import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property

@unittest.skipUnless(os.path.exists(UpperCamelCase_						)   ,						'Tatoeba directory does not exist.'						)
class       snake_case					(      unittest.TestCase						):




  @cached_property
  def 	__lowercase(      self     :	str				)->       Optional[int]:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		tempfile.mkdtemp()
       return TatoebaConverter(save_dir=a_				)




  @slow
  def 	__lowercase(      self     :	Union[str, Any]				)->       Dict:




       """simple docstring"""
       self.resolver.convert_models(['heb-eng']				)




  @slow
  def 	__lowercase(      self     :	Optional[int]				)->       List[str]:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__				:				Dict			=		self.resolver.write_model_card('opus-mt-he-en'     , dry_run=a_				)
       assert mmeta["long_pair"] == "heb-eng"




import requests

SCREAMING_SNAKE_CASE__		:					int						=					"https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="







def     _a				(      lowercase__  :			str ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		requests.get(_NEWS_API + bbc_news_api_key ).json()
     # each article in the list is a dict
     for i, article in enumerate(bbc_news_page['articles']     ,  1 ):
          print(f'''{i}.) {article['title']}''' )


if __name__ == "__main__":
      fetch_bbc_news(bbc_news_api_key="<Your BBC News API key goes here>")



