Fix table model instance_key can be categorical

src/spatialdata/models/models.py

@@ -1045,13 +1045,14 @@ def _validate_table_annotation_metadata(cls, data: AnnData) -> None:
                 np.int64,
                 np.uint64,
                 "O",
+                "category",
             ]
             and not pd.api.types.is_string_dtype(data.obs[attr[cls.INSTANCE_KEY]])
             or (dtype == "O" and (val_dtype := type(data.obs[attr[cls.INSTANCE_KEY]].iloc[0])) is not str)
         ):
             dtype = dtype if dtype != "O" else val_dtype
             raise TypeError(
-                f"Only int, np.int16, np.int32, np.int64, uint equivalents or string allowed as dtype for "
+                f"Only int, np.int16, np.int32, np.int64, uint equivalents, categorical or string allowed as dtype for "
                 f"instance_key column in obs. Dtype found to be {dtype}"
             )
         expected_regions = attr[cls.REGION_KEY] if isinstance(attr[cls.REGION_KEY], list) else [attr[cls.REGION_KEY]]

tests/models/test_models.py

@@ -417,6 +417,14 @@ def test_table_model(
         adata = AnnData(RNG.normal(size=(10, 2)), obs=obs)
         table = model.parse(adata, region=region, region_key=region_key, instance_key="A")
         assert region_key in table.obs
+
+        # categorical instance_key should be accepted
+        obs_cat = obs.copy()
+        obs_cat["A"] = pd.Categorical(obs_cat["A"])
+        adata_cat = AnnData(RNG.normal(size=(10, 2)), obs=obs_cat)
+        table_cat = model.parse(adata_cat, region=region, region_key=region_key, instance_key="A")
+        assert isinstance(table_cat.obs["A"].dtype, pd.CategoricalDtype)
+
         assert isinstance(table.obs[region_key].dtype, pd.CategoricalDtype)
         assert table.obs[region_key].cat.categories.tolist() == np.unique(region).tolist()
         assert table.uns[TableModel.ATTRS_KEY][TableModel.REGION_KEY_KEY] == region_key