
import bsa
import requests




def     a						(							snake_case__: Dict ):


				'''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     a						(							snake_case__: int = 5 ):


				'''simple docstring'''
				lowercase_					  = int(float(snake_case__ ) )
				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(snake_case__ ).content						,       '''html.parser''' )
				return tuple(
				    get_movie_data_from_soup(snake_case__ )
				    for movie in source.find_all('''div'''						,       class_='''lister-item mode-advanced''' ) )


if __name__ == "__main__":
							import json

							__a        = 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)
							    )
							)






from typing import TYPE_CHECKING

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


__a        = {
    'configuration_nystromformer': ['NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NystromformerConfig'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a        = [
						    'NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'NystromformerForMaskedLM',
						    'NystromformerForMultipleChoice',
						    'NystromformerForQuestionAnswering',
						    'NystromformerForSequenceClassification',
						    'NystromformerForTokenClassification',
						    'NystromformerLayer',
						    'NystromformerModel',
						    'NystromformerPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_nystromformer import (
												    NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    NystromformerForMaskedLM,
												    NystromformerForMultipleChoice,
												    NystromformerForQuestionAnswering,
												    NystromformerForSequenceClassification,
												    NystromformerForTokenClassification,
												    NystromformerLayer,
												    NystromformerModel,
												    NystromformerPreTrainedModel,
												)


else:
						import sys

						__a        = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




