orientation[j-3]), np.abs(np.abs(actual_tool_pose[j] - tool_orientation[j-3]) - np.pi*2)) for j in range(3,6)]) tcp_state_data = self.tcp_socket.recv(2048) # prev_actual_tool_pose = np.asarray(actual_tool_pose).copy() actual_tool_pose = self.parse_tcp_state_data(tcp_state_data, 'cartesian_info') time.sleep(0.01) self.tcp_socket.close() def guarded_move_to(self, tool_position, tool_orientation): self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.rtc_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) self.rtc_socket.connect((self.rtc_host_ip, self.rtc_port)) # Read actual tool position tcp_state_data = self.tcp_socket.recv(2048) actual_tool_pose = self.parse_tcp_state_data(tcp_state_data, 'cartesian_info') execute_success = True # Increment every cm, check force self.tool_acc = 0.1 # 1.2 # 0.5 while not all([np.abs(actual_tool_pose[j] - tool_position[j]) < self.tool_pose_tolerance[j] for j in range(3)]): # [min(np.abs(actual_tool_pose[j] - tool_orientation[j-3]), np.abs(np.abs(actual_tool_pose[j] - tool_orientation[j-3]) - np.pi*2)) < self.tool_pose_tolerance[j] for j in range(3,6)] # Compute motion trajectory in 1cm increments increment = np.asarray([(tool_position[j] - actual_tool_pose[j]) for j in range(3)]) if np.linalg.norm(increment) < 0.01: increment_position = tool_position else: increment = 0.01 * increment / np.linalg.norm(increment) increment_position = np.asarray(actual_tool_pose[0:3]) + increment # Move to next increment position (blocking call) tcp_command = "movel(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0)\n" % (increment_position[0], increment_position[1], increment_position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.tool_acc, self.tool_vel) self.tcp_socket.send(str.encode(tcp_command)) time_start = time.time() tcp_state_data = self.tcp_socket.recv(2048) actual_tool_pose = self.parse_tcp_state_data(tcp_state_data, 'cartesian_info') while not all([np.abs(actual_tool_pose[j] - increment_position[j]) < self.tool_pose_tolerance[j] for j in range(3)]): # print([np.abs(actual_tool_pose[j] - increment_position[j]) for j in range(3)]) tcp_state_data = self.tcp_socket.recv(2048) actual_tool_pose = self.parse_tcp_state_data(tcp_state_data, 'cartesian_info') time_snapshot = time.time() if time_snapshot - time_start > 1: break time.sleep(0.01) # Reading TCP forces from real-time client connection rtc_state_data = self.rtc_socket.recv(6496) TCP_forces = self.parse_rtc_state_data(rtc_state_data) # If TCP forces in x/y exceed 20 Newtons, stop moving # print(TCP_forces[0:3]) if np.linalg.norm(np.asarray(TCP_forces[0:2])) > 20 or (time_snapshot - time_start) > 1: print('Warning: contact detected! Movement halted. TCP forces: [%f, %f, %f]' % (TCP_forces[0], TCP_forces[1], TCP_forces[2])) execute_success = False break time.sleep(0.01) self.tool_acc = 1.2 # 1.2 # 0.5 self.tcp_socket.close() self.rtc_socket.close() return execute_success def move_joints(self, joint_configuration): self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "movej([%f" % joint_configuration[0] for joint_idx in range(1, 6): tcp_command = tcp_command + (",%f" % joint_configuration[joint_idx]) tcp_command = tcp_command + "],a=%f,v=%f)\n" % (self.joint_acc, self.joint_vel) self.tcp_socket.send(str.encode(tcp_command)) # Block until robot reaches home state state_data = self.tcp_socket.recv(2048) actual_joint_positions = self.parse_tcp_state_data(state_data, 'joint_data') while not all([np.abs(actual_joint_positions[j] - joint_configuration[j]) < self.joint_tolerance for j in range(6)]): state_data = self.tcp_socket.recv(2048) actual_joint_positions = self.parse_tcp_state_data(state_data, 'joint_data') time.sleep(0.01) self.tcp_socket.close() def go_home(self): self.move_joints(self.home_joint_config) # Note: must be preceded by close_gripper() def check_grasp(self): state_data = self.get_state() tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') return tool_analog_input2 > 0.26 # Primitives ---------------------------------------------------------- def grasp(self, position, heightmap_rotation_angle, workspace_limits): print('Executing: grasp at (%f, %f, %f)' % (position[0], position[1], position[2])) # Compute tool orientation from heightmap rotation angle grasp_orientation = [1.0, 0.0] if heightmap_rotation_angle > np.pi: heightmap_rotation_angle = heightmap_rotation_angle - 2 * np.pi tool_rotation_angle = heightmap_rotation_angle / 2 tool_orientation = np.asarray([grasp_orientation[0] * np.cos(tool_rotation_angle) - grasp_orientation[1] * np.sin(tool_rotation_angle), grasp_orientation[0] * np.sin(tool_rotation_angle) + grasp_orientation[1] * np.cos(tool_rotation_angle), 0.0]) * np.pi tool_orientation_angle = np.linalg.norm(tool_orientation) tool_orientation_axis = tool_orientation / tool_orientation_angle tool_orientation_rotm = utils.angle2rotm(tool_orientation_angle, tool_orientation_axis, point=None)[:3, :3] # Compute tilted tool orientation during dropping into bin tilt_rotm = utils.euler2rotm(np.asarray([-np.pi / 4, 0, 0])) tilted_tool_orientation_rotm = np.dot(tilt_rotm, tool_orientation_rotm) tilted_tool_orientation_axis_angle = utils.rotm2angle(tilted_tool_orientation_rotm) tilted_tool_orientation = tilted_tool_orientation_axis_angle[0] * np.asarray(tilted_tool_orientation_axis_angle[1:4]) # Attempt grasp position = np.asarray(position).copy() position[2] = max(position[2] - 0.05, workspace_limits[2][0]) self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "def process():\n" tcp_command += " set_digital_out(8,False)\n" tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.09)\n" % (position[0], position[1], position[2] + 0.1, tool_orientation[0], tool_orientation[1], 0.0, self.joint_acc * 0.5, self.joint_vel * 0.5) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (position[0], position[1], position[2], tool_orientation[0], tool_orientation[1], 0.0, self.joint_acc * 0.1, self.joint_vel * 0.1) tcp_command += " set_digital_out(8,True)\n" tcp_command += "end\n" self.tcp_socket.send(str.encode(tcp_command)) self.tcp_socket.close() # Block until robot reaches target tool position and gripper fingers have stopped moving state_data = self.get_state() tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') timeout_t0 = time.time() while True: state_data = self.get_state() new_tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') actual_tool_pose = self.parse_tcp_state_data(state_data, 'cartesian_info') timeout_t1 = time.time() if (tool_analog_input2 < 3.7 and (abs(new_tool_analog_input2 - tool_analog_input2) < 0.01) and all([np.abs(actual_tool_pose[j] - position[j]) < self.tool_pose_tolerance[j] for j in range(3)])) or (timeout_t1 - timeout_t0) > 5: break tool_analog_input2 = new_tool_analog_input2 # Check if gripper is open (grasp might be successful) gripper_open = tool_analog_input2 > 0.26 # # Check if grasp is successful # grasp_success = tool_analog_input2 > 0.26 home_position = [0.49, 0.11, 0.03] bin_position = [0.5, -0.45, 0.1] # If gripper is open, drop object in bin and check if grasp is successful grasp_success = False if gripper_open: # Pre-compute blend radius blend_radius = min(abs(bin_position[1] - position[1]) / 2 - 0.01, 0.2) # Attempt placing self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "def process():\n" tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=%f)\n" % (position[0], position[1], bin_position[2], tool_orientation[0], tool_orientation[1], 0.0, self.joint_acc, self.joint_vel, blend_radius) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=%f)\n" % (bin_position[0], bin_position[1], bin_position[2], tilted_tool_orientation[0], tilted_tool_orientation[1], tilted_tool_orientation[2], self.joint_acc, self.joint_vel, blend_radius) tcp_command += " set_digital_out(8,False)\n" tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.0)\n" % (home_position[0], home_position[1], home_position[2], tool_orientation[0], tool_orientation[1], 0.0, self.joint_acc * 0.5, self.joint_vel * 0.5) tcp_command += "end\n" self.tcp_socket.send(str.encode(tcp_command)) self.tcp_socket.close() # print(tcp_command) # Debug # Measure gripper width until robot reaches near bin location state_data = self.get_state() measurements = [] while True: state_data = self.get_state() tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') actual_tool_pose = self.parse_tcp_state_data(state_data, 'cartesian_info') measurements.append(tool_analog_input2) if abs(actual_tool_pose[1] - bin_position[1]) < 0.2 or all([np.abs(actual_tool_pose[j] - home_position[j]) < self.tool_pose_tolerance[j] for j in range(3)]): break # If gripper width did not change before reaching bin location, then object is in grip and grasp is successful if len(measurements) >= 2: if abs(measurements[0] - measurements[1]) < 0.1: grasp_success = True else: self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "def process():\n" tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.09)\n" % (position[0], position[1], position[2] + 0.1, tool_orientation[0], tool_orientation[1], 0.0, self.joint_acc * 0.5, self.joint_vel * 0.5) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.0)\n" % (home_position[0], home_position[1], home_position[2], tool_orientation[0], tool_orientation[1], 0.0, self.joint_acc * 0.5, self.joint_vel * 0.5) tcp_command += "end\n" self.tcp_socket.send(str.encode(tcp_command)) self.tcp_socket.close() # Block until robot reaches home location state_data = self.get_state() tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') actual_tool_pose = self.parse_tcp_state_data(state_data, 'cartesian_info') while True: state_data = self.get_state() new_tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') actual_tool_pose = self.parse_tcp_state_data(state_data, 'cartesian_info') if (abs(new_tool_analog_input2 - tool_analog_input2) < 0.01) and all([np.abs(actual_tool_pose[j] - home_position[j]) < self.tool_pose_tolerance[j] for j in range(3)]): break tool_analog_input2 = new_tool_analog_input2 return grasp_success def push(self, position, heightmap_rotation_angle, workspace_limits): print('Executing: push at (%f, %f, %f)' % (position[0], position[1], position[2])) # Compute tool orientation from heightmap rotation angle push_orientation = [1.0, 0.0] tool_rotation_angle = heightmap_rotation_angle / 2 tool_orientation = np.asarray([push_orientation[0] * np.cos(tool_rotation_angle) - push_orientation[1] * np.sin(tool_rotation_angle), push_orientation[0] * np.sin(tool_rotation_angle) + push_orientation[1] * np.cos(tool_rotation_angle), 0.0]) * np.pi tool_orientation_angle = np.linalg.norm(tool_orientation) tool_orientation_axis = tool_orientation / tool_orientation_angle tool_orientation_rotm = utils.angle2rotm(tool_orientation_angle, tool_orientation_axis, point=None)[:3, :3] # Compute push direction and endpoint (push to right of rotated heightmap) push_direction = np.asarray([push_orientation[0] * np.cos(heightmap_rotation_angle) - push_orientation[1] * np.sin(heightmap_rotation_angle), push_orientation[0] * np.sin(heightmap_rotation_angle) + push_orientation[1] * np.cos(heightmap_rotation_angle), 0.0]) target_x = min(max(position[0] + push_direction[0] * 0.1, workspace_limits[0][0]), workspace_limits[0][1]) target_y = min(max(position[1] + push_direction[1] * 0.1, workspace_limits[1][0]), workspace_limits[1][1]) push_endpoint = np.asarray([target_x, target_y, position[2]]) push_direction.shape = (3, 1) # Compute tilted tool orientation during push tilt_axis = np.dot(utils.euler2rotm(np.asarray([0, 0, np.pi / 2]))[:3, :3], push_direction) tilt_rotm = utils.angle2rotm(-np.pi / 8, tilt_axis, point=None)[:3, :3] tilted_tool_orientation_rotm = np.dot(tilt_rotm, tool_orientation_rotm) tilted_tool_orientation_axis_angle = utils.rotm2angle(tilted_tool_orientation_rotm) tilted_tool_orientation = tilted_tool_orientation_axis_angle[0] * np.asarray(tilted_tool_orientation_axis_angle[1:4]) # Push only within workspace limits position = np.asarray(position).copy() position[0] = min(max(position[0], workspace_limits[0][0]), workspace_limits[0][1]) position[1] = min(max(position[1], workspace_limits[1][0]), workspace_limits[1][1]) position[2] = max(position[2] + 0.005, workspace_limits[2][0] + 0.005) # Add buffer to surface home_position = [0.49, 0.11, 0.03] # Attempt push self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "def process():\n" tcp_command += " set_digital_out(8,True)\n" tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.09)\n" % (position[0], position[1], position[2] + 0.1, tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc * 0.5, self.joint_vel * 0.5) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (position[0], position[1], position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc * 0.1, self.joint_vel * 0.1) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (push_endpoint[0], push_endpoint[1], push_endpoint[2], tilted_tool_orientation[0], tilted_tool_orientation[1], tilted_tool_orientation[2], self.joint_acc * 0.1, self.joint_vel * 0.1) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.03)\n" % (position[0], position[1], position[2] + 0.1, tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc * 0.5, self.joint_vel * 0.5) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (home_position[0], home_position[1], home_position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc * 0.5, self.joint_vel * 0.5) tcp_command += "end\n" self.tcp_socket.send(str.encode(tcp_command)) self.tcp_socket.close() # Block until robot reaches target tool position and gripper fingers have stopped moving state_data = self.get_state() while True: state_data = self.get_state() actual_tool_pose = self.parse_tcp_state_data(state_data, 'cartesian_info') if all([np.abs(actual_tool_pose[j] - home_position[j]) < self.tool_pose_tolerance[j] for j in range(3)]): break push_success = True time.sleep(0.5) return push_success def restart_real(self): # Compute tool orientation from heightmap rotation angle grasp_orientation = [1.0, 0.0] tool_rotation_angle = -np.pi / 4 tool_orientation = np.asarray([grasp_orientation[0] * np.cos(tool_rotation_angle) - grasp_orientation[1] * np.sin(tool_rotation_angle), grasp_orientation[0] * np.sin(tool_rotation_angle) + grasp_orientation[1] * np.cos(tool_rotation_angle), 0.0]) * np.pi tool_orientation_angle = np.linalg.norm(tool_orientation) tool_orientation_axis = tool_orientation / tool_orientation_angle tool_orientation_rotm = utils.angle2rotm(tool_orientation_angle, tool_orientation_axis, point=None)[:3, :3] tilt_rotm = utils.euler2rotm(np.asarray([-np.pi / 4, 0, 0])) tilted_tool_orientation_rotm = np.dot(tilt_rotm, tool_orientation_rotm) tilted_tool_orientation_axis_angle = utils.rotm2angle(tilted_tool_orientation_rotm) tilted_tool_orientation = tilted_tool_orientation_axis_angle[0] * np.asarray(tilted_tool_orientation_axis_angle[1:4]) # Move to box grabbing position box_grab_position = [0.5, -0.35, -0.12] self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "def process():\n" tcp_command += " set_digital_out(8,False)\n" tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.09)\n" % (box_grab_position[0], box_grab_position[1], box_grab_position[2] + 0.1, tilted_tool_orientation[0], tilted_tool_orientation[1], tilted_tool_orientation[2], self.joint_acc, self.joint_vel) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (box_grab_position[0], box_grab_position[1], box_grab_position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc, self.joint_vel) tcp_command += " set_digital_out(8,True)\n" tcp_command += "end\n" self.tcp_socket.send(str.encode(tcp_command)) self.tcp_socket.close() # Block until robot reaches box grabbing position and gripper fingers have stopped moving state_data = self.get_state() tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') while True: state_data = self.get_state() new_tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') actual_tool_pose = self.parse_tcp_state_data(state_data, 'cartesian_info') if tool_analog_input2 < 3.7 and (abs(new_tool_analog_input2 - tool_analog_input2) < 0.01) and all([np.abs(actual_tool_pose[j] - box_grab_position[j]) < self.tool_pose_tolerance[j] for j in range(3)]): break tool_analog_input2 = new_tool_analog_input2 # Move to box release position box_release_position = [0.5, 0.08, -0.12] home_position = [0.49, 0.11, 0.03] self.tcp_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self.tcp_socket.connect((self.tcp_host_ip, self.tcp_port)) tcp_command = "def process():\n" tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (box_release_position[0], box_release_position[1], box_release_position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc * 0.1, self.joint_vel * 0.1) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (box_release_position[0], box_release_position[1], box_release_position[2] + 0.3, tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc * 0.02, self.joint_vel * 0.02) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.29)\n" % (box_grab_position[0] - 0.05, box_grab_position[1] + 0.1, box_grab_position[2] + 0.3, tilted_tool_orientation[0], tilted_tool_orientation[1], tilted_tool_orientation[2], self.joint_acc * 0.5, self.joint_vel * 0.5) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (box_grab_position[0] - 0.05, box_grab_position[1] + 0.1, box_grab_position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc * 0.5, self.joint_vel * 0.5) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (box_grab_position[0], box_grab_position[1], box_grab_position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc * 0.1, self.joint_vel * 0.1) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (box_grab_position[0] + 0.05, box_grab_position[1], box_grab_position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc * 0.1, self.joint_vel * 0.1) tcp_command += " set_digital_out(8,False)\n" tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.09)\n" % (box_grab_position[0], box_grab_position[1], box_grab_position[2] + 0.1, tilted_tool_orientation[0], tilted_tool_orientation[1], tilted_tool_orientation[2], self.joint_acc, self.joint_vel) tcp_command += " movej(p[%f,%f,%f,%f,%f,%f],a=%f,v=%f,t=0,r=0.00)\n" % (home_position[0], home_position[1], home_position[2], tool_orientation[0], tool_orientation[1], tool_orientation[2], self.joint_acc, self.joint_vel) tcp_command += "end\n" self.tcp_socket.send(str.encode(tcp_command)) self.tcp_socket.close() # Block until robot reaches home position state_data = self.get_state() tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') while True: state_data = self.get_state() new_tool_analog_input2 = self.parse_tcp_state_data(state_data, 'tool_data') actual_tool_pose = self.parse_tcp_state_data(state_data, 'cartesian_info') if tool_analog_input2 > 3.0 and (abs(new_tool_analog_input2 - tool_analog_input2) < 0.01) and all([np.abs(actual_tool_pose[j] - home_position[j]) < self.tool_pose_tolerance[j] for j in range(3)]): break tool_analog_input2 = new_tool_analog_input2 # def place(self, position, orientation, workspace_limits): # print('Executing: place at (%f, %f, %f)' % (position[0], position[1], position[2])) # # Attempt placing # position[2] = max(position[2], workspace_limits[2][0]) # self.move_to([position[0], position[1], position[2] + 0.2], orientation) # self.move_to([position[0], position[1], position[2] + 0.05], orientation) # self.tool_acc = 1 # 0.05 # self.tool_vel = 0.02 # 0.02 # self.move_to([position[0], position[1], position[2]], orientation) # self.open_gripper() # self.tool_acc = 1 # 0.5 # self.tool_vel = 0.2 # 0.2 # self.move_to([position[0], position[1], position[2] + 0.2], orientation) # self.close_gripper() # self.go_home()

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4.016646

0.067004

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0.015737

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0.719561

0.694382

0.666789

0.652153

0.631485

0

0.038233

0.210091

31,158

526

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0.736307

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0.065934

0.079692

0.053461

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1

0.052198

false

0

0.019231

0

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null

0

1

0

1

0

null

0

2

83e7df11f7a30a1a6ea7f7518c0377a94ddead08

1,806

py

Python

Qualification/no_parking/main.py

galavasteg/YXProgChallenge2019

4dcdbdcc92f1efec89bdc4c7009024cf66800750

[ "MIT" ]

null

Qualification/no_parking/main.py

galavasteg/YXProgChallenge2019

4dcdbdcc92f1efec89bdc4c7009024cf66800750

[ "MIT" ]

null

Qualification/no_parking/main.py

galavasteg/YXProgChallenge2019

4dcdbdcc92f1efec89bdc4c7009024cf66800750

[ "MIT" ]

null

""" В одном городе запретили машинам останавливаться, кроме как для посадки пасажира. А пассажир не согласен ждать больше 3 минут. В этом городе пешеход заказывает такси в точку X и указывает интервал в 180 секунд. Водитель должен приехать ровно в этот интервал. Если приехать раньше, то ожидать пассажира будет нельзя. Если приехать слишком поздно, то разозленный пассажир отменит заказ. Из-за подобных ограничений в этом городе осталось всего Z водителей, каждый из которых в момент старта задачи находится в какой-то вершине графа дорожного движения. Система управления должна назначить наилучшего водителя из тех, которые успеют приехать в указанный интервал. Наилучшим водителем считается тот, который приедет на заказ максимально близко к началу интервала. Если таких водителей несколько, то любой из них. Нужно для каждого водителя определить, успевает ли он приехать в указанный интервал, и если да - то к какому самому раннему моменту времени в указанном интервале он может приехать. Формальное описание Дано: 1. Ориентированный граф G с N вершинами и K ребрами, вершины пронумерованы от 0 до N-1, 0 ≤ N ≤ 10^4, 0 ≤ K ≤ 10^4. Каждому ребру соответствует время поездки в нем - целое число W, 10 ≤ W ≤ 10^4. 2. Позиция заказа на графе ID_target 3. Z позиций водителей на графе ID_sourcez, 1 ≤ Z ≤ 10^4 4. Время t0, 0 ≤ t0 ≤ 600 - целое число Надо для каждого водителя найти такоe t_min что: 1. существует такой маршрут от ID_sourcez водителя к ID_target, что водитель приезжает в t_min 2. t_min ∈ [t0; t0+180] 3. и это самый ранний возможный t_min : t_min ≤ t_i для любого t_i, удовлетворяющего пунктам 1 и 2; 4. Или убедиться, что такого t_min не существует """ from pathlib import Path scriptDir = Path.cwd() def main(): pass if __name__ == '__main__': main()

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52

0.769103

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4.542763

0.588816

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0.011586

0.037654

0

0.02977

0.181617

1,806

58

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31.137931

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0.166667

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0.333333

0

null

0

1

0

null

0

1

0

2

83ee2bc08be92b2e2f6dc79b6f57d5f107b6c5a7

361

py

Python

src/combustion/lightning/metrics/__init__.py

TidalPaladin/combustion

69b9a2b9baf90b81ed9098b4f0391f5c15efaee7

[ "Apache-2.0" ]

3

2020-07-09T22:18:19.000Z

2021-11-08T03:47:19.000Z

src/combustion/lightning/metrics/__init__.py

TidalPaladin/combustion

69b9a2b9baf90b81ed9098b4f0391f5c15efaee7

[ "Apache-2.0" ]

15

2020-06-12T21:48:59.000Z

2022-02-05T18:41:50.000Z

src/combustion/lightning/metrics/__init__.py

TidalPaladin/combustion

69b9a2b9baf90b81ed9098b4f0391f5c15efaee7

[ "Apache-2.0" ]

1

2021-02-15T20:06:16.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- from .auroc import BoxAUROC from .average_precision import BoxAveragePrecision from .confidence import BootstrapMixin from .entropy import Entropy from .uncertainty import ECE, UCE, ErrorAtUncertainty __all__ = ["BoxAveragePrecision", "BoxAUROC", "BootstrapMixin", "Entropy", "ECE", "UCE", "ErrorAtUncertainty"]

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110

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7.131579

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0.04428

0.177122

0

0.003125

0.113573

361

11

111

32.818182

0.84375

0.116343

0

0.227129

0

1

0

false

0

0.833333

0

0.833333

0

null

0

null

0

1

0

1

0

2

83f06d01eec1969a06fa163324b2ddf8e8cd172e

507

py

Python

fam_assignment/video_collector/models.py

deepanshnagaria/Youtube-Video-Collector

1ee5dac77ab0386c0d4e62f049d1f37af94bba7c

[ "MIT" ]

1

2020-10-13T11:01:45.000Z

fam_assignment/video_collector/models.py

deepanshnagaria/Youtube-Video-Collector

1ee5dac77ab0386c0d4e62f049d1f37af94bba7c

[ "MIT" ]

null

fam_assignment/video_collector/models.py

deepanshnagaria/Youtube-Video-Collector

1ee5dac77ab0386c0d4e62f049d1f37af94bba7c

[ "MIT" ]

null

from django.db import models from datetime import datetime from django.contrib.postgres.fields import ArrayField class Video(models.Model): title = models.CharField(max_length=100) description = models.CharField(max_length=1000) published_at = models.DateTimeField() urls = ArrayField( models.URLField(max_length=100, blank=True), blank = True, null = True, ) channelTitle = models.CharField(max_length=100) def __str__(self): return self.title

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0

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null

0

1

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2

8600657de42e110981abec23d5d5d28989baaafc

183

py

Python

spam.py

lucasnogueiragomes/Bot-Spam-Whatsapp

b5bffefab4094cc2a7099e4899de49c4866fe289

[ "MIT" ]

1

2021-11-21T03:57:15.000Z

spam.py

lucasnogueiragomes/Bot-Spam-Whatsapp

b5bffefab4094cc2a7099e4899de49c4866fe289

[ "MIT" ]

null

spam.py

lucasnogueiragomes/Bot-Spam-Whatsapp

b5bffefab4094cc2a7099e4899de49c4866fe289

[ "MIT" ]

null

import pyautogui, time time.sleep(10) texto = open('roteiro.txt') for frase in texto: pyautogui.typewrite(frase) pyautogui.press('enter')

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8601472200cfb4131cb1477e3f96cef8536f43a9

2,301

py

Python

cloudrail/knowledge/context/aws/efs/efs_mount_target.py

my-devops-info/cloudrail-knowledge

b7c1bbd6fe1faeb79c105a01c0debbe24d031a0e

[ "MIT" ]

null

cloudrail/knowledge/context/aws/efs/efs_mount_target.py

my-devops-info/cloudrail-knowledge

b7c1bbd6fe1faeb79c105a01c0debbe24d031a0e

[ "MIT" ]

null

cloudrail/knowledge/context/aws/efs/efs_mount_target.py

my-devops-info/cloudrail-knowledge

b7c1bbd6fe1faeb79c105a01c0debbe24d031a0e

[ "MIT" ]

null

from typing import List, Optional from dataclasses import dataclass from cloudrail.knowledge.context.aws.networking_config.network_configuration import NetworkConfiguration from cloudrail.knowledge.context.aws.networking_config.network_entity import NetworkEntity from cloudrail.knowledge.context.aws.service_name import AwsServiceName @dataclass class MountTargetSecurityGroups: security_groups_ids: List[str] mount_target_id: str class EfsMountTarget(NetworkEntity): """ Attributes: efs_id: The ID of the EFS the mount target belongs to. mount_target_id: The ID of the mount target. eni_id: The ID of the elastic network interface the target is using. subnet_id: The ID of the subnet the EFS Mount Target is on. security_groups_ids: The security groups protecting the target. """ def __init__(self, account: str, region: str, efs_id: str, mount_target_id: str, eni_id: str, subnet_id: str, security_groups_ids: Optional[List[str]]): super().__init__(mount_target_id, account, region, AwsServiceName.AWS_EFS_MOUNT_TARGET) self.mount_target_id: str = mount_target_id self.efs_id: str = efs_id self.eni_id: str = eni_id self.subnet_id: str = subnet_id self.security_groups_ids: Optional[List[str]] = security_groups_ids def get_keys(self) -> List[str]: return [self.mount_target_id] def get_name(self) -> str: return f'mount target with id: {self.mount_target_id}' def get_arn(self) -> str: pass def get_type(self, is_plural: bool = False) -> str: if not is_plural: return 'EFS mount target' else: return 'EFS mount targets' def get_all_network_configurations(self) -> Optional[List[NetworkConfiguration]]: return [NetworkConfiguration(False, self.security_groups_ids, [self.subnet_id])] def get_cloud_resource_url(self) -> str: return '{0}efs/home?region={1}#/file-systems/{2}?tabId=mounts' \ .format(self.AWS_CONSOLE_URL, self.region, self.efs_id) @property def is_tagable(self) -> bool: return False

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0

null

0

null

0

1

0

2

f7a321a5c6b8c025d43176f17113ca2fbebab2a7

37,316

py

Python

google/cloud/datastore/_generated/datastore_pb2.py

Ofekmeister/google-cloud-python

07dd51bc447beca67b8da1c66f1dfb944ef70418

[ "Apache-2.0" ]

1

2018-12-09T01:32:50.000Z

google/cloud/datastore/_generated/datastore_pb2.py

Ofekmeister/google-cloud-python

07dd51bc447beca67b8da1c66f1dfb944ef70418

[ "Apache-2.0" ]

null

google/cloud/datastore/_generated/datastore_pb2.py

Ofekmeister/google-cloud-python

07dd51bc447beca67b8da1c66f1dfb944ef70418

[ "Apache-2.0" ]

1

2020-09-04T00:05:30.000Z

# Generated by the protocol buffer compiler. DO NOT EDIT! # source: google/datastore/v1/datastore.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database from google.protobuf import descriptor_pb2 # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from google.api import annotations_pb2 as google_dot_api_dot_annotations__pb2 from google.cloud.datastore._generated import entity_pb2 as google_dot_datastore_dot_v1_dot_entity__pb2 from google.cloud.datastore._generated import query_pb2 as google_dot_datastore_dot_v1_dot_query__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='google/datastore/v1/datastore.proto', package='google.datastore.v1', syntax='proto3', serialized_pb=_b('\n#google/datastore/v1/datastore.proto\x12\x13google.datastore.v1\x1a\x1cgoogle/api/annotations.proto\x1a google/datastore/v1/entity.proto\x1a\x1fgoogle/datastore/v1/query.proto\"\x83\x01\n\rLookupRequest\x12\x12\n\nproject_id\x18\x08 \x01(\t\x12\x36\n\x0cread_options\x18\x01 \x01(\x0b\x32 .google.datastore.v1.ReadOptions\x12&\n\x04keys\x18\x03 \x03(\x0b\x32\x18.google.datastore.v1.Key\"\xa2\x01\n\x0eLookupResponse\x12\x30\n\x05\x66ound\x18\x01 \x03(\x0b\x32!.google.datastore.v1.EntityResult\x12\x32\n\x07missing\x18\x02 \x03(\x0b\x32!.google.datastore.v1.EntityResult\x12*\n\x08\x64\x65\x66\x65rred\x18\x03 \x03(\x0b\x32\x18.google.datastore.v1.Key\"\x84\x02\n\x0fRunQueryRequest\x12\x12\n\nproject_id\x18\x08 \x01(\t\x12\x36\n\x0cpartition_id\x18\x02 \x01(\x0b\x32 .google.datastore.v1.PartitionId\x12\x36\n\x0cread_options\x18\x01 \x01(\x0b\x32 .google.datastore.v1.ReadOptions\x12+\n\x05query\x18\x03 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\x03(\x0b\x32\x1d.google.datastore.v1.Mutation\"F\n\x04Mode\x12\x14\n\x10MODE_UNSPECIFIED\x10\x00\x12\x11\n\rTRANSACTIONAL\x10\x01\x12\x15\n\x11NON_TRANSACTIONAL\x10\x02\x42\x16\n\x14transaction_selector\"f\n\x0e\x43ommitResponse\x12=\n\x10mutation_results\x18\x03 \x03(\x0b\x32#.google.datastore.v1.MutationResult\x12\x15\n\rindex_updates\x18\x04 \x01(\x05\"P\n\x12\x41llocateIdsRequest\x12\x12\n\nproject_id\x18\x08 \x01(\t\x12&\n\x04keys\x18\x01 \x03(\x0b\x32\x18.google.datastore.v1.Key\"=\n\x13\x41llocateIdsResponse\x12&\n\x04keys\x18\x01 \x03(\x0b\x32\x18.google.datastore.v1.Key\"\x87\x02\n\x08Mutation\x12-\n\x06insert\x18\x04 \x01(\x0b\x32\x1b.google.datastore.v1.EntityH\x00\x12-\n\x06update\x18\x05 \x01(\x0b\x32\x1b.google.datastore.v1.EntityH\x00\x12-\n\x06upsert\x18\x06 \x01(\x0b\x32\x1b.google.datastore.v1.EntityH\x00\x12*\n\x06\x64\x65lete\x18\x07 \x01(\x0b\x32\x18.google.datastore.v1.KeyH\x00\x12\x16\n\x0c\x62\x61se_version\x18\x08 \x01(\x03H\x01\x42\x0b\n\toperationB\x1d\n\x1b\x63onflict_detection_strategy\"c\n\x0eMutationResult\x12%\n\x03key\x18\x03 \x01(\x0b\x32\x18.google.datastore.v1.Key\x12\x0f\n\x07version\x18\x04 \x01(\x03\x12\x19\n\x11\x63onflict_detected\x18\x05 \x01(\x08\"\xd5\x01\n\x0bReadOptions\x12L\n\x10read_consistency\x18\x01 \x01(\x0e\x32\x30.google.datastore.v1.ReadOptions.ReadConsistencyH\x00\x12\x15\n\x0btransaction\x18\x02 \x01(\x0cH\x00\"M\n\x0fReadConsistency\x12 \n\x1cREAD_CONSISTENCY_UNSPECIFIED\x10\x00\x12\n\n\x06STRONG\x10\x01\x12\x0c\n\x08\x45VENTUAL\x10\x02\x42\x12\n\x10\x63onsistency_type2\xdb\x06\n\tDatastore\x12~\n\x06Lookup\x12\".google.datastore.v1.LookupRequest\x1a#.google.datastore.v1.LookupResponse\"+\x82\xd3\xe4\x93\x02%\" /v1/projects/{project_id}:lookup:\x01*\x12\x86\x01\n\x08RunQuery\x12$.google.datastore.v1.RunQueryRequest\x1a%.google.datastore.v1.RunQueryResponse\"-\x82\xd3\xe4\x93\x02\'\"\"/v1/projects/{project_id}:runQuery:\x01*\x12\xa6\x01\n\x10\x42\x65ginTransaction\x12,.google.datastore.v1.BeginTransactionRequest\x1a-.google.datastore.v1.BeginTransactionResponse\"5\x82\xd3\xe4\x93\x02/\"*/v1/projects/{project_id}:beginTransaction:\x01*\x12~\n\x06\x43ommit\x12\".google.datastore.v1.CommitRequest\x1a#.google.datastore.v1.CommitResponse\"+\x82\xd3\xe4\x93\x02%\" /v1/projects/{project_id}:commit:\x01*\x12\x86\x01\n\x08Rollback\x12$.google.datastore.v1.RollbackRequest\x1a%.google.datastore.v1.RollbackResponse\"-\x82\xd3\xe4\x93\x02\'\"\"/v1/projects/{project_id}:rollback:\x01*\x12\x92\x01\n\x0b\x41llocateIds\x12\'.google.datastore.v1.AllocateIdsRequest\x1a(.google.datastore.v1.AllocateIdsResponse\"0\x82\xd3\xe4\x93\x02*\"%/v1/projects/{project_id}:allocateIds:\x01*B+\n\x17\x63om.google.datastore.v1B\x0e\x44\x61tastoreProtoP\x01\x62\x06proto3') , dependencies=[google_dot_api_dot_annotations__pb2.DESCRIPTOR,google_dot_datastore_dot_v1_dot_entity__pb2.DESCRIPTOR,google_dot_datastore_dot_v1_dot_query__pb2.DESCRIPTOR,]) _sym_db.RegisterFileDescriptor(DESCRIPTOR) _COMMITREQUEST_MODE = _descriptor.EnumDescriptor( name='Mode', full_name='google.datastore.v1.CommitRequest.Mode', filename=None, file=DESCRIPTOR, values=[ _descriptor.EnumValueDescriptor( name='MODE_UNSPECIFIED', index=0, number=0, options=None, type=None), _descriptor.EnumValueDescriptor( name='TRANSACTIONAL', index=1, number=1, options=None, type=None), _descriptor.EnumValueDescriptor( name='NON_TRANSACTIONAL', index=2, number=2, options=None, type=None), ], containing_type=None, options=None, serialized_start=1178, serialized_end=1248, ) _sym_db.RegisterEnumDescriptor(_COMMITREQUEST_MODE) _READOPTIONS_READCONSISTENCY = _descriptor.EnumDescriptor( name='ReadConsistency', full_name='google.datastore.v1.ReadOptions.ReadConsistency', filename=None, file=DESCRIPTOR, values=[ _descriptor.EnumValueDescriptor( name='READ_CONSISTENCY_UNSPECIFIED', index=0, number=0, options=None, type=None), _descriptor.EnumValueDescriptor( name='STRONG', index=1, number=1, options=None, type=None), _descriptor.EnumValueDescriptor( name='EVENTUAL', index=2, number=2, options=None, type=None), ], containing_type=None, options=None, serialized_start=2007, serialized_end=2084, ) _sym_db.RegisterEnumDescriptor(_READOPTIONS_READCONSISTENCY) _LOOKUPREQUEST = _descriptor.Descriptor( name='LookupRequest', full_name='google.datastore.v1.LookupRequest', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='project_id', full_name='google.datastore.v1.LookupRequest.project_id', index=0, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='read_options', full_name='google.datastore.v1.LookupRequest.read_options', index=1, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='keys', full_name='google.datastore.v1.LookupRequest.keys', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=158, serialized_end=289, ) _LOOKUPRESPONSE = _descriptor.Descriptor( name='LookupResponse', full_name='google.datastore.v1.LookupResponse', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='found', full_name='google.datastore.v1.LookupResponse.found', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='missing', full_name='google.datastore.v1.LookupResponse.missing', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='deferred', full_name='google.datastore.v1.LookupResponse.deferred', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=292, serialized_end=454, ) _RUNQUERYREQUEST = _descriptor.Descriptor( name='RunQueryRequest', full_name='google.datastore.v1.RunQueryRequest', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='project_id', full_name='google.datastore.v1.RunQueryRequest.project_id', index=0, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='partition_id', full_name='google.datastore.v1.RunQueryRequest.partition_id', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='read_options', full_name='google.datastore.v1.RunQueryRequest.read_options', index=2, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='query', full_name='google.datastore.v1.RunQueryRequest.query', index=3, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='gql_query', full_name='google.datastore.v1.RunQueryRequest.gql_query', index=4, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='query_type', full_name='google.datastore.v1.RunQueryRequest.query_type', index=0, containing_type=None, fields=[]), ], serialized_start=457, serialized_end=717, ) _RUNQUERYRESPONSE = _descriptor.Descriptor( name='RunQueryResponse', full_name='google.datastore.v1.RunQueryResponse', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='batch', full_name='google.datastore.v1.RunQueryResponse.batch', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='query', full_name='google.datastore.v1.RunQueryResponse.query', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=719, serialized_end=834, ) _BEGINTRANSACTIONREQUEST = _descriptor.Descriptor( name='BeginTransactionRequest', full_name='google.datastore.v1.BeginTransactionRequest', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='project_id', full_name='google.datastore.v1.BeginTransactionRequest.project_id', index=0, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=836, serialized_end=881, ) _BEGINTRANSACTIONRESPONSE = _descriptor.Descriptor( name='BeginTransactionResponse', full_name='google.datastore.v1.BeginTransactionResponse', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='transaction', full_name='google.datastore.v1.BeginTransactionResponse.transaction', index=0, number=1, type=12, cpp_type=9, label=1, has_default_value=False, default_value=_b(""), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=883, serialized_end=930, ) _ROLLBACKREQUEST = _descriptor.Descriptor( name='RollbackRequest', full_name='google.datastore.v1.RollbackRequest', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='project_id', full_name='google.datastore.v1.RollbackRequest.project_id', index=0, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='transaction', full_name='google.datastore.v1.RollbackRequest.transaction', index=1, number=1, type=12, cpp_type=9, label=1, has_default_value=False, default_value=_b(""), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=932, serialized_end=990, ) _ROLLBACKRESPONSE = _descriptor.Descriptor( name='RollbackResponse', full_name='google.datastore.v1.RollbackResponse', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=992, serialized_end=1010, ) _COMMITREQUEST = _descriptor.Descriptor( name='CommitRequest', full_name='google.datastore.v1.CommitRequest', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='project_id', full_name='google.datastore.v1.CommitRequest.project_id', index=0, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='mode', full_name='google.datastore.v1.CommitRequest.mode', index=1, number=5, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='transaction', full_name='google.datastore.v1.CommitRequest.transaction', index=2, number=1, type=12, cpp_type=9, label=1, has_default_value=False, default_value=_b(""), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='mutations', full_name='google.datastore.v1.CommitRequest.mutations', index=3, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ _COMMITREQUEST_MODE, ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='transaction_selector', full_name='google.datastore.v1.CommitRequest.transaction_selector', index=0, containing_type=None, fields=[]), ], serialized_start=1013, serialized_end=1272, ) _COMMITRESPONSE = _descriptor.Descriptor( name='CommitResponse', full_name='google.datastore.v1.CommitResponse', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='mutation_results', full_name='google.datastore.v1.CommitResponse.mutation_results', index=0, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='index_updates', full_name='google.datastore.v1.CommitResponse.index_updates', index=1, number=4, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1274, serialized_end=1376, ) _ALLOCATEIDSREQUEST = _descriptor.Descriptor( name='AllocateIdsRequest', full_name='google.datastore.v1.AllocateIdsRequest', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='project_id', full_name='google.datastore.v1.AllocateIdsRequest.project_id', index=0, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='keys', full_name='google.datastore.v1.AllocateIdsRequest.keys', index=1, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1378, serialized_end=1458, ) _ALLOCATEIDSRESPONSE = _descriptor.Descriptor( name='AllocateIdsResponse', full_name='google.datastore.v1.AllocateIdsResponse', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='keys', full_name='google.datastore.v1.AllocateIdsResponse.keys', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1460, serialized_end=1521, ) _MUTATION = _descriptor.Descriptor( name='Mutation', full_name='google.datastore.v1.Mutation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='insert', full_name='google.datastore.v1.Mutation.insert', index=0, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='update', full_name='google.datastore.v1.Mutation.update', index=1, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='upsert', full_name='google.datastore.v1.Mutation.upsert', index=2, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='delete', full_name='google.datastore.v1.Mutation.delete', index=3, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='base_version', full_name='google.datastore.v1.Mutation.base_version', index=4, number=8, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='operation', full_name='google.datastore.v1.Mutation.operation', index=0, containing_type=None, fields=[]), _descriptor.OneofDescriptor( name='conflict_detection_strategy', full_name='google.datastore.v1.Mutation.conflict_detection_strategy', index=1, containing_type=None, fields=[]), ], serialized_start=1524, serialized_end=1787, ) _MUTATIONRESULT = _descriptor.Descriptor( name='MutationResult', full_name='google.datastore.v1.MutationResult', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='key', full_name='google.datastore.v1.MutationResult.key', index=0, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='version', full_name='google.datastore.v1.MutationResult.version', index=1, number=4, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='conflict_detected', full_name='google.datastore.v1.MutationResult.conflict_detected', index=2, number=5, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1789, serialized_end=1888, ) _READOPTIONS = _descriptor.Descriptor( name='ReadOptions', full_name='google.datastore.v1.ReadOptions', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='read_consistency', full_name='google.datastore.v1.ReadOptions.read_consistency', index=0, number=1, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='transaction', full_name='google.datastore.v1.ReadOptions.transaction', index=1, number=2, type=12, cpp_type=9, label=1, has_default_value=False, default_value=_b(""), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ _READOPTIONS_READCONSISTENCY, ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='consistency_type', full_name='google.datastore.v1.ReadOptions.consistency_type', index=0, containing_type=None, fields=[]), ], serialized_start=1891, serialized_end=2104, ) _LOOKUPREQUEST.fields_by_name['read_options'].message_type = _READOPTIONS _LOOKUPREQUEST.fields_by_name['keys'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._KEY _LOOKUPRESPONSE.fields_by_name['found'].message_type = google_dot_datastore_dot_v1_dot_query__pb2._ENTITYRESULT _LOOKUPRESPONSE.fields_by_name['missing'].message_type = google_dot_datastore_dot_v1_dot_query__pb2._ENTITYRESULT _LOOKUPRESPONSE.fields_by_name['deferred'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._KEY _RUNQUERYREQUEST.fields_by_name['partition_id'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._PARTITIONID _RUNQUERYREQUEST.fields_by_name['read_options'].message_type = _READOPTIONS _RUNQUERYREQUEST.fields_by_name['query'].message_type = google_dot_datastore_dot_v1_dot_query__pb2._QUERY _RUNQUERYREQUEST.fields_by_name['gql_query'].message_type = google_dot_datastore_dot_v1_dot_query__pb2._GQLQUERY _RUNQUERYREQUEST.oneofs_by_name['query_type'].fields.append( _RUNQUERYREQUEST.fields_by_name['query']) _RUNQUERYREQUEST.fields_by_name['query'].containing_oneof = _RUNQUERYREQUEST.oneofs_by_name['query_type'] _RUNQUERYREQUEST.oneofs_by_name['query_type'].fields.append( _RUNQUERYREQUEST.fields_by_name['gql_query']) _RUNQUERYREQUEST.fields_by_name['gql_query'].containing_oneof = _RUNQUERYREQUEST.oneofs_by_name['query_type'] _RUNQUERYRESPONSE.fields_by_name['batch'].message_type = google_dot_datastore_dot_v1_dot_query__pb2._QUERYRESULTBATCH _RUNQUERYRESPONSE.fields_by_name['query'].message_type = google_dot_datastore_dot_v1_dot_query__pb2._QUERY _COMMITREQUEST.fields_by_name['mode'].enum_type = _COMMITREQUEST_MODE _COMMITREQUEST.fields_by_name['mutations'].message_type = _MUTATION _COMMITREQUEST_MODE.containing_type = _COMMITREQUEST _COMMITREQUEST.oneofs_by_name['transaction_selector'].fields.append( _COMMITREQUEST.fields_by_name['transaction']) _COMMITREQUEST.fields_by_name['transaction'].containing_oneof = _COMMITREQUEST.oneofs_by_name['transaction_selector'] _COMMITRESPONSE.fields_by_name['mutation_results'].message_type = _MUTATIONRESULT _ALLOCATEIDSREQUEST.fields_by_name['keys'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._KEY _ALLOCATEIDSRESPONSE.fields_by_name['keys'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._KEY _MUTATION.fields_by_name['insert'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._ENTITY _MUTATION.fields_by_name['update'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._ENTITY _MUTATION.fields_by_name['upsert'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._ENTITY _MUTATION.fields_by_name['delete'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._KEY _MUTATION.oneofs_by_name['operation'].fields.append( _MUTATION.fields_by_name['insert']) _MUTATION.fields_by_name['insert'].containing_oneof = _MUTATION.oneofs_by_name['operation'] _MUTATION.oneofs_by_name['operation'].fields.append( _MUTATION.fields_by_name['update']) _MUTATION.fields_by_name['update'].containing_oneof = _MUTATION.oneofs_by_name['operation'] _MUTATION.oneofs_by_name['operation'].fields.append( _MUTATION.fields_by_name['upsert']) _MUTATION.fields_by_name['upsert'].containing_oneof = _MUTATION.oneofs_by_name['operation'] _MUTATION.oneofs_by_name['operation'].fields.append( _MUTATION.fields_by_name['delete']) _MUTATION.fields_by_name['delete'].containing_oneof = _MUTATION.oneofs_by_name['operation'] _MUTATION.oneofs_by_name['conflict_detection_strategy'].fields.append( _MUTATION.fields_by_name['base_version']) _MUTATION.fields_by_name['base_version'].containing_oneof = _MUTATION.oneofs_by_name['conflict_detection_strategy'] _MUTATIONRESULT.fields_by_name['key'].message_type = google_dot_datastore_dot_v1_dot_entity__pb2._KEY _READOPTIONS.fields_by_name['read_consistency'].enum_type = _READOPTIONS_READCONSISTENCY _READOPTIONS_READCONSISTENCY.containing_type = _READOPTIONS _READOPTIONS.oneofs_by_name['consistency_type'].fields.append( _READOPTIONS.fields_by_name['read_consistency']) _READOPTIONS.fields_by_name['read_consistency'].containing_oneof = _READOPTIONS.oneofs_by_name['consistency_type'] _READOPTIONS.oneofs_by_name['consistency_type'].fields.append( _READOPTIONS.fields_by_name['transaction']) _READOPTIONS.fields_by_name['transaction'].containing_oneof = _READOPTIONS.oneofs_by_name['consistency_type'] DESCRIPTOR.message_types_by_name['LookupRequest'] = _LOOKUPREQUEST DESCRIPTOR.message_types_by_name['LookupResponse'] = _LOOKUPRESPONSE DESCRIPTOR.message_types_by_name['RunQueryRequest'] = _RUNQUERYREQUEST DESCRIPTOR.message_types_by_name['RunQueryResponse'] = _RUNQUERYRESPONSE DESCRIPTOR.message_types_by_name['BeginTransactionRequest'] = _BEGINTRANSACTIONREQUEST DESCRIPTOR.message_types_by_name['BeginTransactionResponse'] = _BEGINTRANSACTIONRESPONSE DESCRIPTOR.message_types_by_name['RollbackRequest'] = _ROLLBACKREQUEST DESCRIPTOR.message_types_by_name['RollbackResponse'] = _ROLLBACKRESPONSE DESCRIPTOR.message_types_by_name['CommitRequest'] = _COMMITREQUEST DESCRIPTOR.message_types_by_name['CommitResponse'] = _COMMITRESPONSE DESCRIPTOR.message_types_by_name['AllocateIdsRequest'] = _ALLOCATEIDSREQUEST DESCRIPTOR.message_types_by_name['AllocateIdsResponse'] = _ALLOCATEIDSRESPONSE DESCRIPTOR.message_types_by_name['Mutation'] = _MUTATION DESCRIPTOR.message_types_by_name['MutationResult'] = _MUTATIONRESULT DESCRIPTOR.message_types_by_name['ReadOptions'] = _READOPTIONS LookupRequest = _reflection.GeneratedProtocolMessageType('LookupRequest', (_message.Message,), dict( DESCRIPTOR = _LOOKUPREQUEST, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.LookupRequest) )) _sym_db.RegisterMessage(LookupRequest) LookupResponse = _reflection.GeneratedProtocolMessageType('LookupResponse', (_message.Message,), dict( DESCRIPTOR = _LOOKUPRESPONSE, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.LookupResponse) )) _sym_db.RegisterMessage(LookupResponse) RunQueryRequest = _reflection.GeneratedProtocolMessageType('RunQueryRequest', (_message.Message,), dict( DESCRIPTOR = _RUNQUERYREQUEST, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.RunQueryRequest) )) _sym_db.RegisterMessage(RunQueryRequest) RunQueryResponse = _reflection.GeneratedProtocolMessageType('RunQueryResponse', (_message.Message,), dict( DESCRIPTOR = _RUNQUERYRESPONSE, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.RunQueryResponse) )) _sym_db.RegisterMessage(RunQueryResponse) BeginTransactionRequest = _reflection.GeneratedProtocolMessageType('BeginTransactionRequest', (_message.Message,), dict( DESCRIPTOR = _BEGINTRANSACTIONREQUEST, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.BeginTransactionRequest) )) _sym_db.RegisterMessage(BeginTransactionRequest) BeginTransactionResponse = _reflection.GeneratedProtocolMessageType('BeginTransactionResponse', (_message.Message,), dict( DESCRIPTOR = _BEGINTRANSACTIONRESPONSE, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.BeginTransactionResponse) )) _sym_db.RegisterMessage(BeginTransactionResponse) RollbackRequest = _reflection.GeneratedProtocolMessageType('RollbackRequest', (_message.Message,), dict( DESCRIPTOR = _ROLLBACKREQUEST, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.RollbackRequest) )) _sym_db.RegisterMessage(RollbackRequest) RollbackResponse = _reflection.GeneratedProtocolMessageType('RollbackResponse', (_message.Message,), dict( DESCRIPTOR = _ROLLBACKRESPONSE, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.RollbackResponse) )) _sym_db.RegisterMessage(RollbackResponse) CommitRequest = _reflection.GeneratedProtocolMessageType('CommitRequest', (_message.Message,), dict( DESCRIPTOR = _COMMITREQUEST, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.CommitRequest) )) _sym_db.RegisterMessage(CommitRequest) CommitResponse = _reflection.GeneratedProtocolMessageType('CommitResponse', (_message.Message,), dict( DESCRIPTOR = _COMMITRESPONSE, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.CommitResponse) )) _sym_db.RegisterMessage(CommitResponse) AllocateIdsRequest = _reflection.GeneratedProtocolMessageType('AllocateIdsRequest', (_message.Message,), dict( DESCRIPTOR = _ALLOCATEIDSREQUEST, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.AllocateIdsRequest) )) _sym_db.RegisterMessage(AllocateIdsRequest) AllocateIdsResponse = _reflection.GeneratedProtocolMessageType('AllocateIdsResponse', (_message.Message,), dict( DESCRIPTOR = _ALLOCATEIDSRESPONSE, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.AllocateIdsResponse) )) _sym_db.RegisterMessage(AllocateIdsResponse) Mutation = _reflection.GeneratedProtocolMessageType('Mutation', (_message.Message,), dict( DESCRIPTOR = _MUTATION, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.Mutation) )) _sym_db.RegisterMessage(Mutation) MutationResult = _reflection.GeneratedProtocolMessageType('MutationResult', (_message.Message,), dict( DESCRIPTOR = _MUTATIONRESULT, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.MutationResult) )) _sym_db.RegisterMessage(MutationResult) ReadOptions = _reflection.GeneratedProtocolMessageType('ReadOptions', (_message.Message,), dict( DESCRIPTOR = _READOPTIONS, __module__ = 'google.datastore.v1.datastore_pb2' # @@protoc_insertion_point(class_scope:google.datastore.v1.ReadOptions) )) _sym_db.RegisterMessage(ReadOptions) DESCRIPTOR.has_options = True DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\n\027com.google.datastore.v1B\016DatastoreProtoP\001')) # @@protoc_insertion_point(module_scope)

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4,517

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0.074203

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0.045752

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0

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0.109122

37,316

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0

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1

0

null

0

2

f7ae9e430fad51920006bf7a558e4c86f472388f

227

py

Python

ex032.py

GabrielMarquesss/Exercicios-Python

90e97ac19ae36220c42892ca773648e578b53f10

[ "MIT" ]

null

ex032.py

GabrielMarquesss/Exercicios-Python

90e97ac19ae36220c42892ca773648e578b53f10

[ "MIT" ]

null

ex032.py

GabrielMarquesss/Exercicios-Python

90e97ac19ae36220c42892ca773648e578b53f10

[ "MIT" ]

null

#Programa que diz se ano é bissexto ou não: ano = int(input('Digite um ano: ')) if ano // 400 and ano % 4 == 0 and ano % 100 != 0 : print('{} é bissexto'.format(ano)) else: print('{} não é ano bissexto.'.format(ano))

25.222222

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39

227

3.512821

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0

0.051136

0.22467

227

8

52

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0.727273

0.185022

0

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1

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false

0

0.4

0

null

0

1

0

1

0

null

0

2

f7b0f10a8f2dbd65f38b1bf5607f8b02637cf3bc

293

py

Python

helpers/fixproj.py

j-caparotta/FML

6dfe3da19ba83805ef7aa181d837223824c0985a

[ "Unlicense" ]

43

2015-01-22T16:53:06.000Z

2020-03-24T18:53:46.000Z

helpers/fixproj.py

j-caparotta/FML

6dfe3da19ba83805ef7aa181d837223824c0985a

[ "Unlicense" ]

6

2016-02-20T14:34:48.000Z

2021-03-02T14:21:59.000Z

helpers/fixproj.py

j-caparotta/FML

6dfe3da19ba83805ef7aa181d837223824c0985a

[ "Unlicense" ]

33

2015-08-14T14:38:53.000Z

2020-04-18T17:09:24.000Z

import sys, os with open(sys.argv[1], 'r') as fd: content = '\n'.join(line.strip() for line in fd if line.strip()) if len(sys.argv) == 3: content = content.replace('Win32', sys.argv[2]).replace('x64', sys.argv[2]) with open(sys.argv[1], 'w') as fd: fd.write(content)

36.625

81

0.59727

51

293

3.431373

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0.2

0.125714

0.171429

0.182857

0

0.038298

0.197952

293

7

82

41.857143

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0

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0

1

0

false

0

0.142857

0

0.142857

0

null

0

1

0

1

0

null

0

2

f7b31606eec2c54f37f556bcc1db3c46a0b97dbd

626

py

Python

login_register/views.py

imranparuk/whether-the-weather

347f3fe97975a6980a37cc60f32e65fdb04a89c6

[ "MIT" ]

null

login_register/views.py

imranparuk/whether-the-weather

347f3fe97975a6980a37cc60f32e65fdb04a89c6

[ "MIT" ]

1

2020-06-05T18:25:45.000Z

login_register/views.py

imranparuk/whether-the-weather

347f3fe97975a6980a37cc60f32e65fdb04a89c6

[ "MIT" ]

null

from django.shortcuts import render from django.http import HttpResponse from django.template import loader from django.contrib.auth import get_user_model User = get_user_model() #def login_reg_view(request): # #template = loader.get_template('login_register/templates/test.html') # return render(request, 'login_register/templates/test.html') from django.contrib.auth.forms import UserCreationForm from django.urls import reverse_lazy from django.views import generic class register(generic.CreateView): form_class = UserCreationForm success_url = reverse_lazy('login') template_name = 'signup.html'

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0.795527

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626

5.831325

0.457831

0.144628

0.070248

0.086777

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626

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null

0

null

0

1

0

1

0

2

f7b62b8cc50d7f9008c5396d0e2fb86e8e20f0d3

734

py

Python

airone/wsgi.py

userlocalhost/airone-1

8aabeabb65fd2117876380f1f69a04f0cf39889d

[ "MIT" ]

null

airone/wsgi.py

userlocalhost/airone-1

8aabeabb65fd2117876380f1f69a04f0cf39889d

[ "MIT" ]

null

airone/wsgi.py

userlocalhost/airone-1

8aabeabb65fd2117876380f1f69a04f0cf39889d

[ "MIT" ]

null

""" WSGI config for airone project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/2.2/howto/deployment/wsgi/ """ import os import importlib from django.conf import settings from configurations.wsgi import get_wsgi_application from airone.lib.log import Logger os.environ.setdefault("DJANGO_SETTINGS_MODULE", "airone.settings") os.environ.setdefault("DJANGO_CONFIGURATION", "Dev") for extension in settings.AIRONE["EXTENSIONS"]: try: importlib.import_module("%s.settings" % extension) except ImportError: Logger.warning("Failed to load settings %s" % extension) application = get_wsgi_application()

28.230769

78

0.76703

97

734

5.721649

0.587629

0.036036

0.064865

0.09009

0

0.003135

0.13079

734

25

79

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1

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false

0

0.538462

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0

null

0

null

0

1

0

1

0

2

f7bb33d8ab751c76b0cd7f5a763e6ccd73116808

615

py

Python

Sources/Python/utility.py

ParliamoDiPC/fasmga

55a340917b6ba4f7557249f0b32a8e2791c488de

[ "MIT" ]

null

Sources/Python/utility.py

ParliamoDiPC/fasmga

55a340917b6ba4f7557249f0b32a8e2791c488de

[ "MIT" ]

null

Sources/Python/utility.py

ParliamoDiPC/fasmga

55a340917b6ba4f7557249f0b32a8e2791c488de

[ "MIT" ]

null

import random, string, json global ratelimit ratelimit = {} Authorizated = json.load(open("Sources/Json/Authorizated.json", "r")) def newUrlID(): return "".join(random.choice(string.ascii_lowercase) for i in range(8)) def ratelimitCheck(dbToken): for auth in Authorizated: ratelimit[auth] = -1 if not dbToken["Owner"] in ratelimit: ratelimit[dbToken["Owner"]] = 1 return True else: if ratelimit[dbToken["Owner"]] < 20: if ratelimit[dbToken["Owner"]] == -1: return True ratelimit[dbToken["Owner"]] += 1 return True elif ratelimit[dbToken["Owner"]] == -1: return True else: return False

27.954545

87

0.697561

81

615

5.283951

0.432099

0.168224

0.245327

0.205607

0.317757

0.168224

0

0.015385

0.154472

615

22

88

27.954545

0.807692

0

0.111111

0

0.099026

0.048701

0

1

0.111111

false

0

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0.277778

0

null

0

1

0

null

0

2

f7cb542b8b2219b7c693d7dd0736895d479ce62c

566

py

Python

tests/test_wallet.py

mschneider/mango-explorer

ed50880ef80b31b679c9c89fa9bf0579391d71c9

[ "MIT" ]

1

2021-09-09T20:49:46.000Z

tests/test_wallet.py

mschneider/mango-explorer

ed50880ef80b31b679c9c89fa9bf0579391d71c9

[ "MIT" ]

null

tests/test_wallet.py

mschneider/mango-explorer

ed50880ef80b31b679c9c89fa9bf0579391d71c9

[ "MIT" ]

2

2021-09-09T20:49:50.000Z

2021-11-05T21:41:41.000Z

from .context import mango def test_constructor(): secret_key = [0] * 32 actual = mango.Wallet(secret_key) assert actual is not None assert actual.logger is not None assert actual.secret_key == secret_key assert actual.account is not None def test_constructor_with_longer_secret_key(): secret_key = [0] * 64 actual = mango.Wallet(secret_key) assert actual is not None assert actual.logger is not None assert actual.secret_key != secret_key assert len(actual.secret_key) == 32 assert actual.account is not None

26.952381

46

0.717314

84

566

4.654762

0.27381

0.230179

0.138107

0.153453

0.690537

0.56266

0

0.018018

0.215548

566

20

47

28.3

0.862613

0

0.5

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0.5625

1

0.125

false

0

0.0625

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0.1875

0

null

1

0

null

0

1

0

2

f7d4a9aa8b746937f3ba159dc212e1cb8a816c3a

3,640

py

Python

ibm-iot-quickstart.py

oscarordaz27/TheIoTLearningInitiative

54678a38d5b58d4f41c839d133ed3c4dc1cd6025

[ "Apache-2.0" ]

null

ibm-iot-quickstart.py

oscarordaz27/TheIoTLearningInitiative

54678a38d5b58d4f41c839d133ed3c4dc1cd6025

[ "Apache-2.0" ]

null

ibm-iot-quickstart.py

oscarordaz27/TheIoTLearningInitiative

54678a38d5b58d4f41c839d133ed3c4dc1cd6025

[ "Apache-2.0" ]

null

##***************************************************************************** ## Copyright (c) 2014 IBM Corporation and other Contributors. ## ## All rights reserved. This program and the accompanying materials ## are made available under the terms of the Eclipse Public License v1.0 ## which accompanies this distribution, and is available at ## http://www.eclipse.org/legal/epl-v10.html ## ## Contributors: ## IBM - Initial Contribution ##***************************************************************************** ## IoT Foundation QuickStart Driver ## A sample IBM Internet of Things Foundation Service client for Intel Internet of Things Gateway Solutions import time import client as mqtt import json import uuid #Class for retrieving CPU % utilisation class CPUutil(object): def __init__(self): self.prev_idle = 0 self.prev_total = 0 self.new_idle = 0 self.new_total = 0 def get(self): self.read() delta_idle = self.new_idle - self.prev_idle delta_total = self.new_total - self.prev_total cpuut = 0.0 if (self.prev_total != 0) and (delta_total != 0): cpuut = ((delta_total - delta_idle) * 100.0 / delta_total) return cpuut def read(self): self.prev_idle = self.new_idle self.prev_total = self.new_total self.new_idle = 0; self.new_total = 0; with open('/proc/stat') as f: line = f.readline() parts = line.split() if len(parts) >= 5: self.new_idle = int(parts[4]) for part in parts[1:]: self.new_total += int(part) #Initialise class to retrieve CPU Usage cpuutil = CPUutil() macAddress = hex(uuid.getnode())[2:-1] macAddress = format(long(macAddress, 16),'012x') #remind the user of the mac address further down in code (post 'connecitng to QS') #Set the variables for connecting to the Quickstart service organization = "quickstart" deviceType = "iotsample-gateway" broker = "" topic = "iot-2/evt/status/fmt/json" username = "" password = "" error_to_catch = getattr(__builtins__,'FileNotFoundError', IOError) try: file_object = open("./device.cfg") for line in file_object: readType, readValue = line.split("=") if readType == "org": organization = readValue.strip() elif readType == "type": deviceType = readValue.strip() elif readType == "id": macAddress = readValue.strip() elif readType == "auth-method": username = "use-token-auth" elif readType == "auth-token": password = readValue.strip() else: print("please check the format of your config file") #will want to repeat this error further down if their connection fails? file_object.close() print("Configuration file found - connecting to the registered service") except error_to_catch: print("No config file found, connecting to the Quickstart service") print("MAC address: " + macAddress) #Creating the client connection #Set clientID and broker clientID = "d:" + organization + ":" + deviceType + ":" + macAddress broker = organization + ".messaging.internetofthings.ibmcloud.com" mqttc = mqtt.Client(clientID) #Set authentication values, if connecting to registered service if username is not "": mqttc.username_pw_set(username, password=password) mqttc.connect(host=broker, port=1883, keepalive=60) #Publishing to IBM Internet of Things Foundation mqttc.loop_start() while mqttc.loop() == 0: cpuutilvalue = cpuutil.get() print cpuutilvalue msg = json.JSONEncoder().encode({"d":{"cpuutil":cpuutilvalue}}) mqttc.publish(topic, payload=msg, qos=0, retain=False) print "message published" time.sleep(5) pass

28

130

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0.44181

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0.0231

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0.121378

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0.014165

0.18544

3,640

129

131

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0.78887

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0

null

0.052632

null

0.078947

0

null

0

null

0

1

0

1

0

2

f7d53a2094471d114a4a21c06099237c0ae7a9d6

2,872

py

Python

test/programytest/aiml_tests/arrow_tests/test_arrow_aiml.py

minhdc/documented-programy

fe947d68c0749201fbe93ee5644d304235d0c626

[ "MIT" ]

null

test/programytest/aiml_tests/arrow_tests/test_arrow_aiml.py

minhdc/documented-programy

fe947d68c0749201fbe93ee5644d304235d0c626

[ "MIT" ]

null

test/programytest/aiml_tests/arrow_tests/test_arrow_aiml.py

minhdc/documented-programy

fe947d68c0749201fbe93ee5644d304235d0c626

[ "MIT" ]

null

import unittest import os from programy.context import ClientContext from programytest.aiml_tests.client import TestClient class ArrowTestClient(TestClient): def __init__(self): TestClient.__init__(self) def load_configuration(self, arguments): super(ArrowTestClient, self).load_configuration(arguments) self.configuration.client_configuration.configurations[0].configurations[0].files.aiml_files._files = [os.path.dirname(__file__)] class ArrowAIMLTests(unittest.TestCase): def setUp(self): client = ArrowTestClient() self._client_context = client.create_client_context("testid") def test_arrow_first_word(self): response = self._client_context.bot.ask_question(self._client_context, "SAY HEY") self.assertIsNotNone(response) self.assertEqual(response, 'ARROW IS SAY') def test_arrow_first_no_word(self): response = self._client_context.bot.ask_question(self._client_context, "HEY") self.assertIsNotNone(response) self.assertEqual(response, 'ARROW IS') def test_arrow_first_multi_word(self): response = self._client_context.bot.ask_question(self._client_context, "WE SAY HEY") self.assertIsNotNone(response) self.assertEqual(response, 'ARROW IS WE SAY') def test_arrow_last_word(self): response = self._client_context.bot.ask_question(self._client_context, "HELLO YOU") self.assertIsNotNone(response) self.assertEqual(response, 'ARROW IS YOU') def test_arrow_no_word(self): response = self._client_context.bot.ask_question(self._client_context, "HELLO") self.assertIsNotNone(response) self.assertEqual(response, 'ARROW IS') def test_arrow_no_multi_word(self): response = self._client_context.bot.ask_question(self._client_context, "HELLO YOU THERE") self.assertIsNotNone(response) self.assertEqual(response, 'ARROW IS YOU THERE') def test_arrow_middle_word(self): response = self._client_context.bot.ask_question(self._client_context, "WELL HI THERE") self.assertIsNotNone(response) self.assertEqual(response, 'ARROW IS HI') def test_arrow_middle_no_word(self): response = self._client_context.bot.ask_question(self._client_context, "WELL THERE") self.assertIsNotNone(response) self.assertEqual(response, 'ARROW IS') def test_arrow_middle_multi_word(self): response = self._client_context.bot.ask_question(self._client_context, "WELL I WAS THERE") self.assertIsNotNone(response) self.assertEqual(response, 'ARROW IS I WAS') def test_arrow_specific_case1(self): response = self._client_context.bot.ask_question(self._client_context, "aaa bbb ccc ddd") self.assertIsNotNone(response) self.assertEqual(response, 'passed')

38.810811

137

0.725975

347

2,872

5.700288

0.184438

0.111223

0.180485

0.111223

0.672396

0.647118

0.517189

0

0.00127

0.177577

2,872

73

138

39.342466

0.836156

0

0.240741

0

0.07695

0

0.37037

1

0.240741

false

0.018519

0.074074

0

0.351852

0

null

0

1

0

null

0

1

0

2

f7de0c5d7c143dbbaa1cce7fc39c805f3b84b54c

31,938

py

Python

tkge/models/model.py

tkg-framework/TKG-framework

98586b7199bda0e96d74b2ea02c62226901822cc

[ "MIT", "Unlicense" ]

null

tkge/models/model.py

tkg-framework/TKG-framework

98586b7199bda0e96d74b2ea02c62226901822cc

[ "MIT", "Unlicense" ]

null

tkge/models/model.py

tkg-framework/TKG-framework

98586b7199bda0e96d74b2ea02c62226901822cc

[ "MIT", "Unlicense" ]

null

import torch from torch import nn from torch.nn import functional as F import numpy as np from enum import Enum import os from collections import defaultdict from typing import Mapping, Dict import random from tkge.common.registry import Registrable from tkge.common.config import Config from tkge.common.error import ConfigurationError from tkge.data.dataset import DatasetProcessor from tkge.models.layers import LSTMModel from tkge.models.utils import * class BaseModel(nn.Module, Registrable): def __init__(self, config: Config, dataset: DatasetProcessor): nn.Module.__init__(self) Registrable.__init__(self, config=config) self.dataset = dataset @staticmethod def create(config: Config, dataset: DatasetProcessor): """Factory method for sampler creation""" model_type = config.get("model.name") if model_type in BaseModel.list_available(): # kwargs = config.get("model.args") # TODO: 需要改成key的格式 return BaseModel.by_name(model_type)(config, dataset) else: raise ConfigurationError( f"{model_type} specified in configuration file is not supported" f"implement your model class with `BaseModel.register(name)" ) def load_config(self): # TODO(gengyuan): 有参数的话加载，没指定参数的话用默认，最好可以直接读config文件然后setattr，需不需要做assert？ raise NotImplementedError def prepare_embedding(self): raise NotImplementedError def get_embedding(self, **kwargs): raise NotImplementedError def forward(self, samples, **kwargs): raise NotImplementedError def predict(self, queries: torch.Tensor): """ Should be a wrapper of method forward or a computation flow same as that in forward. Particularly for prediction task with incomplete queries as inputs. New modules or learnable parameter constructed in this namespace should be avoided since it's not evolved in training procedure. """ raise NotImplementedError def fit(self, samples: torch.Tensor): # TODO(gengyuan): wrapping all the models """ Should be a wrapper of forward or a computation flow same as that in forward. This method is intended to handle arbitrarily-shaped samples due to negative sampling, either matrix or flatteded. Especially when training procedure and prediction procedure are different. Samples should be processed in this method and then passed to forward. Input samples are the direct output of the negative sampling. """ raise NotImplementedError @BaseModel.register(name='de_simple') class DeSimplEModel(BaseModel): def __init__(self, config: Config, dataset: DatasetProcessor): super().__init__(config, dataset) self.prepare_embedding() self.time_nl = torch.sin # TODO add to configuration file def prepare_embedding(self): num_ent = self.dataset.num_entities() num_rel = self.dataset.num_relations() emb_dim = self.config.get("model.embedding.emb_dim") se_prop = self.config.get("model.embedding.se_prop") s_emb_dim = int(se_prop * emb_dim) t_emb_dim = emb_dim - s_emb_dim # torch.manual_seed(0) # torch.cuda.manual_seed_all(0) # np.random.seed(0) # random.seed(0) # torch.backends.cudnn.deterministic = True # os.environ['PYTHONHASHSEED'] = str(0) self.embedding: Dict[str, nn.Module] = defaultdict(dict) self.embedding.update({'ent_embs_h': nn.Embedding(num_ent, s_emb_dim)}) self.embedding.update({'ent_embs_t': nn.Embedding(num_ent, s_emb_dim)}) self.embedding.update({'rel_embs_f': nn.Embedding(num_rel, s_emb_dim + t_emb_dim)}) self.embedding.update({'rel_embs_i': nn.Embedding(num_rel, s_emb_dim + t_emb_dim)}) # frequency embeddings for the entities self.embedding.update({'m_freq_h': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'m_freq_t': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'d_freq_h': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'d_freq_t': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'y_freq_h': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'y_freq_t': nn.Embedding(num_ent, t_emb_dim)}) # phi embeddings for the entities self.embedding.update({'m_phi_h': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'m_phi_t': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'d_phi_h': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'d_phi_t': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'y_phi_h': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'y_phi_t': nn.Embedding(num_ent, t_emb_dim)}) # frequency embeddings for the entities self.embedding.update({'m_amps_h': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'m_amps_t': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'d_amps_h': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'d_amps_t': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'y_amps_h': nn.Embedding(num_ent, t_emb_dim)}) self.embedding.update({'y_amps_t': nn.Embedding(num_ent, t_emb_dim)}) self.embedding = nn.ModuleDict(self.embedding) for k, v in self.embedding.items(): nn.init.xavier_uniform_(v.weight) # nn.init.xavier_uniform_(self.ent_embs_h.weight) # nn.init.xavier_uniform_(self.ent_embs_t.weight) # nn.init.xavier_uniform_(self.rel_embs_f.weight) # nn.init.xavier_uniform_(self.rel_embs_i.weight) # # nn.init.xavier_uniform_(self.m_freq_h.weight) # nn.init.xavier_uniform_(self.d_freq_h.weight) # nn.init.xavier_uniform_(self.y_freq_h.weight) # nn.init.xavier_uniform_(self.m_freq_t.weight) # nn.init.xavier_uniform_(self.d_freq_t.weight) # nn.init.xavier_uniform_(self.y_freq_t.weight) # # nn.init.xavier_uniform_(self.m_phi_h.weight) # nn.init.xavier_uniform_(self.d_phi_h.weight) # nn.init.xavier_uniform_(self.y_phi_h.weight) # nn.init.xavier_uniform_(self.m_phi_t.weight) # nn.init.xavier_uniform_(self.d_phi_t.weight) # nn.init.xavier_uniform_(self.y_phi_t.weight) # # nn.init.xavier_uniform_(self.m_amps_h.weight) # nn.init.xavier_uniform_(self.d_amps_h.weight) # nn.init.xavier_uniform_(self.y_amps_h.weight) # nn.init.xavier_uniform_(self.m_amps_t.weight) # nn.init.xavier_uniform_(self.d_amps_t.weight) # nn.init.xavier_uniform_(self.y_amps_t.weight) # nn.init.xavier_uniform_(self.embedding['ent_embs_h'].weight) # nn.init.xavier_uniform_(self.embedding['ent_embs_t'].weight) # nn.init.xavier_uniform_(self.embedding['rel_embs_f'].weight) # nn.init.xavier_uniform_(self.embedding['rel_embs_i'].weight) # # nn.init.xavier_uniform_(self.embedding['m_freq_h'].weight) # nn.init.xavier_uniform_(self.embedding['d_freq_h'].weight) # nn.init.xavier_uniform_(self.embedding['y_freq_h'].weight) # nn.init.xavier_uniform_(self.embedding['m_freq_t'].weight) # nn.init.xavier_uniform_(self.embedding['d_freq_t'].weight) # nn.init.xavier_uniform_(self.embedding['y_freq_t'].weight) # # nn.init.xavier_uniform_(self.embedding['m_phi_h'].weight) # nn.init.xavier_uniform_(self.embedding['d_phi_h'].weight) # nn.init.xavier_uniform_(self.embedding['y_phi_h'].weight) # nn.init.xavier_uniform_(self.embedding['m_phi_t'].weight) # nn.init.xavier_uniform_(self.embedding['d_phi_t'].weight) # nn.init.xavier_uniform_(self.embedding['y_phi_t'].weight) # # nn.init.xavier_uniform_(self.embedding['m_amps_h'].weight) # nn.init.xavier_uniform_(self.embedding['d_amps_h'].weight) # nn.init.xavier_uniform_(self.embedding['y_amps_h'].weight) # nn.init.xavier_uniform_(self.embedding['m_amps_t'].weight) # nn.init.xavier_uniform_(self.embedding['d_amps_t'].weight) # nn.init.xavier_uniform_(self.embedding['y_amps_t'].weight) # for name, params in self.named_parameters(): # print(name) # print(params) # print(params.size()) # # assert False def get_time_embedding(self, ent, year, month, day, ent_pos): # TODO: enum if ent_pos == "head": time_emb = self.embedding['y_amps_h'](ent) * self.time_nl( self.embedding['y_freq_h'](ent) * year + self.embedding['y_phi_h'](ent)) time_emb += self.embedding['m_amps_h'](ent) * self.time_nl( self.embedding['m_freq_h'](ent) * month + self.embedding['m_phi_h'](ent)) time_emb += self.embedding['d_amps_h'](ent) * self.time_nl( self.embedding['d_freq_h'](ent) * day + self.embedding['d_phi_h'](ent)) else: time_emb = self.embedding['y_amps_t'](ent) * self.time_nl( self.embedding['y_freq_t'](ent) * year + self.embedding['y_phi_t'](ent)) time_emb += self.embedding['m_amps_t'](ent) * self.time_nl( self.embedding['m_freq_t'](ent) * month + self.embedding['m_phi_t'](ent)) time_emb += self.embedding['d_amps_t'](ent) * self.time_nl( self.embedding['d_freq_t'](ent) * day + self.embedding['d_phi_t'](ent)) return time_emb def get_embedding(self, head, rel, tail, year, month, day): year = year.view(-1, 1) month = month.view(-1, 1) day = day.view(-1, 1) h_emb1 = self.embedding['ent_embs_h'](head) r_emb1 = self.embedding['rel_embs_f'](rel) t_emb1 = self.embedding['ent_embs_t'](tail) h_emb2 = self.embedding['ent_embs_h'](tail) r_emb2 = self.embedding['rel_embs_i'](rel) t_emb2 = self.embedding['ent_embs_t'](head) h_emb1 = torch.cat((h_emb1, self.get_time_embedding(head, year, month, day, 'head')), 1) t_emb1 = torch.cat((t_emb1, self.get_time_embedding(tail, year, month, day, 'tail')), 1) h_emb2 = torch.cat((h_emb2, self.get_time_embedding(tail, year, month, day, 'head')), 1) t_emb2 = torch.cat((t_emb2, self.get_time_embedding(head, year, month, day, 'tail')), 1) return h_emb1, r_emb1, t_emb1, h_emb2, r_emb2, t_emb2 def forward(self, samples, **kwargs): head = samples[:, 0].long() rel = samples[:, 1].long() tail = samples[:, 2].long() year = samples[:, 3] month = samples[:, 4] day = samples[:, 5] h_emb1, r_emb1, t_emb1, h_emb2, r_emb2, t_emb2 = self.get_embedding(head, rel, tail, year, month, day) p = self.config.get('model.dropout') scores = ((h_emb1 * r_emb1) * t_emb1 + (h_emb2 * r_emb2) * t_emb2) / 2.0 scores = F.dropout(scores, p=p, training=self.training) # TODO training scores = torch.sum(scores, dim=1) return scores, None def fit(self, samples: torch.Tensor): bs = samples.size(0) dim = samples.size(1) // (1 + self.config.get("negative_sampling.num_samples")) samples = samples.view(-1, dim) scores, factor = self.forward(samples) scores = scores.view(bs, -1) return scores, factor def predict(self, queries: torch.Tensor): assert torch.isnan(queries).sum(1).byte().all(), "Either head or tail should be absent." bs = queries.size(0) dim = queries.size(0) candidates = all_candidates_of_ent_queries(queries, self.dataset.num_entities()) scores, _ = self.forward(candidates) scores = scores.view(bs, -1) return scores @BaseModel.register(name="tcomplex") class TComplExModel(BaseModel): def __init__(self, config: Config, dataset: DatasetProcessor): super().__init__(config, dataset) self.rank = self.config.get("model.rank") self.no_time_emb = self.config.get("model.no_time_emb") self.init_size = self.config.get("model.init_size") self.num_ent = self.dataset.num_entities() self.num_rel = self.dataset.num_relations() self.num_ts = self.dataset.num_timestamps() self.prepare_embedding() def prepare_embedding(self): self.embeddings = nn.ModuleList([ nn.Embedding(s, 2 * self.rank, sparse=True) for s in [self.num_ent, self.num_rel, self.num_ts] ]) for emb in self.embeddings: emb.weight.data *= self.init_size def forward(self, x): """ x is spot """ lhs = self.embeddings[0](x[:, 0].long()) rel = self.embeddings[1](x[:, 1].long()) rhs = self.embeddings[0](x[:, 2].long()) time = self.embeddings[2](x[:, 3].long()) lhs = lhs[:, :self.rank], lhs[:, self.rank:] rel = rel[:, :self.rank], rel[:, self.rank:] rhs = rhs[:, :self.rank], rhs[:, self.rank:] time = time[:, :self.rank], time[:, self.rank:] right = self.embeddings[0].weight # all ent tensor right = right[:, :self.rank], right[:, self.rank:] rt = rel[0] * time[0], rel[1] * time[0], rel[0] * time[1], rel[1] * time[1] full_rel = rt[0] - rt[3], rt[1] + rt[2] # 1st item: scores # 2nd item: reg item factors # 3rd item: time scores = (lhs[0] * full_rel[0] - lhs[1] * full_rel[1]) @ right[0].t() + \ (lhs[1] * full_rel[0] + lhs[0] * full_rel[1]) @ right[1].t() factors = { "n3": (torch.sqrt(lhs[0] ** 2 + lhs[1] ** 2), torch.sqrt(full_rel[0] ** 2 + full_rel[1] ** 2), torch.sqrt(rhs[0] ** 2 + rhs[1] ** 2)), "lambda3": (self.embeddings[2].weight[:-1] if self.no_time_emb else self.embeddings[2].weight) } return scores, factors def predict(self, x): assert torch.isnan(x).sum(1).byte().all(), "Either head or tail should be absent." missing_head_ind = torch.isnan(x)[:, 0].byte().unsqueeze(1) reversed_x = x.clone() reversed_x[:, 1] += 1 reversed_x[:, (0, 2)] = reversed_x[:, (2, 0)] x = torch.where(missing_head_ind, reversed_x, x) lhs = self.embeddings[0](x[:, 0].long()) rel = self.embeddings[1](x[:, 1].long()) time = self.embeddings[2](x[:, 3].long()) lhs = lhs[:, :self.rank], lhs[:, self.rank:] rel = rel[:, :self.rank], rel[:, self.rank:] time = time[:, :self.rank], time[:, self.rank:] right = self.embeddings[0].weight right = right[:, :self.rank], right[:, self.rank:] scores = (lhs[0] * rel[0] * time[0] - lhs[1] * rel[1] * time[0] - lhs[1] * rel[0] * time[1] - lhs[0] * rel[1] * time[1]) @ right[0].t() + \ (lhs[1] * rel[0] * time[0] + lhs[0] * rel[1] * time[0] + lhs[0] * rel[0] * time[1] - lhs[1] * rel[1] * time[1]) @ right[1].t() return scores def forward_over_time(self, x): lhs = self.embeddings[0](x[:, 0]) rel = self.embeddings[1](x[:, 1]) rhs = self.embeddings[0](x[:, 2]) time = self.embeddings[2].weight lhs = lhs[:, :self.rank], lhs[:, self.rank:] rel = rel[:, :self.rank], rel[:, self.rank:] rhs = rhs[:, :self.rank], rhs[:, self.rank:] time = time[:, :self.rank], time[:, self.rank:] return ( (lhs[0] * rel[0] * rhs[0] - lhs[1] * rel[1] * rhs[0] - lhs[1] * rel[0] * rhs[1] + lhs[0] * rel[1] * rhs[1]) @ time[0].t() + (lhs[1] * rel[0] * rhs[0] - lhs[0] * rel[1] * rhs[0] + lhs[0] * rel[0] * rhs[1] - lhs[1] * rel[1] * rhs[1]) @ time[1].t() ) @BaseModel.register(name="hyte") class HyTEModel(BaseModel): def __init__(self, config: Config, dataset: DatasetProcessor): super().__init__(config, dataset) @BaseModel.register(name="atise") class ATiSEModel(BaseModel): def __init__(self, config: Config, dataset: DatasetProcessor): super().__init__(config, dataset) # TODO(gengyuan) load params before initialize self.cmin = self.config.get("model.cmin") self.cmax = self.config.get("model.cmax") self.emb_dim = self.config.get("model.embedding_dim") self.prepare_embedding() def prepare_embedding(self): num_ent = self.dataset.num_entities() num_rel = self.dataset.num_relations() self.embedding: Dict[str, nn.Module] = defaultdict(None) self.embedding.update({'emb_E': nn.Embedding(num_ent, self.emb_dim, padding_idx=0)}) self.embedding.update({'emb_E_var': nn.Embedding(num_ent, self.emb_dim, padding_idx=0)}) self.embedding.update({'emb_R': nn.Embedding(num_rel, self.emb_dim, padding_idx=0)}) self.embedding.update({'emb_R_var': nn.Embedding(num_rel, self.emb_dim, padding_idx=0)}) self.embedding.update({'emb_TE': nn.Embedding(num_ent, self.emb_dim, padding_idx=0)}) self.embedding.update({'alpha_E': nn.Embedding(num_ent, 1, padding_idx=0)}) self.embedding.update({'beta_E': nn.Embedding(num_ent, self.emb_dim, padding_idx=0)}) self.embedding.update({'omega_E': nn.Embedding(num_ent, self.emb_dim, padding_idx=0)}) self.embedding.update({'emb_TR': nn.Embedding(num_rel, self.emb_dim, padding_idx=0)}) self.embedding.update({'alpha_R': nn.Embedding(num_rel, 1, padding_idx=0)}) self.embedding.update({'beta_R': nn.Embedding(num_rel, self.emb_dim, padding_idx=0)}) self.embedding.update({'omega_R': nn.Embedding(num_rel, self.emb_dim, padding_idx=0)}) self.embedding = nn.ModuleDict(self.embedding) r = 6 / np.sqrt(self.emb_dim) self.embedding['emb_E'].weight.data.uniform_(-r, r) self.embedding['emb_E_var'].weight.data.uniform_(self.cmin, self.cmax) self.embedding['emb_R'].weight.data.uniform_(-r, r) self.embedding['emb_R_var'].weight.data.uniform_(self.cmin, self.cmax) self.embedding['emb_TE'].weight.data.uniform_(-r, r) self.embedding['alpha_E'].weight.data.uniform_(0, 0) self.embedding['beta_E'].weight.data.uniform_(0, 0) self.embedding['omega_E'].weight.data.uniform_(-r, r) self.embedding['emb_TR'].weight.data.uniform_(-r, r) self.embedding['alpha_R'].weight.data.uniform_(0, 0) self.embedding['beta_R'].weight.data.uniform_(0, 0) self.embedding['omega_R'].weight.data.uniform_(-r, r) self.embedding['emb_E'].weight.data.renorm_(p=2, dim=0, maxnorm=1) self.embedding['emb_E_var'].weight.data.uniform_(self.cmin, self.cmax) self.embedding['emb_R'].weight.data.renorm_(p=2, dim=0, maxnorm=1) self.embedding['emb_R_var'].weight.data.uniform_(self.cmin, self.cmax) self.embedding['emb_TE'].weight.data.renorm_(p=2, dim=0, maxnorm=1) self.embedding['emb_TR'].weight.data.renorm_(p=2, dim=0, maxnorm=1) def forward(self, sample: torch.Tensor): bs = sample.size(0) # TODO(gengyuan) dim = sample.size(1) // (1 + self.config.get("negative_sampling.num_samples")) sample = sample.view(-1, dim) # TODO(gengyuan) type conversion when feeding the data instead of running the models h_i, t_i, r_i, d_i = sample[:, 0].long(), sample[:, 2].long(), sample[:, 1].long(), sample[:, 3] pi = 3.14159265358979323846 h_mean = self.embedding['emb_E'](h_i).view(-1, self.emb_dim) + \ d_i.view(-1, 1) * self.embedding['alpha_E'](h_i).view(-1, 1) * self.embedding['emb_TE'](h_i).view(-1, self.emb_dim) \ + self.embedding['beta_E'](h_i).view(-1, self.emb_dim) * torch.sin( 2 * pi * self.embedding['omega_E'](h_i).view(-1, self.emb_dim) * d_i.view(-1, 1)) t_mean = self.embedding['emb_E'](t_i).view(-1, self.emb_dim) + \ d_i.view(-1, 1) * self.embedding['alpha_E'](t_i).view(-1, 1) * self.embedding['emb_TE'](t_i).view(-1, self.emb_dim) \ + self.embedding['beta_E'](t_i).view(-1, self.emb_dim) * torch.sin( 2 * pi * self.embedding['omega_E'](t_i).view(-1, self.emb_dim) * d_i.view(-1, 1)) r_mean = self.embedding['emb_R'](r_i).view(-1, self.emb_dim) + \ d_i.view(-1, 1) * self.embedding['alpha_R'](r_i).view(-1, 1) * self.embedding['emb_TR'](r_i).view(-1, self.emb_dim) \ + self.embedding['beta_R'](r_i).view(-1, self.emb_dim) * torch.sin( 2 * pi * self.embedding['omega_R'](r_i).view(-1, self.emb_dim) * d_i.view(-1, 1)) h_var = self.embedding['emb_E_var'](h_i).view(-1, self.emb_dim) t_var = self.embedding['emb_E_var'](t_i).view(-1, self.emb_dim) r_var = self.embedding['emb_R_var'](r_i).view(-1, self.emb_dim) out1 = torch.sum((h_var + t_var) / r_var, 1) + torch.sum(((r_mean - h_mean + t_mean) ** 2) / r_var, 1) - self.emb_dim out2 = torch.sum(r_var / (h_var + t_var), 1) + torch.sum(((h_mean - t_mean - r_mean) ** 2) / (h_var + t_var), 1) - self.emb_dim scores = (out1 + out2) / 4 scores = scores.view(bs, -1) factors = { "renorm": (self.embedding['emb_E'].weight, self.embedding['emb_R'].weight, self.embedding['emb_TE'].weight, self.embedding['emb_TR'].weight), "clamp": (self.embedding['emb_E_var'].weight, self.embedding['emb_R_var'].weight) } return scores, factors # TODO(gengyaun): # walkaround def predict(self, sample: torch.Tensor): bs = sample.size(0) # TODO(gengyuan) dim = sample.size(1) // (self.dataset.num_entities()) sample = sample.view(-1, dim) # TODO(gengyuan) type conversion when feeding the data instead of running the models h_i, t_i, r_i, d_i = sample[:, 0].long(), sample[:, 2].long(), sample[:, 1].long(), sample[:, 3] pi = 3.14159265358979323846 h_mean = self.embedding['emb_E'](h_i).view(-1, self.emb_dim) + \ d_i.view(-1, 1) * self.embedding['alpha_E'](h_i).view(-1, 1) * self.embedding['emb_TE'](h_i).view(-1, self.emb_dim) \ + self.embedding['beta_E'](h_i).view(-1, self.emb_dim) * torch.sin( 2 * pi * self.embedding['omega_E'](h_i).view(-1, self.emb_dim) * d_i.view(-1, 1)) t_mean = self.embedding['emb_E'](t_i).view(-1, self.emb_dim) + \ d_i.view(-1, 1) * self.embedding['alpha_E'](t_i).view(-1, 1) * self.embedding['emb_TE'](t_i).view(-1, self.emb_dim) \ + self.embedding['beta_E'](t_i).view(-1, self.emb_dim) * torch.sin( 2 * pi * self.embedding['omega_E'](t_i).view(-1, self.emb_dim) * d_i.view(-1, 1)) r_mean = self.embedding['emb_R'](r_i).view(-1, self.emb_dim) + \ d_i.view(-1, 1) * self.embedding['alpha_R'](r_i).view(-1, 1) * self.embedding['emb_TR'](r_i).view(-1, self.emb_dim) \ + self.embedding['beta_R'](r_i).view(-1, self.emb_dim) * torch.sin( 2 * pi * self.embedding['omega_R'](r_i).view(-1, self.emb_dim) * d_i.view(-1, 1)) h_var = self.embedding['emb_E_var'](h_i).view(-1, self.emb_dim) t_var = self.embedding['emb_E_var'](t_i).view(-1, self.emb_dim) r_var = self.embedding['emb_R_var'](r_i).view(-1, self.emb_dim) out1 = torch.sum((h_var + t_var) / r_var, 1) + torch.sum(((r_mean - h_mean + t_mean) ** 2) / r_var, 1) - self.emb_dim out2 = torch.sum(r_var / (h_var + t_var), 1) + torch.sum(((h_mean - t_mean - r_mean) ** 2) / (h_var + t_var), 1) - self.emb_dim scores = (out1 + out2) / 4 scores = scores.view(bs, -1) factors = { "renorm": (self.embedding['emb_E'].weight, self.embedding['emb_R'].weight, self.embedding['emb_TE'].weight, self.embedding['emb_TR'].weight), "clamp": (self.embedding['emb_E_var'].weight, self.embedding['emb_R_var'].weight) } return scores, factors # reference: https://github.com/bsantraigi/TA_TransE/blob/master/model.py # reference: https://github.com/jimmywangheng/knowledge_representation_pytorch @BaseModel.register(name="ta_transe") class TATransEModel(BaseModel): def __init__(self, config: Config, dataset: DatasetProcessor): super().__init__(config, dataset) # model params from files self.emb_dim = self.config.get("model.emb_dim") self.l1_flag = self.config.get("model.l1_flag") self.p = self.config.get("model.p") self.dropout = torch.nn.Dropout(p=self.p) self.lstm = LSTMModel(self.emb_dim, n_layer=1) self.prepare_embedding() def prepare_embedding(self): num_ent = self.dataset.num_entities() num_rel = self.dataset.num_relations() num_tem = 32 # should be 32 self.embedding: Dict[str, torch.nn.Embedding] = defaultdict(None) self.embedding['ent'] = torch.nn.Embedding(num_ent, self.emb_dim) self.embedding['rel'] = torch.nn.Embedding(num_rel, self.emb_dim) self.embedding['tem'] = torch.nn.Embedding(num_tem, self.emb_dim) self.embedding = nn.ModuleDict(self.embedding) for _, emb in self.embedding.items(): torch.nn.init.xavier_uniform_(emb.weight) emb.weight.data.renorm(p=2, dim=1, maxnorm=1) def get_rseq(self, rel: torch.LongTensor, tem: torch.LongTensor): r_e = self.embedding['rel'](rel) r_e = r_e.unsqueeze(0).transpose(0, 1) bs = tem.size(0) tem_len = tem.size(1) tem = tem.contiguous() tem = tem.view(bs * tem_len) token_e = self.embedding['tem'](tem) token_e = token_e.view(bs, tem_len, self.emb_dim) seq_e = torch.cat((r_e, token_e), 1) hidden_tem = self.lstm(seq_e) hidden_tem = hidden_tem[0, :, :] rseq_e = hidden_tem return rseq_e def forward(self, samples: torch.Tensor): h, r, t, tem = samples[:, 0].long(), samples[:, 1].long(), samples[:, 2].long(), samples[:, 3:].long() h_e = self.embedding['ent'](h) t_e = self.embedding['ent'](t) rseq_e = self.get_rseq(r, tem) h_e = self.dropout(h_e) t_e = self.dropout(t_e) rseq_e = self.dropout(rseq_e) if self.l1_flag: scores = torch.sum(torch.abs(h_e + rseq_e - t_e), 1) else: scores = torch.sum((h_e + rseq_e - t_e) ** 2, 1) factors = { "norm": (h_e, t_e, rseq_e) } return scores, factors def fit(self, samples: torch.Tensor): bs = samples.size(0) dim = samples.size(1) // (1 + self.config.get("negative_sampling.num_samples")) samples = samples.view(-1, dim) scores, factor = self.forward(samples) scores = scores.view(bs, -1) return scores, factor def predict(self, queries: torch.Tensor): assert torch.isnan(queries).sum(1).byte().all(), "Either head or tail should be absent." bs = queries.size(0) dim = queries.size(0) candidates = all_candidates_of_ent_queries(queries, self.dataset.num_entities()) scores, _ = self.forward(candidates) scores = scores.view(bs, -1) return scores # reference: https://github.com/bsantraigi/TA_TransE/blob/master/model.py @BaseModel.register(name="ta_distmult") class TADistmultModel(BaseModel): def __init__(self, config: Config, dataset: DatasetProcessor): super().__init__(config, dataset) # model params from files self.emb_dim = self.config.get("model.emb_dim") self.l1_flag = self.config.get("model.l1_flag") self.p = self.config.get("model.p") self.dropout = torch.nn.Dropout(p=self.p) self.lstm = LSTMModel(self.emb_dim, n_layer=1) self.criterion = nn.Softplus() self.prepare_embedding() def prepare_embedding(self): num_ent = self.dataset.num_entities() num_rel = self.dataset.num_relations() num_tem = 32 # should be 32 self.embedding: Dict[str, torch.nn.Embedding] = defaultdict(None) self.embedding['ent'] = torch.nn.Embedding(num_ent, self.emb_dim) self.embedding['rel'] = torch.nn.Embedding(num_rel, self.emb_dim) self.embedding['tem'] = torch.nn.Embedding(num_tem, self.emb_dim) self.embedding = nn.ModuleDict(self.embedding) for _, emb in self.embedding.items(): torch.nn.init.xavier_uniform_(emb.weight) emb.weight.data.renorm(p=2, dim=1, maxnorm=1) def forward(self, samples: torch.Tensor): h, r, t, tem = samples[:, 0].long(), samples[:, 1].long(), samples[:, 2].long(), samples[:, 3:].long() h_e = self.embedding['ent'](h) t_e = self.embedding['ent'](t) rseq_e = self.get_rseq(r, tem) h_e = self.dropout(h_e) t_e = self.dropout(t_e) rseq_e = self.dropout(rseq_e) scores = torch.sum(h_e * t_e * rseq_e, 1, False) factors = { "norm": (self.embedding['ent'].weight, self.embedding['rel'].weight, self.embedding['tem'].weight) } return scores, factors def get_rseq(self, rel, tem): r_e = self.embedding['rel'](rel) r_e = r_e.unsqueeze(0).transpose(0, 1) bs = tem.size(0) tem_len = tem.size(1) tem = tem.contiguous() tem = tem.view(bs * tem_len) token_e = self.embedding['tem'](tem) token_e = token_e.view(bs, tem_len, self.emb_dim) seq_e = torch.cat((r_e, token_e), 1) hidden_tem = self.lstm(seq_e) hidden_tem = hidden_tem[0, :, :] rseq_e = hidden_tem return rseq_e def fit(self, samples: torch.Tensor): bs = samples.size(0) dim = samples.size(1) // (1 + self.config.get("negative_sampling.num_samples")) samples = samples.view(-1, dim) scores, factor = self.forward(samples) scores = scores.view(bs, -1) return scores, factor def predict(self, queries: torch.Tensor): assert torch.isnan(queries).sum(1).byte().all(), "Either head or tail should be absent." bs = queries.size(0) dim = queries.size(0) candidates = all_candidates_of_ent_queries(queries, self.dataset.num_entities()) scores, _ = self.forward(candidates) scores = scores.view(bs, -1) return scores

42.301987

136

0.591365

4,452

31,938

4.024483

0.072776

0.129151

0.032371

0.049841

0.780655

0.737344

0.711057

0.68142

0.641346

0.53452

0

0.018796

0.25872

31,938

754

137

42.35809

0.737994

0.134354

0

0.555324

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0.060144

0.006816

0

0.005305

0.008351

1

0.077244

false

0

0.031315

0

0.162839

0

null

0

1

0

null

0

2

f7e464e396dc4a7b5350555581b28024555d3b3e

244

py

Python

app/ml/objects/feature/enum.py

PSE-TECO-2020-TEAM1/e2e-ml_model-management

7f01a008648e25a29c639a5e16124b2e399eb821

[ "MIT" ]

1

2021-05-04T08:46:19.000Z

app/ml/objects/feature/enum.py

PSE-TECO-2020-TEAM1/e2e-ml_model-management

7f01a008648e25a29c639a5e16124b2e399eb821

[ "MIT" ]

null

app/ml/objects/feature/enum.py

PSE-TECO-2020-TEAM1/e2e-ml_model-management

7f01a008648e25a29c639a5e16124b2e399eb821

[ "MIT" ]

1

2022-01-28T21:21:32.000Z

from enum import Enum class Feature(str, Enum): MINIMUM = "MINIMUM" MAXIMUM = "MAXIMUM" VARIANCE = "VARIANCE" ABS_ENERGY = "ABS_ENERGY" MEAN = "MEAN" MEDIAN = "MEDIAN" SKEWNESS = "SKEWNESS" KURTOSIS = "KURTOSIS"

22.181818

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244

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1

0

null

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null

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1

0

2

f7efad003a168e738e4e8d59b3b9142e900130cd

825

py

Python

tools/leetcode.071.Simplify Path/leetcode.071.Simplify Path.submission9.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

4

2015-10-10T00:30:55.000Z

2020-07-27T19:45:54.000Z

tools/leetcode.071.Simplify Path/leetcode.071.Simplify Path.submission9.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

null

tools/leetcode.071.Simplify Path/leetcode.071.Simplify Path.submission9.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

null

class Solution: # @param path, a string # @return a string def simplifyPath(self, path): root = self.node('') root.previous = root p = [i for i in path.split('/') if i != ''] temp = root for i in p: if i == '..': temp = temp.previous temp.next = None elif i != '.': temp.next = self.node(i) temp.next.previous = temp temp = temp.next temp = root.next res = '' while temp != None: res += '/'+temp.val temp = temp.next if not res: return '/' return res class node: def __init__(self,x): self.val = x self.previous = None self.next = None

825

0.420606

90

825

3.811111

0.322222

0.116618

0.034985

0

0.467879

825

1

825

0.781321

0.046061

0

0.074074

0

0.007643

0

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0.074074

false

0

0.222222

0

null

0

1

0

1

0

null

0

2

7904a48fd08bc3a934fe3f4f273745b2570dce4c

21,535

py

Python

hw06_train.py

arao53/BME695-object-detection

7f094cc016d91c6b00d6f86f7c3e2e96acbb0083

[ "MIT" ]

null

hw06_train.py

arao53/BME695-object-detection

7f094cc016d91c6b00d6f86f7c3e2e96acbb0083

[ "MIT" ]

null

hw06_train.py

arao53/BME695-object-detection

7f094cc016d91c6b00d6f86f7c3e2e96acbb0083

[ "MIT" ]

null

# -*- coding: utf-8 -*- """hw06_training.ipynb Automatically generated by Colaboratory. Original file is located at https://colab.research.google.com/drive/1bjAeUIVjt9W8mASk8vw1y2SbuBYuQdlG """ !pip install reports import PIL.Image as Image, requests, urllib, random import argparse, json, PIL.Image, reports, os, pickle from requests.exceptions import ConnectionError, ReadTimeout, TooManyRedirects, MissingSchema, InvalidURL import numpy, torch, cv2, skimage import skimage.io as io from torch import nn import torch.nn.functional as F from pycocotools.coco import COCO import glob from torch.utils.data import DataLoader,Dataset import torchvision.transforms as tvt import matplotlib.pyplot as plt from torchsummary import summary import pandas as pd # Mount google drive to run on Colab #from google.colab import drive #drive.mount('/content/drive') #%cd "/content/drive/My Drive/Colab Notebooks/DeepLearning/hw06/" #!pwd #!ls root_path = "/content/drive/My Drive/Colab Notebooks/DeepLearning/hw06/" coco_json_path = "annotations/instances_train2017.json" class_list = ["person", "dog", "hot dog"] coco = COCO(coco_json_path) class build_annotations: # Structure of the all_annotations file: # indexed by the image filepath, removing the '.jpg' or the string version (with zeros) of the imageID # For each image: # 'imageID': corresponds to the integer image ID assigned within COCO. # 'num_objects': integer number of objects in the image (at most 5) # 'bbox': a dictionary of the bounding box array for each instance within the image. The dictionary key is the string 0-5 of each instance in order of decreasing area # 'labels': a dictionary of the labels of each instance within the image. The key is the same as bbox but the value is the integer category ID assigned within COCO. def __init__(self, root_path, class_list, max_instances = 5): self.root_path = root_path self.image_dir = root_path + '*.jpg' self.cat_IDs = coco.getCatIds(catNms=class_list) self.max_instances = max_instances def __call__(self): all_annotations = {} g = glob.glob(self.image_dir) for i, filename in enumerate(g): filename = filename.split('/')[-1] img_ID = int(filename.split('.')[0]) ann_Ids = coco.getAnnIds(imgIds=img_ID, catIds = self.cat_IDs, iscrowd = False) num_objects = min(len(ann_Ids), self.max_instances) # cap at a max of 5 images anns = coco.loadAnns(ann_Ids) indices = sort_by_area(anns, self.max_instances) bbox = {} label = {} i = 0 for n in indices: instance = anns[n] bbox[str(i)] = instance['bbox'] label[str(i)] = instance['category_id'] i+=1 annotation= {"imageID":img_ID, "num_objects":i, 'bbox': bbox, 'labels':label} all_annotations[filename.split('.')[0]] = annotation ann_path = self.root_path + "image_annotations.p" pickle.dump( all_annotations, open(ann_path, "wb" ) ) print('Annotations saved in:', ann_path) def sort_by_area(anns, num): areas = numpy.zeros(len(anns)) for i, instance in enumerate(anns): areas[i] = instance['area'] indices = numpy.argsort(areas)[-num:] return indices[::-1] class your_dataset_class(Dataset): def __init__(self, path, class_list, coco): self.class_list = class_list self.folder = path self.coco = coco self.catIds = coco.getCatIds(catNms = class_list) self.imgIds = coco.getImgIds(catIds = self.catIds) self.categories = coco.loadCats(self.catIds) #create label dictionary labeldict = {} for idx, in_class in enumerate(self.class_list): for c in self.categories: if c["name"] == in_class: labeldict[c['id']] = idx self.coco_labeldict = labeldict #if first time running, index the image dataset to make annotation .p file annotation_path = path + 'image_annotations.p' if os.path.exists(annotation_path) ==False: print("Indexing dataset to compile annotations...") dataset_annotations = build_annotations(path, class_list) dataset_annotations() self.data_anns = pickle.load(open(annotation_path, "rb" )) def __len__(self): g = glob.glob(self.folder + '*.jpg') # ,'*.jpg') return (len(g)) def get_imagelabel(self, img_path, sc, max_objects = 5): #img_path = file location, sc = scale [0]: width, [1]: height saved_filename = os.path.basename(img_path) filename = saved_filename.split('.jpg')[0] image_id = int(filename)#.split('_')[-1]) bbox_tensor = torch.zeros(max_objects, 4, dtype=torch.uint8) label_tensor = torch.zeros(max_objects+1, dtype=torch.uint8) + len(self.class_list) target_obj = self.data_anns[filename] num_objects = target_obj['num_objects'] for n in range(num_objects): [x,y,w,h] = target_obj['bbox'][str(n)] bbox = [sc[1]*y, x*sc[0], sc[1]*(h), sc[0]*(w)] bbox_tensor[n,:] = torch.tensor(numpy.array(bbox)) cat_label = target_obj['labels'][str(n)] data_label = self.coco_labeldict[cat_label] label_tensor[n] = torch.tensor(data_label) return bbox_tensor, label_tensor def __getitem__(self, item): g = glob.glob(self.folder + '*.jpg') #'**/*.jpg') # , '*.jpg') im = PIL.Image.open(g[item]) im, scale_fac = rescale_factor(im, 128) #overwrite old image with new resized image of size 256 W, H = im.size transformer = tvt.Compose([tvt.ToTensor(), tvt.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))]) im_array = torch.randint(0, 256, (3, H, W)).type(torch.uint8) for i in range(H): for j in range(W): im_array[:, j, i] = torch.tensor(im.getpixel((i, j))) im_scaled = im_array / im_array.max() # scaled from 0-1 im_tf = transformer(numpy.transpose(im_scaled.numpy())) num_classes = len(self.class_list) bbox, label = self.get_imagelabel(g[item], scale_fac) sample = {'im_ID': g[item], 'scale':scale_fac, 'image': im_tf, 'bbox' : bbox, 'label': label} return sample def rescale_factor(im_original, std_size): raw_width, raw_height = im_original.size im = im_original.resize((std_size, std_size), Image.BOX) w_factor = std_size/raw_width h_factor = std_size/raw_height return (im, [w_factor, h_factor]) #train_path = os.path.join(root_path, "Train/") train_path = root_path + "Train/" val_path = os.path.join(root_path, "Val/") batch_size = 64 train_dataset = your_dataset_class(train_path, class_list, coco) #train_dataset.__getitem__(32) train_data_loader = torch.utils.data.DataLoader(dataset = train_dataset, batch_size = batch_size, shuffle = True, num_workers= 2, drop_last=True) #val_dataset = your_dataset_class(val_path, class_list) #val_data_loader = torch.utils.data.DataLoader(dataset = val_dataset, # batch_size = batch_size, # shuffle = True, # num_workers = 4, # drop_last=True) class SkipBlock(nn.Module): def __init__(self,in_ch, out_ch, downsample = False): super().__init__() self.in_ch = in_ch self.out_ch = out_ch self.conv1 = nn.Conv2d(in_ch, out_ch, 3, stride = 1, padding = 1) self.conv2 = nn.Conv2d(in_ch, out_ch, 3, padding = 1) self.bnorm1 = nn.BatchNorm2d(out_ch) self.bnorm2 = nn.BatchNorm2d(out_ch) self.downsample_tf = downsample self.downsampler = nn.Conv2d(in_ch, out_ch, 1, stride= 2) def forward(self, x): identity = x out = self.conv1(x) out = self.bnorm1(out) out = F.relu(out) if self.downsample_tf == True: identity = self.downsampler(identity) out = self.downsampler(out) out += identity else: out = self.conv2(out) out = self.bnorm2(out) out = F.relu(out) out += identity return out class MechEnet(nn.Module): def __init__(self, num_classes, depth): super().__init__() self.depth = depth // 8 self.conv_initial = nn.Conv2d( 3, 64, 3, padding = 1) self.pool = nn.MaxPool2d(2,2) ## assume all layers are 64 channels deep self.skipblock64_1 = nn.ModuleList() for i in range(self.depth): #print("adding layer", i) self.skipblock64_1.append( SkipBlock(64,64, downsample = False) ) #append a 64 in/out ch layer - depth*2/4 convolutions self.skip_downsample = SkipBlock(64,64, downsample= True) self.skipblock64_2 = nn.ModuleList() for i in range(self.depth): #print("adding layer", i + self.depth) self.skipblock64_2.append( SkipBlock(64,64, downsample = False) ) #append a 64 in/out layer - depth*2/4 convolutions self.fc_seqn = nn.Sequential( nn.Linear(64*4*4, 3000), nn.ReLU(inplace =True), nn.Linear(3000,3000), nn.ReLU(inplace =True), nn.Linear(3000,8*8*(5*(5+3))) #5 anchor boxes*(1+ bbox(4) + classes (3)) ) def forward(self, x): # x1 is the output of classification x = self.pool(F.relu(self.conv_initial(x))) x1 = self.skip_downsample(x) for i, skips in enumerate(self.skipblock64_1[self.depth//4 :]): x1 = skips(x1) x1 = self.skip_downsample(x1) for i, skips in enumerate(self.skipblock64_1[:self.depth//4]): x1 = skips(x1) x1 = self.skip_downsample(x1) for i, skips in enumerate(self.skipblock64_2[self.depth//4:]): x1 = skips(x1) x1 = self.skip_downsample(x1) for i, skips in enumerate(self.skipblock64_2[:self.depth//4]): x1 = skips(x1) #x1 = self.skip_downsample(x) x1 = x1.view(x1.size(0),-1) x1 = self.fc_seqn(x1) return x1 class IoULoss(torch.nn.Module): def __init__(self, weight=None, size_average=True): super(IoULoss, self).__init__() def forward(self, inputs, targets, smooth=1): #flatten label and prediction tensors # tensor shape = [b, yolo_cell, anch, yolovector] # flattened tensor = [b, numcells*numanch*8] b_size = inputs.shape[0] pred_unscrm = inputs.view(b_size, 8**2, 5, -1) targ_unscrm = targets.view(b_size, 8**2, 5, -1) pred_bbox = pred_unscrm[:,:,:,1:5] targ_bbox = targ_unscrm[:,:,:,1:5] intersection = targ_bbox*pred_bbox union = targ_bbox + pred_bbox J_idx = torch.div(intersection, union) #print(J_idx) J_dist = 1.0-J_idx return torch.sum(J_dist) ## significant code is adapted from Prof. Kak's Multi-instance detector def run_code_for_training(net, lrate, mom, epochs, im_size, max_objects, yolo_interval = 16): print('Beginning training for', epochs,'epochs...') #criterion1 = torch.nn.CrossEntropyLoss() criterion = torch.nn.MSELoss() #criterion = IoULoss() optimizer = torch.optim.SGD(net.parameters(), lr = lrate, momentum = mom) loss_tracker = [] num_cells_image_height = im_size//yolo_interval num_cells_image_width = im_size//yolo_interval num_yolo_cells = num_cells_image_height*num_cells_image_width print_iteration = 3 num_anchor_boxes = 5 yolo_tensor = torch.zeros(batch_size, num_yolo_cells, num_anchor_boxes, 1*5+3) #batch size, 8*8, 1*5+3 classes class AnchorBox: def __init__(self, AR, topleft, abox_h, abox_w, abox_idx): self.AR = AR self.topleft = topleft self.abox_h = abox_h self.abox_w = abox_w self.abox_idx= abox_idx device = torch.device("cuda:0") for epoch in range(epochs): print('\nEpoch %d training...' %(epoch + 1)) running_loss = 0.0 for i, data in enumerate(train_data_loader): sample_batch = data['im_ID'] im_tensor = data["image"] target_reg = data["bbox"].type(torch.FloatTensor) target_clf = data["label"].type(torch.LongTensor) optimizer.zero_grad() im_tensor = im_tensor.to(device) target_reg = target_reg.to(device) target_clf = target_clf.to(device) yolo_tensor = yolo_tensor.to(device) obj_centers = {ibx : {idx : None for idx in range(max_objects)} for ibx in range(im_tensor.shape[0])} anchor_boxes_1_1 = [[AnchorBox(1/1, (i*yolo_interval,j*yolo_interval), yolo_interval, yolo_interval, 0) for i in range(0,num_cells_image_height)] for j in range(0,num_cells_image_width)] anchor_boxes_1_3 = [[AnchorBox(1/3, (i*yolo_interval,j*yolo_interval), yolo_interval, 3*yolo_interval, 1) for i in range(0,num_cells_image_height)] for j in range(0,num_cells_image_width)] anchor_boxes_3_1 = [[AnchorBox(3/1, (i*yolo_interval,j*yolo_interval), 3*yolo_interval, yolo_interval, 2) for i in range(0,num_cells_image_height)] for j in range(0,num_cells_image_width)] anchor_boxes_1_5 = [[AnchorBox(1/5, (i*yolo_interval,j*yolo_interval), yolo_interval, 5*yolo_interval, 3) for i in range(0,num_cells_image_height)] for j in range(0,num_cells_image_width)] anchor_boxes_5_1 = [[AnchorBox(5/1, (i*yolo_interval,j*yolo_interval), 5*yolo_interval, yolo_interval, 4) for i in range(0,num_cells_image_height)] for j in range(0,num_cells_image_width)] #Build the yolo tensor based on the bounding box and label tensors from the target/dataset for b in range(im_tensor.shape[0]): # Loop through batch index for idx in range(max_objects): # Loop through each object in the target tensor height_center_bb = (target_reg[b][idx][1].item() + target_reg[b][idx][3].item()) // 2 width_center_bb = (target_reg[b][idx][0].item() + target_reg[b][idx][2].item()) // 2 obj_bb_height = target_reg[b][idx][3].item() - target_reg[b][idx][1].item() obj_bb_width = target_reg[b][idx][2].item() - target_reg[b][idx][0].item() obj_label = target_clf[b][idx].item() if obj_label == 13: obj_label = 4 eps = 1e-8 AR = float(obj_bb_height + eps) / float(obj_bb_width + eps) cell_row_idx = int(height_center_bb // yolo_interval) ## for the i coordinate cell_col_idx = int(width_center_bb // yolo_interval) ## for the j coordinates if AR <= 0.2: ## (F) anchbox = anchor_boxes_1_5[cell_row_idx][cell_col_idx] elif AR <= 0.5: anchbox = anchor_boxes_1_3[cell_row_idx][cell_col_idx] elif AR <= 1.5: anchbox = anchor_boxes_1_1[cell_row_idx][cell_col_idx] elif AR <= 4: anchbox = anchor_boxes_3_1[cell_row_idx][cell_col_idx] elif AR > 4: anchbox = anchor_boxes_5_1[cell_row_idx][cell_col_idx] bh = float(obj_bb_height) / float(yolo_interval) ## (G) bw = float(obj_bb_width) / float(yolo_interval) obj_center_x = float(target_reg[b][idx][2].item() + target_reg[b][idx][0].item()) / 2.0 obj_center_y = float(target_reg[b][idx][3].item() + target_reg[b][idx][1].item()) / 2.0 yolocell_center_i = cell_row_idx*yolo_interval + float(yolo_interval) / 2.0 yolocell_center_j = cell_col_idx*yolo_interval + float(yolo_interval) / 2.0 del_x = float(obj_center_x - yolocell_center_j) / yolo_interval del_y = float(obj_center_y - yolocell_center_i) / yolo_interval yolo_vector = [0, del_x, del_y, bh, bw, 0, 0, 0] if obj_label<4: yolo_vector[4 + obj_label] = 1 yolo_vector[0] = 1 yolo_cell_index = cell_row_idx * num_cells_image_width + cell_col_idx yolo_tensor[b, yolo_cell_index, anchbox.abox_idx] = torch.FloatTensor( yolo_vector ) yolo_tensor_flattened = yolo_tensor.view(im_tensor.shape[0], -1) ## Foward Pass pred_yolo = net(im_tensor) #pred_yolo = filter_yolo_tensor(pred_yolo, im_tensor.shape[0], num_yolo_cells, num_anchor_boxes) loss = criterion(pred_yolo, yolo_tensor_flattened) loss.backward(retain_graph = True) pred_unscrm = pred_yolo.view(im_tensor.shape[0], 8**2, 5, -1) sample_yolo_tensor = pred_unscrm optimizer.step() running_loss += loss.item() if (i+1)%print_iteration ==0: average_loss = running_loss/float(print_iteration) print("[epoch: %d, batch: %5d] Avg Batch loss: %.4f" %(epoch + 1, i+1, average_loss)) loss_tracker = numpy.append(loss_tracker, average_loss) running_loss = 0.0 return loss_tracker, sample_yolo_tensor, sample_batch def filter_yolo_tensor(yolo_tensor, batch_size, num_yolo_cells, aboxes): #loop through each yolo_cell_index in the in the prediction tensor # if idx[0] of the yolo vector is less than 0.5, make the whole vector zero zero_vec = torch.zeros(8) print(yolo_tensor.shape) for b in range(batch_size): for num in range(num_yolo_cells): for an in range(aboxes): if yolo_tensor[b,num][an][0] < 0.5: yolo_tensor[b,num][an][:] = torch.zeros(8) return yolo_tensor model = MechEnet(len(class_list), depth = 64) lrate = 5e-3 mom = 0.5 epochs = 1 yolo_int = 16 im_size = 128 max_objects = 5 savepath = "MechEnet.pth" model.load_state_dict(torch.load(savepath)) if torch.cuda.is_available(): device = torch.device("cuda:0") model.cuda() summary(model, (3, im_size, im_size)) training_loss, yolo_sample, batches = run_code_for_training(model, lrate, mom, epochs, im_size, max_objects, yolo_interval = yolo_int) #savepath = "/content/drive/My Drive/Colab Notebooks/DeepLearning/hw06/MechEnet.pth" #torch.save(model.state_dict(), savepath) #pd.DataFrame(training_loss).to_csv("/content/drive/My Drive/Colab Notebooks/DeepLearning/hw06/loss.csv") fig, ax = plt.subplots() ax.plot(training_loss) ax.set_title('Training loss') ax.set_ylabel('Loss') ax.set_xlabel('Iterations') ## Visualize prediction on training set annotation_path = root_path + 'Train/'+ 'image_annotations.p' data_anns = pickle.load(open(annotation_path, "rb" )) def show_image(image_anns): img = coco.loadImgs(rand_img['imageID'])[0] I = io.imread(img['coco_url']) if len(I.shape) == 2: I = skimage.color.gray2rgb(I) catIds = coco.getCatIds(catNms= class_list) annIds = coco.getAnnIds(imgIds=rand_img['imageID'], catIds= catIds, iscrowd=False) anns = coco.loadAnns(annIds) image = numpy.uint8(I) for i in range(rand_img['num_objects']): [x,y,w,h] = rand_img['bbox'][str(i)] label = rand_img['labels'][str(i)] image = cv2.rectangle(image, (int(x), int(y)), (int(x +w), int(y + h)), (36,255,12), 2) class_label = coco_labels_inverse[label] image = cv2.putText(image, 'True ' + class_list[class_label], (int(x), int(y-10)), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (36,255,12), 2) return image bdx =37 #numpy.random.randint(0,64) #55 #18 #5 img_loc = batches[bdx].split('/')[-1].split('.')[0] rand_img = data_anns[img_loc] image = show_image(rand_img) scale = train_dataset.__getitem__(sdx)['scale'] g = glob.glob(root_path + 'Train/*.jpg') for i in range(len(g)): if img_loc in g[i]: sdx = i import math im_considered = yolo_sample[bdx,:,:,:] im_pred_anch = torch.zeros(64,8) cell_pred = [] num_cell_width = 8 yolo_interval = 16 for i in range(im_considered.shape[0]): AR = torch.argmax(im_considered[i,:,0]) im_pred_anch[i,:] = im_considered[i,AR,:] if im_pred_anch[i,0] > 0.75: if AR == 0: w,h = 1,1 elif AR == 1: w,h = 1,3 elif AR == 2: w,h = 3,1 elif AR == 3: w,h = 1,5 elif AR == 4: w,h = 5,1 row_idx = math.floor(i/num_cell_width) col_idx = i%num_cell_width yolo_box = im_pred_anch[i,1:5].cpu().detach().numpy() x1 = ((row_idx + 0.5)*yolo_interval)/scale[0] x2 = x1 + (w*yolo_interval)/scale[0] y1 = (col_idx + 0.5)*yolo_interval/scale[1] y2 = y1+ (h*yolo_interval)/scale[1] label = torch.argmax(im_pred_anch[i,5:]).cpu().detach().numpy() pred_label = str('Predicted ' + class_list[label]) temp = [pred_label, x1,y1, x2,y2] cell_pred = numpy.append(cell_pred, temp) image = cv2.rectangle(image, (int(x1), int(y1)), (int(x2), int(y2)), (255,0,0), 2) image = cv2.putText(image, pred_label, (int(x1), int(y1-10)), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255,0,0), 2) fig, ax = plt.subplots(1,1, dpi = 150) ax.imshow(image) ax.set_axis_off() plt.axis('tight') plt.show()

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2

7905bc2147b61285b910192e1759b412fc9029ee

67

py

Python

webpie/Version.py

webpie/webpie

c7f1bc29a63c0be683c60756165a6c65260211f9

[ "BSD-3-Clause" ]

2

2021-12-10T16:12:51.000Z

2022-01-06T17:29:12.000Z

webpie/Version.py

webpie/webpie

c7f1bc29a63c0be683c60756165a6c65260211f9

[ "BSD-3-Clause" ]

null

webpie/Version.py

webpie/webpie

c7f1bc29a63c0be683c60756165a6c65260211f9

[ "BSD-3-Clause" ]

null

Version = "5.6.5" if __name__ == "__main__": print (Version)

11.166667

26

0.597015

9

67

3.555556

0.777778

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0.057692

0.223881

67

5

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0.19697

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0.333333

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0

null

0

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null

0

2

79079afb5049c4952a78491f534997124403c2b1

999

py

Python

sdk/communication/azure-communication-networktraversal/azure/communication/networktraversal/_generated/models/_communication_network_traversal_client_enums.py

vincenttran-msft/azure-sdk-for-python

348b56f9f03eeb3f7b502eed51daf494ffff874d

[ "MIT" ]

1

2022-03-09T08:59:13.000Z

sdk/communication/azure-communication-networktraversal/azure/communication/networktraversal/_generated/models/_communication_network_traversal_client_enums.py

vincenttran-msft/azure-sdk-for-python

348b56f9f03eeb3f7b502eed51daf494ffff874d

[ "MIT" ]

null

sdk/communication/azure-communication-networktraversal/azure/communication/networktraversal/_generated/models/_communication_network_traversal_client_enums.py

vincenttran-msft/azure-sdk-for-python

348b56f9f03eeb3f7b502eed51daf494ffff874d

[ "MIT" ]

1

2022-03-04T06:21:56.000Z

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from enum import Enum from six import with_metaclass from azure.core import CaseInsensitiveEnumMeta class RouteType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)): """The routing methodology to where the ICE server will be located from the client. "any" will have higher reliability while "nearest" will have lower latency. It is recommended to default to use the "any" routing method unless there are specific scenarios which minimizing latency is critical. """ ANY = "any" NEAREST = "nearest"

43.434783

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0.648649

118

999

5.474576

0.686441

0.018576

0

0.001183

0.154154

999

22

100

45.409091

0.763314

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null

0

null

0

1

0

1

0

2

790dd1c98aa84804fd6deae9806710c465315553

528

py

Python

ex009a.py

emerfelippini/Curso_em_video-Aulas_Python

5b1d78b259732bb9bbad27cd30ce91bba77c5ef0

[ "MIT" ]

null

ex009a.py

emerfelippini/Curso_em_video-Aulas_Python

5b1d78b259732bb9bbad27cd30ce91bba77c5ef0

[ "MIT" ]

null

ex009a.py

emerfelippini/Curso_em_video-Aulas_Python

5b1d78b259732bb9bbad27cd30ce91bba77c5ef0

[ "MIT" ]

null

a = int(input('Digite um número para saber sua tabuada :')) n1 = a*1 n2 = a*2 n3 = a*3 n4 = a*4 n5 = a*5 n6 = a*6 n7 = a*7 n8 = a*8 n9 = a*9 n10 = a*10 print('A sua tabuada é') print('{} x 1 = {}'.format(a, n1)) print('{} x 2 = {}'.format(a, n2)) print('{} x 3 = {}'.format(a, n3)) print('{} x 4 = {}'.format(a, n4)) print('{} x 5 = {}'.format(a, n5)) print('{} x 6 = {}'.format(a, n6)) print('{} x 7 = {}'.format(a, n7)) print('{} x 8 = {}'.format(a, n8)) print('{} x 9 = {}'.format(a, n9)) print('{} x 10 = {}'.format(a, n10))

24

59

0.498106

105

528

2.504762

0.32381

0.228137

0

0.103529

0.195076

528

22

60

24

0.515294

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false

0

0.5

0

null

1

0

null

0

1

0

2

792091588798652fc74a75c6e942925554fc4793

562

py

Python

qiubai/qiubai/items.py

zouyuwuse/Spiders

28764b6f4eeccffcf875a8656f30d0c8bb34ce22

[ "Apache-2.0" ]

31

2017-05-24T02:31:33.000Z

2020-04-19T08:15:23.000Z

qiubai/qiubai/items.py

zouyuwuse/Spiders

28764b6f4eeccffcf875a8656f30d0c8bb34ce22

[ "Apache-2.0" ]

3

2017-05-26T15:12:54.000Z

2018-03-13T05:37:04.000Z

qiubai/qiubai/items.py

zouyuwuse/Spiders

28764b6f4eeccffcf875a8656f30d0c8bb34ce22

[ "Apache-2.0" ]

28

2017-05-24T15:40:45.000Z

2020-04-19T08:15:29.000Z

# -*- coding: utf-8 -*- # Define here the models for your scraped items # # See documentation in: # http://doc.scrapy.org/en/latest/topics/items.html import scrapy class QiubaiItem(scrapy.Item): # define the fields for your item here like: # name = scrapy.Field() _id = scrapy.Field() avatar = scrapy.Field() profile_link = scrapy.Field() name = scrapy.Field() gender = scrapy.Field() age = scrapy.Field() content = scrapy.Field() content_link = scrapy.Field() up = scrapy.Field() comment_num = scrapy.Field()

23.416667

51

0.653025

73

562

4.972603

0.547945

0.333333

0.082645

0

0.002262

0.213523

562

23

52

24.434783

0.819005

0.362989

0

1

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false

0

0.083333

0

1

0

null

1

0

null

0

1

0

2

7926d5a00fb093db1e989099849d56be9ae1af2c

495

py

Python

python/interpret-core/interpret/visual/test/test_interactive.py

prateekiiest/interpret

b5530a587251a77516ab443037fc37f71708564c

[ "MIT" ]

2,674

2019-10-03T14:14:35.000Z

2022-03-31T13:40:49.000Z

python/interpret-core/interpret/visual/test/test_interactive.py

prateekiiest/interpret

b5530a587251a77516ab443037fc37f71708564c

[ "MIT" ]

257

2019-11-08T19:22:56.000Z

2022-03-29T20:09:07.000Z

python/interpret-core/interpret/visual/test/test_interactive.py

prateekiiest/interpret

b5530a587251a77516ab443037fc37f71708564c

[ "MIT" ]

367

2019-10-31T15:33:21.000Z

2022-03-31T13:40:50.000Z

# Copyright (c) 2019 Microsoft Corporation # Distributed under the MIT software license from ..interactive import set_visualize_provider, get_visualize_provider from ...provider import PreserveProvider def test_provider_properties(): provider = PreserveProvider() old_provider = get_visualize_provider() set_visualize_provider(provider) assert get_visualize_provider() == provider set_visualize_provider(old_provider) assert get_visualize_provider() == old_provider

29.117647

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0.148936

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null

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null

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2

7931b1b9e5431194d283b44e51c8b4121c3e6633

228

py

Python

d3rlpy/envs/__init__.py

ningyixue/AIPI530_Final_Project

b95353ffd003692a37a59042dfcd744a18b7e802

[ "MIT" ]

565

2020-08-01T02:44:28.000Z

2022-03-30T15:00:54.000Z

d3rlpy/envs/__init__.py

ningyixue/AIPI530_Final_Project

b95353ffd003692a37a59042dfcd744a18b7e802

[ "MIT" ]

144

2020-08-01T03:45:10.000Z

2022-03-30T14:51:16.000Z

d3rlpy/envs/__init__.py

ningyixue/AIPI530_Final_Project

b95353ffd003692a37a59042dfcd744a18b7e802

[ "MIT" ]

103

2020-08-26T13:27:34.000Z

2022-03-31T12:24:27.000Z

from .batch import AsyncBatchEnv, BatchEnv, SyncBatchEnv from .wrappers import Atari, ChannelFirst, Monitor __all__ = [ "BatchEnv", "SyncBatchEnv", "AsyncBatchEnv", "ChannelFirst", "Atari", "Monitor", ]

19

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0.2

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1

0

null

1

0

null

0

2

793298dd2e5b74126bb9798597b8237bba111ab9

354

py

Python

tests/assertions.py

Smosker/vcrpy

a56a0726d4f325f963696087d83c82b78e2a3464

[ "MIT" ]

2

2016-02-21T17:56:43.000Z

2018-06-10T21:15:32.000Z

tests/assertions.py

Smosker/vcrpy

a56a0726d4f325f963696087d83c82b78e2a3464

[ "MIT" ]

3

2018-07-08T11:07:17.000Z

2018-07-08T11:10:21.000Z

tests/assertions.py

Smosker/vcrpy

a56a0726d4f325f963696087d83c82b78e2a3464

[ "MIT" ]

3

2019-03-08T16:08:30.000Z

2019-07-11T18:57:33.000Z

import json def assert_cassette_empty(cass): assert len(cass) == 0 assert cass.play_count == 0 def assert_cassette_has_one_response(cass): assert len(cass) == 1 assert cass.play_count == 1 def assert_is_json(a_string): try: json.loads(a_string.decode('utf-8')) except Exception: assert False assert True

17.7

44

0.672316

52

354

4.346154

0.519231

0.119469

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0

0.018382

0.231638

354

19

45

18.631579

0.8125

0

0.014124

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1

0.230769

false

0

0.076923

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null

0

null

0

1

0

1

0

2

79345ef9e45ad9b25b5a4a6fddc5730eea2f5284

4,242

py

Python

platecurie/__init__.py

craigmillernz/PlateCurie

1e0f4fc4a9595e3d261c014d6cc5d7ccca944474

[ "MIT" ]

11

2019-10-16T13:29:32.000Z

2022-02-10T09:58:22.000Z

platecurie/__init__.py

craigmillernz/PlateCurie

1e0f4fc4a9595e3d261c014d6cc5d7ccca944474

[ "MIT" ]

4

2020-10-15T13:50:02.000Z

2021-09-22T22:08:07.000Z

platecurie/__init__.py

craigmillernz/PlateCurie

1e0f4fc4a9595e3d261c014d6cc5d7ccca944474

[ "MIT" ]

8

2020-06-12T04:42:48.000Z

2022-03-31T18:41:03.000Z

# Copyright 2019 Pascal Audet # # This file is part of PlateCurie. # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. """ PlateFlex is a software for estimating the effective elastic thickness of the lithosphere from the inversion of flexural isostatic response functions calculated from a wavelet analysis of gravity and topography data. Licence ------- Copyright 2019 Pascal Audet Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. Installation ------------ Dependencies ++++++++++++ The current version was developed using **Python3.7** \ Also, the following package is required: - `plateflex <https://github.com/paudetseis/PlateFlex>`_ See below for full installation details. Conda environment +++++++++++++++++ We recommend creating a custom ``conda`` environment where ``platecurie`` can be installed along with its dependencies. .. sourcecode:: bash conda create -n curie python=3.7 fortran-compiler numpy pymc3 matplotlib seaborn -c conda-forge Activate the newly created environment: .. sourcecode:: bash conda activate curie Install the required ``plateflex`` software (see `here <https://paudetseis.github.io/PlateFlex/getting_started.html#installing-from-source>`_) Installing from source ++++++++++++++++++++++ - Clone the repository: .. sourcecode:: bash git clone https://github.com/paudetseis/PlateCurie.git cd PlateCurie - Install using ``pip`` .. sourcecode:: bash pip install . """ # -*- coding: utf-8 -*- from . import estimate from . import plotting from .classes import MagGrid, ZtGrid, SigZtGrid, Project from plateflex.cpwt import conf_cpwt as cf_wt def set_conf_cpwt(k0=5.336): cf_wt.k0 = k0 set_conf_cpwt() def get_conf_cpwt(): """ Print global variable that controls the spatio-spectral resolution of the wavelet transform .. rubric:: Example >>> import platecurie >>> platecurie.get_conf_cpwt() Wavelet parameter used in platecurie.cpwt: ------------------------------------------ [Internal wavenumber] k0 (float): 5.336 """ print('\n'.join(( 'Wavelet parameter used in platecurie.cpwt:', '------------------------------------------', '[Internal wavenumber] k0 (float): {0:.3f}'.format(cf_wt.k0))))

32.883721

98

0.730552

584

4,242

5.280822

0.373288

0.057069

0.016861

0.015564

0.575227

0

0.008511

0.169024

4,242

128

99

33.140625

0.866383

0.869873

0

0.285714

0.088235

0

1

0.166667

false

0

0.333333

0

0.5

0.083333

0

null

0

1

0

null

0

1

0

2

f715181158ed97a842f823c3209fa5647bf6dec5

246

py

Python

lightning_plus/api_basebone/app/client_urls.py

twocucao/lightning-plus

e69c81da9c15fdfc37355e0362ff7ed804e94b2a

[ "MIT" ]

1

2021-04-15T14:52:12.000Z

lightning_plus/api_basebone/app/client_urls.py

twocucao/lightning

e69c81da9c15fdfc37355e0362ff7ed804e94b2a

[ "MIT" ]

null

lightning_plus/api_basebone/app/client_urls.py

twocucao/lightning

e69c81da9c15fdfc37355e0362ff7ed804e94b2a

[ "MIT" ]

null

from lightning_plus.api_basebone.drf.routers import SimpleRouter from .upload import views as upload_views router = SimpleRouter(custom_base_name="basebone-app") router.register("upload", upload_views.UploadViewSet) urlpatterns = router.urls

24.6

64

0.829268

32

246

6.1875

0.65625

0.111111

0

0.089431

246

9

65

27.333333

0.883929

0

0.073171

0

1

0

false

0

0.4

0

0.4

0

null

0

1

0

null

0

1

0

2

f71bdb90d7af4d9b66887e0eed93bbd899a25113

1,264

py

Python

tests/test_blog.py

Geerocktricks/Blogs4Keeps

5a91a1c9ec38ecc50b5831d526dd376463a56210

[ "MIT" ]

null

tests/test_blog.py

Geerocktricks/Blogs4Keeps

5a91a1c9ec38ecc50b5831d526dd376463a56210

[ "MIT" ]

null

tests/test_blog.py

Geerocktricks/Blogs4Keeps

5a91a1c9ec38ecc50b5831d526dd376463a56210

[ "MIT" ]

null

from app.models import Blog , User from app import db def setUp(self): self.user_Gerald = User(username = 'Gerald',password = 'potato', email = 'geerockface4@gmail.com') self.new_blog = Blog(id=12345,title='Full stack development',content='Is it safe to go the full-stack way or better the Android path',category= "technology" , date = 1-12-2019, time = 16:04 ,user = self.user_Gerald ) def tearDown(self): Blog.query.delete() User.query.delete() def test_check_instance_variables(self): self.assertEquals(self.new_blog.id,12345) self.assertEquals(self.new_blog.title,'Full stack development') self.assertEquals(self.new_blog.content,"Is it safe to go the full-stack way or better the Android path") self.assertEquals(self.new_blog.category,'technology') self.assertEquals(self.new_blog.date, 1-12-2019) self.assertEquals(self.new_blog. time,16:04) self.assertEquals(self.new_blog.user,self.user_Gerald) def test_save_blog(self): self.new_blog.save_blog() self.assertTrue(len(Review.query.all())>0) def test_get_blog_by_id(self): self.new_blog.save_review() got_blogs = Blog.get_blogs(12345) self.assertTrue(len(got_blogs) == 1)

40.774194

224

0.699367

188

1,264

4.558511

0.340426

0.08168

0.128355

0.187865

0.444574

0.130688

0

0.03861

0.18038

1,264

31

225

40.774194

0.78861

0

0.175494

0.017391

0

0.391304

0

null

0.043478

0.086957

null

0

null

0

1

0

null

0

1

0

2

f71edbd83661cc9f7d04a5509ea567a09ae80c46

1,163

py

Python

693.binary-number-with-alternating-bits.py

Lonitch/hackerRank

84991b8340e725422bc47eec664532cc84a3447e

[ "MIT" ]

null

693.binary-number-with-alternating-bits.py

Lonitch/hackerRank

84991b8340e725422bc47eec664532cc84a3447e

[ "MIT" ]

null

693.binary-number-with-alternating-bits.py

Lonitch/hackerRank

84991b8340e725422bc47eec664532cc84a3447e

[ "MIT" ]

null

# # @lc app=leetcode id=693 lang=python3 # # [693] Binary Number with Alternating Bits # # https://leetcode.com/problems/binary-number-with-alternating-bits/description/ # # algorithms # Easy (58.47%) # Likes: 359 # Dislikes: 74 # Total Accepted: 52.4K # Total Submissions: 89.1K # Testcase Example: '5' # # Given a positive integer, check whether it has alternating bits: namely, if # two adjacent bits will always have different values. # # Example 1: # # Input: 5 # Output: True # Explanation: # The binary representation of 5 is: 101 # # # # Example 2: # # Input: 7 # Output: False # Explanation: # The binary representation of 7 is: 111. # # # # Example 3: # # Input: 11 # Output: False # Explanation: # The binary representation of 11 is: 1011. # # # # Example 4: # # Input: 10 # Output: True # Explanation: # The binary representation of 10 is: 1010. # # # # @lc code=start class Solution: def hasAlternatingBits(self, n: int) -> bool: b = list(bin(n)[2:]) if len(b)<2: return True else: return b[0]!=b[1] and len(set(b[::2]))==1 and len(set(b[1::2]))==1 # @lc code=end

17.358209

80

0.625107

162

1,163

4.487654

0.561728

0.077029

0.110041

0.18707

0.371389

0.255846

0

0.069507

0.233018

1,163

66

81

17.621212

0.745516

0.693035

0

1

0.142857

false

0

0.571429

0

null

0

1

0

null

0

1

0

2

f731caeaa20126dfbac6f2f856ed43cf1d1b4fd9

3,511

py

Python

utest/api/test_exposed_api.py

rdagum/robotframework

b7069d505374e9f09a140ed5a9727d2a40716446

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

7,073

2015-01-01T17:19:16.000Z

2022-03-31T22:01:29.000Z

utest/api/test_exposed_api.py

imust6226/robotframework

08c56fef2ebc64d682c7f99acd77c480d8d0e028

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

2,412

2015-01-02T09:29:05.000Z

2022-03-31T13:10:46.000Z

utest/api/test_exposed_api.py

rticau/robotframework

33ee46dfacd5173c0a38d89c1a60abf6a747c8c0

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

2,298

2015-01-03T02:47:15.000Z

2022-03-31T02:00:16.000Z

import unittest from os.path import join from robot import api, model, parsing, reporting, result, running from robot.api import parsing as api_parsing from robot.utils.asserts import assert_equal, assert_true class TestExposedApi(unittest.TestCase): def test_execution_result(self): assert_equal(api.ExecutionResult, result.ExecutionResult) def test_test_suite(self): assert_equal(api.TestSuite, running.TestSuite) def test_result_writer(self): assert_equal(api.ResultWriter, reporting.ResultWriter) def test_visitors(self): assert_equal(api.SuiteVisitor, model.SuiteVisitor) assert_equal(api.ResultVisitor, result.ResultVisitor) def test_deprecated_parsing(self): assert_equal(api.get_model, parsing.get_model) assert_equal(api.get_resource_model, parsing.get_resource_model) assert_equal(api.get_tokens, parsing.get_tokens) assert_equal(api.get_resource_tokens, parsing.get_resource_tokens) assert_equal(api.Token, parsing.Token) def test_parsing_getters(self): assert_equal(api_parsing.get_model, parsing.get_model) assert_equal(api_parsing.get_resource_model, parsing.get_resource_model) assert_equal(api_parsing.get_tokens, parsing.get_tokens) assert_equal(api_parsing.get_resource_tokens, parsing.get_resource_tokens) def test_parsing_token(self): assert_equal(api_parsing.Token, parsing.Token) def test_parsing_model_statements(self): for cls in parsing.model.Statement._statement_handlers.values(): assert_equal(getattr(api_parsing, cls.__name__), cls) assert_true(not hasattr(api_parsing, 'Statement')) def test_parsing_model_blocks(self): for name in ('File', 'SettingSection', 'VariableSection', 'TestCaseSection', 'KeywordSection', 'CommentSection', 'TestCase', 'Keyword', 'For', 'If'): assert_equal(getattr(api_parsing, name), getattr(parsing.model, name)) assert_true(not hasattr(api_parsing, 'Block')) def test_parsing_visitors(self): assert_equal(api_parsing.ModelVisitor, parsing.ModelVisitor) assert_equal(api_parsing.ModelTransformer, parsing.ModelTransformer) class TestModelObjects(unittest.TestCase): """These model objects are part of the public API. They are only seldom needed directly and thus not exposed via the robot.api package. Tests just validate they are not removed accidentally. """ def test_running_objects(self): assert_true(running.TestSuite) assert_true(running.TestCase) assert_true(running.Keyword) def test_result_objects(self): assert_true(result.TestSuite) assert_true(result.TestCase) assert_true(result.Keyword) class TestTestSuiteBuilder(unittest.TestCase): # This list has paths like `/path/file.py/../file.robot` on purpose. # They don't work unless normalized. sources = [join(__file__, '../../../atest/testdata/misc', name) for name in ('pass_and_fail.robot', 'normal.robot')] def test_create_with_datasources_as_list(self): suite = api.TestSuiteBuilder().build(*self.sources) assert_equal(suite.name, 'Pass And Fail & Normal') def test_create_with_datasource_as_string(self): suite = api.TestSuiteBuilder().build(self.sources[0]) assert_equal(suite.name, 'Pass And Fail') if __name__ == '__main__': unittest.main()

37.351064

86

0.720308

432

3,511

5.571759

0.268519

0.10054

0.098878

0.059826

0.331533

0.262983

0.203573

0.107187

0.044038

0

0.00035

0.185417

3,511

93

87

37.752688

0.841259

0.082882

0

0.06625

0.00875

0

0.491803

1

0.229508

false

0.04918

0.081967

0

0.377049

0

null

0

null

0

1

0

1

0

2

f732e886bb6651ccc0f8d71e8ddd18c7c6dbccb9

266

py

Python

Workshop/Part3/part3_sol.py

ibenemerito88/openBF_workshop

a63a6fbd1ef8528890fb1072730124e054875008

[ "Zlib", "Apache-2.0" ]

null

Workshop/Part3/part3_sol.py

ibenemerito88/openBF_workshop

a63a6fbd1ef8528890fb1072730124e054875008

[ "Zlib", "Apache-2.0" ]

null

Workshop/Part3/part3_sol.py

ibenemerito88/openBF_workshop

a63a6fbd1ef8528890fb1072730124e054875008

[ "Zlib", "Apache-2.0" ]

null

import numpy as np import matplotlib.pyplot as plt from scipy import integrate import reslast plt.close("all") # Symmetric network q,a,p,u,c,n,s = reslast.resu("network") # Non-symmetric network qn,an,pn,un,cn,nn,sn = reslast.resu("networknonsym") plt.show()

14.777778

52

0.733083

45

266

4.333333

0.733333

0.164103

0

0.131579

266

18

53

14.777778

0.844156

0.146617

0

0.102222

0

1

0

true

0

0.5

0

0.5

0

null

0

null

0

1

0

1

0

2

f73f94c3158ed613dbc0d80b35b507f9509e5682

212

py

Python

submissions/contains-duplicate/solution.py

Wattyyy/LeetCode

13a9be056d0a0c38c2f8c8222b11dc02cb25a935

[ "MIT" ]

null

submissions/contains-duplicate/solution.py

Wattyyy/LeetCode

13a9be056d0a0c38c2f8c8222b11dc02cb25a935

[ "MIT" ]

1

2022-03-04T20:24:32.000Z

2022-03-04T20:31:58.000Z

submissions/contains-duplicate/solution.py

Wattyyy/LeetCode

13a9be056d0a0c38c2f8c8222b11dc02cb25a935

[ "MIT" ]

null

# https://leetcode.com/problems/contains-duplicate class Solution: def containsDuplicate(self, nums): hs = set() for num in nums: hs.add(num) return len(hs) != len(nums)

21.2

50

0.589623

26

212

4.807692

0.769231

0.096

0

0.287736

212

9

51

23.555556

0.827815

0.226415

0

1

0.166667

false

0

0.5

0

1

0

null

0

1

0

null

0

2

f7430bcfeacf7847fa8004d6e4bccb004f8b8467

164

py

Python

manage.py

guoxianru/goodsmovie

d9f3eab8578719a97b9f4328bc9083f1caeedb3d

[ "Apache-2.0" ]

4

2019-03-19T06:41:58.000Z

2020-10-18T07:24:08.000Z

manage.py

guoxianru/goodsmovie

d9f3eab8578719a97b9f4328bc9083f1caeedb3d

[ "Apache-2.0" ]

7

2020-12-16T02:18:59.000Z

2020-12-16T02:19:01.000Z

manage.py

guoxianru/goodsmovie

d9f3eab8578719a97b9f4328bc9083f1caeedb3d

[ "Apache-2.0" ]

2

2019-07-12T06:48:11.000Z

2019-12-04T03:14:40.000Z

# coding:utf8 # author：GXR from app import app from flask_script import Manager manage = Manager(app) if __name__ == '__main__': # app.run() manage.run()

14.909091

32

0.689024

23

164

4.521739

0.652174

0

0.007576

0.195122

164

10

33

16.4

0.780303

0.195122

0

0.0625

0

1

0

false

0

0.4

0

0.4

0

1

0

null

0

null

0

1

0

2

f74b0037b3b040cd8b224b0b2fbdf1df12cde31e

343

py

Python

minidump/streams/CommentStreamA.py

lucasg/minidump

18474e3221038abe866256e4e0eb255e33615110

[ "MIT" ]

1

2021-06-13T10:00:44.000Z

minidump/streams/CommentStreamA.py

lucasg/minidump

18474e3221038abe866256e4e0eb255e33615110

[ "MIT" ]

null

minidump/streams/CommentStreamA.py

lucasg/minidump

18474e3221038abe866256e4e0eb255e33615110

[ "MIT" ]

null

#!/usr/bin/env python3 # # Author: # Tamas Jos (@skelsec) # class CommentStreamA: def __init__(self): self.data = None @staticmethod def parse(dir, buff): csa = CommentStreamA() buff.seek(dir.Location.Rva) csa.data = buff.read(dir.Location.DataSize).decode() return csa def __str__(self): return 'CommentA: %s' % self.data

19.055556

54

0.685131

46

343

4.934783

0.652174

0.070485

0

0.003497

0.166181

343

18

55

19.055556

0.79021

0.148688

0

0.041667

0

1

0.272727

false

0

0.090909

0.545455

0

null

0

null

0

1

0

1

0

2

f74b6140204c5d56fa5f872e5e75c62e6ed3b64a

701

py

Python

database/models.py

christopherthompson81/fastapi_demo

be6f2486ce810c9574fafb506a153560d1cbcd5e

[ "MIT" ]

5

2019-07-15T21:19:47.000Z

2021-08-07T16:37:25.000Z

database/models.py

christopherthompson81/fastapi_demo

be6f2486ce810c9574fafb506a153560d1cbcd5e

[ "MIT" ]

null

database/models.py

christopherthompson81/fastapi_demo

be6f2486ce810c9574fafb506a153560d1cbcd5e

[ "MIT" ]

1

2019-08-29T02:51:38.000Z

''' FastAPI Demo SQLAlchemy ORM Models ''' # Standard Imports # PyPi Imports from sqlalchemy import ( Boolean, Column, Integer, String ) # Local Imports from database.setup import Base ############################################################################### class User(Base): '''ORM Models - users''' __tablename__ = "users" user_id = Column(Integer, primary_key=True, index=True) username = Column(String, unique=True) salted_password_hash = Column(String) first_name = Column(String) last_name = Column(String) email = Column(String, unique=True) active_boolean = Column(Boolean, nullable=False, default=True) admin_boolean = Column(Boolean, nullable=False, default=False)

21.90625

79

0.661912

79

701

5.721519

0.518987

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1

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f74cc5f2a65a80b8c188d0b2d860a923080ef38b

1,126

py

Python

tendytrader/numeric/get_finance.py

Volhacks-III-Supreme-Team/tendytrader

9b91dc82f43bcc0a06d8ca6d66e4d465c78575e9

[ "MIT" ]

null

tendytrader/numeric/get_finance.py

Volhacks-III-Supreme-Team/tendytrader

9b91dc82f43bcc0a06d8ca6d66e4d465c78575e9

[ "MIT" ]

2

2018-09-30T04:44:34.000Z

2018-10-03T17:51:08.000Z

tendytrader/numeric/get_finance.py

Volhacks-III-Supreme-Team/tendytrader

9b91dc82f43bcc0a06d8ca6d66e4d465c78575e9

[ "MIT" ]

null

import datetime import resource from pandas_datareader import data as pdr import fix_yahoo_finance as yf from tickers import test_tickers def get_all_stock_data(start, end, threads=(int)(resource.RLIMIT_NPROC*0.25)): assert isinstance(start, datetime.datetime), "Error: start time must be datetime object" assert isinstance(end, datetime.datetime), "Error: end time must be datetime object" yf.pdr_override() data = [] for t in test_tickers: data.append((t, pdr.get_data_yahoo(t, start=start, end=end, threads=threads))) return data def get_stock_data(tick, start, end, threads=(int)(resource.RLIMIT_NPROC*0.25)): assert isinstance(start, datetime.datetime), "Error: start time must be datetime object" assert isinstance(end, datetime.datetime), "Error: end time must be datetime object" yf.pdr_override() data = [] if type(tick) is str: data.append((tick, pdr.get_data_yahoo(tick, start=start, end=end, threads=threads))) else: for t in tick: data.append((t, pdr.get_data_yahoo(t, start=start, end=end, threads=threads))) return data

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1,126

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1,126

27

93

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null

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f74d889061c5de72d2336ef0d7d37a36e9e9ca47

1,676

py

Python

sentIA/utils/figure/__init__.py

thomas-brth/sentinel

747bd0b9a4a9356be69aae6d6ebbfa500e845218

[ "MIT" ]

null

sentIA/utils/figure/__init__.py

thomas-brth/sentinel

747bd0b9a4a9356be69aae6d6ebbfa500e845218

[ "MIT" ]

null

sentIA/utils/figure/__init__.py

thomas-brth/sentinel

747bd0b9a4a9356be69aae6d6ebbfa500e845218

[ "MIT" ]

null

# Plotting tools and utility functions # Nested GridSpec : https://matplotlib.org/stable/gallery/subplots_axes_and_figures/gridspec_nested.html#sphx-glr-gallery-subplots-axes-and-figures-gridspec-nested-py # GridSpec : https://matplotlib.org/stable/gallery/subplots_axes_and_figures/gridspec_multicolumn.html#sphx-glr-gallery-subplots-axes-and-figures-gridspec-multicolumn-py # colorbar : https://matplotlib.org/stable/gallery/subplots_axes_and_figures/colorbar_placement.html#sphx-glr-gallery-subplots-axes-and-figures-colorbar-placement-py ############# ## Imports ## ############# ## General imports ## from matplotlib import pyplot as plt from matplotlib import colors import numpy as np import os ############### ## Constants ## ############### ############# ## Classes ## ############# class MidpointNormalize(colors.Normalize): """ Useful object enbling to normalize colorbar with a chosen midpoint. """ def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False): super(MidpointNormalize, self).__init__(vmin, vmax, clip) self.midpoint = midpoint def __call__(self, value, clip=None): x, y = [self.vmin, self.midpoint, self.vmax], [0,0.5,1] return np.ma.masked_array(np.interp(value, x, y)) class FigBase(): """ """ CREDITS = "Credit : EU, contains modified Copernicus Sentinel data, processed with custom script." def __init__(self, title : str, dim : tuple): self.title = title self.fig = plt.figure(figsize=dim) def _format(self): pass def show(self): pass ############### ## Functions ## ############### def main(): pass if __name__ == '__main__': main() else: print(f"Module {__name__} imported.", flush=True)

27.032258

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1,676

62

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0

null

0

null

0

1

0

1

0

2

f74dcd7dd1b925a0a8000af109ee319c3b0e23c1

270

py

Python

stratascratch/Pandas-Solution/Ranking Most Active Guests.py

CAG9/SQL-Interview-Questions

79d0855a7cab28abd8b6462273aacaf38b5d8448

[ "MIT" ]

null

stratascratch/Pandas-Solution/Ranking Most Active Guests.py

CAG9/SQL-Interview-Questions

79d0855a7cab28abd8b6462273aacaf38b5d8448

[ "MIT" ]

null

stratascratch/Pandas-Solution/Ranking Most Active Guests.py

CAG9/SQL-Interview-Questions

79d0855a7cab28abd8b6462273aacaf38b5d8448

[ "MIT" ]

null

# Import your libraries import pandas as pd # Start writing code Grouped = airbnb_contacts.groupby('id_guest').sum().reset_index().sort_values(by=['n_messages'], ascending =False) Grouped['ranking'] = Grouped['n_messages'].rank(method='dense',ascending =False) Grouped

33.75

114

0.762963

37

270

5.405405

0.783784

0.09

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0.085185

270

7

115

38.571429

0.809717

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0.25

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