code: def test_fetch_atlas_msdl(tmp_path, request_mocker):
      labels = pd.DataFrame(
          {
              "x": [1.5, 1.2],
              "y": [1.5, 1.3],
              "z": [1.5, 1.4],
              "name": ["Aud", "DMN"],
              "net name": ["Aud", "DMN"],
          }
      )
      root = Path("MSDL_rois")
      archive = {
          root / "msdl_rois_labels.csv": labels.to_csv(index=False),
          root / "msdl_rois.nii": "",
          root / "README.txt": "",
      }
      request_mocker.url_mapping["*MSDL_rois.zip"] = dict_to_archive(
          archive, "zip"
      )
      dataset = atlas.fetch_atlas_msdl(data_dir=tmp_path, verbose=0)
  
      assert isinstance(dataset.labels, list)
      assert isinstance(dataset.region_coords, list)
      assert isinstance(dataset.networks, list)
      assert isinstance(dataset.maps, str)
      assert request_mocker.url_count == 1
      assert dataset.description != ""
  
imports: import itertools
  import os
  import re
  from pathlib import Path
  import nibabel
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_array_equal
  from nilearn._utils import data_gen
  from nilearn._utils.testing import serialize_niimg
  from nilearn.conftest import _rng
  from nilearn.datasets import atlas
  from nilearn.datasets._utils import fetch_files
  from nilearn.datasets.tests._testing import dict_to_archive
  from nilearn.image import get_data
label_desc: Use image node_id 15 for calling a global function with example usage: test_fetch_atlas_msdl(tmp_path, request_mocker) without return types