use python>=3.10 typing conventions (#968)

* use python>=3.10 typing conventions

* fix tests

Author: quentinblampey

benchmarks/utils.py

@@ -24,7 +24,7 @@
 from collections.abc import Sequence
 from functools import lru_cache
 from types import ModuleType
-from typing import Callable, Literal, Optional, Union, overload
+from typing import Callable, Literal, overload
 
 import anndata as ad
 import numpy as np
@@ -98,7 +98,7 @@ def _structure_at_coordinates(
     *,
     multipliers: Sequence = itertools.repeat(1),
     dtype=None,
-    reduce_fn: Callable[[np.ndarray, np.ndarray, Optional[np.ndarray]], np.ndarray],
+    reduce_fn: Callable[[np.ndarray, np.ndarray, np.ndarray | None], np.ndarray],
 ):
     """Update data with structure at given coordinates.
 
@@ -165,42 +165,42 @@ def _smallest_dtype(n: int) -> np.dtype:
 @overload
 def labeled_particles(
     shape: Sequence[int],
-    dtype: Optional[np.dtype] = None,
+    dtype: np.dtype | None = None,
     n: int = 144,
-    seed: Optional[int] = None,
+    seed: int | None = None,
     return_density: Literal[False] = False,
 ) -> np.ndarray: ...
 
 
 @overload
 def labeled_particles(
     shape: Sequence[int],
-    dtype: Optional[np.dtype] = None,
+    dtype: np.dtype | None = None,
     n: int = 144,
-    seed: Optional[int] = None,
+    seed: int | None = None,
     return_density: Literal[True] = True,
 ) -> tuple[np.ndarray, np.ndarray, np.ndarray]: ...
 
 
 @lru_cache
 def labeled_particles(
     shape: Sequence[int],
-    dtype: Optional[np.dtype] = None,
+    dtype: np.dtype | None = None,
     n: int = 144,
-    seed: Optional[int] = None,
+    seed: int | None = None,
     return_density: bool = False,
-) -> Union[np.ndarray, tuple[np.ndarray, np.ndarray, np.ndarray]]:
+) -> np.ndarray | tuple[np.ndarray, np.ndarray, np.ndarray]:
     """Generate labeled blobs of given shape and dtype.
 
     Parameters
     ----------
     shape : Sequence[int]
         Shape of the resulting array.
-    dtype : Optional[np.dtype]
+    dtype : np.dtype | None
         Dtype of the resulting array.
     n : int
         Number of blobs to generate.
-    seed : Optional[int]
+    seed : int | None
         Seed for the random number generator.
     return_density : bool
         Whether to return the density array and center coordinates.

docs/design_doc.md

@@ -268,7 +268,7 @@ In `spatialdata-io` we use a consistent naming scheme for the `region_key` and `
 ### Summary
 
 - Image `type: Image`
-- Regions `type: Union[Labels, Shapes]`
+- Regions `type: Labels | Shapes`
     - Labels `type: Labels`
     - Shapes `type: Shapes`
 - Points `type: Points`

src/spatialdata/__init__.py

@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 import dask
 
 dask.config.set({"dataframe.query-planning": False})

src/spatialdata/_core/_deepcopy.py

@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 from copy import deepcopy as _deepcopy
 from functools import singledispatch
 

src/spatialdata/_core/_elements.py

@@ -1,7 +1,5 @@
 """SpatialData elements."""
 
-from __future__ import annotations
-
 from collections import UserDict
 from collections.abc import Iterable, KeysView, ValuesView
 from typing import TypeVar

src/spatialdata/_core/_utils.py

@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 from collections.abc import Iterable
 
 from anndata import AnnData

src/spatialdata/_core/centroids.py

@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 from collections import defaultdict
 from functools import singledispatch
 

src/spatialdata/_core/concatenate.py

@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 from collections import defaultdict
 from collections.abc import Callable, Iterable
 from copy import copy  # Should probably go up at the top

src/spatialdata/_core/data_extent.py

@@ -1,9 +1,6 @@
-from __future__ import annotations
-
 # Functions to compute the bounding box describing the extent of a SpatialElement or SpatialData object
 from collections import defaultdict
 from functools import singledispatch
-from typing import Union
 
 import numpy as np
 import pandas as pd
@@ -107,9 +104,7 @@ def get_extent(
     has_labels: bool = True,
     has_points: bool = True,
     has_shapes: bool = True,
-    elements: Union[  # noqa: UP007 # https://github.com/scverse/spatialdata/pull/318#issuecomment-1755714287
-        list[str], None
-    ] = None,
+    elements: list[str] | None = None,  # noqa: UP007 # https://github.com/scverse/spatialdata/pull/318#issuecomment-1755714287
 ) -> BoundingBoxDescription:
     """
     Get the extent (bounding box) of a SpatialData object or a SpatialElement.
@@ -178,9 +173,7 @@ def _(
     has_labels: bool = True,
     has_points: bool = True,
     has_shapes: bool = True,
-    # python 3.9 tests fail if we don't use Union here, see
-    # https://github.com/scverse/spatialdata/pull/318#issuecomment-1755714287
-    elements: Union[list[str], None] = None,  # noqa: UP007
+    elements: list[str] | None = None,
 ) -> BoundingBoxDescription:
     """
     Get the extent (bounding box) of a SpatialData object.

src/spatialdata/_core/operations/aggregate.py

@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 import warnings
 from typing import Any
 
@@ -21,14 +19,7 @@
 from spatialdata._core.query.relational_query import get_values
 from spatialdata._core.spatialdata import SpatialData
 from spatialdata._types import ArrayLike
-from spatialdata.models import (
-    Image2DModel,
-    Labels2DModel,
-    PointsModel,
-    ShapesModel,
-    TableModel,
-    get_model,
-)
+from spatialdata.models import Image2DModel, Labels2DModel, PointsModel, ShapesModel, TableModel, get_model
 from spatialdata.transformations import BaseTransformation, Identity, get_transformation
 
 __all__ = ["aggregate"]