






from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup




def 				A		(					lowercase__  :  str = ""  )		-> dict[str, float]:
	UpperCamelCase__ :Union[str, Any]						=      url or """https://www.imdb.com/chart/top/?ref_=nv_mv_250"""
	UpperCamelCase__ :List[str]						=      BeautifulSoup(requests.get(lowercase__  ).text ,		"""html.parser"""  )
	UpperCamelCase__ :Any						=      soup.find_all("""td""" ,		attrs="""titleColumn"""  )
	UpperCamelCase__ :Optional[int]						=      soup.find_all("""td""" ,		class_="""ratingColumn imdbRating"""  )
	return {
	    title.a.text: float(rating.strong.text  )
	    for title, rating in zip(lowercase__ ,		lowercase__  )
	}




def 				A		(					lowercase__  :  str = "IMDb_Top_250_Movies.csv"  )		-> None:
	UpperCamelCase__ :List[str]						=      get_imdb_top_aaa_movies()
	with open(lowercase__ ,		"""w""" ,		newline=""""""  ) as out_file:
		UpperCamelCase__ :str						=      csv.writer(lowercase__  )
		writer.writerow(["""Movie title""", """IMDb rating"""]  )
		for title, rating in movies.items():
			writer.writerow([title, rating]  )


if __name__ == "__main__":
							write_movies()






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase      							=   {
    'configuration_clipseg': [
        'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'CLIPSegConfig',
        'CLIPSegTextConfig',
        'CLIPSegVisionConfig',
    ],
    'processing_clipseg': ['CLIPSegProcessor'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase      							=   [
           'CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST',
           'CLIPSegModel',
           'CLIPSegPreTrainedModel',
           'CLIPSegTextModel',
           'CLIPSegVisionModel',
           'CLIPSegForImageSegmentation',
       ]

if TYPE_CHECKING:
       from .configuration_clipseg import (
           CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
           CLIPSegConfig,
           CLIPSegTextConfig,
           CLIPSegVisionConfig,
       )
       from .processing_clipseg import CLIPSegProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_clipseg import (
                  CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
                  CLIPSegForImageSegmentation,
                  CLIPSegModel,
                  CLIPSegPreTrainedModel,
                  CLIPSegTextModel,
                  CLIPSegVisionModel,
              )

else:
       import sys

       _lowerCamelCase      							=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

