



'''simple docstring'''

import os

from ...utils import logging
from .utils import DataProcessor, InputExample


_A					:     Optional[Any]      =logging.get_logger(__name__)



class 		lowerCamelCase__   (    A  ):




					'''simple docstring'''



					def __init__(	self					:						Any  ,	UpperCamelCase_					:						Any  ,	UpperCamelCase_					:						Optional[Any]=None       )	->							int:



						'''simple docstring'''





						_lowercase       :							Union[str, Any]  	=		language
						_lowercase       :							Dict  	=		train_language




					def     __UpperCAmelCase  (	self					:						Optional[Any]  ,	UpperCamelCase_					:						str       )	->							Optional[Any]:



						'''simple docstring'''





						_lowercase       :							List[Any]  	=		self.language if self.train_language is None else self.train_language
						_lowercase       :							Any  	=		self._read_tsv(os.path.join(UpperCamelCase_  ,	F'''XNLI-MT-1.0/multinli/multinli.train.{lg}.tsv'''       )       )
						_lowercase       :							int  	=		[]
						for i, line in enumerate(UpperCamelCase_       ):
							if i == 0:
								continue
							_lowercase       :							Optional[Any]  	=		F'''train-{i}'''
							_lowercase       :							Tuple  	=		line[0]
							_lowercase       :							Dict  	=		line[1]
							_lowercase       :							List[str]  	=		'contradiction' if line[2] == 'contradictory' else line[2]
							if not isinstance(UpperCamelCase_  ,	UpperCamelCase_       ):
								raise ValueError(F'''Training input {text_a} is not a string'''       )
							if not isinstance(UpperCamelCase_  ,	UpperCamelCase_       ):
								raise ValueError(F'''Training input {text_b} is not a string'''       )
							if not isinstance(UpperCamelCase_  ,	UpperCamelCase_       ):
								raise ValueError(F'''Training label {label} is not a string'''       )
							examples.append(InputExample(guid=UpperCamelCase_  ,	text_a=UpperCamelCase_  ,	text_b=UpperCamelCase_  ,	label=UpperCamelCase_       )       )
						return examples




					def     __UpperCAmelCase  (	self					:						str  ,	UpperCamelCase_					:						List[str]       )	->							str:



						'''simple docstring'''





						_lowercase       :							Optional[int]  	=		self._read_tsv(os.path.join(UpperCamelCase_  ,	'XNLI-1.0/xnli.test.tsv'       )       )
						_lowercase       :							int  	=		[]
						for i, line in enumerate(UpperCamelCase_       ):
							if i == 0:
								continue
							_lowercase       :							Optional[int]  	=		line[0]
							if language != self.language:
								continue
							_lowercase       :							str  	=		F'''test-{i}'''
							_lowercase       :							Optional[int]  	=		line[6]
							_lowercase       :							Optional[Any]  	=		line[7]
							_lowercase       :							Tuple  	=		line[1]
							if not isinstance(UpperCamelCase_  ,	UpperCamelCase_       ):
								raise ValueError(F'''Training input {text_a} is not a string'''       )
							if not isinstance(UpperCamelCase_  ,	UpperCamelCase_       ):
								raise ValueError(F'''Training input {text_b} is not a string'''       )
							if not isinstance(UpperCamelCase_  ,	UpperCamelCase_       ):
								raise ValueError(F'''Training label {label} is not a string'''       )
							examples.append(InputExample(guid=UpperCamelCase_  ,	text_a=UpperCamelCase_  ,	text_b=UpperCamelCase_  ,	label=UpperCamelCase_       )       )
						return examples




					def     __UpperCAmelCase  (	self					:						Tuple       )	->							Any:



						'''simple docstring'''





						return ["contradiction", "entailment", "neutral"]






_A					:     Union[str, Any]      ={
    '''xnli''': XnliProcessor,
}

_A					:     List[Any]      ={
    '''xnli''': '''classification''',
}

_A					:     Any      ={
    '''xnli''': 3,
}





'''simple docstring'''

import bsa
import requests







def     __UpperCamelCase					(				_lowercase       )			->      dict[str, str]:
	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     __UpperCamelCase					(				_lowercase = 5       )			->      tuple:
	_lowercase       :							List[Any]  	=		int(float(_lowercase       )       )
	if num_movies < 1:
		return ()
	_lowercase       :							Any  	=		(
	    'https://www.imdb.com/search/title?title_type='
	    f'''feature&sort=num_votes,desc&count={num_movies}'''
	)
	_lowercase       :							Tuple  	=		bsa.BeautifulSoup(requests.get(_lowercase       ).content,					'html.parser'       )
	return tuple(
	    get_movie_data_from_soup(_lowercase       )
	    for movie in source.find_all('div',					class_='lister-item mode-advanced'       )       )


if __name__ == "__main__":
		import json

		_A					:     Optional[int]      =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)
		    )
		)
