






'''simple docstring'''


import bsa
import requests







def 						__magic_name__(			_A       ):
						'''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 						__magic_name__(			_A = 5       ):
						'''simple docstring'''





						UpperCamelCase__       =			int(float(_A       )       )
						if num_movies < 1:
												return ()
						UpperCamelCase__       =			(
						    """https://www.imdb.com/search/title?title_type="""
						    f"feature&sort=num_votes,desc&count={num_movies}"
						)
						UpperCamelCase__       =			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

					lowerCamelCase_					:			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)
					    )
					)








'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase_					:			Any     						=				{
    '''configuration_sam''': [
        '''SAM_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SamConfig''',
        '''SamMaskDecoderConfig''',
        '''SamPromptEncoderConfig''',
        '''SamVisionConfig''',
    ],
    '''processing_sam''': ['''SamProcessor'''],
}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase_					:			Union[str, Any]     						=				[
					    '''SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''SamModel''',
					    '''SamPreTrainedModel''',
					]
try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase_					:			Optional[Any]     						=				[
					    '''TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TFSamModel''',
					    '''TFSamPreTrainedModel''',
					]
try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase_					:			Optional[Any]     						=				['''SamImageProcessor''']


if TYPE_CHECKING:
					from .configuration_sam import (
					    SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    SamConfig,
					    SamMaskDecoderConfig,
					    SamPromptEncoderConfig,
					    SamVisionConfig,
					)
					from .processing_sam import SamProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_sam import SamImageProcessor

else:
					import sys

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