Fix to_netcdf(compute=False) with Dask distributed

doc/whats-new.rst

@@ -34,6 +34,9 @@ Bug fixes
 - Fix error when encoding an empty :py:class:`numpy.datetime64` array
   (:issue:`10722`, :pull:`10723`). By `Spencer Clark
   <https://github.com/spencerkclark>`_.
+- Fix error from ``to_netcdf(..., compute=False)`` when using Dask Distributed
+  (:issue:`10725`).
+  By `Stephan Hoyer <https://github.com/shoyer>`_.
 - Propagation coordinate attrs in :py:meth:`xarray.Dataset.map` (:issue:`9317`, :pull:`10602`).
   By `Justus Magin <https://github.com/keewis>`_.
 

xarray/backends/api.py

@@ -1858,6 +1858,20 @@ def open_mfdataset(
     return combined
 
 
+def _get_netcdf_autoclose(dataset: Dataset, engine: T_NetcdfEngine) -> bool:
+    """Should we close files after each write operations?"""
+    scheduler = get_dask_scheduler()
+    have_chunks = any(v.chunks is not None for v in dataset.variables.values())
+
+    autoclose = have_chunks and scheduler in ["distributed", "multiprocessing"]
+    if autoclose and engine == "scipy":
+        raise NotImplementedError(
+            f"Writing netCDF files with the {engine} backend "
+            f"is not currently supported with dask's {scheduler} scheduler"
+        )
+    return autoclose
+
+
 WRITEABLE_STORES: dict[T_NetcdfEngine, Callable] = {
     "netcdf4": backends.NetCDF4DataStore.open,
     "scipy": backends.ScipyDataStore,
@@ -2064,16 +2078,7 @@ def to_netcdf(
     # sanitize unlimited_dims
     unlimited_dims = _sanitize_unlimited_dims(dataset, unlimited_dims)
 
-    # handle scheduler specific logic
-    scheduler = get_dask_scheduler()
-    have_chunks = any(v.chunks is not None for v in dataset.variables.values())
-
-    autoclose = have_chunks and scheduler in ["distributed", "multiprocessing"]
-    if autoclose and engine == "scipy":
-        raise NotImplementedError(
-            f"Writing netCDF files with the {engine} backend "
-            f"is not currently supported with dask's {scheduler} scheduler"
-        )
+    autoclose = _get_netcdf_autoclose(dataset, engine)
 
     if path_or_file is None:
         if not compute:
@@ -2116,7 +2121,7 @@ def to_netcdf(
         writes = writer.sync(compute=compute)
 
     finally:
-        if not multifile:
+        if not multifile and not autoclose:  # type: ignore[redundant-expr,unused-ignore]
             if compute:
                 store.close()
             else:

xarray/tests/test_distributed.py

@@ -85,11 +85,13 @@ def tmp_netcdf_filename(tmpdir):
 
 
 @pytest.mark.parametrize("engine,nc_format", ENGINES_AND_FORMATS)
+@pytest.mark.parametrize("compute", [True, False])
 def test_dask_distributed_netcdf_roundtrip(
     loop,  # noqa: F811
     tmp_netcdf_filename,
     engine,
     nc_format,
+    compute,
 ):
     if engine not in ENGINES:
         pytest.skip("engine not available")
@@ -107,7 +109,11 @@ def test_dask_distributed_netcdf_roundtrip(
                     )
                 return
 
-            original.to_netcdf(tmp_netcdf_filename, engine=engine, format=nc_format)
+            result = original.to_netcdf(
+                tmp_netcdf_filename, engine=engine, format=nc_format, compute=compute
+            )
+            if not compute:
+                result.compute()
 
             with xr.open_dataset(
                 tmp_netcdf_filename, chunks=chunks, engine=engine