How to use the cfgrib.xarray_store function in cfgrib

def test_getitem_list(cache):
    da = xarray_store.open_dataset(TEST_DATA, cache=cache).data_vars['t']
    va = da.values[:]

    assert da.isel(number=[2, 3, 4, 5]).mean() == va[[2, 3, 4, 5]].mean()
    assert da.isel(number=[4, 3, 2, 5]).mean() == va[[4, 3, 2, 5]].mean()
    assert da.sel(number=[2, 3, 4, 5]).mean() == va[[2, 3, 4, 5]].mean()
    assert da.sel(number=[4, 3, 2, 5]).mean() == va[[4, 3, 2, 5]].mean()

def test_reanalysis_Dataset(test_file):
    dataset, request, key_count = TEST_FILES[test_file]
    path = cdscommon.ensure_data(dataset, request, name='cds-' + test_file + '-{uuid}.grib')

    res = cfgrib.xarray_store.open_dataset(path)
    res.to_netcdf(path[:-5] + '.nc')

def test_cds():
    ds = xarray_store.open_dataset(TEST_DATA1)

    res = cfcoords.translate_coords(ds, coord_model=datamodels.CDS)

    assert set(res.dims) == {'forecast_reference_time', 'lat', 'lon', 'plev', 'realization'}
    assert set(res.coords) == {
        'forecast_reference_time',
        'lat',
        'leadtime',
        'lon',
        'plev',
        'realization',
        'time',
    }

    ds = xarray_store.open_dataset(TEST_DATA2)

def test_open_dataset():
    res = xarray_store.open_dataset(TEST_DATA)

    assert res.attrs['GRIB_edition'] == 1

    var = res['t']
    assert var.attrs['GRIB_gridType'] == 'regular_ll'
    assert var.attrs['units'] == 'K'
    assert var.dims == ('number', 'time', 'isobaricInhPa', 'latitude', 'longitude')

    assert var.mean() > 0.0

    with pytest.raises(ValueError):
        xarray_store.open_dataset(TEST_DATA, engine='netcdf4')

    res = xarray_store.open_dataset(TEST_IGNORE, backend_kwargs={'errors': 'warn'})
    assert 'isobaricInhPa' in res.dims

def test_large_Dataset():
    dataset, request, key_count = TEST_FILES['seasonal-original-pressure-levels-ecmwf']
    # make the request large
    request['leadtime_hour'] = list(range(720, 1445, 24))
    request['grid'] = ['1', '1']
    path = cdscommon.ensure_data(dataset, request, name='cds-' + dataset + '-LARGE-{uuid}.grib')

    res = cfgrib.xarray_store.open_dataset(path)
    res.to_netcdf(path[:-5] + '.nc')

def test_all(cache):
    da = xarray_store.open_dataset(TEST_DATA, cache=cache).data_vars['t']
    va = da.values[:]

    assert va.shape == (10, 4, 2, 61, 120)

    assert da.mean() == va.mean()

def test_canonical_dataset_to_grib(grib_name, tmpdir):
    grib_path = os.path.join(SAMPLE_DATA_FOLDER, grib_name + '.grib')
    out_path = str(tmpdir.join(grib_name + '.grib'))

    res = xarray_store.open_dataset(grib_path)

    xarray_to_grib.canonical_dataset_to_grib(res, out_path)
    reread = xarray_store.open_dataset(out_path)
    assert res.equals(reread)

assert res.attrs['GRIB_edition'] == 1

    var = res['t']
    assert var.attrs['GRIB_gridType'] == 'regular_ll'
    assert var.attrs['units'] == 'K'
    assert var.dims == ('number', 'time', 'isobaricInhPa', 'latitude', 'longitude')

    assert var.mean() > 0.0

    with pytest.raises(ValueError):
        xarray_store.open_dataset(TEST_DATA, engine='netcdf4')

    res = xarray_store.open_dataset(TEST_IGNORE, backend_kwargs={'errors': 'warn'})
    assert 'isobaricInhPa' in res.dims

    res = xarray_store.open_dataset(TEST_IGNORE, backend_kwargs={'errors': 'ignore'})
    assert 'isobaricInhPa' in res.dims

    with pytest.raises(ValueError):
        xarray_store.open_dataset(TEST_IGNORE, backend_kwargs={'errors': 'raise'})

def test_open_dataset(grib_name):
    grib_path = os.path.join(SAMPLE_DATA_FOLDER, grib_name + '.grib')
    res = xarray_store.open_dataset(grib_path, cache=False)
    print(res)

def test_Dataset(test_file):
    dataset, request, key_count = TEST_FILES[test_file]
    path = cdscommon.ensure_data(dataset, request, name='cds-' + test_file + '-{uuid}.grib')

    res = cfgrib.xarray_store.open_dataset(path)
    res.to_netcdf(path[:-5] + '.nc')