def METHOD_NAME(tmp_path):
    subdir = tmp_path / "tmp"
    subdir.mkdir()
    (subdir / "labels.csv").touch()
    (subdir / "img.nii.gz").touch()
    archive_spec = {
        "empty_data": subdir,
        "empty_data_path.txt": str(subdir),
        Path("data", "labels.csv"): "a,b,c",
        Path("data", "img.nii.gz"): generate_fake_fmri()[0],
        Path("a", "b", "c"): (100).to_bytes(
            length=1, byteorder="big", signed=False
        ),
    }
    targz = _testing.dict_to_archive(archive_spec)
    extract_dir = tmp_path / "extract"
    extract_dir.mkdir()
    archive_path = tmp_path / "archive"
    with archive_path.open("wb") as f:
        f.write(targz)
    with tarfile.open(str(archive_path)) as tarf:
        tarf.extractall(str(extract_dir))
    img = image.load_img(str(extract_dir / "data" / "img.nii.gz"))
    assert img.shape == (10, 11, 12, 17)
    with (extract_dir / "a" / "b" / "c").open("rb") as f:
        assert int.from_bytes(f.read(), byteorder="big", signed=False) == 100
    with open(str(extract_dir / "empty_data" / "labels.csv")) as f:
        assert f.read() == ""
    zip_archive = _testing.dict_to_archive(
        {"readme.txt": "hello", "archive": targz}, "zip"
    )
    with archive_path.open("wb") as f:
        f.write(zip_archive)
    with zipfile.ZipFile(str(archive_path)) as zipf:
        with zipf.open("archive", "r") as f:
            assert f.read() == targz
    from_list = _testing.list_to_archive(archive_spec.keys())
    with archive_path.open("wb") as f:
        f.write(from_list)
    with tarfile.open(str(archive_path)) as tarf:
        assert sorted(map(Path, tarf.getnames())) == sorted(
            list(map(Path, archive_spec.keys()))
            + [Path("."), Path("a"), Path("a", "b"), Path("data")]
        )