Handle numpy-only attrs in xr.where (#7364)

* check if result has attrs before trying to add them

* add whats new

* Apply suggestions from code review

Co-authored-by: Mick <[email protected]>

Co-authored-by: Mick <[email protected]>

Author: slevang

doc/whats-new.rst

@@ -34,7 +34,8 @@ Deprecations
 
 Bug fixes
 ~~~~~~~~~
-
+- Allow numpy-only objects in :py:func:`where` when ``keep_attrs=True`` (:issue:`7362`, :pull:`7364`).
+  By `Sam Levang <https://github.com/slevang>`_.
 
 Documentation
 ~~~~~~~~~~~~~

xarray/core/computation.py

@@ -1876,7 +1876,7 @@ def where(cond, x, y, keep_attrs=None):
     # be consistent with the `where` method of `DataArray` and `Dataset`
     # rebuild the attrs from x at each level of the output, which could be
     # Dataset, DataArray, or Variable, and also handle coords
-    if keep_attrs is True:
+    if keep_attrs is True and hasattr(result, "attrs"):
         if isinstance(y, Dataset) and not isinstance(x, Dataset):
             # handle special case where x gets promoted to Dataset
             result.attrs = {}

xarray/tests/test_computation.py

@@ -1964,6 +1964,11 @@ def test_where_attrs() -> None:
     expected["a"].attrs = {"attr": "x_coord"}
     assert_identical(expected, actual)
 
+    # no xarray objects, handle no attrs
+    actual_np = xr.where(True, 0, 1, keep_attrs=True)
+    expected_np = np.array(0)
+    assert_identical(expected_np, actual_np)
+
     # DataArray and 2 Datasets, takes attrs from x
     ds_x = xr.Dataset(data_vars={"x": x}, attrs={"attr": "x_ds"})
     ds_y = xr.Dataset(data_vars={"x": y}, attrs={"attr": "y_ds"})