






"""simple docstring"""
import itertools
from pathlib import Path


def        A	(							__snake_case:   list[str]     )						->		int:

       """simple docstring"""





       __magic_name__										=						[tuple(__snake_case     ) for login in logins]

       __magic_name__										=						{char for login in split_logins for char in login}

       for permutation in itertools.permutations(__snake_case     ):
              __magic_name__										=						True
              for login in logins:
                     if not (
                         permutation.index(login[0]     )
                         < permutation.index(login[1]     )
                         < permutation.index(login[2]     )
                     ):
                            __magic_name__										=						False
                            break

              if satisfied:
                     return int(''.join(__snake_case     )     )

       raise Exception('Unable to find the secret passcode'     )


def        A	(							__snake_case:   str = "keylog.txt"     )						->		int:

       """simple docstring"""





       __magic_name__										=						Path(__snake_case     ).parent.joinpath(__snake_case     ).read_text().splitlines()

       return find_secret_passcode(__snake_case     )


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







"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case   :   str    		=		{"""configuration_sew_d""": ["""SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWDConfig"""]}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case   :   Union[str, Any]    		=		[
     """SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """SEWDForCTC""",
     """SEWDForSequenceClassification""",
     """SEWDModel""",
     """SEWDPreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_sew_d import (
      SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
      SEWDForCTC,
      SEWDForSequenceClassification,
      SEWDModel,
      SEWDPreTrainedModel,
  )


else:
 import sys

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