from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__		:					List[Any]					   =					{
    "configuration_informer": [
        "INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "InformerConfig",
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:					str					   =					[
          "INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "InformerForPrediction",
          "InformerModel",
          "InformerPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_informer import INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, InformerConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_informer import (
                INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                InformerForPrediction,
                InformerModel,
                InformerPreTrainedModel,
            )

else:
      import sys

      SCREAMING_SNAKE_CASE__		:					Optional[int]					   =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




import requests

SCREAMING_SNAKE_CASE__		:					int						=					"https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="







def     _a				(      lowercase__  :			str ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		requests.get(_NEWS_API + bbc_news_api_key ).json()
     # each article in the list is a dict
     for i, article in enumerate(bbc_news_page['articles']     ,  1 ):
          print(f'''{i}.) {article['title']}''' )


if __name__ == "__main__":
      fetch_bbc_news(bbc_news_api_key="<Your BBC News API key goes here>")



