Test failure with TestValidateAttrs.test_validating_attrs

[shoyer]

This is due to setting multi-dimensional attributes being an error, as of the latest netCDF4-Python release: https://github.com/Unidata/netcdf4-python/blob/master/Changelog

E.g., as seen on Appveyor: https://ci.appveyor.com/project/shoyer/xray/builds/22834250/job/9q0ip6i3cchlbkw2

================================== FAILURES ===================================
___________________ TestValidateAttrs.test_validating_attrs ___________________
self = <xarray.tests.test_backends.TestValidateAttrs object at 0x00000096BE5FAFD0>
    def test_validating_attrs(self):
        def new_dataset():
            return Dataset({'data': ('y', np.arange(10.0))},
                           {'y': np.arange(10)})
    
        def new_dataset_and_dataset_attrs():
            ds = new_dataset()
            return ds, ds.attrs
    
        def new_dataset_and_data_attrs():
            ds = new_dataset()
            return ds, ds.data.attrs
    
        def new_dataset_and_coord_attrs():
            ds = new_dataset()
            return ds, ds.coords['y'].attrs
    
        for new_dataset_and_attrs in [new_dataset_and_dataset_attrs,
                                      new_dataset_and_data_attrs,
                                      new_dataset_and_coord_attrs]:
            ds, attrs = new_dataset_and_attrs()
    
            attrs[123] = 'test'
            with raises_regex(TypeError, 'Invalid name for attr'):
                ds.to_netcdf('test.nc')
    
            ds, attrs = new_dataset_and_attrs()
            attrs[MiscObject()] = 'test'
            with raises_regex(TypeError, 'Invalid name for attr'):
                ds.to_netcdf('test.nc')
    
            ds, attrs = new_dataset_and_attrs()
            attrs[''] = 'test'
            with raises_regex(ValueError, 'Invalid name for attr'):
                ds.to_netcdf('test.nc')
    
            # This one should work
            ds, attrs = new_dataset_and_attrs()
            attrs['test'] = 'test'
            with create_tmp_file() as tmp_file:
                ds.to_netcdf(tmp_file)
    
            ds, attrs = new_dataset_and_attrs()
            attrs['test'] = {'a': 5}
            with raises_regex(TypeError, 'Invalid value for attr'):
                ds.to_netcdf('test.nc')
    
            ds, attrs = new_dataset_and_attrs()
            attrs['test'] = MiscObject()
            with raises_regex(TypeError, 'Invalid value for attr'):
                ds.to_netcdf('test.nc')
    
            ds, attrs = new_dataset_and_attrs()
            attrs['test'] = 5
            with create_tmp_file() as tmp_file:
                ds.to_netcdf(tmp_file)
    
            ds, attrs = new_dataset_and_attrs()
            attrs['test'] = 3.14
            with create_tmp_file() as tmp_file:
                ds.to_netcdf(tmp_file)
    
            ds, attrs = new_dataset_and_attrs()
            attrs['test'] = [1, 2, 3, 4]
            with create_tmp_file() as tmp_file:
                ds.to_netcdf(tmp_file)
    
            ds, attrs = new_dataset_and_attrs()
            attrs['test'] = (1.9, 2.5)
            with create_tmp_file() as tmp_file:
                ds.to_netcdf(tmp_file)
    
            ds, attrs = new_dataset_and_attrs()
            attrs['test'] = np.arange(5)
            with create_tmp_file() as tmp_file:
                ds.to_netcdf(tmp_file)
    
            ds, attrs = new_dataset_and_attrs()
            attrs['test'] = np.arange(12).reshape(3, 4)
            with create_tmp_file() as tmp_file:
>               ds.to_netcdf(tmp_file)
xarray\tests\test_backends.py:3450: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
xarray\core\dataset.py:1323: in to_netcdf
    compute=compute)
xarray\backends\api.py:767: in to_netcdf
    unlimited_dims=unlimited_dims)
xarray\backends\api.py:810: in dump_to_store
    unlimited_dims=unlimited_dims)
xarray\backends\common.py:262: in store
    self.set_attributes(attributes)
xarray\backends\common.py:278: in set_attributes
    self.set_attribute(k, v)
xarray\backends\netCDF4_.py:418: in set_attribute
    _set_nc_attribute(self.ds, key, value)
xarray\backends\netCDF4_.py:294: in _set_nc_attribute
    obj.setncattr(key, value)
netCDF4\_netCDF4.pyx:2781: in netCDF4._netCDF4.Dataset.setncattr
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
>   ???
E   ValueError: multi-dimensional array attributes not supported
netCDF4\_netCDF4.pyx:1514: ValueError

[jhamman]

@shoyer - I'm surprised we had a test for this behavior. Based on Unidata/netcdf4-python#841, it seems we don't want this behavior to work. Can we just remove this test (or better yet, insure the ValueError is raised)?

[shoyer]

Yes, those both sound like good options to me.

[hmaarrfk]

Sorry for posting on such an old thread.

Are attrs supposed to support 1D arrays?

[dcherian]

I remember being surprised by this:
xr.tutorial.load_dataset("air_temperature").air.attrs["actual_range"] gives
array([185.16, 322.1 ], dtype=float32)

[hmaarrfk]

With the netcdf4 back end, I'm not able to save a 1D attr dataset.

I can save my dataset with the h5netcdf backend

[hmaarrfk]

Sorry for noise. It seems that 1D arrays are still supported.

I still had a 2D array lingering in my codebase.