diff --git a/xarray/backends/chunks.py b/xarray/backends/chunks.py
index 64630455e8b..f17f5375976 100644
--- a/xarray/backends/chunks.py
+++ b/xarray/backends/chunks.py
@@ -141,7 +141,7 @@ def build_grid_chunks(
if region is None:
region = slice(0, size)
- region_start = region.start if region.start else 0
+ region_start = region.start or 0
# Generate the zarr chunks inside the region of this dim
chunks_on_region = [chunk_size - (region_start % chunk_size)]
chunks_on_region.extend([chunk_size] * ((size - chunks_on_region[0]) // chunk_size))
@@ -224,7 +224,7 @@ def validate_grid_chunks_alignment(
)
)
- interval_start = interval.start if interval.start else 0
+ interval_start = interval.start or 0
if len(var_chunks) > 1:
# The first border size is the amount of data that needs to be updated on the
@@ -247,7 +247,7 @@ def validate_grid_chunks_alignment(
)
if not allow_partial_chunks:
- region_stop = interval.stop if interval.stop else size
+ region_stop = interval.stop or size
error_on_last_chunk = base_error.format(
var_chunk_pos=len(var_chunks) - 1,
diff --git a/xarray/backends/pydap_.py b/xarray/backends/pydap_.py
index 301ea430c4c..73b719f8260 100644
--- a/xarray/backends/pydap_.py
+++ b/xarray/backends/pydap_.py
@@ -158,11 +158,12 @@ def get_variables(self):
except AttributeError:
from pydap.model import GroupType
- _vars = list(self.ds.keys())
- # check the key is a BaseType or GridType
- for var in _vars:
- if isinstance(self.ds[var], GroupType):
- _vars.remove(var)
+ _vars = [
+ var
+ for var in self.ds.keys()
+ # check the key is not a BaseType or GridType
+ if not isinstance(self.ds[var], GroupType)
+ ]
return FrozenDict((k, self.open_store_variable(self.ds[k])) for k in _vars)
def get_attrs(self):
diff --git a/xarray/backends/zarr.py b/xarray/backends/zarr.py
index 54ff419b2f2..fff07063964 100644
--- a/xarray/backends/zarr.py
+++ b/xarray/backends/zarr.py
@@ -1184,7 +1184,7 @@ def set_variables(
# with chunk boundaries, then no synchronization is required."
# TODO: incorporate synchronizer to allow writes from multiple dask
# threads
- shape = zarr_shape if zarr_shape else v.shape
+ shape = zarr_shape or v.shape
validate_grid_chunks_alignment(
nd_var_chunks=v.chunks,
enc_chunks=encoding["chunks"],
@@ -1545,7 +1545,7 @@ def guess_can_open(
) -> bool:
if isinstance(filename_or_obj, str | os.PathLike):
_, ext = os.path.splitext(filename_or_obj)
- return ext in {".zarr"}
+ return ext == ".zarr"
return False
diff --git a/xarray/coding/times.py b/xarray/coding/times.py
index e6bc8ca59bd..d1cc36558fa 100644
--- a/xarray/coding/times.py
+++ b/xarray/coding/times.py
@@ -246,7 +246,7 @@ def build_pattern(
]
pattern_list = []
for sep, name, sub_pattern in pieces:
- pattern_list.append((sep if sep else "") + named(name, sub_pattern))
+ pattern_list.append((sep or "") + named(name, sub_pattern))
# TODO: allow timezone offsets?
return "^" + trailing_optional(pattern_list) + "$"
diff --git a/xarray/computation/nanops.py b/xarray/computation/nanops.py
index 17c60b6f663..6475ad890a2 100644
--- a/xarray/computation/nanops.py
+++ b/xarray/computation/nanops.py
@@ -112,7 +112,7 @@ def _nanmean_ddof_object(ddof, value, axis=None, dtype=None, **kwargs):
# As dtype inference is impossible for object dtype, we assume float
# https://github.com/dask/dask/issues/3162
if dtype is None and value.dtype.kind == "O":
- dtype = value.dtype if value.dtype.kind in ["cf"] else float
+ dtype = float
data = np.sum(value, axis=axis, dtype=dtype, **kwargs)
data = data / (valid_count - ddof)
diff --git a/xarray/core/accessor_str.py b/xarray/core/accessor_str.py
index 06570ceba3a..0bab92963a5 100644
--- a/xarray/core/accessor_str.py
+++ b/xarray/core/accessor_str.py
@@ -349,7 +349,7 @@ def f(x, iind):
islice = slice(-1, None) if iind == -1 else slice(iind, iind + 1)
item = x[islice]
- return item if item else default
+ return item or default
return self._apply(func=f, func_args=(i,))
diff --git a/xarray/core/common.py b/xarray/core/common.py
index 6181aa6a8c1..a190766b01a 100644
--- a/xarray/core/common.py
+++ b/xarray/core/common.py
@@ -1782,7 +1782,7 @@ def _full_like_variable(
other.shape,
fill_value,
dtype=dtype,
- chunks=chunks if chunks else other.data.chunks,
+ chunks=chunks or other.data.chunks,
**from_array_kwargs,
)
else:
diff --git a/xarray/core/dataarray.py b/xarray/core/dataarray.py
index c13d33872b6..0bfb0b7ab1c 100644
--- a/xarray/core/dataarray.py
+++ b/xarray/core/dataarray.py
@@ -498,7 +498,7 @@ def _replace(
self,
variable: Variable | None = None,
coords=None,
- name: Hashable | None | Default = _default,
+ name: Hashable | Default | None = _default,
attrs=_default,
indexes=None,
) -> Self:
@@ -520,7 +520,7 @@ def _replace(
def _replace_maybe_drop_dims(
self,
variable: Variable,
- name: Hashable | None | Default = _default,
+ name: Hashable | Default | None = _default,
) -> Self:
if self.sizes == variable.sizes:
coords = self._coords.copy()
@@ -581,7 +581,7 @@ def _to_temp_dataset(self) -> Dataset:
return self._to_dataset_whole(name=_THIS_ARRAY, shallow_copy=False)
def _from_temp_dataset(
- self, dataset: Dataset, name: Hashable | None | Default = _default
+ self, dataset: Dataset, name: Hashable | Default | None = _default
) -> Self:
variable = dataset._variables.pop(_THIS_ARRAY)
coords = dataset._variables
@@ -2609,8 +2609,8 @@ def swap_dims(
def expand_dims(
self,
- dim: None | Hashable | Sequence[Hashable] | Mapping[Any, Any] = None,
- axis: None | int | Sequence[int] = None,
+ dim: Hashable | Sequence[Hashable] | Mapping[Any, Any] | None = None,
+ axis: int | Sequence[int] | None = None,
create_index_for_new_dim: bool = True,
**dim_kwargs: Any,
) -> Self:
diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 95e6f516403..d090f3019cf 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -791,9 +791,9 @@ def _replace(
variables: dict[Hashable, Variable] | None = None,
coord_names: set[Hashable] | None = None,
dims: dict[Any, int] | None = None,
- attrs: dict[Hashable, Any] | None | Default = _default,
+ attrs: dict[Hashable, Any] | Default | None = _default,
indexes: dict[Hashable, Index] | None = None,
- encoding: dict | None | Default = _default,
+ encoding: dict | Default | None = _default,
inplace: bool = False,
) -> Self:
"""Fastpath constructor for internal use.
@@ -840,7 +840,7 @@ def _replace_with_new_dims(
self,
variables: dict[Hashable, Variable],
coord_names: set | None = None,
- attrs: dict[Hashable, Any] | None | Default = _default,
+ attrs: dict[Hashable, Any] | Default | None = _default,
indexes: dict[Hashable, Index] | None = None,
inplace: bool = False,
) -> Self:
@@ -855,7 +855,7 @@ def _replace_vars_and_dims(
variables: dict[Hashable, Variable],
coord_names: set | None = None,
dims: dict[Hashable, int] | None = None,
- attrs: dict[Hashable, Any] | None | Default = _default,
+ attrs: dict[Hashable, Any] | Default | None = _default,
inplace: bool = False,
) -> Self:
"""Deprecated version of _replace_with_new_dims().
@@ -4350,8 +4350,8 @@ def swap_dims(
def expand_dims(
self,
- dim: None | Hashable | Sequence[Hashable] | Mapping[Any, Any] = None,
- axis: None | int | Sequence[int] = None,
+ dim: Hashable | Sequence[Hashable] | Mapping[Any, Any] | None = None,
+ axis: int | Sequence[int] | None = None,
create_index_for_new_dim: bool = True,
**dim_kwargs: Any,
) -> Self:
diff --git a/xarray/core/datatree.py b/xarray/core/datatree.py
index 734927fd3d1..81873635dae 100644
--- a/xarray/core/datatree.py
+++ b/xarray/core/datatree.py
@@ -347,9 +347,9 @@ def _replace( # type: ignore[override]
variables: dict[Hashable, Variable] | None = None,
coord_names: set[Hashable] | None = None,
dims: dict[Any, int] | None = None,
- attrs: dict[Hashable, Any] | None | Default = _default,
+ attrs: dict[Hashable, Any] | Default | None = _default,
indexes: dict[Hashable, Index] | None = None,
- encoding: dict | None | Default = _default,
+ encoding: dict | Default | None = _default,
inplace: bool = False,
) -> Dataset:
"""
diff --git a/xarray/core/datatree_mapping.py b/xarray/core/datatree_mapping.py
index 6262c7f19cd..050a412005d 100644
--- a/xarray/core/datatree_mapping.py
+++ b/xarray/core/datatree_mapping.py
@@ -42,7 +42,7 @@ def map_over_datasets(
def map_over_datasets(
- func: Callable[..., Dataset | None | tuple[Dataset | None, ...]],
+ func: Callable[..., Dataset | tuple[Dataset | None, ...] | None],
*args: Any,
kwargs: Mapping[str, Any] | None = None,
) -> DataTree | tuple[DataTree, ...]:
@@ -106,7 +106,7 @@ def map_over_datasets(
# Walk all trees simultaneously, applying func to all nodes that lie in same position in different trees
# We don't know which arguments are DataTrees so we zip all arguments together as iterables
# Store tuples of results in a dict because we don't yet know how many trees we need to rebuild to return
- out_data_objects: dict[str, Dataset | None | tuple[Dataset | None, ...]] = {}
+ out_data_objects: dict[str, Dataset | tuple[Dataset | None, ...] | None] = {}
tree_args = [arg for arg in args if isinstance(arg, DataTree)]
name = result_name(tree_args)
@@ -171,7 +171,7 @@ def add_note(err: BaseException, msg: str) -> None:
def _check_single_set_return_values(path_to_node: str, obj: Any) -> int | None:
"""Check types returned from single evaluation of func, and return number of return values received from func."""
- if isinstance(obj, None | Dataset):
+ if isinstance(obj, Dataset | None):
return None # no need to pack results
if not isinstance(obj, tuple) or not all(
diff --git a/xarray/core/extension_array.py b/xarray/core/extension_array.py
index 7cc9db96d0d..d85f7e66b55 100644
--- a/xarray/core/extension_array.py
+++ b/xarray/core/extension_array.py
@@ -83,7 +83,7 @@ def __extension_duck_array__reshape(
@dataclass(frozen=True)
-class PandasExtensionArray(Generic[T_ExtensionArray], NDArrayMixin):
+class PandasExtensionArray(NDArrayMixin, Generic[T_ExtensionArray]):
"""NEP-18 compliant wrapper for pandas extension arrays.
Parameters
diff --git a/xarray/core/types.py b/xarray/core/types.py
index 01b908cb723..d51ba59120e 100644
--- a/xarray/core/types.py
+++ b/xarray/core/types.py
@@ -214,7 +214,7 @@ def copy(
# FYI in some cases we don't allow `None`, which this doesn't take account of.
# FYI the `str` is for a size string, e.g. "16MB", supported by dask.
-T_ChunkDim: TypeAlias = str | int | Literal["auto"] | None | tuple[int, ...] # noqa: PYI051
+T_ChunkDim: TypeAlias = str | int | Literal["auto"] | tuple[int, ...] | None # noqa: PYI051
T_ChunkDimFreq: TypeAlias = Union["TimeResampler", T_ChunkDim]
T_ChunksFreq: TypeAlias = T_ChunkDim | Mapping[Any, T_ChunkDimFreq]
# We allow the tuple form of this (though arguably we could transition to named dims only)
diff --git a/xarray/core/utils.py b/xarray/core/utils.py
index 9c1e1fd99bf..562706a1ac0 100644
--- a/xarray/core/utils.py
+++ b/xarray/core/utils.py
@@ -897,7 +897,7 @@ def parse_dims_as_tuple(
*,
check_exists: bool = True,
replace_none: Literal[False],
-) -> tuple[Hashable, ...] | None | EllipsisType: ...
+) -> tuple[Hashable, ...] | EllipsisType | None: ...
def parse_dims_as_tuple(
@@ -906,7 +906,7 @@ def parse_dims_as_tuple(
*,
check_exists: bool = True,
replace_none: bool = True,
-) -> tuple[Hashable, ...] | None | EllipsisType:
+) -> tuple[Hashable, ...] | EllipsisType | None:
"""Parse one or more dimensions.
A single dimension must be always a str, multiple dimensions
@@ -958,7 +958,7 @@ def parse_dims_as_set(
*,
check_exists: bool = True,
replace_none: Literal[False],
-) -> set[Hashable] | None | EllipsisType: ...
+) -> set[Hashable] | EllipsisType | None: ...
def parse_dims_as_set(
@@ -967,7 +967,7 @@ def parse_dims_as_set(
*,
check_exists: bool = True,
replace_none: bool = True,
-) -> set[Hashable] | None | EllipsisType:
+) -> set[Hashable] | EllipsisType | None:
"""Like parse_dims_as_tuple, but returning a set instead of a tuple."""
# TODO: Consider removing parse_dims_as_tuple?
if dim is None or dim is ...:
@@ -999,7 +999,7 @@ def parse_ordered_dims(
*,
check_exists: bool = True,
replace_none: Literal[False],
-) -> tuple[Hashable, ...] | None | EllipsisType: ...
+) -> tuple[Hashable, ...] | EllipsisType | None: ...
def parse_ordered_dims(
@@ -1008,7 +1008,7 @@ def parse_ordered_dims(
*,
check_exists: bool = True,
replace_none: bool = True,
-) -> tuple[Hashable, ...] | None | EllipsisType:
+) -> tuple[Hashable, ...] | EllipsisType | None:
"""Parse one or more dimensions.
A single dimension must be always a str, multiple dimensions
@@ -1086,7 +1086,7 @@ def __get__(self, obj: None, cls) -> type[_Accessor]: ...
@overload
def __get__(self, obj: object, cls) -> _Accessor: ...
- def __get__(self, obj: None | object, cls) -> type[_Accessor] | _Accessor:
+ def __get__(self, obj: object | None, cls) -> type[_Accessor] | _Accessor:
if obj is None:
return self._accessor
@@ -1287,7 +1287,7 @@ def attempt_import(module: str) -> ModuleType:
matplotlib="for plotting",
hypothesis="for the `xarray.testing.strategies` submodule",
)
- package_name = module.split(".")[0] # e.g. "zarr" from "zarr.storage"
+ package_name = module.split(".", maxsplit=1)[0] # e.g. "zarr" from "zarr.storage"
install_name = install_mapping.get(package_name, package_name)
reason = package_purpose.get(package_name, "")
try:
diff --git a/xarray/namedarray/_typing.py b/xarray/namedarray/_typing.py
index 2dba06a5d44..342f72e54f1 100644
--- a/xarray/namedarray/_typing.py
+++ b/xarray/namedarray/_typing.py
@@ -78,7 +78,7 @@ def dtype(self) -> _DType_co: ...
_NormalizedChunks = tuple[tuple[int, ...], ...]
# FYI in some cases we don't allow `None`, which this doesn't take account of.
# # FYI the `str` is for a size string, e.g. "16MB", supported by dask.
-T_ChunkDim: TypeAlias = str | int | Literal["auto"] | None | tuple[int, ...] # noqa: PYI051
+T_ChunkDim: TypeAlias = str | int | Literal["auto"] | tuple[int, ...] | None # noqa: PYI051
# We allow the tuple form of this (though arguably we could transition to named dims only)
T_Chunks: TypeAlias = T_ChunkDim | Mapping[Any, T_ChunkDim]
diff --git a/xarray/plot/facetgrid.py b/xarray/plot/facetgrid.py
index 719b1fde619..e4f330ba27e 100644
--- a/xarray/plot/facetgrid.py
+++ b/xarray/plot/facetgrid.py
@@ -796,7 +796,7 @@ def _get_largest_lims(self) -> dict[str, tuple[float, float]]:
# Find the plot with the largest xlim values:
lower, upper = lims_largest[axis]
for ax in self.axs.flat:
- get_lim: None | Callable[[], tuple[float, float]] = getattr(
+ get_lim: Callable[[], tuple[float, float]] | None = getattr(
ax, f"get_{axis}lim", None
)
if get_lim:
@@ -862,15 +862,15 @@ def _set_labels(
for ax in axes:
getattr(ax, f"set_{axis}label")(label, **kwargs)
- def set_xlabels(self, label: None | str = None, **kwargs: Any) -> None:
+ def set_xlabels(self, label: str | None = None, **kwargs: Any) -> None:
"""Label the x axis on the bottom row of the grid."""
self._set_labels("x", self._bottom_axes, label, **kwargs)
- def set_ylabels(self, label: None | str = None, **kwargs: Any) -> None:
+ def set_ylabels(self, label: str | None = None, **kwargs: Any) -> None:
"""Label the y axis on the left column of the grid."""
self._set_labels("y", self._left_axes, label, **kwargs)
- def set_zlabels(self, label: None | str = None, **kwargs: Any) -> None:
+ def set_zlabels(self, label: str | None = None, **kwargs: Any) -> None:
"""Label the z axis."""
self._set_labels("z", self._left_axes, label, **kwargs)
diff --git a/xarray/plot/utils.py b/xarray/plot/utils.py
index dd47df703b5..ec526d55c26 100644
--- a/xarray/plot/utils.py
+++ b/xarray/plot/utils.py
@@ -955,7 +955,7 @@ def _process_cmap_cbar_kwargs(
cmap_kwargs = {
"plot_data": data,
"levels": levels,
- "cmap": colors if colors else cmap,
+ "cmap": colors or cmap,
"filled": func.__name__ != "contour",
}
@@ -1326,7 +1326,7 @@ def _parse_size(
def _parse_size(
data: DataArray | None,
norm: tuple[float | None, float | None, bool] | Normalize | None,
-) -> None | pd.Series:
+) -> pd.Series | None:
import matplotlib as mpl
if data is None:
@@ -1591,7 +1591,7 @@ def ticks(self) -> np.ndarray | None:
>>> _Normalize(a).ticks
array([1, 3, 5])
"""
- val: None | np.ndarray
+ val: np.ndarray | None
if self.data_is_numeric:
val = None
else:
@@ -1650,13 +1650,13 @@ def format(self) -> FuncFormatter:
"""
import matplotlib.pyplot as plt
- def _func(x: Any, pos: None | Any = None):
+ def _func(x: Any, pos: Any | None = None):
return f"{self._lookup_arr([x])[0]}"
return plt.FuncFormatter(_func)
@property
- def func(self) -> Callable[[Any, None | Any], Any]:
+ def func(self) -> Callable[[Any, Any | None], Any]:
"""
Return a lambda function that maps self.values elements back to
the original value as a numpy array. Useful with ax.legend_elements.
@@ -1675,7 +1675,7 @@ def func(self) -> Callable[[Any, None | Any], Any]:
array([0.5, 3. ])
"""
- def _func(x: Any, pos: None | Any = None):
+ def _func(x: Any, pos: Any | None = None):
return self._lookup_arr(x)
return _func
@@ -1684,8 +1684,8 @@ def _func(x: Any, pos: None | Any = None):
def _determine_guide(
hueplt_norm: _Normalize,
sizeplt_norm: _Normalize,
- add_colorbar: None | bool = None,
- add_legend: None | bool = None,
+ add_colorbar: bool | None = None,
+ add_legend: bool | None = None,
plotfunc_name: str | None = None,
) -> tuple[bool, bool]:
if plotfunc_name == "hist":
diff --git a/xarray/structure/chunks.py b/xarray/structure/chunks.py
index 1afe2e6538f..281cfe278f1 100644
--- a/xarray/structure/chunks.py
+++ b/xarray/structure/chunks.py
@@ -138,7 +138,7 @@ def _maybe_chunk(
# by providing chunks as an input to tokenize.
# subtle bugs result otherwise. see GH3350
# we use str() for speed, and use the name for the final array name on the next line
- token2 = tokenize(token if token else var._data, str(chunks))
+ token2 = tokenize(token or var._data, str(chunks))
name2 = f"{name_prefix}{name}-{token2}"
from_array_kwargs = utils.consolidate_dask_from_array_kwargs(
diff --git a/xarray/structure/combine.py b/xarray/structure/combine.py
index 01c14dffee4..63c3e4cc166 100644
--- a/xarray/structure/combine.py
+++ b/xarray/structure/combine.py
@@ -383,7 +383,7 @@ def _nested_combine(
def combine_nested(
datasets: DATASET_HYPERCUBE,
- concat_dim: str | DataArray | None | Sequence[str | DataArray | pd.Index | None],
+ concat_dim: str | DataArray | Sequence[str | DataArray | pd.Index | None] | None,
compat: str = "no_conflicts",
data_vars: str = "all",
coords: str = "different",
diff --git a/xarray/tests/test_dataarray.py b/xarray/tests/test_dataarray.py
index b2b9ae314c4..45c169bb931 100644
--- a/xarray/tests/test_dataarray.py
+++ b/xarray/tests/test_dataarray.py
@@ -2920,7 +2920,7 @@ def test_reduce_keepdims(self) -> None:
expected = DataArray(
orig.data.mean(keepdims=True),
dims=orig.dims,
- coords={k: v for k, v in coords.items() if k in ["c"]},
+ coords={k: v for k, v in coords.items() if k == "c"},
)
assert_equal(actual, expected)
diff --git a/xarray/tests/test_datatree.py b/xarray/tests/test_datatree.py
index f6d9bd76baa..beb11b5dd3d 100644
--- a/xarray/tests/test_datatree.py
+++ b/xarray/tests/test_datatree.py
@@ -2309,7 +2309,7 @@ class TestUFuncs:
@pytest.mark.xfail(reason="__array_ufunc__ not implemented yet")
def test_tree(self, create_test_datatree):
dt = create_test_datatree()
- expected = create_test_datatree(modify=lambda ds: np.sin(ds))
+ expected = create_test_datatree(modify=np.sin)
result_tree = np.sin(dt)
assert_equal(result_tree, expected)
diff --git a/xarray/tests/test_duck_array_ops.py b/xarray/tests/test_duck_array_ops.py
index eaafe2d4536..5928581de30 100644
--- a/xarray/tests/test_duck_array_ops.py
+++ b/xarray/tests/test_duck_array_ops.py
@@ -587,7 +587,7 @@ def test_reduce(dim_num, dtype, dask, func, skipna, aggdim):
if dask and not has_dask:
pytest.skip("requires dask")
- if dask and skipna is False and dtype in [np.bool_]:
+ if dask and skipna is False and dtype == np.bool_:
pytest.skip("dask does not compute object-typed array")
rtol = 1e-04 if dtype == np.float32 else 1e-05
diff --git a/xarray/tests/test_interp.py b/xarray/tests/test_interp.py
index 3d6fbcf025f..7d5a9bf3db4 100644
--- a/xarray/tests/test_interp.py
+++ b/xarray/tests/test_interp.py
@@ -124,7 +124,7 @@ def test_interpolate_1d(method: InterpOptions, dim: str, case: int) -> None:
if not has_scipy:
pytest.skip("scipy is not installed.")
- if not has_dask and case in [1]:
+ if not has_dask and case == 1:
pytest.skip("dask is not installed in the environment.")
da = get_example_data(case)
@@ -433,7 +433,7 @@ def test_interpolate_nd_with_nan() -> None:
"case", [pytest.param(0, id="no_chunk"), pytest.param(1, id="chunk_y")]
)
def test_interpolate_scalar(method: InterpOptions, case: int) -> None:
- if not has_dask and case in [1]:
+ if not has_dask and case == 1:
pytest.skip("dask is not installed in the environment.")
da = get_example_data(case)
@@ -463,7 +463,7 @@ def func(obj, new_x):
"case", [pytest.param(3, id="no_chunk"), pytest.param(4, id="chunked")]
)
def test_interpolate_nd_scalar(method: InterpOptions, case: int) -> None:
- if not has_dask and case in [4]:
+ if not has_dask and case == 4:
pytest.skip("dask is not installed in the environment.")
da = get_example_data(case)
diff --git a/xarray/tests/test_plot.py b/xarray/tests/test_plot.py
index a3c7c71ce63..bfe0b81e4b6 100644
--- a/xarray/tests/test_plot.py
+++ b/xarray/tests/test_plot.py
@@ -235,7 +235,7 @@ def test_1d_x_y_kw(self) -> None:
z = np.arange(10)
da = DataArray(np.cos(z), dims=["z"], coords=[z], name="f")
- xy: list[list[None | str]] = [[None, None], [None, "z"], ["z", None]]
+ xy: list[list[str | None]] = [[None, None], [None, "z"], ["z", None]]
f, axs = plt.subplots(3, 1, squeeze=False)
for aa, (x, y) in enumerate(xy):
diff --git a/xarray/tests/test_rolling.py b/xarray/tests/test_rolling.py
index 3d7f5657567..d93216a3ccc 100644
--- a/xarray/tests/test_rolling.py
+++ b/xarray/tests/test_rolling.py
@@ -341,7 +341,7 @@ def test_ndrolling_reduce(
assert_allclose(actual, expected)
assert actual.sizes == expected.sizes
- if name in ["mean"]:
+ if name == "mean":
# test our reimplementation of nanmean using np.nanmean
expected = getattr(rolling_obj.construct({"time": "tw", "x": "xw"}), name)(
["tw", "xw"]
diff --git a/xarray/tests/test_utils.py b/xarray/tests/test_utils.py
index 9873b271033..0e6bbf29a45 100644
--- a/xarray/tests/test_utils.py
+++ b/xarray/tests/test_utils.py
@@ -300,7 +300,7 @@ def test_parse_dims_set() -> None:
@pytest.mark.parametrize(
"dim", [pytest.param(None, id="None"), pytest.param(..., id="ellipsis")]
)
-def test_parse_dims_replace_none(dim: None | EllipsisType) -> None:
+def test_parse_dims_replace_none(dim: EllipsisType | None) -> None:
all_dims = ("a", "b", 1, ("b", "c")) # selection of different Hashables
actual = utils.parse_dims_as_tuple(dim, all_dims, replace_none=True)
assert actual == all_dims
diff --git a/xarray/tutorial.py b/xarray/tutorial.py
index ec832694a99..70e7fc68f7e 100644
--- a/xarray/tutorial.py
+++ b/xarray/tutorial.py
@@ -85,7 +85,7 @@ def _check_netcdf_engine_installed(name):
def open_dataset(
name: str,
cache: bool = True,
- cache_dir: None | str | os.PathLike = None,
+ cache_dir: str | os.PathLike | None = None,
*,
engine: T_Engine = None,
**kws,
@@ -216,7 +216,7 @@ def load_dataset(*args, **kwargs) -> Dataset:
return ds.load()
-def scatter_example_dataset(*, seed: None | int = None) -> Dataset:
+def scatter_example_dataset(*, seed: int | None = None) -> Dataset:
"""
Create an example dataset.
@@ -255,7 +255,7 @@ def scatter_example_dataset(*, seed: None | int = None) -> Dataset:
def open_datatree(
name: str,
cache: bool = True,
- cache_dir: None | str | os.PathLike = None,
+ cache_dir: str | os.PathLike | None = None,
*,
engine: T_Engine = None,
**kws,
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