

from __future__ import annotations

import math
from itertools import permutations





def  _snake_case		(snake_case_					:     int  )							->		bool:

  if 1 < number < 4:
    # 2 and 3 are primes
    return True
  elif number < 2 or number % 2 == 0 or number % 3 == 0:
    # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
    return False

  # All primes number are in format of 6k +/- 1
  for i in range(5    ,       int(math.sqrt(snake_case_  ) + 1  )    ,       6  ):
    if number % i == 0 or number % (i + 2) == 0:
      return False
  return True





def  _snake_case		(snake_case_					:     int = 7  )							->		int:
  __UpperCAmelCase	:  Dict		=     ''.join(str(snake_case_  ) for i in range(1    ,       n + 1  )  )
  __UpperCAmelCase	:  Any		=     [int(''.join(snake_case_  )  ) for i in permutations(snake_case_    ,       snake_case_  )]
  __UpperCAmelCase	:  Dict		=     [num for num in perm_list if is_prime(snake_case_  )]
  return max(snake_case_  ) if pandigitals else 0


if __name__ == "__main__":
      print(F'''{solution() = }''')







"""simple docstring"""







import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


SCREAMING_SNAKE_CASE_  					= logging.get_logger(__name__)






class      __a      (       lowerCAmelCase_      ):







       def __init__(       self				,*lowerCamelCase_				,**lowerCamelCase_		):



          '''simple docstring'''

          warnings.warn(
              "The class MobileNetV1FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
              " Please use MobileNetV1ImageProcessor instead."				,lowerCamelCase_				,)
          super().__init__(*lowerCamelCase_				,**lowerCamelCase_		)

