numpy · charris · Mar 15, 2025 · Mar 14, 2025 · Mar 14, 2025 · Mar 14, 2025
diff --git a/numpy/__init__.pyi b/numpy/__init__.pyi
@@ -574,6 +574,7 @@ from numpy.lib._polynomial_impl import (
 
 from numpy.lib._shape_base_impl import (
     column_stack,
+    row_stack,
     dstack,
     array_split,
     split,
@@ -730,10 +731,9 @@ __all__ = [  # noqa: RUF022
     "histogram2d", "mask_indices", "tril_indices", "tril_indices_from", "triu_indices",
     "triu_indices_from",
     # lib._shape_base_impl.__all__
-    # NOTE: `row_stack` is omitted because it is deprecated
     "column_stack", "dstack", "array_split", "split", "hsplit", "vsplit", "dsplit",
     "apply_over_axes", "expand_dims", "apply_along_axis", "kron", "tile",
-    "take_along_axis", "put_along_axis",
+    "take_along_axis", "put_along_axis", "row_stack",
     # lib._type_check_impl.__all__
     "iscomplexobj", "isrealobj", "imag", "iscomplex", "isreal", "nan_to_num", "real",
     "real_if_close", "typename", "mintypecode", "common_type",
@@ -4803,6 +4803,17 @@ class ufunc:
     # outputs, so we can't type it very precisely.
     def at(self, /, *args: Any, **kwargs: Any) -> None: ...
 
+    #
+    def resolve_dtypes(
+        self,
+        /,
+        dtypes: tuple[dtype[Any] | type | None, ...],
+        *,
+        signature: tuple[dtype[Any] | None, ...] | None = None,
+        casting: _CastingKind | None = None,
+        reduction: builtins.bool = False,
+    ) -> tuple[dtype[Any], ...]: ...
+
 # Parameters: `__name__`, `ntypes` and `identity`
 absolute: _UFunc_Nin1_Nout1[L['absolute'], L[20], None]
 add: _UFunc_Nin2_Nout1[L['add'], L[22], L[0]]

diff --git a/numpy/_core/_add_newdocs.pyi b/numpy/_core/_add_newdocs.pyi
@@ -0,0 +1,3 @@
+from .overrides import get_array_function_like_doc as get_array_function_like_doc
+
+def refer_to_array_attribute(attr: str, method: bool = True) -> tuple[str, str]: ...
diff --git a/numpy/_core/_add_newdocs_scalars.pyi b/numpy/_core/_add_newdocs_scalars.pyi
@@ -0,0 +1,16 @@
+from collections.abc import Iterable
+from typing import Final
+
+import numpy as np
+
+possible_aliases: Final[list[tuple[type[np.number], str, str]]] = ...
+_system: Final[str] = ...
+_machine: Final[str] = ...
+_doc_alias_string: Final[str] = ...
+_bool_docstring: Final[str] = ...
+int_name: str = ...
+float_name: str = ...
+
+def numeric_type_aliases(aliases: list[tuple[str, str]]) -> list[tuple[type[np.number], str, str]]: ...
+def add_newdoc_for_scalar_type(obj: str, fixed_aliases: Iterable[str], doc: str) -> None: ...
+def _get_platform_and_machine() -> tuple[str, str]: ...
diff --git a/numpy/_core/_dtype.pyi b/numpy/_core/_dtype.pyi
@@ -0,0 +1,58 @@
+from typing import Any, Final, TypeAlias, TypedDict, overload, type_check_only
+from typing import Literal as L
+
+from typing_extensions import ReadOnly, TypeVar
+
+import numpy as np
+
+###
+
+_T = TypeVar("_T")
+
+_Name: TypeAlias = L["uint", "int", "complex", "float", "bool", "void", "object", "datetime", "timedelta", "bytes", "str"]
+
+@type_check_only
+class _KindToStemType(TypedDict):
+    u: ReadOnly[L["uint"]]
+    i: ReadOnly[L["int"]]
+    c: ReadOnly[L["complex"]]
+    f: ReadOnly[L["float"]]
+    b: ReadOnly[L["bool"]]
+    V: ReadOnly[L["void"]]
+    O: ReadOnly[L["object"]]
+    M: ReadOnly[L["datetime"]]
+    m: ReadOnly[L["timedelta"]]
+    S: ReadOnly[L["bytes"]]
+    U: ReadOnly[L["str"]]
+
+###
+
+_kind_to_stem: Final[_KindToStemType] = ...
+
+#
+def _kind_name(dtype: np.dtype[Any]) -> _Name: ...
+def __str__(dtype: np.dtype[Any]) -> str: ...
+def __repr__(dtype: np.dtype[Any]) -> str: ...
+
+#
+def _isunsized(dtype: np.dtype[Any]) -> bool: ...
+def _is_packed(dtype: np.dtype[Any]) -> bool: ...
+def _name_includes_bit_suffix(dtype: np.dtype[Any]) -> bool: ...
+
+#
+def _construction_repr(dtype: np.dtype[Any], include_align: bool = False, short: bool = False) -> str: ...
+def _scalar_str(dtype: np.dtype[Any], short: bool) -> str: ...
+def _byte_order_str(dtype: np.dtype[Any]) -> str: ...
+def _datetime_metadata_str(dtype: np.dtype[Any]) -> str: ...
+def _struct_dict_str(dtype: np.dtype[Any], includealignedflag: bool) -> str: ...
+def _struct_list_str(dtype: np.dtype[Any]) -> str: ...
+def _struct_str(dtype: np.dtype[Any], include_align: bool) -> str: ...
+def _subarray_str(dtype: np.dtype[Any]) -> str: ...
+def _name_get(dtype: np.dtype[Any]) -> str: ...
+
+#
+@overload
+def _unpack_field(dtype: np.dtype[Any], offset: int, title: _T) -> tuple[np.dtype[Any], int, _T]: ...
+@overload
+def _unpack_field(dtype: np.dtype[Any], offset: int, title: None = None) -> tuple[np.dtype[Any], int, None]: ...
+def _aligned_offset(offset: int, alignment: int) -> int: ...
diff --git a/numpy/_core/_dtype_ctypes.pyi b/numpy/_core/_dtype_ctypes.pyi
@@ -0,0 +1,83 @@
+import _ctypes
+import ctypes as ct
+from typing import Any, overload
+
+import numpy as np
+
+#
+@overload
+def dtype_from_ctypes_type(t: type[_ctypes.Array[Any] | _ctypes.Structure]) -> np.dtype[np.void]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_bool]) -> np.dtype[np.bool]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_int8 | ct.c_byte]) -> np.dtype[np.int8]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_uint8 | ct.c_ubyte]) -> np.dtype[np.uint8]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_int16 | ct.c_short]) -> np.dtype[np.int16]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_uint16 | ct.c_ushort]) -> np.dtype[np.uint16]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_int32 | ct.c_int]) -> np.dtype[np.int32]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_uint32 | ct.c_uint]) -> np.dtype[np.uint32]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_ssize_t | ct.c_long]) -> np.dtype[np.int32 | np.int64]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_size_t | ct.c_ulong]) -> np.dtype[np.uint32 | np.uint64]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_int64 | ct.c_longlong]) -> np.dtype[np.int64]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_uint64 | ct.c_ulonglong]) -> np.dtype[np.uint64]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_float]) -> np.dtype[np.float32]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_double]) -> np.dtype[np.float64]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_longdouble]) -> np.dtype[np.longdouble]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.c_char]) -> np.dtype[np.bytes_]: ...
+@overload
+def dtype_from_ctypes_type(t: type[ct.py_object[Any]]) -> np.dtype[np.object_]: ...
+
+# NOTE: the complex ctypes on python>=3.14 are not yet supported at runtim, see
+# https://github.com/numpy/numpy/issues/28360
+
+#
+def _from_ctypes_array(t: type[_ctypes.Array[Any]]) -> np.dtype[np.void]: ...
+def _from_ctypes_structure(t: type[_ctypes.Structure]) -> np.dtype[np.void]: ...
+def _from_ctypes_union(t: type[_ctypes.Union]) -> np.dtype[np.void]: ...
+
+# keep in sync with `dtype_from_ctypes_type` (minus the first overload)
+@overload
+def _from_ctypes_scalar(t: type[ct.c_bool]) -> np.dtype[np.bool]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_int8 | ct.c_byte]) -> np.dtype[np.int8]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_uint8 | ct.c_ubyte]) -> np.dtype[np.uint8]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_int16 | ct.c_short]) -> np.dtype[np.int16]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_uint16 | ct.c_ushort]) -> np.dtype[np.uint16]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_int32 | ct.c_int]) -> np.dtype[np.int32]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_uint32 | ct.c_uint]) -> np.dtype[np.uint32]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_ssize_t | ct.c_long]) -> np.dtype[np.int32 | np.int64]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_size_t | ct.c_ulong]) -> np.dtype[np.uint32 | np.uint64]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_int64 | ct.c_longlong]) -> np.dtype[np.int64]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_uint64 | ct.c_ulonglong]) -> np.dtype[np.uint64]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_float]) -> np.dtype[np.float32]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_double]) -> np.dtype[np.float64]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_longdouble]) -> np.dtype[np.longdouble]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.c_char]) -> np.dtype[np.bytes_]: ...
+@overload
+def _from_ctypes_scalar(t: type[ct.py_object[Any]]) -> np.dtype[np.object_]: ...
diff --git a/numpy/_core/_exceptions.pyi b/numpy/_core/_exceptions.pyi
@@ -0,0 +1,73 @@
+from collections.abc import Iterable
+from typing import Any, Final, overload
+
+from typing_extensions import TypeVar, Unpack
+
+import numpy as np
+from numpy import _CastingKind
+from numpy._utils import set_module as set_module
+
+###
+
+_T = TypeVar("_T")
+_TupleT = TypeVar("_TupleT", bound=tuple[()] | tuple[Any, Any, Unpack[tuple[Any, ...]]])
+_ExceptionT = TypeVar("_ExceptionT", bound=Exception)
+
+###
+
+class UFuncTypeError(TypeError):
+    ufunc: Final[np.ufunc]
+    def __init__(self, /, ufunc: np.ufunc) -> None: ...
+
+class _UFuncNoLoopError(UFuncTypeError):
+    dtypes: tuple[np.dtype[Any], ...]
+    def __init__(self, /, ufunc: np.ufunc, dtypes: Iterable[np.dtype[Any]]) -> None: ...
+
+class _UFuncBinaryResolutionError(_UFuncNoLoopError):
+    dtypes: tuple[np.dtype[Any], np.dtype[Any]]
+    def __init__(self, /, ufunc: np.ufunc, dtypes: Iterable[np.dtype[Any]]) -> None: ...
+
+class _UFuncCastingError(UFuncTypeError):
+    casting: Final[_CastingKind]
+    from_: Final[np.dtype[Any]]
+    to: Final[np.dtype[Any]]
+    def __init__(self, /, ufunc: np.ufunc, casting: _CastingKind, from_: np.dtype[Any], to: np.dtype[Any]) -> None: ...
+
+class _UFuncInputCastingError(_UFuncCastingError):
+    in_i: Final[int]
+    def __init__(
+        self,
+        /,
+        ufunc: np.ufunc,
+        casting: _CastingKind,
+        from_: np.dtype[Any],
+        to: np.dtype[Any],
+        i: int,
+    ) -> None: ...
+
+class _UFuncOutputCastingError(_UFuncCastingError):
+    out_i: Final[int]
+    def __init__(
+        self,
+        /,
+        ufunc: np.ufunc,
+        casting: _CastingKind,
+        from_: np.dtype[Any],
+        to: np.dtype[Any],
+        i: int,
+    ) -> None: ...
+
+class _ArrayMemoryError(MemoryError):
+    shape: tuple[int, ...]
+    dtype: np.dtype[Any]
+    def __init__(self, /, shape: tuple[int, ...], dtype: np.dtype[Any]) -> None: ...
+    @property
+    def _total_size(self) -> int: ...
+    @staticmethod
+    def _size_to_string(num_bytes: int) -> str: ...
+
+@overload
+def _unpack_tuple(tup: tuple[_T]) -> _T: ...
+@overload
+def _unpack_tuple(tup: _TupleT) -> _TupleT: ...
+def _display_as_base(cls: type[_ExceptionT]) -> type[_ExceptionT]: ...
diff --git a/numpy/_core/_machar.pyi b/numpy/_core/_machar.pyi
@@ -0,0 +1,73 @@
+from collections.abc import Iterable
+from typing import Any, Final, overload
+
+from typing_extensions import TypeVar, Unpack
+
+import numpy as np
+from numpy import _CastingKind
+from numpy._utils import set_module as set_module
+
+###
+
+_T = TypeVar("_T")
+_TupleT = TypeVar("_TupleT", bound=tuple[()] | tuple[Any, Any, Unpack[tuple[Any, ...]]])
+_ExceptionT = TypeVar("_ExceptionT", bound=Exception)
+
+###
+
+class UFuncTypeError(TypeError):
+    ufunc: Final[np.ufunc]
+    def __init__(self, /, ufunc: np.ufunc) -> None: ...
+
+class _UFuncNoLoopError(UFuncTypeError):
+    dtypes: tuple[np.dtype[Any], ...]
+    def __init__(self, /, ufunc: np.ufunc, dtypes: Iterable[np.dtype[Any]]) -> None: ...
+
+class _UFuncBinaryResolutionError(_UFuncNoLoopError):
+    dtypes: tuple[np.dtype[Any], np.dtype[Any]]
+    def __init__(self, /, ufunc: np.ufunc, dtypes: Iterable[np.dtype[Any]]) -> None: ...
+
+class _UFuncCastingError(UFuncTypeError):
+    casting: Final[_CastingKind]
+    from_: Final[np.dtype[Any]]
+    to: Final[np.dtype[Any]]
+    def __init__(self, /, ufunc: np.ufunc, casting: _CastingKind, from_: np.dtype[Any], to: np.dtype[Any]) -> None: ...
+
+class _UFuncInputCastingError(_UFuncCastingError):
+    in_i: Final[int]
+    def __init__(
+        self,
+        /,
+        ufunc: np.ufunc,
+        casting: _CastingKind,
+        from_: np.dtype[Any],
+        to: np.dtype[Any],
+        i: int,
+    ) -> None: ...
+
+class _UFuncOutputCastingError(_UFuncCastingError):
+    out_i: Final[int]
+    def __init__(
+        self,
+        /,
+        ufunc: np.ufunc,
+        casting: _CastingKind,
+        from_: np.dtype[Any],
+        to: np.dtype[Any],
+        i: int,
+    ) -> None: ...
+
+class _ArrayMemoryError(MemoryError):
+    shape: tuple[int, ...]
+    dtype: np.dtype[Any]
+    def __init__(self, /, shape: tuple[int, ...], dtype: np.dtype[Any]) -> None: ...
+    @property
+    def _total_size(self) -> int: ...
+    @staticmethod
+    def _size_to_string(num_bytes: int) -> str: ...
+
+@overload
+def _unpack_tuple(tup: tuple[_T]) -> _T: ...
+@overload
+def _unpack_tuple(tup: _TupleT) -> _TupleT: ...
+def _display_as_base(cls: type[_ExceptionT]) -> type[_ExceptionT]: ...
diff --git a/numpy/_core/_methods.pyi b/numpy/_core/_methods.pyi
@@ -0,0 +1,24 @@
+from collections.abc import Callable
+from typing import Any, TypeAlias
+
+from typing_extensions import Concatenate
+
+import numpy as np
+
+from . import _exceptions as _exceptions
+
+###
+
+_Reduce2: TypeAlias = Callable[Concatenate[object, ...], Any]
+
+###
+
+bool_dt: np.dtype[np.bool] = ...
+umr_maximum: _Reduce2 = ...
+umr_minimum: _Reduce2 = ...
+umr_sum: _Reduce2 = ...
+umr_prod: _Reduce2 = ...
+umr_bitwise_count = np.bitwise_count
+umr_any: _Reduce2 = ...
+umr_all: _Reduce2 = ...
+_complex_to_float: dict[np.dtype[np.complexfloating], np.dtype[np.floating]] = ...
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,3 @@
		from .overrides import get_array_function_like_doc as get_array_function_like_doc

		def refer_to_array_attribute(attr: str, method: bool = True) -> tuple[str, str]: ...