fix tests

Author: dcherian

xarray/core/variable.py

@@ -163,7 +163,7 @@ def as_variable(obj, name=None) -> Variable | IndexVariable:
         if obj.ndim != 1:
             warnings.warn(
                 f"{name!r} has more than 1-dimension and the same name as one of its "
-                f"dimensions {obj.dims!r}. Xarray will not automatically"
+                f"dimensions {obj.dims!r}. Xarray will not automatically "
                 "create an Index object that would allow label-based selection.",
                 RuntimeWarning,
             )

xarray/tests/test_dataset.py

@@ -467,13 +467,15 @@ def test_constructor(self) -> None:
 
         with pytest.raises(ValueError, match=r"conflicting sizes"):
             Dataset({"a": x1, "b": x2})
-        with pytest.raises(ValueError, match=r"disallows such variables"):
-            Dataset({"a": x1, "x": z})
         with pytest.raises(TypeError, match=r"tuple of form"):
             Dataset({"x": (1, 2, 3, 4, 5, 6, 7)})
         with pytest.raises(ValueError, match=r"already exists as a scalar"):
             Dataset({"x": 0, "y": ("x", [1, 2, 3])})
 
+        with pytest.warns(RuntimeWarning, match=r"will not automatically"):
+            actual = Dataset({"a": x1, "x": z})
+            assert "x" not in actual.xindexes
+
         # verify handling of DataArrays
         expected = Dataset({"x": x1, "z": z})
         actual = Dataset({"z": expected["z"]})

xarray/tests/test_variable.py

@@ -1247,8 +1247,9 @@ def test_as_variable(self):
         expected = Variable(("x", "y"), data)
         with pytest.raises(ValueError, match=r"without explicit dimension names"):
             as_variable(data, name="x")
-        with pytest.raises(ValueError, match=r"has more than 1-dimension"):
-            as_variable(expected, name="x")
+        with pytest.warns(RuntimeWarning, match=r"has more than 1-dimension"):
+            actual = as_variable(expected, name="x")
+            assert_identical(expected, actual)
 
         # test datetime, timedelta conversion
         dt = np.array([datetime(1999, 1, 1) + timedelta(days=x) for x in range(10)])