diff --git a/xarray/coding/times.py b/xarray/coding/times.py
index e66adc0887c..d24a2036dc3 100644
--- a/xarray/coding/times.py
+++ b/xarray/coding/times.py
@@ -28,7 +28,7 @@
from xarray.core.utils import attempt_import, emit_user_level_warning
from xarray.core.variable import Variable
from xarray.namedarray.parallelcompat import T_ChunkedArray, get_chunked_array_type
-from xarray.namedarray.pycompat import is_chunked_array
+from xarray.namedarray.pycompat import is_chunked_array, to_numpy
from xarray.namedarray.utils import is_duck_dask_array
try:
@@ -310,7 +310,7 @@ def _decode_cf_datetime_dtype(
# Dataset.__repr__ when users try to view their lazily decoded array.
values = indexing.ImplicitToExplicitIndexingAdapter(indexing.as_indexable(data))
example_value = np.concatenate(
- [first_n_items(values, 1) or [0], last_item(values) or [0]]
+ [to_numpy(first_n_items(values, 1)), to_numpy(last_item(values))]
)
try:
@@ -516,7 +516,7 @@ def decode_cf_datetime(
--------
cftime.num2date
"""
- num_dates = np.asarray(num_dates)
+ num_dates = to_numpy(num_dates)
flat_num_dates = ravel(num_dates)
if calendar is None:
calendar = "standard"
@@ -643,7 +643,7 @@ def decode_cf_timedelta(
"""Given an array of numeric timedeltas in netCDF format, convert it into a
numpy timedelta64 ["s", "ms", "us", "ns"] array.
"""
- num_timedeltas = np.asarray(num_timedeltas)
+ num_timedeltas = to_numpy(num_timedeltas)
unit = _netcdf_to_numpy_timeunit(units)
with warnings.catch_warnings():
diff --git a/xarray/core/formatting.py b/xarray/core/formatting.py
index a6bacccbeef..993cddf2b57 100644
--- a/xarray/core/formatting.py
+++ b/xarray/core/formatting.py
@@ -18,12 +18,12 @@
from pandas.errors import OutOfBoundsDatetime
from xarray.core.datatree_render import RenderDataTree
-from xarray.core.duck_array_ops import array_all, array_any, array_equiv, astype
+from xarray.core.duck_array_ops import array_all, array_any, array_equiv, astype, ravel
from xarray.core.indexing import MemoryCachedArray
from xarray.core.options import OPTIONS, _get_boolean_with_default
from xarray.core.treenode import group_subtrees
from xarray.core.utils import is_duck_array
-from xarray.namedarray.pycompat import array_type, to_duck_array, to_numpy
+from xarray.namedarray.pycompat import array_type, to_duck_array
if TYPE_CHECKING:
from xarray.core.coordinates import AbstractCoordinates
@@ -94,7 +94,7 @@ def first_n_items(array, n_desired):
# pass Variable._data
if isinstance(array, Variable):
array = array._data
- return np.ravel(to_duck_array(array))[:n_desired]
+ return ravel(to_duck_array(array))[:n_desired]
def last_n_items(array, n_desired):
@@ -118,18 +118,13 @@ def last_n_items(array, n_desired):
# pass Variable._data
if isinstance(array, Variable):
array = array._data
- return np.ravel(to_duck_array(array))[-n_desired:]
+ return ravel(to_duck_array(array))[-n_desired:]
def last_item(array):
- """Returns the last item of an array in a list or an empty list."""
- if array.size == 0:
- # work around for https://github.com/numpy/numpy/issues/5195
- return []
-
+ """Returns the last item of an array."""
indexer = (slice(-1, None),) * array.ndim
- # to_numpy since dask doesn't support tolist
- return np.ravel(to_numpy(array[indexer])).tolist()
+ return ravel(to_duck_array(array[indexer]))
def calc_max_rows_first(max_rows: int) -> int:
diff --git a/xarray/namedarray/pycompat.py b/xarray/namedarray/pycompat.py
index 3ce33d4d8ea..68b6a7853bf 100644
--- a/xarray/namedarray/pycompat.py
+++ b/xarray/namedarray/pycompat.py
@@ -102,6 +102,12 @@ def to_numpy(
from xarray.core.indexing import ExplicitlyIndexed
from xarray.namedarray.parallelcompat import get_chunked_array_type
+ try:
+ # for tests only at the moment
+ return data.to_numpy() # type: ignore[no-any-return,union-attr]
+ except AttributeError:
+ pass
+
if isinstance(data, ExplicitlyIndexed):
data = data.get_duck_array() # type: ignore[no-untyped-call]
@@ -122,7 +128,10 @@ def to_numpy(
def to_duck_array(data: Any, **kwargs: dict[str, Any]) -> duckarray[_ShapeType, _DType]:
- from xarray.core.indexing import ExplicitlyIndexed
+ from xarray.core.indexing import (
+ ExplicitlyIndexed,
+ ImplicitToExplicitIndexingAdapter,
+ )
from xarray.namedarray.parallelcompat import get_chunked_array_type
if is_chunked_array(data):
@@ -130,7 +139,7 @@ def to_duck_array(data: Any, **kwargs: dict[str, Any]) -> duckarray[_ShapeType,
loaded_data, *_ = chunkmanager.compute(data, **kwargs) # type: ignore[var-annotated]
return loaded_data
- if isinstance(data, ExplicitlyIndexed):
+ if isinstance(data, ExplicitlyIndexed | ImplicitToExplicitIndexingAdapter):
return data.get_duck_array() # type: ignore[no-untyped-call, no-any-return]
elif is_duck_array(data):
return data
diff --git a/xarray/tests/arrays.py b/xarray/tests/arrays.py
index 7373b6c75ab..cc4c480c437 100644
--- a/xarray/tests/arrays.py
+++ b/xarray/tests/arrays.py
@@ -51,6 +51,10 @@ def __init__(self, array: np.ndarray):
def __getitem__(self, key):
return type(self)(self.array[key])
+ def to_numpy(self) -> np.ndarray:
+ """Allow explicit conversions to numpy in `to_numpy`, but disallow np.asarray etc."""
+ return self.array
+
def __array__(
self, dtype: np.typing.DTypeLike = None, /, *, copy: bool | None = None
) -> np.ndarray:
@@ -58,6 +62,9 @@ def __array__(
def __array_namespace__(self):
"""Present to satisfy is_duck_array test."""
+ from xarray.tests import namespace
+
+ return namespace
CONCATENATABLEARRAY_HANDLED_ARRAY_FUNCTIONS: dict[str, Callable] = {}
diff --git a/xarray/tests/namespace.py b/xarray/tests/namespace.py
new file mode 100644
index 00000000000..f0cc28f4b57
--- /dev/null
+++ b/xarray/tests/namespace.py
@@ -0,0 +1,5 @@
+from xarray.core import duck_array_ops
+
+
+def reshape(array, shape, **kwargs):
+ return type(array)(duck_array_ops.reshape(array.array, shape=shape, **kwargs))
diff --git a/xarray/tests/test_coding_times.py b/xarray/tests/test_coding_times.py
index e736339da1b..09408e32d08 100644
--- a/xarray/tests/test_coding_times.py
+++ b/xarray/tests/test_coding_times.py
@@ -41,6 +41,7 @@
from xarray.core.utils import is_duck_dask_array
from xarray.testing import assert_equal, assert_identical
from xarray.tests import (
+ DuckArrayWrapper,
FirstElementAccessibleArray,
arm_xfail,
assert_array_equal,
@@ -1935,6 +1936,31 @@ def test_lazy_decode_timedelta_error() -> None:
decoded.load()
+@pytest.mark.parametrize(
+ "calendar",
+ [
+ "standard",
+ pytest.param(
+ "360_day", marks=pytest.mark.skipif(not has_cftime, reason="no cftime")
+ ),
+ ],
+)
+def test_duck_array_decode_times(calendar) -> None:
+ from xarray.core.indexing import LazilyIndexedArray
+
+ days = LazilyIndexedArray(DuckArrayWrapper(np.array([1.0, 2.0, 3.0])))
+ var = Variable(
+ ["time"], days, {"units": "days since 2001-01-01", "calendar": calendar}
+ )
+ decoded = conventions.decode_cf_variable(
+ "foo", var, decode_times=CFDatetimeCoder(use_cftime=None)
+ )
+ if calendar not in _STANDARD_CALENDARS:
+ assert decoded.dtype == np.dtype("O")
+ else:
+ assert decoded.dtype == np.dtype("=M8[ns]")
+
+
@pytest.mark.parametrize("decode_timedelta", [True, False])
@pytest.mark.parametrize("mask_and_scale", [True, False])
def test_decode_timedelta_mask_and_scale(
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