






"""simple docstring"""



import bsa
import requests



def 						lowercase   (    __snake_case    :			Tuple     ):
		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 						lowercase   (    __snake_case    :			Dict = 5     ):
		lowercase_			:			Union[str, Any]								=       int(float(lowerCamelCase_     )     )
		if num_movies < 1:
				return ()
		lowercase_			:			Dict								=       (
		    '''https://www.imdb.com/search/title?title_type='''
		    F'''feature&sort=num_votes,desc&count={num_movies}'''
		)
		lowercase_			:			str								=       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

						__A		:	str      =		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_tokenizers_available, is_torch_available


__A		:	Any      =		{
    '''configuration_realm''': ['''REALM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RealmConfig'''],
    '''tokenization_realm''': ['''RealmTokenizer'''],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:	Tuple      =		['''RealmTokenizerFast''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:	Optional[int]      =		[
						    '''REALM_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''RealmEmbedder''',
						    '''RealmForOpenQA''',
						    '''RealmKnowledgeAugEncoder''',
						    '''RealmPreTrainedModel''',
						    '''RealmReader''',
						    '''RealmScorer''',
						    '''load_tf_weights_in_realm''',
						]
						__A		:	Union[str, Any]      =		['''RealmRetriever''']


if TYPE_CHECKING:
						from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
						from .tokenization_realm import RealmTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_realm import RealmTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_realm import (
												    REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
												    RealmEmbedder,
												    RealmForOpenQA,
												    RealmKnowledgeAugEncoder,
												    RealmPreTrainedModel,
												    RealmReader,
												    RealmScorer,
												    load_tf_weights_in_realm,
												)
												from .retrieval_realm import RealmRetriever


else:
						import sys

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



