Fix for scalar detection (#8821)

Co-authored-by: Justus Magin <keewis@users.noreply.github.com>
Co-authored-by: Trevor James Smith <10819524+Zeitsperre@users.noreply.github.com>
Co-authored-by: Pascal Bourgault <bourgault.pascal@ouranos.ca>

Author: 4 people

xarray/core/indexing.py

@@ -769,7 +769,14 @@ def __repr__(self) -> str:
 
 def _wrap_numpy_scalars(array):
     """Wrap NumPy scalars in 0d arrays."""
-    if np.isscalar(array):
+    if np.ndim(array) == 0 and (
+        isinstance(array, np.generic)
+        or not (is_duck_array(array) or isinstance(array, NDArrayMixin))
+    ):
+        return np.array(array)
+    elif hasattr(array, "dtype"):
+        return array
+    elif np.ndim(array) == 0:
         return np.array(array)
     else:
         return array

xarray/tests/test_backends.py

@@ -2276,6 +2276,36 @@ def test_write_inconsistent_chunks(self) -> None:
     def test_roundtrip_coordinates(self) -> None:
         super().test_roundtrip_coordinates()
 
+    @requires_cftime
+    def test_roundtrip_cftime_bnds(self):
+        # Regression test for issue #7794
+        import cftime
+
+        original = xr.Dataset(
+            {
+                "foo": ("time", [0.0]),
+                "time_bnds": (
+                    ("time", "bnds"),
+                    [
+                        [
+                            cftime.Datetime360Day(2005, 12, 1, 0, 0, 0, 0),
+                            cftime.Datetime360Day(2005, 12, 2, 0, 0, 0, 0),
+                        ]
+                    ],
+                ),
+            },
+            {"time": [cftime.Datetime360Day(2005, 12, 1, 12, 0, 0, 0)]},
+        )
+
+        with create_tmp_file() as tmp_file:
+            original.to_netcdf(tmp_file)
+            with open_dataset(tmp_file) as actual:
+                # Operation to load actual time_bnds into memory
+                assert_array_equal(actual.time_bnds.values, original.time_bnds.values)
+                chunked = actual.chunk(time=1)
+                with create_tmp_file() as tmp_file_chunked:
+                    chunked.to_netcdf(tmp_file_chunked)
+
 
 @requires_zarr
 @pytest.mark.usefixtures("default_zarr_format")