'''simple docstring'''






from __future__ import annotations

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

_UpperCAmelCase    :     str         =       (
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
_UpperCAmelCase    :     list[int]         =       [ord(letter) for letter in string.ascii_lowercase]
_UpperCAmelCase    :     set[int]         =       {ord(char) for char in VALID_CHARS}

_UpperCAmelCase    :     list[str]         =       ["the", "be", "to", "of", "and", "in", "that", "have"]





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			list[int]   ,		__snake_case							:			tuple[int, ...]				):
     _A    		=  ""
     _A    		=  42
     _A    		=  42
     _A    		=  42

     for keychar, cipherchar in zip(cycle(__snake_case				)   ,		__snake_case				):
          _A    		=  cipherchar ^ keychar
          if decodedchar not in VALID_INTS:
               return None
          decoded += chr(__snake_case				)

     return decoded





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			list[int]				):
     _A    		=  []
     for key in product(__snake_case   ,		repeat=3				):
          _A    		=  try_key(__snake_case   ,		__snake_case				)
          if encoded is not None:
               possibles.append(__snake_case				)
     return possibles





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			list[str]   ,		__snake_case							:			str				):
     return [possible for possible in possibles if common_word in possible.lower()]





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			str = "p059_cipher.txt"				):
     _A    		=  42
     _A    		=  42
     _A    		=  42
     _A    		=  42
     _A    		=  Path(__snake_case				).parent.joinpath(__snake_case				).read_text(encoding='utf-8'				)

     _A    		=  [int(__snake_case				) for number in data.strip().split(','				)]

     _A    		=  filter_valid_chars(__snake_case				)
     for common_word in COMMON_WORDS:
          _A    		=  filter_common_word(__snake_case   ,		__snake_case				)
          if len(__snake_case				) == 1:
               break

     _A    		=  possibles[0]
     return sum(ord(__snake_case				) for char in decoded_text				)


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




'''simple docstring'''






import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand





def  _SCREAMING_SNAKE_CASE		(      __snake_case							:			Union[str, Any]				):
     return EnvironmentCommand()







class lowercase_       (		_UpperCamelCase			):







   """simple docstring"""

   @staticmethod
   def 	__UpperCAmelCase   (      UpperCamelCase__      :			ArgumentParser     )  ->			List[str]:
        _A    		=  parser.add_parser('env'     )
        download_parser.set_defaults(func=UpperCamelCase__     )
   def 	__UpperCAmelCase   (      self      :			Optional[int]     )  ->			Optional[Any]:
        _A    		=  huggingface_hub.__version__

        _A    		=  'not installed'
        _A    		=  'NA'
        if is_torch_available():
             import torch

             _A    		=  torch.__version__
             _A    		=  torch.cuda.is_available()

        _A    		=  'not installed'
        if is_transformers_available():
             import transformers

             _A    		=  transformers.__version__

        _A    		=  'not installed'
        if is_accelerate_available():
             import accelerate

             _A    		=  accelerate.__version__

        _A    		=  'not installed'
        if is_xformers_available():
             import xformers

             _A    		=  xformers.__version__

        _A    		=  {
            '`diffusers` version': version,
            'Platform': platform.platform(),
            'Python version': platform.python_version(),
            'PyTorch version (GPU?)': f'{pt_version} ({pt_cuda_available})',
            'Huggingface_hub version': hub_version,
            'Transformers version': transformers_version,
            'Accelerate version': accelerate_version,
            'xFormers version': xformers_version,
            'Using GPU in script?': '<fill in>',
            'Using distributed or parallel set-up in script?': '<fill in>',
        }

        print('\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'     )
        print(self.format_dict(UpperCamelCase__     )     )

        return info

   @staticmethod
   def 	__UpperCAmelCase   (      UpperCamelCase__      :			List[Any]     )  ->			Dict:
        return "\n".join([f'- {prop}: {val}' for prop, val in d.items()]     ) + "\n"



