html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1193#issuecomment-517056258,https://api.github.com/repos/pydata/xarray/issues/1193,517056258,MDEyOklzc3VlQ29tbWVudDUxNzA1NjI1OA==,26384082,2019-07-31T23:13:35Z,2019-07-31T23:13:35Z,NONE,"In order to maintain a list of currently relevant issues, we mark issues as stale after a period of inactivity

If this issue remains relevant, please comment here or remove the `stale` label; otherwise it will be marked as closed automatically
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,199032440
https://github.com/pydata/xarray/issues/1193#issuecomment-326135257,https://api.github.com/repos/pydata/xarray/issues/1193,326135257,MDEyOklzc3VlQ29tbWVudDMyNjEzNTI1Nw==,2443309,2017-08-30T22:18:25Z,2017-08-30T22:18:25Z,MEMBER,"@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 `scipy`engine 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'```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,199032440
https://github.com/pydata/xarray/issues/1193#issuecomment-270763249,https://api.github.com/repos/pydata/xarray/issues/1193,270763249,MDEyOklzc3VlQ29tbWVudDI3MDc2MzI0OQ==,1217238,2017-01-05T21:30:51Z,2017-01-05T21:30:51Z,MEMBER,"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.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,199032440
https://github.com/pydata/xarray/issues/1193#issuecomment-270737056,https://api.github.com/repos/pydata/xarray/issues/1193,270737056,MDEyOklzc3VlQ29tbWVudDI3MDczNzA1Ng==,6645714,2017-01-05T19:38:47Z,2017-01-05T20:01:34Z,CONTRIBUTOR,"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","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,199032440