chore: python 3.15

.github/workflows/ci-gpu.yml

@@ -9,6 +9,10 @@ on:
       - opened
       - synchronize
 
+defaults:
+  run:
+    shell: bash
+
 env:
   PYTEST_ADDOPTS: "-v --color=yes"
   FORCE_COLOR: "1"
@@ -35,9 +39,6 @@ jobs:
       pull-requests: write  # for removing the label
     runs-on: "cirun-aws-gpu--${{ github.run_id }}"
     timeout-minutes: 30
-    defaults:
-      run:
-        shell: bash -el {0}
     steps:
       - uses: actions/checkout@v7
         with:
@@ -46,7 +47,7 @@ jobs:
         run: nvidia-smi
       - uses: actions/setup-python@v7.0.0
         with:
-          python-version: "3.12"
+          python-version: "3.13"
       - uses: astral-sh/setup-uv@v10.2.0
         with:
           enable-cache: true  # "auto" is `false` on non-GitHub runners

.github/workflows/ci.yml

@@ -7,6 +7,10 @@ on:
     branches: [main]
   pull_request:
 
+defaults:
+  run:
+    shell: bash
+
 env:
   PYTEST_ADDOPTS: "-v --color=yes"
   FORCE_COLOR: "1"
@@ -17,6 +21,7 @@ jobs:
     outputs:
       envs: ${{ steps.get-envs.outputs.envs }}
       pythons: ${{ steps.get-pythons.outputs.pythons }}
+      latest-full: ${{ steps.get-pythons.outputs.latest-full }}
     steps:
       - uses: actions/checkout@v7
         with: { fetch-depth: 0, filter: "blob:none" }
@@ -36,6 +41,8 @@ jobs:
         run: |
           PYTHONS_JSON=$(echo "$ENVS_JSON" | jq -c 'map(.python) | unique')
           echo "pythons=$PYTHONS_JSON" | tee $GITHUB_OUTPUT
+          LATEST_FULL_JSON=$(echo "$ENVS_JSON" | jq -c 'map(select(.name | endswith("-full"))) | max_by(.python | split(".") | map(tonumber))')
+          echo "latest-full=$LATEST_FULL_JSON" | tee -a $GITHUB_OUTPUT
   test:
     name: Tests
     needs: get-environments
@@ -47,9 +54,7 @@ jobs:
         env: ${{ fromJSON(needs.get-environments.outputs.envs) }}
         os: [ubuntu-latest]
         include:
-          - env:
-              name: hatch-test.py3.14-full
-              python: "3.14"
+          - env: ${{ fromJSON(needs.get-environments.outputs.latest-full) }}
             os: macos-latest
     steps:
       - uses: actions/checkout@v7

.github/workflows/publish.yml

@@ -4,6 +4,10 @@ on:
   release:
     types: [published]
 
+defaults:
+  run:
+    shell: bash
+
 jobs:
   publish:
     runs-on: ubuntu-latest

.gitignore

@@ -15,3 +15,4 @@ _version.py
 
 # IDEs
 /.idea/
+/ci/min-constraints.txt

.vscode/settings.json

@@ -1,10 +1,7 @@
 {
-    "[toml][json][jsonc][python]": {
+    "[json][jsonc][python]": {
         "editor.formatOnSave": true,
     },
-    "[toml]": {
-        "editor.defaultFormatter": "tamasfe.even-better-toml",
-    },
     "[json][jsonc]": {
         "editor.defaultFormatter": "biomejs.biome",
     },

ci/h5py-nightly.txt

@@ -0,0 +1 @@
+h5py>=3.17.0.dev0

ci/min-constraints.py

@@ -0,0 +1,14 @@
+# SPDX-License-Identifier: MPL-2.0
+"""Pin every `>=` lower bound of the dependencies and extras (not test deps) to `==`."""
+
+from __future__ import annotations
+
+import tomllib
+from pathlib import Path
+
+
+HERE = Path(__file__).parent
+
+project = tomllib.loads((HERE.parent / "pyproject.toml").read_text())["project"]
+deps: list[str] = [*project["dependencies"], *(d for ds in project["optional-dependencies"].values() for d in ds)]
+(HERE / "min-constraints.txt").write_text("".join(f"{d.replace('>=', '==')}\n" for d in deps if ">=" in d))

pyproject.toml

@@ -13,22 +13,21 @@ license = "MPL-2.0"
 authors = [
   { name = "Philipp A.", email = "flying-sheep@web.de" },
 ]
-requires-python = ">=3.12"
+requires-python = ">=3.13"
 classifiers = [
   "Development Status :: 5 - Production/Stable",
   "Intended Audience :: Developers",
   "Programming Language :: Python :: 3 :: Only",
-  "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: 3.13",
   "Programming Language :: Python :: 3.14",
   "Programming Language :: Python :: 3.15",
 ]
 dynamic = [ "description", "readme", "version" ]
-dependencies = [ "array-api-compat", "numpy>=2" ]
-optional-dependencies.accel = [ "numba>=0.57" ]
+dependencies = [ "array-api-compat", "numpy>=2.1" ]
+optional-dependencies.accel = [ "numba>=0.61" ]
 optional-dependencies.dask = [ "dask>=2023.6.1" ]
 optional-dependencies.full = [ "fast-array-utils[accel,dask,sparse]", "h5py", "zarr" ]
-optional-dependencies.sparse = [ "scipy>=1.13" ]
+optional-dependencies.sparse = [ "scipy>=1.15" ]
 optional-dependencies.testing = [ "packaging" ]
 urls."Issue Tracker" = "https://github.com/scverse/fast-array-utils/issues"
 urls."Source Code" = "https://github.com/scverse/fast-array-utils"
@@ -92,16 +91,24 @@ envs.hatch-check-types.dependency-groups = [ "typecheck", "test" ]
 envs.hatch-test.extra-dependencies = [ "ipycytoscape", "ipykernel" ]
 envs.hatch-test.env-vars.CODSPEED_PROFILE_FOLDER = "test-data/codspeed"
 envs.hatch-test.matrix = [
-  { python = [ "3.14", "3.12" ], extras = [ "full", "min" ] },
-  { python = [ "3.12" ], extras = [ "full" ], resolution = [ "lowest" ] },
+  { python = [ "3.15", "3.13" ], extras = [ "full", "min" ] },
+  { python = [ "3.13" ], extras = [ "full" ], resolution = [ "lowest" ] },
 ]
 envs.hatch-test.overrides.matrix.extras.dependency-groups = [
   { value = "test", if = [ "full" ] },
 ]
-envs.hatch-test.overrides.matrix.resolution.dependencies = [
-  { value = "numpy==2", if = [ "lowest" ] },
-  { value = "dask==2023.6.1", if = [ "lowest" ] },
-  { value = "scipy==1.13.0", if = [ "lowest" ] },
+envs.hatch-test.overrides.matrix.resolution.pre-install-commands = [
+  { value = "python ci/min-constraints.py", if = [ "lowest" ] },
+]
+envs.hatch-test.overrides.matrix.resolution.env-vars = [
+  { key = "UV_CONSTRAINT", value = "ci/min-constraints.txt", if = [ "lowest" ] },
+]
+# TODO: remove once h5py ships cp315 wheels: https://github.com/h5py/h5py/issues/2972
+envs.hatch-test.overrides.matrix.python.env-vars = [
+  { key = "UV_FIND_LINKS", value = "https://pypi.anaconda.org/scientific-python-nightly-wheels/simple/h5py/", if = [
+    "3.15"
+  ] },
+  { key = "UV_CONSTRAINT", value = "ci/h5py-nightly.txt", if = [ "3.15" ] },
 ]
 envs.hatch-test.default-args = []
 envs.hatch-test.dependency-groups = [ "test-min" ]
@@ -129,7 +136,8 @@ lint.ignore = [
   "S101",    # asserts are fine
   "TID252",  # relative imports are fine
 ]
-# No __init__.py in docs
+# No __init__.py in scripts and docs
+lint.per-file-ignores."ci/**/*.py" = [ "INP001" ]
 lint.per-file-ignores."docs/**/*.py" = [ "INP001" ]
 # Shadows builtins like `sum`
 lint.per-file-ignores."src/**/stats/*.py" = [ "A001", "A004" ]

src/testing/fast_array_utils/__init__.py

@@ -6,7 +6,7 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, cast
+from typing import TYPE_CHECKING
 
 from ._array_type import ArrayType, ConversionContext, Flags, random_mat
 
@@ -28,25 +28,23 @@
 ]
 
 
-_TP_MEM = (
+_TP_MEM: tuple[ArrayType[CpuArray | GpuArray, None], ...] = (
     ArrayType("numpy", "ndarray", Flags.Any),
     ArrayType("cupy", "ndarray", Flags.Any | Flags.Gpu),
-    *(ArrayType("scipy.sparse", n, Flags.Any | Flags.Sparse) for n in ["csr_array", "csc_array"]),
-    *(
-        ArrayType(mod, n, Flags.Any | Flags.Sparse | Flags.Matrix | flags)
-        for n in ["csr_matrix", "csc_matrix"]
-        for (mod, flags) in [("scipy.sparse", Flags(0)), ("cupyx.scipy.sparse", Flags.Gpu)]
-    ),
+    ArrayType("scipy.sparse", "csr_array", Flags.Any | Flags.Sparse),
+    ArrayType("scipy.sparse", "csc_array", Flags.Any | Flags.Sparse),
+    ArrayType("scipy.sparse", "csr_matrix", Flags.Any | Flags.Sparse | Flags.Matrix),
+    ArrayType("scipy.sparse", "csc_matrix", Flags.Any | Flags.Sparse | Flags.Matrix),
+    ArrayType("cupyx.scipy.sparse", "csr_matrix", Flags.Any | Flags.Sparse | Flags.Matrix | Flags.Gpu),
+    ArrayType("cupyx.scipy.sparse", "csc_matrix", Flags.Any | Flags.Sparse | Flags.Matrix | Flags.Gpu),
 )
-_TP_DASK = tuple(
-    ArrayType("dask.array", "Array", Flags.Dask | t.flags, inner=t)  # type: ignore[type-var]
-    for t in cast("tuple[ArrayType[CpuArray | GpuArray, None], ...]", _TP_MEM)
+_TP_DASK = tuple(ArrayType("dask.array", "Array", Flags.Dask | t.flags, inner=t) for t in _TP_MEM)
+_TP_DISK_DENSE: tuple[ArrayType[DiskArray, None], ...] = (
+    ArrayType("h5py", "Dataset", Flags.Any | Flags.Disk),
+    ArrayType("zarr", "Array", Flags.Any | Flags.Disk),
 )
-_TP_DISK_DENSE = tuple(ArrayType(m, n, Flags.Any | Flags.Disk) for m, n in [("h5py", "Dataset"), ("zarr", "Array")])
 _TP_DISK_SPARSE = tuple(
-    ArrayType("anndata.abc", n, Flags.Any | Flags.Disk | Flags.Sparse, inner=t)  # type: ignore[type-var]
-    for t in cast("tuple[ArrayType[DiskArray, None], ...]", _TP_DISK_DENSE)
-    for n in ["CSRDataset", "CSCDataset"]
+    ArrayType("anndata.abc", n, Flags.Any | Flags.Disk | Flags.Sparse, inner=t) for t in _TP_DISK_DENSE for n in ["CSRDataset", "CSCDataset"]
 )
 
 SUPPORTED_TYPES: tuple[ArrayType, ...] = (*_TP_MEM, *_TP_DASK, *_TP_DISK_DENSE, *_TP_DISK_SPARSE)

src/testing/fast_array_utils/_array_type.py

@@ -4,11 +4,10 @@
 from __future__ import annotations
 
 import enum
-import sys
 from dataclasses import KW_ONLY, dataclass, field
 from functools import cached_property, partial
 from importlib.metadata import version
-from typing import TYPE_CHECKING, Generic, TypedDict, TypeVar, cast
+from typing import TYPE_CHECKING, TypedDict, cast
 
 import numpy as np
 from packaging.version import Version
@@ -74,17 +73,8 @@ class ConversionContext:
     hdf5_file: h5py.File  # TODO(flying-sheep): ReadOnly <https://peps.python.org/pep-0767/>
 
 
-if TYPE_CHECKING or sys.version_info >= (3, 13):
-    # TODO(flying-sheep): move vars into type parameter syntax  # noqa: TD003
-    Arr = TypeVar("Arr", bound="ExtendedArray", default="Array")
-    Inner = TypeVar("Inner", bound="ArrayType[InnerArray, None] | None", default="Any")
-else:
-    Arr = TypeVar("Arr")
-    Inner = TypeVar("Inner")
-
-
 @dataclass(frozen=True)
-class ArrayType(Generic[Arr, Inner]):  # noqa: UP046
+class ArrayType[Arr: ExtendedArray = Array, Inner: ArrayType[InnerArray, None] | None = ArrayType[InnerArray, None] | None]:
     """Supported array type with methods for conversion and random generation.
 
     Examples

src/testing/fast_array_utils/pytest.py

@@ -159,7 +159,7 @@ def hdf5_file(self) -> h5py.File:  # type: ignore[override]
 
 
 @pytest.fixture
-def tmp_hdf5_file(tmp_path: Path) -> Generator[h5py.File, None, None]:
+def tmp_hdf5_file(tmp_path: Path) -> Generator[h5py.File]:
     import h5py
 
     with h5py.File(tmp_path / "test.h5", "w") as f:

tests/test_stats.py

@@ -3,7 +3,6 @@
 
 from concurrent.futures import ThreadPoolExecutor
 from functools import partial
-from importlib.metadata import version
 from importlib.util import find_spec
 from pathlib import Path
 from typing import TYPE_CHECKING, cast
@@ -12,7 +11,6 @@
 import pytest
 import scipy.sparse as sps
 from numpy.exceptions import AxisError
-from packaging.version import Version
 
 from fast_array_utils import stats, types
 from testing.fast_array_utils import SUPPORTED_TYPES, Flags
@@ -43,11 +41,6 @@
 ATS_CUPY_SPARSE = {at for at in SUPPORTED_TYPES if "cupyx.scipy" in str(at)}
 
 
-def _xfail_if_old_scipy(array_type: ArrayType[Any], ndim: Literal[1, 2]) -> pytest.MarkDecorator:
-    cond = ndim == 1 and bool(array_type.flags & Flags.Sparse) and Version(version("scipy")) < Version("1.14")
-    return pytest.mark.xfail(cond, reason="Sparse matrices don’t support 1d arrays")
-
-
 @pytest.fixture(
     scope="session",
     params=[
@@ -145,10 +138,7 @@ def pbmc64k_reduced_raw() -> sps.csr_array[np.float32]:
 @pytest.mark.array_type(skip={*ATS_SPARSE_DS, Flags.Matrix})
 @pytest.mark.parametrize("func", STAT_FUNCS)
 @pytest.mark.parametrize(("ndim", "axis"), [(1, 0), (2, 3), (2, -1)], ids=["1d-ax0", "2d-ax3", "2d-axneg"])
-def test_ndim_error(
-    request: pytest.FixtureRequest, array_type: ArrayType[Array], func: StatFunNoDtype, ndim: Literal[1, 2], axis: Literal[0, 1] | None
-) -> None:
-    request.applymarker(_xfail_if_old_scipy(array_type, ndim))
+def test_ndim_error(array_type: ArrayType[Array], func: StatFunNoDtype, ndim: Literal[1, 2], axis: Literal[0, 1] | None) -> None:
     check_ndim(array_type, ndim)
     # not using the fixture because we don’t need to test multiple dtypes
     np_arr = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32)
@@ -163,15 +153,12 @@ def test_ndim_error(
 @pytest.mark.array_type(skip=ATS_SPARSE_DS)
 def test_sum(
     *,
-    request: pytest.FixtureRequest,
     array_type: ArrayType[CpuArray | GpuArray | DiskArray | types.DaskArray],
     dtype_in: type[DTypeIn],
     dtype_arg: type[DTypeOut] | None,
     axis: Literal[0, 1] | None,
     np_arr: NDArray[DTypeIn],
-    ndim: Literal[1, 2],
 ) -> None:
-    request.applymarker(_xfail_if_old_scipy(array_type, ndim))
     if np.dtype(dtype_arg).kind in "iu" and (array_type.flags & Flags.Gpu) and (array_type.flags & Flags.Sparse):
         pytest.skip("GPU sparse matrices don’t support int dtypes")
     arr = array_type(np_arr.copy())
@@ -242,8 +229,7 @@ def test_dask_shapes(array_type: ArrayType[types.DaskArray], axis: Literal[0, 1]
 
 
 @pytest.mark.array_type(skip=ATS_SPARSE_DS)
-def test_mean(request: pytest.FixtureRequest, array_type: ArrayType[Array], axis: Literal[0, 1] | None, np_arr: NDArray[DTypeIn], ndim: Literal[1, 2]) -> None:
-    request.applymarker(_xfail_if_old_scipy(array_type, ndim))
+def test_mean(array_type: ArrayType[Array], axis: Literal[0, 1] | None, np_arr: NDArray[DTypeIn]) -> None:
     arr = array_type(np_arr)
 
     result = stats.mean(arr, axis=axis)  # type: ignore[arg-type]  # https://github.com/python/mypy/issues/16777
@@ -258,13 +244,10 @@ def test_mean(request: pytest.FixtureRequest, array_type: ArrayType[Array], axis
 
 @pytest.mark.array_type(skip=Flags.Disk)
 def test_mean_var(
-    request: pytest.FixtureRequest,
     array_type: ArrayType[CpuArray | GpuArray | types.DaskArray],
     axis: Literal[0, 1] | None,
     np_arr: NDArray[DTypeIn],
-    ndim: Literal[1, 2],
 ) -> None:
-    request.applymarker(_xfail_if_old_scipy(array_type, ndim))
     arr = array_type(np_arr)
 
     mean, var = stats.mean_var(arr, axis=axis, correction=1)