




import bsa
import requests
def 					snake_case_     (		SCREAMING_SNAKE_CASE_				)			-> Optional[Any]:
							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 					snake_case_     (		SCREAMING_SNAKE_CASE_ = 5				)			-> Optional[Any]:
							lowercase__  :       Dict   					=							int(float(_SCREAMING_SNAKE_CASE				)				)
							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__  :       List[str]   					=							bsa.BeautifulSoup(requests.get(_SCREAMING_SNAKE_CASE				).content				,"html.parser"				)
							return tuple(
							    get_movie_data_from_soup(_SCREAMING_SNAKE_CASE				)
							    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)
						    )
						)


from typing import TYPE_CHECKING

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


UpperCamelCase__     :					Dict								=			{
    "configuration_donut_swin": ["DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "DonutSwinConfig"],
    "processing_donut": ["DonutProcessor"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__     :					Optional[int]								=			[
           "DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DonutSwinModel",
           "DonutSwinPreTrainedModel",
       ]

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__     :					List[Any]								=			["DonutFeatureExtractor"]
       UpperCamelCase__     :					Dict								=			["DonutImageProcessor"]


if TYPE_CHECKING:
       from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
       from .processing_donut import DonutProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_donut_swin import (
                  DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DonutSwinModel,
                  DonutSwinPreTrainedModel,
              )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_donut import DonutFeatureExtractor
              from .image_processing_donut import DonutImageProcessor

else:
       import sys

       UpperCamelCase__     :					Tuple								=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


