Keeping unused dimensions when opening a Dataset?

What is your issue?

I am attempting to open a dataset which has unused dimensions. Is it possible for this information to be retained?

import xarray as xr
import netCDF4
import numpy as np

# create dataset with dims x, y and a variable f
f = netCDF4.Dataset("test.nc", "w")
f.createDimension("x", 2)
f.createDimension("y", 3)
f.createVariable("f", np.float32)
print(f)
f.close()

print('\n')

# open dataset with xarray
ds = xr.open_dataset('test.nc')
print(ds)

This prints the following:

<class 'netCDF4._netCDF4.Dataset'>
root group (NETCDF4 data model, file format HDF5):
    dimensions(sizes): x(2), y(3)
    variables(dimensions): float32 f()
    groups: 


<xarray.Dataset> Size: 4B
Dimensions:  ()
Data variables:
    f        float32 4B ...

The output of ncdump test.nc is shown here:

netcdf test {
dimensions:
        x = 2 ;
        y = 3 ;
variables:
        float f ;
data:

 f = _ ;
}

This appears to be the same issue as was discussed here, but I could not find if the OP ever opened an issue.

Start by running the provided Python reproduction with netCDF4 and xarray.open_dataset, then trace how the unused dimensions are represented after opening the file. Done means the opened xarray.Dataset retains dimensions x and y with their sizes, and the behavior is covered by a regression test based on this example.