



"""simple docstring"""




import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin






class       UpperCAmelCase_    (							_UpperCamelCase			,     unittest.TestCase		):
      __SCREAMING_SNAKE_CASE		:  Optional[Any]						=					XLMTokenizer
      __SCREAMING_SNAKE_CASE		:  Union[str, Any]						=					False



      def 		snake_case_   (	self	:      Union[str, Any]		):
           super().setUp()

           # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
           _UpperCAmelCase     :      Union[str, Any]														=       [
               "l",
               "o",
               "w",
               "e",
               "r",
               "s",
               "t",
               "i",
               "d",
               "n",
               "w</w>",
               "r</w>",
               "t</w>",
               "lo",
               "low",
               "er</w>",
               "low</w>",
               "lowest</w>",
               "newer</w>",
               "wider</w>",
               "<unk>",
           ]
           _UpperCAmelCase     :      str														=       dict(zip(A	,      range(len(A		)		)		)		)
           _UpperCAmelCase     :      Dict														=       ["l o 123", "lo w 1456", "e r</w> 1789", ""]

           _UpperCAmelCase     :      str														=       os.path.join(self.tmpdirname	,      VOCAB_FILES_NAMES["vocab_file"]		)
           _UpperCAmelCase     :      Union[str, Any]														=       os.path.join(self.tmpdirname	,      VOCAB_FILES_NAMES["merges_file"]		)
           with open(self.vocab_file	,      "w"		) as fp:
                fp.write(json.dumps(A		)		)
           with open(self.merges_file	,      "w"		) as fp:
                fp.write("\n".join(A		)		)



      def 		snake_case_   (	self	:      Optional[int]	,      A	:      str		):
           _UpperCAmelCase     :      Optional[int]														=       "lower newer"
           _UpperCAmelCase     :      int														=       "lower newer"
           return input_text, output_text



      def 		snake_case_   (	self	:      Optional[Any]		):
           _UpperCAmelCase     :      Union[str, Any]														=       XLMTokenizer(self.vocab_file	,      self.merges_file		)

           _UpperCAmelCase     :      Any														=       "lower"
           _UpperCAmelCase     :      Tuple														=       ["low", "er</w>"]
           _UpperCAmelCase     :      str														=       tokenizer.tokenize(A		)
           self.assertListEqual(A	,      A		)

           _UpperCAmelCase     :      Optional[int]														=       tokens + ["<unk>"]
           _UpperCAmelCase     :      Dict														=       [1_4, 1_5, 2_0]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(A		)	,      A		)



      @slow
      def 		snake_case_   (	self	:      List[str]		):
           _UpperCAmelCase     :      Optional[int]														=       XLMTokenizer.from_pretrained("xlm-mlm-en-2048"		)

           _UpperCAmelCase     :      int														=       tokenizer.encode("sequence builders"	,      add_special_tokens=A		)
           _UpperCAmelCase     :      Any														=       tokenizer.encode("multi-sequence build"	,      add_special_tokens=A		)

           _UpperCAmelCase     :      Tuple														=       tokenizer.build_inputs_with_special_tokens(A		)
           _UpperCAmelCase     :      Optional[int]														=       tokenizer.build_inputs_with_special_tokens(A	,      A		)

           assert encoded_sentence == [0] + text + [1]
           assert encoded_pair == [0] + text + [1] + text_a + [1]





"""simple docstring"""




import requests

_lowerCAmelCase							:   List[Any]				=				"https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="

def 		__snake_case		( SCREAMING_SNAKE_CASE__      :		str							)    ->  None:





     '''simple docstring'''

     _UpperCAmelCase     :      List[str]														=       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>")
