


'''simple docstring'''






import csv

import tweepy

# Twitter API credentials
__A					:  str											=      ""
__A					:  Any											=      ""
__A					:  Optional[int]											=      ""
__A					:  Tuple											=      ""







def 				UpperCamelCase_			(    A__					:   str					):
  '''simple docstring'''





  lowerCAmelCase_			:      Tuple			=   tweepy.OAuthHandler(A__							,    A__					)
  auth.set_access_token(A__							,    A__					)
  lowerCAmelCase_			:      int			=   tweepy.API(A__					)

  # initialize a list to hold all the tweepy Tweets
  lowerCAmelCase_			:      Dict			=   []

  # make initial request for most recent tweets (200 is the maximum allowed count)
  lowerCAmelCase_			:      Tuple			=   api.user_timeline(screen_name=A__							,    count=2_00					)

  # save most recent tweets
  alltweets.extend(A__					)

  # save the id of the oldest tweet less one
  lowerCAmelCase_			:      List[str]			=   alltweets[-1].id - 1

  # keep grabbing tweets until there are no tweets left to grab
  while len(A__					) > 0:
    print(f'getting tweets before {oldest}'					)

    # all subsequent requests use the max_id param to prevent duplicates
    lowerCAmelCase_			:      str			=   api.user_timeline(
        screen_name=A__							,    count=2_00							,    max_id=A__					)

    # save most recent tweets
    alltweets.extend(A__					)

    # update the id of the oldest tweet less one
    lowerCAmelCase_			:      List[Any]			=   alltweets[-1].id - 1

    print(f'...{len(A__					)} tweets downloaded so far'					)

  # transform the tweepy tweets into a 2D array that will populate the csv
  lowerCAmelCase_			:      Optional[int]			=   [[tweet.id_str, tweet.created_at, tweet.text] for tweet in alltweets]

  # write the csv
  with open(f'new_{screen_name}_tweets.csv'							,    """w"""					) as f:
    lowerCAmelCase_			:      str			=   csv.writer(A__					)
    writer.writerow(["""id""", """created_at""", """text"""]					)
    writer.writerows(A__					)


if __name__ == "__main__":
  # pass in the username of the account you want to download
  get_all_tweets("FirePing32")







'''simple docstring'''






# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool






class    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase    =					'philschmid/bart-large-cnn-samsum'
    lowercase    =					(
        'This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, '
        'and returns a summary of the text.'
    )
    lowercase    =					'summarizer'
    lowercase    =					AutoTokenizer
    lowercase    =					AutoModelForSeqaSeqLM

    lowercase    =					['text']
    lowercase    =					['text']

    def __lowercase   (   self    :  Dict    ,						lowerCamelCase    :  Dict		)   ->  Any:
      return self.pre_processor(lowerCamelCase    ,						return_tensors="""pt"""    ,						truncation=lowerCamelCase		)

    def __lowercase   (   self    :  Optional[Any]    ,						lowerCamelCase    :  Tuple		)   ->  List[str]:
      return self.model.generate(**lowerCamelCase		)[0]





    def __lowercase   (   self    :  str    ,						lowerCamelCase    :  Dict		)   ->  List[Any]:
      return self.pre_processor.decode(lowerCamelCase    ,						skip_special_tokens=lowerCamelCase    ,						clean_up_tokenization_spaces=lowerCamelCase		)



