

'''simple docstring'''
import random
import sys

_lowerCamelCase	 =			"ABCDEFGHIJKLMNOPQRSTUVWXYZ"


def       a__    (  )			-> str:


	"""simple docstring"""





	UpperCAmelCase_			:	int      =   input("Enter message: "							)
	UpperCAmelCase_			:	Union[str, Any]      =   'LFWOAYUISVKMNXPBDCRJTQEGHZ'
	UpperCAmelCase_			:	List[str]      =   input("Encrypt/Decrypt [e/d]: "							)

	check_valid_key(_lowerCamelCase							)

	if resp.lower().startswith("e"							):
		UpperCAmelCase_			:	Optional[Any]      =   'encrypt'
		UpperCAmelCase_			:	int      =   encrypt_message(_lowerCamelCase     ,							_lowerCamelCase							)
	elif resp.lower().startswith("d"							):
		UpperCAmelCase_			:	int      =   'decrypt'
		UpperCAmelCase_			:	Union[str, Any]      =   decrypt_message(_lowerCamelCase     ,							_lowerCamelCase							)

	print(F'''\n{mode.title()}ion: \n{translated}'''							)


def       a__    (  _SCREAMING_SNAKE_CASE					:    str							)			-> List[Any]:


	"""simple docstring"""





	UpperCAmelCase_			:	Any      =   list(_lowerCamelCase							)
	UpperCAmelCase_			:	Tuple      =   list(_lowerCamelCase							)
	key_list.sort()
	letters_list.sort()

	if key_list != letters_list:
		sys.exit("Error in the key or symbol set."							)


def       a__    (  _SCREAMING_SNAKE_CASE					:    Dict     ,							_SCREAMING_SNAKE_CASE					:    Any							)			-> Union[str, Any]:


	"""simple docstring"""





	return translate_message(_lowerCamelCase     ,							_lowerCamelCase     ,							"encrypt"							)


def       a__    (  _SCREAMING_SNAKE_CASE					:    int     ,							_SCREAMING_SNAKE_CASE					:    int							)			-> Union[str, Any]:


	"""simple docstring"""





	return translate_message(_lowerCamelCase     ,							_lowerCamelCase     ,							"decrypt"							)


def       a__    (  _SCREAMING_SNAKE_CASE					:    str     ,							_SCREAMING_SNAKE_CASE					:    Union[str, Any]     ,							_SCREAMING_SNAKE_CASE					:    Dict							)			-> Any:


	"""simple docstring"""





	UpperCAmelCase_			:	str      =   ''
	UpperCAmelCase_			:	Union[str, Any]      =   LETTERS
	UpperCAmelCase_			:	Optional[int]      =   key

	if mode == "decrypt":
		UpperCAmelCase_			:	int      =   chars_b, chars_a

	for symbol in message:
		if symbol.upper() in chars_a:
			UpperCAmelCase_			:	List[Any]      =   chars_a.find(symbol.upper()							)
			if symbol.isupper():
				translated += chars_b[sym_index].upper()
			else:
				translated += chars_b[sym_index].lower()
		else:
			translated += symbol

	return translated


def       a__    (  )			-> Optional[Any]:


	"""simple docstring"""





	UpperCAmelCase_			:	Tuple      =   list(_lowerCamelCase							)
	random.shuffle(_lowerCamelCase							)
	return "".join(_lowerCamelCase							)


if __name__ == "__main__":
					main()












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

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A_			: Dict				=			{"configuration_qdqbert": ["QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "QDQBertConfig"]}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A_			: Tuple				=			[
          "QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "QDQBertForMaskedLM",
          "QDQBertForMultipleChoice",
          "QDQBertForNextSentencePrediction",
          "QDQBertForQuestionAnswering",
          "QDQBertForSequenceClassification",
          "QDQBertForTokenClassification",
          "QDQBertLayer",
          "QDQBertLMHeadModel",
          "QDQBertModel",
          "QDQBertPreTrainedModel",
          "load_tf_weights_in_qdqbert",
      ]


if TYPE_CHECKING:
      from .configuration_qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_qdqbert import (
                QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                QDQBertForMaskedLM,
                QDQBertForMultipleChoice,
                QDQBertForNextSentencePrediction,
                QDQBertForQuestionAnswering,
                QDQBertForSequenceClassification,
                QDQBertForTokenClassification,
                QDQBertLayer,
                QDQBertLMHeadModel,
                QDQBertModel,
                QDQBertPreTrainedModel,
                load_tf_weights_in_qdqbert,
            )


else:
      import sys

      A_			: Tuple				=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

