code: def array(shape, dtype=_np.float64, autolock=False):
      
      assert _NP_AVAILABLE, "To use the shared array object, numpy must be available!"
      if not isinstance(dtype, _np.dtype):
          dtype = _np.dtype(dtype)
      # Not bothering to translate the numpy dtypes to ctype types directly,
      # because they're only partially supported. Instead, create a byte ctypes
      # array of the right size and use a view of the appropriate datatype.
      shared_arr = _multiprocessing.Array(
          "b", int(_np.prod(shape) * dtype.alignment), lock=autolock
      )
      with _warnings.catch_warnings():
          # For more information on why this is necessary, see
          # https://www.reddit.com/r/Python/comments/j3qjb/parformatlabpool_replacement
          _warnings.simplefilter("ignore", RuntimeWarning)
          data = _np.ctypeslib.as_array(shared_arr).view(dtype).reshape(shape)
      return data
docs: Factory method for shared memory arrays supporting all numpy dtypes.