
"""simple docstring"""


import shutil

import requests



def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase = False       ,					__UpperCamelCase = "."			)							->					str:
	_lowerCAmelCase								="""https://api.nasa.gov/planetary/apod"""
	return requests.get(lowerCAmelCase__       ,					params={"""api_key""": api_key}			).json()



def        _lowerCamelCase(__UpperCamelCase       ,					__UpperCamelCase = "."			)							->					Union[str, Any]:
	_lowerCAmelCase								=get_apod_data(lowerCAmelCase__			)
	_lowerCAmelCase								=apod_data["""url"""]
	_lowerCAmelCase								=img_url.split("""/"""			)[-1]
	_lowerCAmelCase								=requests.get(lowerCAmelCase__       ,					stream=lowerCAmelCase__			)

	with open(F'''{path}/{img_name}'''       ,					"""wb+"""			) as img_file:
		shutil.copyfileobj(response.raw       ,					lowerCAmelCase__			)
	del response
	return apod_data



def        _lowerCamelCase(__UpperCamelCase			)							->					List[str]:
	_lowerCAmelCase								="""https://images-api.nasa.gov/search"""
	return requests.get(lowerCAmelCase__       ,					params={"""q""": query}			).json()


if __name__ == "__main__":
			print(save_apod('YOUR API KEY'))
			__A					=			get_archive_data('apollo 2011')['collection']['items']
			print(apollo_aaaa_items[0]['data'][0]['description'])




import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp






def  __lowerCamelCase						(		):
       lowerCAmelCase__	      =   ArgumentParser(
           description=(
               'PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes'
           )      )

       # Optional arguments for the launch helper
       parser.add_argument('--num_cores'      ,    type=lowerCAmelCase__      ,    default=1      ,    help='Number of TPU cores to use (1 or 8).'      )

       # positional
       parser.add_argument(
           'training_script'      ,    type=lowerCAmelCase__      ,    help=(
               'The full path to the single TPU training '
               'program/script to be launched in parallel, '
               'followed by all the arguments for the '
               'training script'
           )      ,    )

       # rest from the training program
       parser.add_argument('training_script_args'      ,    nargs=lowerCAmelCase__      )

       return parser.parse_args()






def  __lowerCamelCase						(		):
       lowerCAmelCase__	      =   parse_args()

       # Import training_script as a module.
       lowerCAmelCase__	      =   Path(args.training_script      )
       sys.path.append(str(script_fpath.parent.resolve()      )      )
       lowerCAmelCase__	      =   script_fpath.stem
       lowerCAmelCase__	      =   importlib.import_module(lowerCAmelCase__      )

       # Patch sys.argv
       lowerCAmelCase__	      =   [args.training_script] + args.training_script_args + ['--tpu_num_cores', str(args.num_cores      )]

       xmp.spawn(mod._mp_fn      ,    args=()      ,    nprocs=args.num_cores      )


if __name__ == "__main__":
    main()
