Merge pull request #22587 from BvB93/typing

TYP: Update type annotations for new 1.24 features

numpy/__init__.pyi

@@ -620,6 +620,7 @@ from numpy.lib.utils import (
     lookfor as lookfor,
     byte_bounds as byte_bounds,
     safe_eval as safe_eval,
+    show_runtime as show_runtime,
 )
 
 from numpy.matrixlib import (

numpy/core/shape_base.pyi

@@ -2,7 +2,13 @@ from collections.abc import Sequence
 from typing import TypeVar, overload, Any, SupportsIndex
 
 from numpy import generic, _CastingKind
-from numpy._typing import ArrayLike, NDArray, _ArrayLike, DTypeLike
+from numpy._typing import (
+    NDArray,
+    ArrayLike,
+    DTypeLike,
+    _ArrayLike,
+    _DTypeLike,
+)
 
 _SCT = TypeVar("_SCT", bound=generic)
 _ArrayType = TypeVar("_ArrayType", bound=NDArray[Any])
@@ -34,39 +40,62 @@ def atleast_3d(*arys: ArrayLike) -> list[NDArray[Any]]: ...
 def vstack(
     tup: Sequence[_ArrayLike[_SCT]],
     *,
-    dtype: DTypeLike  = ..., 
+    dtype: None = ...,
     casting: _CastingKind = ...
 ) -> NDArray[_SCT]: ...
 @overload
 def vstack(
     tup: Sequence[ArrayLike],
     *,
-    dtype: DTypeLike  = ..., 
+    dtype: _DTypeLike[_SCT],
+    casting: _CastingKind = ...
+) -> NDArray[_SCT]: ...
+@overload
+def vstack(
+    tup: Sequence[ArrayLike],
+    *,
+    dtype: DTypeLike = ...,
     casting: _CastingKind = ...
 ) -> NDArray[Any]: ...
 
 @overload
 def hstack(
-    tup: Sequence[_ArrayLike[_SCT]], 
+    tup: Sequence[_ArrayLike[_SCT]],
+    *,
+    dtype: None = ...,
+    casting: _CastingKind = ...
+) -> NDArray[_SCT]: ...
+@overload
+def hstack(
+    tup: Sequence[ArrayLike],
     *,
-    dtype: DTypeLike  = ..., 
+    dtype: _DTypeLike[_SCT],
     casting: _CastingKind = ...
 ) -> NDArray[_SCT]: ...
 @overload
 def hstack(
-    tup: Sequence[ArrayLike], 
+    tup: Sequence[ArrayLike],
     *,
-    dtype: DTypeLike  = ..., 
+    dtype: DTypeLike = ...,
     casting: _CastingKind = ...
 ) -> NDArray[Any]: ...
 
 @overload
 def stack(
     arrays: Sequence[_ArrayLike[_SCT]],
     axis: SupportsIndex = ...,
-    out: None  = ...,
+    out: None = ...,
     *,
-    dtype: DTypeLike = ...,
+    dtype: None = ...,
+    casting: _CastingKind = ...
+) -> NDArray[_SCT]: ...
+@overload
+def stack(
+    arrays: Sequence[ArrayLike],
+    axis: SupportsIndex = ...,
+    out: None = ...,
+    *,
+    dtype: _DTypeLike[_SCT],
     casting: _CastingKind = ...
 ) -> NDArray[_SCT]: ...
 @overload
@@ -75,7 +104,7 @@ def stack(
     axis: SupportsIndex = ...,
     out: None = ...,
     *,
-    dtype: DTypeLike  = ...,
+    dtype: DTypeLike = ...,
     casting: _CastingKind = ...
 ) -> NDArray[Any]: ...
 @overload
@@ -84,7 +113,7 @@ def stack(
     axis: SupportsIndex = ...,
     out: _ArrayType = ...,
     *,
-    dtype: DTypeLike  = ...,
+    dtype: DTypeLike = ...,
     casting: _CastingKind = ...
 ) -> _ArrayType: ...
 

numpy/lib/__init__.pyi

@@ -231,6 +231,7 @@ from numpy.lib.utils import (
     lookfor as lookfor,
     byte_bounds as byte_bounds,
     safe_eval as safe_eval,
+    show_runtime as show_runtime,
 )
 
 from numpy.core.multiarray import (

numpy/lib/function_base.pyi

@@ -441,12 +441,8 @@ def sinc(x: _ArrayLikeFloat_co) -> NDArray[floating[Any]]: ...
 @overload
 def sinc(x: _ArrayLikeComplex_co) -> NDArray[complexfloating[Any, Any]]: ...
 
-@overload
-def msort(a: _ArrayType) -> _ArrayType: ...
-@overload
-def msort(a: _ArrayLike[_SCT]) -> NDArray[_SCT]: ...
-@overload
-def msort(a: ArrayLike) -> NDArray[Any]: ...
+# NOTE: Deprecated
+# def msort(a: ArrayLike) -> NDArray[Any]: ...
 
 @overload
 def median(

numpy/lib/utils.pyi

@@ -87,3 +87,5 @@ def lookfor(
 ) -> None: ...
 
 def safe_eval(source: str | AST) -> Any: ...
+
+def show_runtime() -> None: ...

numpy/ma/core.pyi

@@ -276,7 +276,6 @@ class MaskedArray(ndarray[_ShapeType, _DType_co]):
     def sort(self, axis=..., kind=..., order=..., endwith=..., fill_value=...): ...
     def min(self, axis=..., out=..., fill_value=..., keepdims=...): ...
     # NOTE: deprecated
-    # def mini(self, axis=...): ...
     # def tostring(self, fill_value=..., order=...): ...
     def max(self, axis=..., out=..., fill_value=..., keepdims=...): ...
     def ptp(self, axis=..., out=..., fill_value=..., keepdims=...): ...

numpy/polynomial/_polybase.pyi

@@ -9,6 +9,8 @@ class ABCPolyBase(abc.ABC):
     maxpower: ClassVar[int]
     coef: Any
     @property
+    def symbol(self) -> str: ...
+    @property
     @abc.abstractmethod
     def domain(self): ...
     @property
@@ -21,7 +23,7 @@ class ABCPolyBase(abc.ABC):
     def has_samedomain(self, other): ...
     def has_samewindow(self, other): ...
     def has_sametype(self, other): ...
-    def __init__(self, coef, domain=..., window=...): ...
+    def __init__(self, coef, domain=..., window=..., symbol: str = ...) -> None: ...
     def __format__(self, fmt_str): ...
     def __call__(self, arg): ...
     def __iter__(self): ...

numpy/typing/tests/data/reveal/array_constructors.pyi

@@ -187,12 +187,15 @@ reveal_type(np.atleast_2d(A))  # E: ndarray[Any, dtype[{float64}]]
 reveal_type(np.atleast_3d(A))  # E: ndarray[Any, dtype[{float64}]]
 
 reveal_type(np.vstack([A, A]))  # E: ndarray[Any, Any]
+reveal_type(np.vstack([A, A], dtype=np.float64))  # E: ndarray[Any, dtype[{float64}]]
 reveal_type(np.vstack([A, C]))  # E: ndarray[Any, dtype[Any]]
 reveal_type(np.vstack([C, C]))  # E: ndarray[Any, dtype[Any]]
 
 reveal_type(np.hstack([A, A]))  # E: ndarray[Any, Any]
+reveal_type(np.hstack([A, A], dtype=np.float64))  # E: ndarray[Any, dtype[{float64}]]
 
 reveal_type(np.stack([A, A]))  # E: Any
+reveal_type(np.stack([A, A], dtype=np.float64))  # E: ndarray[Any, dtype[{float64}]]
 reveal_type(np.stack([A, C]))  # E: ndarray[Any, dtype[Any]]
 reveal_type(np.stack([C, C]))  # E: ndarray[Any, dtype[Any]]
 reveal_type(np.stack([A, A], axis=0))  # E: Any

numpy/typing/tests/data/reveal/lib_function_base.pyi

@@ -123,10 +123,6 @@ reveal_type(np.sinc(1j))  # E: complexfloating[Any, Any]
 reveal_type(np.sinc(AR_f8))  # E: ndarray[Any, dtype[floating[Any]]]
 reveal_type(np.sinc(AR_c16))  # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
 
-reveal_type(np.msort(CHAR_AR_U))  # E: Any
-reveal_type(np.msort(AR_U))  # E: ndarray[Any, dtype[str_]]
-reveal_type(np.msort(AR_LIKE_f8))  # E: ndarray[Any, dtype[Any]]
-
 reveal_type(np.median(AR_f8, keepdims=False))  # E: floating[Any]
 reveal_type(np.median(AR_c16, overwrite_input=True))  # E: complexfloating[Any, Any]
 reveal_type(np.median(AR_m))  # E: timedelta64