code: 
  
  
  
  
  
  from __future__ import annotations
  
  from collections import Counter
  
  
  
  
  def   lowerCamelCase_       (					UpperCAmelCase__      ):
  
  
  
  						"""simple docstring"""
  
  
  
  
  						a_					=		[True] * n
  						a_					=		False
  						a_					=		False
  						a_					=		True
  
  						for i in range(3       ,    int(n**0.5 + 1      )       ,    2      ):
  												a_					=		i * 2
  												while index < n:
  																		a_					=		False
  																		a_					=		index + i
  
  						a_					=		[2]
  
  						for i in range(3       ,    UpperCAmelCase__       ,    2      ):
  												if is_prime[i]:
  																		primes.append(UpperCAmelCase__      )
  
  						return primes
  
  
  
  
  def   lowerCamelCase_       (					UpperCAmelCase__      ):
  
  
  
  						"""simple docstring"""
  
  
  
  
  						a_					=		str(UpperCAmelCase__      )
  						a_					=		[]
  						a_					=		["""0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9"""]
  
  						for duplicate in Counter(UpperCAmelCase__      ) - Counter(set(UpperCAmelCase__      )      ):
  												a_					=		[int(number_str.replace(UpperCAmelCase__       ,    UpperCAmelCase__      )      ) for digit in digits]
  												replacements.append(UpperCAmelCase__      )
  
  						return replacements
  
  
  
  
  def   lowerCamelCase_       (					UpperCAmelCase__ = 8      ):
  
  
  
  						"""simple docstring"""
  
  
  
  
  						a_					=		set()
  
  						# Filter primes with less than 3 replaceable digits
  						a_					=		{
  						    x for x in set(prime_sieve(1_000_000      )      ) if len(str(UpperCAmelCase__      )      ) - len(set(str(UpperCAmelCase__      )      )      ) >= 3
  						}
  
  						for prime in primes:
  												if prime in numbers_checked:
  																		continue
  
  												a_					=		digit_replacements(UpperCAmelCase__      )
  
  												for family in replacements:
  																		numbers_checked.update(UpperCAmelCase__      )
  																		a_					=		primes.intersection(UpperCAmelCase__      )
  
  																		if len(UpperCAmelCase__      ) != family_length:
  																								continue
  
  																		return min(UpperCAmelCase__      )
  
  						return -1
  
  
  if __name__ == "__main__":
  	print(solution())
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
  
  
  A_    :					Optional[Any]             ={
      """configuration_wav2vec2_conformer""": [
          """WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
          """Wav2Vec2ConformerConfig""",
      ],
  }
  
  
  try:
  	if not is_torch_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	A_    :					Union[str, Any]             =[
  	    """WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
  	    """Wav2Vec2ConformerForAudioFrameClassification""",
  	    """Wav2Vec2ConformerForCTC""",
  	    """Wav2Vec2ConformerForPreTraining""",
  	    """Wav2Vec2ConformerForSequenceClassification""",
  	    """Wav2Vec2ConformerForXVector""",
  	    """Wav2Vec2ConformerModel""",
  	    """Wav2Vec2ConformerPreTrainedModel""",
  	]
  
  if TYPE_CHECKING:
  	from .configuration_wavaveca_conformer import (
  	    WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
  	    WavaVecaConformerConfig,
  	)
  
  	try:
  		if not is_torch_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_wavaveca_conformer import (
  		    WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
  		    WavaVecaConformerForAudioFrameClassification,
  		    WavaVecaConformerForCTC,
  		    WavaVecaConformerForPreTraining,
  		    WavaVecaConformerForSequenceClassification,
  		    WavaVecaConformerForXVector,
  		    WavaVecaConformerModel,
  		    WavaVecaConformerPreTrainedModel,
  		)
  
  else:
  	import sys
  
  	A_    :					Union[str, Any]             =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)