


"""simple docstring"""





import bsa
import requests


def   _snake_case    (    _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    (    _snake_case					:      Optional[Any] = 5      ):
      lowerCAmelCase       :						Dict							= int(float(_a      )      )
      if num_movies < 1:
            return ()
      lowerCAmelCase       :						Dict							= (
          '''https://www.imdb.com/search/title?title_type='''
          f'''feature&sort=num_votes,desc&count={num_movies}'''
      )
      lowerCAmelCase       :						Union[str, Any]							= 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

 snake_case__		:  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 .chunk_utils import chunk_layer
from .data_transforms import make_atomaa_masks
from .feats import atomaa_to_atomaa, frames_and_literature_positions_to_atomaa_pos, torsion_angles_to_frames
from .loss import compute_predicted_aligned_error, compute_tm
from .protein import Protein as OFProtein
from .protein import to_pdb
from .rigid_utils import Rigid, Rotation
from .tensor_utils import dict_multimap, flatten_final_dims, permute_final_dims




