

"""simple docstring"""


from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup



def   _A					(	_a	:						str = ""				):



      """simple docstring"""






      A				  =		url or """https://www.imdb.com/chart/top/?ref_=nv_mv_250"""
      A				  =		BeautifulSoup(requests.get(_a				).text     ,   """html.parser"""				)
      A				  =		soup.find_all("""td"""     ,   attrs="""titleColumn"""				)
      A				  =		soup.find_all("""td"""     ,   class_="""ratingColumn imdbRating"""				)
      return {
          title.a.text: float(rating.strong.text				)
          for title, rating in zip(_a     ,   _a				)
      }



def   _A					(	_a	:						str = "IMDb_Top_250_Movies.csv"				):



      """simple docstring"""






      A				  =		get_imdb_top_aaa_movies()
      with open(_a     ,   """w"""     ,   newline=""""""				) as out_file:
            A				  =		csv.writer(_a				)
            writer.writerow(["""Movie title""", """IMDb rating"""]				)
            for title, rating in movies.items():
                  writer.writerow([title, rating]				)


if __name__ == "__main__":
  write_movies()







"""simple docstring"""


from typing import TYPE_CHECKING

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


UpperCAmelCase													={
    "configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase													=[
      "MEGA_PRETRAINED_MODEL_ARCHIVE_LIST",
      "MegaForCausalLM",
      "MegaForMaskedLM",
      "MegaForMultipleChoice",
      "MegaForQuestionAnswering",
      "MegaForSequenceClassification",
      "MegaForTokenClassification",
      "MegaModel",
      "MegaPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig, MegaOnnxConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mega import (
        MEGA_PRETRAINED_MODEL_ARCHIVE_LIST,
        MegaForCausalLM,
        MegaForMaskedLM,
        MegaForMultipleChoice,
        MegaForQuestionAnswering,
        MegaForSequenceClassification,
        MegaForTokenClassification,
        MegaModel,
        MegaPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase													=_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




