


'''simple docstring'''





from typing import TYPE_CHECKING

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


UpperCAmelCase__  			=				{
    '''configuration_groupvit''': [
        '''GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''GroupViTConfig''',
        '''GroupViTOnnxConfig''',
        '''GroupViTTextConfig''',
        '''GroupViTVisionConfig''',
    ],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__  			=				[
					    '''GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''GroupViTModel''',
					    '''GroupViTPreTrainedModel''',
					    '''GroupViTTextModel''',
					    '''GroupViTVisionModel''',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__  			=				[
					    '''TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TFGroupViTModel''',
					    '''TFGroupViTPreTrainedModel''',
					    '''TFGroupViTTextModel''',
					    '''TFGroupViTVisionModel''',
					]

if TYPE_CHECKING:
					from .configuration_groupvit import (
					    GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    GroupViTConfig,
					    GroupViTOnnxConfig,
					    GroupViTTextConfig,
					    GroupViTVisionConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_groupvit import (
										    GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GroupViTModel,
										    GroupViTPreTrainedModel,
										    GroupViTTextModel,
										    GroupViTVisionModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_groupvit import (
										    TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFGroupViTModel,
										    TFGroupViTPreTrainedModel,
										    TFGroupViTTextModel,
										    TFGroupViTVisionModel,
										)

else:
					import sys

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







'''simple docstring'''





from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: str = "" ):






			"""simple docstring"""




			__A=	url or 'https://www.imdb.com/chart/top/?ref_=nv_mv_250'
			__A=	BeautifulSoup(requests.get(_SCREAMING_SNAKE_CASE ).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(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE )
			}






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: str = "IMDb_Top_250_Movies.csv" ):






			"""simple docstring"""




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


if __name__ == "__main__":
					write_movies()



