

"""simple docstring"""

from __future__ import annotations

from string import ascii_letters





def 					__UpperCamelCase (     a__:			str			,						a__:			int			,						a__:			str | None = None      )					->      str:




					"""simple docstring"""



					__lowercase        =      alphabet or ascii_letters

					# The final result string
					__lowercase        =      ''''''

					for character in input_string:
										if character not in alpha:
															# Append without encryption if character is not in the alphabet
															result += character
										else:
															# Get the index of the new key and make sure it isn't too large
															__lowercase        =      (alpha.index(a__      ) + key) % len(a__      )

															# Append the encoded character to the alphabet
															result += alpha[new_key]

					return result





def 					__UpperCamelCase (     a__:			str			,						a__:			int			,						a__:			str | None = None      )					->      str:




					"""simple docstring"""



					key *= -1

					return encrypt(a__			,						a__			,						a__      )





def 					__UpperCamelCase (     a__:			str			,						a__:			str | None = None      )					->      dict[int, str]:




					"""simple docstring"""



					__lowercase        =      alphabet or ascii_letters

					# To store data on all the combinations
					__lowercase        =      {}

					# Cycle through each combination
					for key in range(1			,						len(a__      ) + 1      ):
										# Decrypt the message and store the result in the data
										__lowercase        =      decrypt(a__			,						a__			,						a__      )

					return brute_force_data


if __name__ == "__main__":
							while True:
														print(f"""\n{"-" * 10}\n Menu\n{"-" * 10}""")
														print(*["""1.Encrypt""", """2.Decrypt""", """3.BruteForce""", """4.Quit"""], sep="""\n""")

														# get user input
														a__			:						Union[str, Any]							=			input("""\nWhat would you like to do?: """).strip() or """4"""

														# run functions based on what the user chose
														if choice not in ("1", "2", "3", "4"):
																					print("""Invalid choice, please enter a valid choice""")
														elif choice == "1":
																					a__			:						Tuple							=			input("""Please enter the string to be encrypted: """)
																					a__			:						Tuple							=			int(input("""Please enter off-set: """).strip())

																					print(encrypt(input_string, key))
														elif choice == "2":
																					a__			:						Dict							=			input("""Please enter the string to be decrypted: """)
																					a__			:						int							=			int(input("""Please enter off-set: """).strip())

																					print(decrypt(input_string, key))
														elif choice == "3":
																					a__			:						int							=			input("""Please enter the string to be decrypted: """)
																					a__			:						Optional[Any]							=			brute_force(input_string)

																					for key, value in brute_force_data.items():
																												print(f"""Key: {key} | Message: {value}""")

														elif choice == "4":
																					print("""Goodbye.""")
																					break





"""simple docstring"""

from typing import TYPE_CHECKING

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


a__			:						str							=			{
    """configuration_rwkv""": ["""RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RwkvConfig""", """RwkvOnnxConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a__			:						Optional[int]							=			[
							    """RWKV_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """RwkvForCausalLM""",
							    """RwkvModel""",
							    """RwkvPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_rwkv import (
														    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
														    RwkvForCausalLM,
														    RwkvModel,
														    RwkvPreTrainedModel,
														)
else:
							import sys

							a__			:						List[str]							=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


