"""simple docstring"""




import bsa
import requests






def 	UpperCAmelCase       (						UpperCamelCase__					):






							"""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 	UpperCAmelCase       (						UpperCamelCase__ = 5					):






							"""simple docstring"""





							A__						  =				int(float(snake_case_					)					)
							if num_movies < 1:
														return ()
							A__						  =				(
							    "https://www.imdb.com/search/title?title_type="
							    F'''feature&sort=num_votes,desc&count={num_movies}'''
							)
							A__						  =				bsa.BeautifulSoup(requests.get(snake_case_					).content							,     'html.parser'					)
							return tuple(
							    get_movie_data_from_soup(snake_case_					)
							    for movie in source.find_all('div'							,     class_='lister-item mode-advanced'					)					)


if __name__ == "__main__":
				import json

				__lowerCamelCase									=	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_tokenizers_available,
    is_torch_available,
)


UpperCamelCase					=     {
    """configuration_led""": ["""LED_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LEDConfig"""],
    """tokenization_led""": ["""LEDTokenizer"""],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     ["""LEDTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     [
      """LED_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """LEDForConditionalGeneration""",
      """LEDForQuestionAnswering""",
      """LEDForSequenceClassification""",
      """LEDModel""",
      """LEDPreTrainedModel""",
  ]


try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     ["""TFLEDForConditionalGeneration""", """TFLEDModel""", """TFLEDPreTrainedModel"""]


if TYPE_CHECKING:
  from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
  from .tokenization_led import LEDTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_led_fast import LEDTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_led import (
        LED_PRETRAINED_MODEL_ARCHIVE_LIST,
        LEDForConditionalGeneration,
        LEDForQuestionAnswering,
        LEDForSequenceClassification,
        LEDModel,
        LEDPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
  import sys

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






