


from __future__ import annotations

import math
from itertools import permutations






def    _UpperCAmelCase	(   __lowerCamelCase       )		->bool:


 '''simple docstring'''

 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(__lowerCamelCase       ) + 1       ) ,     6       ):
  if number % i == 0 or number % (i + 2) == 0:
   return False
 return True






def    _UpperCAmelCase	(   __lowerCamelCase = 7       )		->int:


 '''simple docstring'''
 snake_case   : Union[str, Any]	  =      ''''''.join(str(__lowerCamelCase       ) for i in range(1 ,     n + 1       )       )
 snake_case   : Any	  =      [int(''''''.join(__lowerCamelCase       )       ) for i in permutations(__lowerCamelCase ,     __lowerCamelCase       )]
 snake_case   : List[Any]	  =      [num for num in perm_list if is_prime(__lowerCamelCase       )]
 return max(__lowerCamelCase       ) if pandigitals else 0


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










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


a				:							List[str]					=			{
    'configuration_donut_swin': ['DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DonutSwinConfig'],
    'processing_donut': ['DonutProcessor'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a				:							Dict					=			[
      'DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
      'DonutSwinModel',
      'DonutSwinPreTrainedModel',
  ]

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a				:							Any					=			['DonutFeatureExtractor']
  a				:							Dict					=			['DonutImageProcessor']


if TYPE_CHECKING:
  from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
  from .processing_donut import DonutProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_donut_swin import (
        DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
        DonutSwinModel,
        DonutSwinPreTrainedModel,
    )

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_donut import DonutFeatureExtractor
    from .image_processing_donut import DonutImageProcessor

else:
  import sys

  a				:							Union[str, Any]					=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






