MAINT: Tighten the type-constraints of the `__array__` dtype parameter

The likes of `np.array(..., dtype=dtype)` will always pass `np.dtype` instances to `__array__(self, dtype=...)`, so that latter should not have to take arbitrary dtype-like objects but only actual `np.dtype` instances.

6 files changed, 13 insertions, 15 deletions

diff --git a/numpy/__init__.pyi b/numpy/__init__.pyi
index 9cdc4f2e1..b1ab7c14f 100644
--- a/numpy/__init__.pyi
+++ b/numpy/__init__.pyi
@@ -853,7 +853,7 @@ class flatiter(Generic[_NdArraySubClass]):
     @overload
     def __array__(self: flatiter[ndarray[Any, _DType]], __dtype: None = ...) -> ndarray[Any, _DType]: ...
     @overload
-    def __array__(self, __dtype: DTypeLike) -> ndarray[Any, dtype[Any]]: ...
+    def __array__(self, __dtype: _DType) -> ndarray[Any, _DType]: ...
 
 _OrderKACF = Optional[Literal["K", "A", "C", "F"]]
 _OrderACF = Optional[Literal["A", "C", "F"]]
@@ -1362,7 +1362,7 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]):
     @overload
     def __array__(self, __dtype: None = ...) -> ndarray[Any, _DType_co]: ...
     @overload
-    def __array__(self, __dtype: DTypeLike) -> ndarray[Any, dtype[Any]]: ...
+    def __array__(self, __dtype: _DType) -> ndarray[Any, _DType]: ...
     @property
     def ctypes(self) -> _ctypes: ...
     @property
@@ -2409,7 +2409,7 @@ class generic(_ArrayOrScalarCommon):
     @overload
     def __array__(self: _ScalarType, __dtype: None = ...) -> ndarray[Any, dtype[_ScalarType]]: ...
     @overload
-    def __array__(self, __dtype: DTypeLike) -> ndarray[Any, dtype[Any]]: ...
+    def __array__(self, __dtype: _DType) -> ndarray[Any, _DType]: ...
     @property
     def base(self) -> None: ...
     @property
diff --git a/numpy/typing/tests/data/pass/arithmetic.py b/numpy/typing/tests/data/pass/arithmetic.py
index 7a297cfc5..62bd79004 100644
--- a/numpy/typing/tests/data/pass/arithmetic.py
+++ b/numpy/typing/tests/data/pass/arithmetic.py
@@ -25,7 +25,7 @@ i = int(1)
 
 
 class Object:
-    def __array__(self, dtype: None = None) -> np.ndarray[Any, np.dtype[np.object_]]:
+    def __array__(self) -> np.ndarray[Any, np.dtype[np.object_]]:
         ret = np.empty((), dtype=object)
         ret[()] = self
         return ret
diff --git a/numpy/typing/tests/data/pass/array_like.py b/numpy/typing/tests/data/pass/array_like.py
index 563fc08c7..e16d196b6 100644
--- a/numpy/typing/tests/data/pass/array_like.py
+++ b/numpy/typing/tests/data/pass/array_like.py
@@ -1,7 +1,7 @@
 from typing import Any, List, Optional
 
 import numpy as np
-from numpy.typing import ArrayLike, DTypeLike, _SupportsArray
+from numpy.typing import ArrayLike, _SupportsArray
 
 x1: ArrayLike = True
 x2: ArrayLike = 5
@@ -18,20 +18,20 @@ x12: ArrayLike = memoryview(b'foo')
 
 
 class A:
-    def __array__(self, dtype: DTypeLike = None) -> np.ndarray:
+    def __array__(self, dtype: Optional[np.dtype] = None) -> np.ndarray:
         return np.array([1, 2, 3])
 
 
 x13: ArrayLike = A()
 
 scalar: _SupportsArray = np.int64(1)
-scalar.__array__(None)
+scalar.__array__()
 array: _SupportsArray = np.array(1)
-array.__array__(None)
+array.__array__()
 
 a: _SupportsArray = A()
-a.__array__(None)
-a.__array__(dtype=None)
+a.__array__()
+a.__array__()
 
 # Escape hatch for when you mean to make something like an object
 # array.
diff --git a/numpy/typing/tests/data/pass/flatiter.py b/numpy/typing/tests/data/pass/flatiter.py
index 4fdf25299..63c839af4 100644
--- a/numpy/typing/tests/data/pass/flatiter.py
+++ b/numpy/typing/tests/data/pass/flatiter.py
@@ -13,4 +13,4 @@ a[[0, 1, 2]]
 a[...]
 a[:]
 a.__array__()
-a.__array__(np.float64)
+a.__array__(np.dtype(np.float64))
diff --git a/numpy/typing/tests/data/pass/ufunclike.py b/numpy/typing/tests/data/pass/ufunclike.py
index 448ee66bb..7eac89e8f 100644
--- a/numpy/typing/tests/data/pass/ufunclike.py
+++ b/numpy/typing/tests/data/pass/ufunclike.py
@@ -13,9 +13,7 @@ class Object:
     def __ge__(self, value: object) -> bool:
         return True
 
-    def __array__(
-        self, dtype: None = None
-    ) -> np.ndarray[Any, np.dtype[np.object_]]:
+    def __array__(self) -> np.ndarray[Any, np.dtype[np.object_]]:
         ret = np.empty((), dtype=object)
         ret[()] = self
         return ret
diff --git a/numpy/typing/tests/data/reveal/flatiter.py b/numpy/typing/tests/data/reveal/flatiter.py
index 221101ebb..97776dd9f 100644
--- a/numpy/typing/tests/data/reveal/flatiter.py
+++ b/numpy/typing/tests/data/reveal/flatiter.py
@@ -14,4 +14,4 @@ reveal_type(a[[0, 1, 2]])  # E: numpy.ndarray[Any, numpy.dtype[numpy.str_]]
 reveal_type(a[...])  # E: numpy.ndarray[Any, numpy.dtype[numpy.str_]]
 reveal_type(a[:])  # E: numpy.ndarray[Any, numpy.dtype[numpy.str_]]
 reveal_type(a.__array__())  # E: numpy.ndarray[Any, numpy.dtype[numpy.str_]]
-reveal_type(a.__array__(np.float64))  # E: numpy.ndarray[Any, numpy.dtype[Any]]
+reveal_type(a.__array__(np.dtype(np.float64)))  # E: numpy.ndarray[Any, numpy.dtype[{float64}]]