diff --git a/pyproject.toml b/pyproject.toml
index 01281a9ce72..90a2b8505f2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -254,6 +254,7 @@ extend-select = [
"ISC", # flake8-implicit-str-concat
"PIE", # flake8-pie
"TID", # flake8-tidy-imports (absolute imports)
+ "PYI", # flake8-pyi
"I", # isort
"PERF", # Perflint
"W", # pycodestyle warnings
@@ -268,6 +269,8 @@ extend-safe-fixes = [
ignore = [
"C40", # unnecessary generator, comprehension, or literal
"PIE790", # unnecessary pass statement
+ "PYI019", # use `Self` instead of custom TypeVar
+ "PYI041", # use `float` instead of `int | float`
"PERF203", # try-except within a loop incurs performance overhead
"E402", # module level import not at top of file
"E731", # do not assign a lambda expression, use a def
@@ -283,6 +286,9 @@ ignore = [
[tool.ruff.lint.per-file-ignores]
# don't enforce absolute imports
"asv_bench/**" = ["TID252"]
+# looks like ruff bugs
+"xarray/core/_typed_ops.py" = ["PYI034"]
+"xarray/namedarray/_typing.py" = ["PYI018", "PYI046"]
[tool.ruff.lint.isort]
known-first-party = ["xarray"]
diff --git a/xarray/backends/api.py b/xarray/backends/api.py
index f30f4e54705..cf6d8e525e5 100644
--- a/xarray/backends/api.py
+++ b/xarray/backends/api.py
@@ -71,7 +71,7 @@
T_NetcdfEngine = Literal["netcdf4", "scipy", "h5netcdf"]
T_Engine = Union[
T_NetcdfEngine,
- Literal["pydap", "zarr"],
+ Literal["pydap", "zarr"], # noqa: PYI051
type[BackendEntrypoint],
str, # no nice typing support for custom backends
None,
@@ -710,8 +710,8 @@ def open_dataset(
def open_dataarray(
filename_or_obj: str | os.PathLike[Any] | ReadBuffer | AbstractDataStore,
*,
- engine: T_Engine | None = None,
- chunks: T_Chunks | None = None,
+ engine: T_Engine = None,
+ chunks: T_Chunks = None,
cache: bool | None = None,
decode_cf: bool | None = None,
mask_and_scale: bool | None = None,
@@ -1394,7 +1394,7 @@ def open_mfdataset(
| os.PathLike
| ReadBuffer
| NestedSequence[str | os.PathLike | ReadBuffer],
- chunks: T_Chunks | None = None,
+ chunks: T_Chunks = None,
concat_dim: (
str
| DataArray
@@ -1406,7 +1406,7 @@ def open_mfdataset(
) = None,
compat: CompatOptions = "no_conflicts",
preprocess: Callable[[Dataset], Dataset] | None = None,
- engine: T_Engine | None = None,
+ engine: T_Engine = None,
data_vars: Literal["all", "minimal", "different"] | list[str] = "all",
coords="different",
combine: Literal["by_coords", "nested"] = "by_coords",
diff --git a/xarray/computation/apply_ufunc.py b/xarray/computation/apply_ufunc.py
index 41f4adb5fd5..1d7ceefb859 100644
--- a/xarray/computation/apply_ufunc.py
+++ b/xarray/computation/apply_ufunc.py
@@ -16,16 +16,14 @@
Iterator,
Mapping,
Sequence,
- Set,
)
-from typing import TYPE_CHECKING, Any, Literal, TypeVar, Union
+from collections.abc import (
+ Set as AbstractSet,
+)
+from typing import TYPE_CHECKING, Any, Literal
import numpy as np
-_T = TypeVar("_T", bound=Union["Dataset", "DataArray"])
-_U = TypeVar("_U", bound=Union["Dataset", "DataArray"])
-_V = TypeVar("_V", bound=Union["Dataset", "DataArray"])
-
from xarray.core import duck_array_ops, utils
from xarray.core.formatting import limit_lines
from xarray.core.indexes import Index, filter_indexes_from_coords
@@ -200,7 +198,7 @@ def _get_coords_list(args: Iterable[Any]) -> list[Coordinates]:
def build_output_coords_and_indexes(
args: Iterable[Any],
signature: _UFuncSignature,
- exclude_dims: Set = frozenset(),
+ exclude_dims: AbstractSet = frozenset(),
combine_attrs: CombineAttrsOptions = "override",
) -> tuple[list[dict[Any, Variable]], list[dict[Any, Index]]]:
"""Build output coordinates and indexes for an operation.
@@ -616,7 +614,7 @@ def apply_groupby_func(func, *args):
def unified_dim_sizes(
- variables: Iterable[Variable], exclude_dims: Set = frozenset()
+ variables: Iterable[Variable], exclude_dims: AbstractSet = frozenset()
) -> dict[Hashable, int]:
dim_sizes: dict[Hashable, int] = {}
@@ -896,7 +894,7 @@ def apply_ufunc(
*args: Any,
input_core_dims: Sequence[Sequence] | None = None,
output_core_dims: Sequence[Sequence] | None = ((),),
- exclude_dims: Set = frozenset(),
+ exclude_dims: AbstractSet = frozenset(),
vectorize: bool = False,
join: JoinOptions = "exact",
dataset_join: str = "exact",
diff --git a/xarray/core/accessor_dt.py b/xarray/core/accessor_dt.py
index 72b9710372f..0a5f34a3c46 100644
--- a/xarray/core/accessor_dt.py
+++ b/xarray/core/accessor_dt.py
@@ -5,6 +5,7 @@
import numpy as np
import pandas as pd
+from typing_extensions import Self
from xarray.coding.calendar_ops import _decimal_year
from xarray.coding.times import infer_calendar_name
@@ -650,7 +651,7 @@ def total_seconds(self) -> T_DataArray:
class CombinedDatetimelikeAccessor(
DatetimeAccessor[T_DataArray], TimedeltaAccessor[T_DataArray]
):
- def __new__(cls, obj: T_DataArray) -> CombinedDatetimelikeAccessor:
+ def __new__(cls, obj: T_DataArray) -> Self:
# CombinedDatetimelikeAccessor isn't really instantiated. Instead
# we need to choose which parent (datetime or timedelta) is
# appropriate. Since we're checking the dtypes anyway, we'll just
diff --git a/xarray/core/datatree_render.py b/xarray/core/datatree_render.py
index f1042d9eeef..b88b4d7162e 100644
--- a/xarray/core/datatree_render.py
+++ b/xarray/core/datatree_render.py
@@ -8,15 +8,18 @@
from __future__ import annotations
-from collections import namedtuple
from collections.abc import Iterable, Iterator
from math import ceil
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, NamedTuple
if TYPE_CHECKING:
from xarray.core.datatree import DataTree
-Row = namedtuple("Row", ("pre", "fill", "node"))
+
+class Row(NamedTuple):
+ pre: str
+ fill: str
+ node: DataTree | str
class AbstractStyle:
diff --git a/xarray/core/indexes.py b/xarray/core/indexes.py
index b9abf4fef2d..70c950a858a 100644
--- a/xarray/core/indexes.py
+++ b/xarray/core/indexes.py
@@ -1657,7 +1657,7 @@ class Indexes(collections.abc.Mapping, Generic[T_PandasOrXarrayIndex]):
"""
- _index_type: type[Index] | type[pd.Index]
+ _index_type: type[Index | pd.Index]
_indexes: dict[Any, T_PandasOrXarrayIndex]
_variables: dict[Any, Variable]
@@ -1675,7 +1675,7 @@ def __init__(
self,
indexes: Mapping[Any, T_PandasOrXarrayIndex] | None = None,
variables: Mapping[Any, Variable] | None = None,
- index_type: type[Index] | type[pd.Index] = Index,
+ index_type: type[Index | pd.Index] = Index,
):
"""Constructor not for public consumption.
diff --git a/xarray/core/types.py b/xarray/core/types.py
index 5c7c8eaafd0..1e5ae9aa342 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, ...]
+T_ChunkDim: TypeAlias = str | int | Literal["auto"] | None | tuple[int, ...] # 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)
@@ -329,7 +329,7 @@ def mode(self) -> str:
# for _get_filepath_or_buffer
...
- def seek(self, __offset: int, __whence: int = ...) -> int:
+ def seek(self, offset: int, whence: int = ..., /) -> int:
# with one argument: gzip.GzipFile, bz2.BZ2File
# with two arguments: zip.ZipFile, read_sas
...
@@ -345,7 +345,7 @@ def tell(self) -> int:
@runtime_checkable
class ReadBuffer(BaseBuffer, Protocol[AnyStr_co]):
- def read(self, __n: int = ...) -> AnyStr_co:
+ def read(self, n: int = ..., /) -> AnyStr_co:
# for BytesIOWrapper, gzip.GzipFile, bz2.BZ2File
...
diff --git a/xarray/core/utils.py b/xarray/core/utils.py
index 7ede0bb9f08..c792e4ce60f 100644
--- a/xarray/core/utils.py
+++ b/xarray/core/utils.py
@@ -61,9 +61,11 @@
MutableMapping,
MutableSet,
Sequence,
- Set,
ValuesView,
)
+from collections.abc import (
+ Set as AbstractSet,
+)
from enum import Enum
from pathlib import Path
from types import EllipsisType, ModuleType
@@ -1055,7 +1057,7 @@ def parse_ordered_dims(
)
-def _check_dims(dim: Set[Hashable], all_dims: Set[Hashable]) -> None:
+def _check_dims(dim: AbstractSet[Hashable], all_dims: AbstractSet[Hashable]) -> None:
wrong_dims = (dim - all_dims) - {...}
if wrong_dims:
wrong_dims_str = ", ".join(f"'{d}'" for d in wrong_dims)
diff --git a/xarray/groupers.py b/xarray/groupers.py
index 0ae8e3c87cd..46dc47582a3 100644
--- a/xarray/groupers.py
+++ b/xarray/groupers.py
@@ -902,7 +902,7 @@ def factorize(self, group: T_Group) -> EncodedGroups:
first_items = agged["first"]
counts = agged["count"]
- index_class: type[CFTimeIndex] | type[pd.DatetimeIndex]
+ index_class: type[CFTimeIndex | pd.DatetimeIndex]
if _contains_cftime_datetimes(group.data):
index_class = CFTimeIndex
datetime_class = type(first_n_items(group.data, 1).item())
diff --git a/xarray/namedarray/_typing.py b/xarray/namedarray/_typing.py
index 95e7d7adfc3..2dba06a5d44 100644
--- a/xarray/namedarray/_typing.py
+++ b/xarray/namedarray/_typing.py
@@ -39,7 +39,6 @@ class Default(Enum):
_default = Default.token
# https://stackoverflow.com/questions/74633074/how-to-type-hint-a-generic-numpy-array
-_T = TypeVar("_T")
_T_co = TypeVar("_T_co", covariant=True)
_dtype = np.dtype
@@ -79,7 +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, ...]
+T_ChunkDim: TypeAlias = str | int | Literal["auto"] | None | tuple[int, ...] # 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/namedarray/dtypes.py b/xarray/namedarray/dtypes.py
index a29fbdfd41c..a49f7686179 100644
--- a/xarray/namedarray/dtypes.py
+++ b/xarray/namedarray/dtypes.py
@@ -13,19 +13,19 @@
@functools.total_ordering
class AlwaysGreaterThan:
- def __gt__(self, other: Any) -> Literal[True]:
+ def __gt__(self, other: object) -> Literal[True]:
return True
- def __eq__(self, other: Any) -> bool:
+ def __eq__(self, other: object) -> bool:
return isinstance(other, type(self))
@functools.total_ordering
class AlwaysLessThan:
- def __lt__(self, other: Any) -> Literal[True]:
+ def __lt__(self, other: object) -> Literal[True]:
return True
- def __eq__(self, other: Any) -> bool:
+ def __eq__(self, other: object) -> bool:
return isinstance(other, type(self))
diff --git a/xarray/structure/chunks.py b/xarray/structure/chunks.py
index 2c993137996..e6dcd7b8b83 100644
--- a/xarray/structure/chunks.py
+++ b/xarray/structure/chunks.py
@@ -167,15 +167,15 @@ def _maybe_chunk(
@overload
-def unify_chunks(__obj: _T) -> tuple[_T]: ...
+def unify_chunks(obj: _T, /) -> tuple[_T]: ...
@overload
-def unify_chunks(__obj1: _T, __obj2: _U) -> tuple[_T, _U]: ...
+def unify_chunks(obj1: _T, obj2: _U, /) -> tuple[_T, _U]: ...
@overload
-def unify_chunks(__obj1: _T, __obj2: _U, __obj3: _V) -> tuple[_T, _U, _V]: ...
+def unify_chunks(obj1: _T, obj2: _U, obj3: _V, /) -> tuple[_T, _U, _V]: ...
@overload
diff --git a/xarray/structure/merge.py b/xarray/structure/merge.py
index ca1e5ccb2bb..b2a459ba652 100644
--- a/xarray/structure/merge.py
+++ b/xarray/structure/merge.py
@@ -1,7 +1,8 @@
from __future__ import annotations
from collections import defaultdict
-from collections.abc import Hashable, Iterable, Mapping, Sequence, Set
+from collections.abc import Hashable, Iterable, Mapping, Sequence
+from collections.abc import Set as AbstractSet
from typing import TYPE_CHECKING, Any, NamedTuple, Union
import pandas as pd
@@ -396,7 +397,7 @@ def collect_from_coordinates(
def merge_coordinates_without_align(
objects: list[Coordinates],
prioritized: Mapping[Any, MergeElement] | None = None,
- exclude_dims: Set = frozenset(),
+ exclude_dims: AbstractSet = frozenset(),
combine_attrs: CombineAttrsOptions = "override",
) -> tuple[dict[Hashable, Variable], dict[Hashable, Index]]:
"""Merge variables/indexes from coordinates without automatic alignments.
diff --git a/xarray/tests/test_backends.py b/xarray/tests/test_backends.py
index 6a14142a7ff..9a6c2248233 100644
--- a/xarray/tests/test_backends.py
+++ b/xarray/tests/test_backends.py
@@ -6215,9 +6215,7 @@ def test_h5netcdf_entrypoint(tmp_path: Path) -> None:
@requires_netCDF4
@pytest.mark.parametrize("str_type", (str, np.str_))
-def test_write_file_from_np_str(
- str_type: type[str] | type[np.str_], tmpdir: str
-) -> None:
+def test_write_file_from_np_str(str_type: type[str | np.str_], tmpdir: str) -> None:
# https://github.com/pydata/xarray/pull/5264
scenarios = [str_type(v) for v in ["scenario_a", "scenario_b", "scenario_c"]]
years = range(2015, 2100 + 1)
diff --git a/xarray/util/generate_aggregations.py b/xarray/util/generate_aggregations.py
index 089ef558581..8812a1abb22 100644
--- a/xarray/util/generate_aggregations.py
+++ b/xarray/util/generate_aggregations.py
@@ -13,9 +13,9 @@
"""
-import collections
import textwrap
from dataclasses import dataclass, field
+from typing import NamedTuple
MODULE_PREAMBLE = '''\
"""Mixin classes with reduction operations."""
@@ -227,7 +227,14 @@ def {method}(
and better supported. ``cumsum`` and ``cumprod`` may be deprecated
in the future."""
-ExtraKwarg = collections.namedtuple("ExtraKwarg", "docs kwarg call example")
+
+class ExtraKwarg(NamedTuple):
+ docs: str
+ kwarg: str
+ call: str
+ example: str
+
+
skipna = ExtraKwarg(
docs=_SKIPNA_DOCSTRING,
kwarg="skipna: bool | None = None,",
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