♻️ refactor type variable names from _SCT to _ScalarT

src/_numtype/@test/test_to_array.pyi

@@ -5,12 +5,12 @@ from typing_extensions import TypeVar
 import _numtype as _nt
 import numpy as np
 
-_SCT = TypeVar("_SCT", bound=np.generic)
-_0D: TypeAlias = np.ndarray[tuple[()], np.dtype[_SCT]]
-_1D: TypeAlias = np.ndarray[tuple[int], np.dtype[_SCT]]
-_2D: TypeAlias = np.ndarray[tuple[int, int], np.dtype[_SCT]]
-_3D: TypeAlias = np.ndarray[tuple[int, int, int], np.dtype[_SCT]]
-_ND: TypeAlias = np.ndarray[tuple[int, ...], np.dtype[_SCT]]
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_0D: TypeAlias = np.ndarray[tuple[()], np.dtype[_ScalarT]]
+_1D: TypeAlias = np.ndarray[tuple[int], np.dtype[_ScalarT]]
+_2D: TypeAlias = np.ndarray[tuple[int, int], np.dtype[_ScalarT]]
+_3D: TypeAlias = np.ndarray[tuple[int, int, int], np.dtype[_ScalarT]]
+_ND: TypeAlias = np.ndarray[tuple[int, ...], np.dtype[_ScalarT]]
 
 b_0d: bool
 i_0d: int

src/numpy-stubs/@test/static/accept/array_constructors.pyi

@@ -7,9 +7,9 @@ from typing_extensions import TypeVar, assert_type
 import numpy as np
 import numpy.typing as npt
 
-_SCT_co = TypeVar("_SCT_co", bound=np.generic, covariant=True)
+_ScalarT_co = TypeVar("_ScalarT_co", bound=np.generic, covariant=True)
 
-class MyArray(np.ndarray[tuple[int], np.dtype[_SCT_co]]): ...
+class MyArray(np.ndarray[tuple[int], np.dtype[_ScalarT_co]]): ...
 
 i8: np.int64
 

src/numpy-stubs/@test/static/accept/multiarray.pyi

@@ -7,9 +7,9 @@ import numpy.typing as npt
 
 ###
 
-_SCT_co = TypeVar("_SCT_co", bound=np.generic, covariant=True)
+_ScalarT_co = TypeVar("_ScalarT_co", bound=np.generic, covariant=True)
 
-class SubClass(npt.NDArray[_SCT_co]): ...
+class SubClass(npt.NDArray[_ScalarT_co]): ...
 
 subclass: SubClass[np.float64]
 

src/numpy-stubs/@test/static/accept/twodim_base.pyi

@@ -4,9 +4,9 @@ from typing_extensions import TypeVar, assert_type
 import numpy as np
 import numpy.typing as npt
 
-_SCT = TypeVar("_SCT", bound=np.generic)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
 
-def func1(ar: npt.NDArray[_SCT], a: int) -> npt.NDArray[_SCT]: ...
+def func1(ar: npt.NDArray[_ScalarT], a: int) -> npt.NDArray[_ScalarT]: ...
 def func2(ar: npt.NDArray[np.number], a: str) -> npt.NDArray[np.float64]: ...
 
 AR_b: npt.NDArray[np.bool]

src/numpy-stubs/__init__.pyi

@@ -1195,7 +1195,7 @@ class dtype(Generic[_ScalarT_co], metaclass=_DTypeMeta):
     ) -> dtype[float64]: ...
 
     # Overload for `dtype` instances, scalar types, and instances that have a
-    # `dtype: dtype[_SCT]` attribute
+    # `dtype: dtype[_ScalarT]` attribute
     @overload
     def __new__(  # type: ignore[overload-overlap]
         cls,

src/numpy-stubs/_core/records.pyi

@@ -20,11 +20,11 @@ __all__ = [
 ]
 
 _T = TypeVar("_T")
-_SCT = TypeVar("_SCT", bound=np.generic)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
 _DTypeT_co = TypeVar("_DTypeT_co", bound=np.dtype, covariant=True)
 _ShapeT_co = TypeVar("_ShapeT_co", bound=tuple[int, ...], covariant=True)
 
-_RecArray: TypeAlias = recarray[Any, np.dtype[_SCT]]
+_RecArray: TypeAlias = recarray[Any, np.dtype[_ScalarT]]
 
 @type_check_only
 class _SupportsReadInto(Protocol):
@@ -220,7 +220,7 @@ def fromfile(
 # exported in `numpy.rec`
 @overload
 def array(  # type: ignore[overload-overlap]
-    obj: _SCT | NDArray[_SCT],
+    obj: _ScalarT | NDArray[_ScalarT],
     dtype: None = None,
     shape: _ShapeLike | None = None,
     offset: int = 0,
@@ -231,7 +231,7 @@ def array(  # type: ignore[overload-overlap]
     aligned: bool = False,
     byteorder: None = None,
     copy: bool = True,
-) -> _RecArray[_SCT]: ...
+) -> _RecArray[_ScalarT]: ...
 @overload
 def array(
     obj: ArrayLike,

src/numpy-stubs/_core/shape_base.pyi

@@ -9,7 +9,7 @@ __all__ = ["atleast_1d", "atleast_2d", "atleast_3d", "block", "hstack", "stack",
 
 ###
 
-_SCT = TypeVar("_SCT", bound=np.generic)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
 _SCT0 = TypeVar("_SCT0", bound=np.generic)
 _SCT1 = TypeVar("_SCT1", bound=np.generic)
 
@@ -41,11 +41,13 @@ def atleast_1d(a0: _Array1T0, a1: _Array1T1, /) -> tuple[_Array1T0, _Array1T1]:
 @overload
 def atleast_1d(a0: _Array1T, a1: _Array1T, /, *arys: _Array1T) -> tuple[_Array1T, ...]: ...  # type: ignore[overload-overlap]
 @overload
-def atleast_1d(a0: _ArrayLike[_SCT], /) -> NDArray[_SCT]: ...
+def atleast_1d(a0: _ArrayLike[_ScalarT], /) -> NDArray[_ScalarT]: ...
 @overload
 def atleast_1d(a0: _ArrayLike[_SCT0], a2: _ArrayLike[_SCT1], /) -> tuple[NDArray[_SCT0], NDArray[_SCT1]]: ...
 @overload
-def atleast_1d(a0: _ArrayLike[_SCT], a2: _ArrayLike[_SCT], /, *arys: _ArrayLike[_SCT]) -> tuple[NDArray[_SCT], ...]: ...
+def atleast_1d(
+    a0: _ArrayLike[_ScalarT], a2: _ArrayLike[_ScalarT], /, *arys: _ArrayLike[_ScalarT]
+) -> tuple[NDArray[_ScalarT], ...]: ...
 @overload
 def atleast_1d(a0: ArrayLike, /) -> NDArray[Any]: ...
 @overload
@@ -61,11 +63,13 @@ def atleast_2d(a0: _Array2T0, a1: _Array2T1, /) -> tuple[_Array2T0, _Array2T1]:
 @overload
 def atleast_2d(a0: _Array2T, a1: _Array2T, /, *arys: _Array2T) -> tuple[_Array2T, ...]: ...  # type: ignore[overload-overlap]
 @overload
-def atleast_2d(a0: _ArrayLike[_SCT], /) -> NDArray[_SCT]: ...
+def atleast_2d(a0: _ArrayLike[_ScalarT], /) -> NDArray[_ScalarT]: ...
 @overload
 def atleast_2d(a0: _ArrayLike[_SCT0], a2: _ArrayLike[_SCT1], /) -> tuple[NDArray[_SCT0], NDArray[_SCT1]]: ...
 @overload
-def atleast_2d(a0: _ArrayLike[_SCT], a2: _ArrayLike[_SCT], /, *arys: _ArrayLike[_SCT]) -> tuple[NDArray[_SCT], ...]: ...
+def atleast_2d(
+    a0: _ArrayLike[_ScalarT], a2: _ArrayLike[_ScalarT], /, *arys: _ArrayLike[_ScalarT]
+) -> tuple[NDArray[_ScalarT], ...]: ...
 @overload
 def atleast_2d(a0: ArrayLike, /) -> NDArray[Any]: ...
 @overload
@@ -81,11 +85,13 @@ def atleast_3d(a0: _Array3T0, a1: _Array3T1, /) -> tuple[_Array3T0, _Array3T1]:
 @overload
 def atleast_3d(a0: _Array3T, a1: _Array3T, /, *arys: _Array3T) -> tuple[_Array3T, ...]: ...  # type: ignore[overload-overlap]
 @overload
-def atleast_3d(a0: _ArrayLike[_SCT], /) -> NDArray[_SCT]: ...
+def atleast_3d(a0: _ArrayLike[_ScalarT], /) -> NDArray[_ScalarT]: ...
 @overload
 def atleast_3d(a0: _ArrayLike[_SCT0], a2: _ArrayLike[_SCT1], /) -> tuple[NDArray[_SCT0], NDArray[_SCT1]]: ...
 @overload
-def atleast_3d(a0: _ArrayLike[_SCT], a2: _ArrayLike[_SCT], /, *arys: _ArrayLike[_SCT]) -> tuple[NDArray[_SCT], ...]: ...
+def atleast_3d(
+    a0: _ArrayLike[_ScalarT], a2: _ArrayLike[_ScalarT], /, *arys: _ArrayLike[_ScalarT]
+) -> tuple[NDArray[_ScalarT], ...]: ...
 @overload
 def atleast_3d(a0: ArrayLike, /) -> NDArray[Any]: ...
 @overload
@@ -96,18 +102,18 @@ def atleast_3d(a0: ArrayLike, a2: ArrayLike, /, *arys: ArrayLike) -> tuple[NDArr
 #
 @overload
 def vstack(
-    tup: Sequence[_ArrayLike[_SCT]],
+    tup: Sequence[_ArrayLike[_ScalarT]],
     *,
     dtype: None = None,
     casting: np._CastingKind = "same_kind",
-) -> NDArray[_SCT]: ...
+) -> NDArray[_ScalarT]: ...
 @overload
 def vstack(
     tup: Sequence[ArrayLike],
     *,
-    dtype: _DTypeLike[_SCT],
+    dtype: _DTypeLike[_ScalarT],
     casting: np._CastingKind = "same_kind",
-) -> NDArray[_SCT]: ...
+) -> NDArray[_ScalarT]: ...
 @overload
 def vstack(
     tup: Sequence[ArrayLike],
@@ -119,18 +125,18 @@ def vstack(
 #
 @overload
 def hstack(
-    tup: Sequence[_ArrayLike[_SCT]],
+    tup: Sequence[_ArrayLike[_ScalarT]],
     *,
     dtype: None = None,
     casting: np._CastingKind = "same_kind",
-) -> NDArray[_SCT]: ...
+) -> NDArray[_ScalarT]: ...
 @overload
 def hstack(
     tup: Sequence[ArrayLike],
     *,
-    dtype: _DTypeLike[_SCT],
+    dtype: _DTypeLike[_ScalarT],
     casting: np._CastingKind = "same_kind",
-) -> NDArray[_SCT]: ...
+) -> NDArray[_ScalarT]: ...
 @overload
 def hstack(
     tup: Sequence[ArrayLike],
@@ -142,22 +148,22 @@ def hstack(
 #
 @overload
 def stack(
-    arrays: Sequence[_ArrayLike[_SCT]],
+    arrays: Sequence[_ArrayLike[_ScalarT]],
     axis: SupportsIndex = 0,
     out: None = None,
     *,
     dtype: None = None,
     casting: np._CastingKind = "same_kind",
-) -> NDArray[_SCT]: ...
+) -> NDArray[_ScalarT]: ...
 @overload
 def stack(
     arrays: Sequence[ArrayLike],
     axis: SupportsIndex = 0,
     out: None = None,
     *,
-    dtype: _DTypeLike[_SCT],
+    dtype: _DTypeLike[_ScalarT],
     casting: np._CastingKind = "same_kind",
-) -> NDArray[_SCT]: ...
+) -> NDArray[_ScalarT]: ...
 @overload
 def stack(
     arrays: Sequence[ArrayLike],
@@ -188,12 +194,12 @@ def stack(
 
 #
 @overload
-def unstack(array: _ArrayLike[_SCT], /, *, axis: SupportsIndex = 0) -> tuple[NDArray[_SCT], ...]: ...
+def unstack(array: _ArrayLike[_ScalarT], /, *, axis: SupportsIndex = 0) -> tuple[NDArray[_ScalarT], ...]: ...
 @overload
 def unstack(array: ArrayLike, /, *, axis: SupportsIndex = 0) -> tuple[NDArray[Any], ...]: ...
 
 #
 @overload
-def block(arrays: _ArrayLike[_SCT]) -> NDArray[_SCT]: ...
+def block(arrays: _ArrayLike[_ScalarT]) -> NDArray[_ScalarT]: ...
 @overload
 def block(arrays: ArrayLike) -> NDArray[Any]: ...

src/numpy-stubs/lib/_arraypad_impl.pyi

@@ -9,7 +9,7 @@ __all__ = ["pad"]
 
 ###
 
-_SCT = TypeVar("_SCT", bound=np.generic)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
 
 _ModeKind: TypeAlias = L[
     "constant",
@@ -35,15 +35,15 @@ class _ModeFunc(Protocol):
 # specific modes. Consider adding more overloads to express this in the future.
 @overload
 def pad(
-    array: _ArrayLike[_SCT],
+    array: _ArrayLike[_ScalarT],
     pad_width: _ArrayLikeInt,
     mode: _ModeKind = ...,
     *,
     stat_length: _ArrayLikeInt | None = ...,
     constant_values: ArrayLike = ...,
     end_values: ArrayLike = ...,
     reflect_type: L["odd", "even"] = ...,
-) -> NDArray[_SCT]: ...
+) -> NDArray[_ScalarT]: ...
 @overload
 def pad(
     array: ArrayLike,
@@ -56,6 +56,6 @@ def pad(
     reflect_type: L["odd", "even"] = ...,
 ) -> NDArray[Any]: ...
 @overload
-def pad(array: _ArrayLike[_SCT], pad_width: _ArrayLikeInt, mode: _ModeFunc, **kwargs: object) -> NDArray[_SCT]: ...
+def pad(array: _ArrayLike[_ScalarT], pad_width: _ArrayLikeInt, mode: _ModeFunc, **kwargs: object) -> NDArray[_ScalarT]: ...
 @overload
 def pad(array: ArrayLike, pad_width: _ArrayLikeInt, mode: _ModeFunc, **kwargs: object) -> NDArray[Any]: ...

src/numpy-stubs/lib/_stride_tricks_impl.pyi

@@ -7,7 +7,7 @@ from numpy._typing import ArrayLike, NDArray, _ArrayLike, _Shape, _ShapeLike
 
 __all__ = ["broadcast_arrays", "broadcast_shapes", "broadcast_to"]
 
-_SCT = TypeVar("_SCT", bound=np.generic)
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
 
 class DummyArray:
     __array_interface__: dict[str, Any]
@@ -16,12 +16,12 @@ class DummyArray:
 
 @overload
 def as_strided(
-    x: _ArrayLike[_SCT],
+    x: _ArrayLike[_ScalarT],
     shape: Iterable[int] | None = ...,
     strides: Iterable[int] | None = ...,
     subok: bool = ...,
     writeable: bool = ...,
-) -> NDArray[_SCT]: ...
+) -> NDArray[_ScalarT]: ...
 @overload
 def as_strided(
     x: ArrayLike,
@@ -32,13 +32,13 @@ def as_strided(
 ) -> NDArray[Any]: ...
 @overload
 def sliding_window_view(
-    x: _ArrayLike[_SCT],
+    x: _ArrayLike[_ScalarT],
     window_shape: int | Iterable[int],
     axis: SupportsIndex | None = ...,
     *,
     subok: bool = ...,
     writeable: bool = ...,
-) -> NDArray[_SCT]: ...
+) -> NDArray[_ScalarT]: ...
 @overload
 def sliding_window_view(
     x: ArrayLike,
@@ -49,7 +49,7 @@ def sliding_window_view(
     writeable: bool = ...,
 ) -> NDArray[Any]: ...
 @overload
-def broadcast_to(array: _ArrayLike[_SCT], shape: int | Iterable[int], subok: bool = ...) -> NDArray[_SCT]: ...
+def broadcast_to(array: _ArrayLike[_ScalarT], shape: int | Iterable[int], subok: bool = ...) -> NDArray[_ScalarT]: ...
 @overload
 def broadcast_to(array: ArrayLike, shape: int | Iterable[int], subok: bool = ...) -> NDArray[Any]: ...
 def broadcast_shapes(*args: _ShapeLike) -> _Shape: ...