code: def np_dtype_to_arrays(any_real_numpy_dtype):
      """
      Fixture returning actual and expected dtype, pandas and numpy arrays and
      mask from a given numpy dtype
      """
      np_dtype = np.dtype(any_real_numpy_dtype)
      pa_type = pa.from_numpy_dtype(np_dtype)
  
      # None ensures the creation of a bitmask buffer.
      pa_array = pa.array([0, 1, 2, None], type=pa_type)
      # Since masked Arrow buffer slots are not required to contain a specific
      # value, assert only the first three values of the created np.array
      np_expected = np.array([0, 1, 2], dtype=np_dtype)
      mask_expected = np.array([True, True, True, False])
      return np_dtype, pa_array, np_expected, mask_expected
  
file_path: pandas/pandas/tests/arrays/masked/test_arrow_compat.py
imports: import numpy
  import pytest
  import pandas
  import pandas._testing
  from pandas.core.arrays.arrow._arrow_utils import pyarrow_array_to_numpy_and_mask
label_desc: Use image node_id 8 for calling a global function with example usage: np_dtype_to_arrays(any_real_numpy_dtype) and returns: np_dtype,  pa_array,  np_expected,  mask_expected