






"""simple docstring"""



import sys
from collections.abc import Mapping

import numpy as np
import pyarrow as pa

from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter

class 			a	(  TensorFormatter[Mapping, np.ndarray, Mapping]      ):







    def __init__(     self				,						_lowerCamelCase=None				,						**_lowerCamelCase			):
      super().__init__(features=_lowerCamelCase			)
      lowercase				       =			np_array_kwargs







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      if isinstance(_lowerCamelCase				,						_lowerCamelCase			):
        if column and all(
            isinstance(_lowerCamelCase				,						np.ndarray			) and x.shape == column[0].shape and x.dtype == column[0].dtype for x in column			):
          return np.stack(_lowerCamelCase			)
        else:
          # don't use np.array(column, dtype=object)
          # since it fails in certain cases
          # see https://stackoverflow.com/q/51005699
          lowercase				       =			np.empty(len(_lowerCamelCase			)				,						dtype=_lowerCamelCase			)
          lowercase				       =			column
          return out
      return column







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      if isinstance(_lowerCamelCase				,						(str, bytes, type(_lowerCamelCase			))			):
        return value
      elif isinstance(_lowerCamelCase				,						(np.character, np.ndarray)			) and np.issubdtype(value.dtype				,						np.character			):
        return value
      elif isinstance(_lowerCamelCase				,						np.number			):
        return value

      lowercase				       =			{}

      if isinstance(_lowerCamelCase				,						np.ndarray			) and np.issubdtype(value.dtype				,						np.integer			):
        lowercase				       =			{'dtype': np.intaa}
      elif isinstance(_lowerCamelCase				,						np.ndarray			) and np.issubdtype(value.dtype				,						np.floating			):
        lowercase				       =			{'dtype': np.floataa}
      elif config.PIL_AVAILABLE and "PIL" in sys.modules:
        import PIL.Image

        if isinstance(_lowerCamelCase				,						PIL.Image.Image			):
          return np.asarray(_lowerCamelCase				,						**self.np_array_kwargs			)

      return np.asarray(_lowerCamelCase				,						**{**default_dtype, **self.np_array_kwargs}			)







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      # support for torch, tf, jax etc.
      if config.TORCH_AVAILABLE and "torch" in sys.modules:
        import torch

        if isinstance(_lowerCamelCase				,						torch.Tensor			):
          return self._tensorize(data_struct.detach().cpu().numpy()[()]			)
      if hasattr(_lowerCamelCase				,						'__array__'			) and not isinstance(_lowerCamelCase				,						(np.ndarray, np.character, np.number)			):
        lowercase				       =			data_struct.__array__()
      # support for nested types like struct of list of struct
      if isinstance(_lowerCamelCase				,						np.ndarray			):
        if data_struct.dtype == object:
          return self._consolidate([self.recursive_tensorize(_lowerCamelCase			) for substruct in data_struct]			)
      if isinstance(_lowerCamelCase				,						(list, tuple)			):
        return self._consolidate([self.recursive_tensorize(_lowerCamelCase			) for substruct in data_struct]			)
      return self._tensorize(_lowerCamelCase			)







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      return map_nested(self._recursive_tensorize				,						_lowerCamelCase				,						map_list=_lowerCamelCase			)







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      lowercase				       =			self.numpy_arrow_extractor().extract_row(_lowerCamelCase			)
      lowercase				       =			self.python_features_decoder.decode_row(_lowerCamelCase			)
      return self.recursive_tensorize(_lowerCamelCase			)







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      lowercase				       =			self.numpy_arrow_extractor().extract_column(_lowerCamelCase			)
      lowercase				       =			self.python_features_decoder.decode_column(_lowerCamelCase				,						pa_table.column_names[0]			)
      lowercase				       =			self.recursive_tensorize(_lowerCamelCase			)
      lowercase				       =			self._consolidate(_lowerCamelCase			)
      return column







    def      UpperCamelCase_ (     self				,						_lowerCamelCase			):
      lowercase				       =			self.numpy_arrow_extractor().extract_batch(_lowerCamelCase			)
      lowercase				       =			self.python_features_decoder.decode_batch(_lowerCamelCase			)
      lowercase				       =			self.recursive_tensorize(_lowerCamelCase			)
      for column_name in batch:
        lowercase				       =			self._consolidate(batch[column_name]			)
      return batch








'''simple docstring'''





from __future__ import annotations

import random
import string




class      UpperCamelCase       :



  def __init__(			self		,     __lowerCAmelCase = None ):







      '''simple docstring'''


      _a				:							List[Any]							       =      passcode or self.__passcode_creator()
      _a				:							List[str]							       =      self.__make_key_list()
      _a				:							Optional[int]							       =      self.__make_shift_key()



  def __str__(			self ):







      '''simple docstring'''


      return "".join(self.__passcode )



  def     a_							(			self		,     __lowerCAmelCase ):







      '''simple docstring'''


      for i in range(1		,     len(__lowerCAmelCase )		,     2 ):
          iterlist[i] *= -1
      return iterlist



  def     a_							(			self ):







      '''simple docstring'''


      _a				:							Optional[int]							       =      string.ascii_letters + string.digits
      _a				:							str							       =      [random.choice(__lowerCAmelCase ) for _ in range(random.randint(10		,     20 ) )]
      return password



  def     a_							(			self ):







      '''simple docstring'''


      _a				:							Dict							       =      (
          string.ascii_letters + string.digits + string.punctuation + """ \t\n"""
      )

      _a				:							str							       =      []

      # creates points known as breakpoints to break the key_list_options at those
      # points and pivot each substring
      _a				:							Dict							       =      sorted(set(self.__passcode ) )
      _a				:							list[str]							       =      []

      # algorithm for creating a new shuffled list, keys_l, out of key_list_options
      for i in key_list_options:
          temp_list.extend(__lowerCAmelCase )

          # checking breakpoints at which to pivot temporary sublist and add it into
          # keys_l
          if i in breakpoints or i == key_list_options[-1]:
              keys_l.extend(temp_list[::-1] )
              temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
      return keys_l



  def     a_							(			self ):







      '''simple docstring'''


      _a				:							Optional[Any]							       =      sum(self.__neg_pos([ord(__lowerCAmelCase ) for x in self.__passcode] ) )
      return num if num > 0 else len(self.__passcode )



  def     a_							(			self		,     __lowerCAmelCase ):







      '''simple docstring'''


      _a				:							Tuple							       =      """"""

      # decoding shift like Caesar cipher algorithm implementing negative shift or
      # reverse shift or left shift
      for i in encoded_message:
          _a				:							List[str]							       =      self.__key_list.index(__lowerCAmelCase )
          decoded_message += self.__key_list[
              (position - self.__shift_key) % -len(self.__key_list )
          ]

      return decoded_message



  def     a_							(			self		,     __lowerCAmelCase ):







      '''simple docstring'''


      _a				:							List[str]							       =      """"""

      # encoding shift like Caesar cipher algorithm implementing positive shift or
      # forward shift or right shift
      for i in plaintext:
          _a				:							Any							       =      self.__key_list.index(__lowerCAmelCase )
          encoded_message += self.__key_list[
              (position + self.__shift_key) % len(self.__key_list )
          ]

      return encoded_message






def UpperCAmelCase    (       UpperCAmelCase_ = "Hello, this is a modified Caesar cipher"						):
    _a				:							Union[str, Any]							       =      ShuffledShiftCipher()
    return cipa.decrypt(cipa.encrypt(UpperCAmelCase_						)						)


if __name__ == "__main__":
  import doctest

  doctest.testmod()


