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@petercable - do you recall which backend/engine you were using? Did you have netcdf4 installed? I'm not able to reproduce this with either netcdf4 or h5netcdf. The scipyengine does result in an error:

Python In [4]: import xarray as xr ...: import numpy as np ...: engine = 'scipy' ...: a = np.array([[]], 'str') ...: ...: ds = xr.Dataset() ...: ds['x'] = (['dim0', 'dim1'], a, {}) ...: ds.to_netcdf('test.nc', engine=engine) ...: ...: ds = xr.open_dataset('test.nc', engine=engine) ...: ds.load() ...: print(ds)

``` ---> 10 ds = xr.open_dataset('test.nc', engine='scipy') 11 ds.load()

/Users/jhamman/Dropbox/src/xarray/xarray/backends/api.py in open_dataset(filename_or_obj, group, decode_cf, mask_and_scale, decode_times, autoclose, concat_characters, decode_coords, engine, chunks, lock, cache, drop_variables) 283 elif engine == 'scipy': 284 store = backends.ScipyDataStore(filename_or_obj, --> 285 autoclose=autoclose) 286 elif engine == 'pydap': 287 store = backends.PydapDataStore(filename_or_obj)

/Users/jhamman/Dropbox/src/xarray/xarray/backends/scipy_.py in init(self, filename_or_obj, mode, format, group, writer, mmap, autoclose) 133 filename=filename_or_obj, 134 mode=mode, mmap=mmap, version=version) --> 135 self.ds = opener() 136 self._autoclose = autoclose 137 self._isopen = True

/Users/jhamman/Dropbox/src/xarray/xarray/backends/scipy_.py in _open_scipy_netcdf(filename, mode, mmap, version) 81 try: 82 return scipy.io.netcdf_file(filename, mode=mode, mmap=mmap, ---> 83 version=version) 84 except TypeError as e: # netcdf3 message is obscure in this case 85 errmsg = e.args[0]

/Users/jhamman/anaconda/envs/xarray36/lib/python3.6/site-packages/scipy/io/netcdf.py in init(self, filename, mode, mmap, version, maskandscale) 264 265 if mode in 'ra': --> 266 self._read() 267 268 def setattr(self, attr, value):

/Users/jhamman/anaconda/envs/xarray36/lib/python3.6/site-packages/scipy/io/netcdf.py in _read(self) 591 self._read_dim_array() 592 self._read_gatt_array() --> 593 self._read_var_array() 594 595 def _read_numrecs(self):

/Users/jhamman/anaconda/envs/xarray36/lib/python3.6/site-packages/scipy/io/netcdf.py in read_var_array(self) 672 else: # not a record variable 673 # Calculate size to avoid problems with vsize (above) --> 674 a_size = reduce(mul, shape, 1) * size 675 if self.use_mmap: 676 data = self._mm_buf[begin:begin_+a_size].view(dtype=dtype_)

TypeError: unsupported operand type(s) for *: 'int' and 'NoneType'```

This looks like a bug to me.

The simplest thing would be to ensure that we never try to view the array with dtype='S0' (which is not valid). So some sort of special case for a size-zero trailing dimension in char_to_string is probably the right approach.

I found that changing char_to_string resulted in dropping the 0 length dimension:

before:

<xarray.Dataset> Dimensions: (dim0: 1, dim1: 0) Coordinates: * dim0 (dim0) int64 0 * dim1 (dim1) int64 Data variables: x (dim0, dim1) |S1

after:

<xarray.Dataset> Dimensions: (dim0: 1) Coordinates: * dim0 (dim0) int64 0 Data variables: x (dim0) |S1

So, instead I modified conventions.decode_cf_variable to not wrap character arrays with a terminal zero length dimension as CharToStringArray:

if concat_characters: if data.dtype.kind == 'S' and data.dtype.itemsize == 1 and data.shape[-1] != 0: dimensions = dimensions[:-1] data = CharToStringArray(data)

And this appears to round-trip correctly.

EDIT: fixed output when modifying char_to_string