

import os
from argparse import ArgumentParser
from typing import List

import torch.utils.data

from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node


_UpperCAmelCase		:       Optional[int]						    =	4
_UpperCAmelCase		:       Dict						    =	3







class 			lowercase    (	lowercase_      ):
				pass





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							for shard in shards:
														for i in range(UpperCamelCase__				):
																					yield {"i": i, "shard": shard}





def  __lowerCamelCase     (			):







							'''simple docstring'''






							snake_case_          =   int(os.environ['RANK']				)
							snake_case_          =   int(os.environ['WORLD_SIZE']				)

							snake_case_          =   ArgumentParser()
							parser.add_argument('--streaming'       ,							type=UpperCamelCase__				)
							parser.add_argument('--local_rank'       ,							type=UpperCamelCase__				)
							parser.add_argument('--num_workers'       ,							type=UpperCamelCase__       ,							default=0				)
							snake_case_          =   parser.parse_args()
							snake_case_          =   args.streaming
							snake_case_          =   args.num_workers

							snake_case_          =   {'shards': [F'''shard_{shard_idx}''' for shard_idx in range(UpperCamelCase__				)]}
							snake_case_          =   IterableDataset.from_generator(UpperCamelCase__       ,							gen_kwargs=UpperCamelCase__				)
							if not streaming:
														snake_case_          =   Dataset.from_list(list(UpperCamelCase__				)				)

							snake_case_          =   split_dataset_by_node(UpperCamelCase__       ,							rank=UpperCamelCase__       ,							world_size=UpperCamelCase__				)
							snake_case_          =   torch.utils.data.DataLoader(UpperCamelCase__       ,							num_workers=UpperCamelCase__				)

							snake_case_          =   NUM_SHARDS * NUM_ITEMS_PER_SHARD
							snake_case_          =   full_size // world_size
							expected_local_size += int(rank < (full_size % world_size)				)

							snake_case_          =   sum(1 for _ in dataloader				)
							if local_size != expected_local_size:
														raise FailedTestError(F'''local_size {local_size} != expected_local_size {expected_local_size}'''				)


if __name__ == "__main__":
					main()







import requests

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





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							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>""")




