Reset23/the-stack-v2-filtered-python · Datasets at Hugging Face

c70783d8cfd93612801582b5e2235579428603b7

e9538b7ad6d0ce0ccfbb8e10c458f9e0b73926f6

/tests/unit/modules/network/fortios/test_fortios_log_gui_display.py

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[]

no_license

ansible-collection-migration/misc.not_a_real_collection

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refs/heads/master

2020-12-18T13:48:51.849567

2020-01-22T17:39:18

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# Copyright 2019 Fortinet, Inc. # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program 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 General Public License for more details. # # You should have received a copy of the GNU General Public License # along with Ansible. If not, see <https://www.gnu.org/licenses/>. # Make coding more python3-ish from __future__ import (absolute_import, division, print_function) __metaclass__ = type import os import json import pytest from mock import ANY from ansible_collections.misc.not_a_real_collection.plugins.module_utils.network.fortios.fortios import FortiOSHandler try: from ansible_collections.misc.not_a_real_collection.plugins.modules import fortios_log_gui_display except ImportError: pytest.skip("Could not load required modules for testing", allow_module_level=True) @pytest.fixture(autouse=True) def connection_mock(mocker): connection_class_mock = mocker.patch('ansible_collections.misc.not_a_real_collection.plugins.modules.fortios_log_gui_display.Connection') return connection_class_mock fos_instance = FortiOSHandler(connection_mock) def test_log_gui_display_creation(mocker): schema_method_mock = mocker.patch('ansible_collections.misc.not_a_real_collection.plugins.module_utils.network.fortios.fortios.FortiOSHandler.schema') set_method_result = {'status': 'success', 'http_method': 'POST', 'http_status': 200} set_method_mock = mocker.patch('ansible_collections.misc.not_a_real_collection.plugins.module_utils.network.fortios.fortios.FortiOSHandler.set', return_value=set_method_result) input_data = { 'username': 'admin', 'state': 'present', 'log_gui_display': { 'fortiview_unscanned_apps': 'enable', 'resolve_apps': 'enable', 'resolve_hosts': 'enable' }, 'vdom': 'root'} is_error, changed, response = fortios_log_gui_display.fortios_log(input_data, fos_instance) expected_data = { 'fortiview-unscanned-apps': 'enable', 'resolve-apps': 'enable', 'resolve-hosts': 'enable' } set_method_mock.assert_called_with('log', 'gui-display', data=expected_data, vdom='root') schema_method_mock.assert_not_called() assert not is_error assert changed assert response['status'] == 'success' assert response['http_status'] == 200 def test_log_gui_display_creation_fails(mocker): schema_method_mock = mocker.patch('ansible_collections.misc.not_a_real_collection.plugins.module_utils.network.fortios.fortios.FortiOSHandler.schema') set_method_result = {'status': 'error', 'http_method': 'POST', 'http_status': 500} set_method_mock = mocker.patch('ansible_collections.misc.not_a_real_collection.plugins.module_utils.network.fortios.fortios.FortiOSHandler.set', return_value=set_method_result) input_data = { 'username': 'admin', 'state': 'present', 'log_gui_display': { 'fortiview_unscanned_apps': 'enable', 'resolve_apps': 'enable', 'resolve_hosts': 'enable' }, 'vdom': 'root'} is_error, changed, response = fortios_log_gui_display.fortios_log(input_data, fos_instance) expected_data = { 'fortiview-unscanned-apps': 'enable', 'resolve-apps': 'enable', 'resolve-hosts': 'enable' } set_method_mock.assert_called_with('log', 'gui-display', data=expected_data, vdom='root') schema_method_mock.assert_not_called() assert is_error assert not changed assert response['status'] == 'error' assert response['http_status'] == 500 def test_log_gui_display_idempotent(mocker): schema_method_mock = mocker.patch('ansible_collections.misc.not_a_real_collection.plugins.module_utils.network.fortios.fortios.FortiOSHandler.schema') set_method_result = {'status': 'error', 'http_method': 'DELETE', 'http_status': 404} set_method_mock = mocker.patch('ansible_collections.misc.not_a_real_collection.plugins.module_utils.network.fortios.fortios.FortiOSHandler.set', return_value=set_method_result) input_data = { 'username': 'admin', 'state': 'present', 'log_gui_display': { 'fortiview_unscanned_apps': 'enable', 'resolve_apps': 'enable', 'resolve_hosts': 'enable' }, 'vdom': 'root'} is_error, changed, response = fortios_log_gui_display.fortios_log(input_data, fos_instance) expected_data = { 'fortiview-unscanned-apps': 'enable', 'resolve-apps': 'enable', 'resolve-hosts': 'enable' } set_method_mock.assert_called_with('log', 'gui-display', data=expected_data, vdom='root') schema_method_mock.assert_not_called() assert not is_error assert not changed assert response['status'] == 'error' assert response['http_status'] == 404 def test_log_gui_display_filter_foreign_attributes(mocker): schema_method_mock = mocker.patch('ansible_collections.misc.not_a_real_collection.plugins.module_utils.network.fortios.fortios.FortiOSHandler.schema') set_method_result = {'status': 'success', 'http_method': 'POST', 'http_status': 200} set_method_mock = mocker.patch('ansible_collections.misc.not_a_real_collection.plugins.module_utils.network.fortios.fortios.FortiOSHandler.set', return_value=set_method_result) input_data = { 'username': 'admin', 'state': 'present', 'log_gui_display': { 'random_attribute_not_valid': 'tag', 'fortiview_unscanned_apps': 'enable', 'resolve_apps': 'enable', 'resolve_hosts': 'enable' }, 'vdom': 'root'} is_error, changed, response = fortios_log_gui_display.fortios_log(input_data, fos_instance) expected_data = { 'fortiview-unscanned-apps': 'enable', 'resolve-apps': 'enable', 'resolve-hosts': 'enable' } set_method_mock.assert_called_with('log', 'gui-display', data=expected_data, vdom='root') schema_method_mock.assert_not_called() assert not is_error assert changed assert response['status'] == 'success' assert response['http_status'] == 200

[ "ansible_migration@example.com" ]

ansible_migration@example.com

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/eggs/Paste-1.7.5.1-py2.7.egg/paste/exceptions/reporter.py

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asmmhossain/phyG

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2014-02-14T12:33:08

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2013-10-23T11:04:25

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# (c) 2005 Ian Bicking and contributors; written for Paste (http://pythonpaste.org) # Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php from email.MIMEText import MIMEText from email.MIMEMultipart import MIMEMultipart import smtplib import time try: from socket import sslerror except ImportError: sslerror = None from paste.exceptions import formatter class Reporter(object): def __init__(self, **conf): for name, value in conf.items(): if not hasattr(self, name): raise TypeError( "The keyword argument %s was not expected" % name) setattr(self, name, value) self.check_params() def check_params(self): pass def format_date(self, exc_data): return time.strftime('%c', exc_data.date) def format_html(self, exc_data, **kw): return formatter.format_html(exc_data, **kw) def format_text(self, exc_data, **kw): return formatter.format_text(exc_data, **kw) class EmailReporter(Reporter): to_addresses = None from_address = None smtp_server = 'localhost' smtp_username = None smtp_password = None smtp_use_tls = False subject_prefix = '' def report(self, exc_data): msg = self.assemble_email(exc_data) server = smtplib.SMTP(self.smtp_server) if self.smtp_use_tls: server.ehlo() server.starttls() server.ehlo() if self.smtp_username and self.smtp_password: server.login(self.smtp_username, self.smtp_password) server.sendmail(self.from_address, self.to_addresses, msg.as_string()) try: server.quit() except sslerror: # sslerror is raised in tls connections on closing sometimes pass def check_params(self): if not self.to_addresses: raise ValueError("You must set to_addresses") if not self.from_address: raise ValueError("You must set from_address") if isinstance(self.to_addresses, (str, unicode)): self.to_addresses = [self.to_addresses] def assemble_email(self, exc_data): short_html_version = self.format_html( exc_data, show_hidden_frames=False) long_html_version = self.format_html( exc_data, show_hidden_frames=True) text_version = self.format_text( exc_data, show_hidden_frames=False) msg = MIMEMultipart() msg.set_type('multipart/alternative') msg.preamble = msg.epilogue = '' text_msg = MIMEText(text_version) text_msg.set_type('text/plain') text_msg.set_param('charset', 'ASCII') msg.attach(text_msg) html_msg = MIMEText(short_html_version) html_msg.set_type('text/html') # @@: Correct character set? html_msg.set_param('charset', 'UTF-8') html_long = MIMEText(long_html_version) html_long.set_type('text/html') html_long.set_param('charset', 'UTF-8') msg.attach(html_msg) msg.attach(html_long) subject = '%s: %s' % (exc_data.exception_type, formatter.truncate(str(exc_data.exception_value))) msg['Subject'] = self.subject_prefix + subject msg['From'] = self.from_address msg['To'] = ', '.join(self.to_addresses) return msg class LogReporter(Reporter): filename = None show_hidden_frames = True def check_params(self): assert self.filename is not None, ( "You must give a filename") def report(self, exc_data): text = self.format_text( exc_data, show_hidden_frames=self.show_hidden_frames) f = open(self.filename, 'a') try: f.write(text + '\n' + '-'*60 + '\n') finally: f.close() class FileReporter(Reporter): file = None show_hidden_frames = True def check_params(self): assert self.file is not None, ( "You must give a file object") def report(self, exc_data): text = self.format_text( exc_data, show_hidden_frames=self.show_hidden_frames) self.file.write(text + '\n' + '-'*60 + '\n') class WSGIAppReporter(Reporter): def __init__(self, exc_data): self.exc_data = exc_data def __call__(self, environ, start_response): start_response('500 Server Error', [('Content-type', 'text/html')]) return [formatter.format_html(self.exc_data)]

[ "mukarram819@gmail.com" ]

mukarram819@gmail.com

3c31d6df0e8e6f26f2bc2df7c1841a03cf228944

d9f7123433fe473cfa2fd5c3438251f83ffb326c

/apps/login/migrations/0001_initial.py

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[]

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mazurbeam/friends

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refs/heads/master

2021-01-01T18:27:12.875643

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# -*- coding: utf-8 -*- # Generated by Django 1.10 on 2017-07-25 17:42 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('f_name', models.CharField(max_length=400)), ('l_name', models.CharField(max_length=400)), ('email', models.CharField(max_length=400)), ('password', models.CharField(max_length=400)), ], ), ]

[ "mazurbeam@gmail.com" ]

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/ludwig/datasets/archives.py

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permissive

ludwig-ai/ludwig

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Python

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py

#! /usr/bin/env python # Copyright (c) 2019 Uber Technologies, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== import gzip import logging import os import shutil import tarfile from enum import Enum from typing import List, Optional from zipfile import ZipFile from ludwig.utils.fs_utils import upload_output_directory logger = logging.getLogger(__name__) class ArchiveType(str, Enum): """The type of file archive.""" UNKNOWN = "unknown" ZIP = "zip" GZIP = "gz" TAR = "tar" TAR_ZIP = "tar.z" TAR_BZ2 = "tar.bz2" TAR_GZ = "tar.gz" def infer_archive_type(archive_path): """Try to infer archive type from file extension.""" # Get the path extension including multiple extensions, ex. ".tar.gz" extension = ".".join(["", *os.path.basename(archive_path).split(".")[1:]]) extension = extension.lower() if extension.endswith(".tar.z") or extension.endswith(".tar.zip"): return ArchiveType.TAR_ZIP elif extension.endswith(".tar.bz2") or extension.endswith(".tbz2"): return ArchiveType.TAR_BZ2 elif extension.endswith(".tar.gz") or extension.endswith(".tgz"): return ArchiveType.TAR_GZ elif extension.endswith(".tar"): return ArchiveType.TAR elif extension.endswith(".zip") or extension.endswith(".zipx"): return ArchiveType.ZIP elif extension.endswith(".gz") or extension.endswith(".gzip"): return ArchiveType.GZIP else: return ArchiveType.UNKNOWN def is_archive(path): """Does this path a supported archive type.""" return infer_archive_type(path) != ArchiveType.UNKNOWN def list_archive(archive_path, archive_type: Optional[ArchiveType] = None) -> List[str]: """Return list of files extracted in an archive (without extracting them).""" if archive_type is None: archive_type = infer_archive_type(archive_path) if archive_type == ArchiveType.UNKNOWN: logger.error( f"Could not infer type of archive {archive_path}. May be an unsupported archive type." "Specify archive_type in the dataset config if this file has an unknown file extension." ) return [] if archive_type == ArchiveType.ZIP: with ZipFile(archive_path) as zfile: return zfile.namelist() elif archive_type == ArchiveType.GZIP: return [".".join(archive_path.split(".")[:-1])] # Path minus the .gz extension elif archive_type in {ArchiveType.TAR, ArchiveType.TAR_ZIP, ArchiveType.TAR_BZ2, ArchiveType.TAR_GZ}: with tarfile.open(archive_path) as tar_file: return tar_file.getnames() else: logger.error(f"Unsupported archive: {archive_path}") return [] def extract_archive(archive_path: str, archive_type: Optional[ArchiveType] = None) -> List[str]: """Extracts files from archive (into the same directory), returns a list of extracted files. Args: archive_path - The full path to the archive. Returns A list of the files extracted. """ if archive_type is None: archive_type = infer_archive_type(archive_path) if archive_type == ArchiveType.UNKNOWN: logger.error( f"Could not infer type of archive {archive_path}. May be an unsupported archive type." "Specify archive_type in the dataset config if this file has an unknown file extension." ) return [] archive_directory = os.path.dirname(archive_path) directory_contents_before = os.listdir(archive_directory) with upload_output_directory(archive_directory) as (tmpdir, _): if archive_type == ArchiveType.ZIP: with ZipFile(archive_path) as zfile: zfile.extractall(tmpdir) elif archive_type == ArchiveType.GZIP: gzip_content_file = ".".join(archive_path.split(".")[:-1]) # Path minus the .gz extension with gzip.open(archive_path) as gzfile: with open(os.path.join(tmpdir, gzip_content_file), "wb") as output: shutil.copyfileobj(gzfile, output) elif archive_type in {ArchiveType.TAR, ArchiveType.TAR_ZIP, ArchiveType.TAR_BZ2, ArchiveType.TAR_GZ}: with tarfile.open(archive_path) as tar_file: def is_within_directory(directory, target): abs_directory = os.path.abspath(directory) abs_target = os.path.abspath(target) prefix = os.path.commonprefix([abs_directory, abs_target]) return prefix == abs_directory def safe_extract(tar, path=".", members=None, *, numeric_owner=False): for member in tar.getmembers(): member_path = os.path.join(path, member.name) if not is_within_directory(path, member_path): raise Exception("Attempted Path Traversal in Tar File") tar.extractall(path, members, numeric_owner=numeric_owner) safe_extract(tar_file, path=tmpdir) else: logger.error(f"Unsupported archive: {archive_path}") directory_contents_after = set(os.listdir(archive_directory)) return directory_contents_after.difference(directory_contents_before)

[ "noreply@github.com" ]

ludwig-ai.noreply@github.com

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/myapps/error_handlers.py

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phares/mall

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refs/heads/master

2021-01-22T23:53:27.535609

2017-04-30T09:17:53

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py

from django.shortcuts import render def _403(request): return render(request, '403.html', {}) def _404(request): return render(request, '404.html', {}) def _500(request): return render(request, '500.html', {})

[ "cndeti@gmail.com" ]

cndeti@gmail.com

8ce8de29e51709461abbc005a1bb995b1642d349

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/viedeos_manager-New_code_with_resolve_issoe/imratedme/urls.py

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[]

no_license

sidkushwah123/video_manager

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2021-09-11T15:56:00

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"""imratedme URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.0/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.conf import settings from django.contrib import admin from django.urls import path,include from django.conf.urls.static import static urlpatterns = [ path('admin/', admin.site.urls), path('summernote/', include('django_summernote.urls')), path('', include('django.contrib.auth.urls')), path('', include(('home.urls','home'),namespace='home')), path('account/', include(('account.urls','account'),namespace='account')), path('video/', include(('videos.urls','videos'),namespace='videos')), path('profiles/', include(('profiles.urls','profiles'),namespace='profiles')), path('dashboard/', include(('my_videos.urls','my_videos'),namespace='my_videos')), path('videos-detail/', include(('videos_detail.urls','videos_detail'),namespace='videos_detail')), path('favourite-videos/', include(('favourite_videos.urls','favourite_videos'),namespace='favourite_videos')), path('search/', include(('search.urls','search'),namespace='search')), path('subscription/', include(('subscription.urls','subscription'),namespace='subscription')), ] + static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

[ "sachinkushwah0007@gmail.com" ]

sachinkushwah0007@gmail.com

615dc11cdddc204b7d4d84d3e3e6ffd4e4ab1827

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arm98sub/djangoDeploy

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Python

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# Generated by Django 3.1.6 on 2021-03-18 17:14 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('usuarios', '0001_initial'), ] operations = [ migrations.AlterField( model_name='usuario', name='foto', field=models.ImageField(blank=True, null=True, upload_to='perfiles', verbose_name='Foto de perfil'), ), ]

[ "vagrant@ubuntu1804.localdomain" ]

vagrant@ubuntu1804.localdomain

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no_license

janiszewskibartlomiej/Python_Code_Me_Gda

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2020-03-02T08:53:28

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py

liczba_str = input('Wpisz liczbę całkowią: ') liczba = int(liczba_str) liczba_podzielna_przez_2 = liczba % 2 liczba_podzielna_przez_3 = liczba % 3 liczba_podzielna_przez_4 = liczba % 4 liczba_podzielna_przez_5 = liczba % 5 liczba_podzielna_przez_6 = liczba % 6 liczba_podzielna_przez_9 = liczba % 9 liczba_podzielna_przez_10 = liczba % 10 if liczba_podzielna_przez_2 == 0: print('Liczba ', liczba,' jest podzielna przez 2') if liczba_podzielna_przez_3 == 0: print('Liczba ', liczba,' jest podzielna przez 3') if liczba_podzielna_przez_4 == 0: print('Liczba ', liczba,' jest podzielna przez 4') if liczba_podzielna_przez_5 == 0: print('Liczba ', liczba,' jest podzielna przez 5') if liczba_podzielna_przez_6 == 0: print('Liczba ', liczba,' jest podzielna przez 6') if liczba_podzielna_przez_9 == 0: print('Liczba ', liczba,' jest podzielna przez 9') if liczba_podzielna_przez_10 == 0: print('Liczba ', liczba,' jest podzielna przez 10')

[ "janiszewski.bartlomiej@gmail.com" ]

janiszewski.bartlomiej@gmail.com

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/random/solutions/q08_ThirdMaximumNumber.py

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[]

no_license

varunkumar032/lockdown-leetcode

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15a72a53be9005eca816f018cb1b244f2aa4cdfb

refs/heads/master

2023-06-30T08:31:54.323747

2021-07-12T11:29:59

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2021-05-06T10:24:48

2020-05-02T04:52:37

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UTF-8

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# Given integer array nums, return the third maximum number in this array. If the third maximum does not exist, return the maximum number. # Example 1: # Input: nums = [3,2,1] # Output: 1 # Explanation: The third maximum is 1. # Example 2: # Input: nums = [1,2] # Output: 2 # Explanation: The third maximum does not exist, so the maximum (2) is returned instead. # Example 3: # Input: nums = [2,2,3,1] # Output: 1 # Explanation: Note that the third maximum here means the third maximum distinct number. # Both numbers with value 2 are both considered as second maximum. def thirdMax(nums): firstMaxNum = secondMaxNum = thirdMaxNum = None for num in nums: if num == firstMaxNum or num == secondMaxNum or num == thirdMaxNum: continue if firstMaxNum is None or num > firstMaxNum: thirdMaxNum = secondMaxNum secondMaxNum = firstMaxNum firstMaxNum = num elif secondMaxNum is None or num > secondMaxNum: thirdMaxNum = secondMaxNum secondMaxNum = num elif thirdMaxNum is None or num > thirdMaxNum: thirdMaxNum = num return thirdMaxNum if thirdMaxNum is not None else firstMaxNum

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#!/usr/bin/python # -*- encoding: utf-8 -*- import sys sys.path.append("/home/yhl2/workspace/xtp_test//xtp/api") from xtp_test_case import * sys.path.append("/home/yhl2/workspace/xtp_test//service") from ServiceConfig import * from ARmainservice import * from QueryStkPriceQty import * from log import * sys.path.append("/home/yhl2/workspace/xtp_test//mysql") from CaseParmInsertMysql import * from SqlData_Transfer import * sys.path.append("/home/yhl2/workspace/xtp_test//utils") from QueryOrderErrorMsg import queryOrderErrorMsg from env_restart import * class YCHF_KCBYCHF_SHBP_288(xtp_test_case): def setUp(self): #sql_transfer = SqlData_Transfer() #sql_transfer.transfer_fund_asset('YCHF_KCBYCHF_SHBP_288') #clear_data_and_restart_all() #Api.trade.Logout() #Api.trade.Login() pass # def test_YCHF_KCBYCHF_SHBP_288(self): title = '重启数据库服务（沪A限价部撤卖出）' # 定义当前测试用例的期待值 # 期望状态：初始、未成交、部成、全成、部撤已报、部撤、已报待撤、已撤、废单、撤废、内部撤单 # xtp_ID和cancel_xtpID默认为0，不需要变动 case_goal = { '期望状态': '部撤', 'errorID': 0, 'errorMSG': queryOrderErrorMsg(0), '是否生成报单': '是', '是否是撤废': '否', # '是否是新股申购': '', 'xtp_ID': 0, 'cancel_xtpID': 0, } logger.warning(title) # 定义委托参数信息------------------------------------------ # 参数：证券代码、市场、证券类型、证券状态、交易状态、买卖方向（Ｂ买Ｓ卖）、期望状态、Api stkparm = QueryStkPriceQty('688000', '1', '4', '2', '0', 'S', case_goal['期望状态'], Api) # 如果下单参数获取失败，则用例失败 if stkparm['返回结果'] is False: rs = { '报单测试结果': stkparm['返回结果'], '测试错误原因': '获取下单参数失败,' + stkparm['错误原因'], } print(stkparm['错误原因']) self.assertEqual(rs['报单测试结果'], True) else: wt_reqs = { 'business_type': Api.const.XTP_BUSINESS_TYPE['XTP_BUSINESS_TYPE_CASH'], 'order_client_id':3, 'market': Api.const.XTP_MARKET_TYPE['XTP_MKT_SH_A'], 'ticker': stkparm['证券代码'], 'side': Api.const.XTP_SIDE_TYPE['XTP_SIDE_SELL'], 'price_type': Api.const.XTP_PRICE_TYPE['XTP_PRICE_LIMIT'], 'price': stkparm['随机中间价'], 'quantity': 300, 'position_effect':Api.const.XTP_POSITION_EFFECT_TYPE['XTP_POSITION_EFFECT_INIT'] } rs = serviceTest(Api, case_goal, wt_reqs) logger.warning('执行结果为' + str(rs['报单测试结果']) + ',' + str(rs['用例错误源']) + ',' + str(rs['用例错误原因'])) ## 还原可用资金 #sql_transfer = SqlData_Transfer() #sql_transfer.transfer_fund_asset('YW_KCB_BAK_000') #oms_restart() self.assertEqual(rs['报单测试结果'], True) # 211 if __name__ == '__main__': unittest.main()

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import requests import unittest class Test_login(unittest.TestCase): url = 'https://passport.womai.com/login/login.do' headers = {'Accept': 'application/json, text/javascript, */*', 'Accept-Encoding': 'gzip, deflate, br', 'Accept-Language': 'zh-CN,zh;q=0.9', 'Connection': 'keep-alive', 'Content-Length': '177', 'Content-Type': 'application/x-www-form-urlencoded', 'Host': 'passport.womai.com', 'Origin': 'https: // passport.womai.com', 'Referer': 'https: // passport.womai.com / redirect / redirect.do?mid = 0 & returnUrl = http % 3', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.26 Safari/537.36 Core/1.63.6756.400 QQBrowser/10.3.2473.400', 'X-Requested-With': 'XMLHttpRequest'} payload = {'serverPath': 'http://www.womai.com/', 'loginId': 'qiaoxu1123', 'password': 'haotest2018', 'validateCode': '', 'tempcode': '', 'mid': '0', 'returnUrl': 'http://www.womai.com/index-31000-0.htm'} def test_login(self): response = requests.post(self.url, headers=self.headers, data=self.payload) json_data = response.json() print(json_data) # 断言：测试结果与期望结果对比 self.assertEqual('2', json_data['msg']) if __name__ == '__main__': unittest.main()

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from jinja2 import FileSystemLoader, StrictUndefined from jinja2.environment import Environment from netmiko import ConnectHandler from mydevices import nxos1, nxos2 from pprint import pprint import textfsm import time import re from colorama import Fore, Back, Style env = Environment(undefined=StrictUndefined) env.loader = FileSystemLoader("./templates/") template_file = "question2.j2" interface = "1" nxos1_vars = { "device_name": "nxos1", "local_as": 22, "interface": interface, "ip_address": "10.1.100.1", "netmask": "24" } nxos2_vars = { "device_name": "nxos2", "local_as": 22, "interface": interface, "ip_address": "10.1.100.2", "netmask": "24" } nxos1_vars["peer_ip"] = nxos2_vars["ip_address"] nxos2_vars["peer_ip"] = nxos1_vars["ip_address"] # Add Jinja2 vars to be included in the Netmiko device dictionary nxos1["j2_vars"] = nxos1_vars nxos2["j2_vars"] = nxos2_vars template = env.get_template(template_file) def config(): for device in [nxos1,nxos2]: ### Pop the device dict 'j2_vars' to 'device_var', ### leaving 'device' with just the netmiko parameters device_var = device.pop('j2_vars') cfg = template.render(**device_var) Node = { "host": device['host'], "username": device['username'], "password": device['password'], "device_type": device['device_type'] } net_connect = ConnectHandler(**Node) print(f"Updating {device['host']} ".center(80, "#")) output = net_connect.send_config_set(cfg) print('Completed' + '\n') def verify(): for device in [nxos1,nxos2]: Node = { "host": device['host'], "username": device['username'], "password": device['password'], "device_type": device['device_type'] } net_connect = ConnectHandler(**Node) raw_text_data = net_connect.send_command('show ip bgp sum') net_connect.disconnect() textfsm_file = "templates/question3.template" textfsm_template = open(textfsm_file) # with open("show_ip_bgp_sum.txt") as f: # raw_text_data = f.read() # The argument 'template' is a file handle and 'raw_text_data' is a string. re_table = textfsm.TextFSM(textfsm_template) bgp_status = re_table.ParseText(raw_text_data)[0][0] bgp_state = re_table.ParseText(raw_text_data)[0][1] textfsm_template.close() ### Regular expressions to match the bgp variables above regex_status = re.compile(r'[0-9]{1,2}:[0-9]{1,2}:[0-9]{1,2}') regex_state = re.compile(r'\d+') if regex_status.match(bgp_status) and regex_state.match(bgp_state): ''' These two conditions are to match - Whether or not there is an time counter - Whether or not the bgp state is a number, and NOT a building bgp state ''' print(f"BGP has been established on: {device['host']}") else: print(f"The current BGP State of {device['host']} is: {bgp_state}. Please review") def run(): config() time.sleep(15) verify() if __name__ == "__main__": run()

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from config import ServerConfig from question_generator import QuestionGenerator from server import Server c = ServerConfig() qg = QuestionGenerator(c.QuestionFilepath) qg.PrintAll() s = Server(c, qg) s.Run()

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''' ================================= 3D surface with polar coordinates ================================= Demonstrates plotting a surface defined in polar coordinates. Uses the reversed version of the YlGnBu color map. Also demonstrates writing axis labels with latex math mode. Example contributed by Armin Moser. ''' # This import registers the 3D projection, but is otherwise unused. from mpl_toolkits.mplot3d import Axes3D # noqa: F401 unused import import matplotlib.pyplot as plt import numpy as np fig = plt.figure() ax = fig.add_subplot(111, projection='3d') # Create the mesh in polar coordinates and compute corresponding Z. r = np.linspace(0, 1.25, 50) p = np.linspace(0, 2*np.pi, 50) R, P = np.meshgrid(r, p) Z = ((R**2 - 1)**2) # Express the mesh in the cartesian system. X, Y = R*np.cos(P), R*np.sin(P) # Plot the surface. ax.plot_surface(X, Y, Z, cmap=plt.cm.YlGnBu_r) # Tweak the limits and add latex math labels. ax.set_zlim(0, 1) ax.set_xlabel(r'$\phi_\mathrm{real}$') ax.set_ylabel(r'$\phi_\mathrm{im}$') ax.set_zlabel(r'$V(\phi)$') plt.show()

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# -*- coding: utf-8 -*- # !/usr/bin/env python from setuptools import setup, find_packages setup( name='wechat-sdk', version='0.5.2', keywords=('wechat', 'sdk', 'wechat sdk'), description=u'微信公众平台Python开发包', long_description=open("README.rst").read(), license='BSD License', url='https://github.com/doraemonext/wechat-python-sdk', author='doraemonext', author_email='doraemonext@gmail.com', packages=find_packages(), include_package_data=True, platforms='any', install_requires=open("requirements.txt").readlines(), )

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lxtxl/aws_cli

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#!/usr/bin/python # -*- codding: utf-8 -*- import os import sys sys.path.append(os.path.dirname(os.path.abspath(os.path.dirname(__file__)))) from common.execute_command import write_three_parameter # url : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/backup/put-backup-vault-notifications.html if __name__ == '__main__': """ delete-backup-vault-notifications : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/backup/delete-backup-vault-notifications.html get-backup-vault-notifications : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/backup/get-backup-vault-notifications.html """ parameter_display_string = """ # backup-vault-name : The name of a logical container where backups are stored. Backup vaults are identified by names that are unique to the account used to create them and the AWS Region where they are created. They consist of lowercase letters, numbers, and hyphens. # sns-topic-arn : The Amazon Resource Name (ARN) that specifies the topic for a backup vaultâs events; for example, arn:aws:sns:us-west-2:111122223333:MyVaultTopic . # backup-vault-events : An array of events that indicate the status of jobs to back up resources to the backup vault. (string) """ add_option_dict = {} add_option_dict["parameter_display_string"] = parameter_display_string # ex: add_option_dict["no_value_parameter_list"] = "--single-parameter" write_three_parameter("backup", "put-backup-vault-notifications", "backup-vault-name", "sns-topic-arn", "backup-vault-events", add_option_dict)

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#!/usr/bin/env python3 # integrate ax from 0 to 3 with a = 5 # using scipy.integrate.quad # intgrand = 5x # limit = 0 to 3 # ans = 5x**2/2 = 2.5 x**2 from scipy import integrate import numpy as np a = 5 # lambda method fun = lambda a,x: a*x # function method def fun(a,x): return a*x y = integrate.quad(fun, 0, 3, args=(a)) print(y) y2 = 2.5 * (3**2 - 0**2) print(y2)

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from time import time from jiayq.utils import mpiutils def hms(t,template='{}h {}m {:.2f}s'): ''' format the time value to "xxh xxm xxs" ''' # not implemented hour = int(t / 3600.0) t = t % 3600.0 minute = int (t / 60) t = t % 60 return template.format(hour,minute,t) class Timer: ''' class Timer implements some sugar functions that works like a stopwatch. Timer.reset() resets the watch Timer.lap() returns the time elapsed since the last lap() call Timer.total() returns the total time elapsed since the last reset ''' def __init__(self): # t is the total time # l is the lap time self.t = time() self.l = time() def reset(self): self.t = time() self.l = time() def lap(self): diff = time() - self.l self.l = time() return diff def total(self): return time() - self.t class LoopReporter: ''' class LoopReporter implements some sugar functions that reports the stats of a loop that Yangqing usually needs. ''' def __init__(self, step = 100, header = '', rootOnly = False): self.timer = Timer() self.header = header self.step = step self.rootOnly = rootOnly def reset(self): self.timer.reset() def report(self,processed,total): if processed % self.step != 0: return elapsed = self.timer.total() if processed == 0: eta = 0.0 else: eta = elapsed * (total - processed) / processed if self.rootOnly: mpiutils.rootprint('{} {}/{}, elapsed {}, eta {}.'.format(self.header, processed, total, hms(elapsed), hms(eta))) else: mpiutils.nodeprint('{} {}/{}, elapsed {}, eta {}.'.format(self.header, processed, total, hms(elapsed), hms(eta)))

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""" Django settings for demonstration Intended to be used with ``make run``. """ from sandbox.settings.base import * # noqa: F403 DEBUG = True TEMPLATES[0]['OPTIONS']['debug'] = DEBUG # noqa: F405 DATABASES = { "default": { "ENGINE": "django.db.backends.sqlite3", "NAME": VAR_PATH / "db" / "db.sqlite3", # noqa: F405 } } # Import local settings if any try: from .local import * # noqa: F401,F403 except ImportError: pass

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# -*- coding: utf-8 -*- import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Changing field 'Item.title' db.alter_column('feedmanager_item', 'title', self.gf('django.db.models.fields.TextField')()) def backwards(self, orm): # Changing field 'Item.title' db.alter_column('feedmanager_item', 'title', self.gf('django.db.models.fields.CharField')(max_length=70)) models = { 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'feedmanager.feed': { 'Meta': {'object_name': 'Feed'}, 'added': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'hash': ('django.db.models.fields.CharField', [], {'max_length': '32'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'last_checked': ('django.db.models.fields.DateTimeField', [], {'null': 'True', 'blank': 'True'}), 'last_updated': ('django.db.models.fields.DateTimeField', [], {'null': 'True', 'blank': 'True'}), 'title': ('django.db.models.fields.TextField', [], {}), 'url': ('django.db.models.fields.TextField', [], {}), 'users': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.User']", 'symmetrical': 'False'}) }, 'feedmanager.item': { 'Meta': {'object_name': 'Item'}, 'added': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {}), 'feed': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['feedmanager.Feed']"}), 'guid': ('django.db.models.fields.TextField', [], {}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'link': ('django.db.models.fields.TextField', [], {}), 'pubdate': ('django.db.models.fields.DateTimeField', [], {}), 'title': ('django.db.models.fields.TextField', [], {}) } } complete_apps = ['feedmanager']

[ "isaac@bythewood.me" ]

isaac@bythewood.me

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/flashsale/pay/migrations/0004_create_brand_and_brand_product_add_amount_flow_outer_id.py

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[]

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nidepuzi/ndpuzsys

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2023-01-06T22:52:49.861479

2019-07-09T11:00:06

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2022-12-26T20:15:24

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models import jsonfield.fields class Migration(migrations.Migration): dependencies = [ ('pay', '0003_auto_20160425_1212'), ] operations = [ migrations.CreateModel( name='BrandEntry', fields=[ ('created', models.DateTimeField(auto_now_add=True, verbose_name='\u521b\u5efa\u65e5\u671f', db_index=True)), ('modified', models.DateTimeField(auto_now=True, verbose_name='\u4fee\u6539\u65e5\u671f', db_index=True)), ('id', models.AutoField(serialize=False, primary_key=True)), ('brand_name', models.CharField(db_index=True, max_length=32, verbose_name='\u54c1\u724c\u540d\u79f0', blank=True)), ('brand_desc', models.TextField(max_length=512, verbose_name='\u54c1\u724c\u6d3b\u52a8\u63cf\u8ff0', blank=True)), ('brand_pic', models.CharField(max_length=256, verbose_name='\u54c1\u724c\u56fe\u7247', blank=True)), ('brand_post', models.CharField(max_length=256, verbose_name='\u54c1\u724c\u6d77\u62a5', blank=True)), ('brand_applink', models.CharField(max_length=256, verbose_name='\u54c1\u724cAPP\u534f\u8bae\u94fe\u63a5', blank=True)), ('start_time', models.DateTimeField(db_index=True, null=True, verbose_name='\u5f00\u59cb\u65f6\u95f4', blank=True)), ('end_time', models.DateTimeField(null=True, verbose_name='\u7ed3\u675f\u65f6\u95f4', blank=True)), ('order_val', models.IntegerField(default=0, verbose_name='\u6392\u5e8f\u503c')), ('is_active', models.BooleanField(default=True, verbose_name='\u4e0a\u7ebf')), ], options={ 'db_table': 'flashsale_brand_entry', 'verbose_name': '\u7279\u5356/\u54c1\u724c\u63a8\u5e7f\u5165\u53e3', 'verbose_name_plural': '\u7279\u5356/\u54c1\u724c\u63a8\u5e7f\u5165\u53e3', }, ), migrations.CreateModel( name='BrandProduct', fields=[ ('created', models.DateTimeField(auto_now_add=True, verbose_name='\u521b\u5efa\u65e5\u671f', db_index=True)), ('modified', models.DateTimeField(auto_now=True, verbose_name='\u4fee\u6539\u65e5\u671f', db_index=True)), ('id', models.AutoField(serialize=False, primary_key=True)), ('brand_name', models.CharField(db_index=True, max_length=32, verbose_name='\u54c1\u724c\u540d\u79f0', blank=True)), ('product_id', models.BigIntegerField(default=0, verbose_name='\u5546\u54c1id', db_index=True)), ('product_name', models.CharField(max_length=64, verbose_name='\u5546\u54c1\u540d\u79f0', blank=True)), ('product_img', models.CharField(max_length=256, verbose_name='\u5546\u54c1\u56fe\u7247', blank=True)), ('start_time', models.DateTimeField(db_index=True, null=True, verbose_name='\u5f00\u59cb\u65f6\u95f4', blank=True)), ('end_time', models.DateTimeField(null=True, verbose_name='\u7ed3\u675f\u65f6\u95f4', blank=True)), ('brand', models.ForeignKey(related_name='brand_products', verbose_name='\u54c1\u724c\u7f16\u53f7id', to='pay.BrandEntry')), ], options={ 'db_table': 'flashsale_brand_product', 'verbose_name': '\u7279\u5356/\u54c1\u724c\u5546\u54c1', 'verbose_name_plural': '\u7279\u5356/\u54c1\u724c\u5546\u54c1', }, ), migrations.AddField( model_name='salerefund', name='amount_flow', field=jsonfield.fields.JSONField(default=b'{"desc":""}', max_length=512, verbose_name='\u9000\u6b3e\u53bb\u5411', blank=True), ), migrations.AlterField( model_name='saleorder', name='outer_id', field=models.CharField(max_length=32, verbose_name='\u5546\u54c1\u5916\u90e8\u7f16\u7801', blank=True), ), migrations.AlterField( model_name='saleorder', name='outer_sku_id', field=models.CharField(max_length=32, verbose_name='\u89c4\u683c\u5916\u90e8\u7f16\u7801', blank=True), ), ]

[ "xiuqing.mei@xiaolu.so" ]

xiuqing.mei@xiaolu.so

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/tests/test_utils/reference_implementation_helper.py

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permissive

xadupre/sklearn-onnx

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refs/heads/master

2023-09-01T15:58:38.112315

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2023-01-04T13:41:33

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# SPDX-License-Identifier: Apache-2.0 import numpy as np def ErfInv(x): sgn = -1. if x < 0 else 1. x = (1. - x) * (1 + x) log = np.log(x) v = 2. / (3.14159 * 0.147) + 0.5 * log v2 = 1. / 0.147 * log v3 = -v + np.sqrt(v * v - v2) x = sgn * np.sqrt(v3) return x def ComputeLogistic(val): v = 1. / (1. + np.exp(-np.abs(val))) return (1. - v) if val < 0 else v def ComputeProbit(val): return 1.41421356 * ErfInv(val * 2 - 1) def ComputeSoftmax(values): v_max = values.max() values[:] = np.exp(values - v_max) this_sum = values.sum() values /= this_sum return values def ComputeSoftmaxZero(values): v_max = values.max() exp_neg_v_max = np.exp(-v_max) s = 0 for i in range(len(values)): v = values[i] if v > 0.0000001 or v < -0.0000001: values[i] = np.exp(v - v_max) s += values[i] else: values[i] *= exp_neg_v_max values[i] /= s return values def sigmoid_probability(score, proba, probb): # ref: https://github.com/arnaudsj/libsvm/blob/ # eaaefac5ebd32d0e07902e1ae740e038eaaf0826/svm.cpp#L1818 val = score * proba + probb return 1 - ComputeLogistic(val) def multiclass_probability(k, R): max_iter = max(100, k) Q = np.empty((k, k), dtype=R.dtype) Qp = np.empty((k, ), dtype=R.dtype) P = np.empty((k, ), dtype=R.dtype) eps = 0.005 / k for t in range(0, k): P[t] = 1.0 / k Q[t, t] = 0 for j in range(t): Q[t, t] += R[j, t] * R[j, t] Q[t, j] = Q[j, t] for j in range(t + 1, k): Q[t, t] += R[j, t] * R[j, t] Q[t, j] = -R[j, t] * R[t, j] for it in range(max_iter): # stopping condition, recalculate QP,pQP for numerical accuracy pQp = 0 for t in range(0, k): Qp[t] = 0 for j in range(k): Qp[t] += Q[t, j] * P[j] pQp += P[t] * Qp[t] max_error = 0 for t in range(0, k): error = np.abs(Qp[t] - pQp) if error > max_error: max_error = error if max_error < eps: break for t in range(k): diff = (-Qp[t] + pQp) / Q[t, t] P[t] += diff pQp = ((pQp + diff * (diff * Q[t, t] + 2 * Qp[t])) / (1 + diff) ** 2) for j in range(k): Qp[j] = (Qp[j] + diff * Q[t, j]) / (1 + diff) P[j] /= (1 + diff) return P def write_scores(n_classes, scores, post_transform, add_second_class): if n_classes >= 2: if post_transform == "PROBIT": res = [] for score in scores: res.append(ComputeProbit(score)) return np.array(res, dtype=scores.dtype) if post_transform == "LOGISTIC": res = [] for score in scores: res.append(ComputeLogistic(score)) return np.array(res, dtype=scores.dtype) if post_transform == "SOFTMAX": return ComputeSoftmax(scores) if post_transform == "SOFTMAX_ZERO": return ComputeSoftmaxZero(scores) return scores if n_classes == 1: if post_transform == "PROBIT": return np.array([ComputeProbit(scores[0])], dtype=scores.dtype) if add_second_class == 0: res = np.array([1 - scores[0], scores[0]], dtype=scores.dtype) elif add_second_class == 1: res = np.array([1 - scores[0], scores[0]], dtype=scores.dtype) elif add_second_class in (2, 3): if post_transform == "LOGISTIC": return np.array([ComputeLogistic(-scores[0]), ComputeLogistic(scores[0])], dtype=scores.dtype) return np.array([-scores[0], scores[0]], dtype=scores.dtype) return np.array([scores[0]], dtype=scores.dtype) raise NotImplementedError(f"n_classes={n_classes} not supported.") def set_score_svm(max_weight, maxclass, n, post_transform, has_proba, weights_are_all_positive_, classlabels, posclass, negclass): write_additional_scores = -1 if len(classlabels) == 2: write_additional_scores = 2 if post_transform == "NONE" else 0 if not has_proba: if weights_are_all_positive_ and max_weight >= 0.5: return classlabels[1], write_additional_scores if max_weight > 0 and not weights_are_all_positive_: return classlabels[1], write_additional_scores return classlabels[maxclass], write_additional_scores if max_weight > 0: return posclass, write_additional_scores return negclass, write_additional_scores

[ "noreply@github.com" ]

xadupre.noreply@github.com

c9186add6d0c25f076889a28cd4e487475439e09

f3bd271bf00325881fb5b2533b9ef7f7448a75ec

/xcp2k/classes/_com1.py

c9f4959959fa47cab33563e9c613b6405be5674a

[]

no_license

obaica/xcp2k

7f99fc9d494859e16b9b0ea8e217b0493f4b2f59

6e15c2c95658f545102595dc1783f5e03a9e6916

refs/heads/master

2020-07-15T17:27:43.378835

2019-02-11T16:32:24

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UTF-8

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py

from xcp2k.inputsection import InputSection from _each74 import _each74 class _com1(InputSection): def __init__(self): InputSection.__init__(self) self.Section_parameters = None self.Add_last = None self.Common_iteration_levels = None self.Filename = None self.Log_print_key = None self.EACH = _each74() self._name = "COM" self._keywords = {'Common_iteration_levels': 'COMMON_ITERATION_LEVELS', 'Log_print_key': 'LOG_PRINT_KEY', 'Add_last': 'ADD_LAST', 'Filename': 'FILENAME'} self._subsections = {'EACH': 'EACH'} self._attributes = ['Section_parameters']

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

1c850d20f46c8bacea3e2001b3b00d03e4f2e38e

5d1c43bb4881039f198eedcee2ceb101b406e0a0

/Django/myvenv/Scripts/rst2man.py

52894792e98bd74e7fc0f83fd5849d6aff9320c2

[]

no_license

MunSeoHee/Likelion_Gachon_2020

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e0e48845fdb0e4aa2365e7c47e29880a27f0f261

refs/heads/master

2021-04-10T09:51:06.618980

2020-12-07T10:06:43

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#!c:\users\munseohee\desktop\likelion_gachon_2020\django\myvenv\scripts\python.exe # Author: # Contact: grubert@users.sf.net # Copyright: This module has been placed in the public domain. """ man.py ====== This module provides a simple command line interface that uses the man page writer to output from ReStructuredText source. """ import locale try: locale.setlocale(locale.LC_ALL, '') except: pass from docutils.core import publish_cmdline, default_description from docutils.writers import manpage description = ("Generates plain unix manual documents. " + default_description) publish_cmdline(writer=manpage.Writer(), description=description)

[ "nansh9815@naver.com" ]

nansh9815@naver.com

8f06941c60c03810aab9bda1e07ab6e226fdb88d

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/mall/utils/token_jwt.py

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[]

no_license

py-king/ready

6ddc7e8b830742bcdeb696791ec49ad9d30f2296

e352aa335b07f6852f4c99e7fbd030f2eb8f16da

refs/heads/master

2022-12-09T13:31:38.199448

2019-01-24T02:13:35

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0

null

2022-12-08T02:29:02

2019-01-24T01:52:28

HTML

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#!/usr/bin/python # -*- coding: UTF-8 -*- # author:caozy time:19-1-10 from rest_framework_jwt.settings import api_settings def token_jwt(user): jwt_payload_handler = api_settings.JWT_PAYLOAD_HANDLER jwt_encode_handler = api_settings.JWT_ENCODE_HANDLER payload = jwt_payload_handler(user) token = jwt_encode_handler(payload) return token

[ "xwp_fullstack@163.com" ]

xwp_fullstack@163.com

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/PythonWebBasics_Django/Django_Web_Basics/manage.py

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[]

no_license

Ivaylo-Atanasov93/The-Learning-Process

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refs/heads/master

2023-03-30T20:59:34.304207

2021-03-29T15:23:05

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#!/usr/bin/env python """Django's command-line utility for administrative tasks.""" import os import sys def main(): """Run administrative tasks.""" os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'Django_Web_Basics.settings') try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv) if __name__ == '__main__': main()

[ "ivailo.atanasov93@gmail.com" ]

ivailo.atanasov93@gmail.com

ee216ef4dc793f6328f24c7d46838a6ff173f7bf

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/backend/mobile_build_a_dev_16819/urls.py

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[]

no_license

crowdbotics-apps/mobile-build-a-dev-16819

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refs/heads/master

2023-02-07T10:56:17.932363

2020-12-16T14:17:06

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"""mobile_build_a_dev_16819 URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.2/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path, include from allauth.account.views import confirm_email from rest_framework import permissions from drf_yasg.views import get_schema_view from drf_yasg import openapi urlpatterns = [ path("", include("home.urls")), path("accounts/", include("allauth.urls")), path("api/v1/", include("home.api.v1.urls")), path("admin/", admin.site.urls), path("users/", include("users.urls", namespace="users")), path("rest-auth/", include("rest_auth.urls")), # Override email confirm to use allauth's HTML view instead of rest_auth's API view path("rest-auth/registration/account-confirm-email/<str:key>/", confirm_email), path("rest-auth/registration/", include("rest_auth.registration.urls")), ] admin.site.site_header = "mobile build A" admin.site.site_title = "mobile build A Admin Portal" admin.site.index_title = "mobile build A Admin" # swagger api_info = openapi.Info( title="mobile build A API", default_version="v1", description="API documentation for mobile build A App", ) schema_view = get_schema_view( api_info, public=True, permission_classes=(permissions.IsAuthenticated,), ) urlpatterns += [ path("api-docs/", schema_view.with_ui("swagger", cache_timeout=0), name="api_docs") ]

[ "team@crowdbotics.com" ]

team@crowdbotics.com

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/privacy/migrations/0038_auto_20200602_1034.py

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[]

no_license

murengera/eshoping-api

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90acb0f8db519a38a1bd0976bd1f704f6d02f2dd

refs/heads/master

2022-12-25T10:19:39.431427

2020-09-26T12:35:38

286,399,741

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py

# Generated by Django 3.0 on 2020-06-02 08:34 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('privacy', '0037_auto_20200602_1031'), ] operations = [ migrations.AlterField( model_name='privacypoliciesandtermsofuse', name='language', field=models.CharField(choices=[('rwandese', 'rwandese'), ('english', 'english')], max_length=30), ), ]

[ "daltonbigirimana5@gmail.com" ]

daltonbigirimana5@gmail.com

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/bot/event.py

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[ "MIT" ]

permissive

RxJellyBot/Jelly-Bot

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py

""" Events for the bot to trigger after certain conditions are met. Methods prefixed with ``signal_`` should be called when the certain event occurs. Methods prefixed with ``on_`` will be executed on all of the events specified occur. """ from django.conf import settings from JellyBot.systemconfig import System from bot.user import perform_existence_check from bot.system import record_boot_dt from extutils.ddns import activate_ddns_update from msghandle import HandlingFunctionBox __all__ = ["signal_discord_ready", "signal_django_ready"] _ready = { "Discord": False, "Django": False } def signal_django_ready(): """Signal that Django application is ready.""" _ready["Discord"] = True _check_all_ready() def signal_discord_ready(): """Signal that called when the Discord bot is ready.""" _ready["Django"] = True _check_all_ready() def _check_all_ready(): if all(_ready.values()): on_system_fully_ready() def on_system_fully_ready(): """Code to execute when the system is fully prepared (Discord bot and Django application ready).""" HandlingFunctionBox.load() record_boot_dt() if settings.PRODUCTION: perform_existence_check(set_name_to_cache=True) activate_ddns_update(System.DDNSUpdateIntervalSeconds)

[ "raenonx0710@gmail.com" ]

raenonx0710@gmail.com

e1c6b71f6753abc16634e2ceac2ea85cb7d57daf

5754e080348df0fc7f1fffe46c6909edf681ee79

/branch/dome2-12.py

463148dadbe21d3912ba1bb5f43a3507a8d00409

[]

no_license

biao111/learn_python

57e373d62979096b94b9ea96664dec3b7d88dfce

609a6a9634a37ecd1c59fa639fcca1eaa6472bfd

refs/heads/master

2023-01-05T23:15:39.670105

2020-11-08T05:23:57

310,991,572

0

null

UTF-8

Python

false

370

py

#定义变量year，并接收“请输入正确的年份：” year = input("请输入正确的年份") #判断是否是闰年：1、能被4整除,但是不能被100整除的年份 2、能被400整除的年份 if int(year) / 4 and not int(year) / 100 and int(year) / 400: print("{0}年是闰年".format(year)) else: print("{0}年不是闰年".format(year))

[ "18211149974@163.com" ]

18211149974@163.com

332fdd820f0bc7ff950fcaeb827614a42af1283e

6e932aa6ec9424ae0238c559112fdd0214c52be6

/ffawp/ch03/6_excel_value_match_pattern.py

d1e792c640076832617e29f290e915655527f22c

[]

no_license

LingChenBill/python_first_introduce

d1c780dcd3653ef4cda39cc4a0c631a99071f088

32ff4a16fe10505fcb49e4762fc573f5f1c62167

refs/heads/master

2020-07-29T13:03:15.447728

2020-06-09T13:39:07

209,813,590

0

null

UTF-8

Python

false

1,922

py

# Date:2020/5/24 # Author:Lingchen # Mark: 使用基础Python筛选出Excel中客户姓名包含一个特定模式（以大写字母J开始） # python 6_excel_value_match_pattern.py data/sales_2013.xlsx data/output/6_output.xlsx import sys import re from datetime import date from xlrd import open_workbook, xldate_as_tuple from xlwt import Workbook input_file = sys.argv[1] output_file = sys.argv[2] output_workbook = Workbook() output_worksheet = output_workbook.add_sheet('jan_2013_output') # 特定模式 # r表示单引号之间的模式是一个原始字符串，正则是 ^J.* pattern = re.compile(r'(?P<my_pattern>^J.*)') # 姓名列索引 customer_name_index = 1 with open_workbook(input_file) as workbook: worksheet = workbook.sheet_by_name('january_2013') data = [] # 标题处理 header = worksheet.row_values(0) data.append(header) for row_index in range(1, worksheet.nrows): row_list = [] # 姓名正则匹配筛选 if pattern.search(worksheet.cell_value(row_index, customer_name_index)): for column_index in range(worksheet.ncols): cell_value = worksheet.cell_value(row_index, column_index) cell_type = worksheet.cell_type(row_index, column_index) # 购买日期列判断处理 if cell_type == 3: date_cell = xldate_as_tuple(cell_value, workbook.datemode) # 日期格式化 date_cell = date(*date_cell[0:3]).strftime('%m/%d/%Y') row_list.append(date_cell) else: row_list.append(cell_value) if row_list: data.append(row_list) for list_index, output_list in enumerate(data): for element_index, element in enumerate(output_list): output_worksheet.write(list_index, element_index, element) output_workbook.save(output_file)

[ "lingchen1316@163.com" ]

lingchen1316@163.com

a8ac8c461732d4ded453bead82fc9acec29dbbba

ac5e52a3fc52dde58d208746cddabef2e378119e

/schedRUN/batchExps.py

7db0515b331adb3b60252aaf47cb1feafd1af7df

[]

no_license

ricardobtxr/experiment-scripts

1e2abfcd94fb0ef5a56c5d7dffddfe814752eef1

7bcebff7ac2f2822423f211f1162cd017a18babb

refs/heads/master

2023-04-09T02:37:41.466794

2021-04-25T03:27:16

358,926,457

0

null

UTF-8

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false

2,656

py

#!/usr/bin/env python import expconfig as cfg import model.SystemResourceGenerator as generator import schedulability.schedulabilityRUN as mySched #x = utilLimit, y=resDistr def saveFile(fileName, Data, resN, reqN, resW): out_file = open(fileName,"w") out_file.write("# utilLimit, resDistr, success\n") for k1 in cfg.UL: for k2 in cfg.RD: out_file.write(str(k1)+" "+str(k2)+" "+str(Data[k1][k2][resN][reqN][resW])+"\n") out_file.write("\n") out_file.close() def main(): #(self, periodDistr, utilDistr, resDistr, resWeight, resNumber, utilLimit, cpuLimit) schedResultRUN = {} surplusUtilRUN = {} for utilLimit in cfg.UL: schedResultRUN[utilLimit] = {} surplusUtilRUN[utilLimit] = {} for resDistr in cfg.RD: schedResultRUN[utilLimit][resDistr] = {} surplusUtilRUN[utilLimit][resDistr] = {} for resNumb in cfg.RN: schedResultRUN[utilLimit][resDistr][resNumb] = {} surplusUtilRUN[utilLimit][resDistr][resNumb] = {} for reqNumb in cfg.QN : schedResultRUN[utilLimit][resDistr][resNumb][reqNumb] = {} surplusUtilRUN[utilLimit][resDistr][resNumb][reqNumb] = {} for resWeight in cfg.RW: taskSetGenerator = generator.SystemResourcesGenerator( cfg.NAMED_PERIODS['uni-moderate'], cfg.NAMED_UTILIZATIONS['uni-medium'], resDistr, resWeight, resNumb, reqNumb, utilLimit, cfg.cpuLimit) averageSurplusRUN = [] counterRUN = 0 for i in range(0, cfg.NumExps): taskSet = taskSetGenerator.generateTaskSetLinear() initialUtil = sum([float(x.cost)/float(x.period) for x in taskSet]) mySchedRUN = mySched.SchedulabilityTestRUN(range(0, resNumb), taskSet) if mySchedRUN.isSchedulable(cfg.cpuLimit) : counterRUN += 1 averageSurplusRUN.append(100.0*(mySchedRUN.getFinalUtilization() - initialUtil)/initialUtil) schedResultRUN[utilLimit][resDistr][resNumb][reqNumb][resWeight] = float(counterRUN)/float(cfg.NumExps) surplusUtilRUN[utilLimit][resDistr][resNumb][reqNumb][resWeight] = sum(averageSurplusRUN)/float(max(len(averageSurplusRUN), 1)) for resN in cfg.RN: for reqN in cfg.QN: for resW in cfg.RW: saveFile("/home/ricardo/litmus/experiment-scripts/output/RUNsched:"+str(resN)+":"+str(reqN)+":"+str(resW), schedResultRUN, resN, reqN, resW) saveFile("/home/ricardo/litmus/experiment-scripts/output/RUNsurpl:"+str(resN)+":"+str(reqN)+":"+str(resW), surplusUtilRUN, resN, reqN, resW) if __name__ == '__main__': main()

[ "ricardo.btxr@gmail.com" ]

ricardo.btxr@gmail.com

45a2dc394fecfadccc2ed49b79f85b17928b0fb6

aa369073fab4f8e13ac27a714fe0d975a5a4a9ed

/mathematics/math/math_isinf.py

38f0c57b3c57471a56b8a47acecc32dda6634bd6

[]

no_license

ramsayleung/python3-module-of-week

4076599a8b1d8aa5794de5d73e2083555abe9f0c

54266c7e62025c3816a6987191c40f3bc0fdd97c

refs/heads/master

2021-06-18T09:07:30.256614

2017-06-25T10:14:54

null

0

null

UTF-8

Python

false

265

py

import math print('{:^3} {:6} {:6}{:^}'.format('e', 'e', 'x**2', 'isinf')) print('{:-^3} {:-^6} {:^6} {:-^6}'.format('', '', '', '')) for e in range(0, 201, 20): x = 10.0**e y = x * x print('{:3d} {:<6g} {:<6g} {!s:6}'.format(e, x, y, math.isinf(y)))

[ "samrayleung@gmail.com" ]

samrayleung@gmail.com

934d2b157de713c6d466541d5d13b2e7e9e822df

9aa488e813b6986d463b35a394a997727a2b26e2

/NimGame.py

710f59aac2f9cd39102407a9ac5574b1c545f0ad

[]

no_license

s781825175/learnpython

5fb2304e3183acb0faa068470b416620115c07dc

458c84693d8a27e13dab5cb0dc649f894dbba621

refs/heads/master

2020-12-30T10:49:13.531546

2017-12-14T10:01:32

98,855,316

1

0

null

UTF-8

Python

false

186

py

class Solution(object): def canWinNim(self, n): """ :type n: int :rtype: bool """ return bool(n%4) a=Solution() n=4 b=a.canWinNim(n) print(b)

[ "781825175@qq.com" ]

781825175@qq.com

35391ce5c447621ce5679aed9db59627ffd82563

a4681043cb56a9ab45be32a62fa9700b391f087f

/16-Hypothesis_Testing_with_SciPy/P-Values.py

f449cb0cb34998455568dd581dbc9c0f9e642373

[]

no_license

MarceloDL-A/Python

b16b221ae4355b6323092d069bf83d1d142b9975

c091446ae0089f03ffbdc47b3a6901f4fa2a25fb

refs/heads/main

2023-01-01T02:29:31.591861

2020-10-27T19:04:11

301,565,957

0

null

2020-10-27T19:04:12

2020-10-05T23:41:30

Python

UTF-8

Python

false

1,894

py

""" A p-value of 0.05 means that if the null hypothesis is true, there is a 5% chance that an observed sample statistic could have occurred due to random sampling error. For example, in comparing two sample means, a p-value of 0.05 indicates there is a 5% chance that the observed difference in sample means occurred by random chance, even though the population means are equal. Before conducting a hypothesis test, we determine the necessary threshold we would need before concluding that the results are significant. A higher threshold is more likely to give a false positive so if we want to be very sure that the result is not due to just chance, we will select a very small threshold. It is important that we choose the significance level before we perform our statistical hypothesis tests to yield a p-value. If we wait until after we see the results, we might pick our threshold such that we get the result we want to see. For instance, if we're trying to publish our results, we might set a significance level that makes our results seem statistically significant. Choosing our significance level in advance helps keep us honest. Generally, we want a p-value of less than 0.05, meaning that there is less than a 5% chance that our results are due to random chance. """ """ Fill in the body of the given function reject_null_hypothesis to return True if the p-value is small enough to reject the null hypothesis (i.e., it's less than 0.05), and return False otherwise. """ def reject_null_hypothesis(p_value): """ Returns the truthiness of whether the null hypothesis can be rejected Takes a p-value as its input and assumes p <= 0.05 is significant """ if p_value < 0.05: return True else: return False hypothesis_tests = [0.1, 0.009, 0.051, 0.012, 0.37, 0.6, 0.11, 0.025, 0.0499, 0.0001] for p_value in hypothesis_tests: reject_null_hypothesis(p_value)

[ "marcelo.delmondes.lima@usp.br" ]

marcelo.delmondes.lima@usp.br

4e9e704c291b63d48880b728ff72d7853655dd19

0381663735f6187eaba2a080972c696fef6a122c

/tests/test_transforms.py

aa34fda2fe829d05a840aac3a1b185df62f77444

[ "MIT", "LicenseRef-scancode-unknown-license-reference" ]

permissive

ankitshah009/CovidPrognosis

3cfe8740511ff6672d3d27b547d83ba83eb6eb48

febabc43a56a1c55e5237513f85f592f578910ea

refs/heads/master

2023-02-28T08:14:17.475669

2021-02-08T07:50:53

330,040,422

0

MIT

2021-02-08T07:50:54

2021-01-15T22:57:31

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UTF-8

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py

""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import covidprognosis.data.transforms as cpt import numpy as np import pytest import torch import torchvision.transforms as tvt from scipy.ndimage import gaussian_filter from .conftest import create_input @pytest.mark.parametrize("shape", [[32, 32, 3], [45, 16, 3]]) def test_compose(shape): sample = create_input(shape) transform = cpt.Compose( [tvt.RandomHorizontalFlip(), tvt.ToTensor(), cpt.RandomGaussianBlur()] ) sample = transform(sample) assert sample["image"] is not None @pytest.mark.parametrize("shape, label_idx", [[[32, 32, 3], 0], [[45, 16, 3], 5]]) def test_nan_to_int(shape, label_idx): sample = create_input(shape) transform = cpt.Compose([tvt.ToTensor(), cpt.NanToInt(5)]) sample["labels"][label_idx] = np.nan sample = transform(sample) assert sample["labels"][label_idx] == 5 @pytest.mark.parametrize( "shape, label_idx, start_label, end_label", [[[32, 32, 3], 2, -1, 0], [[45, 16, 3], 10, 1, 0]], ) def test_remap_label(shape, label_idx, start_label, end_label): sample = create_input(shape) transform = cpt.Compose([tvt.ToTensor(), cpt.RemapLabel(start_label, end_label)]) sample["labels"][label_idx] = start_label sample = transform(sample) assert sample["labels"][label_idx] == end_label @pytest.mark.parametrize("shape", [[32, 32, 3], [45, 16, 3]]) def test_histnorm(shape): """Test this to guard against an implementation change.""" sample = create_input(shape) transform = cpt.Compose([tvt.ToTensor(), cpt.HistogramNormalize()]) image = np.transpose( torch.tensor(np.array(sample["image"]), dtype=torch.float).numpy(), (2, 0, 1) ) # get image histogram image_histogram, bins = np.histogram( image.flatten(), transform.transforms[1].number_bins, density=True ) cdf = image_histogram.cumsum() # cumulative distribution function cdf = 255 * cdf / cdf[-1] # normalize # use linear interpolation of cdf to find new pixel values image_equalized = np.interp(image.flatten(), bins[:-1], cdf) image_equalized.reshape(image.shape) image = torch.tensor(image_equalized.reshape(image.shape)).to(torch.float) sample = transform(sample) assert torch.allclose(sample["image"], image) @pytest.mark.parametrize("shape", [[32, 32, 3], [45, 16, 3]]) def test_rand_gauss_blur(shape): """Test this to guard against an implementation change.""" seed = 123 sample = create_input(shape) transform = cpt.Compose([tvt.ToTensor(), cpt.RandomGaussianBlur(p=1)]) # run the custom blur np.random.seed(seed) image = tvt.functional.to_tensor(sample["image"]) * 1 sigma = np.random.uniform( transform.transforms[1].sigma_range[0], transform.transforms[1].sigma_range[1] ) image = torch.tensor(gaussian_filter(image.numpy(), sigma), dtype=image.dtype,) # transform blur transform = cpt.Compose( [tvt.ToTensor(), cpt.RandomGaussianBlur(p=1, sigma_range=(sigma, sigma))] ) sample = transform(sample) assert torch.allclose(sample["image"], image) # retest for 0 probability sample = create_input(shape) transform = cpt.Compose([tvt.ToTensor(), cpt.RandomGaussianBlur(p=-0.1)]) # run the custom blur image = tvt.functional.to_tensor(sample["image"]) * 1 # transform blur sample = transform(sample) assert torch.allclose(sample["image"], image) @pytest.mark.parametrize("shape", [[32, 32, 3], [45, 16, 3]]) def test_add_noise(shape): """Test this to guard against an implementation change.""" seed = 456 sample = create_input(shape) transform = cpt.Compose([tvt.ToTensor(), cpt.AddGaussianNoise(p=1)]) # run the custom noise np.random.seed(seed) image = tvt.functional.to_tensor(sample["image"]) * 1 np.random.uniform() snr_level = np.random.uniform( low=transform.transforms[1].snr_range[0], high=transform.transforms[1].snr_range[1], ) signal_level = np.mean(image.numpy()) image = image + (signal_level / snr_level) * torch.tensor( np.random.normal(size=tuple(image.shape)), dtype=image.dtype, ) # transform blur np.random.seed(seed) sample = transform(sample) assert torch.allclose(sample["image"], image) # retest for 0 probability sample = create_input(shape) transform = cpt.Compose([tvt.ToTensor(), cpt.AddGaussianNoise(p=-0.1)]) # run the custom blur image = tvt.functional.to_tensor(sample["image"]) * 1 # transform blur sample = transform(sample) assert torch.allclose(sample["image"], image) @pytest.mark.parametrize("shape", [[32, 32, 3], [45, 16, 3]]) def test_tensor_to_rgb(shape): sample = create_input(shape) transform = cpt.Compose([tvt.ToTensor(), cpt.TensorToRGB()]) image = tvt.functional.to_tensor(sample["image"]) * 1 expands = list() for i in range(image.ndim): if i == 0: expands.append(3) else: expands.append(-1) image = image.expand(*expands) sample = transform(sample) assert torch.allclose(sample["image"], image)

[ "matt.muckley@gmail.com" ]

matt.muckley@gmail.com

ad3872fe9215e5b4563df49a87e54b6899c3d9a4

316b8375a7ef8095f09973d13f5a49bc7fbe7580

/leetcode/1319.py

f921bc8cfc4b6c03132ff116954b9e8c0afdc9b9

[]

no_license

zhaolijian/suanfa

9a8d23fbca01d994f7eef24631783c4b7ed25683

4f3b25f360f30c0e604ba4dc4d5774ccb5f25b32

refs/heads/master

2023-06-08T17:12:41.522937

2021-06-27T08:13:16

313,269,459

1

0

null

UTF-8

Python

false

1,443

py

# 用以太网线缆将 n 台计算机连接成一个网络，计算机的编号从 0 到 n-1。线缆用 connections 表示，其中 connections[i] = [a, b] 连接了计算机 a 和 b。 # 网络中的任何一台计算机都可以通过网络直接或者间接访问同一个网络中其他任意一台计算机。 # 给你这个计算机网络的初始布线 connections，你可以拔开任意两台直连计算机之间的线缆，并用它连接一对未直连的计算机。 # 请你计算并返回使所有计算机都连通所需的最少操作次数。如果不可能，则返回 -1 。 # 如果线数<n-1,则返回-1 # 否则线数肯定够，返回连通分量数-1 class Solution: def makeConnected(self, n: int, connections) -> int: def find(node): if parent[node] != node: parent[node] = find(parent[node]) return parent[node] def union(node1, node2): nonlocal res root_1, root_2 = find(node1), find(node2) # 根节点不同，则说明不是一个连通分量 if root_1 != root_2: parent[find(node2)] = find(node1) res -= 1 if len(connections) < n - 1: return -1 parent = [i for i in range(n)] # 初始化连通分量数为节点数n res = n for first, second in connections: union(first, second) return res - 1

[ "820913569@qq.com" ]

820913569@qq.com

1f48b579b46935fd936d8a0e11a65d6de57091ac

6c492996b452423ff3c02ae2bda35c806b5e2beb

/ALDS1_3_C.py

8c03c6d04d4818cf18920a385da7b33829d1b0aa

[]

no_license

TakuroKato/AOJ

4764820aa0fc523d1f2719d968ab9a30069cdef7

cdcf173eca3079c89041967121f746b200d39ea7

refs/heads/master

2021-05-09T17:34:24.953074

2018-01-27T07:09:04

119,141,600

0

null

UTF-8

Python

false

630

py

# -*- coding:utf-8 -*- n = int(input()) arr = [] for i in range(n): c = input() try: tmp = c.split() com = str(tmp[0]) num = int(tmp[1]) except: com = str(c) num = -1 if num != -1: if com == 'insert': arr.insert(0,num) if com == 'delete': ind = arr.index(num) arr.pop(ind) else: if com == 'deleteFirst': arr.pop(0) if com == 'deleteLast': arr.pop(-1) if len(arr) != 1: for i in range(len(arr)-1): print(arr[i], end = ' ') print(arr[-1]) else: print(arr[0])

[ "kttk.aero@gmail.com" ]

kttk.aero@gmail.com

9ba9418423e0772feb3012850b6a1961edec013b

181af10fcf40b824fe92d3b8f72fd15d6d1490c2

/Contests/201-300/week 239/1851. Minimum Interval to Include Each Query/Minimum Interval to Include Each Query.py

11dc19b8a31558f91781f8fb8511f15ad9f7d71f

[]

no_license

wangyendt/LeetCode

402c59a0b7b7f5b3a672231ea5dad8056ade36af

4a3ba15284c45b2d8bf38306c8c8526ae174615c

refs/heads/master

2023-08-10T06:27:54.995152

2023-08-10T02:22:27

176,651,399

6

0

null

UTF-8

Python

false

797

py

#!/usr/bin/env python # -*- coding:utf-8 _*- """ @author: wangye(Wayne) @license: Apache Licence @file: Minimum Interval to Include Each Query.py @time: 2021/05/02 @contact: wang121ye@hotmail.com @site: @software: PyCharm # code is far away from bugs. """ from typing import * import heapq class Solution: def minInterval(self, A: List[List[int]], queries: List[int]) -> List[int]: A = sorted(A)[::-1] h = [] res = {} for q in sorted(queries): while A and A[-1][0] <= q: i, j = A.pop() if j >= q: heapq.heappush(h, [j - i + 1, j]) while h and h[0][1] < q: heapq.heappop(h) res[q] = h[0][0] if h else -1 return [res[q] for q in queries]

[ "905317742@qq.com" ]

905317742@qq.com

ff2271359db1616124e1268faddb92c674bae44a

7b47c686684e145ad06f2096c4be9fcf4dba4c68

/regress_nn.py

e40313ea874bca697c0ccb86cfd15631c9e9e903

[]

no_license

evanthebouncy/learn_torch

3e5f52fb9dc7d8dbcf6fe5f2f3dcaf252c523512

d612375e1b0f6b8dee667e25644d03d297e3da65

refs/heads/master

2020-04-09T19:00:59.485452

2018-03-07T19:01:37

124,240,753

0

null

UTF-8

Python

false

1,959

py

import torch from torch.autograd import Variable import numpy as np # generate the data A = np.array([[1.0, 2.0],[3.0, 4.0]]) B = np.array([[4.0, 3.0],[2.0, 1.0]]) def to_torch(x): x = Variable(torch.from_numpy(x)).type(torch.cuda.FloatTensor) return x def gen_xy(): x = np.random.rand(2) y = np.matmul(A,x) if np.sum(x) > 1.0 else np.matmul(B,x) return x, y def gen_xy_batch(): xs, ys = [], [] for i in range(30): x,y = gen_xy() xs.append(x) ys.append(y) return np.array(xs), np.array(ys) print (gen_xy()) n_hidden = 200 model = torch.nn.Sequential( torch.nn.Linear(2, n_hidden), torch.nn.ReLU(), torch.nn.Linear(n_hidden, n_hidden), torch.nn.ReLU(), torch.nn.Linear(n_hidden, 2), ).cuda() loss_fn = torch.nn.MSELoss(size_average=False) learning_rate = 1e-3 for t in range(5000): x, y = gen_xy_batch() x = to_torch(x) y = to_torch(y) y_pred = model(x) # Compute and print loss. We pass Variables containing the predicted and true # values of y, and the loss function returns a Variable containing the loss. loss = loss_fn(y_pred, y) print(t, loss.data[0]) # Zero the gradients before running the backward pass. model.zero_grad() # Backward pass: compute gradient of the loss with respect to all the learnable # parameters of the model. Internally, the parameters of each Module are stored # in Variables with requires_grad=True, so this call will compute gradients for # all learnable parameters in the model. loss.backward() # Update the weights using gradient descent. Each parameter is a Variable, so # we can access its data and gradients like we did before. for param in model.parameters(): param.data -= learning_rate * param.grad.data for i in range(100): print ("========================") x, y = gen_xy() print (x) print ("prediction ") print (model(to_torch(x))) print ("truth") print (y)

[ "evanthebouncy@gmail.com" ]

evanthebouncy@gmail.com

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NYCPlanning/db-data-recipes

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from dataflows import * from lib import joined_lower, create_base_path, dump_to_s3 def ETL(): table_name = 'nysopwdd_providers' url = 'https://data.ny.gov/api/views/ieqx-cqyk/rows.csv?accessType=DOWNLOAD' base_path = create_base_path(__file__) Flow( load(url, name=table_name, format='csv', force_strings=True), joined_lower(resources=table_name), update_resource(resources=table_name, path=table_name+'.csv'), dump_to_s3(resources=table_name, params=dict(base_path=base_path)) ).process() if __name__ == '__main__': ETL()

[ "caobaiyue@gmail.com" ]

caobaiyue@gmail.com

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15051882416/food_shop

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from datetime import datetime, timedelta from flask_script import Manager from app.libs.enums import OrderStatus from app.models import Order from app.service.order import OrderService from food_shop import app pay = Manager() @pay.command def pay_deadline(): now = datetime.now() date_30mins_ago = (now - timedelta(seconds=1)).timestamp() orders = Order.query.filter_by(order_status=OrderStatus.UNPAID.value).filter( Order.create_time <= date_30mins_ago ).all() if not orders: app.logger.info('没有订单数据') return for item in orders: OrderService.cancel_order(item) app.logger.info('超过30分钟未支付订单已关闭')

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import time import os os.system('python resetnew.py') os.system('python word_key.py') os.system('python set_AZCM.py') os.system('python word_count_key.py')

[ "campanulamediuml@gmail.com" ]

campanulamediuml@gmail.com

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############################################################################### # # Tests for XlsxWriter. # # SPDX-License-Identifier: BSD-2-Clause # Copyright (c), 2013-2022, John McNamara, jmcnamara@cpan.org # import unittest from io import StringIO from ...workbook import Workbook from ...exceptions import UndefinedImageSize from ...exceptions import UnsupportedImageFormat class TestInsertImage(unittest.TestCase): """ Test exceptions with insert_image(). """ def test_undefined_image_size(self): """Test adding an image with no height/width data.""" fh = StringIO() workbook = Workbook() workbook._set_filehandle(fh) worksheet = workbook.add_worksheet() worksheet.insert_image('B13', 'xlsxwriter/test/comparison/images/nosize.png') self.assertRaises(UndefinedImageSize, workbook._prepare_drawings) workbook.fileclosed = True def test_unsupported_image(self): """Test adding an unsupported image type.""" fh = StringIO() workbook = Workbook() workbook._set_filehandle(fh) worksheet = workbook.add_worksheet() worksheet.insert_image('B13', 'xlsxwriter/test/comparison/images/unsupported.txt') self.assertRaises(UnsupportedImageFormat, workbook._prepare_drawings) workbook.fileclosed = True

[ "jmcnamara@cpan.org" ]

jmcnamara@cpan.org

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/feder/questionaries/models.py

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from django.core.urlresolvers import reverse from django.db import models from django.utils.encoding import python_2_unicode_compatible from django.utils.translation import ugettext_lazy as _ from jsonfield import JSONField from model_utils.models import TimeStampedModel from feder.monitorings.models import Monitoring from .utils import get_modulators _('Questionaries index') LOCK_HELP = _("Prevent of edit question to protect against destruction the data set") @python_2_unicode_compatible class Questionary(TimeStampedModel): title = models.CharField(max_length=250, verbose_name=_("Title")) monitoring = models.ForeignKey(Monitoring, verbose_name=_("Monitoring")) lock = models.BooleanField(default=False, verbose_name=_("Lock of edition"), help_text=LOCK_HELP) def get_absolute_url(self): return reverse('questionaries:details', kwargs={'pk': self.pk}) def __str__(self): return self.title class Meta: ordering = ['created', ] verbose_name = _("Questionary") verbose_name_plural = _("Questionaries") @python_2_unicode_compatible class Question(models.Model): questionary = models.ForeignKey(Questionary, verbose_name=_("Questionary")) position = models.SmallIntegerField(default=0, verbose_name=_("Position")) genre = models.CharField(max_length=25, verbose_name=_("Genre")) definition = JSONField(verbose_name=_("Technical definition")) def get_absolute_url(self): return reverse('questionaries:question_update', kwargs={'pk': self.pk}) @property def is_configured(self): return bool(self.definition) @property def modulator(self): return get_modulators()[self.genre]() def __str__(self): if not self.is_configured: return _("Undefined question - {description}").format( description=self.modulator.description) return self.modulator.get_label_text(self.definition) class Meta: ordering = ['position', ] verbose_name = _("Question") verbose_name_plural = _("Questions")

[ "naczelnik@jawnosc.tk" ]

naczelnik@jawnosc.tk

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import unittest from twisted.internet import task from spyd.utils.rate_limiter import RateLimiter class TestRateLimiter(unittest.TestCase): def setUp(self): self.clock = task.Clock() RateLimiter.clock = self.clock self.rate_limiter = RateLimiter(5) def test_check_drop_first_second(self): self.assertFalse(any(map(lambda _: self.rate_limiter.check_drop(), xrange(5)))) self.assertTrue(all(map(lambda _: self.rate_limiter.check_drop(), xrange(5)))) def test_check_drop_two_seconds(self): self.assertFalse(any(map(lambda _: self.rate_limiter.check_drop(), xrange(5)))) self.assertTrue(all(map(lambda _: self.rate_limiter.check_drop(), xrange(5)))) self.clock.advance(1) self.assertFalse(any(map(lambda _: self.rate_limiter.check_drop(), xrange(5)))) self.assertTrue(all(map(lambda _: self.rate_limiter.check_drop(), xrange(5))))

[ "fd.chasm@gmail.com" ]

fd.chasm@gmail.com

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potykion/repka

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import datetime as dt import pytest from aiopg.sa import SAConnection from pydantic import BaseModel from repka.utils import model_to_primitive, create_async_db_connection class MyModel(BaseModel): id: int title: str created: dt.datetime @pytest.fixture() def model() -> MyModel: return MyModel(id=1, title="model", created=dt.datetime(2020, 1, 4)) def test_model_to_primitive(model: MyModel) -> None: dict_ = model_to_primitive(model) assert dict_ == {"id": model.id, "title": model.title, "created": '2020-01-04T00:00:00'} def test_model_to_primitive_with_python_primitives(model: MyModel) -> None: dict_ = model_to_primitive(model, keep_python_primitives=True) assert dict_ == {"id": model.id, "title": model.title, "created": model.created} def test_model_to_primitive_excludes_id(model: MyModel) -> None: dict_ = model_to_primitive(model, without_id=True) assert "id" not in dict_ def test_model_to_primitive_excludes_fields_from_list(model: MyModel) -> None: dict_ = model_to_primitive(model, exclude=["title", "created"]) assert "title" not in dict_ and "created" not in dict_ @pytest.mark.asyncio async def test_create_async_db_connection(db_url: str) -> None: async with create_async_db_connection(db_url) as connection: conn: SAConnection = connection assert conn.connection.status

[ "potykion@gmail.com" ]

potykion@gmail.com

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LiuFang816/SALSTM_py_data

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#! /usr/bin/env python import os import sys from barf import BARF from barf.arch import ARCH_ARM_MODE_ARM if __name__ == "__main__": # # Open file # try: filename = os.path.abspath("../../bin/arm/constraint1") barf = BARF(filename) except Exception as err: print err print "[-] Error opening file : %s" % filename sys.exit(1) # # Check constraint # # 00008390 <main>: # 8390: e52db004 push {fp} ; (str fp, [sp, #-4]!) # 8394: e28db000 add fp, sp, #0 # 8398: e24dd014 sub sp, sp, #20 # 839c: e51b2008 ldr r2, [fp, #-8] # 83a0: e51b300c ldr r3, [fp, #-12] # 83a4: e0823003 add r3, r2, r3 # 83a8: e2833005 add r3, r3, #5 # 83ac: e50b3010 str r3, [fp, #-16] # 83b0: e51b3010 ldr r3, [fp, #-16] # 83b4: e1a00003 mov r0, r3 # 83b8: e28bd000 add sp, fp, #0 # 83bc: e8bd0800 ldmfd sp!, {fp} # 83c0: e12fff1e bx lr start_addr = 0x8390 end_addr = 0x83bc # Add instructions to analyze print("[+] Adding instructions to the analyzer...") for addr, asm_instr, reil_instrs in barf.translate(ea_start=start_addr, ea_end=end_addr, arch_mode=ARCH_ARM_MODE_ARM): print("0x{0:08x} : {1}".format(addr, asm_instr)) for reil_instr in reil_instrs: print("{0:14}{1}".format("", reil_instr)) barf.code_analyzer.add_instruction(reil_instr) # Get smt expressions and set pre and post conditions print("[+] Adding pre and post conditions to the analyzer...") # Get smt expression for eax and ebp registers fp = barf.code_analyzer.get_register_expr("fp") # Get smt expressions for memory locations (each one of 4 bytes) a = barf.code_analyzer.get_memory_expr(fp - 0x08, 4) b = barf.code_analyzer.get_memory_expr(fp - 0x0c, 4) c = barf.code_analyzer.get_memory_expr(fp - 0x10, 4) # Set range for variable a and b barf.code_analyzer.set_preconditions([a >= 2, a <= 100]) barf.code_analyzer.set_preconditions([b >= 2, b <= 100]) # Set desired value for the result barf.code_analyzer.set_postconditions([c >= 26, c <= 28]) # Check satisfiability print("[+] Check for satisfiability...") if barf.code_analyzer.check() == 'sat': print(" SAT! :: Possible assigments : ") # Get concrete value for expressions a_val = barf.code_analyzer.get_expr_value(a) b_val = barf.code_analyzer.get_expr_value(b) c_val = barf.code_analyzer.get_expr_value(c) # Print values print(" a : 0x{0:08x} ({0})".format(a_val)) print(" b : 0x{0:08x} ({0})".format(b_val)) print(" c : 0x{0:08x} ({0})".format(c_val)) assert(a_val + b_val + 5 == c_val) else: print(" UNSAT!")

[ "659338505@qq.com" ]

659338505@qq.com

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# 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 copy import deepcopy from typing import Any, Awaitable, TYPE_CHECKING from azure.core.rest import AsyncHttpResponse, HttpRequest from azure.mgmt.core import AsyncARMPipelineClient from .. import models as _models from .._serialization import Deserializer, Serializer from ._configuration import QuotaMgmtClientConfiguration from .operations import QuotaOperationOperations, QuotaOperations, QuotaRequestStatusOperations, UsagesOperations if TYPE_CHECKING: # pylint: disable=unused-import,ungrouped-imports from azure.core.credentials_async import AsyncTokenCredential class QuotaMgmtClient: # pylint: disable=client-accepts-api-version-keyword """Microsoft Azure Quota Resource Provider. :ivar usages: UsagesOperations operations :vartype usages: azure.mgmt.quota.aio.operations.UsagesOperations :ivar quota: QuotaOperations operations :vartype quota: azure.mgmt.quota.aio.operations.QuotaOperations :ivar quota_request_status: QuotaRequestStatusOperations operations :vartype quota_request_status: azure.mgmt.quota.aio.operations.QuotaRequestStatusOperations :ivar quota_operation: QuotaOperationOperations operations :vartype quota_operation: azure.mgmt.quota.aio.operations.QuotaOperationOperations :param credential: Credential needed for the client to connect to Azure. Required. :type credential: ~azure.core.credentials_async.AsyncTokenCredential :param base_url: Service URL. Default value is "https://management.azure.com". :type base_url: str :keyword api_version: Api Version. Default value is "2023-02-01". Note that overriding this default value may result in unsupported behavior. :paramtype api_version: str :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. """ def __init__( self, credential: "AsyncTokenCredential", base_url: str = "https://management.azure.com", **kwargs: Any ) -> None: self._config = QuotaMgmtClientConfiguration(credential=credential, **kwargs) self._client: AsyncARMPipelineClient = AsyncARMPipelineClient(base_url=base_url, config=self._config, **kwargs) client_models = {k: v for k, v in _models.__dict__.items() if isinstance(v, type)} self._serialize = Serializer(client_models) self._deserialize = Deserializer(client_models) self._serialize.client_side_validation = False self.usages = UsagesOperations(self._client, self._config, self._serialize, self._deserialize) self.quota = QuotaOperations(self._client, self._config, self._serialize, self._deserialize) self.quota_request_status = QuotaRequestStatusOperations( self._client, self._config, self._serialize, self._deserialize ) self.quota_operation = QuotaOperationOperations(self._client, self._config, self._serialize, self._deserialize) def _send_request(self, request: HttpRequest, **kwargs: Any) -> Awaitable[AsyncHttpResponse]: """Runs the network request through the client's chained policies. >>> from azure.core.rest import HttpRequest >>> request = HttpRequest("GET", "https://www.example.org/") <HttpRequest [GET], url: 'https://www.example.org/'> >>> response = await client._send_request(request) <AsyncHttpResponse: 200 OK> For more information on this code flow, see https://aka.ms/azsdk/dpcodegen/python/send_request :param request: The network request you want to make. Required. :type request: ~azure.core.rest.HttpRequest :keyword bool stream: Whether the response payload will be streamed. Defaults to False. :return: The response of your network call. Does not do error handling on your response. :rtype: ~azure.core.rest.AsyncHttpResponse """ request_copy = deepcopy(request) request_copy.url = self._client.format_url(request_copy.url) return self._client.send_request(request_copy, **kwargs) async def close(self) -> None: await self._client.close() async def __aenter__(self) -> "QuotaMgmtClient": await self._client.__aenter__() return self async def __aexit__(self, *exc_details: Any) -> None: await self._client.__aexit__(*exc_details)

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Occy88/console_game

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import time class Timer: def __init__(self): self.timer_start = 0 self.timer_end = 0 self.elapsed = 0 self.running = False self.prev_lap = 0 def poll(self): if self.running: return time.time() - self.timer_start else: return self.elapsed def lap(self): if not self.running: to_return = self.timer_end - self.prev_lap self.prev_lap = self.timer_end else: to_return = time.time() - self.prev_lap self.prev_lap = time.time() return to_return def stop(self): self.timer_end = time.time() self.elapsed = self.timer_end - self.timer_start self.running = False def start(self): self.timer_start = time.time() self.prev_lap = self.timer_start self.running = True

[ "octavio.delser@gmail.com" ]

octavio.delser@gmail.com

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iluxonchik/webscraping-with-python-book

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import os from urllib.request import urlretrieve from urllib.request import urlopen from bs4 import BeautifulSoup downloadDirectory = "downloaded" baseUrl = "http://pythonscraping.com" def getAbsoluteURL(baseUrl, source): if source.startswith("http://www."): url = "http://" + source[11:] elif source.startswith("http://"): url = source elif source.startswith("www."): url = "http://" + source[4:] else: url = baseUrl + "/" + source if baseUrl not in url: return None return url def getDownloadPath(baseUrl, absoluteUrl, dowonloadDirectory): path = absoluteUrl.replace("www.", "") path = path.replace(baseUrl, "") path = dowonloadDirectory + path directory = os.path.dirname(path) if not os.path.exists(directory): os.makedirs(directory) return removeGet(path) def removeGet(fileName): """ Removes any characters after "?" in string """ pos = fileName.find("?") if pos != -1: return fileName[:pos] return fileName html = urlopen(baseUrl) bsObj = BeautifulSoup(html, "html.parser") downloadList = bsObj.findAll(src=True) for download in downloadList: fileUrl = getAbsoluteURL(baseUrl, download["src"]) if fileUrl is not None: print(fileUrl) urlretrieve(fileUrl, getDownloadPath(baseUrl, fileUrl, downloadDirectory))

[ "iluxon4ik@hotmail.com" ]

iluxon4ik@hotmail.com

fc2ab2260587bdda8ade496a114f769bb62fa695

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/integration_distributed_training/server/sanity_check_redis.py

be2d662f50ca2b88be7b8e88384c2d38df63a90f

[]

no_license

Jessilee/ImportanceSamplingSGD

cf74a220a55b468b72fed0538b3a6740f532fcb2

0831b9b1833726391a20594d2b2f64f80e1b8fe2

refs/heads/master

2021-01-24T10:12:48.285641

2016-02-05T19:25:34

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import redis import numpy as np import time import progressbar import signal import sys from redis_server_wrapper import EphemeralRedisServer def start_redis_server(server_port=None): server_scratch_path = "." if server_port is None: server_port = np.random.randint(low=1025, high=65535) #server_password = "".join(["%d" % np.random.randint(low=0, high=10) for _ in range(10)]) server_password = None rserv = EphemeralRedisServer( scratch_path=server_scratch_path, port=server_port, password=server_password) rserv.start() time.sleep(5) rsconn = rserv.get_client() print "pinging master server : %s" % (rsconn.ping(),) import socket hostname = socket.gethostname() D_server_desc = {'hostname' : hostname, 'port' : server_port, 'password' : server_password} return (rserv, rsconn, D_server_desc) def test_cycle_queue(rsconn, N=20): queue_name = "L_queue" for n in range(N): #value = n value = (n * np.ones(100000, dtype=np.int8)).tostring() rsconn.rpush(queue_name, value) Nread = rsconn.llen(queue_name) print "(N, Nread) is (%d, %d)." % (N, Nread) for _ in range(1000): for n in range(N): e = rsconn.lpop(queue_name) rsconn.rpush(queue_name, e) L = [] while 0 < rsconn.llen(queue_name): e = rsconn.lpop(queue_name) L.append(e) print [np.fromstring(e, dtype=np.int8)[0] for e in L] def test_timestamp_hashmap(rsconn): #def get_next_timestamp(): # get_next_timestamp.counter += 1.0 # return get_next_timestamp.counter #get_next_timestamp.counter = 0.0 def get_next_timestamp(): return time.time() N = 100 hashmap_name = "H_timestamps" D_ref = {} for n in range(N): #value = n value = (n * np.ones(100000, dtype=np.int8)).tostring() timestamp_str = str(get_next_timestamp()) rsconn.hset(hashmap_name, value, timestamp_str) D_ref[value] = timestamp_str Niter = 1000 widgets = ['Parsing lines: ', progressbar.Percentage(), ' ', progressbar.Bar(marker=progressbar.RotatingMarker()), ' ', progressbar.ETA()] pbar = progressbar.ProgressBar(widgets=widgets, maxval=Niter-1).start() previous_timestamp = time.time() for niter in range(Niter): for (k, local_recorded_timestamp_str) in D_ref.items(): current_timestamp = get_next_timestamp() database_recorded_timestamp_str = rsconn.hget(hashmap_name, k) database_recorded_timestamp = float(database_recorded_timestamp_str) local_recorded_timestamp = float(local_recorded_timestamp_str) assert local_recorded_timestamp <= current_timestamp, (local_recorded_timestamp, current_timestamp) assert database_recorded_timestamp <= current_timestamp, (database_recorded_timestamp, current_timestamp) current_timestamp_str = str(current_timestamp) D_ref[k] = current_timestamp_str rsconn.hset(hashmap_name, k, current_timestamp_str) pbar.update(niter) def run(): (rserv, rsconn, _) = start_redis_server() def signal_handler(signal, frame): rserv.stop() sys.exit(0) signal.signal(signal.SIGINT, signal_handler) #test_cycle_queue(rsconn) test_timestamp_hashmap(rsconn) if __name__ == "__main__": run()

[ "gyomalin@gmail.com" ]

gyomalin@gmail.com

d516c0765a53652ce4b81c21c84245df87e8baf7

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/面向对象02/04-__del__方法.py

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[]

no_license

oweson/python-river-master

faa31c5248e297a92054cc302e213e2b37fb8bd5

cf9e99e611311b712465eb11dec4bb8f712929b2

refs/heads/master

2021-06-21T15:47:01.755957

2019-10-02T00:08:05

205,607,518

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null

2021-06-10T21:55:20

2019-08-31T23:39:55

Python

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py

class Dog: def __init__(self): print("英雄出生啦！") def __del__(self): print("-----英雄over------") dog1 = Dog() dog2 = dog1 pig = dog2 del pig del dog1 # 不会调用 __del__方法,因为这个对象还有其他的变量指向它,即引用计算不是0 del dog2 # 此时会调用__del__方法,因为没有变量指向它了 print("====================") # 如果在程序结束时,有些对象还存在,那么python解释器会自动调用它们的__del__方法来完成清理工作

[ "570347720@qq.com" ]

570347720@qq.com

d6451583c9261fe045e59096f4413197ec245229

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/Python_codes/p03816/s835463454.py

bb046e7283c6af48d8494de5f20feb193506bf36

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

UTF-8

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false

131

py

N = int(input()) A = list(map(int, input().split())) s = set(A) if len(s)%2 == 0: ans = len(s)-1 else: ans = len(s) print(ans)

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

853bed2cb752c48a90ca0259b3a04f2b8aee8684

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/modules/ifttt_manage/ifttt_scene_query/ifttt_scene_query_detail.py

042e1159acc9f5254e74791f0a6593cdb8438812

[]

no_license

showgea/AIOT

7f9ffcd49da54836714b3342232cdba330d11e6c

fe8275aba1c4b5402c7c2c2987509c0ecf49f330

refs/heads/master

2020-07-23T10:19:37.478456

2019-09-23T12:25:59

207,525,184

2

0

null

UTF-8

Python

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642

py

import requests from config import readcfg header_Gary = readcfg.header_Gary header_Jenny = readcfg.header_Jenny url = readcfg.url def ifttt_scene_query_detail(sceneId): url_ = url + "/app/v1.0/lumi/ifttt/scene/query/detail" params_ = { "sceneId": sceneId } proxies = {'http': 'http://127.0.0.1:8888', 'https': 'http://127.0.0.1:8888'} print("请求数据：%s" % params_) r = requests.get(url=url_, params=params_, headers=header_Gary, proxies=proxies, verify=False) return r if __name__ == '__main__': result_main = ifttt_scene_query_detail("AL.615944318139310080") print(result_main.text)

[ "tangguobing2011@163.com" ]

tangguobing2011@163.com

8c68e381114915acc331eee949fba0bca03c4ec5

754d39fbc163cb38bcff31d4b16bfc583242b759

/Session20L.py

81de6bb7d8ef42101807af128a981e9329e89bd2

[]

no_license

MUSKANJASSAL/PythonTraining2019

c68654b5548860c7b501252ce2289a48dbe575c3

0e3f226d2d7443759c92b3808d9d7f176c9a4a84

refs/heads/master

2020-06-22T14:39:29.491716

2019-07-21T10:46:10

197,730,687

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UTF-8

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py

import pandas as pd import matplotlib.pyplot as plt import numpy as np result = pd.read_csv('CityTemps.csv', delimiter = ',') print(result) print("Maximum Temparature of Ludhiana", result['Ludhiana'].max()) print("Maximum Temparature of Amritsar", result['Amritsar'].max()) print("Maximum Temparature of Chandigarh", result['Chandigarh'].max()) print("Minimum Temparature of Ludhiana", result['Ludhiana'].min()) print("Minimum Temparature of Amritsar", result['Amritsar'].min()) print("Minimum Temparature of Chandigarh", result['Chandigarh'].min()) # max_temp = {"Ldh":21.1, "Amr":22.0, "Chd":20.4} # min_temp = {"Ldh":-8.6, "Amr":8.9, "Chd":10.3} # for i, key in enumerate(max_temp): # for i, key in enumerate(max_temp): # # plt.bar(i, scores[key]) # plt.bar(key, min_temp[key]) # plt.bar(key, max_temp[key]) # plt.xlabel("Cities") # plt.ylabel("Temp") # plt.title("Temp_Cties") # # plt.show() # data to plot n_groups = 2 ldh = (21.1, 8.6) amr = (22.0, 8.9) chd = (20.4, 10.3) # create plot fig, ax = plt.subplots() index = np.arange(n_groups) bar_width = 0.05 opacity = 0.8 rects1 = plt.bar(index, ldh, bar_width,alpha=opacity,color='b',label='Ldh') rects2 = plt.bar(index + bar_width, amr, bar_width,alpha=opacity,color='g',label='Amr') rects3 = plt.bar(index + bar_width, chd, bar_width,alpha=opacity,color='m',label='Chd') plt.xlabel('Cities') plt.ylabel('Temp') plt.title('Scores by Temp_Cties') plt.xticks(index + bar_width, ('Ldh', 'Amr', 'Chd')) plt.legend() plt.tight_layout() plt.show()

[ "muskan124.jassal@gmail.com" ]

muskan124.jassal@gmail.com

9c40c6ed010c2cd1f0ebcc2470ac11538c1ffa5f

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/test/test_plants/test_plants/test_noFuelPlant.py

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permissive

alexanderkell/elecsim

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refs/heads/master

2023-04-06T10:03:35.367411

2023-04-05T16:52:16

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2022-12-08T01:57:45

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Jupyter Notebook

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""" File name: test_noFuelPlant Date created: 28/11/2018 Feature: #Enter feature description here """ from unittest import TestCase from pytest import approx from elecsim.plants.plant_type.non_fuel_plant import NonFuelPlant __author__ = "Alexander Kell" __copyright__ = "Copyright 2018, Alexander Kell" __license__ = "MIT" __email__ = "alexander@kell.es" class TestNoFuelPlant(TestCase): # def create_2018_biomass_power_plant(self): # fuel_plant = FuelPlant(name="Test_Plant", plant_type="Biomass_wood", capacity_mw=1200, construction_year=2010, # average_load_factor=0.93, efficiency=0.54, pre_dev_period=3, construction_period=3, # operating_period=25, pre_dev_spend_years=[0.44, 0.44, 0.12], # construction_spend_years=[0.4, 0.4, 0.2], pre_dev_cost_per_mw=1000, # construction_cost_per_mw=500, infrastructure=15100, fixed_o_and_m_per_mw=12200, # variable_o_and_m_per_mwh=3, insurance_cost_per_mw=2100, connection_cost_per_mw=3300) # return fuel_plant # # # def test_calculate_lcoe(self): # power_plant = self.create_2018_biomass_power_plant() # print("LCOE for biomass: {}".format(power_plant.calculate_lcoe(0.1))) # # assert power_plant.calculate_lcoe() == 1 def test_small_hydro_plant_lcoe_calculation(self): params = {'connection_cost_per_mw': 0.0, 'construction_cost_per_mw': 4103676.6103626275, 'fixed_o_and_m_per_mw': 37265.847352193756, 'infrastructure': 311.06133108680143, 'insurance_cost_per_mw': 0.0, 'pre_dev_cost_per_mw': 0, 'variable_o_and_m_per_mwh': 3.074841257793032, 'pre_dev_period': 0, 'operating_period': 35, 'construction_period': 0, 'efficiency': 1, 'average_load_factor': 0.4, 'construction_spend_years': [1.0], 'pre_dev_spend_years': []} hydro_plant = NonFuelPlant(name="Hydro", plant_type="Hydro", capacity_mw=5, construction_year=2002, **params) assert hydro_plant.calculate_lcoe(0.075) == approx(103.8260236534459)

[ "alexander@kell.es" ]

alexander@kell.es

6335ca36003aa92af24d10cb4f58f016985db399

16546a94e9f078c3e7a39337d47b21d7b71b6799

/siphon.py

09a895c8d1f3ff55df5b9a8edae0e64a5d8af074

[]

no_license

mdevaev/arduino-siphon

7c7259bb87f116fa9c0eb65b2c1b8941c11dd06a

56a7959a13a73311faeefcd54a9f3aeb9f7989ff

refs/heads/master

2021-01-21T08:57:33.710400

2016-01-09T05:06:40

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#!/usr/bin/env python3 import sys import xmlrpc.client import serial import struct import time import logging # ===== class Siphon: def __init__(self, device): self._tty = serial.Serial(device, 115200) def send(self, download, upload, has_download, has_upload): self._tty.write(struct.pack("<cHccccc", *((b"\x01", download) + (b"\x00",) * 5))) self._tty.write(struct.pack("<cHccccc", *((b"\x02", upload) + (b"\x00",) * 5))) self._tty.write(struct.pack("<cccccccc", *((b"\x03", self._make_byte(has_download)) + (b"\x00",) * 6))) self._tty.write(struct.pack("<cccccccc", *((b"\x04", self._make_byte(has_upload)) + (b"\x00",) * 6))) def _make_byte(self, value): return bytes([int(value)]) def receive(self): self._tty.write(struct.pack("<cccccccc", *((b"\x05",) + (b"\x00",) * 7))) download = struct.unpack("<H", self._tty.read(2))[0] self._tty.write(struct.pack("<cccccccc", *((b"\x06",) + (b"\x00",) * 7))) upload = struct.unpack("<H", self._tty.read(2))[0] return (download, upload) class Server: def __init__(self, url) : self._server = xmlrpc.client.ServerProxy(url) self._prev_down = None self._prev_up = None def get_speed(self) : multicall = xmlrpc.client.MultiCall(self._server) multicall.get_down_rate() multicall.get_up_rate() return tuple(map(self._make_speed, multicall())) def set_speed_limits(self, download, upload) : if self._prev_down != download or self._prev_up != upload : multicall = xmlrpc.client.MultiCall(self._server) if self._prev_down != download : multicall.set_download_rate(self._make_limit(download)) self._prev_down = download if self._prev_up != upload : multicall.set_upload_rate(self._make_limit(upload)) self._prev_up = upload multicall() return True return False def _make_speed(self, speed) : return int(speed * 8.0 / (1024.0 ** 2)) def _make_limit(self, speed) : return int(speed / 8.0 * (1024.0 ** 2)) # ===== def main(): assert len(sys.argv) == 3 logger = logging.getLogger("siphon") logger.setLevel(logging.DEBUG) handler = logging.StreamHandler() handler.setLevel(logging.DEBUG) formatter = logging.Formatter("%(asctime)s - %(name)s [%(levelname)s]: %(message)s") handler.setFormatter(formatter) logger.addHandler(handler) server = Server(sys.argv[1]) siphon = Siphon(sys.argv[2]) while True : (download, upload) = server.get_speed() logger.info("siphon << server: speed: D:%d / U:%d", download, upload) siphon.send(download, upload, download != 0, upload != 0) (download, upload) = siphon.receive() if server.set_speed_limits(download, upload): logger.info("siphon >> server: limits: D:%d / U:%d", download, upload) time.sleep(1) if __name__ == "__main__" : main()

[ "mdevaev@gmail.com" ]

mdevaev@gmail.com

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/11 - Unit 4/4.3.6.py

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[]

no_license

srujanprophet/PythonPractice

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ebc13e9f21a6b0f594d10b8524ef358c797979de

refs/heads/master

2021-09-12T15:37:22.423484

2018-04-18T05:05:59

67,717,033

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null

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py

c=dict() n = input("Enter total number ") i=1 while i<=n: a=raw_input("enter place") b=raw_input("enter number") c[a]=b i=i+1 print "place","\t","number" for i in c: print i,"\t",c[i]

[ "noreply@github.com" ]

srujanprophet.noreply@github.com

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/s02e03.py

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[]

no_license

tjmode/python

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refs/heads/master

2020-08-30T10:49:27.190948

2019-10-29T18:32:52

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null

2019-10-29T18:32:09

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UTF-8

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false

137

py

a=int(input()) count=0; for i in range(2,a): if a%i==0 : count=count+1 if count==0 : print("yes") else : print("no")

[ "noreply@github.com" ]

tjmode.noreply@github.com

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[ "Apache-2.0" ]

permissive

tanxicccc/rsopt

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refs/heads/master

2023-01-06T19:21:40.065806

2020-10-24T23:48:34

288,584,476

0

Apache-2.0

2020-08-18T23:19:55

2020-08-18T23:19:54

null

UTF-8

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py

# Templated codes have schema files that can be used to check input and create run files. Otherwise user # must supply module containing inputs _TEMPLATED_CODES = ['elegant', 'opal'] # Supported codes have defined Job class # FUTURE: 'Unsupported' codes could become a class of supported codes that have expanded user input required to run _SUPPORTED_CODES = ['python', 'genesis', *_TEMPLATED_CODES]

[ "chall@radiasoft.net" ]

chall@radiasoft.net

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/forms.py

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[ "Apache-2.0" ]

permissive

craigderington/snowy-owl-api

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refs/heads/master

2023-02-05T00:38:41.008820

2020-12-23T22:49:41

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py

from wtforms import Form, BooleanField, StringField, PasswordField, validators class LoginForm(Form): username = StringField('Username', [validators.Length(min=4, max=25)]) password = StringField('Email Address', [validators.Length(min=6, max=35)])

[ "craig@craigderington.me" ]

craig@craigderington.me

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/src/learningCurve/ninetyPercent/lrClassifierC.py

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[]

no_license

TanemuraKiyoto/PPI-native-detection-via-LR

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refs/heads/master

2022-12-05T11:59:01.014309

2020-08-10T00:41:17

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UTF-8

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# 9 September 2019 # Kiyoto Aramis Tanemura # I modified the rfClassifier.py script to implement a logistic regression classifier. This classifier runs faster than the random forest classifier and Jun previously observed comparable results between logistic regression and random forest classifiers for the protein folding system. Due to the lesser time cost, I may sample a greater hyperparameter space using the logistic regression classifier. If the sampling yields a region in which overfitting is not observed, then I can refine the search. If the results are similar to that of the random forest classifier, then I may have exhausted the dataset for generalizability. # Modified 26 October 2019 by Kiyoto Aramis Tanemura. Apply logistic regression classifier to CASF-PPI dataset. # Modified 2020-02-09 by KAT. Code generalized for public use on GitHub. import pandas as pd import numpy as np import os import json import pickle #from multiprocessing import Pool from time import time from sklearn.linear_model import LogisticRegression from sklearn.model_selection import RandomizedSearchCV from sklearn.preprocessing import StandardScaler from random import shuffle, random #os.chdir('/mnt/scratch/tanemur1/') toc = time() # Randomize input file orders pathToInput = 'data/comparison_descriptors/' pathToOutput = 'results/learningCurve/' fileNames = [x for x in os.listdir(pathToInput) if '.csv' in x] shuffle(fileNames) # note: shuffle is in-place. Do not assign to variable # Specify training set fraction train_fraction = 0.9 if len(fileNames) * train_fraction == int(len(fileNames) * train_fraction): train_file_number = int(len(fileNames) * train_fraction) else: train_file_number = int(len(fileNames) * train_fraction + 1) x_train = pd.DataFrame() y_train = pd.DataFrame() # Read individual csv for comparison descriptors, append to train_data, and partition to x_train, y_train fileNamesWithPath = [pathToInput + fileName for fileName in fileNames] def read_csv(filePath): return pd.read_csv(filePath, index_col = 0) print('begin read training set') #with Pool(np.min([train_file_number, 28])) as p: # train_dataList = list(p.map(read_csv, fileNamesWithPath[:train_file_number])) train_dataList = list(map(read_csv, fileNamesWithPath[:train_file_number])) print('begin append DF | ', (time() - toc) / 60, ' min') # Append DataFrames into one. While loop used to reduce append operations. Iteratively, DFs in a list are appended # to the following DF. while len(train_dataList) != 1: number = int(len(train_dataList) / 2) for i in range(number): train_dataList[2 * i] = train_dataList[2 * i].append(train_dataList[2 * i + 1], sort = True) for j in range(number): del train_dataList[j + 1] x_train = train_dataList[0] del train_dataList print('train_data dimensions', x_train.shape, ' | ', (time() - toc) / 60, ' min') y_train = x_train['class'] x_train = x_train.drop('class', axis = 1) # x_train contains only nonbonding descriptors feature_names = x_train.columns scaler = StandardScaler() scaler.fit(x_train) x_train = scaler.transform(x_train) y_train = y_train.values print('Dimensions x_train ', x_train.shape, ' | y_train', y_train.shape) # Define a logistic regression classifier along with pertinent hyperparameters. Here, default values are used. clf = LogisticRegression(penalty='l2', verbose = 1) def sampleRationalVals(minVal, maxVal): return 2 ** (random() * (np.log2(maxVal) - np.log2(minVal)) + np.log2(minVal)) def sampleRationalList(minVal, maxVal): theList = [] for i in range(int(2 * np.log2(maxVal - minVal) + 1)): theVal = sampleRationalVals(minVal, maxVal) theList.append(theVal) return theList parameters = { # include any hyperparameters to sample. Otherwise, leave empty to perform five fold cross validation with default values. For example: # 'C': sampleRationalList(0.001, 1000), # 'solver': ['newton-cg', 'lbfgs', 'sag','saga'] } print('begin RandomizedSearchCV | ' + str((time() - toc)/60) + ' mins') randomized_search = RandomizedSearchCV(estimator = clf, param_distributions = parameters, n_iter = 1, scoring = 'accuracy', refit = True, cv = 5, verbose = 1, n_jobs = 1, pre_dispatch = 'n_jobs', return_train_score=True) randomized_search.fit(x_train, y_train) print('begin output | ', (time() - toc) / 60 / 60, ' hours') tic = time() with open(pathToOutput + 'bestParamC.json', 'w') as g: json.dump(randomized_search.best_estimator_.get_params(), g) with open(pathToOutput + 'modelC.pkl', 'wb') as h: pickle.dump(randomized_search, h) with open(pathToOutput + 'trainingSetC.txt', 'w') as i: i.write('Training set:\n') for pdbID in fileNames[:train_file_number]: i.write(pdbID + '\n') i.write('\nJob time: ' + str((tic - toc) / 60 / 60) + ' hours') with open(pathToOutput + 'standardScalerC.pkl', 'wb') as j: pickle.dump(scaler, j) bestCoefficient = randomized_search.best_estimator_.coef_ coefDf = pd.DataFrame(bestCoefficient, columns = feature_names) with open(pathToOutput + 'coefficientsC.csv', 'w') as f: coefDf.to_csv(f)

[ "tanemur1@msu.edu" ]

tanemur1@msu.edu

bd66eed366baf1ce93deacad00fb25566d2e9611

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/redditdownloader/tests/integration/processing/handlers/test_ytdl.py

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[]

no_license

shadowmoose/RedditDownloader

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ebcb791f78e5d761efcca28b5ebd5b7e1b61df85

refs/heads/master

2023-07-13T09:55:21.700858

2023-07-02T05:02:18

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from tests.mock import StagedTest, mock_handler_request from processing.handlers import ytdl class YTDLHandlerTest(StagedTest): """ Test the YT_DL Handler's downloading capabilities """ def test_gfycat(self): """ Attempt Gfycat.com download """ _task, _prog, _file = mock_handler_request(self.dir, 'https://gfycat.com/sarcasticfixedanemoneshrimp') res = ytdl.handle(_task, _prog) self.assertTrue(res, "Failed to download Gfycat video!") self.assertTrue(_file.exists(), "Gfycat video was not downloaded! %s" % res.failure_reason) self.assertTrue(_file.relative().endswith('.mp4'), 'Failed to use .mp4 extension for video file!') def test_youtube(self): """ Attempt Youtube download """ _task, _prog, _file = mock_handler_request(self.dir, 'https://www.youtube.com/watch?v=8URukvnUYTw') res = ytdl.handle(_task, _prog) self.assertTrue(res, "Failed to download YouTube video!") self.assertTrue(_file.exists(), "YouTube video was not downloaded! %s" % res.failure_reason) self.assertTrue('.' in _file.relative(), "YTDL failed to apply file extension! (%s)" % _file.absolute()) self.assertTrue('unknown' not in _file.relative(), 'Invalid name for video file! (%s)' % _file.absolute())

[ "theshadowmoose@gmail.com" ]

theshadowmoose@gmail.com

5cc085f2bcede2101a78d224a389fcf4d5aedfc7

40da919c52cfdb9658b7400f26c48c11e124e315

/ising3D.py

0d08754fec2e3fa6bd878d34ac543fa856d3c52f

[]

no_license

bvillasen/isingModel

ae71f57c94db58ac35d3bc26b36c944b70fed2b0

b4d47c8b563cf6f787fe9a764ccdbd560964acbe

refs/heads/master

2021-01-19T14:07:01.017178

2019-11-23T22:36:08

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# 3D Ising model simulation # made by Bruno Villasenor # contact me at: bvillasen@gmail.com # personal web page: https://bvillasen.webs.com # github: https://github.com/bvillasen #To run you need these complementary files: CUDAising3D.cu, volumeRender.py, CUDAvolumeRender.cu, cudaTools.py #you can find them in my github: # https://github.com/bvillasen/volumeRender # https://github.com/bvillasen/tools import sys, time, os import numpy as np #import pylab as plt import pycuda.driver as cuda from pycuda.compiler import SourceModule import pycuda.gpuarray as gpuarray import pycuda.curandom as curandom #Add Modules from other directories currentDirectory = os.getcwd() parentDirectory = currentDirectory[:currentDirectory.rfind("/")] toolsDirectory = parentDirectory + "/tools" volumeRenderDirectory = parentDirectory + "/volumeRender" sys.path.extend( [toolsDirectory, volumeRenderDirectory] ) import volumeRender_old as volumeRender from cudaTools import setCudaDevice, getFreeMemory, gpuArray3DtocudaArray nPoints = 512 useDevice = 0 for option in sys.argv: #if option == "128" or option == "256": nPoints = int(option) if option.find("device=") != -1: useDevice = int(option[-1]) #set simulation volume dimentions nWidth = nPoints nHeight = nPoints nDepth = nPoints nData = nWidth*nHeight*nDepth temp = 3 beta = np.float32( 1./temp) plotVar = 1 upVal = 0.7 downVal = 0.4 #Initialize openGL volumeRender.nWidth = nWidth volumeRender.nHeight = nHeight volumeRender.nDepth = nDepth volumeRender.windowTitle = "Ising3D spins={0}x{1}x{2} T={3:.1f}".format(nHeight, nWidth, nDepth, float(temp)) volumeRender.initGL() #set thread grid for CUDA kernels block_size_x, block_size_y, block_size_z = 8,8,8 #hardcoded, tune to your needs gridx = nWidth // block_size_x + 1 * ( nWidth % block_size_x != 0 ) gridy = nHeight // block_size_y + 1 * ( nHeight % block_size_y != 0 ) gridz = nDepth // block_size_z + 1 * ( nDepth % block_size_z != 0 ) block3D = (block_size_x, block_size_y, block_size_z) grid3D = (gridx, gridy, gridz) grid3D_ising = (gridx//2, gridy, gridz) #initialize pyCUDA context cudaDevice = setCudaDevice( devN=useDevice, usingAnimation=True ) #Read and compile CUDA code print "\nCompiling CUDA code" cudaCodeString_raw = open("CUDAising3D.cu", "r").read() cudaCodeString = cudaCodeString_raw # % { "BLOCK_WIDTH":block2D[0], "BLOCK_HEIGHT":block2D[1], "BLOCK_DEPTH":block2D[2], } cudaCode = SourceModule(cudaCodeString) tex_spins = cudaCode.get_texref('tex_spinsIn') surf_spins = cudaCode.get_surfref('surf_spinsOut') isingKernel = cudaCode.get_function('ising_kernel') ######################################################################## from pycuda.elementwise import ElementwiseKernel ######################################################################## changeIntToFloat = ElementwiseKernel(arguments="float a, float b, int *input, float *output", operation = "output[i] = a*input[i] + b;", name = "intToFloat_kernel") ######################################################################## floatToUchar = ElementwiseKernel(arguments="float *input, unsigned char *output", operation = "output[i] = (unsigned char) ( -255*(input[i]-1));", name = "floatToUchar_kernel") ######################################################################## def sendToScreen( plotData ): floatToUchar( plotDataFloat_d, plotData_d ) copyToScreenArray() ######################################################################## def swipe(): randomNumbers_d = curandom.rand((nData)) stepNumber = np.int32(0) #saveEnergy = np.int32(0) tex_spins.set_array( spinsInArray_d ) surf_spins.set_array( spinsInArray_d ) isingKernel( stepNumber, np.int32(nWidth), np.int32(nHeight), np.int32(nDepth), beta, spinsOut_d, randomNumbers_d, plotDataFloat_d, np.float32(upVal), np.float32(downVal), grid=grid3D_ising, block=block3D ) #copy3D_dtod() stepNumber = np.int32(1) #saveEnergy = np.int32(0) tex_spins.set_array( spinsInArray_d ) surf_spins.set_array( spinsInArray_d ) isingKernel( stepNumber, np.int32(nWidth), np.int32(nHeight), np.int32(nDepth), beta, spinsOut_d, randomNumbers_d, plotDataFloat_d, np.float32(upVal), np.float32(downVal), grid=grid3D_ising, block=block3D ) #copy3D_dtod() ######################################################################## def stepFunction(): sendToScreen( spinsOut_d ) swipe() ######################################################################## def changePlotting(): global upVal, downVal if plotVar == 1: upVal, downVal = 0.7, 0.4 if plotVar == 2: upVal, downVal = 0.7, 100. if plotVar == 3: upVal, downVal = 0, 0.4 ######################################################################## def specialKeyboardFunc( key, x, y ): global temp, beta, plotVar if key== volumeRender.GLUT_KEY_UP: temp += 0.1 if key== volumeRender.GLUT_KEY_DOWN: if temp > 0.1: temp -= 0.1 if key== volumeRender.GLUT_KEY_RIGHT: plotVar += 1 if plotVar == 4: plotVar = 1 if key== volumeRender.GLUT_KEY_LEFT: plotVar -= 1 if plotVar == 0: plotVar = 3 beta = np.float32(1./temp) changePlotting() volumeRender.windowTitle = "Ising3D spins={0}x{1}x{2} T={3:.1f}".format(nHeight, nWidth, nDepth, float(temp)) ######################################################################## ######################################################################## #Initialize all gpu data print "\nInitializing Data" initialMemory = getFreeMemory( show=True ) #Set initial random distribution spins_h = (2*np.random.random_integers(0,1,[nDepth, nHeight, nWidth ]) - 1 ).astype(np.int32) #spins_h = np.ones([nDepth, nHeight, nWidth ]).astype(np.int32) spinsOut_d = gpuarray.to_gpu( spins_h ) randomNumbers_d = curandom.rand((nData)) #For texture version spinsInArray_d, copy3D_dtod = gpuArray3DtocudaArray( spinsOut_d, allowSurfaceBind=True ) #For shared version #memory for plotting plotDataFloat_d = gpuarray.to_gpu(np.zeros_like(spins_h)) plotData_d = gpuarray.to_gpu(np.zeros([nDepth, nHeight, nWidth], dtype = np.uint8)) volumeRender.plotData_dArray, copyToScreenArray = gpuArray3DtocudaArray( plotData_d ) finalMemory = getFreeMemory( show=False ) print " Total Global Memory Used: {0} Mbytes\n".format(float(initialMemory-finalMemory)/1e6) #configure volumeRender functions volumeRender.stepFunc = stepFunction volumeRender.specialKeys = specialKeyboardFunc #stepFunction() #run volumeRender animation volumeRender.animate()

[ "bvillasen@gmail.com" ]

bvillasen@gmail.com

eb699c07c9e6654200ed8d1ce223b385bfd7154d

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/2013spring/cd/w16_gearwidth2.py

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[]

no_license

chiamingyen/mdeCourse

e9caf13ee9f701d4641e91c04963d60aec5d85e3

43dea5078df8ede58d8cfaa013b94d54750feead

refs/heads/master

2021-01-16T21:22:01.906176

2013-10-25T14:25:28

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#coding: utf-8 ''' "本程式的目的在輔助設計者選擇齒輪的尺寸大小，"; "由於相囓合的兩齒輪其徑節 (Diametral Pitch) 相同"; "，齒的大小也相同。因徑節為每單位直徑的齒數，因此徑節愈大，則其齒的尺寸愈小"; "；反之，徑節愈小，則齒的尺寸則愈大。"; "一般在設計齒輪對時，為避免使用過大的齒及過寬的齒面厚度，因此必須要就齒輪大小與強度與負載加以設計。"; "一般而言是希望齒輪面的寬度 (Face Width) 能大於3倍周節 (Circular Pitch)，以避免選用太大的齒尺寸。"; "並且希望齒輪面的寬度 (Face Width) 能小於5倍周節，以便齒面傳遞負載時能有較為均勻的分佈，因此"; "設 d 為齒輪的節圓直徑(Pitch Diameter)，單位為英吋"; "N 為齒數"; "P 為徑節，即單位英吋的齒數"; "因此 d=N/P"; "設 V 為節線速度(Pitch Line Velocity)，單位為英呎/分鐘"; "因此 V=(PI) * d * n/12"; "其中 n 為齒輪轉速，單位為 rpm"; "設傳輸負載大小為 W，單位為 pounds"; "因此 W=33000H/V"; "其中 H 為傳輸功率，單位為 hourse power"; "若設 K 為速度因子(Velocity Factor)"; "因此 K=1200/(1200+V)"; "最後可求出齒輪的齒面寬度(Face Width) F ，單位為英吋"; "即 F=WP/KYS"; "其中 S 為齒面的材料彎曲應力強度"; "設計要求:控制所選齒的尺寸大小，在滿足強度與傳輸負載的要求下，讓齒面厚度介於3倍周節與5倍周節之間。"; "設計者可以選擇的參數:"; "安全係數(建議值為3以上)"; "齒輪減速比"; "馬達傳輸功率，單位為 horse power"; "馬達轉速，單位為 rpm"; "齒制(Gear System)"; "齒輪材料與強度"; ''' # 這個程式要計算正齒輪的齒面寬, 資料庫連結希望使用 pybean 與 SQLite # 導入 pybean 模組與所要使用的 Store 及 SQLiteWriter 方法 from pybean import Store, SQLiteWriter import math SQLite連結 = Store(SQLiteWriter("lewis.db", frozen=True)) # 執行 formfactor 內插運算的函式 def interpolation(小齒輪齒數, 齒形): global SQLite連結 # 使用內插法求值 # 找出比目標齒數大的其中的最小的,就是最鄰近的大值 lewis_factor = SQLite連結.find_one("lewis","gearno > ?",[小齒輪齒數]) if(齒形 == 1): larger_formfactor = lewis_factor.type1 elif(齒形 == 2): larger_formfactor = lewis_factor.type2 elif(齒形 == 3): larger_formfactor = lewis_factor.type3 else: larger_formfactor = lewis_factor.type4 larger_toothnumber = lewis_factor.gearno # 找出比目標齒數小的其中的最大的,就是最鄰近的小值 lewis_factor = SQLite連結.find_one("lewis","gearno < ? order by gearno DESC",[小齒輪齒數]) if(齒形 == 1): smaller_formfactor = lewis_factor.type1 elif(齒形 == 2): smaller_formfactor = lewis_factor.type2 elif(齒形 == 3): smaller_formfactor = lewis_factor.type3 else: smaller_formfactor = lewis_factor.type4 smaller_toothnumber = lewis_factor.gearno calculated_factor = larger_formfactor + (小齒輪齒數 - larger_toothnumber) * (larger_formfactor - smaller_formfactor) / (larger_toothnumber - smaller_toothnumber) # 只傳回小數點後五位數 return round(calculated_factor, 5) # 取得設計參數馬力 = 100 轉速 = 1120 減速比 = 4 齒形 = 4 安全係數 = 3 #unsno_treatment 材料 = "G10350_CD" 小齒輪齒數 = 18 # 改寫為齒面寬的設計函式 def gear_width(馬力, 轉速, 減速比, 齒形, 安全係數, 材料, 小齒輪齒數): global SQLite連結 # 根據所選用的齒形決定壓力角 if(齒形 == 1 or 齒形 == 2): 壓力角 = 20 else: 壓力角 = 25 # 根據壓力角決定最小齒數 if(壓力角== 20): 最小齒數 = 18 else: 最小齒數 = 12 # 直接設最小齒數 if 小齒輪齒數 <= 最小齒數: 小齒輪齒數 = 最小齒數 # 大於400的齒數則視為齒條(Rack) if 小齒輪齒數 >= 400: 小齒輪齒數 = 400 # 根據所選用的材料查詢強度值 # 由 material之序號查 steel 表以得材料之降伏強度S單位為 kpsi 因此查得的值要成乘上1000 # 利用 Store 建立資料庫檔案對應物件, 並且設定 frozen=True 表示不要開放動態資料表的建立 #SQLite連結 = Store(SQLiteWriter("lewis.db", frozen=True)) # 指定 steel 資料表 steel = SQLite連結.new("steel") # 資料查詢 # 將 unsno 與 treatment 從材料字串中隔開 unsno, treatment = 材料.split("_", 1) #print(unsno, treatment) treatment = treatment.replace("_", " ") #print(treatment) material = SQLite連結.find_one("steel","unsno=? and treatment=?",[unsno, treatment]) # 列出 steel 資料表中的資料筆數 #print(SQLite連結.count("steel")) #print (material.yield_str) strengthstress = material.yield_str*1000 # 由小齒輪的齒數與齒形類別,查詢lewis form factor # 先查驗是否有直接對應值 on_table = SQLite連結.count("lewis","gearno=?",[小齒輪齒數]) if on_table == 1: # 直接進入設計運算 #print("直接運算") #print(on_table) lewis_factor = SQLite連結.find_one("lewis","gearno=?",[小齒輪齒數]) #print(lewis_factor.type1) # 根據齒形查出 formfactor 值 if(齒形 == 1): formfactor = lewis_factor.type1 elif(齒形 == 2): formfactor = lewis_factor.type2 elif(齒形 == 3): formfactor = lewis_factor.type3 else: formfactor = lewis_factor.type4 else: # 沒有直接對應值, 必須進行查表內插運算後, 再執行設計運算 #print("必須內插") #print(interpolation(小齒輪齒數, 齒形)) formfactor = interpolation(小齒輪齒數, 齒形) # 開始進行設計運算 ngear = 小齒輪齒數 * 減速比 # 重要的最佳化設計---儘量用整數的diametralpitch # 先嘗試用整數算若 diametralpitch 找到100 仍無所獲則改用 0.25 作為增量再不行則宣告 fail counter = 0 i = 0.1 facewidth = 0 circularpitch = 0 while (facewidth <= 3 * circularpitch or facewidth >= 5 * circularpitch): diametralpitch = i #circularpitch = 3.14159/diametralpitch circularpitch = math.pi/diametralpitch pitchdiameter = 小齒輪齒數/diametralpitch #pitchlinevelocity = 3.14159*pitchdiameter*轉速/12 pitchlinevelocity = math.pi * pitchdiameter * 轉速/12 transmittedload = 33000 * 馬力/pitchlinevelocity velocityfactor = 1200/(1200 + pitchlinevelocity) # formfactor is Lewis form factor # formfactor need to get from table 13-3 and determined ty teeth number and type of tooth # formfactor = 0.293 # 90 is the value get from table corresponding to material type facewidth = transmittedload * diametralpitch * 安全係數/velocityfactor/formfactor/strengthstress if(counter>5000): print("超過5000次的設計運算,仍無法找到答案!") print("可能所選用的傳遞功率過大,或無足夠強度的材料可以使用!") # 離開while迴圈 break i += 0.1 counter += 1 facewidth = round(facewidth, 4) if(counter<5000): print("進行"+str(counter)+"次重複運算後,得到合用的facewidth值為:"+str(facewidth)) # 執行正齒輪齒面寬的設計運算 #gear_width(馬力, 轉速, 減速比, 齒形, 安全係數, 材料, 小齒輪齒數) # 執行輸入檔案的解讀輸入檔案 = open('design_input.txt', encoding="UTF-8") # 開檔案的內建模式為 read # 先將數字檔案中各行資料打包成為 list 輸入= [] while True: # readline() 讀取單行 # readlines() 讀取多行, 並放入串列資料格式中各行資料 = 輸入檔案.readline() #print(各行資料,end="") # 以下兩行判斷式在確定檔案讀到最後一行後就會跳出 while 迴圈, 不會無限執行 if len(各行資料) == 0: # 若該行的字數為 0, 表示已經到底 break # 去掉各行最後面的跳行符號各行資料 = 各行資料.rstrip() #print(各行資料,end="") # 依照資料的區隔符號 "\t" 將各行資料拆開, 並且存為 list, 到這裡各行資料為 list 各行資料 = 各行資料.split("\t") ''' # 取得設計參數馬力 = 100 轉速 = 1120 減速比 = 4 齒形 = 4 安全係數 = 3 #unsno_treatment 材料 = "G10350_CD" 小齒輪齒數 = 18 ''' 馬力 = int(各行資料[0]) 轉速 = int(各行資料[1]) 減速比 = float(各行資料[2]) 齒形 = int(各行資料[3]) 安全係數 = float(各行資料[4]) 材料 = 各行資料[5] 小齒輪齒數 = int(各行資料[6]) gear_width(馬力, 轉速, 減速比, 齒形, 安全係數, 材料, 小齒輪齒數) # 可以將各行資料印出檢查 #print(各行資料) # 將各行資料數列再疊成數字 list #輸入.append(各行資料) #print(輸入) # 取得各行輸入值後, 再呼叫 gear_width 執行齒面寬的設計運算輸入檔案.close()

[ "chiamingyen@gmail.com" ]

chiamingyen@gmail.com

5cfb3d0d5e2118c2eb69149f2e71449e382566cd

8d014a0120864b42748ef63dddfa3c733370118c

/layint_api/models/clair_layer.py

930dd8c648cdb805eef50bded4091bd69bb4939c

[ "Apache-2.0", "LicenseRef-scancode-unknown" ]

permissive

LayeredInsight/layint_api_python

3a6cf0bf62219f09010b828d7e02c2f3852a6f6f

a5c9a5b24098bd823c5102b7ab9e4745432f19b4

refs/heads/develop

2020-03-27T05:43:35.831400

2018-10-15T22:28:54

146,044,385

0

Apache-2.0

2018-10-15T22:28:55

2018-08-24T22:11:08

Python

UTF-8

Python

false

7,525

py

# coding: utf-8 """ Layered Insight Assessment, Compliance, Witness & Control LI Assessment & Compliance performs static vulnerability analysis, license and package compliance. LI Witness provides deep insight and analytics into containerized applications. Control provides dynamic runtime security and analytics for containerized applications. You can find out more about the Layered Insight Suite at [http://layeredinsight.com](http://layeredinsight.com). OpenAPI spec version: 0.10 Contact: help@layeredinsight.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from pprint import pformat from six import iteritems import re class ClairLayer(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { 'name': 'str', 'namespace_name': 'str', 'path': 'str', 'parent_name': 'str', 'format': 'str', 'indexed_by_version': 'int', 'features': 'list[ClairFeature]' } attribute_map = { 'name': 'Name', 'namespace_name': 'NamespaceName', 'path': 'Path', 'parent_name': 'ParentName', 'format': 'Format', 'indexed_by_version': 'IndexedByVersion', 'features': 'Features' } def __init__(self, name=None, namespace_name=None, path=None, parent_name=None, format=None, indexed_by_version=None, features=None): """ ClairLayer - a model defined in Swagger """ self._name = None self._namespace_name = None self._path = None self._parent_name = None self._format = None self._indexed_by_version = None self._features = None if name is not None: self.name = name if namespace_name is not None: self.namespace_name = namespace_name if path is not None: self.path = path if parent_name is not None: self.parent_name = parent_name if format is not None: self.format = format if indexed_by_version is not None: self.indexed_by_version = indexed_by_version if features is not None: self.features = features @property def name(self): """ Gets the name of this ClairLayer. Machine name of layer :return: The name of this ClairLayer. :rtype: str """ return self._name @name.setter def name(self, name): """ Sets the name of this ClairLayer. Machine name of layer :param name: The name of this ClairLayer. :type: str """ self._name = name @property def namespace_name(self): """ Gets the namespace_name of this ClairLayer. Name of namespace of this layer :return: The namespace_name of this ClairLayer. :rtype: str """ return self._namespace_name @namespace_name.setter def namespace_name(self, namespace_name): """ Sets the namespace_name of this ClairLayer. Name of namespace of this layer :param namespace_name: The namespace_name of this ClairLayer. :type: str """ self._namespace_name = namespace_name @property def path(self): """ Gets the path of this ClairLayer. :return: The path of this ClairLayer. :rtype: str """ return self._path @path.setter def path(self, path): """ Sets the path of this ClairLayer. :param path: The path of this ClairLayer. :type: str """ self._path = path @property def parent_name(self): """ Gets the parent_name of this ClairLayer. Parent of this layer - reference to container :return: The parent_name of this ClairLayer. :rtype: str """ return self._parent_name @parent_name.setter def parent_name(self, parent_name): """ Sets the parent_name of this ClairLayer. Parent of this layer - reference to container :param parent_name: The parent_name of this ClairLayer. :type: str """ self._parent_name = parent_name @property def format(self): """ Gets the format of this ClairLayer. :return: The format of this ClairLayer. :rtype: str """ return self._format @format.setter def format(self, format): """ Sets the format of this ClairLayer. :param format: The format of this ClairLayer. :type: str """ self._format = format @property def indexed_by_version(self): """ Gets the indexed_by_version of this ClairLayer. :return: The indexed_by_version of this ClairLayer. :rtype: int """ return self._indexed_by_version @indexed_by_version.setter def indexed_by_version(self, indexed_by_version): """ Sets the indexed_by_version of this ClairLayer. :param indexed_by_version: The indexed_by_version of this ClairLayer. :type: int """ self._indexed_by_version = indexed_by_version @property def features(self): """ Gets the features of this ClairLayer. :return: The features of this ClairLayer. :rtype: list[ClairFeature] """ return self._features @features.setter def features(self, features): """ Sets the features of this ClairLayer. :param features: The features of this ClairLayer. :type: list[ClairFeature] """ self._features = features def to_dict(self): """ Returns the model properties as a dict """ result = {} for attr, _ in iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """ Returns the string representation of the model """ return pformat(self.to_dict()) def __repr__(self): """ For `print` and `pprint` """ return self.to_str() def __eq__(self, other): """ Returns true if both objects are equal """ if not isinstance(other, ClairLayer): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """ Returns true if both objects are not equal """ return not self == other

[ "Scott Oberg" ]

Scott Oberg

2b8ef6e4ddfe11306702678e9a8e5c00eac0656c

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p02901/s181974865.py

e2137c4696abe05b40a7101f829d7767622b0d43

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

UTF-8

Python

false

442

py

N, M = map(int, input().split()) key = [] for _ in range(M): a, b = map(int, input().split()) s = 0 C = list(map(lambda x:int(x)-1, input().split())) for c in C: s |= 1<<c key += [(s, a)] dp = [float('inf')]*(1<<N) dp[0] = 0 for s in range(1<<N): for i in range(M): t = s | key[i][0] # 遷移先 cost = dp[s] + key[i][1] dp[t] = min(dp[t], cost) if dp[-1] == float('inf'): print(-1) else: print(dp[-1])

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

e9cac985d19977a538b2f9e0a5dcdfd6c2452669

971300f5983692e12805805dd49e2f77fa20250f

/src/branches/dae_dtalite_integration/core/models/abstract_regression_model.py

9648228c09e3b79b4c09baf452bbfcb9febf81a4

[]

no_license

MAlbertini95/simtravel

3a18ee302f6d9ab676455caaad15461874a698a9

4844927243a854b9a93f1b1d93f795ff116a7212

refs/heads/master

2021-04-19T03:04:26.752252

2014-07-12T00:50:11

null

0

null

UTF-8

Python

false

5,342

py

from numpy import all, array, zeros from scipy import exp from openamos.core.models.abstract_model import Model from openamos.core.errors import SpecificationError, ErrorSpecificationError class AbstractRegressionModel(Model): def __init__(self, specification, error_specification): """ This is the base class for all regression based mathematical formulations in OpenAMOS Inputs: specification - Specification object error_specifciation - ErrorSpecification object """ Model.__init__(self, specification) if not isinstance(self.specification, Specification): raise SpecificationError, """specification input is not a """\ """valid Specification object""" self.error_specification = error_specification if specification.number_choices > 1: raise SpecificationError, """invalid specification for regression """\ """ model only one equation needs to be specified""" if not isinstance(self.error_specification, ErrorSpecification): raise ErrorSpecificationError, """invalid error specification"""\ """ it should be of type ErrorSpecification""" def calc_expected_value(self, data): """ The method returns the expected values for the different choices using the coefficients specified in the specification input. Inputs: data - DataArray object """ return self.calculate_expected_values(data) def calc_exp_expected_value(self, data): """ The method returns the exponent of the expected values for the different choices using the coefficients specified in the specification input. Inputs: data - DataArray object """ return self.calculate_exp_expected_values(data) def calc_errorcomponent(self): """ The method returns the contribution of the error in the calculation of the predicted value for the different choices. Inputs: None """ raise Exception('method not implemented') def calc_predvalue(self): """ The method returns the predicted value for the different choices in the specification input. Inputs: None """ raise Exception('method not implemented') import unittest from openamos.core.data_array import DataArray from openamos.core.models.model_components import Specification from openamos.core.models.error_specification import ErrorSpecification class TestBadSpecificationRegressionModel(unittest.TestCase): def setUp(self): choices = ['SOV', 'HOV'] coefficients = [{'Constant':2, 'Var1':2.11}, {'Constant':1.2}] data = array([[1, 1.1], [1, -0.25], [1, 3.13], [1, -0.11]]) variance = array([[1.1]]) variance1 = array([[1.1, 1.2], [2.1, 2.2]]) self.data = DataArray(data, ['Constant', 'VAR1']) self.specification = Specification(choices, coefficients) self.errorspecification = ErrorSpecification(variance, 'normal') self.errorspecification1 = ErrorSpecification(variance1, 'normal') def testtwodependentvars(self): self.assertRaises(SpecificationError, AbstractRegressionModel, self.specification, self.errorspecification) def testtwoerrorcomponents(self): self.assertRaises(SpecificationError, AbstractRegressionModel, self.specification, self.errorspecification1) class TestAbstractRegressionModel(unittest.TestCase): def setUp(self): choice = ['SOV'] coefficients = [{'constant':2, 'Var1':2.11}] data = array([[1, 1.1], [1, -0.25], [1, 3.13], [1, -0.11]]) variance = array([[1.1]]) self.data = DataArray(data, ['Constant', 'VaR1']) self.specification = Specification(choice, coefficients) self.errorspecification = ErrorSpecification(variance, 'normal') def testvalues(self): model = AbstractRegressionModel(self.specification, self.errorspecification) model_expected_values = model.calc_expected_value(self.data) expected_act = zeros((self.data.rows, 1)) expected_act[:,0] = self.data.data[:,0] * 2 + self.data.data[:,1] * 2.11 expected_diff = all(expected_act == model_expected_values.data) self.assertEqual(True, expected_diff) exp_expected_act = exp(expected_act) model_exp_expected_values = model.calc_exp_expected_value(self.data) exp_expected_diff = all(exp_expected_act == model_exp_expected_values.data) self.assertEqual(True, exp_expected_diff) def testerrorspecification(self): #TODO:Write the tests for errorspecification if any in here #or should they just be written in the specifica implementations #e.g. stochastic-frontier, linear regression etc. pass if __name__ == '__main__': unittest.main()

[ "karthik.charan@8e946292-11aa-11df-992a-f3fa5211fe9f" ]

karthik.charan@8e946292-11aa-11df-992a-f3fa5211fe9f

86b0d00083516ac574501614cf84a7ab1f14f983

25b2daa09d3994672936231b7949ad60292fd052

/apps/cart/forms.py

7c4ace067207ccb673e8085d0db87a30f6253f02

[]

no_license

pavelm2007/shop

c1896145e3b3c43fd25c32e0e39697b6cbacadc9

979bbdfd51c53f1757e1cc5646e61bd71e8fce40

refs/heads/master

2021-01-25T10:29:50.502933

2014-05-15T07:54:07

null

0

null

UTF-8

Python

false

3,570

py

# -*- coding: utf-8 -*- from django import forms from django.forms.models import inlineformset_factory from django.contrib.contenttypes.models import ContentType from django.template.defaultfilters import striptags from .models import Order, OrderItem, Contact_info BASKET_OPTIONS_USE_KEEP = False class OrderItemForm(forms.ModelForm): class Meta: model = OrderItem content_type = forms.ModelChoiceField(queryset=ContentType.objects.all(), widget=forms.HiddenInput) object_id = forms.IntegerField(widget=forms.HiddenInput) if BASKET_OPTIONS_USE_KEEP: keep = forms.BooleanField(initial=True, required=False) def save(self, *args, **kwargs): if BASKET_OPTIONS_USE_KEEP: if not self.cleaned_data.get('keep', False): self.cleaned_data['quantity'] = 0 self.instance.order.set_quantity(self.instance.content_object, self.cleaned_data.get('quantity', 0)) OrderFormset = inlineformset_factory(Order, OrderItem, extra=0, can_delete=False, form=OrderItemForm) class DefaultOrderForm(forms.ModelForm): # name = forms.CharField(label=u'Имя', max_length=100, required=True) # phone = forms.CharField(label=u'Телефон', max_length=100, required=True) # email = forms.CharField(label=u'E-mail', max_length=100, required=True) # comment = forms.CharField(label=u'Комментарий к заказу', max_length=255, # widget=forms.Textarea(), required=True) def __init__(self, *args, **kwargs): super(DefaultOrderForm, self).__init__(*args, **kwargs) self.fields['comment'].widget.attrs['cols'] = '35' self.fields['comment'].widget.attrs['rows'] = '5' for field in self.fields: self.fields[field].widget.attrs['class'] = 'filed-znach-text' if self.errors: # bf_errors = self.error_class(error for error in bf.errors]) # Escape and cache in local variable. for field, key in self.fields.iteritems(): error_text = u'' for i, j in self.errors.iteritems(): if field == i: error_text += unicode(striptags(j)) self.fields[field].initial = None # self.fields[field].widget.attrs['value'] = error_text self.fields[field].widget.attrs['placeholder'] = error_text class Meta: model = Contact_info exclude = ('order',) # class DefaultOrderForm(forms.Form): # name = forms.CharField(label=u'Имя', max_length=100,required=True) # phone = forms.CharField(label=u'Телефон', max_length=100,required=True) # email = forms.CharField(label=u'E-mail', max_length=100,required=True) # # address = forms.CharField(label=_('Delivery address'), max_length=255) # # contact_time = forms.CharField(label=_('Convenient time to call'), # # max_length=50, required=False) # comment = forms.CharField(label=u'Комментарий к заказу', max_length=255, # widget=forms.Textarea(), required=True) # # def __init__(self, request, *args, **kwargs): # super(DefaultOrderForm, self).__init__(*args, **kwargs) # self.fields['comment'].widget.attrs['cols'] = '35' # self.fields['comment'].widget.attrs['rows'] = '5' # for field in self.fields: # self.fields[field].widget.attrs['class'] = 'filed-znach-text'

[ "pavelm2007@yandex.ru" ]

pavelm2007@yandex.ru

3c34105bfa17f674e7bb3b8621bc4ceb8ae112b5

bb88122fc4978b14e8a9b02d8c11f1ce67ea17d0

/01_keras/keras31_cifar100_1_imshow.py

c2765b3208fba97f52169ea5492007275762cd5d

[]

no_license

star10919/Keras_

c2c8a6f3d0e1a7ceba9e81dbc51ecfd12bd5fe78

f3156b7db6e12feea075b46e94b09157f43a141c

refs/heads/main

2023-08-17T22:44:54.324315

2021-10-24T02:47:00

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from tensorflow.keras.datasets import cifar100 import numpy as np import matplotlib.pyplot as plt from icecream import ic (x_train, y_train), (x_test, y_test) = cifar100.load_data() ic(x_train.shape, y_train.shape) # (50000, 32, 32, 3), (50000, 1) ic(x_test.shape, y_test.shape) # (10000, 32, 32, 3), (10000, 1) ic(x_train[27]) print('y[27] 값 :', y_train[27]) # [52] plt.imshow(x_train[27]) plt.show()

[ "star10919@naver.com" ]

star10919@naver.com

1183fbfc216acc8a1e4f790c2cf4417f3125aa41

f694b37f548fe67656bf737073e0221e23b53dfb

/app/models.py

b29b69f52d28438d63166cea33e9228099faca9c

[]

no_license

itsumura-h/django_api_auth_sample

d92937834e79856b7956fddf174682d1d5bd22dc

4a3244c8a3471573f1f29c3a67ddf924f8649ed1

refs/heads/master

2020-05-25T18:51:40.285232

2019-05-22T01:08:54

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from django.db import models from django.contrib.auth.hashers import make_password from django.utils import timezone import hashlib # Create your models here. class User(models.Model): def __str__(self): return str(self.name) name = models.CharField(max_length=255) password = models.CharField(max_length=255) email = models.CharField(max_length=255, blank=True, null=True) tel = models.CharField(max_length=255, blank=True, null=True) is_studio = models.BooleanField(default=0) class Meta: db_table = 'users' verbose_name_plural = 'user' def save(self, *args, **kwargs): self.password = make_password(self.password) #パスワード暗号化 super().save(*args, **kwargs) class LoginToken(models.Model): def __str__(self): # メールアドレスとアクセス日時、トークンが見えるようにする dt = timezone.localtime(self.access_datetime).strftime("%Y/%m/%d %H:%M:%S") return self.user.email + '(' + dt + ') - ' + self.token user = models.ForeignKey(User, on_delete=models.CASCADE) token = models.CharField(max_length=40) #トークン access_datetime = models.DateTimeField() #アクセス日時 class Meta: db_table = 'tokens' verbose_name_plural = 'token' @staticmethod def create(user: User): # ユーザの既存のトークンを取得 if LoginToken.objects.filter(user=user).exists(): # トークンが既に存在している場合は削除する LoginToken.objects.get(user=user).delete() # トークン生成（メールアドレス + パスワード + システム日付のハッシュ値とする） dt = timezone.now() str = user.email + user.password + dt.strftime('%Y%m%d%H%M%S%f') hash = hashlib.sha1(str.encode('utf-8')).hexdigest() # utf-8でエンコードしないとエラーになる # トークンをデータベースに追加 token = LoginToken.objects.create( user = user, token = hash, access_datetime = dt) return token class Group(models.Model): owner_id = models.ForeignKey(User, on_delete=models.PROTECT) class Meta: db_table = 'groups' verbose_name_plural = 'group' class GroupUser(models.Model): group = models.ForeignKey(Group, on_delete=models.PROTECT) user = models.ForeignKey(User, on_delete=models.PROTECT) class Meta: db_table = 'group_users' verbose_name_plural = 'group_user' class Studio(models.Model): def __str__(self): return str(self.name) name = models.CharField(max_length=255) prefecture = models.CharField(max_length=255) city = models.CharField(max_length=255) address = models.CharField(max_length=255) gps = models.CharField(max_length=255, blank=True, null=True) user = models.ForeignKey(User, on_delete=models.PROTECT) class Meta: db_table = 'studios' verbose_name_plural = 'studio' class Room(models.Model): def __str__(self): return str(self.name) name = models.CharField(max_length=255) wide = models.IntegerField(blank=True, null=True) capacity = models.IntegerField(blank=True, null=True) studio = models.ForeignKey(Studio, on_delete=models.PROTECT) class Meta: db_table = 'rooms' verbose_name_plural = 'room' class Current(models.Model): member_no = models.IntegerField(blank=True, null=True) user = models.ForeignKey(User, on_delete=models.PROTECT) studio = models.ForeignKey(Studio, on_delete=models.PROTECT) class Meta: db_table = 'currents' verbose_name_plural = 'current' class Booking(models.Model): user = models.ForeignKey(User, on_delete=models.PROTECT) room = models.ForeignKey(Room, on_delete=models.PROTECT) group = models.ForeignKey(Group, on_delete=models.PROTECT) start = models.DateTimeField() end = models.DateTimeField() class Meta: db_table = 'bookings' verbose_name_plural = 'booking' class EquipmentKind(models.Model): def __str__(self): return str(self.name) name = models.CharField(max_length=255) class Meta: db_table = 'equipment_kinds' verbose_name_plural = 'equipment_kind' class Equipment(models.Model): def __str__(self): return str(self.name) name = models.CharField(max_length=255) kind = models.ForeignKey(EquipmentKind, on_delete=models.PROTECT) room = models.ForeignKey(Room, on_delete=models.PROTECT) class Meta: db_table = 'equipments' verbose_name_plural = 'equipment'

[ "dumblepy@gmail.com" ]

dumblepy@gmail.com

610035bce67bfdabe6c21fe5bf50792c3954ccad

f02eb256fdaf94bc7fc8e2d7ecb7352b98eaf494

/tests/test_save_reload_user.py

a0d68fd0753ad0addf27d58d3cb85bc80ff0f58f

[]

no_license

andres0191/AirBnB_clone

b98c4ef70c5f933154367557fc4026a2ce4e258a

818e60d89939650a2962164690987a0703792ef5

refs/heads/master

2021-01-03T23:58:42.569557

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#!/usr/bin/python3 from models.engine.file_storage import FileStorage from models.base_model import BaseModel from models.user import User storage = FileStorage() storage.reload() all_objs = storage.all() print("-- Reloaded objects --") for obj_id in all_objs.keys(): obj = all_objs[obj_id] print(obj) print("-- Create a new User --") my_user = User() my_user.first_name = "Betty" my_user.last_name = "Holberton" my_user.email = "airbnb@holbertonshool.com" my_user.password = "root" my_user.save() print(my_user) print("-- Create a new User 2 --") my_user2 = User() my_user2.first_name = "John" my_user2.email = "airbnb2@holbertonshool.com" my_user2.password = "root" my_user2.save() print(my_user2)

[ "jodia.ms@outlook.com" ]

jodia.ms@outlook.com

fc1aed88264779358eff660f119563fd54d8a910

ae3abdd710878d79e60b1f1c56c5cd394ab511f4

/scripts/ajive_analysis.py

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[]

no_license

idc9/breast_cancer_image_analysis

0eee6c7d796aabde8a447085996e32563acf6bd1

4a4af9d6b55b3ca38b26111d0f55af89a48b1282

refs/heads/master

2020-11-27T14:22:07.967478

2020-04-13T23:51:53

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import os from joblib import dump import matplotlib.pyplot as plt from jive.AJIVE import AJIVE from explore.BlockBlock import BlockBlock from explore.Base import Union from cbcs_joint.load_analysis_data import load_analysis_data from cbcs_joint.viz_utils import savefig, mpl_noaxis from cbcs_joint.Paths import Paths # make directories for saved results os.makedirs(os.path.join(Paths().results_dir, 'data'), exist_ok=True) os.makedirs(os.path.join(Paths().results_dir, 'common', 'loadings'), exist_ok=True) os.makedirs(os.path.join(Paths().results_dir, 'genetic_indiv', 'loadings'), exist_ok=True) os.makedirs(os.path.join(Paths().results_dir, 'image_indiv'), exist_ok=True) # load pre-computed data e.g. patch features data = load_analysis_data(load_patch_feats=False) subj_img_feats = data['subj_img_feats'] genes = data['genes'] clinical_data = data['clinical_data'] # initial signal ranks determined from PCA scree plots init_signal_ranks = {'images': 81, 'genes': 30} # run AJIVE ajive = AJIVE(init_signal_ranks=init_signal_ranks, n_wedin_samples=1000, n_randdir_samples=1000, zero_index_names=False, n_jobs=-1, store_full=False) ajive = ajive.fit({'images': subj_img_feats, 'genes': genes}) dump(ajive, os.path.join(Paths().results_dir, 'data', 'fit_ajive')) ##################### # AJIVE diagnostics # ##################### # diagnostic plot plt.figure(figsize=[10, 10]) ajive.plot_joint_diagnostic() savefig(os.path.join(Paths().results_dir, 'ajive_diagnostic.png')) ####################### # plot PAM50 loadings # ####################### # set visualization configs mpl_noaxis(labels=True) n_genes = 50 inches = 5 height_scale = n_genes // 25 load_figsize = (inches, height_scale * inches) # common loadings load_dir = os.path.join(Paths().results_dir, 'common', 'loadings') os.makedirs(load_dir, exist_ok=True) for r in range(ajive.common.rank): plt.figure(figsize=load_figsize) ajive.blocks['genes'].plot_common_loading(r) plt.title('common component {}'.format(r + 1)) savefig(os.path.join(load_dir, 'loadings_comp_{}.png'.format(r + 1))) # genetic individual loadings load_dir = os.path.join(Paths().results_dir, 'genetic_indiv', 'loadings') os.makedirs(load_dir, exist_ok=True) n_indiv_comps = min(5, ajive.blocks['genes'].individual.rank) for r in range(n_indiv_comps): plt.figure(figsize=load_figsize) ajive.blocks['genes'].individual.plot_loading(r) plt.title('genetic individual component {}'.format(r + 1)) savefig(os.path.join(load_dir, 'loadings_comp_{}.png'.format(r + 1))) ######################################### # compare AJIVE scores to clinical data # ######################################### # see documentation of explore package # BlockBlock compares all variables from one block (AJIVE scores) to # all variables of another block (clinical variables) # and adjusts for multiple testing comparision_kws = {'alpha': 0.05, 'multi_test': 'fdr_bh', 'cat_test': 'auc', # equivalent to a Mann-Whitney test 'multi_cat': 'ovo', 'nan_how': 'drop'} common_scd = BlockBlock(**comparision_kws) common_scd.fit(ajive.common.scores(norm=True), clinical_data) gene_indiv_scd = BlockBlock(**comparision_kws) gene_indiv_scd = gene_indiv_scd.\ fit(ajive.blocks['genes'].individual.scores_.iloc[:, 0:5], clinical_data) image_indiv_scd = BlockBlock(**comparision_kws) image_indiv_scd = BlockBlock().\ fit(ajive.blocks['images'].individual.scores_.iloc[:, 0:5], clinical_data) all_tests = Union().add_tests([('common', common_scd), ('gene_indiv', gene_indiv_scd), ('image_indiv', image_indiv_scd)]) all_tests.correct_multi_tests() dump(all_tests, os.path.join(Paths().results_dir, 'data', 'clinical_data_comparisions')) inches = 6 # common n_row, n_col = common_scd.comparisons_.shape plt.figure(figsize=(inches * n_col, inches * n_row)) common_scd.plot() savefig(os.path.join(Paths().results_dir, 'common', 'cns_vs_clinical_data.png'), dpi=100) # genetic individual n_row, n_col = gene_indiv_scd.comparisons_.shape plt.figure(figsize=(inches * n_col, inches * n_row)) gene_indiv_scd.plot() savefig(os.path.join(Paths().results_dir, 'genetic_indiv', 'genetic_indiv_vs_clinical_data.png'), dpi=100) # image individual n_row, n_col = image_indiv_scd.comparisons_.shape plt.figure(figsize=(inches * n_col, inches * n_row)) image_indiv_scd.plot() savefig(os.path.join(Paths().results_dir, 'image_indiv', 'image_indiv_vs_clinical_data.png'), dpi=100)

[ "idc9@cornell.edu" ]

idc9@cornell.edu

93278531bd2f7b0295e3a883583124b4e66288e2

c0385ff098c71e6b9e9883e5e0b1a23d6ddee30a

/src/apps/accounts/urls.py

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[ "MIT" ]

permissive

ehoversten/Travel-Buddy

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refs/heads/master

2022-12-11T08:35:16.098525

2020-08-10T18:11:40

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from django.conf.urls import url from .views import ( register_view, LoginFormView ) urlpatterns = [ url(r'^$', LoginFormView.as_view(), name='login'), # url(r'^$', login_view, name='login'), url(r'^register/$', register_view, name='register'), ]

[ "sixgg4@gmail.com" ]

sixgg4@gmail.com

088de244f3f420206a51d57f323c763474709895

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/to_nwb/extensions/general/gen_yaml.py

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[ "BSD-3-Clause" ]

permissive

deeptimittal12/to_nwb

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refs/heads/master

2021-05-19T13:12:45.463079

2019-06-19T22:09:02

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BSD-3-Clause

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from pynwb.spec import NWBDatasetSpec, NWBNamespaceBuilder, NWBGroupSpec, \ NWBAttributeSpec namespace = 'general' ns_path = namespace + '.namespace.yaml' ext_source = namespace + '.extensions.yaml' values = NWBAttributeSpec(name='values', dtype='text', doc='values that the indices are indexing', shape=(None,)) cat_cell_info = NWBGroupSpec( neurodata_type_def='CatCellInfo', doc='Categorical Cell Info', attributes=[NWBAttributeSpec( name='help', doc='help', dtype='text', value='Categorical information about cells. For most cases the units tables is more appropriate. This ' 'structure can be used if you need multiple entries per cell')], datasets=[ NWBDatasetSpec(doc='global id for neuron', shape=(None,), name='cell_index', dtype='int', quantity='?'), NWBDatasetSpec(name='indices', doc='list of indices for values', shape=(None,), dtype='int', attributes=[values])], neurodata_type_inc='NWBDataInterface') cat_timeseries = NWBGroupSpec( neurodata_type_def='CatTimeSeries', neurodata_type_inc='TimeSeries', doc='Categorical data through time', datasets=[NWBDatasetSpec(name='data', shape=(None,), dtype='int', doc='timeseries of indicies for values', attributes=[values])]) ns_builder = NWBNamespaceBuilder(doc=namespace + ' extensions', name=namespace, version='1.0', author='Ben Dichter', contact='bendichter@gmail.com') for spec in (cat_cell_info, cat_timeseries): ns_builder.add_spec(ext_source, spec) ns_builder.export(ns_path)

[ "ben.dichter@gmail.com" ]

ben.dichter@gmail.com

bde00068d71ed1c31ca61ddb9cd7e7d3d39ec8d1

aff774e066b5db7fdefa4ca9c760b55fc80a678e

/modelrunner/redis_utils.py

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[]

no_license

piensa/modelrunner

3e965d75f2401ace5e7ac931da64b4794e0d1d96

385e1e01a8007e156855495393d57a1403ec72b2

refs/heads/master

2020-03-18T14:56:37.852622

2019-02-04T22:16:05

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# -*- coding: utf-8 -*- """ functions associated with implementing modelrunner 'protocol' via Redis command dicts are serialized as json """ import logging from .utils import json_dumps_datetime, json_loads_datetime # setup log logger = logging.getLogger('modelrunner') def pop_command(redis_conn, queue_name, timeout=0): """ *Blocking* Waits for command on redis queue timeout: if 0, wait forever for item on queue, else seconds to timeout Returns command dict or None if timeout """ result = redis_conn.blpop(queue_name, timeout=timeout) if result is None: # timedout return None command_dict = json_loads_datetime(result[1]) return command_dict def enqueue_command(redis_conn, queue_name, command_dict): """ enqueue command on redis queue """ logger.info( "adding command {} to queue {}". format(command_dict, queue_name)) redis_conn.rpush(queue_name, json_dumps_datetime(command_dict)) def remove_command(redis_conn, queue_name, command_dict): """ find and remove all matching commands from queue """ result = redis_conn.lrange(queue_name, 0, -1) matches = filter(lambda d: d == command_dict, [json_loads_datetime(item) for item in result]) for match in matches: redis_conn.lrem(queue_name, 1, json_dumps_datetime(match)) def publish_command(redis_conn, channel_name, command_dict): """ publish a message to a channel """ redis_conn.publish(channel_name, json_dumps_datetime(command_dict)) def get_all_commands(redis_conn, queue_name): """ get all command_dicts on queue """ result = redis_conn.lrange(queue_name, 0, -1) return [json_loads_datetime(item) for item in result] def pubsub_listen(pubsub): """ generator that returns command_dict on subscribed pubsub object """ assert pubsub.subscribed for raw_message in pubsub.listen(): logger.info("message received {}".format(raw_message)) # assume we subscribed and throw away anything other than messages if raw_message is not None and raw_message['type'] == 'message': message_dict = json_loads_datetime(raw_message['data']) yield message_dict

[ "chris.natali@gmail.com" ]

chris.natali@gmail.com

8c347fbf4734a6975b4f15136fa2ac019f6ac964

e5d4d867e8369194e3519d795d57a6df81357c99

/exps/utils/quaternion.py

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hyperplane-lab/Generative-3D-Part-Assembly

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refs/heads/main

2023-05-06T20:15:26.504273

2021-05-27T13:18:18

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# Copyright (c) 2018-present, Facebook, Inc. # All rights reserved. # # This source code is licensed under the license found in the # LICENSE file in the root directory of this source tree. # import torch import numpy as np # PyTorch-backed implementations def qmul(q, r): """ Multiply quaternion(s) q with quaternion(s) r. Expects two equally-sized tensors of shape (*, 4), where * denotes any number of dimensions. Returns q*r as a tensor of shape (*, 4). """ assert q.shape[-1] == 4 assert r.shape[-1] == 4 original_shape = q.shape # Compute outer product terms = torch.bmm(r.view(-1, 4, 1), q.view(-1, 1, 4)) w = terms[:, 0, 0] - terms[:, 1, 1] - terms[:, 2, 2] - terms[:, 3, 3] x = terms[:, 0, 1] + terms[:, 1, 0] - terms[:, 2, 3] + terms[:, 3, 2] y = terms[:, 0, 2] + terms[:, 1, 3] + terms[:, 2, 0] - terms[:, 3, 1] z = terms[:, 0, 3] - terms[:, 1, 2] + terms[:, 2, 1] + terms[:, 3, 0] return torch.stack((w, x, y, z), dim=1).view(original_shape) def qrot(q, v): """ Rotate vector(s) v about the rotation described by quaternion(s) q. Expects a tensor of shape (*, 4) for q and a tensor of shape (*, 3) for v, where * denotes any number of dimensions. Returns a tensor of shape (*, 3). """ assert q.shape[-1] == 4 assert v.shape[-1] == 3 assert q.shape[:-1] == v.shape[:-1] original_shape = list(v.shape) q = q.view(-1, 4) v = v.view(-1, 3) qvec = q[:, 1:] uv = torch.cross(qvec, v, dim=1) uuv = torch.cross(qvec, uv, dim=1) return (v + 2 * (q[:, :1] * uv + uuv)).view(original_shape) def qeuler(q, order, epsilon=0): """ Convert quaternion(s) q to Euler angles. Expects a tensor of shape (*, 4), where * denotes any number of dimensions. Returns a tensor of shape (*, 3). """ assert q.shape[-1] == 4 original_shape = list(q.shape) original_shape[-1] = 3 q = q.view(-1, 4) q0 = q[:, 0] q1 = q[:, 1] q2 = q[:, 2] q3 = q[:, 3] if order == 'xyz': x = torch.atan2(2 * (q0 * q1 - q2 * q3), 1 - 2*(q1 * q1 + q2 * q2)) y = torch.asin(torch.clamp(2 * (q1 * q3 + q0 * q2), -1+epsilon, 1-epsilon)) z = torch.atan2(2 * (q0 * q3 - q1 * q2), 1 - 2*(q2 * q2 + q3 * q3)) elif order == 'yzx': x = torch.atan2(2 * (q0 * q1 - q2 * q3), 1 - 2*(q1 * q1 + q3 * q3)) y = torch.atan2(2 * (q0 * q2 - q1 * q3), 1 - 2*(q2 * q2 + q3 * q3)) z = torch.asin(torch.clamp(2 * (q1 * q2 + q0 * q3), -1+epsilon, 1-epsilon)) elif order == 'zxy': x = torch.asin(torch.clamp(2 * (q0 * q1 + q2 * q3), -1+epsilon, 1-epsilon)) y = torch.atan2(2 * (q0 * q2 - q1 * q3), 1 - 2*(q1 * q1 + q2 * q2)) z = torch.atan2(2 * (q0 * q3 - q1 * q2), 1 - 2*(q1 * q1 + q3 * q3)) elif order == 'xzy': x = torch.atan2(2 * (q0 * q1 + q2 * q3), 1 - 2*(q1 * q1 + q3 * q3)) y = torch.atan2(2 * (q0 * q2 + q1 * q3), 1 - 2*(q2 * q2 + q3 * q3)) z = torch.asin(torch.clamp(2 * (q0 * q3 - q1 * q2), -1+epsilon, 1-epsilon)) elif order == 'yxz': x = torch.asin(torch.clamp(2 * (q0 * q1 - q2 * q3), -1+epsilon, 1-epsilon)) y = torch.atan2(2 * (q1 * q3 + q0 * q2), 1 - 2*(q1 * q1 + q2 * q2)) z = torch.atan2(2 * (q1 * q2 + q0 * q3), 1 - 2*(q1 * q1 + q3 * q3)) elif order == 'zyx': x = torch.atan2(2 * (q0 * q1 + q2 * q3), 1 - 2*(q1 * q1 + q2 * q2)) y = torch.asin(torch.clamp(2 * (q0 * q2 - q1 * q3), -1+epsilon, 1-epsilon)) z = torch.atan2(2 * (q0 * q3 + q1 * q2), 1 - 2*(q2 * q2 + q3 * q3)) else: raise return torch.stack((x, y, z), dim=1).view(original_shape) # Numpy-backed implementations def qmul_np(q, r): q = torch.from_numpy(q).contiguous() r = torch.from_numpy(r).contiguous() return qmul(q, r).numpy() def qrot_np(q, v): q = torch.from_numpy(q).contiguous() v = torch.from_numpy(v).contiguous() return qrot(q, v).numpy() def qeuler_np(q, order, epsilon=0, use_gpu=False): if use_gpu: q = torch.from_numpy(q).cuda() return qeuler(q, order, epsilon).cpu().numpy() else: q = torch.from_numpy(q).contiguous() return qeuler(q, order, epsilon).numpy() def qfix(q): """ Enforce quaternion continuity across the time dimension by selecting the representation (q or -q) with minimal distance (or, equivalently, maximal dot product) between two consecutive frames. Expects a tensor of shape (L, J, 4), where L is the sequence length and J is the number of joints. Returns a tensor of the same shape. """ assert len(q.shape) == 3 assert q.shape[-1] == 4 result = q.copy() dot_products = np.sum(q[1:]*q[:-1], axis=2) mask = dot_products < 0 mask = (np.cumsum(mask, axis=0)%2).astype(bool) result[1:][mask] *= -1 return result def expmap_to_quaternion(e): """ Convert axis-angle rotations (aka exponential maps) to quaternions. Stable formula from "Practical Parameterization of Rotations Using the Exponential Map". Expects a tensor of shape (*, 3), where * denotes any number of dimensions. Returns a tensor of shape (*, 4). """ assert e.shape[-1] == 3 original_shape = list(e.shape) original_shape[-1] = 4 e = e.reshape(-1, 3) theta = np.linalg.norm(e, axis=1).reshape(-1, 1) w = np.cos(0.5*theta).reshape(-1, 1) xyz = 0.5*np.sinc(0.5*theta/np.pi)*e return np.concatenate((w, xyz), axis=1).reshape(original_shape) def euler_to_quaternion(e, order): """ Convert Euler angles to quaternions. """ assert e.shape[-1] == 3 original_shape = list(e.shape) original_shape[-1] = 4 e = e.reshape(-1, 3) x = e[:, 0] y = e[:, 1] z = e[:, 2] rx = np.stack((np.cos(x/2), np.sin(x/2), np.zeros_like(x), np.zeros_like(x)), axis=1) ry = np.stack((np.cos(y/2), np.zeros_like(y), np.sin(y/2), np.zeros_like(y)), axis=1) rz = np.stack((np.cos(z/2), np.zeros_like(z), np.zeros_like(z), np.sin(z/2)), axis=1) result = None for coord in order: if coord == 'x': r = rx elif coord == 'y': r = ry elif coord == 'z': r = rz else: raise if result is None: result = r else: result = qmul_np(result, r) # Reverse antipodal representation to have a non-negative "w" if order in ['xyz', 'yzx', 'zxy']: result *= -1 return result.reshape(original_shape)

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from __future__ import absolute_import, unicode_literals from .fields import StringField, FloatField, IntegerField, BaseField from .messages import BaseMessage EVENT_TYPES = {} def register_event(event_type): def register(cls): EVENT_TYPES[event_type] = cls return cls return register class BaseEvent(BaseMessage): type = 'event' event = '' @register_event('subscribe') class SubscribeEvent(BaseEvent): event = 'subscribe' @register_event('unsubscribe') class UnsubscribeEvent(BaseEvent): event = 'unsubscribe' @register_event('subscribe_scan') class SubscribeScanEvent(BaseEvent): event = 'subscribe_scan' scene_id = StringField('EventKey') ticket = StringField('Ticket') @register_event('scan') class ScanEvent(BaseEvent): event = 'scan' scene_id = StringField('EventKey') ticket = StringField('Ticket') @register_event('location') class LocationEvent(BaseEvent): event = 'location' latitude = FloatField('Latitude', 0.0) longitude = FloatField('Longitude', 0.0) precision = FloatField('Precision', 0.0) @register_event('click') class ClickEvent(BaseEvent): event = 'click' key = StringField('EventKey') @register_event('view') class ViewEvent(BaseEvent): event = 'view' url = StringField('EventKey') @register_event('masssendjobfinish') class MassSendJobFinishEvent(BaseEvent): event = 'masssendjobfinish' status = StringField('Status') total_count = IntegerField('TotalCount', 0) filter_count = IntegerField('FilterCount', 0) sent_count = IntegerField('SentCount', 0) error_count = IntegerField('ErrorCount', 0) @register_event('templatesendjobfinish') class TemplateSendJobFinishEvent(BaseEvent): event = 'templatesendjobfinish' status = StringField('Status') class BaseScanCodeEvent(BaseEvent): key = StringField('EventKey') scan_code_info = BaseField('ScanCodeInfo', {}) @property def scan_type(self): return self.scan_code_info['ScanType'] @property def scan_result(self): return self.scan_code_info['ScanResult'] @register_event('scancode_push') class ScanCodePushEvent(BaseScanCodeEvent): event = 'scancode_push' @register_event('scancode_waitmsg') class ScanCodeWaitMsgEvent(BaseScanCodeEvent): event = 'scancode_waitmsg' class BasePictureEvent(BaseEvent): key = StringField('EventKey') pictures_info = BaseField('SendPicsInfo', {}) @property def count(self): return int(self.pictures_info['Count']) @property def pictures(self): items = self.pictures_info['PicList']['item'] if self.count > 1: return items return [items] @register_event('pic_sysphoto') class PicSysPhotoEvent(BasePictureEvent): event = 'pic_sysphoto' @register_event('pic_photo_or_album') class PicPhotoOrAlbumEvent(BasePictureEvent): event = 'pic_photo_or_album' @register_event('pic_weixin') class PicWeChatEvent(BasePictureEvent): event = 'pic_weixin' @register_event('location_select') class LocationSelectEvent(BaseEvent): event = 'location_select' key = StringField('EventKey') location_info = BaseField('SendLocationInfo', {}) @property def location_x(self): return self.location_info['Location_X'] @property def location_y(self): return self.location_info['Location_Y'] @property def location(self): return self.location_x, self.location_y @property def scale(self): return self.location_info['Scale'] @property def label(self): return self.location_info['Label'] @property def poiname(self): return self.location_info['Poiname'] @register_event('card_pass_check') class CardPassCheckEvent(BaseEvent): event = 'card_pass_check' card_id = StringField('CardId') @register_event('card_not_pass_check') class CardNotPassCheckEvent(BaseEvent): event = 'card_not_pass_check' card_id = StringField('CardId') @register_event('user_get_card') class UserGetCardEvent(BaseEvent): event = 'user_get_card' card_id = StringField('CardId') is_given_by_friend = IntegerField('IsGiveByFriend') code = StringField('UserCardCode') @register_event('user_del_card') class UserDeleteCardEvent(BaseEvent): event = 'user_del_card' card_id = StringField('CardId') code = StringField('UserCardCode')

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messense@icloud.com

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/source/res/scripts/client/gui/scaleform/daapi/view/lobby/profile/ProfileSection.py

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[]

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TrenSeP/WorldOfTanks-Decompiled

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refs/heads/1.4.1

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2019-03-05T17:37:06

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# Python bytecode 2.7 (decompiled from Python 2.7) # Embedded file name: scripts/client/gui/Scaleform/daapi/view/lobby/profile/ProfileSection.py from helpers import dependency from helpers import i18n from gui.Scaleform.daapi.view.meta.ProfileSectionMeta import ProfileSectionMeta from gui.Scaleform.locale.PROFILE import PROFILE from gui.Scaleform.genConsts.PROFILE_DROPDOWN_KEYS import PROFILE_DROPDOWN_KEYS from skeletons.gui.lobby_context import ILobbyContext from skeletons.gui.shared import IItemsCache from soft_exception import SoftException class ProfileSection(ProfileSectionMeta): itemsCache = dependency.descriptor(IItemsCache) lobbyContext = dependency.descriptor(ILobbyContext) def __init__(self, *args): super(ProfileSection, self).__init__() self.__isActive = False self._battlesType = PROFILE_DROPDOWN_KEYS.ALL self._userName = args[0] self._userID = args[1] self._databaseID = args[2] self._selectedData = args[3] self._data = None self._dossier = None self.__needUpdate = False return def _populate(self): super(ProfileSection, self)._populate() self.requestDossier(self._battlesType) def _dispose(self): self._data = None self._dossier = None super(ProfileSection, self)._dispose() return def requestDossier(self, bType): self._battlesType = bType self.invokeUpdate() def onSectionActivated(self): pass def _dataProviderEntryAutoTranslate(self, key): return self._dataProviderEntry(key, i18n.makeString(PROFILE.profile_dropdown_labels(key))) @classmethod def _dataProviderEntry(cls, key, label): return {'key': key, 'label': label} @classmethod def _getTotalStatsBlock(cls, dossier): return dossier.getRandomStats() def __receiveDossier(self): if self.__isActive and self.__needUpdate: self.__needUpdate = False accountDossier = self.itemsCache.items.getAccountDossier(self._userID) self._sendAccountData(self._getNecessaryStats(accountDossier), accountDossier) def _getNecessaryStats(self, accountDossier=None): if accountDossier is None: accountDossier = self.itemsCache.items.getAccountDossier(self._userID) if self._battlesType == PROFILE_DROPDOWN_KEYS.ALL: data = self._getTotalStatsBlock(accountDossier) elif self._battlesType == PROFILE_DROPDOWN_KEYS.TEAM: data = accountDossier.getTeam7x7Stats() elif self._battlesType == PROFILE_DROPDOWN_KEYS.STATICTEAM: data = accountDossier.getRated7x7Stats() elif self._battlesType == PROFILE_DROPDOWN_KEYS.HISTORICAL: data = accountDossier.getHistoricalStats() elif self._battlesType == PROFILE_DROPDOWN_KEYS.FORTIFICATIONS: data = self._receiveFortDossier(accountDossier) elif self._battlesType == PROFILE_DROPDOWN_KEYS.FORTIFICATIONS_SORTIES: data = accountDossier.getFortSortiesStats() elif self._battlesType == PROFILE_DROPDOWN_KEYS.FORTIFICATIONS_BATTLES: data = accountDossier.getFortBattlesStats() elif self._battlesType == PROFILE_DROPDOWN_KEYS.COMPANY: data = accountDossier.getCompanyStats() elif self._battlesType == PROFILE_DROPDOWN_KEYS.CLAN: data = accountDossier.getGlobalMapStats() elif self._battlesType == PROFILE_DROPDOWN_KEYS.FALLOUT: data = accountDossier.getFalloutStats() elif self._battlesType == PROFILE_DROPDOWN_KEYS.RANKED: data = accountDossier.getRankedStats() elif self._battlesType == PROFILE_DROPDOWN_KEYS.EPIC_RANDOM: data = accountDossier.getEpicRandomStats() else: raise SoftException('ProfileSection: Unknown battle type: ' + self._battlesType) return data def _receiveFortDossier(self, accountDossier): return None def _sendAccountData(self, targetData, accountDossier): self._data = targetData self._dossier = accountDossier def setActive(self, value): self.__isActive = value self.__receiveDossier() def invokeUpdate(self): self._data = None self._dossier = None self.__needUpdate = True self.__receiveDossier() return @property def isActive(self): return self.__isActive def _formIconLabelInitObject(self, i18key, icon): return {'description': i18n.makeString(i18key), 'icon': icon}

[ "StranikS_Scan@mail.ru" ]

StranikS_Scan@mail.ru

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/clients/keto/python/test/test_ory_access_control_policy_roles.py

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permissive

simoneromano96/sdk

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# coding: utf-8 """ ORY Keto A cloud native access control server providing best-practice patterns (RBAC, ABAC, ACL, AWS IAM Policies, Kubernetes Roles, ...) via REST APIs. # noqa: E501 The version of the OpenAPI document: v0.0.0-alpha.1 Contact: hi@ory.sh Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import unittest import ory_keto_client from ory_keto_client.models.ory_access_control_policy_roles import OryAccessControlPolicyRoles # noqa: E501 from ory_keto_client.rest import ApiException class TestOryAccessControlPolicyRoles(unittest.TestCase): """OryAccessControlPolicyRoles unit test stubs""" def setUp(self): pass def tearDown(self): pass def testOryAccessControlPolicyRoles(self): """Test OryAccessControlPolicyRoles""" # FIXME: construct object with mandatory attributes with example values # model = ory_keto_client.models.ory_access_control_policy_roles.OryAccessControlPolicyRoles() # noqa: E501 pass if __name__ == '__main__': unittest.main()

[ "noreply@github.com" ]

simoneromano96.noreply@github.com

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/apps/recruitpro/recruitpro/projects/doctype/project/test_project.py

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sharmilaviji/RecruitPRO-NEW

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refs/heads/master

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2020-04-27T04:40:50

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# -*- coding: utf-8 -*- # Copyright (c) 2020, teampro and Contributors # See license.txt from __future__ import unicode_literals # import frappe import unittest class TestProject(unittest.TestCase): pass

[ "sharmiviji1997@gmail.com" ]

sharmiviji1997@gmail.com

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/shopstats/manage.py

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rajesh67/shopstats

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refs/heads/master

2021-01-10T04:53:59.464927

2016-01-15T16:37:21

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

[ "rajeshmeena.iitkgp@gmail.com" ]

rajeshmeena.iitkgp@gmail.com

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/python编程从入门到实践/第十七章/17-1/java_repos.py

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huanglun1994/learn

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refs/heads/master

2021-01-01T06:30:34.652264

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# -*- coding: utf-8 -*- """xxxxx""" __author__ = 'Huang Lun' import requests import pygal from pygal.style import LightColorizedStyle as LCS, LightenStyle as LS # 执行API调用并存储响应 url = 'https://api.github.com/search/repositories?q=language:java&sort=stars' r = requests.get(url) print('Status code: ', r.status_code) # 将API响应存储在一个变量中 response_dict = r.json() print('Total repositories: ', response_dict['total_count']) print('Total items: ', len(response_dict['items'])) # 研究有关仓库的信息 repo_dicts = response_dict['items'] names, plot_dicts = [], [] for repo_dict in repo_dicts: names.append(repo_dict['name']) plot_dict = {} plot_dict['value'] = repo_dict['stargazers_count'] if repo_dict['description']: plot_dict['label'] = repo_dict['description'] elif not repo_dict['description']: plot_dict['label'] = 'No description' plot_dict['xlink'] = repo_dict['html_url'] plot_dicts.append(plot_dict) # 可视化 my_style = LS('#333366', base_style=LCS) my_config = pygal.Config() my_config.x_label_rotation = 45 my_config.show_legend = False my_config.title_font_size = 24 my_config.label_font_size = 14 my_config.major_label_font_size = 16 my_config.truncate_label = 15 my_config.show_y_guides = False my_config.width = 1000 chart = pygal.Bar(my_config, style=my_style) chart.title = 'Most-Starred Java Projects on GitHub' chart.x_labels = names chart.add('', plot_dicts) chart.render_to_file('java_repos.svg')

[ "492593760@qq.com" ]

492593760@qq.com

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/book/_build/jupyter_execute/matplotlib/04_LinesAndMarkers.py

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[]

no_license

hossainlab/dataviz

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refs/heads/master

2023-07-20T01:42:47.144900

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#!/usr/bin/env python # coding: utf-8 # In[1]: import matplotlib import matplotlib.pyplot as plt import numpy as np matplotlib.interactive(True) plt.ion() matplotlib.is_interactive() # #### We start off with the previously seen sine curve # In[2]: x = np.linspace(start=0, stop=10, num=50) # In[3]: plt.plot(x, np.sin(x)) plt.show() # #### Having multiple plots in a pyplot # The colors of each plot is chosen by iterating over a color palette. The default palette is {'tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan'} # In[4]: plt.plot(x, np.sin(x), label='sine curve') plt.plot(x, np.cos(x), label='cosine curve') plt.legend() plt.title('Playing with Plots') plt.show() # #### Specifying colors # We pick the colors of green and magenta for the curves # * We have specified the full name of the green color # * Magenta has been specified in shorthand ('g' is short for green) <br /> # # The colors and codes for Matplotlib are here: # https://matplotlib.org/2.0.2/api/colors_api.html # # The full list of named colors is here: # https://matplotlib.org/examples/color/named_colors.html # In[5]: plt.plot(x, np.sin(x), label='sine curve', color='green') plt.plot(x, np.cos(x), label='cosine curve', color='m') plt.legend() plt.title('Playing with Plots') plt.show() # ### Formats for lines and markers # Line formats: https://matplotlib.org/gallery/lines_bars_and_markers/line_styles_reference.html <br /> # Marker formats: https://matplotlib.org/1.4.1/api/markers_api.html <br /> # #### Plots need not be lines # Start off by plotting a random array of 20 numbers # In[6]: random_array = np.random.randn(20) # In[7]: plt.plot(random_array, color='green') plt.show() # #### Line styles # We can have solid, dashed, dotted or dash-dot lines # In[8]: plt.plot(random_array, color='green', linestyle=':') plt.show() # In[9]: plt.plot(random_array, color='green', linestyle='--') plt.show() # #### Adjust the line width # The default is 1 # In[10]: plt.plot(random_array, color='green', linestyle='--', linewidth=3) plt.show() # #### We use markers to denote the points # The 'd' denotes small diamonds. For all the marker styles check out this page: <br /> # https://matplotlib.org/1.4.1/api/markers_api.html # In[11]: plt.plot(random_array, color='green', marker = 'd') plt.show() # #### Adjust the marker size # Default is 6 # In[12]: plt.plot(random_array, color='green', marker = 'd', markersize=10) plt.show() # #### Get rid of the line and use only markers # In[13]: plt.plot(random_array, color='green', marker = 'd', linestyle = 'None') plt.show() # #### Scatter plots # These are similar to regular plots but you need to specify the x coordinates. Below we create the same plot as above, but explicitly give the x coordinates as a list of 0-19 # In[14]: plt.scatter(range(0,20), random_array, color='green', marker = 'd') plt.show() # In[ ]:

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work.jubayer@gmail.com

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/test/vnx/resource/test_migration.py

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# coding=utf-8 # Copyright (c) 2015 EMC Corporation. # 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. from __future__ import unicode_literals from unittest import TestCase from hamcrest import assert_that, equal_to, instance_of, raises from storops.exception import VNXLunNotMigratingError from storops.vnx.resource.lun import VNXLun from test.vnx.cli_mock import t_cli, patch_cli from storops.vnx.enums import VNXMigrationRate from storops.vnx.resource.migration import VNXMigrationSession __author__ = 'Cedric Zhuang' class VNXMigrationSessionTest(TestCase): @patch_cli def test_properties(self): ms = VNXMigrationSession(0, t_cli()) assert_that(ms.source_lu_id, equal_to(0)) assert_that(ms.source_lu_name, equal_to('LUN 0')) assert_that(ms.dest_lu_id, equal_to(1)) assert_that(ms.dest_lu_name, equal_to('LUN 1')) assert_that(ms.migration_rate, equal_to(VNXMigrationRate.HIGH)) assert_that(ms.percent_complete, equal_to(50.0)) assert_that(ms.time_remaining, equal_to('0 second(s)')) assert_that(ms.current_state, equal_to('MIGRATING')) assert_that(ms.is_migrating, equal_to(True)) assert_that(ms.is_success, equal_to(False)) assert_that(ms.existed, equal_to(True)) @patch_cli def test_source_lun(self): ms = VNXMigrationSession(0, t_cli()) lun = ms.source_lun assert_that(lun, instance_of(VNXLun)) assert_that(lun.get_id(lun), equal_to(ms.source_lu_id)) @patch_cli def test_destination_lun(self): ms = VNXMigrationSession(0, t_cli()) lun = ms.destination_lun assert_that(lun, instance_of(VNXLun)) assert_that(lun.get_id(lun), equal_to(ms.dest_lu_id)) @patch_cli def test_get_all(self): ms_list = VNXMigrationSession.get(t_cli()) assert_that(len(ms_list), equal_to(2)) @patch_cli(output='migrate_-list_none.txt') def test_get_all_none(self): ms_list = VNXMigrationSession.get(t_cli()) assert_that(len(ms_list), equal_to(0)) @patch_cli def test_get_no_session(self): ms = VNXMigrationSession(10, t_cli()) assert_that(ms.existed, equal_to(False)) assert_that(ms.is_migrating, equal_to(False)) assert_that(ms.is_success, equal_to(True)) @patch_cli def test_get_lun_not_exists(self): ms = VNXMigrationSession(1234, t_cli()) assert_that(ms.existed, equal_to(False)) @patch_cli def test_cancel_migrate(self): def f(): ms = VNXMigrationSession(0, t_cli()) ms.cancel() assert_that(f, raises(VNXLunNotMigratingError, 'not currently migrating'))

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cedric.zhuang@emc.com

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/PA2/part1/linear_regression.py

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trademark152/Machine_Learning_CSCI567_USC

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2022-12-16T11:50:57.912882

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""" Do not change the input and output format. If our script cannot run your code or the format is improper, your code will not be graded. The only functions you need to implement in this template is linear_regression_noreg, linear_regression_invertible，regularized_linear_regression, tune_lambda, test_error and mapping_data. """ import numpy as np import pandas as pd ###### Q1.1 ###### def mean_square_error(w, X, y): """ Compute the mean squre error on test set given X, y, and model parameter w. Inputs: - X: A numpy array of shape (num_samples, D) containing test feature. - y: A numpy array of shape (num_samples, ) containing test label - w: a numpy array of shape (D, ) Returns: - err: the mean square error """ ##################################################### # TODO 1: Fill in your code here # ##################################################### # Calculate mean square error # MSE = 1/n * sum [(y_true-y_pred)^2] # Dimension: X: num_samples*D; y: num_samples err = np.mean(np.power(np.subtract(y, np.matmul(X,w)),2)) return err ###### Q1.2 ###### def linear_regression_noreg(X, y): """ Compute the weight parameter given X and y. Inputs: - X: A numpy array of shape (num_samples, D) containing feature. - y: A numpy array of shape (num_samples, ) containing label Returns: - w: a numpy array of shape (D, ) """ ##################################################### # TODO 2: Fill in your code here # ##################################################### # Closed form solution: w=(Xt*X)^-1*Xt*y # Covariance matrix covMat = np.matmul(np.transpose(X), X) # weight vector w = np.matmul(np.matmul(np.linalg.inv(covMat), np.transpose(X)),y) return w ###### Q1.3 ###### def linear_regression_invertible(X, y): """ Compute the weight parameter given X and y. Inputs: - X: A numpy array of shape (num_samples, D) containing feature. - y: A numpy array of shape (num_samples, ) containing label Returns: - w: a numpy array of shape (D, ) """ ##################################################### # TODO 3: Fill in your code here # ##################################################### # Number of dimensions dim = len(X[0]) # print(dim) # Covariance matrix covMat = np.matmul(np.transpose(X), X) # Find eigenvalues: eigVals = np.linalg.eigvals(covMat) # print(eigVals) # print(np.amin(np.absolute(eigVals))) if np.amin(np.absolute(eigVals)) >= 10**(-5): # weight vector return np.matmul(np.matmul(np.linalg.inv(covMat), np.transpose(X)), y) # If the smallest absolute value of any eigenvalue is smaller than 10^-5 # Consider matrix non-invertibale and start improving: k = 0 while np.amin(np.absolute(eigVals)) < 10**(-5): # solve issue of non-invertible (slides 29-31 csci567 lecture 3) k += 1 eigVals = np.linalg.eigvals(covMat+k*10**(-1)*np.identity(dim)) # print(k) return np.matmul(np.matmul(np.linalg.inv(covMat+k*(10**(-1))*np.identity(dim)), np.transpose(X)), y) ###### Q1.4 ###### def regularized_linear_regression(X, y, lambd): """ Compute the weight parameter given X, y and lambda. Inputs: - X: A numpy array of shape (num_samples, D) containing feature. - y: A numpy array of shape (num_samples, ) containing label - lambd: a float number containing regularization strength Returns: - w: a numpy array of shape (D, ) """ ##################################################### # TODO 4: Fill in your code here # ##################################################### # handle exception # if lambd == None: # lambd = 0. # Number of dimensions dim = len(X[0]) # print(dim) # Covariance matrix covMat = np.matmul(np.transpose(X), X) # # Find eigenvalues: # eigVals = np.linalg.eigvals(covMat) # # print(eigVals) # # print(np.amin(np.absolute(eigVals))) # # if matrix is invertible # if np.amin(np.absolute(eigVals)) >= 10**(-5): # # weight vector # return np.matmul(np.matmul(np.linalg.inv(covMat), np.transpose(X)), y) # # # If the smallest absolute value of any eigenvalue is smaller than 10^-5 # # Consider matrix non-invertibale and start improving: # else: # # solve issue of non-invertible (slides 50 csci567 lecture 3) # eigVals = np.linalg.eigvals(covMat+lambd*np.identity(dim)) return np.matmul(np.matmul(np.linalg.inv(covMat+lambd*np.identity(dim)), np.transpose(X)), y) ###### Q1.5 ###### def tune_lambda(Xtrain, ytrain, Xval, yval): """ Find the best lambda value. Inputs: - Xtrain: A numpy array of shape (num_training_samples, D) containing training feature. - ytrain: A numpy array of shape (num_training_samples, ) containing training label - Xval: A numpy array of shape (num_val_samples, D) containing validation feature. - yval: A numpy array of shape (num_val_samples, ) containing validation label Returns: - bestlambda: the best lambda you find in lambds """ ##################################################### # TODO 5: Fill in your code here # ##################################################### bestlambda = -1 lowestMSE = np.inf lambd = 10**(-20) while lambd < 10**20: # update lambd lambd *= 10 # print(float("{0:.2e}".format(lambd))) # use given training data to train model w = regularized_linear_regression(Xtrain, ytrain, lambd) # compute the mse mse = mean_square_error(w, Xval, yval) # print(mse) # update the mse if mse < lowestMSE: lowestMSE = mse bestlambda = lambd if bestlambda == None: return 0 else: # print(bestlambda) # avoid representation error in floating number return float("{0:.2e}".format(bestlambda)) ###### Q1.6 ###### def mapping_data(X, power): """ Mapping the data. Inputs: - X: A numpy array of shape (num_training_samples, D) containing training feature. - power: A integer that indicate the power in polynomial regression Returns: - X: mapped_X, shape(num_samples, D*power) You can manually calculate the size of X based on the power and original size of X """ ##################################################### # TODO 6: Fill in your code here # ##################################################### """ GOAL: input [[1,2,3],[0,5,5]] --> output [[1,2,3,1,4,9],[0,5,5,0,25,25]]""" # loop through each training sample # mapped_X = np.zeros((len(X), len(X[0])*(power-1))) mapped_X = [[] for i in range(len(X))] # mapped_X=[] # print(mapped_X) for index, sample in enumerate(X): # print(sample) # loop through all power in range for i in range(2, power+1): # create an element-wise power of the original sample sample_power_i = np.power(sample[:len(X[0])], i) # print(sample_power_i) # obtain the index of the last element end_idx = len(sample) # print(end_idx) # add that to the end of the original row sample = np.insert(sample, end_idx, sample_power_i) # print(sample.tolist()) # modify X mapped_X[index] = sample return np.asarray(mapped_X)

[ "trademark152@gmail.com" ]

trademark152@gmail.com

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/wrappedapp/tests/models/test_auth.py

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ralphbean/wrappedapp

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# -*- coding: utf-8 -*- """Test suite for the TG app's models""" from nose.tools import eq_ from wrappedapp import model from wrappedapp.tests.models import ModelTest class TestGroup(ModelTest): """Unit test case for the ``Group`` model.""" klass = model.Group attrs = dict( group_name = u"test_group", display_name = u"Test Group" ) class TestUser(ModelTest): """Unit test case for the ``User`` model.""" klass = model.User attrs = dict( user_name = u"ignucius", email_address = u"ignucius@example.org" ) def test_obj_creation_username(self): """The obj constructor must set the user name right""" eq_(self.obj.user_name, u"ignucius") def test_obj_creation_email(self): """The obj constructor must set the email right""" eq_(self.obj.email_address, u"ignucius@example.org") def test_no_permissions_by_default(self): """User objects should have no permission by default.""" eq_(len(self.obj.permissions), 0) def test_getting_by_email(self): """Users should be fetcheable by their email addresses""" him = model.User.by_email_address(u"ignucius@example.org") eq_(him, self.obj) class TestPermission(ModelTest): """Unit test case for the ``Permission`` model.""" klass = model.Permission attrs = dict( permission_name = u"test_permission", description = u"This is a test Description" )

[ "ralph.bean@gmail.com" ]

ralph.bean@gmail.com

9481c3b012fa6b02185d777dafa526c7ef1e00d7

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/cam_esp32cam.py

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[]

no_license

rkuo2000/cv2

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refs/heads/master

2022-10-12T00:11:35.964818

2022-09-30T06:50:35

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# open browser at ipaddr of ESP32-CAM to set stream size # 320x240 doesn't work, other resolution are OK import numpy as np import cv2 from urllib.request import urlopen # port 81 has stream, see ESP32-CAM webserver.ino url = 'http://192.168.1.5:81/stream' CAMERA_BUFFER_SIZE = 4096 stream = urlopen(url) bbb=b'' while True: bbb += stream.read(CAMERA_BUFFER_SIZE) a = bbb.find(b'\xff\xd8') b = bbb.find(b'\xff\xd9') if a>-1 and b>-1: jpg = bbb[a:b+2] bbb = bbb[b+2:] img = cv2.imdecode(np.frombuffer(jpg, dtype=np.uint8),cv2.IMREAD_COLOR) cv2.imshow('CAM', img) cv2.waitKey(1) cv2.destroyAllWindows()

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/test/test_policy.py

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ax-ncolyer/automox-console-sdk-python

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# coding: utf-8 """ Automox Console API API for use with the Automox Console # noqa: E501 OpenAPI spec version: 2021-08-10 Contact: support@automox.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import automox_console_sdk from automox_console_sdk.models.policy import Policy # noqa: E501 from automox_console_sdk.rest import ApiException class TestPolicy(unittest.TestCase): """Policy unit test stubs""" def setUp(self): pass def tearDown(self): pass def testPolicy(self): """Test Policy""" # FIXME: construct object with mandatory attributes with example values # model = automox_console_sdk.models.policy.Policy() # noqa: E501 pass if __name__ == '__main__': unittest.main()

[ "zachary.youtz@automox.com" ]

zachary.youtz@automox.com

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/aol/documents/tests.py

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[]

no_license

mdj2/aol

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refs/heads/master

2021-01-09T20:48:48.372586

2014-03-18T18:23:14

2014-03-18T18:23:33

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import os from django.test import TestCase from django.core.urlresolvers import reverse from django.conf import settings as SETTINGS from .models import Document from aol.users.tests.test_views import LoginMixin from aol.lakes.models import NHDLake as Lake class ViewTest(LoginMixin): fixtures = ['lakes.json'] def test_add_document(self): lake = Lake.objects.get(title="Matt Lake") response = self.client.get(reverse('admin-add-document', args=(lake.pk,))) self.assertEqual(response.status_code, 200) # test posting to the form data = { 'name': 'foo', 'rank': '1', 'file': open(os.path.join(SETTINGS.MEDIA_ROOT, "photos", "test.jpg")), 'type': Document.OTHER, } pre_count = Document.objects.filter(lake=lake).count() response = self.client.post(reverse('admin-add-document', args=(lake.pk,)), data) # the response should be valid, so a redirect should happen self.assertEqual(response.status_code, 302) # make sure the document got added to the lake self.assertEqual(Document.objects.filter(lake=lake).count(), pre_count + 1) # delete a required field to make the form invalid del data['name'] response = self.client.post(reverse('admin-add-document', args=(lake.pk,)), data) self.assertFalse(response.context['form'].is_valid()) def test_edit_document(self): document = Document.objects.get(pk=1) response = self.client.get(reverse('admin-edit-document', args=(document.pk,))) self.assertEqual(response.status_code, 200) # edit the document data = response.context['form'].initial data['name'] = "whatever" response = self.client.post(reverse('admin-edit-document', args=(document.pk,)), data) # the response should be valid, so a redirect should happen self.assertEqual(response.status_code, 302) # make sure the caption got updated document = Document.objects.get(pk=1) self.assertEqual(document.name, data['name'])

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mdj2@pdx.edu

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/django-rest/sxfunc/snippets/views.py

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[]

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2XL/hwDjango

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refs/heads/master

2021-01-13T09:15:33.791503

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from django.shortcuts import render # Create your views here. ############ Wrapping Views with function based decorator from rest_framework import status from rest_framework.decorators import api_view from rest_framework.response import Response from .models import Snippet from .serializers import SnippetSerializer @api_view(['GET', 'POST']) def snippet_list(request, format=None): """ <List:GET> all snippets, or <Create:POST> a new snippet. """ if request.method == 'GET': snippets = Snippet.objects.all() serializer = SnippetSerializer(snippets, many=True) return Response(serializer.data) elif request.method == 'POST': serializer = SnippetSerializer(data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data, status=status.HTTP_201_CREATED) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) @api_view(['GET', 'PUT', 'DELETE']) def snippet_detail(request, pk, format=None): """ Retrieve, update or delete a snippet instance. """ try: snippet = Snippet.objects.get(pk=pk) except Snippet.DoesNotExist: return Response(status=status.HTTP_404_NOT_FOUND) if request.method == 'GET': serializer = SnippetSerializer(snippet) return Response(serializer.data) elif request.method == 'PUT': serializer = SnippetSerializer(snippet, data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) elif request.method == 'DELETE': snippet.delete() return Response(status=status.HTTP_204_NO_CONTENT)

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chenglong.zq@gmail.com

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/beta/download.py

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li3637/JD_Diy

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#!/usr/bin/env python3 # -*- coding: utf-8 -*- # @Author : Chiupam # @Data : 2021-06-15 # @Version : v 1.0 # @Updata : # @Future : from JD_Diy import chat_id, jdbot, _ConfigDir, _ScriptsDir, _OwnDir, logger, _JdbotDir from ..bot.utils import cmd, press_event, backfile, jdcmd, V4, QL, _ConfigFile, mycron, split_list, row, qlcron, _Auth, upcron, mybot from ..diy.utils import mycronup from telethon import events, Button from asyncio import exceptions import requests, re, os, asyncio import json @jdbot.on(events.NewMessage(from_users=chat_id, pattern=r'^https?://.*(js|py|sh)$')) async def mydownload(event): try: SENDER = event.sender_id furl = event.raw_text if '下载代理' in mybot.keys() and str(mybot['下载代理']).lower() != 'false' and 'github' in furl: furl = f'{str(mybot["下载代理"])}/{furl}' try: resp = requests.get(furl).text if "</html>" in resp: await jdbot.send_message(chat_id, f"接收到的[链接]({furl})是一个页面并非raw数据，会话结束") return except Exception as e: await jdbot.send_message(chat_id, f"下载失败\n{e}") return async with jdbot.conversation(SENDER, timeout=60) as conv: fname = furl.split('/')[-1] fname_cn = '' if furl.endswith(".js"): fname_cn = re.findall(r"(?<=new\sEnv\(').*(?=')", resp, re.M) if fname_cn != []: fname_cn = fname_cn[0] else: fname_cn = '' if V4: btns = [Button.inline('放入config目录', data=_ConfigDir), Button.inline('放入jbot/diy目录', data=f'{_JdbotDir}/diy'), Button.inline('放入scripts目录', data=_ScriptsDir), Button.inline('放入own目录', data=_OwnDir ), Button.inline('取消对话', data='cancel')] else: btns = [Button.inline('放入config目录', data=_ConfigDir), Button.inline('放入scripts目录', data=_ScriptsDir), Button.inline('取消对话', data='cancel')] write, cmdtext = True, False msg = await conv.send_message(f'成功下载{fname_cn}脚本\n现在，请做出你的选择：', buttons=split_list(btns, row)) convdata = await conv.wait_event(press_event(SENDER)) res1 = bytes.decode(convdata.data) if res1 == 'cancel': await jdbot.edit_message(msg, '对话已取消，感谢你的使用') conv.cancel() return elif res1 == _ScriptsDir: fpath = f"{_ScriptsDir}/{fname}" btns = [Button.inline("是", data="confirm"), Button.inline("否", data="cancel")] msg = await jdbot.edit_message(msg, f"请问需要运行{fname_cn}脚本吗？", buttons=btns) convdata = await conv.wait_event(press_event(SENDER)) res2 = bytes.decode(convdata.data) if res2 == "confirm": cmdtext = f'{jdcmd} {_ScriptsDir}/{fname} now' msg = await jdbot.edit_message(msg, f"请问需要添加定时吗？", buttons=btns) convdata = await conv.wait_event(press_event(SENDER)) res2 = bytes.decode(convdata.data) if res2 == 'cancel': await jdbot.edit_message(msg, f"{fname_cn}脚本将保存到{_ScriptsDir}目录") else: await mycronup(jdbot, conv, resp, fname, msg, SENDER, btns, _ScriptsDir) elif res1 == _OwnDir: fpath = f"{_OwnDir}/raw/{fname}" btns = [Button.inline("是", data="confirm"), Button.inline("否", data="cancel")] msg = await jdbot.edit_message(msg, f"请问需要运行{fname_cn}脚本吗？", buttons=btns) convdata = await conv.wait_event(press_event(SENDER)) res2 = bytes.decode(convdata.data) if res2 == "confirm": cmdtext = f'{jdcmd} {fpath} now' await jdbot.edit_message(msg, f"文件将保存到{res1}目录，且已写入配置中，准备执行脚本") else: await jdbot.edit_message(msg, f'文件将保存到{res1}目录，且已写入配置中，准备拉取单个脚本，请耐心等待') with open(_ConfigFile, 'r', encoding="utf-8") as f1: configs = f1.readlines() for config in configs: if config.find("OwnRawFile") != -1 and config.find("## ") == -1: line = configs.index(config) + 1 configs.insert(line, f"\t{event.raw_text}\n") with open(_ConfigFile, 'w', encoding="utf-8") as f2: f2.write(''.join(configs)) elif config.find("第五区域") != -1: break await cmd("jup own") else: fpath = f"{res1}/{fname}" await jdbot.edit_message(msg, f"文件将保存到{res1}目录") backfile(fpath) with open(fpath, 'w+', encoding='utf-8') as f: f.write(resp) conv.cancel() if cmdtext: await cmd(cmdtext) except exceptions.TimeoutError: msg = await jdbot.edit_message(msg, '选择已超时，对话已停止，感谢你的使用') except Exception as e: await jdbot.send_message(chat_id, 'something wrong,I\'m sorry\n' + str(e)) logger.error('something wrong,I\'m sorry\n' + str(e))

[ "chiupam@126.com" ]

chiupam@126.com

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class A: def __init__(self, elements): self.elements = elements def __len__(self): return len(self.elements) a = A([2]) print(len(a))

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/adminphotoload/templatetags/widget_photo_iframe.py

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# -*- coding: utf-8 -*- from django import template from django.conf import settings register = template.Library() @register.inclusion_tag('templatetags/iframe.html') def widget_photo_iframe(app, model, id, change): """ Inserta el código para la herramienta para subir fotos en un iframe """ return {'app': app, 'model': model, 'id': id, 'change': change, 'STATIC_URL': settings.STATIC_URL}

[ "luisjarufe@gmail.com" ]

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/.ipynb_checkpoints/vis_util-checkpoint.py

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import torchvision import torchvision.datasets as dset import torchvision.transforms as T import torchvision.models as models import torch import torch.nn as nn import matplotlib.pyplot as plt import time import os import copy import numpy as np def check_accuracy_vis(prefix,loader, model, device, plot=True): print('Checking accuracy on sequential validation set') model.eval() # set model to evaluation mode count = 0 score_array = np.empty((0,14)) gt_array = np.empty((0,14)) plt.figure() with torch.no_grad(): for x, y in loader: x = x.to(device=device, dtype=torch.float) # move to device, e.g. CPU y = y.to(device=device, dtype=torch.float) scores = model(x) loss_fn = torch.nn.MSELoss(reduction='mean') loss = loss_fn(scores,y) scores = scores.to(device="cpu",dtype=torch.float) y = y.to(device = "cpu", dtype = torch.float) if plot: plt.plot(range(count, len(scores) + count), scores.numpy()[:,0:3], 'b') plt.plot(range(count, len(scores) + count), y.numpy()[:,0:3], 'r') # append our results score_array = np.vstack((score_array,scores.numpy())) gt_array = np.vstack((gt_array,y.numpy())) count = count + len(scores) #save our results print('saving our results...') np.savetxt(prefix+'_vis_scores.dat', score_array, delimiter=',') # X is an array np.savetxt(prefix+'_vis_gt.dat', gt_array, delimiter=',') # X is an array print('MSE loss is: %f ' % loss) plt.show()

[ "google-dl-platform@googlegroups.com" ]

google-dl-platform@googlegroups.com

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gingerwizard/python-ece-client

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# coding: utf-8 """ No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) OpenAPI spec version: Generated by: https://github.com/swagger-api/swagger-codegen.git """ from pprint import pformat from six import iteritems import re class MatchQuery(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { 'query': 'str', 'operator': 'str', 'minimum_should_match': 'int', 'analyzer': 'str' } attribute_map = { 'query': 'query', 'operator': 'operator', 'minimum_should_match': 'minimum_should_match', 'analyzer': 'analyzer' } def __init__(self, query=None, operator=None, minimum_should_match=None, analyzer=None): """ MatchQuery - a model defined in Swagger """ self._query = None self._operator = None self._minimum_should_match = None self._analyzer = None self.query = query if operator is not None: self.operator = operator if minimum_should_match is not None: self.minimum_should_match = minimum_should_match if analyzer is not None: self.analyzer = analyzer @property def query(self): """ Gets the query of this MatchQuery. The text/numeric/date to query for. :return: The query of this MatchQuery. :rtype: str """ return self._query @query.setter def query(self, query): """ Sets the query of this MatchQuery. The text/numeric/date to query for. :param query: The query of this MatchQuery. :type: str """ if query is None: raise ValueError("Invalid value for `query`, must not be `None`") self._query = query @property def operator(self): """ Gets the operator of this MatchQuery. The operator flag can be set to or or and to control the boolean clauses (defaults to or). :return: The operator of this MatchQuery. :rtype: str """ return self._operator @operator.setter def operator(self, operator): """ Sets the operator of this MatchQuery. The operator flag can be set to or or and to control the boolean clauses (defaults to or). :param operator: The operator of this MatchQuery. :type: str """ self._operator = operator @property def minimum_should_match(self): """ Gets the minimum_should_match of this MatchQuery. The minimum number of optional should clauses to match. :return: The minimum_should_match of this MatchQuery. :rtype: int """ return self._minimum_should_match @minimum_should_match.setter def minimum_should_match(self, minimum_should_match): """ Sets the minimum_should_match of this MatchQuery. The minimum number of optional should clauses to match. :param minimum_should_match: The minimum_should_match of this MatchQuery. :type: int """ self._minimum_should_match = minimum_should_match @property def analyzer(self): """ Gets the analyzer of this MatchQuery. The analyzer that will be used to perform the analysis process on the text. Defaults to the analyzer that was used to index the field. :return: The analyzer of this MatchQuery. :rtype: str """ return self._analyzer @analyzer.setter def analyzer(self, analyzer): """ Sets the analyzer of this MatchQuery. The analyzer that will be used to perform the analysis process on the text. Defaults to the analyzer that was used to index the field. :param analyzer: The analyzer of this MatchQuery. :type: str """ self._analyzer = analyzer def to_dict(self): """ Returns the model properties as a dict """ result = {} for attr, _ in iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """ Returns the string representation of the model """ return pformat(self.to_dict()) def __repr__(self): """ For `print` and `pprint` """ return self.to_str() def __eq__(self, other): """ Returns true if both objects are equal """ if not isinstance(other, MatchQuery): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """ Returns true if both objects are not equal """ return not self == other

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#!/usr/bin/python -t # dfs from typing import ( List, ) class Solution: def __init__(self): self.cur_max = 0 self.ret = None """ @param score: When the j-th driver gets the i-th order, we can get score[i][j] points. @return: return an array that means the array[i]-th driver gets the i-th order. """ def orderAllocation(self, score: List[List[int]]) -> List[int]: # write your code here m = len(score) ret = [None] * m self.dfs(score, 0, ret) return self.ret def dfs(self, score, index, ret): print(score, index, ret) if index == len(ret): val = 0 for i in range(len(ret)): val += score[i][ret[i]] if val > self.cur_max: self.cur_max = val self.ret = list(ret) return for i in range(len(ret)): if i not in ret: ret[index] = i self.dfs(score, index+1, ret) ret[index] = None return if __name__ == '__main__': s = Solution() a = [[1,2,4],[7,11,16],[37,29,22]] print(s.orderAllocation(a)) # dp # 状态压缩DP版 # 我硬生生把一个medium题目做成了Hard。不过你们也可以看一眼，能练习状态压缩的题目真的不多了。 # # 首先这里dpij的意思是说当第i个司机被分配完了订单以后，订单的状态应该是j。 j里面bit里面的1表示的是这个订单被分配出去了。 # # 然后我们开始循环，从把第0个司机分配每种订单开始作为初始状态。然后从第一个司机开始，所以这个时候，应该就是有2个司机被分配完了，我们用一个helper function去state里面，把所有有2个1的给找出来，其他的就丢掉。然后开始转移，转移的方法就是，找到一个k， k表示要把第k个订单分给第i个司机，那么转移方程就是，当i-1个司机分配完，状态里面是有i - 1个1，并且这个状态prevstate跟j的唯一差别就是第k位上面的订单是要分给第i个司机的。所有用个xor把第k位给搞成0，就得到了prevstate，然后我们当然要从这个所有的k里面找到最大的，这个由两部分组成，一个是对于前面i-1个司机，还有个是第k个订单给第i个司机，这2个要加起来最大才行。 # # 上面步骤做好以后，那么最多多少分肯定能算出来。然后我们就倒回去算到底怎么匹配的。首先，我们要知道最后一个司机当state是11111的时候， allocation里面存的就是这个司机分的单号。然后知道这个以后，我们就把这个单号从state里面去掉就得到了上一个单号，以此类推就做完了。 # # 当然我做的时候，是在给driver分配订单，其实是做反了的，更好的办法应该是给订单分配driver，这样return的时候，不需要向我这样再倒腾一次。 class Solution: """ @param score: When the j-th driver gets the i-th order, we can get score[i][j] points. @return: return an array that means the array[i]-th driver gets the i-th order. """ def orderAllocation(self, score): num_states = 1 << len(score) # dp[i][j] = Driver i is assigned to state j dp = [[0] * num_states for _ in range(len(score))] max_score = 0 last_order = -1 allocation = [[-1] * num_states for _ in range(len(score))] for i in range(len(score)): bit_index = 1 << i dp[0][bit_index] = score[i][0] allocation[0][bit_index] = i for i in range(2, len(score) + 1): for j in range(num_states + 1): if self.num_of_ones(j) != i: continue for k in range(len(score)): if j & (1 << k) == 0: continue prev_state = j ^ (1 << k) if dp[i - 2][prev_state] + score[k][i - 1] > dp[i - 1][j]: dp[i - 1][j] = dp[i - 2][prev_state] + score[k][i - 1] allocation[i - 1][j] = k driver_to_order = [-1] * len(score) last_state = num_states - 1 for i in range(len(score) - 1, -1, -1): driver_to_order[i] = allocation[i][last_state] last_state = (1 << driver_to_order[i]) ^ last_state order_to_driver = [-1] * len(score) for driver, order in enumerate(driver_to_order): order_to_driver[order] = driver return order_to_driver def num_of_ones(self, state): num_of_ones = 0 while state > 0: state -= self.lowbit(state) num_of_ones += 1 return num_of_ones def lowbit(self, state): return state & (-state)

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# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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. from aliyunsdkcore.request import RpcRequest from aliyunsdkccc.endpoint import endpoint_data class CreateCabInstanceRequest(RpcRequest): def __init__(self): RpcRequest.__init__(self, 'CCC', '2017-07-05', 'CreateCabInstance') self.set_method('POST') if hasattr(self, "endpoint_map"): setattr(self, "endpoint_map", endpoint_data.getEndpointMap()) if hasattr(self, "endpoint_regional"): setattr(self, "endpoint_regional", endpoint_data.getEndpointRegional()) def get_MaxConcurrentConversation(self): return self.get_query_params().get('MaxConcurrentConversation') def set_MaxConcurrentConversation(self,MaxConcurrentConversation): self.add_query_param('MaxConcurrentConversation',MaxConcurrentConversation) def get_InstanceName(self): return self.get_query_params().get('InstanceName') def set_InstanceName(self,InstanceName): self.add_query_param('InstanceName',InstanceName) def get_CallCenterInstanceId(self): return self.get_query_params().get('CallCenterInstanceId') def set_CallCenterInstanceId(self,CallCenterInstanceId): self.add_query_param('CallCenterInstanceId',CallCenterInstanceId) def get_InstanceDescription(self): return self.get_query_params().get('InstanceDescription') def set_InstanceDescription(self,InstanceDescription): self.add_query_param('InstanceDescription',InstanceDescription)

[ "sdk-team@alibabacloud.com" ]

sdk-team@alibabacloud.com