




"""simple docstring"""




from __future__ import annotations

import string
from itertools import cycle, product
from pathlib import Path

a_	   =    (
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
a_	   =    [ord(letter) for letter in string.ascii_lowercase]
a_	   =    {ord(char) for char in VALID_CHARS}

a_	   =    ["the", "be", "to", "of", "and", "in", "that", "have"]







def 			__UpperCAmelCase			(      __UpperCamelCase     ,							__UpperCamelCase     ):
			__lowercase       :   str        =    ""
			__lowercase       :   int
			__lowercase       :   int
			__lowercase       :   int

			for keychar, cipherchar in zip(cycle(__UpperCamelCase     )     ,							__UpperCamelCase     ):
						__lowercase       :   List[Any]        =    cipherchar ^ keychar
						if decodedchar not in VALID_INTS:
									return None
						decoded += chr(__UpperCamelCase     )

			return decoded







def 			__UpperCAmelCase			(      __UpperCamelCase     ):
			__lowercase       :   list[str]        =    []
			for key in product(__UpperCamelCase     ,							repeat=3     ):
						__lowercase       :   List[Any]        =    try_key(__UpperCamelCase     ,							__UpperCamelCase     )
						if encoded is not None:
									possibles.append(__UpperCamelCase     )
			return possibles







def 			__UpperCAmelCase			(      __UpperCamelCase     ,							__UpperCamelCase     ):
			return [possible for possible in possibles if common_word in possible.lower()]







def 			__UpperCAmelCase			(      __UpperCamelCase = "p059_cipher.txt"     ):
			__lowercase       :   list[int]
			__lowercase       :   list[str]
			__lowercase       :   str
			__lowercase       :   str
			__lowercase       :   str        =    Path(__UpperCamelCase     ).parent.joinpath(__UpperCamelCase     ).read_text(encoding='''utf-8'''     )

			__lowercase       :   List[Any]        =    [int(__UpperCamelCase     ) for number in data.strip().split(''','''     )]

			__lowercase       :   Optional[int]        =    filter_valid_chars(__UpperCamelCase     )
			for common_word in COMMON_WORDS:
						__lowercase       :   Dict        =    filter_common_word(__UpperCamelCase     ,							__UpperCamelCase     )
						if len(__UpperCamelCase     ) == 1:
									break

			__lowercase       :   Union[str, Any]        =    possibles[0]
			return sum(ord(__UpperCamelCase     ) for char in decoded_text     )


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











'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_A	:			Union[str, Any]         ={
    '''configuration_swiftformer''': [
        '''SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SwiftFormerConfig''',
        '''SwiftFormerOnnxConfig''',
    ]
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A	:			Optional[Any]         =[
			    '''SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''SwiftFormerForImageClassification''',
			    '''SwiftFormerModel''',
			    '''SwiftFormerPreTrainedModel''',
			]

if TYPE_CHECKING:
			from .configuration_swiftformer import (
			    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    SwiftFormerConfig,
			    SwiftFormerOnnxConfig,
			)

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_swiftformer import (
						    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SwiftFormerForImageClassification,
						    SwiftFormerModel,
						    SwiftFormerPreTrainedModel,
						)

else:
			import sys

			_A	:			Tuple         =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

