code: def pyarrow_array_to_numpy_and_mask(
      arr, dtype: np.dtype
  ) -> tuple[np.ndarray, np.ndarray]:
      """
      Convert a primitive pyarrow.Array to a numpy array and boolean mask based
      on the buffers of the Array.
  
      At the moment pyarrow.BooleanArray is not supported.
  
      Parameters
      ----------
      arr : pyarrow.Array
      dtype : numpy.dtype
  
      Returns
      -------
      (data, mask)
          Tuple of two numpy arrays with the raw data (with specified dtype) and
          a boolean mask (validity mask, so False means missing)
      """
      dtype = np.dtype(dtype)
  
      if pyarrow.types.is_null(arr.type):
          # No initialization of data is needed since everything is null
          data = np.empty(len(arr), dtype=dtype)
          mask = np.zeros(len(arr), dtype=bool)
          return data, mask
      buflist = arr.buffers()
      # Since Arrow buffers might contain padding and the data might be offset,
      # the buffer gets sliced here before handing it to numpy.
      # See also https://github.com/pandas-dev/pandas/issues/40896
      offset = arr.offset * dtype.itemsize
      length = len(arr) * dtype.itemsize
      data_buf = buflist[1][offset : offset + length]
      data = np.frombuffer(data_buf, dtype=dtype)
      bitmask = buflist[0]
      if bitmask is not None:
          mask = pyarrow.BooleanArray.from_buffers(
              pyarrow.bool_(),
              len(arr),
              [None, bitmask],
              offset=arr.offset,
          )
          mask = np.asarray(mask)
      else:
          mask = np.ones(len(arr), dtype=bool)
      return data, mask
  
file_path: pandas/pandas/core/arrays/arrow/_arrow_utils.py
imports: from __future__ import annotations
  import warnings
  import numpy
  import pyarrow
  from pandas.errors import PerformanceWarning
  from pandas.util._exceptions import find_stack_level
label_desc: Use image node_id 2 for calling a global function with example usage: pyarrow_array_to_numpy_and_mask(arr, dtype) and returns: data,  mask, data,  mask