Revert .oindex and .vindex additions in _ElementwiseFunctionArray, NativeEndiannessArray, and BoolTypeArray classes

xarray/coding/strings.py

@@ -249,15 +249,20 @@ def shape(self) -> tuple[int, ...]:
     def __repr__(self):
         return f"{type(self).__name__}({self.array!r})"
 
-    def _vindex_get(self, key):
-        return _numpy_char_to_bytes(self.array.vindex[key])
-
-    def _oindex_get(self, key):
-        return _numpy_char_to_bytes(self.array.oindex[key])
+    def _check_and_raise_if_non_basic_indexer(self, indexer) -> None:
+        ...
+        # TODO: this is a temporary fix until BackendArray supports vindex and oindex
 
     def __getitem__(self, key):
         # require slicing the last dimension completely
         key = type(key)(indexing.expanded_indexer(key.tuple, self.array.ndim))
         if key.tuple[-1] != slice(None):
             raise IndexError("too many indices")
-        return _numpy_char_to_bytes(self.array[key])
+        # TODO: this is a temporary fix until BackendArray supports vindex and oindex
+        if isinstance(key, indexing.OuterIndexer):
+            data = self.array.oindex[key]
+        elif isinstance(key, indexing.VectorizedIndexer):
+            data = self.array.vindex[key]
+        else:
+            data = self.array[key]
+        return _numpy_char_to_bytes(data)

xarray/coding/variables.py

@@ -68,14 +68,19 @@ def __init__(self, array, func: Callable, dtype: np.typing.DTypeLike):
     def dtype(self) -> np.dtype:
         return np.dtype(self._dtype)
 
-    def _oindex_get(self, key):
-        return type(self)(self.array.oindex[key], self.func, self.dtype)
-
-    def _vindex_get(self, key):
-        return type(self)(self.array.vindex[key], self.func, self.dtype)
+    def _check_and_raise_if_non_basic_indexer(self, indexer) -> None:
+        ...
+        # TODO: this is a temporary fix until BackendArray supports vindex and oindex
 
     def __getitem__(self, key):
-        return type(self)(self.array[key], self.func, self.dtype)
+        # TODO: this is a temporary fix until BackendArray supports vindex and oindex
+        if isinstance(key, indexing.OuterIndexer):
+            data = self.array.oindex[key]
+        elif isinstance(key, indexing.VectorizedIndexer):
+            data = self.array.vindex[key]
+        else:
+            data = self.array[key]
+        return type(self)(data, self.func, self.dtype)
 
     def get_duck_array(self):
         return self.func(self.array.get_duck_array())
@@ -113,14 +118,19 @@ def __init__(self, array) -> None:
     def dtype(self) -> np.dtype:
         return np.dtype(self.array.dtype.kind + str(self.array.dtype.itemsize))
 
-    def _oindex_get(self, key):
-        return np.asarray(self.array.oindex[key], dtype=self.dtype)
-
-    def _vindex_get(self, key):
-        return np.asarray(self.array.vindex[key], dtype=self.dtype)
+    def _check_and_raise_if_non_basic_indexer(self, indexer) -> None:
+        ...
+        # TODO: this is a temporary fix until BackendArray supports vindex and oindex
 
     def __getitem__(self, key) -> np.ndarray:
-        return np.asarray(self.array[key], dtype=self.dtype)
+        # TODO: this is a temporary fix until BackendArray supports vindex and oindex
+        if isinstance(key, indexing.OuterIndexer):
+            data = self.array.oindex[key]
+        elif isinstance(key, indexing.VectorizedIndexer):
+            data = self.array.vindex[key]
+        else:
+            data = self.array[key]
+        return np.asarray(data, dtype=self.dtype)
 
 
 class BoolTypeArray(indexing.ExplicitlyIndexedNDArrayMixin):
@@ -151,14 +161,19 @@ def __init__(self, array) -> None:
     def dtype(self) -> np.dtype:
         return np.dtype("bool")
 
-    def _oindex_get(self, key):
-        return np.asarray(self.array.oindex[key], dtype=self.dtype)
-
-    def _vindex_get(self, key):
-        return np.asarray(self.array.vindex[key], dtype=self.dtype)
+    def _check_and_raise_if_non_basic_indexer(self, indexer) -> None:
+        ...
+        # TODO: this is a temporary fix until BackendArray supports vindex and oindex
 
     def __getitem__(self, key) -> np.ndarray:
-        return np.asarray(self.array[key], dtype=self.dtype)
+        # TODO: this is a temporary fix until BackendArray supports vindex and oindex
+        if isinstance(key, indexing.OuterIndexer):
+            data = self.array.oindex[key]
+        elif isinstance(key, indexing.VectorizedIndexer):
+            data = self.array.vindex[key]
+        else:
+            data = self.array[key]
+        return np.asarray(data, dtype=self.dtype)
 
 
 def lazy_elemwise_func(array, func: Callable, dtype: np.typing.DTypeLike):

xarray/core/indexing.py

@@ -639,7 +639,18 @@ def shape(self) -> _Shape:
         return tuple(shape)
 
     def get_duck_array(self):
-        if isinstance(self.array, ExplicitlyIndexedNDArrayMixin):
+        from xarray.coding import strings, variables
+
+        if isinstance(self.array, ExplicitlyIndexedNDArrayMixin) and not isinstance(
+            self.array,
+            (
+                strings.StackedBytesArray,
+                variables._ElementwiseFunctionArray,
+                variables.BoolTypeArray,
+                variables.NativeEndiannessArray,
+            ),
+        ):
+            # TODO: Remove the isinstance check for variables.BoolTypeArray and variables.NativeEndiannessArray once the BackendArrray is updated with oindex and vindex properties
             array = apply_indexer(self.array, self.key)
         else:
             # If the array is not an ExplicitlyIndexedNDArrayMixin,
@@ -715,7 +726,18 @@ def shape(self) -> _Shape:
         return np.broadcast(*self.key.tuple).shape
 
     def get_duck_array(self):
-        if isinstance(self.array, ExplicitlyIndexedNDArrayMixin):
+        from xarray.coding import strings, variables
+
+        if isinstance(self.array, ExplicitlyIndexedNDArrayMixin) and not isinstance(
+            self.array,
+            (
+                strings.StackedBytesArray,
+                variables._ElementwiseFunctionArray,
+                variables.BoolTypeArray,
+                variables.NativeEndiannessArray,
+            ),
+        ):
+            # TODO: Remove the isinstance check for variables.BoolTypeArray and variables.NativeEndiannessArray once the BackendArrray is updated with oindex and vindex properties
             array = apply_indexer(self.array, self.key)
         else:
             # If the array is not an ExplicitlyIndexedNDArrayMixin,

xarray/tests/test_backends.py

@@ -3211,6 +3211,15 @@
             unpickled = pickle.loads(pickle.dumps(ds))
             assert_identical(unpickled, data)
 
+    def test_scipy_wrapper_array_oindex_vindex(self) -> None:
+        ds = xr.Dataset()
+        ds["A"] = xr.DataArray([[1, "a"], [2, "b"]], dims=["x", "y"])
+        with create_tmp_file(allow_cleanup_failure=False) as path:
+            ds.to_netcdf(path, engine="scipy")
+            with xr.open_dataset(path, engine="scipy") as ds2:
+                with create_tmp_file(allow_cleanup_failure=False) as path2:
+                    ds2.sel(y=[1]).to_netcdf(path2)
+
 
 @requires_scipy
 class TestScipyFileObject(CFEncodedBase, NetCDF3Only):

xarray/tests/test_coding_strings.py

@@ -181,7 +181,7 @@ def test_StackedBytesArray_vectorized_indexing() -> None:
 
     V = IndexerMaker(indexing.VectorizedIndexer)
     indexer = V[np.array([[0, 1], [1, 0]])]
-    actual = stacked.vindex[indexer]
+    actual = stacked[indexer]
     assert_array_equal(actual, expected)