



import shutil

import requests


def 						UpperCAmelCase__   (   UpperCAmelCase__			:str			,       UpperCAmelCase__			:bool = False			,       UpperCAmelCase__			:str = "."       ):






 '''simple docstring'''

 a							=		"https://api.nasa.gov/planetary/apod"
 return requests.get(UpperCAmelCase__			,       params={"api_key": api_key}       ).json()


def 						UpperCAmelCase__   (   UpperCAmelCase__			:str			,       UpperCAmelCase__			:str = "."       ):






 '''simple docstring'''

 a							=		get_apod_data(UpperCAmelCase__       )
 a							=		apod_data["url"]
 a							=		img_url.split("/"       )[-1]
 a							=		requests.get(UpperCAmelCase__			,       stream=UpperCAmelCase__       )

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


def 						UpperCAmelCase__   (   UpperCAmelCase__			:str       ):






 '''simple docstring'''

 a							=		"https://images-api.nasa.gov/search"
 return requests.get(UpperCAmelCase__			,       params={"q": query}       ).json()


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



from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
							from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore
class       A__  (		lowerCAmelCase__							):
							lowerCAmelCase__						:		Any            =				c_float





							@property
							def      a__					(					self    :  List[str]							)		->						int:



											"""simple docstring"""


											return sizeof(self.value							)






def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: int       ,				SCREAMING_SNAKE_CASE			: int       ,				SCREAMING_SNAKE_CASE			: int = 0     )	->		int:
				# < 0 is possible if using a dynamic axis
				if dimension <= 0:
								__lowercase								=   fixed_dimension

				dimension -= num_token_to_add
				return dimension




def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: int       ,				SCREAMING_SNAKE_CASE			: ParameterFormat     )	->		int:
				return num_parameters * dtype.size




def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: str     )	->		Optional[Union["AutoTokenizer", "AutoFeatureExtractor", "AutoProcessor"]]:
				from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

				try:
								return AutoProcessor.from_pretrained(SCREAMING_SNAKE_CASE     )
				except (ValueError, OSError, KeyError):
								__lowercase						,   __lowercase								=   None, None
								try:
												__lowercase								=   AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE     )
								except (OSError, KeyError):
												pass
								try:
												__lowercase								=   AutoFeatureExtractor.from_pretrained(SCREAMING_SNAKE_CASE     )
								except (OSError, KeyError):
												pass

								if tokenizer is not None and feature_extractor is not None:
												raise ValueError(
												    F"""Couldn't auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor."""     )
								elif tokenizer is None and feature_extractor is None:
												return None
								elif tokenizer is not None:
												return tokenizer
								else:
												return feature_extractor





