issue_comments: 979759002

Would like to chime in that we use a similar approach as in the last comment of @DerWeh . But we extend this by overloading the __str__ method of the enum.Enum base class, and implement a Dimension base class to use for our enum dimensions:

``` class Dimension(str, enum.Enum): """Base class for all dimension enums

It is of type string because this is needed for xarray.
"""

def __str__(self):
    return type(self).__name__ + "." + self.name

```

Using this the xarray output is more consistent:

```

class CoordId(Dimension): ... LAT = 'lat' ... LON = 'lon' ... xr.DataArray( ... data=np.arange(3 * 2).reshape(3, 2), ... coords={CoordId.LAT: [1, 2, 3], CoordId.LON: [7, 8]}, ... dims=[CoordId.LAT, CoordId.LON], ... ) <xarray.DataArray (CoordId.LAT: 3, CoordId.LON: 2)> array([[0, 1], [2, 3], [4, 5]]) Coordinates: * CoordId.LAT (CoordId.LAT) int64 1 2 3 * CoordId.LON (CoordId.LON) int64 7 8 ```

We then have deserialization code, that re-creates enum members when reading NetCDF files with corresponding dimensions (and coordinates). Access to coordinates works with enum members as well as their string value.