



import requests

lowerCAmelCase__		:					Union[str, Any]							='''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''






def      __lowercase       (			a__       )    ->			None:
							# fetching a list of articles in json format
							__SCREAMING_SNAKE_CASE									= 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>''')











from typing import TYPE_CHECKING

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


lowerCAmelCase__		:					str							={'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase__		:					Optional[int]							=[
			    '''VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''ViTMAEForPreTraining''',
			    '''ViTMAELayer''',
			    '''ViTMAEModel''',
			    '''ViTMAEPreTrainedModel''',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase__		:					List[str]							=[
			    '''TFViTMAEForPreTraining''',
			    '''TFViTMAEModel''',
			    '''TFViTMAEPreTrainedModel''',
			]

if TYPE_CHECKING:
			from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_vit_mae import (
						    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
						    ViTMAEForPreTraining,
						    ViTMAELayer,
						    ViTMAEModel,
						    ViTMAEPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
			import sys

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






