class_docstr: Python binding for Porcupine wake word engine. It detects utterances of given keywords within an incoming stream of
  audio in real-time. It processes incoming audio in consecutive frames and for each frame emits the detection result.
  The number of samples per frame can be attained by calling `.frame_length`. The incoming audio needs to have a
  sample rate equal to `.sample_rate` and be 16-bit linearly-encoded. Porcupine operates on single-channel audio.
code: def _get_error_stack(self) -> Sequence[str]:
      message_stack_ref = POINTER(c_char_p)()
      message_stack_depth = c_int()
      status = self._get_error_stack_func(
          byref(message_stack_ref), byref(message_stack_depth)
      )
      if status is not self.PicovoiceStatuses.SUCCESS:
          raise self._PICOVOICE_STATUS_TO_EXCEPTION[status](
              message="Unable to get Porcupine error state"
          )
  
      message_stack = list()
      for i in range(message_stack_depth.value):
          message_stack.append(message_stack_ref[i].decode("utf-8"))
  
      self._free_error_stack_func(message_stack_ref)
  
      return message_stack
  
imports: import os
  from ctypes import *
  from enum import Enum
  from typing import Sequence
label_desc: Use image node_id 7 for calling the Porcupine obj's underlying member method code with example usage: obj._get_error_stack() and returns: message_stack