import requests

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





def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				__lowercase 			=							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_tokenizers_available, is_torch_available


__a  :     Any       =  {
    """configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConfig"""],
}
try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__a  :     Optional[int]       =  ["""BloomTokenizerFast"""]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__a  :     str       =  [
		    """BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """BloomForCausalLM""",
		    """BloomModel""",
		    """BloomPreTrainedModel""",
		    """BloomForSequenceClassification""",
		    """BloomForTokenClassification""",
		    """BloomForQuestionAnswering""",
		]

if TYPE_CHECKING:
		from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_bloom_fast import BloomTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_bloom import (
				    BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BloomForCausalLM,
				    BloomForQuestionAnswering,
				    BloomForSequenceClassification,
				    BloomForTokenClassification,
				    BloomModel,
				    BloomPreTrainedModel,
				)

else:
		import sys

		__a  :     Dict       =  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)