
import bsa
import requests


def 		UpperCAmelCase    (			a_		)	->			dict[str, str]:







				"""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 		UpperCAmelCase    (			a_ = 5		)	->			tuple:







				"""simple docstring"""



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


if __name__ == "__main__":
					import json

					SCREAMING_SNAKE_CASE							:List[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)
					    )
					)


from ...utils import is_transformers_available
from .pipeline_latent_diffusion_superresolution import LDMSuperResolutionPipeline


if is_transformers_available():
					from .pipeline_latent_diffusion import LDMBertModel, LDMTextToImagePipeline
