
"""simple docstring"""


from __future__ import annotations

import math
from itertools import permutations



def        _lowerCamelCase(__UpperCamelCase			)							->					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(__UpperCamelCase			) + 1			)       ,					6			):
		if number % i == 0 or number % (i + 2) == 0:
			return False
	return True



def        _lowerCamelCase(__UpperCamelCase = 7			)							->					int:
	_lowerCAmelCase								="""""".join(str(__UpperCamelCase			) for i in range(1       ,					n + 1			)			)
	_lowerCAmelCase								=[int("""""".join(__UpperCamelCase			)			) for i in permutations(__UpperCamelCase       ,					__UpperCamelCase			)]
	_lowerCAmelCase								=[num for num in perm_list if is_prime(__UpperCamelCase			)]
	return max(__UpperCamelCase			) if pandigitals else 0


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





"""simple docstring"""


from typing import TYPE_CHECKING

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


__A					=			{
    '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					=			[
			    'DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'DonutSwinModel',
			    'DonutSwinPreTrainedModel',
			]

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A					=			['DonutFeatureExtractor']
			__A					=			['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					=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



