From fd6b339c3f51e83d5f9deb12e837f822cd51a2f7 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Mon, 18 Nov 2024 11:03:25 -0500
Subject: [PATCH 01/24] lots more duck array compat, plus tests

---
 xarray/core/array_api_compat.py          |  28 ++
 xarray/core/common.py                    |   5 +-
 xarray/core/computation.py               |   8 +-
 xarray/core/dataset.py                   |  12 +-
 xarray/core/duck_array_ops.py            | 122 +++++---
 xarray/core/nanops.py                    |   2 +-
 xarray/core/nputils.py                   |   6 +
 xarray/core/rolling.py                   |   3 +
 xarray/core/variable.py                  |  39 ++-
 xarray/tests/test_duck_array_wrapping.py | 371 +++++++++++++++++++++++
 xarray/tests/test_strategies.py          |  19 +-
 xarray/tests/test_variable.py            |  39 +--
 12 files changed, 563 insertions(+), 91 deletions(-)
 create mode 100644 xarray/tests/test_duck_array_wrapping.py

diff --git a/xarray/core/array_api_compat.py b/xarray/core/array_api_compat.py
index da072de5b69..28d671cc349 100644
--- a/xarray/core/array_api_compat.py
+++ b/xarray/core/array_api_compat.py
@@ -1,5 +1,7 @@
 import numpy as np
 
+from xarray.namedarray.pycompat import array_type
+
 
 def is_weak_scalar_type(t):
     return isinstance(t, bool | int | float | complex | str | bytes)
@@ -42,3 +44,29 @@ def result_type(*arrays_and_dtypes, xp) -> np.dtype:
         return xp.result_type(*arrays_and_dtypes)
     else:
         return _future_array_api_result_type(*arrays_and_dtypes, xp=xp)
+
+
+def get_array_namespace(*values):
+    def _get_single_namespace(x):
+        if hasattr(x, "__array_namespace__"):
+            return x.__array_namespace__()
+        elif isinstance(x, array_type("cupy")):
+            # special case cupy for now
+            import cupy as cp
+
+            return cp
+        else:
+            return np
+
+    namespaces = {_get_single_namespace(t) for t in values}
+    non_numpy = namespaces - {np}
+
+    if len(non_numpy) > 1:
+        names = [module.__name__ for module in non_numpy]
+        raise TypeError(f"Mixed array types {names} are not supported.")
+    elif non_numpy:
+        [xp] = non_numpy
+    else:
+        xp = np
+
+    return xp
diff --git a/xarray/core/common.py b/xarray/core/common.py
index 6f788f408d0..8aaa153c1a8 100644
--- a/xarray/core/common.py
+++ b/xarray/core/common.py
@@ -496,7 +496,7 @@ def clip(
             keep_attrs = _get_keep_attrs(default=True)
 
         return apply_ufunc(
-            np.clip, self, min, max, keep_attrs=keep_attrs, dask="allowed"
+            duck_array_ops.clip, self, min, max, keep_attrs=keep_attrs, dask="allowed"
         )
 
     def get_index(self, key: Hashable) -> pd.Index:
@@ -1760,7 +1760,8 @@ def _full_like_variable(
             **from_array_kwargs,
         )
     else:
-        data = np.full_like(other.data, fill_value, dtype=dtype)
+        xp = duck_array_ops.get_array_namespace(other.data)
+        data = xp.full_like(other.data, fill_value, dtype=dtype)
 
     return Variable(dims=other.dims, data=data, attrs=other.attrs)
 
diff --git a/xarray/core/computation.py b/xarray/core/computation.py
index b15ed7f3f34..0bfe21642f7 100644
--- a/xarray/core/computation.py
+++ b/xarray/core/computation.py
@@ -34,7 +34,7 @@
 from xarray.core.utils import is_dict_like, is_scalar, parse_dims_as_set, result_name
 from xarray.core.variable import Variable
 from xarray.namedarray.parallelcompat import get_chunked_array_type
-from xarray.namedarray.pycompat import is_chunked_array
+from xarray.namedarray.pycompat import is_chunked_array, to_numpy
 from xarray.util.deprecation_helpers import deprecate_dims
 
 if TYPE_CHECKING:
@@ -1702,7 +1702,7 @@ def cross(
             )
 
     c = apply_ufunc(
-        np.cross,
+        duck_array_ops.cross,
         a,
         b,
         input_core_dims=[[dim], [dim]],
@@ -2174,9 +2174,13 @@ def _calc_idxminmax(
         # we need to attach back the dim name
         res.name = dim
     else:
+        indx.data = to_numpy(indx.data)
         res = array[dim][(indx,)]
         # The dim is gone but we need to remove the corresponding coordinate.
         del res.coords[dim]
+        # Cast to array namespace
+        xp = duck_array_ops.get_array_namespace(array.data)
+        res.data = xp.asarray(res.data)
 
     if skipna or (skipna is None and array.dtype.kind in na_dtypes):
         # Put the NaN values back in after removing them
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index cc34a8cc04b..6e5a8e163b8 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -127,7 +127,7 @@
     calculate_dimensions,
 )
 from xarray.namedarray.parallelcompat import get_chunked_array_type, guess_chunkmanager
-from xarray.namedarray.pycompat import array_type, is_chunked_array
+from xarray.namedarray.pycompat import array_type, is_chunked_array, to_numpy
 from xarray.plot.accessor import DatasetPlotAccessor
 from xarray.util.deprecation_helpers import _deprecate_positional_args, deprecate_dims
 
@@ -6564,7 +6564,7 @@ def dropna(
             array = self._variables[k]
             if dim in array.dims:
                 dims = [d for d in array.dims if d != dim]
-                count += np.asarray(array.count(dims))
+                count += to_numpy(array.count(dims).data)
                 size += math.prod([self.sizes[d] for d in dims])
 
         if thresh is not None:
@@ -8678,16 +8678,20 @@ def _integrate_one(self, coord, datetime_unit=None, cumulative=False):
                     coord_names.add(k)
             else:
                 if k in self.data_vars and dim in v.dims:
+                    # cast coord data to duck array if needed
+                    coord_data = duck_array_ops.get_array_namespace(v.data).asarray(
+                        coord_var.data
+                    )
                     if _contains_datetime_like_objects(v):
                         v = datetime_to_numeric(v, datetime_unit=datetime_unit)
                     if cumulative:
                         integ = duck_array_ops.cumulative_trapezoid(
-                            v.data, coord_var.data, axis=v.get_axis_num(dim)
+                            v.data, coord_data, axis=v.get_axis_num(dim)
                         )
                         v_dims = v.dims
                     else:
                         integ = duck_array_ops.trapz(
-                            v.data, coord_var.data, axis=v.get_axis_num(dim)
+                            v.data, coord_data, axis=v.get_axis_num(dim)
                         )
                         v_dims = list(v.dims)
                         v_dims.remove(dim)
diff --git a/xarray/core/duck_array_ops.py b/xarray/core/duck_array_ops.py
index 77e62e4c71e..d67f8d17207 100644
--- a/xarray/core/duck_array_ops.py
+++ b/xarray/core/duck_array_ops.py
@@ -18,23 +18,17 @@
 import pandas as pd
 from numpy import all as array_all  # noqa: F401
 from numpy import any as array_any  # noqa: F401
-from numpy import concatenate as _concatenate
 from numpy import (  # noqa: F401
-    full_like,
-    gradient,
     isclose,
-    isin,
     isnat,
     take,
-    tensordot,
-    transpose,
     unravel_index,
 )
-from numpy.lib.stride_tricks import sliding_window_view  # noqa: F401
 from packaging.version import Version
 from pandas.api.types import is_extension_array_dtype
 
 from xarray.core import dask_array_ops, dtypes, nputils
+from xarray.core.array_api_compat import get_array_namespace
 from xarray.core.options import OPTIONS
 from xarray.core.utils import is_duck_array, is_duck_dask_array, module_available
 from xarray.namedarray import pycompat
@@ -55,28 +49,6 @@
 dask_available = module_available("dask")
 
 
-def get_array_namespace(*values):
-    def _get_array_namespace(x):
-        if hasattr(x, "__array_namespace__"):
-            return x.__array_namespace__()
-        else:
-            return np
-
-    namespaces = {_get_array_namespace(t) for t in values}
-    non_numpy = namespaces - {np}
-
-    if len(non_numpy) > 1:
-        raise TypeError(
-            "cannot deal with more than one type supporting the array API at the same time"
-        )
-    elif non_numpy:
-        [xp] = non_numpy
-    else:
-        xp = np
-
-    return xp
-
-
 def einsum(*args, **kwargs):
     from xarray.core.options import OPTIONS
 
@@ -85,7 +57,23 @@ def einsum(*args, **kwargs):
 
         return opt_einsum.contract(*args, **kwargs)
     else:
-        return np.einsum(*args, **kwargs)
+        xp = get_array_namespace(*args)
+        return xp.einsum(*args, **kwargs)
+
+
+def tensordot(*args, **kwargs):
+    xp = get_array_namespace(*args)
+    return xp.tensordot(*args, **kwargs)
+
+
+def cross(*args, **kwargs):
+    xp = get_array_namespace(*args)
+    return xp.cross(*args, **kwargs)
+
+
+def gradient(f, *varargs, axis=None, edge_order=1):
+    xp = get_array_namespace(f)
+    return xp.gradient(f, *varargs, axis=axis, edge_order=edge_order)
 
 
 def _dask_or_eager_func(
@@ -153,7 +141,7 @@ def isnull(data):
         )
     ):
         # these types cannot represent missing values
-        return full_like(data, dtype=bool, fill_value=False)
+        return full_like(data, dtype=xp.bool, fill_value=False)
     else:
         # at this point, array should have dtype=object
         if isinstance(data, np.ndarray) or is_extension_array_dtype(data):
@@ -200,11 +188,23 @@ def cumulative_trapezoid(y, x, axis):
 
     # Pad so that 'axis' has same length in result as it did in y
     pads = [(1, 0) if i == axis else (0, 0) for i in range(y.ndim)]
-    integrand = np.pad(integrand, pads, mode="constant", constant_values=0.0)
+
+    xp = get_array_namespace(y, x)
+    integrand = xp.pad(integrand, pads, mode="constant", constant_values=0.0)
 
     return cumsum(integrand, axis=axis, skipna=False)
 
 
+def full_like(a, fill_value, **kwargs):
+    xp = get_array_namespace(a)
+    return xp.full_like(a, fill_value, **kwargs)
+
+
+def empty_like(a, **kwargs):
+    xp = get_array_namespace(a)
+    return xp.empty_like(a, **kwargs)
+
+
 def astype(data, dtype, **kwargs):
     if hasattr(data, "__array_namespace__"):
         xp = get_array_namespace(data)
@@ -335,7 +335,8 @@ def array_notnull_equiv(arr1, arr2):
 
 def count(data, axis=None):
     """Count the number of non-NA in this array along the given axis or axes"""
-    return np.sum(np.logical_not(isnull(data)), axis=axis)
+    xp = get_array_namespace(data)
+    return xp.sum(xp.logical_not(isnull(data)), axis=axis)
 
 
 def sum_where(data, axis=None, dtype=None, where=None):
@@ -350,7 +351,7 @@ def sum_where(data, axis=None, dtype=None, where=None):
 
 def where(condition, x, y):
     """Three argument where() with better dtype promotion rules."""
-    xp = get_array_namespace(condition)
+    xp = get_array_namespace(condition, x, y)
     return xp.where(condition, *as_shared_dtype([x, y], xp=xp))
 
 
@@ -367,15 +368,25 @@ def fillna(data, other):
     return where(notnull(data), data, other)
 
 
+def logical_not(data):
+    xp = get_array_namespace(data)
+    return xp.logical_not(data)
+
+
+def clip(data, min=None, max=None):
+    xp = get_array_namespace(data)
+    return xp.clip(data, min, max)
+
+
 def concatenate(arrays, axis=0):
     """concatenate() with better dtype promotion rules."""
-    # TODO: remove the additional check once `numpy` adds `concat` to its array namespace
-    if hasattr(arrays[0], "__array_namespace__") and not isinstance(
-        arrays[0], np.ndarray
-    ):
-        xp = get_array_namespace(arrays[0])
+    # TODO: `concat` is the xp compliant name, but fallback to concatenate for
+    # older numpy and for cupy
+    xp = get_array_namespace(*arrays)
+    if hasattr(xp, "concat"):
         return xp.concat(as_shared_dtype(arrays, xp=xp), axis=axis)
-    return _concatenate(as_shared_dtype(arrays), axis=axis)
+    else:
+        return xp.concatenate(as_shared_dtype(arrays, xp=xp), axis=axis)
 
 
 def stack(arrays, axis=0):
@@ -393,6 +404,32 @@ def ravel(array):
     return reshape(array, (-1,))
 
 
+def transpose(array, axes=None):
+    xp = get_array_namespace(array)
+    return xp.transpose(array, axes)
+
+
+def moveaxis(array, source, destination):
+    xp = get_array_namespace(array)
+    return xp.moveaxis(array, source, destination)
+
+
+def pad(array, pad_width, **kwargs):
+    xp = get_array_namespace(array)
+    return xp.pad(array, pad_width, **kwargs)
+
+
+def sliding_window_view(array, window_shape, axis=None):
+    # TODO: some array libraries don't support this, implement an alternative?
+    xp = get_array_namespace(array)
+    return xp.lib.stride_tricks.sliding_window_view(array, window_shape, axis=axis)
+
+
+def quantile(array, q, axis=None, **kwargs):
+    xp = get_array_namespace(array)
+    return xp.quantile(array, q, axis=axis, **kwargs)
+
+
 @contextlib.contextmanager
 def _ignore_warnings_if(condition):
     if condition:
@@ -734,6 +771,11 @@ def last(values, axis, skipna=None):
     return take(values, -1, axis=axis)
 
 
+def isin(element, test_elements, **kwargs):
+    xp = get_array_namespace(element, test_elements)
+    return xp.isin(element, test_elements, **kwargs)
+
+
 def least_squares(lhs, rhs, rcond=None, skipna=False):
     """Return the coefficients and residuals of a least-squares fit."""
     if is_duck_dask_array(rhs):
diff --git a/xarray/core/nanops.py b/xarray/core/nanops.py
index 7fbb63068c0..4894cf02be2 100644
--- a/xarray/core/nanops.py
+++ b/xarray/core/nanops.py
@@ -128,7 +128,7 @@ def nanmean(a, axis=None, dtype=None, out=None):
             "ignore", r"Mean of empty slice", category=RuntimeWarning
         )
 
-        return np.nanmean(a, axis=axis, dtype=dtype)
+        return nputils.nanmean(a, axis=axis, dtype=dtype)
 
 
 def nanmedian(a, axis=None, out=None):
diff --git a/xarray/core/nputils.py b/xarray/core/nputils.py
index cd20dbccd87..24d6b1dda72 100644
--- a/xarray/core/nputils.py
+++ b/xarray/core/nputils.py
@@ -7,6 +7,7 @@
 import pandas as pd
 from packaging.version import Version
 
+from xarray.core.array_api_compat import get_array_namespace
 from xarray.core.utils import is_duck_array, module_available
 from xarray.namedarray import pycompat
 
@@ -179,6 +180,11 @@ def f(values, axis=None, **kwargs):
         dtype = kwargs.get("dtype")
         bn_func = getattr(bn, name, None)
 
+        xp = get_array_namespace(values)
+        if xp is not np:
+            func = getattr(xp, name, None)
+            if func is not None:
+                return func(values, axis=axis, **kwargs)
         if (
             module_available("numbagg")
             and pycompat.mod_version("numbagg") >= Version("0.5.0")
diff --git a/xarray/core/rolling.py b/xarray/core/rolling.py
index 781550207ff..dfeab5e409e 100644
--- a/xarray/core/rolling.py
+++ b/xarray/core/rolling.py
@@ -639,6 +639,7 @@ def _array_reduce(
             )
             del kwargs["dim"]
 
+        xp = duck_array_ops.get_array_namespace(self.obj.data)
         if (
             OPTIONS["use_numbagg"]
             and module_available("numbagg")
@@ -654,6 +655,7 @@ def _array_reduce(
             # TODO: we could also allow this, probably as part of a refactoring of this
             # module, so we can use the machinery in `self.reduce`.
             and self.ndim == 1
+            and xp is np
         ):
             import numbagg
 
@@ -676,6 +678,7 @@ def _array_reduce(
                 or module_available("dask", "2024.11.0")
             )
             and self.ndim == 1
+            and xp is np
         ):
             return self._bottleneck_reduce(
                 bottleneck_move_func, keep_attrs=keep_attrs, **kwargs
diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index a6ea44b1ee5..f4db3fa6b1d 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -822,7 +822,7 @@ def __getitem__(self, key) -> Self:
         data = indexing.apply_indexer(indexable, indexer)
 
         if new_order:
-            data = np.moveaxis(data, range(len(new_order)), new_order)
+            data = duck_array_ops.moveaxis(data, range(len(new_order)), new_order)
         return self._finalize_indexing_result(dims, data)
 
     def _finalize_indexing_result(self, dims, data) -> Self:
@@ -860,12 +860,17 @@ def _getitem_with_mask(self, key, fill_value=dtypes.NA):
             # we need to invert the mask in order to pass data first. This helps
             # pint to choose the correct unit
             # TODO: revert after https://github.com/hgrecco/pint/issues/1019 is fixed
-            data = duck_array_ops.where(np.logical_not(mask), data, fill_value)
+            # cast mask to any duck array type
+            if not is_duck_dask_array(mask):
+                mask = duck_array_ops.get_array_namespace(data).asarray(mask)
+            data = duck_array_ops.where(
+                duck_array_ops.logical_not(mask), data, fill_value
+            )
         else:
             # array cannot be indexed along dimensions of size 0, so just
             # build the mask directly instead.
             mask = indexing.create_mask(indexer, self.shape)
-            data = np.broadcast_to(fill_value, getattr(mask, "shape", ()))
+            data = duck_array_ops.broadcast_to(fill_value, getattr(mask, "shape", ()))
 
         if new_order:
             data = duck_array_ops.moveaxis(data, range(len(new_order)), new_order)
@@ -896,7 +901,7 @@ def __setitem__(self, key, value):
         if new_order:
             value = duck_array_ops.asarray(value)
             value = value[(len(dims) - value.ndim) * (np.newaxis,) + (Ellipsis,)]
-            value = np.moveaxis(value, new_order, range(len(new_order)))
+            value = duck_array_ops.moveaxis(value, new_order, range(len(new_order)))
 
         indexable = as_indexable(self._data)
         indexing.set_with_indexer(indexable, index_tuple, value)
@@ -1098,7 +1103,7 @@ def _shift_one_dim(self, dim, count, fill_value=dtypes.NA):
         dim_pad = (width, 0) if count >= 0 else (0, width)
         pads = [(0, 0) if d != dim else dim_pad for d in self.dims]
 
-        data = np.pad(
+        data = duck_array_ops.pad(
             duck_array_ops.astype(trimmed_data, dtype),
             pads,
             mode="constant",
@@ -1244,7 +1249,7 @@ def pad(
         if reflect_type is not None:
             pad_option_kwargs["reflect_type"] = reflect_type
 
-        array = np.pad(
+        array = duck_array_ops.pad(
             duck_array_ops.astype(self.data, dtype, copy=False),
             pad_width_by_index,
             mode=mode,
@@ -1533,14 +1538,16 @@ def _unstack_once(
             if is_missing_values:
                 dtype, fill_value = dtypes.maybe_promote(self.dtype)
 
-                create_template = partial(np.full_like, fill_value=fill_value)
+                create_template = partial(
+                    duck_array_ops.full_like, fill_value=fill_value
+                )
             else:
                 dtype = self.dtype
                 fill_value = dtypes.get_fill_value(dtype)
-                create_template = np.empty_like
+                create_template = duck_array_ops.empty_like
         else:
             dtype = self.dtype
-            create_template = partial(np.full_like, fill_value=fill_value)
+            create_template = partial(duck_array_ops.full_like, fill_value=fill_value)
 
         if sparse:
             # unstacking a dense multitindexed array to a sparse array
@@ -1630,7 +1637,8 @@ def clip(self, min=None, max=None):
         """
         from xarray.core.computation import apply_ufunc
 
-        return apply_ufunc(np.clip, self, min, max, dask="allowed")
+        xp = duck_array_ops.get_array_namespace(self.data)
+        return apply_ufunc(xp.clip, self, min, max, dask="parallelized")
 
     def reduce(  # type: ignore[override]
         self,
@@ -1923,13 +1931,15 @@ def quantile(
         if skipna or (skipna is None and self.dtype.kind in "cfO"):
             _quantile_func = nputils.nanquantile
         else:
-            _quantile_func = np.quantile
+            _quantile_func = duck_array_ops.quantile
 
         if keep_attrs is None:
             keep_attrs = _get_keep_attrs(default=False)
 
+        xp = duck_array_ops.get_array_namespace(self.data)
+
         scalar = utils.is_scalar(q)
-        q = np.atleast_1d(np.asarray(q, dtype=np.float64))
+        q = xp.atleast_1d(xp.asarray(q, dtype=float))
 
         if dim is None:
             dim = self.dims
@@ -1939,9 +1949,10 @@ def quantile(
 
         def _wrapper(npa, **kwargs):
             # move quantile axis to end. required for apply_ufunc
-            return np.moveaxis(_quantile_func(npa, **kwargs), 0, -1)
+            return xp.moveaxis(_quantile_func(npa, **kwargs), 0, -1)
 
-        axis = np.arange(-1, -1 * len(dim) - 1, -1)
+        # jax requires hashable
+        axis = tuple(range(-1, -1 * len(dim) - 1, -1))
 
         kwargs = {"q": q, "axis": axis, "method": method}
 
diff --git a/xarray/tests/test_duck_array_wrapping.py b/xarray/tests/test_duck_array_wrapping.py
new file mode 100644
index 00000000000..1fc8ece98dd
--- /dev/null
+++ b/xarray/tests/test_duck_array_wrapping.py
@@ -0,0 +1,371 @@
+import numpy as np
+import pandas as pd
+import pytest
+
+import xarray as xr
+
+# TODO: how to test these in CI?
+jnp = pytest.importorskip("jax.numpy")
+cp = pytest.importorskip("cupy")
+
+
+def get_test_dataarray(xp):
+    return xr.DataArray(
+        xp.asarray([[1, 2, 3, np.nan, 5]]),
+        dims=["y", "x"],
+        coords={"y": [1], "x": np.arange(5)},
+        name="foo",
+    )
+
+
+@pytest.mark.parametrize("xp", [cp, jnp])
+class TestTopLevelMethods:
+    @pytest.fixture(autouse=True)
+    def setUp(self, xp):
+        self.xp = xp
+        self.Array = xp.ndarray
+        self.x1 = get_test_dataarray(xp)
+        self.x2 = get_test_dataarray(xp).assign_coords(x=np.arange(2, 7))
+
+    def test_apply_ufunc(self):
+        func = lambda x: x + 1
+        result = xr.apply_ufunc(func, self.x1)
+        assert isinstance(result.data, self.Array)
+
+    def test_align(self):
+        result = xr.align(self.x1, self.x2)
+        assert isinstance(result[0].data, self.Array)
+        assert isinstance(result[1].data, self.Array)
+
+    def test_broadcast(self):
+        result = xr.broadcast(self.x1, self.x2)
+        assert isinstance(result[0].data, self.Array)
+        assert isinstance(result[1].data, self.Array)
+
+    def test_concat(self):
+        result = xr.concat([self.x1, self.x2], dim="x")
+        assert isinstance(result.data, self.Array)
+
+    def test_merge(self):
+        result = xr.merge([self.x1, self.x2], compat="override")
+        assert isinstance(result.foo.data, self.Array)
+
+    def test_where(self):
+        x1, x2 = xr.align(self.x1, self.x2, join="inner")
+        result = xr.where(x1 > 2, x1, x2)
+        assert isinstance(result.data, self.Array)
+
+    def test_full_like(self):
+        result = xr.full_like(self.x1, 0)
+        assert isinstance(result.data, self.Array)
+
+    def test_cov(self):
+        result = xr.cov(self.x1, self.x2)
+        assert isinstance(result.data, self.Array)
+
+    def test_corr(self):
+        result = xr.corr(self.x1, self.x2)
+        assert isinstance(result.data, self.Array)
+
+    def test_cross(self):
+        x1, x2 = xr.align(self.x1.squeeze(), self.x2.squeeze(), join="inner")
+        result = xr.cross(x1, x2, dim="x")
+        assert isinstance(result.data, self.Array)
+
+    def test_dot(self):
+        result = xr.dot(self.x1, self.x2)
+        assert isinstance(result.data, self.Array)
+
+    def test_map_blocks(self):
+        result = xr.map_blocks(lambda x: x + 1, self.x1)
+        assert isinstance(result.data, self.Array)
+
+
+@pytest.mark.parametrize("xp", [cp, jnp])
+class TestDataArrayMethods:
+    @pytest.fixture(autouse=True)
+    def setUp(self, xp):
+        self.xp = xp
+        self.Array = xp.ndarray
+        self.x = get_test_dataarray(xp)
+
+    def test_loc(self):
+        result = self.x.loc[{"x": slice(1, 3)}]
+        assert isinstance(result.data, self.Array)
+
+    def test_isel(self):
+        result = self.x.isel(x=slice(1, 3))
+        assert isinstance(result.data, self.Array)
+
+    def test_sel(self):
+        result = self.x.sel(x=slice(1, 3))
+        assert isinstance(result.data, self.Array)
+
+    def test_squeeze(self):
+        result = self.x.squeeze("y")
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.xfail(reason="interp is not namespace aware")
+    def test_interp(self):
+        result = self.x.interp(x=2.5)
+        assert isinstance(result.data, self.Array)
+
+    def test_isnull(self):
+        result = self.x.isnull()
+        assert isinstance(result.data, self.Array)
+
+    def test_notnull(self):
+        result = self.x.notnull()
+        assert isinstance(result.data, self.Array)
+
+    def test_count(self):
+        result = self.x.count()
+        assert isinstance(result.data, self.Array)
+
+    def test_dropna(self):
+        result = self.x.dropna(dim="x")
+        assert isinstance(result.data, self.Array)
+
+    def test_fillna(self):
+        result = self.x.fillna(0)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.xfail(reason="ffill is not namespace aware")
+    def test_ffill(self):
+        result = self.x.ffill()
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.xfail(reason="bfill is not namespace aware")
+    def test_bfill(self):
+        result = self.x.bfill()
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.xfail(reason="interpolate_na is not namespace aware")
+    def test_interpolate_na(self):
+        result = self.x.interpolate_na()
+        assert isinstance(result.data, self.Array)
+
+    def test_where(self):
+        result = self.x.where(self.x > 2)
+        assert isinstance(result.data, self.Array)
+
+    def test_isin(self):
+        result = self.x.isin(self.xp.asarray([1]))
+        assert isinstance(result.data, self.Array)
+
+    def test_groupby(self):
+        result = self.x.groupby("x").mean()
+        assert isinstance(result.data, self.Array)
+
+    def test_rolling(self):
+        if self.xp is jnp:
+            pytest.xfail("no sliding_window_view in jax")
+        result = self.x.rolling(x=3).mean()
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.xfail(reason="rolling_exp is not namespace aware")
+    def test_rolling_exp(self):
+        result = self.x.rolling_exp(x=3).mean()
+        assert isinstance(result.data, self.Array)
+
+    def test_weighted(self):
+        result = self.x.weighted(self.x.fillna(0)).mean()
+        assert isinstance(result.data, self.Array)
+
+    def test_coarsen(self):
+        result = self.x.coarsen(x=2, boundary="pad").mean()
+        assert isinstance(result.data, self.Array)
+
+    def test_resample(self):
+        time_coord = pd.date_range("2000-01-01", periods=5)
+        result = self.x.assign_coords(x=time_coord).resample(x="D").mean()
+        assert isinstance(result.data, self.Array)
+
+    def test_diff(self):
+        result = self.x.diff("x")
+        assert isinstance(result.data, self.Array)
+
+    def test_dot(self):
+        result = self.x.dot(self.x)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_quantile(self, skipna):
+        if self.xp is cp and skipna:
+            pytest.xfail("no nanquantile in cupy")
+        result = self.x.quantile(0.5, skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    def test_differentiate(self):
+        if self.xp is jnp:
+            pytest.xfail("edge_order kwarg")
+        result = self.x.differentiate("x")
+        assert isinstance(result.data, self.Array)
+
+    def test_integrate(self):
+        result = self.x.integrate("x")
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.xfail(reason="polyfit is not namespace aware")
+    def test_polyfit(self):
+        result = self.x.polyfit("x", 1)
+        assert isinstance(result.polyfit_coefficients.data, self.Array)
+
+    def test_map_blocks(self):
+        result = self.x.map_blocks(lambda x: x + 1)
+        assert isinstance(result.data, self.Array)
+
+    def test_all(self):
+        result = self.x.all(dim="x")
+        assert isinstance(result.data, self.Array)
+
+    def test_any(self):
+        result = self.x.any(dim="x")
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_argmax(self, skipna):
+        result = self.x.argmax(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_argmin(self, skipna):
+        result = self.x.argmin(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_idxmax(self, skipna):
+        result = self.x.idxmax(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_idxmin(self, skipna):
+        result = self.x.idxmin(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_max(self, skipna):
+        result = self.x.max(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_min(self, skipna):
+        result = self.x.min(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_mean(self, skipna):
+        result = self.x.mean(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_median(self, skipna):
+        result = self.x.median(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_prod(self, skipna):
+        result = self.x.prod(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_sum(self, skipna):
+        result = self.x.sum(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_std(self, skipna):
+        if self.xp is cp and not skipna:
+            pytest.xfail("ddof/correction kwarg mismatch")
+        result = self.x.std(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_var(self, skipna):
+        if self.xp is cp and not skipna:
+            pytest.xfail("ddof/correction kwarg mismatch")
+        result = self.x.var(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_cumsum(self, skipna):
+        result = self.x.cumsum(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_cumprod(self, skipna):
+        result = self.x.cumprod(dim="x", skipna=skipna)
+        assert isinstance(result.data, self.Array)
+
+    def test_argsort(self):
+        result = self.x.argsort()
+        assert isinstance(result.data, self.Array)
+
+    def test_clip(self):
+        result = self.x.clip(min=2.0, max=4.0)
+        assert isinstance(result.data, self.Array)
+
+    def test_conj(self):
+        result = self.x.conj()
+        assert isinstance(result.data, self.Array)
+
+    def test_conjugate(self):
+        result = self.x.conjugate()
+        assert isinstance(result.data, self.Array)
+
+    def test_imag(self):
+        result = self.x.imag
+        assert isinstance(result.data, self.Array)
+
+    def test_searchsorted(self):
+        result = self.x.squeeze().searchsorted(self.xp.asarray(3))
+        assert isinstance(result, self.Array)
+
+    def test_round(self):
+        result = self.x.round()
+        assert isinstance(result.data, self.Array)
+
+    def test_real(self):
+        result = self.x.real
+        assert isinstance(result.data, self.Array)
+
+    def test_T(self):
+        result = self.x.T
+        assert isinstance(result.data, self.Array)
+
+    @pytest.mark.xfail(reason="rank is not namespace aware")
+    def test_rank(self):
+        result = self.x.rank()
+        assert isinstance(result.data, self.Array)
+
+    def test_transpose(self):
+        result = self.x.transpose()
+        assert isinstance(result.data, self.Array)
+
+    def test_stack(self):
+        result = self.x.stack(z=("x", "y"))
+        assert isinstance(result.data, self.Array)
+
+    def test_unstack(self):
+        result = self.x.stack(z=("x", "y")).unstack("z")
+        assert isinstance(result.data, self.Array)
+
+    def test_shift(self):
+        result = self.x.shift(x=1)
+        assert isinstance(result.data, self.Array)
+
+    def test_roll(self):
+        result = self.x.roll(x=1)
+        assert isinstance(result.data, self.Array)
+
+    def test_pad(self):
+        result = self.x.pad(x=1)
+        assert isinstance(result.data, self.Array)
+
+    def test_sortby(self):
+        result = self.x.sortby("x")
+        assert isinstance(result.data, self.Array)
+
+    def test_broadcast_like(self):
+        result = self.x.broadcast_like(self.x)
+        assert isinstance(result.data, self.Array)
diff --git a/xarray/tests/test_strategies.py b/xarray/tests/test_strategies.py
index 798f5f732d1..48819333ca2 100644
--- a/xarray/tests/test_strategies.py
+++ b/xarray/tests/test_strategies.py
@@ -13,6 +13,7 @@
 from hypothesis import given
 from hypothesis.extra.array_api import make_strategies_namespace
 
+from xarray.core.options import set_options
 from xarray.core.variable import Variable
 from xarray.testing.strategies import (
     attrs,
@@ -267,14 +268,14 @@ def test_mean(self, data, var):
         Test that given a Variable of at least one dimension,
         the mean of the Variable is always equal to the mean of the underlying array.
         """
+        with set_options(use_numbagg=False):
+            # specify arbitrary reduction along at least one dimension
+            reduction_dims = data.draw(unique_subset_of(var.dims, min_size=1))
 
-        # specify arbitrary reduction along at least one dimension
-        reduction_dims = data.draw(unique_subset_of(var.dims, min_size=1))
+            # create expected result (using nanmean because arrays with Nans will be generated)
+            reduction_axes = tuple(var.get_axis_num(dim) for dim in reduction_dims)
+            expected = np.nanmean(var.data, axis=reduction_axes)
 
-        # create expected result (using nanmean because arrays with Nans will be generated)
-        reduction_axes = tuple(var.get_axis_num(dim) for dim in reduction_dims)
-        expected = np.nanmean(var.data, axis=reduction_axes)
-
-        # assert property is always satisfied
-        result = var.mean(dim=reduction_dims).data
-        npt.assert_equal(expected, result)
+            # assert property is always satisfied
+            result = var.mean(dim=reduction_dims).data
+            npt.assert_equal(expected, result)
diff --git a/xarray/tests/test_variable.py b/xarray/tests/test_variable.py
index 9c6f50037d3..1461489e731 100644
--- a/xarray/tests/test_variable.py
+++ b/xarray/tests/test_variable.py
@@ -1978,26 +1978,27 @@ def test_reduce_funcs(self):
     def test_reduce_keepdims(self):
         v = Variable(["x", "y"], self.d)
 
-        assert_identical(
-            v.mean(keepdims=True), Variable(v.dims, np.mean(self.d, keepdims=True))
-        )
-        assert_identical(
-            v.mean(dim="x", keepdims=True),
-            Variable(v.dims, np.mean(self.d, axis=0, keepdims=True)),
-        )
-        assert_identical(
-            v.mean(dim="y", keepdims=True),
-            Variable(v.dims, np.mean(self.d, axis=1, keepdims=True)),
-        )
-        assert_identical(
-            v.mean(dim=["y", "x"], keepdims=True),
-            Variable(v.dims, np.mean(self.d, axis=(1, 0), keepdims=True)),
-        )
+        with set_options(use_numbagg=False):
+            assert_identical(
+                v.mean(keepdims=True), Variable(v.dims, np.mean(self.d, keepdims=True))
+            )
+            assert_identical(
+                v.mean(dim="x", keepdims=True),
+                Variable(v.dims, np.mean(self.d, axis=0, keepdims=True)),
+            )
+            assert_identical(
+                v.mean(dim="y", keepdims=True),
+                Variable(v.dims, np.mean(self.d, axis=1, keepdims=True)),
+            )
+            assert_identical(
+                v.mean(dim=["y", "x"], keepdims=True),
+                Variable(v.dims, np.mean(self.d, axis=(1, 0), keepdims=True)),
+            )
 
-        v = Variable([], 1.0)
-        assert_identical(
-            v.mean(keepdims=True), Variable([], np.mean(v.data, keepdims=True))
-        )
+            v = Variable([], 1.0)
+            assert_identical(
+                v.mean(keepdims=True), Variable([], np.mean(v.data, keepdims=True))
+            )
 
     @requires_dask
     def test_reduce_keepdims_dask(self):

From f7866ce78bd71e604a8e05d14cc8080dd7dd9ec4 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Mon, 18 Nov 2024 15:15:27 -0500
Subject: [PATCH 02/24] merge sliding_window_view

---
 xarray/core/duck_array_ops.py | 27 +++++++++++++--------------
 1 file changed, 13 insertions(+), 14 deletions(-)

diff --git a/xarray/core/duck_array_ops.py b/xarray/core/duck_array_ops.py
index cca07a44f52..f994fec7ae8 100644
--- a/xarray/core/duck_array_ops.py
+++ b/xarray/core/duck_array_ops.py
@@ -122,21 +122,20 @@ def fail_on_dask_array_input(values, msg=None, func_name=None):
     "masked_invalid", eager_module=np.ma, dask_module="dask.array.ma"
 )
 
-# sliding_window_view will not dispatch arbitrary kwargs (automatic_rechunk),
-# so we need to hand-code this.
-sliding_window_view = _dask_or_eager_func(
-    "sliding_window_view",
-    eager_module=np.lib.stride_tricks,
-    dask_module=dask_array_compat,
-    dask_only_kwargs=("automatic_rechunk",),
-    numpy_only_kwargs=("subok", "writeable"),
-)
-
 
-# def sliding_window_view(array, window_shape, axis=None):
-#     # TODO: some array libraries don't support this, implement an alternative?
-#     xp = get_array_namespace(array)
-#     return xp.lib.stride_tricks.sliding_window_view(array, window_shape, axis=axis)
+def sliding_window_view(array, window_shape, axis=None, **kwargs):
+    # TODO: some libraries (e.g. jax) don't have this, implement an alternative?
+    xp = get_array_namespace(array)
+    # sliding_window_view will not dispatch arbitrary kwargs (automatic_rechunk),
+    # so we need to hand-code this.
+    func = _dask_or_eager_func(
+        "sliding_window_view",
+        eager_module=xp.lib.stride_tricks,
+        dask_module=dask_array_compat,
+        dask_only_kwargs=("automatic_rechunk",),
+        numpy_only_kwargs=("subok", "writeable"),
+    )
+    return func(array, window_shape, axis=axis, **kwargs)
 
 
 def round(array):

From 90037fe8e883cef727f8a4893541f94a46c583cc Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Mon, 18 Nov 2024 15:25:57 -0500
Subject: [PATCH 03/24] namespaces constant

---
 xarray/tests/test_duck_array_wrapping.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/xarray/tests/test_duck_array_wrapping.py b/xarray/tests/test_duck_array_wrapping.py
index 1fc8ece98dd..c58c62bf84b 100644
--- a/xarray/tests/test_duck_array_wrapping.py
+++ b/xarray/tests/test_duck_array_wrapping.py
@@ -8,6 +8,8 @@
 jnp = pytest.importorskip("jax.numpy")
 cp = pytest.importorskip("cupy")
 
+NAMESPACES = [cp, jnp]
+
 
 def get_test_dataarray(xp):
     return xr.DataArray(
@@ -18,7 +20,7 @@ def get_test_dataarray(xp):
     )
 
 
-@pytest.mark.parametrize("xp", [cp, jnp])
+@pytest.mark.parametrize("xp", NAMESPACES)
 class TestTopLevelMethods:
     @pytest.fixture(autouse=True)
     def setUp(self, xp):
@@ -81,7 +83,7 @@ def test_map_blocks(self):
         assert isinstance(result.data, self.Array)
 
 
-@pytest.mark.parametrize("xp", [cp, jnp])
+@pytest.mark.parametrize("xp", NAMESPACES)
 class TestDataArrayMethods:
     @pytest.fixture(autouse=True)
     def setUp(self, xp):

From 5ba1a2f81280007b1e6ac1089aa9934e76c5c83e Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Mon, 18 Nov 2024 15:32:03 -0500
Subject: [PATCH 04/24] revert dask allowed

---
 xarray/core/variable.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index 1597e4bbe66..dd67b290cf2 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -1638,7 +1638,7 @@ def clip(self, min=None, max=None):
         from xarray.core.computation import apply_ufunc
 
         xp = duck_array_ops.get_array_namespace(self.data)
-        return apply_ufunc(xp.clip, self, min, max, dask="parallelized")
+        return apply_ufunc(xp.clip, self, min, max, dask="allowed")
 
     def reduce(  # type: ignore[override]
         self,

From 6225ae3a70d785047259decda130513d1e5df03a Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Tue, 19 Nov 2024 15:20:12 -0500
Subject: [PATCH 05/24] fix up some tests

---
 xarray/core/dataset.py        | 9 ++++++---
 xarray/core/duck_array_ops.py | 3 ++-
 xarray/core/nputils.py        | 3 +++
 xarray/core/variable.py       | 6 +++---
 4 files changed, 14 insertions(+), 7 deletions(-)

diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 6e5a8e163b8..b7ecacf98b3 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -8679,9 +8679,12 @@ def _integrate_one(self, coord, datetime_unit=None, cumulative=False):
             else:
                 if k in self.data_vars and dim in v.dims:
                     # cast coord data to duck array if needed
-                    coord_data = duck_array_ops.get_array_namespace(v.data).asarray(
-                        coord_var.data
-                    )
+                    if isinstance(v.data, array_type("cupy")):
+                        coord_data = duck_array_ops.get_array_namespace(v.data).asarray(
+                            coord_var.data
+                        )
+                    else:
+                        coord_data = coord_var.data
                     if _contains_datetime_like_objects(v):
                         v = datetime_to_numeric(v, datetime_unit=datetime_unit)
                     if cumulative:
diff --git a/xarray/core/duck_array_ops.py b/xarray/core/duck_array_ops.py
index f994fec7ae8..746004c630d 100644
--- a/xarray/core/duck_array_ops.py
+++ b/xarray/core/duck_array_ops.py
@@ -168,7 +168,8 @@ def isnull(data):
         )
     ):
         # these types cannot represent missing values
-        return full_like(data, dtype=xp.bool, fill_value=False)
+        dtype = xp.bool_ if hasattr(xp, "bool_") else xp.bool
+        return full_like(data, dtype=dtype, fill_value=False)
     else:
         # at this point, array should have dtype=object
         if isinstance(data, np.ndarray) or is_extension_array_dtype(data):
diff --git a/xarray/core/nputils.py b/xarray/core/nputils.py
index 24d6b1dda72..b5f399debab 100644
--- a/xarray/core/nputils.py
+++ b/xarray/core/nputils.py
@@ -236,6 +236,9 @@ def f(values, axis=None, **kwargs):
             # bottleneck does not take care dtype, min_count
             kwargs.pop("dtype", None)
             result = bn_func(values, axis=axis, **kwargs)
+            # bottleneck returns python scalars for reduction over all axes
+            if isinstance(result, float):
+                result = np.float64(result)
         else:
             result = getattr(npmodule, name)(values, axis=axis, **kwargs)
 
diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index dd67b290cf2..dd6feb4f07d 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -1936,10 +1936,8 @@ def quantile(
         if keep_attrs is None:
             keep_attrs = _get_keep_attrs(default=False)
 
-        xp = duck_array_ops.get_array_namespace(self.data)
-
         scalar = utils.is_scalar(q)
-        q = xp.atleast_1d(xp.asarray(q, dtype=float))
+        q = np.atleast_1d(np.asarray(q, dtype=np.float64))
 
         if dim is None:
             dim = self.dims
@@ -1947,6 +1945,8 @@ def quantile(
         if utils.is_scalar(dim):
             dim = [dim]
 
+        xp = duck_array_ops.get_array_namespace(self.data)
+
         def _wrapper(npa, **kwargs):
             # move quantile axis to end. required for apply_ufunc
             return xp.moveaxis(_quantile_func(npa, **kwargs), 0, -1)

From e2911c2810a628a5b1a7becec103c2c8528d1c37 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Tue, 19 Nov 2024 16:16:19 -0500
Subject: [PATCH 06/24] backwards compat sparse mask

---
 xarray/core/variable.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index dd6feb4f07d..833b15d7993 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -861,7 +861,7 @@ def _getitem_with_mask(self, key, fill_value=dtypes.NA):
             # pint to choose the correct unit
             # TODO: revert after https://github.com/hgrecco/pint/issues/1019 is fixed
             # cast mask to any duck array type
-            if not is_duck_dask_array(mask):
+            if type(mask) is not type(data):
                 mask = duck_array_ops.get_array_namespace(data).asarray(mask)
             data = duck_array_ops.where(
                 duck_array_ops.logical_not(mask), data, fill_value

From 2ac37f9769236225d6d6692e2e2ce60414d5e9d0 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Wed, 20 Nov 2024 22:13:22 -0500
Subject: [PATCH 07/24] add as_array methods

---
 xarray/core/dataarray.py       | 22 ++++++++++++++++++++++
 xarray/core/dataset.py         | 26 ++++++++++++++++++++++++++
 xarray/namedarray/core.py      |  4 ++++
 xarray/tests/test_dataarray.py | 13 +++++++++++++
 xarray/tests/test_dataset.py   | 15 +++++++++++++++
 5 files changed, 80 insertions(+)

diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 52ce2463d51..2b19863e35e 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -842,6 +842,28 @@ def as_numpy(self) -> Self:
         coords = {k: v.as_numpy() for k, v in self._coords.items()}
         return self._replace(self.variable.as_numpy(), coords, indexes=self._indexes)
 
+    def as_array(self, asarray: Callable[[ArrayLike, ...], Any], **kwargs) -> Self:
+        """
+        Coerces wrapped data into a specific array type.
+
+        `asarray` should output an object that supports the Array API Standard.
+        This method does not convert index coordinates, which can't generally be
+        represented as arbitrary array types.
+
+        Parameters
+        ----------
+        asarray : Callable
+            Function that converts an array-like object to the desired array type.
+            For example, `cupy.asarray`, `jax.numpy.asarray`, or `sparse.COO.from_numpy`.
+        **kwargs : dict
+            Additional keyword arguments passed to the `asarray` function.
+
+        Returns
+        -------
+        DataArray
+        """
+        return self._replace(self.variable.as_array(asarray, **kwargs))
+
     @property
     def _in_memory(self) -> bool:
         return self.variable._in_memory
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index b7ecacf98b3..700d733a543 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -1434,6 +1434,32 @@ def as_numpy(self) -> Self:
         numpy_variables = {k: v.as_numpy() for k, v in self.variables.items()}
         return self._replace(variables=numpy_variables)
 
+    def as_array(self, asarray: Callable[[ArrayLike, ...], Any], **kwargs) -> Self:
+        """
+        Converts wrapped data into a specific array type.
+
+        `asarray` should output an object that supports the Array API Standard.
+        This method does not convert index coordinates, which can't generally be
+        represented as arbitrary array types.
+
+        Parameters
+        ----------
+        asarray : Callable
+            Function that converts an array-like object to the desired array type.
+            For example, `cupy.asarray`, `jax.numpy.asarray`, or `sparse.COO.from_numpy`.
+        **kwargs : dict
+            Additional keyword arguments passed to the `asarray` function.
+
+        Returns
+        -------
+        Dataset
+        """
+        array_variables = {
+            k: v.as_array(asarray, **kwargs) if k not in self._indexes else v
+            for k, v in self.variables.items()
+        }
+        return self._replace(variables=array_variables)
+
     def _copy_listed(self, names: Iterable[Hashable]) -> Self:
         """Create a new Dataset with the listed variables from this dataset and
         the all relevant coordinates. Skips all validation.
diff --git a/xarray/namedarray/core.py b/xarray/namedarray/core.py
index 98d96c73e91..8ae17ebce13 100644
--- a/xarray/namedarray/core.py
+++ b/xarray/namedarray/core.py
@@ -860,6 +860,10 @@ def as_numpy(self) -> Self:
         """Coerces wrapped data into a numpy array, returning a Variable."""
         return self._replace(data=self.to_numpy())
 
+    def as_array(self, asarray: Callable[[ArrayLike, ...], Any], **kwargs) -> Self:
+        """Coerces wrapped data into a specific array type, returning a Variable."""
+        return self._replace(data=asarray(self._data, **kwargs))
+
     def reduce(
         self,
         func: Callable[..., Any],
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index b5ecc9517d9..aa6cb5e1721 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -39,6 +39,7 @@
 from xarray.core.utils import is_scalar
 from xarray.testing import _assert_internal_invariants
 from xarray.tests import (
+    DuckArrayWrapper,
     InaccessibleArray,
     ReturnItem,
     assert_allclose,
@@ -7165,6 +7166,18 @@ def test_from_pint_wrapping_dask(self) -> None:
         np.testing.assert_equal(da.to_numpy(), arr)
 
 
+def test_as_array() -> None:
+    da = xr.DataArray([1, 2, 3], dims=["x"], coords={"x": [4, 5, 6]})
+
+    def as_duck_array(arr):
+        return DuckArrayWrapper(arr)
+
+    result = da.as_array(as_duck_array)
+
+    assert isinstance(result.data, DuckArrayWrapper)
+    assert isinstance(result.x.data, np.ndarray)
+
+
 class TestStackEllipsis:
     # https://github.com/pydata/xarray/issues/6051
     def test_result_as_expected(self) -> None:
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index be82655515d..bbfc2df3fd7 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -7639,6 +7639,21 @@ def test_from_pint_wrapping_dask(self) -> None:
         assert_identical(result, expected)
 
 
+def test_as_array() -> None:
+    ds = xr.Dataset(
+        {"a": ("x", [1, 2, 3])}, coords={"lat": ("x", [4, 5, 6]), "x": [7, 8, 9]}
+    )
+
+    def as_duck_array(arr):
+        return DuckArrayWrapper(arr)
+
+    result = ds.as_array(as_duck_array)
+
+    assert isinstance(result.a.data, DuckArrayWrapper)
+    assert isinstance(result.lat.data, DuckArrayWrapper)
+    assert isinstance(result.x.data, np.ndarray)
+
+
 def test_string_keys_typing() -> None:
     """Tests that string keys to `variables` are permitted by mypy"""
 

From 1cc344ba46164fd2294c2d6fdaf8bc1e7c273afd Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Wed, 20 Nov 2024 22:42:54 -0500
Subject: [PATCH 08/24] to_like_array helper

---
 xarray/core/array_api_compat.py | 6 ++++++
 xarray/core/computation.py      | 5 ++---
 xarray/core/dataset.py          | 9 ++-------
 xarray/core/variable.py         | 5 ++---
 4 files changed, 12 insertions(+), 13 deletions(-)

diff --git a/xarray/core/array_api_compat.py b/xarray/core/array_api_compat.py
index 28d671cc349..1845d6eddcc 100644
--- a/xarray/core/array_api_compat.py
+++ b/xarray/core/array_api_compat.py
@@ -70,3 +70,9 @@ def _get_single_namespace(x):
         xp = np
 
     return xp
+
+
+def to_like_array(array, like):
+    # Mostly for cupy compatibility, because cupy binary ops require all cupy arrays
+    xp = get_array_namespace(like)
+    return xp.asarray(array)
diff --git a/xarray/core/computation.py b/xarray/core/computation.py
index 0bfe21642f7..0945f4638f6 100644
--- a/xarray/core/computation.py
+++ b/xarray/core/computation.py
@@ -24,6 +24,7 @@
 
 from xarray.core import dtypes, duck_array_ops, utils
 from xarray.core.alignment import align, deep_align
+from xarray.core.array_api_compat import to_like_array
 from xarray.core.common import zeros_like
 from xarray.core.duck_array_ops import datetime_to_numeric
 from xarray.core.formatting import limit_lines
@@ -2178,9 +2179,7 @@ def _calc_idxminmax(
         res = array[dim][(indx,)]
         # The dim is gone but we need to remove the corresponding coordinate.
         del res.coords[dim]
-        # Cast to array namespace
-        xp = duck_array_ops.get_array_namespace(array.data)
-        res.data = xp.asarray(res.data)
+        res.data = to_like_array(res.data, array.data)
 
     if skipna or (skipna is None and array.dtype.kind in na_dtypes):
         # Put the NaN values back in after removing them
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 700d733a543..eded1d89d05 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -55,6 +55,7 @@
     align,
 )
 from xarray.core.arithmetic import DatasetArithmetic
+from xarray.core.array_api_compat import to_like_array
 from xarray.core.common import (
     DataWithCoords,
     _contains_datetime_like_objects,
@@ -8704,13 +8705,7 @@ def _integrate_one(self, coord, datetime_unit=None, cumulative=False):
                     coord_names.add(k)
             else:
                 if k in self.data_vars and dim in v.dims:
-                    # cast coord data to duck array if needed
-                    if isinstance(v.data, array_type("cupy")):
-                        coord_data = duck_array_ops.get_array_namespace(v.data).asarray(
-                            coord_var.data
-                        )
-                    else:
-                        coord_data = coord_var.data
+                    coord_data = to_like_array(coord_var.data, like=v.data)
                     if _contains_datetime_like_objects(v):
                         v = datetime_to_numeric(v, datetime_unit=datetime_unit)
                     if cumulative:
diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index 833b15d7993..a472e809876 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -19,6 +19,7 @@
 import xarray as xr  # only for Dataset and DataArray
 from xarray.core import common, dtypes, duck_array_ops, indexing, nputils, ops, utils
 from xarray.core.arithmetic import VariableArithmetic
+from xarray.core.array_api_compat import to_like_array
 from xarray.core.common import AbstractArray
 from xarray.core.extension_array import PandasExtensionArray
 from xarray.core.indexing import (
@@ -860,9 +861,7 @@ def _getitem_with_mask(self, key, fill_value=dtypes.NA):
             # we need to invert the mask in order to pass data first. This helps
             # pint to choose the correct unit
             # TODO: revert after https://github.com/hgrecco/pint/issues/1019 is fixed
-            # cast mask to any duck array type
-            if type(mask) is not type(data):
-                mask = duck_array_ops.get_array_namespace(data).asarray(mask)
+            mask = to_like_array(mask, data)
             data = duck_array_ops.where(
                 duck_array_ops.logical_not(mask), data, fill_value
             )

From 372439ce144f97fdf1e2fdee1e0d5c5f05ae919e Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Wed, 20 Nov 2024 22:58:45 -0500
Subject: [PATCH 09/24] only cast non-numpy

---
 xarray/core/array_api_compat.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/xarray/core/array_api_compat.py b/xarray/core/array_api_compat.py
index 1845d6eddcc..e7424325de8 100644
--- a/xarray/core/array_api_compat.py
+++ b/xarray/core/array_api_compat.py
@@ -75,4 +75,7 @@ def _get_single_namespace(x):
 def to_like_array(array, like):
     # Mostly for cupy compatibility, because cupy binary ops require all cupy arrays
     xp = get_array_namespace(like)
-    return xp.asarray(array)
+    if xp is not np:
+        return xp.asarray(array)
+    # avoid casting things like pint quantities to numpy arrays
+    return array

From 0eef2cbe2d0cae5fd80c8d3e510e54e1d2978df3 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Wed, 20 Nov 2024 23:27:43 -0500
Subject: [PATCH 10/24] better idxminmax approach

---
 xarray/core/computation.py | 17 ++++++++---------
 1 file changed, 8 insertions(+), 9 deletions(-)

diff --git a/xarray/core/computation.py b/xarray/core/computation.py
index 0945f4638f6..6e233425e95 100644
--- a/xarray/core/computation.py
+++ b/xarray/core/computation.py
@@ -35,7 +35,7 @@
 from xarray.core.utils import is_dict_like, is_scalar, parse_dims_as_set, result_name
 from xarray.core.variable import Variable
 from xarray.namedarray.parallelcompat import get_chunked_array_type
-from xarray.namedarray.pycompat import is_chunked_array, to_numpy
+from xarray.namedarray.pycompat import is_chunked_array
 from xarray.util.deprecation_helpers import deprecate_dims
 
 if TYPE_CHECKING:
@@ -2171,15 +2171,14 @@ def _calc_idxminmax(
         chunks = dict(zip(array.dims, array.chunks, strict=True))
         dask_coord = chunkmanager.from_array(array[dim].data, chunks=chunks[dim])
         data = dask_coord[duck_array_ops.ravel(indx.data)]
-        res = indx.copy(data=duck_array_ops.reshape(data, indx.shape))
-        # we need to attach back the dim name
-        res.name = dim
     else:
-        indx.data = to_numpy(indx.data)
-        res = array[dim][(indx,)]
-        # The dim is gone but we need to remove the corresponding coordinate.
-        del res.coords[dim]
-        res.data = to_like_array(res.data, array.data)
+        arr_coord = to_like_array(array[dim].data, array.data)
+        data = arr_coord[duck_array_ops.ravel(indx.data)]
+
+    # rebuild like the argmin/max output, and rename as the dim name
+    data = duck_array_ops.reshape(data, indx.shape)
+    res = indx.copy(data=data)
+    res.name = dim
 
     if skipna or (skipna is None and array.dtype.kind in na_dtypes):
         # Put the NaN values back in after removing them

From 6739504fc7a7f2f4646ff7c06aa7b2653840c00d Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Wed, 20 Nov 2024 23:58:38 -0500
Subject: [PATCH 11/24] fix mypy

---
 xarray/core/dataarray.py  | 2 +-
 xarray/core/dataset.py    | 2 +-
 xarray/namedarray/core.py | 6 +++++-
 3 files changed, 7 insertions(+), 3 deletions(-)

diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 2f8a6ce620b..ff9880bf2da 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -842,7 +842,7 @@ def as_numpy(self) -> Self:
         coords = {k: v.as_numpy() for k, v in self._coords.items()}
         return self._replace(self.variable.as_numpy(), coords, indexes=self._indexes)
 
-    def as_array(self, asarray: Callable[[ArrayLike, ...], Any], **kwargs) -> Self:
+    def as_array(self, asarray: Callable, **kwargs) -> Self:
         """
         Coerces wrapped data into a specific array type.
 
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index eded1d89d05..3711045f8c9 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -1435,7 +1435,7 @@ def as_numpy(self) -> Self:
         numpy_variables = {k: v.as_numpy() for k, v in self.variables.items()}
         return self._replace(variables=numpy_variables)
 
-    def as_array(self, asarray: Callable[[ArrayLike, ...], Any], **kwargs) -> Self:
+    def as_array(self, asarray: Callable, **kwargs) -> Self:
         """
         Converts wrapped data into a specific array type.
 
diff --git a/xarray/namedarray/core.py b/xarray/namedarray/core.py
index 8ae17ebce13..e80a15fdc3f 100644
--- a/xarray/namedarray/core.py
+++ b/xarray/namedarray/core.py
@@ -860,7 +860,11 @@ def as_numpy(self) -> Self:
         """Coerces wrapped data into a numpy array, returning a Variable."""
         return self._replace(data=self.to_numpy())
 
-    def as_array(self, asarray: Callable[[ArrayLike, ...], Any], **kwargs) -> Self:
+    def as_array(
+        self,
+        asarray: Callable[[duckarray[Any, _DType_co]], duckarray[Any, _DType_co]],
+        **kwargs: Any,
+    ) -> Self:
         """Coerces wrapped data into a specific array type, returning a Variable."""
         return self._replace(data=asarray(self._data, **kwargs))
 

From 9e6d6f8155a467f1c941de8496255bcca2b4ddbf Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Thu, 21 Nov 2024 09:27:02 -0500
Subject: [PATCH 12/24] naming, add is_array_type

---
 xarray/core/dataarray.py       | 22 +++++++++++++++++++---
 xarray/core/dataset.py         | 26 +++++++++++++++++++++++---
 xarray/namedarray/core.py      | 31 +++++++++++++++++++++++++++++--
 xarray/tests/test_dataarray.py |  7 +++++--
 xarray/tests/test_dataset.py   |  7 +++++--
 5 files changed, 81 insertions(+), 12 deletions(-)

diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index ff9880bf2da..7796904d897 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -842,7 +842,7 @@ def as_numpy(self) -> Self:
         coords = {k: v.as_numpy() for k, v in self._coords.items()}
         return self._replace(self.variable.as_numpy(), coords, indexes=self._indexes)
 
-    def as_array(self, asarray: Callable, **kwargs) -> Self:
+    def as_array_type(self, asarray: Callable, **kwargs) -> Self:
         """
         Coerces wrapped data into a specific array type.
 
@@ -854,7 +854,8 @@ def as_array(self, asarray: Callable, **kwargs) -> Self:
         ----------
         asarray : Callable
             Function that converts an array-like object to the desired array type.
-            For example, `cupy.asarray`, `jax.numpy.asarray`, or `sparse.COO.from_numpy`.
+            For example, `cupy.asarray`, `jax.numpy.asarray`, `sparse.COO.from_numpy`,
+            or any `from_dlpack` method.
         **kwargs : dict
             Additional keyword arguments passed to the `asarray` function.
 
@@ -862,7 +863,22 @@ def as_array(self, asarray: Callable, **kwargs) -> Self:
         -------
         DataArray
         """
-        return self._replace(self.variable.as_array(asarray, **kwargs))
+        return self._replace(self.variable.as_array_type(asarray, **kwargs))
+
+    def is_array_type(self, array_type: type) -> bool:
+        """
+        Check if the wrapped data is of a specific array type.
+
+        Parameters
+        ----------
+        array_type : type
+            The array type to check for.
+
+        Returns
+        -------
+        bool
+        """
+        return self.variable.is_array_type(array_type)
 
     @property
     def _in_memory(self) -> bool:
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 3711045f8c9..32ea1b98308 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -1435,7 +1435,7 @@ def as_numpy(self) -> Self:
         numpy_variables = {k: v.as_numpy() for k, v in self.variables.items()}
         return self._replace(variables=numpy_variables)
 
-    def as_array(self, asarray: Callable, **kwargs) -> Self:
+    def as_array_type(self, asarray: Callable, **kwargs) -> Self:
         """
         Converts wrapped data into a specific array type.
 
@@ -1447,7 +1447,8 @@ def as_array(self, asarray: Callable, **kwargs) -> Self:
         ----------
         asarray : Callable
             Function that converts an array-like object to the desired array type.
-            For example, `cupy.asarray`, `jax.numpy.asarray`, or `sparse.COO.from_numpy`.
+            For example, `cupy.asarray`, `jax.numpy.asarray`, `sparse.COO.from_numpy`,
+            or any `from_dlpack` method.
         **kwargs : dict
             Additional keyword arguments passed to the `asarray` function.
 
@@ -1456,11 +1457,30 @@ def as_array(self, asarray: Callable, **kwargs) -> Self:
         Dataset
         """
         array_variables = {
-            k: v.as_array(asarray, **kwargs) if k not in self._indexes else v
+            k: v.as_array_type(asarray, **kwargs) if k not in self._indexes else v
             for k, v in self.variables.items()
         }
         return self._replace(variables=array_variables)
 
+    def is_array_type(self, array_type: type) -> bool:
+        """
+        Check if all data variables and non-index coordinates are of a specific array type.
+
+        Parameters
+        ----------
+        array_type : type
+            The array type to check for.
+
+        Returns
+        -------
+        bool
+        """
+        return all(
+            v.is_array_type(array_type)
+            for k, v in self.variables.items()
+            if k not in self._indexes
+        )
+
     def _copy_listed(self, names: Iterable[Hashable]) -> Self:
         """Create a new Dataset with the listed variables from this dataset and
         the all relevant coordinates. Skips all validation.
diff --git a/xarray/namedarray/core.py b/xarray/namedarray/core.py
index e80a15fdc3f..2558ecec9c7 100644
--- a/xarray/namedarray/core.py
+++ b/xarray/namedarray/core.py
@@ -860,14 +860,41 @@ def as_numpy(self) -> Self:
         """Coerces wrapped data into a numpy array, returning a Variable."""
         return self._replace(data=self.to_numpy())
 
-    def as_array(
+    def as_array_type(
         self,
         asarray: Callable[[duckarray[Any, _DType_co]], duckarray[Any, _DType_co]],
         **kwargs: Any,
     ) -> Self:
-        """Coerces wrapped data into a specific array type, returning a Variable."""
+        """Converts wrapped data into a specific array type.
+
+        Parameters
+        ----------
+        asarray : callable
+            Function that converts the data into a specific array type.
+        **kwargs : dict
+            Additional keyword arguments passed on to `asarray`.
+
+        Returns
+        -------
+        array : NamedArray
+            Array with the same data, but converted into a specific array type
+        """
         return self._replace(data=asarray(self._data, **kwargs))
 
+    def is_array_type(self, array_type: type) -> bool:
+        """Check if the data is an instance of a specific array type.
+
+        Parameters
+        ----------
+        array_type : type
+            Array type to check against.
+
+        Returns
+        -------
+        is_array_type : bool
+        """
+        return isinstance(self._data, array_type)
+
     def reduce(
         self,
         func: Callable[..., Any],
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index 6e1efe85185..8bc63f3bf4b 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -7166,16 +7166,19 @@ def test_from_pint_wrapping_dask(self) -> None:
         np.testing.assert_equal(da.to_numpy(), arr)
 
 
-def test_as_array() -> None:
+def test_as_array_type_is_array_type() -> None:
     da = xr.DataArray([1, 2, 3], dims=["x"], coords={"x": [4, 5, 6]})
 
+    assert da.is_array_type(np.ndarray)
+
     def as_duck_array(arr):
         return DuckArrayWrapper(arr)
 
-    result = da.as_array(as_duck_array)
+    result = da.as_array_type(as_duck_array)
 
     assert isinstance(result.data, DuckArrayWrapper)
     assert isinstance(result.x.data, np.ndarray)
+    assert result.is_array_type(DuckArrayWrapper)
 
 
 class TestStackEllipsis:
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index 13917e28225..edca2a02c93 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -7639,19 +7639,22 @@ def test_from_pint_wrapping_dask(self) -> None:
         assert_identical(result, expected)
 
 
-def test_as_array() -> None:
+def test_as_array_type_is_array_type() -> None:
     ds = xr.Dataset(
         {"a": ("x", [1, 2, 3])}, coords={"lat": ("x", [4, 5, 6]), "x": [7, 8, 9]}
     )
+    # lat is a PandasIndex here
+    assert ds.drop_vars("lat").is_array_type(np.ndarray)
 
     def as_duck_array(arr):
         return DuckArrayWrapper(arr)
 
-    result = ds.as_array(as_duck_array)
+    result = ds.as_array_type(as_duck_array)
 
     assert isinstance(result.a.data, DuckArrayWrapper)
     assert isinstance(result.lat.data, DuckArrayWrapper)
     assert isinstance(result.x.data, np.ndarray)
+    assert result.is_array_type(DuckArrayWrapper)
 
 
 def test_string_keys_typing() -> None:

From e72101155ed172a217b90d5fc36c95a495545049 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Thu, 21 Nov 2024 09:31:45 -0500
Subject: [PATCH 13/24] add public doc and whats new

---
 doc/api.rst       | 4 ++++
 doc/whats-new.rst | 4 ++++
 2 files changed, 8 insertions(+)

diff --git a/doc/api.rst b/doc/api.rst
index 0c30ddc4c20..e5517eaf07e 100644
--- a/doc/api.rst
+++ b/doc/api.rst
@@ -117,6 +117,8 @@ Dataset contents
    Dataset.convert_calendar
    Dataset.interp_calendar
    Dataset.get_index
+   Dataset.as_array_type
+   Dataset.is_array_type
 
 Comparisons
 -----------
@@ -315,6 +317,8 @@ DataArray contents
    DataArray.get_index
    DataArray.astype
    DataArray.item
+   DataArray.as_array_type
+   DataArray.is_array_type
 
 Indexing
 --------
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 3a04467d483..8084cc17780 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -64,6 +64,10 @@ New Features
   underlying array's backend. Provides better support for certain wrapped array types
   like ``jax.numpy.ndarray``. (:issue:`7848`, :pull:`9776`).
   By `Sam Levang <https://github.com/slevang>`_.
+- Make more xarray methods fully compatible with duck array types, and introduce new
+  ``as_array_type`` and ``is_array_type`` methods for converting wrapped data to other
+  duck array types. (:issue:`7848`, :pull:`9798`).
+  By `Sam Levang <https://github.com/slevang>`_.
 
 Breaking changes
 ~~~~~~~~~~~~~~~~

From 1fe41316b2063db6b131828c0fcd26e1d3926abc Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Thu, 21 Nov 2024 10:19:28 -0500
Subject: [PATCH 14/24] update comments

---
 xarray/core/array_api_compat.py          |  3 ++-
 xarray/core/dataarray.py                 |  2 +-
 xarray/tests/test_duck_array_wrapping.py | 27 ++++++++++++------------
 3 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/xarray/core/array_api_compat.py b/xarray/core/array_api_compat.py
index e7424325de8..e1e5d5c5bdc 100644
--- a/xarray/core/array_api_compat.py
+++ b/xarray/core/array_api_compat.py
@@ -51,7 +51,8 @@ def _get_single_namespace(x):
         if hasattr(x, "__array_namespace__"):
             return x.__array_namespace__()
         elif isinstance(x, array_type("cupy")):
-            # special case cupy for now
+            # cupy is fully compliant from xarray's perspective, but will not expose
+            # __array_namespace__ until at least v14. Special case it for now
             import cupy as cp
 
             return cp
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index 7796904d897..ead13663cb8 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -844,7 +844,7 @@ def as_numpy(self) -> Self:
 
     def as_array_type(self, asarray: Callable, **kwargs) -> Self:
         """
-        Coerces wrapped data into a specific array type.
+        Converts wrapped data into a specific array type.
 
         `asarray` should output an object that supports the Array API Standard.
         This method does not convert index coordinates, which can't generally be
diff --git a/xarray/tests/test_duck_array_wrapping.py b/xarray/tests/test_duck_array_wrapping.py
index c58c62bf84b..ffaa1440e1a 100644
--- a/xarray/tests/test_duck_array_wrapping.py
+++ b/xarray/tests/test_duck_array_wrapping.py
@@ -107,8 +107,9 @@ def test_squeeze(self):
         result = self.x.squeeze("y")
         assert isinstance(result.data, self.Array)
 
-    @pytest.mark.xfail(reason="interp is not namespace aware")
+    @pytest.mark.xfail(reason="interp uses numpy and scipy")
     def test_interp(self):
+        # TODO: some cases could be made to work
         result = self.x.interp(x=2.5)
         assert isinstance(result.data, self.Array)
 
@@ -132,17 +133,17 @@ def test_fillna(self):
         result = self.x.fillna(0)
         assert isinstance(result.data, self.Array)
 
-    @pytest.mark.xfail(reason="ffill is not namespace aware")
+    @pytest.mark.xfail(reason="ffill uses bottleneck or numbagg")
     def test_ffill(self):
         result = self.x.ffill()
         assert isinstance(result.data, self.Array)
 
-    @pytest.mark.xfail(reason="bfill is not namespace aware")
+    @pytest.mark.xfail(reason="bfill uses bottleneck or numbagg")
     def test_bfill(self):
         result = self.x.bfill()
         assert isinstance(result.data, self.Array)
 
-    @pytest.mark.xfail(reason="interpolate_na is not namespace aware")
+    @pytest.mark.xfail(reason="interpolate_na uses numpy and scipy")
     def test_interpolate_na(self):
         result = self.x.interpolate_na()
         assert isinstance(result.data, self.Array)
@@ -165,7 +166,7 @@ def test_rolling(self):
         result = self.x.rolling(x=3).mean()
         assert isinstance(result.data, self.Array)
 
-    @pytest.mark.xfail(reason="rolling_exp is not namespace aware")
+    @pytest.mark.xfail(reason="rolling_exp uses numbagg")
     def test_rolling_exp(self):
         result = self.x.rolling_exp(x=3).mean()
         assert isinstance(result.data, self.Array)
@@ -199,17 +200,18 @@ def test_quantile(self, skipna):
         assert isinstance(result.data, self.Array)
 
     def test_differentiate(self):
-        if self.xp is jnp:
-            pytest.xfail("edge_order kwarg")
-        result = self.x.differentiate("x")
+        # edge_order is not implemented in jax, and only supports passing None
+        edge_order = None if self.xp is jnp else 1
+        result = self.x.differentiate("x", edge_order=edge_order)
         assert isinstance(result.data, self.Array)
 
     def test_integrate(self):
         result = self.x.integrate("x")
         assert isinstance(result.data, self.Array)
 
-    @pytest.mark.xfail(reason="polyfit is not namespace aware")
+    @pytest.mark.xfail(reason="polyfit uses numpy linalg")
     def test_polyfit(self):
+        # TODO: this could work, there are just a lot of different linalg calls
         result = self.x.polyfit("x", 1)
         assert isinstance(result.polyfit_coefficients.data, self.Array)
 
@@ -277,15 +279,11 @@ def test_sum(self, skipna):
 
     @pytest.mark.parametrize("skipna", [True, False])
     def test_std(self, skipna):
-        if self.xp is cp and not skipna:
-            pytest.xfail("ddof/correction kwarg mismatch")
         result = self.x.std(dim="x", skipna=skipna)
         assert isinstance(result.data, self.Array)
 
     @pytest.mark.parametrize("skipna", [True, False])
     def test_var(self, skipna):
-        if self.xp is cp and not skipna:
-            pytest.xfail("ddof/correction kwarg mismatch")
         result = self.x.var(dim="x", skipna=skipna)
         assert isinstance(result.data, self.Array)
 
@@ -335,8 +333,9 @@ def test_T(self):
         result = self.x.T
         assert isinstance(result.data, self.Array)
 
-    @pytest.mark.xfail(reason="rank is not namespace aware")
+    @pytest.mark.xfail(reason="rank uses bottleneck")
     def test_rank(self):
+        # TODO: scipy has rankdata, as does jax, so this can work
         result = self.x.rank()
         assert isinstance(result.data, self.Array)
 

From 205c1995703d0f259cfce907337558c6256c0a43 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Thu, 21 Nov 2024 10:57:26 -0500
Subject: [PATCH 15/24] add support for chunked arrays in as_array_type

---
 xarray/core/dataarray.py       |  2 ++
 xarray/core/dataset.py         |  2 ++
 xarray/namedarray/core.py      | 14 +++++++++++---
 xarray/tests/test_dataarray.py | 19 +++++++++++++++----
 xarray/tests/test_dataset.py   | 24 ++++++++++++++++++++----
 5 files changed, 50 insertions(+), 11 deletions(-)

diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index ead13663cb8..021e9d85474 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -846,6 +846,8 @@ def as_array_type(self, asarray: Callable, **kwargs) -> Self:
         """
         Converts wrapped data into a specific array type.
 
+        If the data is a chunked array, the conversion is applied to each block.
+
         `asarray` should output an object that supports the Array API Standard.
         This method does not convert index coordinates, which can't generally be
         represented as arbitrary array types.
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 32ea1b98308..038d503e682 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -1439,6 +1439,8 @@ def as_array_type(self, asarray: Callable, **kwargs) -> Self:
         """
         Converts wrapped data into a specific array type.
 
+        If the data is a chunked array, the conversion is applied to each block.
+
         `asarray` should output an object that supports the Array API Standard.
         This method does not convert index coordinates, which can't generally be
         represented as arbitrary array types.
diff --git a/xarray/namedarray/core.py b/xarray/namedarray/core.py
index 2558ecec9c7..ab4b3bc1820 100644
--- a/xarray/namedarray/core.py
+++ b/xarray/namedarray/core.py
@@ -40,8 +40,8 @@
     _SupportsImag,
     _SupportsReal,
 )
-from xarray.namedarray.parallelcompat import guess_chunkmanager
-from xarray.namedarray.pycompat import to_numpy
+from xarray.namedarray.parallelcompat import get_chunked_array_type, guess_chunkmanager
+from xarray.namedarray.pycompat import is_chunked_array, to_numpy
 from xarray.namedarray.utils import (
     either_dict_or_kwargs,
     infix_dims,
@@ -867,6 +867,8 @@ def as_array_type(
     ) -> Self:
         """Converts wrapped data into a specific array type.
 
+        If the data is a chunked array, the conversion is applied to each block.
+
         Parameters
         ----------
         asarray : callable
@@ -879,7 +881,13 @@ def as_array_type(
         array : NamedArray
             Array with the same data, but converted into a specific array type
         """
-        return self._replace(data=asarray(self._data, **kwargs))
+        if is_chunked_array(self._data):
+            chunkmanager = get_chunked_array_type(self._data)
+            new_data = chunkmanager.map_blocks(asarray, self._data, **kwargs)
+        else:
+            new_data = asarray(self._data, **kwargs)
+
+        return self._replace(data=new_data)
 
     def is_array_type(self, array_type: type) -> bool:
         """Check if the data is an instance of a specific array type.
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index 8bc63f3bf4b..b4af9d37e35 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -7171,16 +7171,27 @@ def test_as_array_type_is_array_type() -> None:
 
     assert da.is_array_type(np.ndarray)
 
-    def as_duck_array(arr):
-        return DuckArrayWrapper(arr)
-
-    result = da.as_array_type(as_duck_array)
+    result = da.as_array_type(lambda x: DuckArrayWrapper(x))
 
     assert isinstance(result.data, DuckArrayWrapper)
     assert isinstance(result.x.data, np.ndarray)
     assert result.is_array_type(DuckArrayWrapper)
 
 
+@requires_dask
+def test_as_array_type_dask() -> None:
+    import dask.array
+
+    da = xr.DataArray([1, 2, 3], dims=["x"], coords={"x": [4, 5, 6]}).chunk()
+
+    result = da.as_array_type(lambda x: DuckArrayWrapper(x))
+
+    assert isinstance(result.data, dask.array.Array)
+    assert isinstance(result.data._meta, DuckArrayWrapper)
+    assert isinstance(result.x.data, np.ndarray)
+    assert result.is_array_type(dask.array.Array)
+
+
 class TestStackEllipsis:
     # https://github.com/pydata/xarray/issues/6051
     def test_result_as_expected(self) -> None:
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index edca2a02c93..b8dbcabf3ce 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -7646,10 +7646,7 @@ def test_as_array_type_is_array_type() -> None:
     # lat is a PandasIndex here
     assert ds.drop_vars("lat").is_array_type(np.ndarray)
 
-    def as_duck_array(arr):
-        return DuckArrayWrapper(arr)
-
-    result = ds.as_array_type(as_duck_array)
+    result = ds.as_array_type(lambda x: DuckArrayWrapper(x))
 
     assert isinstance(result.a.data, DuckArrayWrapper)
     assert isinstance(result.lat.data, DuckArrayWrapper)
@@ -7657,6 +7654,25 @@ def as_duck_array(arr):
     assert result.is_array_type(DuckArrayWrapper)
 
 
+@requires_dask
+def test_as_array_type_dask() -> None:
+    import dask.array
+
+    ds = xr.Dataset(
+        {"a": ("x", [1, 2, 3])}, coords={"lat": ("x", [4, 5, 6]), "x": [7, 8, 9]}
+    ).chunk()
+
+    assert ds.is_array_type(dask.array.Array)
+
+    result = ds.as_array_type(lambda x: DuckArrayWrapper(x))
+
+    assert isinstance(result.a.data, dask.array.Array)
+    assert isinstance(result.a.data._meta, DuckArrayWrapper)
+    assert isinstance(result.lat.data, dask.array.Array)
+    assert isinstance(result.lat.data._meta, DuckArrayWrapper)
+    assert isinstance(result.x.data, np.ndarray)
+
+
 def test_string_keys_typing() -> None:
     """Tests that string keys to `variables` are permitted by mypy"""
 

From c8d4e5ec713358f05a0def3789b38f778e346ad5 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Fri, 22 Nov 2024 14:19:25 -0500
Subject: [PATCH 16/24] revert array_type methods

---
 doc/api.rst                    |  4 ---
 doc/whats-new.rst              |  5 ++--
 xarray/core/dataarray.py       | 40 ----------------------------
 xarray/core/dataset.py         | 48 ----------------------------------
 xarray/namedarray/core.py      | 47 ++-------------------------------
 xarray/tests/test_dataarray.py | 27 -------------------
 xarray/tests/test_dataset.py   | 34 ------------------------
 7 files changed, 4 insertions(+), 201 deletions(-)

diff --git a/doc/api.rst b/doc/api.rst
index 7a596fdaa2d..85ef46ca6ba 100644
--- a/doc/api.rst
+++ b/doc/api.rst
@@ -117,8 +117,6 @@ Dataset contents
    Dataset.convert_calendar
    Dataset.interp_calendar
    Dataset.get_index
-   Dataset.as_array_type
-   Dataset.is_array_type
 
 Comparisons
 -----------
@@ -317,8 +315,6 @@ DataArray contents
    DataArray.get_index
    DataArray.astype
    DataArray.item
-   DataArray.as_array_type
-   DataArray.is_array_type
 
 Indexing
 --------
diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index 8084cc17780..3801075a310 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -64,9 +64,8 @@ New Features
   underlying array's backend. Provides better support for certain wrapped array types
   like ``jax.numpy.ndarray``. (:issue:`7848`, :pull:`9776`).
   By `Sam Levang <https://github.com/slevang>`_.
-- Make more xarray methods fully compatible with duck array types, and introduce new
-  ``as_array_type`` and ``is_array_type`` methods for converting wrapped data to other
-  duck array types. (:issue:`7848`, :pull:`9798`).
+- Better support wrapping additional array types (e.g. ``cupy`` or ``jax``) by calling generalized
+  duck array operations throughout more xarray methods. (:issue:`7848`, :pull:`9798`).
   By `Sam Levang <https://github.com/slevang>`_.
 
 Breaking changes
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index e45aaac5836..eae11c0c491 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -844,46 +844,6 @@ def as_numpy(self) -> Self:
         coords = {k: v.as_numpy() for k, v in self._coords.items()}
         return self._replace(self.variable.as_numpy(), coords, indexes=self._indexes)
 
-    def as_array_type(self, asarray: Callable, **kwargs) -> Self:
-        """
-        Converts wrapped data into a specific array type.
-
-        If the data is a chunked array, the conversion is applied to each block.
-
-        `asarray` should output an object that supports the Array API Standard.
-        This method does not convert index coordinates, which can't generally be
-        represented as arbitrary array types.
-
-        Parameters
-        ----------
-        asarray : Callable
-            Function that converts an array-like object to the desired array type.
-            For example, `cupy.asarray`, `jax.numpy.asarray`, `sparse.COO.from_numpy`,
-            or any `from_dlpack` method.
-        **kwargs : dict
-            Additional keyword arguments passed to the `asarray` function.
-
-        Returns
-        -------
-        DataArray
-        """
-        return self._replace(self.variable.as_array_type(asarray, **kwargs))
-
-    def is_array_type(self, array_type: type) -> bool:
-        """
-        Check if the wrapped data is of a specific array type.
-
-        Parameters
-        ----------
-        array_type : type
-            The array type to check for.
-
-        Returns
-        -------
-        bool
-        """
-        return self.variable.is_array_type(array_type)
-
     @property
     def _in_memory(self) -> bool:
         return self.variable._in_memory
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index dd2df1c77c1..b305e4b51de 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -1437,54 +1437,6 @@ def as_numpy(self) -> Self:
         numpy_variables = {k: v.as_numpy() for k, v in self.variables.items()}
         return self._replace(variables=numpy_variables)
 
-    def as_array_type(self, asarray: Callable, **kwargs) -> Self:
-        """
-        Converts wrapped data into a specific array type.
-
-        If the data is a chunked array, the conversion is applied to each block.
-
-        `asarray` should output an object that supports the Array API Standard.
-        This method does not convert index coordinates, which can't generally be
-        represented as arbitrary array types.
-
-        Parameters
-        ----------
-        asarray : Callable
-            Function that converts an array-like object to the desired array type.
-            For example, `cupy.asarray`, `jax.numpy.asarray`, `sparse.COO.from_numpy`,
-            or any `from_dlpack` method.
-        **kwargs : dict
-            Additional keyword arguments passed to the `asarray` function.
-
-        Returns
-        -------
-        Dataset
-        """
-        array_variables = {
-            k: v.as_array_type(asarray, **kwargs) if k not in self._indexes else v
-            for k, v in self.variables.items()
-        }
-        return self._replace(variables=array_variables)
-
-    def is_array_type(self, array_type: type) -> bool:
-        """
-        Check if all data variables and non-index coordinates are of a specific array type.
-
-        Parameters
-        ----------
-        array_type : type
-            The array type to check for.
-
-        Returns
-        -------
-        bool
-        """
-        return all(
-            v.is_array_type(array_type)
-            for k, v in self.variables.items()
-            if k not in self._indexes
-        )
-
     def _copy_listed(self, names: Iterable[Hashable]) -> Self:
         """Create a new Dataset with the listed variables from this dataset and
         the all relevant coordinates. Skips all validation.
diff --git a/xarray/namedarray/core.py b/xarray/namedarray/core.py
index ab4b3bc1820..98d96c73e91 100644
--- a/xarray/namedarray/core.py
+++ b/xarray/namedarray/core.py
@@ -40,8 +40,8 @@
     _SupportsImag,
     _SupportsReal,
 )
-from xarray.namedarray.parallelcompat import get_chunked_array_type, guess_chunkmanager
-from xarray.namedarray.pycompat import is_chunked_array, to_numpy
+from xarray.namedarray.parallelcompat import guess_chunkmanager
+from xarray.namedarray.pycompat import to_numpy
 from xarray.namedarray.utils import (
     either_dict_or_kwargs,
     infix_dims,
@@ -860,49 +860,6 @@ def as_numpy(self) -> Self:
         """Coerces wrapped data into a numpy array, returning a Variable."""
         return self._replace(data=self.to_numpy())
 
-    def as_array_type(
-        self,
-        asarray: Callable[[duckarray[Any, _DType_co]], duckarray[Any, _DType_co]],
-        **kwargs: Any,
-    ) -> Self:
-        """Converts wrapped data into a specific array type.
-
-        If the data is a chunked array, the conversion is applied to each block.
-
-        Parameters
-        ----------
-        asarray : callable
-            Function that converts the data into a specific array type.
-        **kwargs : dict
-            Additional keyword arguments passed on to `asarray`.
-
-        Returns
-        -------
-        array : NamedArray
-            Array with the same data, but converted into a specific array type
-        """
-        if is_chunked_array(self._data):
-            chunkmanager = get_chunked_array_type(self._data)
-            new_data = chunkmanager.map_blocks(asarray, self._data, **kwargs)
-        else:
-            new_data = asarray(self._data, **kwargs)
-
-        return self._replace(data=new_data)
-
-    def is_array_type(self, array_type: type) -> bool:
-        """Check if the data is an instance of a specific array type.
-
-        Parameters
-        ----------
-        array_type : type
-            Array type to check against.
-
-        Returns
-        -------
-        is_array_type : bool
-        """
-        return isinstance(self._data, array_type)
-
     def reduce(
         self,
         func: Callable[..., Any],
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index b4af9d37e35..c8b438948de 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -39,7 +39,6 @@
 from xarray.core.utils import is_scalar
 from xarray.testing import _assert_internal_invariants
 from xarray.tests import (
-    DuckArrayWrapper,
     InaccessibleArray,
     ReturnItem,
     assert_allclose,
@@ -7166,32 +7165,6 @@ def test_from_pint_wrapping_dask(self) -> None:
         np.testing.assert_equal(da.to_numpy(), arr)
 
 
-def test_as_array_type_is_array_type() -> None:
-    da = xr.DataArray([1, 2, 3], dims=["x"], coords={"x": [4, 5, 6]})
-
-    assert da.is_array_type(np.ndarray)
-
-    result = da.as_array_type(lambda x: DuckArrayWrapper(x))
-
-    assert isinstance(result.data, DuckArrayWrapper)
-    assert isinstance(result.x.data, np.ndarray)
-    assert result.is_array_type(DuckArrayWrapper)
-
-
-@requires_dask
-def test_as_array_type_dask() -> None:
-    import dask.array
-
-    da = xr.DataArray([1, 2, 3], dims=["x"], coords={"x": [4, 5, 6]}).chunk()
-
-    result = da.as_array_type(lambda x: DuckArrayWrapper(x))
-
-    assert isinstance(result.data, dask.array.Array)
-    assert isinstance(result.data._meta, DuckArrayWrapper)
-    assert isinstance(result.x.data, np.ndarray)
-    assert result.is_array_type(dask.array.Array)
-
-
 class TestStackEllipsis:
     # https://github.com/pydata/xarray/issues/6051
     def test_result_as_expected(self) -> None:
diff --git a/xarray/tests/test_dataset.py b/xarray/tests/test_dataset.py
index b8dbcabf3ce..67d38aac0fe 100644
--- a/xarray/tests/test_dataset.py
+++ b/xarray/tests/test_dataset.py
@@ -7639,40 +7639,6 @@ def test_from_pint_wrapping_dask(self) -> None:
         assert_identical(result, expected)
 
 
-def test_as_array_type_is_array_type() -> None:
-    ds = xr.Dataset(
-        {"a": ("x", [1, 2, 3])}, coords={"lat": ("x", [4, 5, 6]), "x": [7, 8, 9]}
-    )
-    # lat is a PandasIndex here
-    assert ds.drop_vars("lat").is_array_type(np.ndarray)
-
-    result = ds.as_array_type(lambda x: DuckArrayWrapper(x))
-
-    assert isinstance(result.a.data, DuckArrayWrapper)
-    assert isinstance(result.lat.data, DuckArrayWrapper)
-    assert isinstance(result.x.data, np.ndarray)
-    assert result.is_array_type(DuckArrayWrapper)
-
-
-@requires_dask
-def test_as_array_type_dask() -> None:
-    import dask.array
-
-    ds = xr.Dataset(
-        {"a": ("x", [1, 2, 3])}, coords={"lat": ("x", [4, 5, 6]), "x": [7, 8, 9]}
-    ).chunk()
-
-    assert ds.is_array_type(dask.array.Array)
-
-    result = ds.as_array_type(lambda x: DuckArrayWrapper(x))
-
-    assert isinstance(result.a.data, dask.array.Array)
-    assert isinstance(result.a.data._meta, DuckArrayWrapper)
-    assert isinstance(result.lat.data, dask.array.Array)
-    assert isinstance(result.lat.data._meta, DuckArrayWrapper)
-    assert isinstance(result.x.data, np.ndarray)
-
-
 def test_string_keys_typing() -> None:
     """Tests that string keys to `variables` are permitted by mypy"""
 

From f306768fe78d4751e6f264ff992dff09e20453a8 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Fri, 22 Nov 2024 14:20:21 -0500
Subject: [PATCH 17/24] fix up whats new

---
 doc/whats-new.rst | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index ccaac9e7263..e1fb12269ed 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -64,11 +64,11 @@ New Features
   underlying array's backend. Provides better support for certain wrapped array types
   like ``jax.numpy.ndarray``. (:issue:`7848`, :pull:`9776`).
   By `Sam Levang <https://github.com/slevang>`_.
+- Speed up loading of large zarr stores using dask arrays. (:issue:`8902`)
+  By `Deepak Cherian <https://github.com/dcherian>`_.
 - Better support wrapping additional array types (e.g. ``cupy`` or ``jax``) by calling generalized
   duck array operations throughout more xarray methods. (:issue:`7848`, :pull:`9798`).
   By `Sam Levang <https://github.com/slevang>`_.
-- Speed up loading of large zarr stores using dask arrays. (:issue:`8902`)
-  By `Deepak Cherian <https://github.com/dcherian>`_.
 
 Breaking changes
 ~~~~~~~~~~~~~~~~

From 18ebdcdb29bda39395d254be4f7cb3c3f88b6e16 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Fri, 22 Nov 2024 17:22:06 -0500
Subject: [PATCH 18/24] comment about bool_

---
 xarray/core/duck_array_ops.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/xarray/core/duck_array_ops.py b/xarray/core/duck_array_ops.py
index 59f3da2c8f7..7e7333fd8ea 100644
--- a/xarray/core/duck_array_ops.py
+++ b/xarray/core/duck_array_ops.py
@@ -166,6 +166,7 @@ def isnull(data):
         )
     ):
         # these types cannot represent missing values
+        # bool_ is for backwards compat with numpy<2, and cupy
         dtype = xp.bool_ if hasattr(xp, "bool_") else xp.bool
         return full_like(data, dtype=dtype, fill_value=False)
     else:

From 121af9e5b1a12d2759a2f846dd7207afa3100bcb Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Sat, 23 Nov 2024 11:09:25 -0500
Subject: [PATCH 19/24] add jax to complete ci envs

---
 ci/requirements/environment-3.13.yml         | 2 ++
 ci/requirements/environment-windows-3.13.yml | 2 ++
 ci/requirements/environment-windows.yml      | 2 ++
 ci/requirements/environment.yml              | 2 ++
 4 files changed, 8 insertions(+)

diff --git a/ci/requirements/environment-3.13.yml b/ci/requirements/environment-3.13.yml
index dbb446f4454..937cb013711 100644
--- a/ci/requirements/environment-3.13.yml
+++ b/ci/requirements/environment-3.13.yml
@@ -47,3 +47,5 @@ dependencies:
   - toolz
   - typing_extensions
   - zarr
+  - pip:
+      - jax # no way to get cpu-only jaxlib from conda if gpu is present
diff --git a/ci/requirements/environment-windows-3.13.yml b/ci/requirements/environment-windows-3.13.yml
index 448e3f70c0c..0d32fd13a96 100644
--- a/ci/requirements/environment-windows-3.13.yml
+++ b/ci/requirements/environment-windows-3.13.yml
@@ -42,3 +42,5 @@ dependencies:
   - toolz
   - typing_extensions
   - zarr
+  - pip:
+      - jax # no way to get cpu-only jaxlib from conda if gpu is present
diff --git a/ci/requirements/environment-windows.yml b/ci/requirements/environment-windows.yml
index 3b2e6dc62e6..a9a53d0c1b1 100644
--- a/ci/requirements/environment-windows.yml
+++ b/ci/requirements/environment-windows.yml
@@ -42,3 +42,5 @@ dependencies:
   - toolz
   - typing_extensions
   - zarr
+  - pip:
+      - jax # no way to get cpu-only jaxlib from conda if gpu is present
diff --git a/ci/requirements/environment.yml b/ci/requirements/environment.yml
index 43938880592..364ae03666f 100644
--- a/ci/requirements/environment.yml
+++ b/ci/requirements/environment.yml
@@ -49,3 +49,5 @@ dependencies:
   - toolz
   - typing_extensions
   - zarr
+  - pip:
+      - jax # no way to get cpu-only jaxlib from conda if gpu is present

From 472ae7e7e1fc499adc3598511e96475e8d7ab045 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Sat, 23 Nov 2024 11:10:17 -0500
Subject: [PATCH 20/24] add pint and sparse to tests

---
 xarray/core/common.py                    |   3 +-
 xarray/tests/test_duck_array_wrapping.py | 154 +++++++++++++++++------
 2 files changed, 118 insertions(+), 39 deletions(-)

diff --git a/xarray/core/common.py b/xarray/core/common.py
index 8aaa153c1a8..32135996d3c 100644
--- a/xarray/core/common.py
+++ b/xarray/core/common.py
@@ -1760,8 +1760,7 @@ def _full_like_variable(
             **from_array_kwargs,
         )
     else:
-        xp = duck_array_ops.get_array_namespace(other.data)
-        data = xp.full_like(other.data, fill_value, dtype=dtype)
+        data = duck_array_ops.full_like(other.data, fill_value, dtype=dtype)
 
     return Variable(dims=other.dims, data=data, attrs=other.attrs)
 
diff --git a/xarray/tests/test_duck_array_wrapping.py b/xarray/tests/test_duck_array_wrapping.py
index ffaa1440e1a..05c0ab68bea 100644
--- a/xarray/tests/test_duck_array_wrapping.py
+++ b/xarray/tests/test_duck_array_wrapping.py
@@ -4,30 +4,107 @@
 
 import xarray as xr
 
-# TODO: how to test these in CI?
-jnp = pytest.importorskip("jax.numpy")
-cp = pytest.importorskip("cupy")
-
-NAMESPACES = [cp, jnp]
-
-
-def get_test_dataarray(xp):
-    return xr.DataArray(
-        xp.asarray([[1, 2, 3, np.nan, 5]]),
-        dims=["y", "x"],
-        coords={"y": [1], "x": np.arange(5)},
-        name="foo",
-    )
-
-
-@pytest.mark.parametrize("xp", NAMESPACES)
-class TestTopLevelMethods:
+# Don't run cupy in CI because it requires a GPU
+NAMESPACE_ARRAYS = {
+    "jax.numpy": {
+        "array": "ndarray",
+        "constructor": "asarray",
+        "xfails": {
+            "rolling": "no sliding_window_view",
+            "rolling_mean": "no sliding_window_view",
+        },
+    },
+    "cupy": {
+        "array": "ndarray",
+        "constructor": "asarray",
+        "xfails": {"quantile": "no nanquantile"},
+    },
+    "pint": {
+        "array": "Quantity",
+        "constructor": "Quantity",
+        "xfails": {
+            "all": "returns a bool",
+            "any": "returns a bool",
+            "argmax": "returns an int",
+            "argmin": "returns an int",
+            "argsort": "returns an int",
+            "count": "returns an int",
+            "dot": "no tensordot",
+            "full_like": "should work, see: https://github.com/hgrecco/pint/pull/1669",
+            "idxmax": "returns the coordinate",
+            "idxmin": "returns the coordinate",
+            "isin": "returns a bool",
+            "isnull": "returns a bool",
+            "notnull": "returns a bool",
+            "rolling_mean": "no dispatch for numbagg/bottleneck",
+            "searchsorted": "returns an int",
+            "weighted": "no tensordot",
+        },
+    },
+    "sparse": {
+        "array": "COO",
+        "constructor": "COO",
+        "xfails": {
+            "cov": "dense output",
+            "corr": "no nanstd",
+            "cross": "no cross",
+            "count": "dense output",
+            "isin": "no isin",
+            "rolling": "no sliding_window_view",
+            "rolling_mean": "no sliding_window_view",
+            "weighted": "fill_value error",
+            "coarsen": "pad constant_values must be fill_value",
+            "quantile": "no non skipping version",
+            "differentiate": "no gradient",
+            "argmax": "no nan skipping version",
+            "argmin": "no nan skipping version",
+            "idxmax": "no nan skipping version",
+            "idxmin": "no nan skipping version",
+            "median": "no nan skipping version",
+            "std": "no nan skipping version",
+            "var": "no nan skipping version",
+            "cumsum": "no cumsum",
+            "cumprod": "no cumprod",
+            "argsort": "no argsort",
+            "conjugate": "no conjugate",
+            "searchsorted": "no searchsorted",
+            "shift": "pad constant_values must be fill_value",
+            "pad": "pad constant_values must be fill_value",
+        },
+    },
+}
+
+
+class _BaseTest:
+    def setup_for_test(self, request, namespace):
+        self.namespace = namespace
+        self.xp = pytest.importorskip(namespace)
+        self.Array = getattr(self.xp, NAMESPACE_ARRAYS[namespace]["array"])
+        self.constructor = getattr(self.xp, NAMESPACE_ARRAYS[namespace]["constructor"])
+        xarray_method = request.node.name.split("test_")[1].split("[")[0]
+        if xarray_method in NAMESPACE_ARRAYS[namespace]["xfails"]:
+            reason = NAMESPACE_ARRAYS[namespace]["xfails"][xarray_method]
+            pytest.xfail(f"xfail for {self.namespace}: {reason}")
+
+    def get_test_dataarray(self):
+        data = np.asarray([[1, 2, 3, np.nan, 5]])
+        x = np.arange(5)
+        data = self.constructor(data)
+        return xr.DataArray(
+            data,
+            dims=["y", "x"],
+            coords={"y": [1], "x": x},
+            name="foo",
+        )
+
+
+@pytest.mark.parametrize("namespace", NAMESPACE_ARRAYS)
+class TestTopLevelMethods(_BaseTest):
     @pytest.fixture(autouse=True)
-    def setUp(self, xp):
-        self.xp = xp
-        self.Array = xp.ndarray
-        self.x1 = get_test_dataarray(xp)
-        self.x2 = get_test_dataarray(xp).assign_coords(x=np.arange(2, 7))
+    def setUp(self, request, namespace):
+        self.setup_for_test(request, namespace)
+        self.x1 = self.get_test_dataarray()
+        self.x2 = self.get_test_dataarray().assign_coords(x=np.arange(2, 7))
 
     def test_apply_ufunc(self):
         func = lambda x: x + 1
@@ -83,13 +160,12 @@ def test_map_blocks(self):
         assert isinstance(result.data, self.Array)
 
 
-@pytest.mark.parametrize("xp", NAMESPACES)
-class TestDataArrayMethods:
+@pytest.mark.parametrize("namespace", NAMESPACE_ARRAYS)
+class TestDataArrayMethods(_BaseTest):
     @pytest.fixture(autouse=True)
-    def setUp(self, xp):
-        self.xp = xp
-        self.Array = xp.ndarray
-        self.x = get_test_dataarray(xp)
+    def setUp(self, request, namespace):
+        self.setup_for_test(request, namespace)
+        self.x = self.get_test_dataarray()
 
     def test_loc(self):
         result = self.x.loc[{"x": slice(1, 3)}]
@@ -153,7 +229,8 @@ def test_where(self):
         assert isinstance(result.data, self.Array)
 
     def test_isin(self):
-        result = self.x.isin(self.xp.asarray([1]))
+        test_elements = self.constructor(np.asarray([1]))
+        result = self.x.isin(test_elements)
         assert isinstance(result.data, self.Array)
 
     def test_groupby(self):
@@ -161,9 +238,13 @@ def test_groupby(self):
         assert isinstance(result.data, self.Array)
 
     def test_rolling(self):
-        if self.xp is jnp:
-            pytest.xfail("no sliding_window_view in jax")
-        result = self.x.rolling(x=3).mean()
+        result = self.x.rolling(x=3)
+        elem = next(iter(result))[1]
+        assert isinstance(elem.data, self.Array)
+
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_rolling_mean(self, skipna):
+        result = self.x.rolling(x=3).mean(skipna=skipna)
         assert isinstance(result.data, self.Array)
 
     @pytest.mark.xfail(reason="rolling_exp uses numbagg")
@@ -194,14 +275,12 @@ def test_dot(self):
 
     @pytest.mark.parametrize("skipna", [True, False])
     def test_quantile(self, skipna):
-        if self.xp is cp and skipna:
-            pytest.xfail("no nanquantile in cupy")
         result = self.x.quantile(0.5, skipna=skipna)
         assert isinstance(result.data, self.Array)
 
     def test_differentiate(self):
         # edge_order is not implemented in jax, and only supports passing None
-        edge_order = None if self.xp is jnp else 1
+        edge_order = None if self.namespace == "jax.numpy" else 1
         result = self.x.differentiate("x", edge_order=edge_order)
         assert isinstance(result.data, self.Array)
 
@@ -318,7 +397,8 @@ def test_imag(self):
         assert isinstance(result.data, self.Array)
 
     def test_searchsorted(self):
-        result = self.x.squeeze().searchsorted(self.xp.asarray(3))
+        v = self.constructor(np.asarray([3]))
+        result = self.x.squeeze().searchsorted(v)
         assert isinstance(result, self.Array)
 
     def test_round(self):

From 5aa4a392b314544750ce0395395492b02dbddae6 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Sat, 23 Nov 2024 11:19:25 -0500
Subject: [PATCH 21/24] remove from windows

---
 ci/requirements/environment-windows-3.13.yml | 2 --
 ci/requirements/environment-windows.yml      | 2 --
 2 files changed, 4 deletions(-)

diff --git a/ci/requirements/environment-windows-3.13.yml b/ci/requirements/environment-windows-3.13.yml
index 0d32fd13a96..448e3f70c0c 100644
--- a/ci/requirements/environment-windows-3.13.yml
+++ b/ci/requirements/environment-windows-3.13.yml
@@ -42,5 +42,3 @@ dependencies:
   - toolz
   - typing_extensions
   - zarr
-  - pip:
-      - jax # no way to get cpu-only jaxlib from conda if gpu is present
diff --git a/ci/requirements/environment-windows.yml b/ci/requirements/environment-windows.yml
index a9a53d0c1b1..3b2e6dc62e6 100644
--- a/ci/requirements/environment-windows.yml
+++ b/ci/requirements/environment-windows.yml
@@ -42,5 +42,3 @@ dependencies:
   - toolz
   - typing_extensions
   - zarr
-  - pip:
-      - jax # no way to get cpu-only jaxlib from conda if gpu is present

From 390df6f7715b46d557cb64fd32a21e6567e64e21 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Sat, 23 Nov 2024 12:40:31 -0500
Subject: [PATCH 22/24] mypy, xfail one more sparse

---
 xarray/tests/test_duck_array_wrapping.py | 31 ++++++++++++++++--------
 1 file changed, 21 insertions(+), 10 deletions(-)

diff --git a/xarray/tests/test_duck_array_wrapping.py b/xarray/tests/test_duck_array_wrapping.py
index 05c0ab68bea..63413aba1a3 100644
--- a/xarray/tests/test_duck_array_wrapping.py
+++ b/xarray/tests/test_duck_array_wrapping.py
@@ -7,21 +7,27 @@
 # Don't run cupy in CI because it requires a GPU
 NAMESPACE_ARRAYS = {
     "jax.numpy": {
-        "array": "ndarray",
-        "constructor": "asarray",
+        "attrs": {
+            "array": "ndarray",
+            "constructor": "asarray",
+        },
         "xfails": {
             "rolling": "no sliding_window_view",
             "rolling_mean": "no sliding_window_view",
         },
     },
     "cupy": {
-        "array": "ndarray",
-        "constructor": "asarray",
+        "attrs": {
+            "array": "ndarray",
+            "constructor": "asarray",
+        },
         "xfails": {"quantile": "no nanquantile"},
     },
     "pint": {
-        "array": "Quantity",
-        "constructor": "Quantity",
+        "attrs": {
+            "array": "Quantity",
+            "constructor": "Quantity",
+        },
         "xfails": {
             "all": "returns a bool",
             "any": "returns a bool",
@@ -42,13 +48,16 @@
         },
     },
     "sparse": {
-        "array": "COO",
-        "constructor": "COO",
+        "attrs": {
+            "array": "COO",
+            "constructor": "COO",
+        },
         "xfails": {
             "cov": "dense output",
             "corr": "no nanstd",
             "cross": "no cross",
             "count": "dense output",
+            "dot": "fails on some platforms/versions",
             "isin": "no isin",
             "rolling": "no sliding_window_view",
             "rolling_mean": "no sliding_window_view",
@@ -79,8 +88,10 @@ class _BaseTest:
     def setup_for_test(self, request, namespace):
         self.namespace = namespace
         self.xp = pytest.importorskip(namespace)
-        self.Array = getattr(self.xp, NAMESPACE_ARRAYS[namespace]["array"])
-        self.constructor = getattr(self.xp, NAMESPACE_ARRAYS[namespace]["constructor"])
+        self.Array = getattr(self.xp, NAMESPACE_ARRAYS[namespace]["attrs"]["array"])
+        self.constructor = getattr(
+            self.xp, NAMESPACE_ARRAYS[namespace]["attrs"]["constructor"]
+        )
         xarray_method = request.node.name.split("test_")[1].split("[")[0]
         if xarray_method in NAMESPACE_ARRAYS[namespace]["xfails"]:
             reason = NAMESPACE_ARRAYS[namespace]["xfails"][xarray_method]

From f6074d2fa3b9c2d3900cda25c4cb322f2c698bd1 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Mon, 25 Nov 2024 10:01:59 -0500
Subject: [PATCH 23/24] add dask and a few other methods

---
 xarray/tests/test_duck_array_wrapping.py | 73 +++++++++++++++++++-----
 1 file changed, 60 insertions(+), 13 deletions(-)

diff --git a/xarray/tests/test_duck_array_wrapping.py b/xarray/tests/test_duck_array_wrapping.py
index 63413aba1a3..59928dce370 100644
--- a/xarray/tests/test_duck_array_wrapping.py
+++ b/xarray/tests/test_duck_array_wrapping.py
@@ -6,22 +6,35 @@
 
 # Don't run cupy in CI because it requires a GPU
 NAMESPACE_ARRAYS = {
-    "jax.numpy": {
+    "cupy": {
         "attrs": {
             "array": "ndarray",
             "constructor": "asarray",
         },
+        "xfails": {"quantile": "no nanquantile"},
+    },
+    "dask.array": {
+        "attrs": {
+            "array": "Array",
+            "constructor": "from_array",
+        },
         "xfails": {
-            "rolling": "no sliding_window_view",
-            "rolling_mean": "no sliding_window_view",
+            "argsort": "no argsort",
+            "conjugate": "conj but no conjugate",
+            "searchsorted": "dask.array.searchsorted but no Array.searchsorted",
         },
     },
-    "cupy": {
+    "jax.numpy": {
         "attrs": {
             "array": "ndarray",
             "constructor": "asarray",
         },
-        "xfails": {"quantile": "no nanquantile"},
+        "xfails": {
+            "rolling_construct": "no sliding_window_view",
+            "rolling_reduce": "no sliding_window_view",
+            "cumulative_construct": "no sliding_window_view",
+            "cumulative_reduce": "no sliding_window_view",
+        },
     },
     "pint": {
         "attrs": {
@@ -42,7 +55,8 @@
             "isin": "returns a bool",
             "isnull": "returns a bool",
             "notnull": "returns a bool",
-            "rolling_mean": "no dispatch for numbagg/bottleneck",
+            "rolling_reduce": "no dispatch for numbagg/bottleneck",
+            "cumulative_reduce": "no dispatch for numbagg/bottleneck",
             "searchsorted": "returns an int",
             "weighted": "no tensordot",
         },
@@ -59,8 +73,12 @@
             "count": "dense output",
             "dot": "fails on some platforms/versions",
             "isin": "no isin",
-            "rolling": "no sliding_window_view",
-            "rolling_mean": "no sliding_window_view",
+            "rolling_construct": "no sliding_window_view",
+            "rolling_reduce": "no sliding_window_view",
+            "cumulative_construct": "no sliding_window_view",
+            "cumulative_reduce": "no sliding_window_view",
+            "coarsen_construct": "pad constant_values must be fill_value",
+            "coarsen_reduce": "pad constant_values must be fill_value",
             "weighted": "fill_value error",
             "coarsen": "pad constant_values must be fill_value",
             "quantile": "no non skipping version",
@@ -119,7 +137,7 @@ def setUp(self, request, namespace):
 
     def test_apply_ufunc(self):
         func = lambda x: x + 1
-        result = xr.apply_ufunc(func, self.x1)
+        result = xr.apply_ufunc(func, self.x1, dask="parallelized")
         assert isinstance(result.data, self.Array)
 
     def test_align(self):
@@ -248,26 +266,51 @@ def test_groupby(self):
         result = self.x.groupby("x").mean()
         assert isinstance(result.data, self.Array)
 
-    def test_rolling(self):
+    def test_groupby_bins(self):
+        result = self.x.groupby_bins("x", bins=[0, 2, 4, 6]).mean()
+        assert isinstance(result.data, self.Array)
+
+    def test_rolling_iter(self):
         result = self.x.rolling(x=3)
         elem = next(iter(result))[1]
         assert isinstance(elem.data, self.Array)
 
+    def test_rolling_construct(self):
+        result = self.x.rolling(x=3).construct(x="window")
+        assert isinstance(result.data, self.Array)
+
     @pytest.mark.parametrize("skipna", [True, False])
-    def test_rolling_mean(self, skipna):
+    def test_rolling_reduce(self, skipna):
         result = self.x.rolling(x=3).mean(skipna=skipna)
         assert isinstance(result.data, self.Array)
 
     @pytest.mark.xfail(reason="rolling_exp uses numbagg")
-    def test_rolling_exp(self):
+    def test_rolling_exp_reduce(self):
         result = self.x.rolling_exp(x=3).mean()
         assert isinstance(result.data, self.Array)
 
+    def test_cumulative_iter(self):
+        result = self.x.cumulative("x")
+        elem = next(iter(result))[1]
+        assert isinstance(elem.data, self.Array)
+
+    def test_cumulative_construct(self):
+        result = self.x.cumulative("x").construct(x="window")
+        assert isinstance(result.data, self.Array)
+
+    def test_cumulative_reduce(self):
+        result = self.x.cumulative("x").sum()
+        assert isinstance(result.data, self.Array)
+
     def test_weighted(self):
         result = self.x.weighted(self.x.fillna(0)).mean()
         assert isinstance(result.data, self.Array)
 
-    def test_coarsen(self):
+    def test_coarsen_construct(self):
+        result = self.x.coarsen(x=2, boundary="pad").construct(x=["a", "b"])
+        assert isinstance(result.data, self.Array)
+
+    def test_coarsen_reduce(self):
         result = self.x.coarsen(x=2, boundary="pad").mean()
         assert isinstance(result.data, self.Array)
 
@@ -391,6 +434,10 @@ def test_argsort(self):
         result = self.x.argsort()
         assert isinstance(result.data, self.Array)
 
+    def test_astype(self):
+        result = self.x.astype(int)
+        assert isinstance(result.data, self.Array)
+
     def test_clip(self):
         result = self.x.clip(min=2.0, max=4.0)
         assert isinstance(result.data, self.Array)

From bfd6aebbb0cb2f91f86a71a82e7593ae2b9365e3 Mon Sep 17 00:00:00 2001
From: Sam Levang <slevang@salientpredictions.com>
Date: Mon, 25 Nov 2024 10:03:45 -0500
Subject: [PATCH 24/24] move whats new

---
 doc/whats-new.rst | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index ab1cba8d9a6..906fd0a25b2 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -21,6 +21,9 @@ v.2024.11.1 (unreleased)
 
 New Features
 ~~~~~~~~~~~~
+- Better support wrapping additional array types (e.g. ``cupy`` or ``jax``) by calling generalized
+  duck array operations throughout more xarray methods. (:issue:`7848`, :pull:`9798`).
+  By `Sam Levang <https://github.com/slevang>`_.
 
 
 Breaking changes
@@ -85,9 +88,6 @@ New Features
   By `Sam Levang <https://github.com/slevang>`_.
 - Speed up loading of large zarr stores using dask arrays. (:issue:`8902`)
   By `Deepak Cherian <https://github.com/dcherian>`_.
-- Better support wrapping additional array types (e.g. ``cupy`` or ``jax``) by calling generalized
-  duck array operations throughout more xarray methods. (:issue:`7848`, :pull:`9798`).
-  By `Sam Levang <https://github.com/slevang>`_.
 
 Breaking Changes
 ~~~~~~~~~~~~~~~~

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