TYP: replace _DType with _DTypeT (numpy#28684)

Co-authored-by: Joren Hammudoglu <[email protected]>

Author: guan404ming

numpy/__init__.pyi

@@ -91,14 +91,14 @@ __all__ = [
 
 _ShapeT_co = TypeVar("_ShapeT_co", bound=tuple[int, ...], covariant=True)
 _SCT = TypeVar("_SCT", bound=np.character)
-_CharDType_co = TypeVar("_CharDType_co", bound=dtype[np.character], covariant=True)
+_CharDTypeT_co = TypeVar("_CharDTypeT_co", bound=dtype[np.character], covariant=True)
 _CharArray: TypeAlias = chararray[tuple[int, ...], dtype[_SCT]]
 
 _StringDTypeArray: TypeAlias = np.ndarray[_Shape, np.dtypes.StringDType]
 _StringDTypeSupportsArray: TypeAlias = _SupportsArray[np.dtypes.StringDType]
 _StringDTypeOrUnicodeArray: TypeAlias = np.ndarray[_Shape, np.dtype[np.str_]] | np.ndarray[_Shape, np.dtypes.StringDType]
 
-class chararray(ndarray[_ShapeT_co, _CharDType_co]):
+class chararray(ndarray[_ShapeT_co, _CharDTypeT_co]):
     @overload
     def __new__(
         subtype,
@@ -123,9 +123,9 @@ class chararray(ndarray[_ShapeT_co, _CharDType_co]):
     ) -> chararray[_Shape, dtype[str_]]: ...
 
     def __array_finalize__(self, obj: object) -> None: ...
-    def __mul__(self, other: i_co) -> chararray[_Shape, _CharDType_co]: ...
-    def __rmul__(self, other: i_co) -> chararray[_Shape, _CharDType_co]: ...
-    def __mod__(self, i: Any) -> chararray[_Shape, _CharDType_co]: ...
+    def __mul__(self, other: i_co) -> chararray[_Shape, _CharDTypeT_co]: ...
+    def __rmul__(self, other: i_co) -> chararray[_Shape, _CharDTypeT_co]: ...
+    def __mod__(self, i: Any) -> chararray[_Shape, _CharDTypeT_co]: ...
 
     @overload
     def __eq__(
@@ -273,7 +273,7 @@ class chararray(ndarray[_ShapeT_co, _CharDType_co]):
     def expandtabs(
         self,
         tabsize: i_co = ...,
-    ) -> chararray[_Shape, _CharDType_co]: ...
+    ) -> chararray[_Shape, _CharDTypeT_co]: ...
 
     @overload
     def find(
@@ -498,12 +498,12 @@ class chararray(ndarray[_ShapeT_co, _CharDType_co]):
         deletechars: None | S_co = ...,
     ) -> _CharArray[bytes_]: ...
 
-    def zfill(self, width: i_co) -> chararray[_Shape, _CharDType_co]: ...
-    def capitalize(self) -> chararray[_ShapeT_co, _CharDType_co]: ...
-    def title(self) -> chararray[_ShapeT_co, _CharDType_co]: ...
-    def swapcase(self) -> chararray[_ShapeT_co, _CharDType_co]: ...
-    def lower(self) -> chararray[_ShapeT_co, _CharDType_co]: ...
-    def upper(self) -> chararray[_ShapeT_co, _CharDType_co]: ...
+    def zfill(self, width: i_co) -> chararray[_Shape, _CharDTypeT_co]: ...
+    def capitalize(self) -> chararray[_ShapeT_co, _CharDTypeT_co]: ...
+    def title(self) -> chararray[_ShapeT_co, _CharDTypeT_co]: ...
+    def swapcase(self) -> chararray[_ShapeT_co, _CharDTypeT_co]: ...
+    def lower(self) -> chararray[_ShapeT_co, _CharDTypeT_co]: ...
+    def upper(self) -> chararray[_ShapeT_co, _CharDTypeT_co]: ...
     def isalnum(self) -> ndarray[_ShapeT_co, dtype[np.bool]]: ...
     def isalpha(self) -> ndarray[_ShapeT_co, dtype[np.bool]]: ...
     def isdigit(self) -> ndarray[_ShapeT_co, dtype[np.bool]]: ...

numpy/_core/defchararray.pyi

@@ -193,7 +193,7 @@ __all__ = [
 ]
 
 _SCT = TypeVar("_SCT", bound=generic)
-_DType = TypeVar("_DType", bound=np.dtype[Any])
+_DTypeT = TypeVar("_DTypeT", bound=np.dtype[Any])
 _ArrayT = TypeVar("_ArrayT", bound=ndarray[Any, Any])
 _ArrayT_co = TypeVar(
     "_ArrayT_co",
@@ -260,10 +260,10 @@ class _ConstructorEmpty(Protocol):
         self,
         /,
         shape: SupportsIndex,
-        dtype: _DType | _SupportsDType[_DType],
+        dtype: _DTypeT | _SupportsDType[_DTypeT],
         order: _OrderCF = ...,
         **kwargs: Unpack[_KwargsEmpty],
-    ) -> ndarray[tuple[int], _DType]: ...
+    ) -> ndarray[tuple[int], _DTypeT]: ...
     @overload
     def __call__(
         self,
@@ -298,10 +298,10 @@ class _ConstructorEmpty(Protocol):
         self,
         /,
         shape: _AnyShapeT,
-        dtype: _DType | _SupportsDType[_DType],
+        dtype: _DTypeT | _SupportsDType[_DTypeT],
         order: _OrderCF = ...,
         **kwargs: Unpack[_KwargsEmpty],
-    ) -> ndarray[_AnyShapeT, _DType]: ...
+    ) -> ndarray[_AnyShapeT, _DTypeT]: ...
     @overload
     def __call__(
         self,
@@ -334,10 +334,10 @@ class _ConstructorEmpty(Protocol):
     def __call__(
         self, /,
         shape: _ShapeLike,
-        dtype: _DType | _SupportsDType[_DType],
+        dtype: _DTypeT | _SupportsDType[_DTypeT],
         order: _OrderCF = ...,
         **kwargs: Unpack[_KwargsEmpty],
-    ) -> ndarray[Any, _DType]: ...
+    ) -> ndarray[Any, _DTypeT]: ...
     @overload
     def __call__(
         self, /,
@@ -382,7 +382,7 @@ set_datetimeparse_function: Final[Callable[..., object]]
 def get_handler_name(a: NDArray[Any] = ..., /) -> str | None: ...
 def get_handler_version(a: NDArray[Any] = ..., /) -> int | None: ...
 def format_longfloat(x: np.longdouble, precision: int) -> str: ...
-def scalar(dtype: _DType, object: bytes | object = ...) -> ndarray[tuple[()], _DType]: ...
+def scalar(dtype: _DTypeT, object: bytes | object = ...) -> ndarray[tuple[()], _DTypeT]: ...
 def set_typeDict(dict_: dict[str, np.dtype[Any]], /) -> None: ...
 typeinfo: Final[dict[str, np.dtype[np.generic]]]
 

numpy/_core/multiarray.pyi

@@ -189,7 +189,7 @@ __all__ = [
 
 _T = TypeVar("_T")
 _SCT = TypeVar("_SCT", bound=generic)
-_DType = TypeVar("_DType", bound=np.dtype[Any])
+_DTypeT = TypeVar("_DTypeT", bound=np.dtype[Any])
 _ArrayT = TypeVar("_ArrayT", bound=np.ndarray[Any, Any])
 _ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...])
 
@@ -293,10 +293,10 @@ def full(
 def full(
     shape: SupportsIndex,
     fill_value: Any,
-    dtype: _DType | _SupportsDType[_DType],
+    dtype: _DTypeT | _SupportsDType[_DTypeT],
     order: _OrderCF = ...,
     **kwargs: Unpack[_KwargsEmpty],
-) -> np.ndarray[tuple[int], _DType]: ...
+) -> np.ndarray[tuple[int], _DTypeT]: ...
 @overload
 def full(
     shape: SupportsIndex,
@@ -326,10 +326,10 @@ def full(
 def full(
     shape: _AnyShapeT,
     fill_value: Any,
-    dtype: _DType | _SupportsDType[_DType],
+    dtype: _DTypeT | _SupportsDType[_DTypeT],
     order: _OrderCF = ...,
     **kwargs: Unpack[_KwargsEmpty],
-) -> np.ndarray[_AnyShapeT, _DType]: ...
+) -> np.ndarray[_AnyShapeT, _DTypeT]: ...
 @overload
 def full(
     shape: _AnyShapeT,
@@ -359,10 +359,10 @@ def full(
 def full(
     shape: _ShapeLike,
     fill_value: Any,
-    dtype: _DType | _SupportsDType[_DType],
+    dtype: _DTypeT | _SupportsDType[_DTypeT],
     order: _OrderCF = ...,
     **kwargs: Unpack[_KwargsEmpty],
-) -> np.ndarray[Any, _DType]: ...
+) -> np.ndarray[Any, _DTypeT]: ...
 @overload
 def full(
     shape: _ShapeLike,

numpy/_core/numeric.pyi

@@ -20,8 +20,8 @@
 _T = TypeVar("_T")
 _SCT = TypeVar("_SCT", bound=np.generic)
 _SCT_co = TypeVar("_SCT_co", bound=np.generic, covariant=True)
-_DType = TypeVar("_DType", bound=dtype[Any])
-_DType_co = TypeVar("_DType_co", covariant=True, bound=dtype[Any])
+_DTypeT = TypeVar("_DTypeT", bound=dtype[Any])
+_DTypeT_co = TypeVar("_DTypeT_co", covariant=True, bound=dtype[Any])
 
 NDArray: TypeAlias = np.ndarray[_Shape, dtype[_SCT_co]]
 
@@ -31,8 +31,8 @@
 # Concrete implementations of the protocol are responsible for adding
 # any and all remaining overloads
 @runtime_checkable
-class _SupportsArray(Protocol[_DType_co]):
-    def __array__(self) -> np.ndarray[Any, _DType_co]: ...
+class _SupportsArray(Protocol[_DTypeT_co]):
+    def __array__(self) -> np.ndarray[Any, _DTypeT_co]: ...
 
 
 @runtime_checkable
@@ -66,8 +66,8 @@ def __array_function__(
 # One representing types that can be parametrized w.r.t. `np.dtype`
 # and another one for the rest
 _DualArrayLike: TypeAlias = (
-    _SupportsArray[_DType]
-    | _NestedSequence[_SupportsArray[_DType]]
+    _SupportsArray[_DTypeT]
+    | _NestedSequence[_SupportsArray[_DTypeT]]
     | _T
     | _NestedSequence[_T]
 )

numpy/_typing/_array_like.py

@@ -26,7 +26,7 @@
 )
 
 _SCT = TypeVar("_SCT", bound=np.generic)
-_DType_co = TypeVar("_DType_co", covariant=True, bound=np.dtype[Any])
+_DTypeT_co = TypeVar("_DTypeT_co", covariant=True, bound=np.dtype[Any])
 
 _DTypeLikeNested: TypeAlias = Any  # TODO: wait for support for recursive types
 
@@ -49,9 +49,9 @@ class _DTypeDict(_DTypeDictBase, total=False):
 
 # A protocol for anything with the dtype attribute
 @runtime_checkable
-class _SupportsDType(Protocol[_DType_co]):
+class _SupportsDType(Protocol[_DTypeT_co]):
     @property
-    def dtype(self) -> _DType_co: ...
+    def dtype(self) -> _DTypeT_co: ...
 
 
 # A subset of `npt.DTypeLike` that can be parametrized w.r.t. `np.generic`

numpy/_typing/_dtype_like.py

@@ -69,8 +69,8 @@ from numpy._typing import (
 __all__ = ["load_library", "ndpointer", "c_intp", "as_ctypes", "as_array", "as_ctypes_type"]
 
 # TODO: Add a proper `_Shape` bound once we've got variadic typevars
-_DType = TypeVar("_DType", bound=dtype[Any])
-_DTypeOptional = TypeVar("_DTypeOptional", bound=None | dtype[Any])
+_DTypeT = TypeVar("_DTypeT", bound=dtype[Any])
+_DTypeOptionalT = TypeVar("_DTypeOptionalT", bound=None | dtype[Any])
 _SCT = TypeVar("_SCT", bound=generic)
 
 _FlagsKind: TypeAlias = L[
@@ -83,10 +83,10 @@ _FlagsKind: TypeAlias = L[
 ]
 
 # TODO: Add a shape typevar once we have variadic typevars (PEP 646)
-class _ndptr(ctypes.c_void_p, Generic[_DTypeOptional]):
+class _ndptr(ctypes.c_void_p, Generic[_DTypeOptionalT]):
     # In practice these 4 classvars are defined in the dynamic class
     # returned by `ndpointer`
-    _dtype_: ClassVar[_DTypeOptional]
+    _dtype_: ClassVar[_DTypeOptionalT]
     _shape_: ClassVar[None]
     _ndim_: ClassVar[None | int]
     _flags_: ClassVar[None | list[_FlagsKind]]
@@ -96,13 +96,13 @@ class _ndptr(ctypes.c_void_p, Generic[_DTypeOptional]):
     def from_param(cls: type[_ndptr[None]], obj: NDArray[Any]) -> _ctypes[Any]: ...
     @overload
     @classmethod
-    def from_param(cls: type[_ndptr[_DType]], obj: ndarray[Any, _DType]) -> _ctypes[Any]: ...
+    def from_param(cls: type[_ndptr[_DTypeT]], obj: ndarray[Any, _DTypeT]) -> _ctypes[Any]: ...
 
-class _concrete_ndptr(_ndptr[_DType]):
-    _dtype_: ClassVar[_DType]
+class _concrete_ndptr(_ndptr[_DTypeT]):
+    _dtype_: ClassVar[_DTypeT]
     _shape_: ClassVar[tuple[int, ...]]
     @property
-    def contents(self) -> ndarray[_Shape, _DType]: ...
+    def contents(self) -> ndarray[_Shape, _DTypeT]: ...
 
 def load_library(libname: StrOrBytesPath, loader_path: StrOrBytesPath) -> ctypes.CDLL: ...
 

numpy/ctypeslib/_ctypeslib.pyi

@@ -219,8 +219,8 @@ __all__ = [
 
 _ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...])
 _ShapeT_co = TypeVar("_ShapeT_co", bound=tuple[int, ...], covariant=True)
-_DType = TypeVar("_DType", bound=dtype[Any])
-_DType_co = TypeVar("_DType_co", bound=dtype[Any], covariant=True)
+_DTypeT = TypeVar("_DTypeT", bound=dtype[Any])
+_DTypeT_co = TypeVar("_DTypeT_co", bound=dtype[Any], covariant=True)
 _ArrayT = TypeVar("_ArrayT", bound=ndarray[Any, Any])
 _SCT = TypeVar("_SCT", bound=generic)
 # A subset of `MaskedArray` that can be parametrized w.r.t. `np.generic`
@@ -371,7 +371,7 @@ class MaskedIterator:
     def __setitem__(self, index, value): ...
     def __next__(self): ...
 
-class MaskedArray(ndarray[_ShapeT_co, _DType_co]):
+class MaskedArray(ndarray[_ShapeT_co, _DTypeT_co]):
     __array_priority__: Any
     def __new__(cls, data=..., mask=..., dtype=..., copy=..., subok=..., ndmin=..., fill_value=..., keep_mask=..., hard_mask=..., shrink=..., order=...): ...
     def __array_finalize__(self, obj): ...
@@ -380,9 +380,9 @@ class MaskedArray(ndarray[_ShapeT_co, _DType_co]):
     def __getitem__(self, indx): ...
     def __setitem__(self, indx, value): ...
     @property
-    def dtype(self) -> _DType_co: ...
+    def dtype(self) -> _DTypeT_co: ...
     @dtype.setter
-    def dtype(self: MaskedArray[Any, _DType], dtype: _DType, /) -> None: ...
+    def dtype(self: MaskedArray[Any, _DTypeT], dtype: _DTypeT, /) -> None: ...
     @property
     def shape(self) -> _ShapeT_co: ...
     @shape.setter
@@ -745,7 +745,7 @@ class MaskedArray(ndarray[_ShapeT_co, _DType_co]):
     def __reduce__(self): ...
     def __deepcopy__(self, memo=...): ...
 
-class mvoid(MaskedArray[_ShapeT_co, _DType_co]):
+class mvoid(MaskedArray[_ShapeT_co, _DTypeT_co]):
     def __new__(
         self,  # pyright: ignore[reportSelfClsParameterName]
         data,

numpy/ma/core.pyi

@@ -13,9 +13,9 @@ __all__ = [
 ]
 
 _ShapeT_co = TypeVar("_ShapeT_co", covariant=True, bound=tuple[int, ...])
-_DType_co = TypeVar("_DType_co", bound=dtype[Any], covariant=True)
+_DTypeT_co = TypeVar("_DTypeT_co", bound=dtype[Any], covariant=True)
 
-class MaskedRecords(MaskedArray[_ShapeT_co, _DType_co]):
+class MaskedRecords(MaskedArray[_ShapeT_co, _DTypeT_co]):
     def __new__(
         cls,
         shape,