Merge pull request numpy#28657 from jorenham/typing/_typing-cleanup

TYP: simplified type-aliases in ``numpy._typing``

Author: charris

numpy/_typing/_array_like.py

@@ -5,22 +5,7 @@
 from typing import Any, Protocol, TypeAlias, TypeVar, runtime_checkable, TYPE_CHECKING
 
 import numpy as np
-from numpy import (
-    ndarray,
-    dtype,
-    generic,
-    unsignedinteger,
-    integer,
-    floating,
-    complexfloating,
-    number,
-    timedelta64,
-    datetime64,
-    object_,
-    void,
-    str_,
-    bytes_,
-)
+from numpy import dtype
 from ._nbit_base import _32Bit, _64Bit
 from ._nested_sequence import _NestedSequence
 from ._shape import _Shape
@@ -33,12 +18,12 @@
     from numpy._core.multiarray import StringDType
 
 _T = TypeVar("_T")
-_ScalarType = TypeVar("_ScalarType", bound=generic)
-_ScalarType_co = TypeVar("_ScalarType_co", bound=generic, covariant=True)
+_ScalarType = TypeVar("_ScalarType", bound=np.generic)
+_ScalarType_co = TypeVar("_ScalarType_co", bound=np.generic, covariant=True)
 _DType = TypeVar("_DType", bound=dtype[Any])
 _DType_co = TypeVar("_DType_co", covariant=True, bound=dtype[Any])
 
-NDArray: TypeAlias = ndarray[_Shape, dtype[_ScalarType_co]]
+NDArray: TypeAlias = np.ndarray[_Shape, dtype[_ScalarType_co]]
 
 # The `_SupportsArray` protocol only cares about the default dtype
 # (i.e. `dtype=None` or no `dtype` parameter at all) of the to-be returned
@@ -47,7 +32,7 @@
 # any and all remaining overloads
 @runtime_checkable
 class _SupportsArray(Protocol[_DType_co]):
-    def __array__(self) -> ndarray[Any, _DType_co]: ...
+    def __array__(self) -> np.ndarray[Any, _DType_co]: ...
 
 
 @runtime_checkable
@@ -94,87 +79,33 @@ def __array_function__(
     class _Buffer(Protocol):
         def __buffer__(self, flags: int, /) -> memoryview: ...
 
-ArrayLike: TypeAlias = _Buffer | _DualArrayLike[
-    dtype[Any],
-    bool | int | float | complex | str | bytes,
-]
+ArrayLike: TypeAlias = _Buffer | _DualArrayLike[dtype[Any], complex | bytes | str]
 
 # `ArrayLike<X>_co`: array-like objects that can be coerced into `X`
 # given the casting rules `same_kind`
-_ArrayLikeBool_co: TypeAlias = _DualArrayLike[
-    dtype[np.bool],
-    bool,
-]
-_ArrayLikeUInt_co: TypeAlias = _DualArrayLike[
-    dtype[np.bool] | dtype[unsignedinteger[Any]],
-    bool,
-]
-_ArrayLikeInt_co: TypeAlias = _DualArrayLike[
-    dtype[np.bool] | dtype[integer[Any]],
-    bool | int,
-]
-_ArrayLikeFloat_co: TypeAlias = _DualArrayLike[
-    dtype[np.bool] | dtype[integer[Any]] | dtype[floating[Any]],
-    bool | int | float,
-]
-_ArrayLikeComplex_co: TypeAlias = _DualArrayLike[
-    (
-        dtype[np.bool]
-        | dtype[integer[Any]]
-        | dtype[floating[Any]]
-        | dtype[complexfloating[Any, Any]]
-    ),
-    bool | int | float | complex,
-]
-_ArrayLikeNumber_co: TypeAlias = _DualArrayLike[
-    dtype[np.bool] | dtype[number[Any]],
-    bool | int | float | complex,
-]
-_ArrayLikeTD64_co: TypeAlias = _DualArrayLike[
-    dtype[np.bool] | dtype[integer[Any]] | dtype[timedelta64],
-    bool | int,
-]
-_ArrayLikeDT64_co: TypeAlias = (
-    _SupportsArray[dtype[datetime64]]
-    | _NestedSequence[_SupportsArray[dtype[datetime64]]]
-)
-_ArrayLikeObject_co: TypeAlias = (
-    _SupportsArray[dtype[object_]]
-    | _NestedSequence[_SupportsArray[dtype[object_]]]
-)
-
-_ArrayLikeVoid_co: TypeAlias = (
-    _SupportsArray[dtype[void]]
-    | _NestedSequence[_SupportsArray[dtype[void]]]
-)
-_ArrayLikeStr_co: TypeAlias = _DualArrayLike[
-    dtype[str_],
-    str,
-]
-_ArrayLikeBytes_co: TypeAlias = _DualArrayLike[
-    dtype[bytes_],
-    bytes,
-]
-_ArrayLikeString_co: TypeAlias = _DualArrayLike[
-    StringDType,
-    str
-]
-_ArrayLikeAnyString_co: TypeAlias = (
-    _ArrayLikeStr_co |
-    _ArrayLikeBytes_co |
-    _ArrayLikeString_co
-)
+_ArrayLikeBool_co: TypeAlias = _DualArrayLike[dtype[np.bool], bool]
+_ArrayLikeUInt_co: TypeAlias = _DualArrayLike[dtype[np.bool | np.unsignedinteger], bool]
+_ArrayLikeInt_co: TypeAlias = _DualArrayLike[dtype[np.bool | np.integer], int]
+_ArrayLikeFloat_co: TypeAlias = _DualArrayLike[dtype[np.bool | np.integer | np.floating], float]
+_ArrayLikeComplex_co: TypeAlias = _DualArrayLike[dtype[np.bool | np.number], complex]
+_ArrayLikeNumber_co: TypeAlias = _ArrayLikeComplex_co
+_ArrayLikeTD64_co: TypeAlias = _DualArrayLike[dtype[np.bool | np.integer | np.timedelta64], int]
+_ArrayLikeDT64_co: TypeAlias = _ArrayLike[np.datetime64]
+_ArrayLikeObject_co: TypeAlias = _ArrayLike[np.object_]
+
+_ArrayLikeVoid_co: TypeAlias = _ArrayLike[np.void]
+_ArrayLikeBytes_co: TypeAlias = _DualArrayLike[dtype[np.bytes_], bytes]
+_ArrayLikeStr_co: TypeAlias = _DualArrayLike[dtype[np.str_], str]
+_ArrayLikeString_co: TypeAlias = _DualArrayLike[StringDType, str]
+_ArrayLikeAnyString_co: TypeAlias = _DualArrayLike[dtype[np.character] | StringDType, bytes | str]
 
 __Float64_co: TypeAlias = np.floating[_64Bit] | np.float32 | np.float16 | np.integer | np.bool
 __Complex128_co: TypeAlias = np.number[_64Bit] | np.number[_32Bit] | np.float16 | np.integer | np.bool
-_ArrayLikeFloat64_co: TypeAlias = _DualArrayLike[dtype[__Float64_co], float | int]
-_ArrayLikeComplex128_co: TypeAlias = _DualArrayLike[dtype[__Complex128_co], complex | float | int]
+_ArrayLikeFloat64_co: TypeAlias = _DualArrayLike[dtype[__Float64_co], float]
+_ArrayLikeComplex128_co: TypeAlias = _DualArrayLike[dtype[__Complex128_co], complex]
 
 # NOTE: This includes `builtins.bool`, but not `numpy.bool`.
-_ArrayLikeInt: TypeAlias = _DualArrayLike[
-    dtype[integer[Any]],
-    int,
-]
+_ArrayLikeInt: TypeAlias = _DualArrayLike[dtype[np.integer], int]
 
 # Extra ArrayLike type so that pyright can deal with NDArray[Any]
 # Used as the first overload, should only match NDArray[Any],
@@ -185,8 +116,4 @@ def __buffer__(self, flags: int, /) -> memoryview: ...
 else:
     from typing import NoReturn as _UnknownType
 
-
-_ArrayLikeUnknown: TypeAlias = _DualArrayLike[
-    dtype[_UnknownType],
-    _UnknownType,
-]
+_ArrayLikeUnknown: TypeAlias = _DualArrayLike[dtype[_UnknownType], _UnknownType]