typing

Author: jorisvandenbossche

pandas/core/arrays/_mixins.py

@@ -115,6 +115,12 @@ def _validate_scalar(self, value):
 
     # ------------------------------------------------------------------------
 
+    @overload
+    def view(self) -> Self: ...
+
+    @overload
+    def view(self, dtype: Dtype | None = ...) -> ArrayLike: ...
+
     def view(self, dtype: Dtype | None = None) -> ArrayLike:
         # We handle datetime64, datetime64tz, timedelta64, and period
         #  dtypes here. Everything else we pass through to the underlying

pandas/core/arrays/_utils.py

@@ -22,7 +22,7 @@
 
 def to_numpy_dtype_inference(
     arr: ArrayLike, dtype: npt.DTypeLike | None, na_value, hasna: bool
-) -> tuple[npt.DTypeLike, Any]:
+) -> tuple[np.dtype | None, Any]:
     if dtype is None and is_numeric_dtype(arr.dtype):
         dtype_given = False
         if hasna:

pandas/core/arrays/base.py

@@ -1853,6 +1853,12 @@ def copy(self) -> Self:
         """
         raise AbstractMethodError(self)
 
+    @overload
+    def view(self) -> Self: ...
+
+    @overload
+    def view(self, dtype: Dtype | None = ...) -> ArrayLike: ...
+
     def view(self, dtype: Dtype | None = None) -> ArrayLike:
         """
         Return a view on the array.

pandas/core/arrays/numpy_.py

@@ -159,7 +159,7 @@ def dtype(self) -> NumpyEADtype:
     # NumPy Array Interface
 
     def __array__(
-        self, dtype: NpDtype | None = None, copy: bool | None = None
+        self, dtype: np.dtype | None = None, copy: bool | None = None
     ) -> np.ndarray:
         if copy is not None:
             # Note: branch avoids `copy=None` for NumPy 1.x support