What happened?

I found myself using a netcdf with empty units and by using xarray i was unable to use open_dataset due to the parsing of cf conventions. I reproduce the bug, and it happens in a particular situation when the units is an empty list (See Minimal Complete Verifiable Example)

What did you expect to happen?

To parse the units attribute as an empty string ?

Minimal Complete Verifiable Example

```Python temp = 15 + 8 * np.random.randn(2, 2, 3) precip = 10 * np.random.rand(2, 2, 3) lon = [[-99.83, -99.32], [-99.79, -99.23]] lat = [[42.25, 42.21], [42.63, 42.59]]

for real use cases, its good practice to supply array attributes such as

units, but we won't bother here for the sake of brevity

ds = xr.Dataset( { "temperature": (["x", "y", "time"], temp), "precipitation": (["x", "y", "time"], precip), }, coords={ "lon": (["x", "y"], lon), "lat": (["x", "y"], lat), "time": pd.date_range("2014-09-06", periods=3), "reference_time": pd.Timestamp("2014-09-05"), }, ) ds.temperature.attrs["units"] = []

ds.to_netcdf("test.nc")

ds = xr.open_dataset("test.nc") ds.close() ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

```Python

TypeError Traceback (most recent call last) Input In [3], in <cell line: 1>() ----> 1 ds = xr.open_dataset("test.nc") 2 print(ds["temperature"].attrs) 3 ds.close()

File ~/.local/src/miniconda/envs/uptodatexarray/lib/python3.10/site-packages/xarray/backends/api.py:495, in open_dataset(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, backend_kwargs, args, kwargs) 483 decoders = _resolve_decoders_kwargs( 484 decode_cf, 485 open_backend_dataset_parameters=backend.open_dataset_parameters, (...) 491 decode_coords=decode_coords, 492 ) 494 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None) --> 495 backend_ds = backend.open_dataset( 496 filename_or_obj, 497 drop_variables=drop_variables, 498 decoders, 499 kwargs, 500 ) 501 ds = _dataset_from_backend_dataset( 502 backend_ds, 503 filename_or_obj, (...) 510 *kwargs, 511 ) 512 return ds

File ~/.local/src/miniconda/envs/uptodatexarray/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:564, in NetCDF4BackendEntrypoint.open_dataset(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, lock, autoclose) 562 store_entrypoint = StoreBackendEntrypoint() 563 with close_on_error(store): --> 564 ds = store_entrypoint.open_dataset( 565 store, 566 mask_and_scale=mask_and_scale, 567 decode_times=decode_times, 568 concat_characters=concat_characters, 569 decode_coords=decode_coords, 570 drop_variables=drop_variables, 571 use_cftime=use_cftime, 572 decode_timedelta=decode_timedelta, 573 ) 574 return ds

File ~/.local/src/miniconda/envs/uptodatexarray/lib/python3.10/site-packages/xarray/backends/store.py:27, in StoreBackendEntrypoint.open_dataset(self, store, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta) 24 vars, attrs = store.load() 25 encoding = store.get_encoding() ---> 27 vars, attrs, coord_names = conventions.decode_cf_variables( 28 vars, 29 attrs, 30 mask_and_scale=mask_and_scale, 31 decode_times=decode_times, 32 concat_characters=concat_characters, 33 decode_coords=decode_coords, 34 drop_variables=drop_variables, 35 use_cftime=use_cftime, 36 decode_timedelta=decode_timedelta, 37 ) 39 ds = Dataset(vars, attrs=attrs) 40 ds = ds.set_coords(coord_names.intersection(vars))

File ~/.local/src/miniconda/envs/uptodatexarray/lib/python3.10/site-packages/xarray/conventions.py:503, in decode_cf_variables(variables, attributes, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables, use_cftime, decode_timedelta) 499 continue 500 stack_char_dim = ( 501 concat_characters and v.dtype == "S1" and v.ndim > 0 and stackable(v.dims[-1]) 502 ) --> 503 new_vars[k] = decode_cf_variable( 504 k, 505 v, 506 concat_characters=concat_characters, 507 mask_and_scale=mask_and_scale, 508 decode_times=decode_times, 509 stack_char_dim=stack_char_dim, 510 use_cftime=use_cftime, 511 decode_timedelta=decode_timedelta, 512 ) 513 if decode_coords in [True, "coordinates", "all"]: 514 var_attrs = new_vars[k].attrs

File ~/.local/src/miniconda/envs/uptodatexarray/lib/python3.10/site-packages/xarray/conventions.py:354, in decode_cf_variable(name, var, concat_characters, mask_and_scale, decode_times, decode_endianness, stack_char_dim, use_cftime, decode_timedelta) 351 var = coder.decode(var, name=name) 353 if decode_timedelta: --> 354 var = times.CFTimedeltaCoder().decode(var, name=name) 355 if decode_times: 356 var = times.CFDatetimeCoder(use_cftime=use_cftime).decode(var, name=name)

File ~/.local/src/miniconda/envs/uptodatexarray/lib/python3.10/site-packages/xarray/coding/times.py:537, in CFTimedeltaCoder.decode(self, variable, name) 534 def decode(self, variable, name=None): 535 dims, data, attrs, encoding = unpack_for_decoding(variable) --> 537 if "units" in attrs and attrs["units"] in TIME_UNITS: 538 units = pop_to(attrs, encoding, "units") 539 transform = partial(decode_cf_timedelta, units=units)

TypeError: unhashable type: 'numpy.ndarray' ```

Anything else we need to know?

The following assignation produces the bug :

python ds.temperature.attrs["units"] = []

But these ones does not produce the bug : python ds.temperature.attrs["units"] = "[]" ds.temperature.attrs["units"] = ""

Also, i don't know how the units attributes get encoded for writing but i see no difference between ds.temperature.attrs["units"] = "" and ds.temperature.attrs["units"] = [] when using ncdump on the file

Environment

This bug was encountered with versions below this one.

When using xr.open_mfdataset() with two exact same files by mistake, it causes an unclear error message

What happened:

With of course the time dimension existing :

python ds=xr.open_mfdataset(["some_file.nc","some_file.nc"],concat_dim="time",engine="netcdf4")

```python

ValueError Traceback (most recent call last)

~/.local/src/miniconda/envs/minireobs/lib/python3.8/site-packages/xarray/backends/api.py in open_mfdataset(paths, chunks, concat_dim, compat, preprocess, engine, lock, data_vars, coords, combine, parallel, join, attrs_file, **kwargs) 966 # Redo ordering from coordinates, ignoring how they were ordered 967 # previously --> 968 combined = combine_by_coords( 969 datasets, 970 compat=compat,

~/.local/src/miniconda/envs/minireobs/lib/python3.8/site-packages/xarray/core/combine.py in combine_by_coords(datasets, compat, data_vars, coords, fill_value, join, combine_attrs) 762 concatenated_grouped_by_data_vars = [] 763 for vars, datasets_with_same_vars in grouped_by_vars: --> 764 combined_ids, concat_dims = _infer_concat_order_from_coords( 765 list(datasets_with_same_vars) 766 )

~/.local/src/miniconda/envs/minireobs/lib/python3.8/site-packages/xarray/core/combine.py in _infer_concat_order_from_coords(datasets) 106 107 if len(datasets) > 1 and not concat_dims: --> 108 raise ValueError( 109 "Could not find any dimension coordinates to use to " 110 "order the datasets for concatenation"

ValueError: Could not find any dimension coordinates to use to order the datasets for concatenation ``` What you expected to happen: A warning saying that we are using the same dataset ? A more explicit error message (exact same dimensions) ? No error and no concatenation, remove duplicated datasets?

Environment: