Support CuPy-backed arrays in DaskManager

xarray/compat/array_api_compat.py

@@ -1,3 +1,5 @@
+from types import ModuleType
+
 import numpy as np
 
 from xarray.namedarray.pycompat import array_type
@@ -46,7 +48,7 @@ def result_type(*arrays_and_dtypes, xp) -> np.dtype:
         return _future_array_api_result_type(*arrays_and_dtypes, xp=xp)
 
 
-def get_array_namespace(*values):
+def get_array_namespace(*values) -> ModuleType:
     def _get_single_namespace(x):
         if hasattr(x, "__array_namespace__"):
             return x.__array_namespace__()

xarray/core/indexing.py

@@ -9,13 +9,15 @@
 from contextlib import suppress
 from dataclasses import dataclass, field
 from datetime import timedelta
+from types import ModuleType
 from typing import TYPE_CHECKING, Any, cast, overload
 
 import numpy as np
 import pandas as pd
 from numpy.typing import DTypeLike
 from packaging.version import Version
 
+from xarray.compat.array_api_compat import get_array_namespace
 from xarray.compat.npcompat import HAS_STRING_DTYPE
 from xarray.core import duck_array_ops
 from xarray.core.coordinate_transform import CoordinateTransform
@@ -693,7 +695,10 @@ def __array__(
         else:
             return np.asarray(to_numpy(self.get_duck_array()), dtype=dtype)
 
-    def get_duck_array(self):
+    def __array_namespace__(self: Any) -> ModuleType:
+        return get_array_namespace(self.array)
+
+    def get_duck_array(self) -> duckarray:
         return self.array.get_duck_array()
 
     def __getitem__(self, key: Any):

xarray/namedarray/core.py

@@ -843,7 +843,7 @@ def chunk(
                 # Using OuterIndexer is a pragmatic choice: dask does not yet handle
                 # different indexing types in an explicit way:
                 # https://github.com/dask/dask/issues/2883
-                ndata = ImplicitToExplicitIndexingAdapter(data_old, OuterIndexer)  # type: ignore[assignment]
+                ndata = ImplicitToExplicitIndexingAdapter(data_old, OuterIndexer)
 
             if is_dict_like(chunks):
                 chunks = tuple(starmap(chunks.get, enumerate(ndata.shape)))

xarray/namedarray/daskmanager.py

@@ -68,8 +68,9 @@ def from_array(
         import dask.array as da
 
         if isinstance(data, ImplicitToExplicitIndexingAdapter):
-            # lazily loaded backend array classes should use NumPy array operations.
-            kwargs["meta"] = np.ndarray
+            # lazily loaded backend array classes should use NumPy or CuPy array operations.
+            xp = data.__array_namespace__()
+            kwargs["meta"] = xp.ndarray
 
         return da.from_array(
             data,

xarray/namedarray/pycompat.py

@@ -140,7 +140,7 @@ def to_duck_array(data: Any, **kwargs: dict[str, Any]) -> duckarray[_ShapeType,
         return loaded_data
 
     if isinstance(data, ExplicitlyIndexed | ImplicitToExplicitIndexingAdapter):
-        return data.get_duck_array()  # type: ignore[no-untyped-call, no-any-return]
+        return data.get_duck_array()
     elif is_duck_array(data):
         return data
     else: