
'''simple docstring'''




import requests
from bsa import BeautifulSoup







def 		lowerCAmelCase_				(   snake_case__ = "https://www.worldometers.info/coronavirus"						):




    '''simple docstring'''



    A       :   Optional[Any]					=						BeautifulSoup(requests.get(snake_case__						).text		,				'''html.parser'''						)
    A       :   Any					=						soup.findAll('''h1'''						)
    A       :   Union[str, Any]					=						soup.findAll('''div'''		,				{'''class''': '''maincounter-number'''}						)
    keys += soup.findAll('''span'''		,				{'''class''': '''panel-title'''}						)
    values += soup.findAll('''div'''		,				{'''class''': '''number-table-main'''}						)
    return {key.text.strip(): value.text.strip() for key, value in zip(snake_case__		,				snake_case__						)}


if __name__ == "__main__":
      print('\033[1m' + 'COVID-19 Status of the World' + '\033[0m\n')
      for key, value in world_covidaa_stats().items():
            print(f'''{key}\n{value}\n''')






'''simple docstring'''




from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest





@require_tokenizers
class  A				(							__snake_case						):
     __magic_name__						=		DistilBertTokenizer
     __magic_name__						=		DistilBertTokenizerFast
     __magic_name__						=		True





     @slow
     def 				__lowerCAmelCase							(							self	) ->				Any:






         """simple docstring"""






         A       :   List[Any]					=						DistilBertTokenizer.from_pretrained('''distilbert-base-uncased'''	)

         A       :   Dict					=						tokenizer.encode('''sequence builders'''						,			add_special_tokens=SCREAMING_SNAKE_CASE	)
         A       :   List[str]					=						tokenizer.encode('''multi-sequence build'''						,			add_special_tokens=SCREAMING_SNAKE_CASE	)

         A       :   Optional[Any]					=						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE	)
         A       :   Tuple					=						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)

         assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
         assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
             tokenizer.sep_token_id
         ]




