


'''simple docstring'''

import bsa
import requests

def _SCREAMING_SNAKE_CASE				(A	)	->	Any:






       """simple docstring"""







       return {
           "name": soup.ha.a.text,
           "genre": soup.find('''span'''  ,			class_='''genre'''	).text.strip(),
           "rating": soup.strong.text,
           "page_link": f"https://www.imdb.com{soup.a.get('href'	)}",
       }

def _SCREAMING_SNAKE_CASE				(A = 5	)	->	Optional[Any]:






       """simple docstring"""







       lowercase__				      =			int(float(_lowerCAmelCase	)	)
       if num_movies < 1:
              return ()
       lowercase__				      =			(
           '''https://www.imdb.com/search/title?title_type='''
           f"feature&sort=num_votes,desc&count={num_movies}"
       )
       lowercase__				      =			bsa.BeautifulSoup(requests.get(_lowerCAmelCase	).content  ,			'''html.parser'''	)
       return tuple(
           get_movie_data_from_soup(_lowerCAmelCase	)
           for movie in source.find_all('''div'''  ,			class_='''lister-item mode-advanced'''	)	)


if __name__ == "__main__":
    import json

    lowerCamelCase							:       Union[str, Any]  						=     int(input('How many movies would you like to see? '))
    print(
        ', '.join(
            json.dumps(movie, indent=4) for movie in get_imdb_top_movies(num_movies)
        )
    )








'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


lowerCamelCase							:       Tuple  						=     {'configuration_bert_generation': ['BertGenerationConfig']}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:       Union[str, Any]  						=     ['BertGenerationTokenizer']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:       Dict  						=     [
     'BertGenerationDecoder',
     'BertGenerationEncoder',
     'BertGenerationPreTrainedModel',
     'load_tf_weights_in_bert_generation',
 ]


if TYPE_CHECKING:
 from .configuration_bert_generation import BertGenerationConfig

 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_bert_generation import BertGenerationTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_bert_generation import (
      BertGenerationDecoder,
      BertGenerationEncoder,
      BertGenerationPreTrainedModel,
      load_tf_weights_in_bert_generation,
  )

else:
 import sys

 lowerCamelCase							:       int  						=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




