Fix h5netcdf saving scalars with filters or chunks (pydata#2591)

* Fix h5netcdf saving scalars with filters or chunks

* Revert adding scalar dataset to central test function

* Add fix description to what's new.

doc/whats-new.rst

@@ -45,6 +45,9 @@ Enhancements
 Bug fixes
 ~~~~~~~~~
 
+- Fix h5netcdf saving scalars with filters or chunks (:issue:`2563`).
+  By `Martin Raspaud <https://github.com/mraspaud>`_.
+
 .. _whats-new.0.11.0:
 
 v0.11.0 (7 November 2018)

xarray/backends/h5netcdf_.py

@@ -208,10 +208,12 @@ def prepare_variable(self, name, variable, check_encoding=False,
 
         encoding['chunks'] = encoding.pop('chunksizes', None)
 
-        for key in ['compression', 'compression_opts', 'shuffle',
-                    'chunks', 'fletcher32']:
-            if key in encoding:
-                kwargs[key] = encoding[key]
+        # Do not apply compression, filters or chunking to scalars.
+        if variable.shape:
+            for key in ['compression', 'compression_opts', 'shuffle',
+                        'chunks', 'fletcher32']:
+                if key in encoding:
+                    kwargs[key] = encoding[key]
         if name not in self.ds:
             nc4_var = self.ds.create_variable(
                 name, dtype=dtype, dimensions=variable.dims,

xarray/tests/test_backends.py

@@ -1840,6 +1840,8 @@ def test_compression_encoding_h5py(self):
             data['var2'].encoding.update(compr_in)
             data['var2'].encoding.update(compr_common)
             compr_out.update(compr_common)
+            data['scalar'] = ('scalar_dim', np.array([2.0]))
+            data['scalar'] = data['scalar'][0]
             with self.roundtrip(data) as actual:
                 for k, v in compr_out.items():
                     assert v == actual['var2'].encoding[k]