On Windows, enable successful test of opening a dataset containing a …

…cftime index (#6305)

* Exit cluster context before deleting temporary directory

Previously, on Windows, the scheduler in the outer context prevented deleting
the temporary directory upon exiting the inner context of the latter.  That
caused the test to fail and the temporary directory and file to remain.

* Use fixture instead of context manager for temporary directory

* Edit whats-new entry

doc/whats-new.rst

@@ -52,7 +52,7 @@ Bug fixes
 
 - Variables which are chunked using dask in larger (but aligned) chunks than the target zarr chunk size
   can now be stored using `to_zarr()` (:pull:`6258`) By `Tobias Kölling <https://github.com/d70-t>`_.
-- Multi-file datasets containing encoded :py:class:`cftime.datetime` objects can be read in parallel again (:issue:`6226`, :pull:`6249`).  By `Martin Bergemann <https://github.com/antarcticrainforest>`_.
+- Multi-file datasets containing encoded :py:class:`cftime.datetime` objects can be read in parallel again (:issue:`6226`, :pull:`6249`, :pull:`6305`).  By `Martin Bergemann <https://github.com/antarcticrainforest>`_ and `Stan West <https://github.com/stanwest>`_.
 
 Documentation
 ~~~~~~~~~~~~~

xarray/tests/test_distributed.py

@@ -1,8 +1,6 @@
 """ isort:skip_file """
-import os
 import pickle
 import numpy as np
-import tempfile
 
 import pytest
 from packaging.version import Version
@@ -113,19 +111,18 @@ def test_dask_distributed_netcdf_roundtrip(
 
 @requires_cftime
 @requires_netCDF4
-def test_open_mfdataset_can_open_files_with_cftime_index():
+def test_open_mfdataset_can_open_files_with_cftime_index(tmp_path):
     T = xr.cftime_range("20010101", "20010501", calendar="360_day")
     Lon = np.arange(100)
     data = np.random.random((T.size, Lon.size))
     da = xr.DataArray(data, coords={"time": T, "Lon": Lon}, name="test")
+    file_path = tmp_path / "test.nc"
+    da.to_netcdf(file_path)
     with cluster() as (s, [a, b]):
         with Client(s["address"]):
-            with tempfile.TemporaryDirectory() as td:
-                data_file = os.path.join(td, "test.nc")
-                da.to_netcdf(data_file)
-                for parallel in (False, True):
-                    with xr.open_mfdataset(data_file, parallel=parallel) as tf:
-                        assert_identical(tf["test"], da)
+            for parallel in (False, True):
+                with xr.open_mfdataset(file_path, parallel=parallel) as tf:
+                    assert_identical(tf["test"], da)
 
 
 @pytest.mark.parametrize("engine,nc_format", ENGINES_AND_FORMATS)