ENH: Add annotations for 4 objects in `np.core.numerictypes`

* `cast`
* `nbytes`
* `ScalarType`
* `typecodes`

2 files changed, 56 insertions, 12 deletions

diff --git a/numpy/__init__.pyi b/numpy/__init__.pyi
index 2fa5b3d41..08050a524 100644
--- a/numpy/__init__.pyi
+++ b/numpy/__init__.pyi
@@ -327,6 +327,10 @@ from numpy.core.numerictypes import (
     issubdtype as issubdtype,
     sctype2char as sctype2char,
     find_common_type as find_common_type,
+    nbytes as nbytes,
+    cast as cast,
+    ScalarType as ScalarType,
+    typecodes as typecodes,
 )
 
 from numpy.core.shape_base import (
@@ -504,14 +508,6 @@ class vectorize:
     def __call__(self, *args: Any, **kwargs: Any) -> Any: ...
     def __getattr__(self, key: str) -> Any: ...
 
-# Placeholders for miscellaneous objects
-# NOTE: `cast` and `nbytes` are in fact instances of a `dict` subclass that
-# converts passed `DTypeLike` objects into the actual keys (`np.generic`)
-ScalarType: Tuple[Type[Any], ...]
-cast: Dict[DTypeLike, Callable[..., ndarray[Any, dtype[Any]]]]
-nbytes: Dict[DTypeLike, int]
-typecodes: Dict[str, str]
-
 # Placeholders for Python-based functions
 def angle(z, deg=...): ...
 def append(arr, values, axis=...): ...
diff --git a/numpy/core/numerictypes.pyi b/numpy/core/numerictypes.pyi
index c8b4e1c65..1c9c84e95 100644
--- a/numpy/core/numerictypes.pyi
+++ b/numpy/core/numerictypes.pyi
@@ -1,9 +1,55 @@
-from typing import TypeVar, Optional, Type, Union, Tuple, Sequence, overload, Any
+import sys
+from typing import (
+    TypeVar,
+    Optional,
+    Type,
+    Union,
+    Tuple,
+    Sequence,
+    overload,
+    Any,
+    TypeVar,
+    Dict,
+    List,
+)
 
 from numpy import generic, ndarray, dtype
-from numpy.typing import DTypeLike
+
+from numpy.core._type_aliases import (
+    sctypeDict as sctypeDict,
+    sctypes as sctypes,
+)
+
+from numpy.typing import DTypeLike, ArrayLike
+
+if sys.version_info >= (3, 8):
+    from typing import Literal, Protocol, TypedDict
+else:
+    from typing_extensions import Literal, Protocol, TypedDict
 
 _T = TypeVar("_T")
+_ScalarType = TypeVar("_ScalarType", bound=generic)
+
+class _CastFunc(Protocol):
+    def __call__(
+        self, x: ArrayLike, k: DTypeLike = ...
+    ) -> ndarray[Any, dtype[Any]]: ...
+
+class _TypeCodes(TypedDict):
+    Character: Literal['c']
+    Integer: Literal['bhilqp']
+    UnsignedInteger: Literal['BHILQP']
+    Float: Literal['efdg']
+    Complex: Literal['FDG']
+    AllInteger: Literal['bBhHiIlLqQpP']
+    AllFloat: Literal['efdgFDG']
+    Datetime: Literal['Mm']
+    All: Literal['?bhilqpBHILQPefdgFDGSUVOMm']
+
+class _typedict(Dict[Type[generic], _T]):
+    def __getitem__(self, key: DTypeLike) -> _T: ...
+
+__all__: List[str]
 
 def maximum_sctype(t: DTypeLike) -> dtype: ...
 def issctype(rep: object) -> bool: ...
@@ -25,5 +71,7 @@ def find_common_type(
     array_types: Sequence[DTypeLike], scalar_types: Sequence[DTypeLike]
 ) -> dtype: ...
 
-# TODO: Add annotations for the following objects:
-# nbytes, cast, ScalarType & typecodes
+cast: _typedict[_CastFunc]
+nbytes: _typedict[int]
+typecodes: _TypeCodes
+ScalarType: Tuple[type, ...]