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.

In the xarray.core.dataset.pymodule, more particulary in the reindex method the tolerance argument is set to be a Number

https://github.com/pydata/xarray/blob/f08672847abec18f46df75e2f620646d27fa41a2/xarray/core/dataset.py#L2743

But the _reindex function call reindex_variable function. In the reindex_variable the type for tolerance is Any. This function ends to call get_indexer_nd which call the pandas function get_indexer :

https://github.com/pydata/xarray/blob/f08672847abec18f46df75e2f620646d27fa41a2/xarray/core/indexes.py#L137

In pandas the type of tolerance according to the docs can be a scalar or a list-like object

• [x] Tests added
• [x] Passes pre-commit run --all-files
• [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

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: