chore: SPEC0 update (Python 3.12+)

.github/workflows/ci-gpu.yml

@@ -43,9 +43,9 @@ jobs:
       - uses: actions/setup-python@v5
         with:
           python-version: "3.12"
-      - uses: hynek/setup-cached-uv@v2
+      - uses: astral-sh/setup-uv@v6
         with:
-          cache-dependency-path: pyproject.toml
+          enable-cache: true  # "auto" is `false` on non-GitHub runners
       - name: Install package
         run: uv pip install --system -e .[test,full] cupy-cuda12x --extra-index-url=https://pypi.nvidia.com --index-strategy=unsafe-best-match
       - name: List installed packages

.github/workflows/ci.yml

@@ -75,7 +75,7 @@ jobs:
     steps:
       - uses: actions/checkout@v5
         with: { fetch-depth: 0, filter: "blob:none" }
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: '3.13'
       - uses: astral-sh/setup-uv@v7
@@ -90,7 +90,7 @@ jobs:
     steps:
       - uses: actions/checkout@v5
         with: { fetch-depth: 0, filter: "blob:none" }
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: '3.13'
       - uses: astral-sh/setup-uv@v7
@@ -110,7 +110,7 @@ jobs:
     steps:
       - uses: actions/checkout@v5
         with: { fetch-depth: 0, filter: "blob:none" }
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
       - uses: pre-commit/action@v3.0.1

.github/workflows/publish.yml

@@ -13,8 +13,8 @@ jobs:
     permissions:
       id-token: write # to authenticate as Trusted Publisher to pypi.org
     steps:
-      - uses: actions/checkout@v4
-      - uses: actions/setup-python@v5
+      - uses: actions/checkout@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: "3.x"
           cache: pip

.readthedocs.yml

@@ -2,7 +2,7 @@ version: 2
 build:
   os: ubuntu-24.04
   tools:
-    python: "3.12"
+    python: "3.13"
 python:
   install:
     - method: pip

docs/conf.py

@@ -9,16 +9,20 @@
 from typing import TYPE_CHECKING
 
 from docutils.nodes import Text
+from sphinx.util import logging
 
 
 if TYPE_CHECKING:
+    from typing import Final
+
     from docutils.nodes import TextElement, reference
     from sphinx.addnodes import pending_xref
     from sphinx.application import Sphinx
     from sphinx.environment import BuildEnvironment
 
 
-HERE = Path(__file__).parent
+HERE: Final = Path(__file__).parent
+LOGGER: Final = logging.getLogger("fast_array_utils")
 
 
 # -- General configuration ------------------------------------------------
@@ -134,7 +138,8 @@ def resolve_type_aliases(app: Sphinx, env: BuildEnvironment, node: pending_xref,
         ref = resolve_reference_any_inventory(env=env, honor_disabled_refs=False, node=node, contnode=contnode)
     if ref is None:
         msg = f"Could not resolve {typ} {target} (from {node['reftarget']})"
-        raise AssertionError(msg)
+        LOGGER.warning(msg, type="ref")
+        return ref
     if name:
         ref.children[:] = [Text(name)]
     return ref

pyproject.toml

@@ -14,12 +14,11 @@ license = "MPL-2.0"
 authors = [
   { name = "Philipp A.", email = "flying-sheep@web.de" },
 ]
-requires-python = ">=3.11"
+requires-python = ">=3.12"
 classifiers = [
   "Development Status :: 5 - Production/Stable",
   "Intended Audience :: Developers",
   "Programming Language :: Python :: 3 :: Only",
-  "Programming Language :: Python :: 3.11",
   "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: 3.13",
   "Programming Language :: Python :: 3.14",
@@ -107,11 +106,11 @@ overrides.matrix.resolution.dependencies = [
 ]
 
 [[tool.hatch.envs.hatch-test.matrix]]
-python = [ "3.13", "3.11" ]
+python = [ "3.13", "3.12" ]
 extras = [ "full", "min" ]
 
 [[tool.hatch.envs.hatch-test.matrix]]
-python = [ "3.11" ]
+python = [ "3.12" ]
 extras = [ "full" ]
 resolution = [ "lowest" ]
 

src/fast_array_utils/conv/__init__.py

@@ -5,7 +5,6 @@
 
 from typing import TYPE_CHECKING, overload
 
-from ..typing import CpuArray, DiskArray, GpuArray  # noqa: TC001
 from ._to_dense import to_dense_
 
 
@@ -15,6 +14,7 @@
     from numpy.typing import NDArray
 
     from .. import types
+    from ..typing import CpuArray, DiskArray, GpuArray
 
 
 __all__ = ["to_dense"]

src/fast_array_utils/conv/_to_dense.py

@@ -8,14 +8,15 @@
 import numpy as np
 
 from .. import types
-from ..typing import CpuArray, DiskArray, GpuArray  # noqa: TC001
 
 
 if TYPE_CHECKING:
     from typing import Any, Literal
 
     from numpy.typing import NDArray
 
+    from ..typing import CpuArray, DiskArray, GpuArray
+
 
 # fallback’s arg0 type has to include types of registered functions
 @singledispatch

src/fast_array_utils/stats/__init__.py

@@ -10,7 +10,6 @@
 from typing import TYPE_CHECKING, cast, get_args, overload
 
 from .._validation import validate_axis
-from ..typing import CpuArray, DiskArray, GpuArray  # noqa: TC001
 from ._generic_ops import DtypeOps
 
 
@@ -22,6 +21,7 @@
     from optype.numpy import ToDType
 
     from .. import types
+    from ..typing import CpuArray, DiskArray, GpuArray
     from ._generic_ops import Ops
     from ._typing import NoDtypeOps, StatFunDtype, StatFunNoDtype
 

src/fast_array_utils/stats/_generic_ops.py

@@ -12,14 +12,14 @@
 
 
 if TYPE_CHECKING:
-    from typing import Any, Literal, TypeAlias
+    from typing import Any, Literal
 
     from numpy.typing import DTypeLike, NDArray
 
     from ..typing import CpuArray, DiskArray, GpuArray
     from ._typing import Ops
 
-    ComplexAxis: TypeAlias = tuple[Literal[0], Literal[1]] | tuple[Literal[0, 1]] | Literal[0, 1] | None
+    type ComplexAxis = tuple[Literal[0], Literal[1]] | tuple[Literal[0, 1]] | Literal[0, 1] | None
 
 
 def _run_numpy_op(

src/fast_array_utils/stats/_is_constant.py

@@ -11,13 +11,10 @@
 
 
 if TYPE_CHECKING:
-    from collections.abc import Callable
-    from typing import Any, Literal, TypeVar
+    from typing import Any, Literal
 
     from numpy.typing import NDArray
 
-    C = TypeVar("C", bound=Callable[..., Any])
-
 
 @singledispatch
 def is_constant_(

src/fast_array_utils/stats/_power.py

@@ -10,20 +10,15 @@
 
 
 if TYPE_CHECKING:
-    from typing import TypeAlias, TypeVar
-
     from numpy.typing import DTypeLike
 
     from fast_array_utils.typing import CpuArray, GpuArray
 
     # All supported array types except for disk ones and CSDataset
-    Array: TypeAlias = CpuArray | GpuArray | types.DaskArray
-
-    _Arr = TypeVar("_Arr", bound=Array)
-    _Mat = TypeVar("_Mat", bound=types.CSBase | types.CupyCSMatrix)
+    type Array = CpuArray | GpuArray | types.DaskArray
 
 
-def power(x: _Arr, n: int, /, dtype: DTypeLike | None = None) -> _Arr:
+def power[Arr: Array](x: Arr, n: int, /, dtype: DTypeLike | None = None) -> Arr:
     """Take array or matrix to a power."""
     # This wrapper is necessary because TypeVars can’t be used in `singledispatch` functions
     return _power(x, n, dtype=dtype)  # type: ignore[return-value]
@@ -37,7 +32,7 @@ def _power(x: Array, n: int, /, dtype: DTypeLike | None = None) -> Array:
 
 
 @_power.register(types.CSBase | types.CupyCSMatrix)
-def _power_cs(x: _Mat, n: int, /, dtype: DTypeLike | None = None) -> _Mat:
+def _power_cs[Mat: types.CSBase | types.CupyCSMatrix](x: Mat, n: int, /, dtype: DTypeLike | None = None) -> Mat:
     new_data = power(x.data, n, dtype=dtype)
     return type(x)((new_data, x.indices, x.indptr), shape=x.shape, dtype=new_data.dtype)  # type: ignore[call-overload,return-value]
 

src/fast_array_utils/stats/_typing.py

@@ -1,7 +1,7 @@
 # SPDX-License-Identifier: MPL-2.0
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Generic, Literal, Protocol, TypedDict, TypeVar
+from typing import TYPE_CHECKING, Literal, Protocol, TypedDict
 
 import numpy as np
 
@@ -11,17 +11,17 @@
 
 
 if TYPE_CHECKING:
-    from typing import Any, TypeAlias
+    from typing import Any
 
     from numpy.typing import DTypeLike, NDArray
 
 
-Array: TypeAlias = CpuArray | GpuArray | DiskArray | types.CSDataset | types.DaskArray
+type Array = CpuArray | GpuArray | DiskArray | types.CSDataset | types.DaskArray
 
-DTypeIn: TypeAlias = np.float32 | np.float64 | np.int32 | np.bool_
-DTypeOut: TypeAlias = np.float32 | np.float64 | np.int64
+type DTypeIn = np.float32 | np.float64 | np.int32 | np.bool_
+type DTypeOut = np.float32 | np.float64 | np.int64
 
-NdAndAx: TypeAlias = tuple[Literal[1], None] | tuple[Literal[2], Literal[0, 1] | None]
+type NdAndAx = tuple[Literal[1], None] | tuple[Literal[2], Literal[0, 1] | None]
 
 
 class StatFunNoDtype(Protocol):
@@ -48,11 +48,8 @@ def __call__(
 
 NoDtypeOps = Literal["max", "min"]
 DtypeOps = Literal["sum"]
-Ops: TypeAlias = NoDtypeOps | DtypeOps
+type Ops = NoDtypeOps | DtypeOps
 
 
-_DT = TypeVar("_DT", bound="DTypeLike")
-
-
-class DTypeKw(TypedDict, Generic[_DT], total=False):
-    dtype: _DT
+class DTypeKw[DT: DTypeLike](TypedDict, total=False):
+    dtype: DT

src/fast_array_utils/stats/_utils.py

@@ -2,25 +2,24 @@
 from __future__ import annotations
 
 from functools import partial
-from typing import TYPE_CHECKING, Literal, TypeVar, cast, get_args
+from typing import TYPE_CHECKING, Literal, cast, get_args
 
 import numpy as np
 from numpy.exceptions import AxisError
 
 from .. import types
-from ..typing import GpuArray
 from ._typing import DtypeOps
 
 
 if TYPE_CHECKING:
-    from typing import Any, Literal, TypeAlias
+    from typing import Any, Literal
 
     from numpy.typing import DTypeLike, NDArray
 
-    from ..typing import CpuArray
+    from ..typing import CpuArray, GpuArray
     from ._typing import DTypeKw, Ops
 
-    ComplexAxis: TypeAlias = tuple[Literal[0], Literal[1]] | tuple[Literal[0, 1]] | Literal[0, 1] | None
+    type ComplexAxis = tuple[Literal[0], Literal[1]] | tuple[Literal[0, 1]] | Literal[0, 1] | None
 
 
 __all__ = ["_dask_inner"]
@@ -71,7 +70,7 @@ def _dask_block(
     from . import max, min, sum
 
     if computing_meta:  # dask.blockwise doesn’t allow to pass `meta` in, and reductions below don’t handle a 0d matrix
-        return (types.CupyArray if isinstance(a, GpuArray) else np.ndarray)((), dtype or a.dtype)
+        return (types.CupyArray if isinstance(a, types.CupyArray | types.CupyCSMatrix) else np.ndarray)((), dtype or a.dtype)
 
     fns = {fn.__name__: fn for fn in (min, max, sum)}
 
@@ -114,8 +113,5 @@ def _get_shape(a: NDArray[Any] | np.number[Any] | types.CupyArray, *, axis: Lite
             raise AssertionError(msg)
 
 
-DT = TypeVar("DT", bound="DTypeLike")
-
-
-def _dtype_kw(dtype: DT | None, op: Ops) -> DTypeKw[DT]:
+def _dtype_kw[DT: DTypeLike](dtype: DT | None, op: Ops) -> DTypeKw[DT]:
     return {"dtype": dtype} if dtype is not None and op in get_args(DtypeOps) else {}

src/fast_array_utils/types.py

@@ -4,7 +4,7 @@
 from __future__ import annotations
 
 from importlib.util import find_spec
-from typing import TYPE_CHECKING, TypeVar
+from typing import TYPE_CHECKING
 
 
 __all__ = [
@@ -34,8 +34,6 @@
     "spmatrix",
 ]
 
-T_co = TypeVar("T_co", covariant=True)
-
 
 # scipy sparse
 if TYPE_CHECKING:

src/fast_array_utils/typing.py

@@ -16,13 +16,14 @@
 
 __all__ = ["CpuArray", "DiskArray", "GpuArray"]
 
+# change to `type` syntax once this is released: https://github.com/sphinx-doc/sphinx/pull/13508
 
-CpuArray: TypeAlias = NDArray[Any] | types.CSBase
+CpuArray: TypeAlias = NDArray[Any] | types.CSBase  # noqa: UP040
 """Arrays and matrices stored in CPU memory."""
 
-GpuArray: TypeAlias = types.CupyArray | types.CupyCSMatrix
+GpuArray: TypeAlias = types.CupyArray | types.CupyCSMatrix  # noqa: UP040
 """Arrays and matrices stored in GPU memory."""
 
 # TODO(flying-sheep): types.CSDataset  # noqa: TD003
-DiskArray: TypeAlias = types.H5Dataset | types.ZarrArray
+DiskArray: TypeAlias = types.H5Dataset | types.ZarrArray  # noqa: UP040
 """Arrays and matrices stored on disk."""