Merge pull request #1651 from scipy/ruff/UP046

🚨 fix/ignore `UP046` ruff errors

Author: jorenham

pyproject.toml

@@ -285,7 +285,6 @@ ignore = [
   "FIX",
   "DOC",
   # TODO(@jorenham): https://github.com/scipy/scipy-stubs/pull/1615
-  "UP046",
   "UP047",
 ]
 

scipy-stubs/integrate/_tanhsinh.pyi

@@ -27,7 +27,7 @@ _MaxLevelT_co = TypeVar("_MaxLevelT_co", covariant=True)
 @type_check_only
 class _TanhSinhResult(
     _RichResult[_ResultT_co | _SuccessT_co | _StatusT_co | _MaxLevelT_co],
-    Generic[_ResultT_co, _SuccessT_co, _StatusT_co, _MaxLevelT_co],
+    Generic[_ResultT_co, _SuccessT_co, _StatusT_co, _MaxLevelT_co],  # noqa: UP046
 ):
     integral: _ResultT_co
     error: _ResultT_co

scipy-stubs/io/_harwell_boeing/_fortran_format_parser.pyi

@@ -1,15 +1,13 @@
 import abc
 import re
-from typing import Final, Generic, Literal, Self, TypeVar, type_check_only
+from typing import Final, Literal, Self, type_check_only
 
 import optype.numpy as onp
 
 __all__ = ["BadFortranFormat", "ExpFormat", "FortranFormatParser", "IntFormat"]
 
 ###
 
-_NumberT = TypeVar("_NumberT", int, float)
-
 type _TokenType = Literal["INT", "INT_ID", "EXP_ID", "DOT", "LPAR", "RPAR"]
 
 ###
@@ -19,7 +17,7 @@ TOKENS: Final[dict[_TokenType, str]]
 class BadFortranFormat(SyntaxError): ...
 
 @type_check_only
-class _NumberFormat(Generic[_NumberT], metaclass=abc.ABCMeta):
+class _NumberFormat[NumberT: (int, float)](metaclass=abc.ABCMeta):
     width: Final[int]
     repeat: Final[int | None]
     min: Final[int | None]
@@ -28,7 +26,7 @@ class _NumberFormat(Generic[_NumberT], metaclass=abc.ABCMeta):
     @property
     def python_format(self, /) -> str: ...
     @classmethod
-    def from_number(cls, n: _NumberT, min: int | None = None) -> Self: ...
+    def from_number(cls, n: NumberT, min: int | None = None) -> Self: ...
 
 class IntFormat(_NumberFormat[int]):
     def __init__(self, /, width: int, min: int | None = None, repeat: int | None = None) -> None: ...

scipy-stubs/linalg/_testutils.pyi

@@ -1,30 +1,29 @@
 from _typeshed import Unused
 from collections.abc import Callable, Iterable
-from typing import Any, Final, Generic, TypeVar
+from typing import Any, Final
 
 import numpy as np
 import optype.numpy as onp
 
-_ScalarT = TypeVar("_ScalarT", bound=np.generic)
-_ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...])
+class _FakeMatrix[ScalarT: np.generic, ShapeT: tuple[int, ...]]:  # undocumented
+    _data: onp.ArrayND[ScalarT, ShapeT]
 
-class _FakeMatrix(Generic[_ScalarT, _ShapeT]):  # undocumented
-    _data: onp.ArrayND[_ScalarT, _ShapeT]
-
-    def __init__(self, /, data: onp.ArrayND[_ScalarT, _ShapeT]) -> None: ...
+    def __init__(self, /, data: onp.ArrayND[ScalarT, ShapeT]) -> None: ...
     __array_interface__: Final[Callable[[], dict[str, Any]]] = ...
 
     @property
-    def shape(self) -> _ShapeT: ...
+    def shape(self) -> ShapeT: ...
 
-class _FakeMatrix2(Generic[_ScalarT, _ShapeT]):  # undocumented
-    _data: onp.ArrayND[_ScalarT, _ShapeT]
-    def __init__(self, /, data: onp.ArrayND[_ScalarT, _ShapeT]) -> None: ...
-    def __array__(self, /, dtype: np.dtype[Any] | None = None, copy: bool | None = None) -> onp.ArrayND[_ScalarT, _ShapeT]: ...
+class _FakeMatrix2[ScalarT: np.generic, ShapeT: tuple[int, ...]]:  # undocumented
+    _data: onp.ArrayND[ScalarT, ShapeT]
+    def __init__(self, /, data: onp.ArrayND[ScalarT, ShapeT]) -> None: ...
+    def __array__(self, /, dtype: np.dtype[Any] | None = None, copy: bool | None = None) -> onp.ArrayND[ScalarT, ShapeT]: ...
     @property
-    def shape(self) -> _ShapeT: ...
+    def shape(self) -> ShapeT: ...
 
-def _get_array(shape: _ShapeT, dtype: type[_ScalarT]) -> onp.ArrayND[_ScalarT, _ShapeT]: ...  # undocumented
+def _get_array[ScalarT: np.generic, ShapeT: tuple[int, ...]](
+    shape: ShapeT, dtype: type[ScalarT]
+) -> onp.ArrayND[ScalarT, ShapeT]: ...  # undocumented
 def _id[T](x: T) -> T: ...  # undocumented
 
 #

scipy-stubs/optimize/_root.pyi

@@ -19,7 +19,6 @@ _ScalarT = TypeVar("_ScalarT", bound=npc.inexact)
 _ScalarT_co = TypeVar("_ScalarT_co", bound=npc.inexact, default=np.float64 | Any, covariant=True)
 _ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...])
 _ShapeT_co = TypeVar("_ShapeT_co", bound=tuple[int, ...], default=tuple[Any, ...], covariant=True)
-_JacOptionsT = TypeVar("_JacOptionsT", bound=Mapping[str, object])
 
 @type_check_only
 class _RootOptionsHybr(TypedDict, total=False):
@@ -43,7 +42,7 @@ class _RootOptionsLM(TypedDict, total=False):
     diag: onp.ToFloat1D
 
 @type_check_only
-class _RootOptionsNonlin(TypedDict, Generic[_JacOptionsT], total=False):
+class _RootOptionsNonlin[JacOptionsT: Mapping[str, object]](TypedDict, total=False):
     nit: int
     disp: bool
     maxiter: int
@@ -53,7 +52,7 @@ class _RootOptionsNonlin(TypedDict, Generic[_JacOptionsT], total=False):
     xatol: float
     tol_norm: Callable[[onp.Array1D[np.float64]], float]
     line_search: Literal["armijo", "wolfe"] | None
-    jac_options: _JacOptionsT
+    jac_options: JacOptionsT
 
 @type_check_only
 class _JacOptionsBase(TypedDict, total=False):

scipy-stubs/stats/_distribution_infrastructure.pyi

@@ -162,7 +162,7 @@ _null: Final[_Null] = ...
 
 def _isnull(x: object) -> TypeIs[_Null | None]: ...
 
-class _Domain(abc.ABC, Generic[_XT_co]):
+class _Domain(abc.ABC, Generic[_XT_co]):  # noqa: UP046
     @classmethod
     def __class_getitem__(cls, arg: object, /) -> types.GenericAlias: ...
 
@@ -180,7 +180,7 @@ class _Domain(abc.ABC, Generic[_XT_co]):
     @abc.abstractmethod
     def get_numerical_endpoints(self, /, x: _ParamValues) -> tuple[onp.ArrayND[_OutFloat], onp.ArrayND[_OutFloat]]: ...
 
-class _Interval(_Domain[_XT_co], Generic[_XT_co]):  # pyrefly: ignore[implicit-abstract-class]
+class _Interval(_Domain[_XT_co], Generic[_XT_co]):  # pyrefly: ignore[implicit-abstract-class]  # noqa: UP046
     @override
     @abc.abstractmethod
     def __str__(self, /) -> str: ...

scipy-stubs/stats/_typing.pyi

@@ -48,8 +48,8 @@ class BunchMixin(Generic[_TupleT_co]):
     # NOTE: `._asdict()` includes both `{fields}` and `{extra_fields}`
     def _asdict[T](self: BunchMixin[tuple[T, ...]], /) -> dict[str, T]: ...
 
-@type_check_only
-class BaseBunch(tuple[*_Ts], BunchMixin[tuple[*_Ts]], Generic[*_Ts]):
+@type_check_only  # ty currently (0.0.40) doens't support PEP 695 with variadic type parameters.
+class BaseBunch(tuple[*_Ts], BunchMixin[tuple[*_Ts]], Generic[*_Ts]):  # noqa: UP046
     @abc.abstractmethod
     def __new__(_cls) -> Self: ...
     @abc.abstractmethod