TYP: use npt.DTypeLike for type annotation of dtype arg in to_numpy

pandas/core/arrays/base.py

@@ -449,7 +449,7 @@ def __ne__(self, other: Any) -> ArrayLike:  # type: ignore[override]
 
     def to_numpy(
         self,
-        dtype: Dtype | None = None,
+        dtype: npt.DTypeLike | None = None,
         copy: bool = False,
         na_value=lib.no_default,
     ) -> np.ndarray:
@@ -478,12 +478,7 @@ def to_numpy(
         -------
         numpy.ndarray
         """
-        # error: Argument "dtype" to "asarray" has incompatible type
-        # "Union[ExtensionDtype, str, dtype[Any], Type[str], Type[float], Type[int],
-        # Type[complex], Type[bool], Type[object], None]"; expected "Union[dtype[Any],
-        # None, type, _SupportsDType, str, Union[Tuple[Any, int], Tuple[Any, Union[int,
-        # Sequence[int]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
-        result = np.asarray(self, dtype=dtype)  # type: ignore[arg-type]
+        result = np.asarray(self, dtype=dtype)
         if copy or na_value is not lib.no_default:
             result = result.copy()
         if na_value is not lib.no_default:

pandas/core/arrays/masked.py

@@ -224,12 +224,9 @@ def __len__(self) -> int:
     def __invert__(self: BaseMaskedArrayT) -> BaseMaskedArrayT:
         return type(self)(~self._data, self._mask.copy())
 
-    # error: Argument 1 of "to_numpy" is incompatible with supertype "ExtensionArray";
-    # supertype defines the argument type as "Union[ExtensionDtype, str, dtype[Any],
-    # Type[str], Type[float], Type[int], Type[complex], Type[bool], Type[object], None]"
-    def to_numpy(  # type: ignore[override]
+    def to_numpy(
         self,
-        dtype: NpDtype | None = None,
+        dtype: npt.DTypeLike | None = None,
         copy: bool = False,
         na_value: Scalar = lib.no_default,
     ) -> np.ndarray:

pandas/core/arrays/numpy_.py

@@ -10,6 +10,7 @@
     Dtype,
     NpDtype,
     Scalar,
+    npt,
 )
 from pandas.compat.numpy import function as nv
 
@@ -365,12 +366,9 @@ def skew(
     # ------------------------------------------------------------------------
     # Additional Methods
 
-    # error: Argument 1 of "to_numpy" is incompatible with supertype "ExtensionArray";
-    # supertype defines the argument type as "Union[ExtensionDtype, str, dtype[Any],
-    # Type[str], Type[float], Type[int], Type[complex], Type[bool], Type[object], None]"
-    def to_numpy(  # type: ignore[override]
+    def to_numpy(
         self,
-        dtype: NpDtype | None = None,
+        dtype: npt.DTypeLike | None = None,
         copy: bool = False,
         na_value=lib.no_default,
     ) -> np.ndarray:

pandas/core/arrays/string_arrow.py

@@ -24,6 +24,7 @@
     Scalar,
     ScalarIndexer,
     SequenceIndexer,
+    npt,
 )
 from pandas.compat import (
     pa_version_under1p0,
@@ -199,12 +200,9 @@ def __arrow_array__(self, type=None):
         """Convert myself to a pyarrow Array or ChunkedArray."""
         return self._data
 
-    # error: Argument 1 of "to_numpy" is incompatible with supertype "ExtensionArray";
-    # supertype defines the argument type as "Union[ExtensionDtype, str, dtype[Any],
-    # Type[str], Type[float], Type[int], Type[complex], Type[bool], Type[object], None]"
-    def to_numpy(  # type: ignore[override]
+    def to_numpy(
         self,
-        dtype: NpDtype | None = None,
+        dtype: npt.DTypeLike | None = None,
         copy: bool = False,
         na_value=lib.no_default,
     ) -> np.ndarray:

pandas/core/base.py

@@ -516,16 +516,8 @@ def to_numpy(
         """
         if is_extension_array_dtype(self.dtype):
             # error: Too many arguments for "to_numpy" of "ExtensionArray"
-
-            # error: Argument 1 to "to_numpy" of "ExtensionArray" has incompatible type
-            # "Optional[Union[dtype[Any], None, type, _SupportsDType[dtype[Any]], str,
-            # Union[Tuple[Any, int], Tuple[Any, Union[SupportsIndex,
-            # Sequence[SupportsIndex]]], List[Any], _DTypeDict, Tuple[Any, Any]]]]";
-            # expected "Optional[Union[ExtensionDtype, Union[str, dtype[Any]],
-            # Type[str], Type[float], Type[int], Type[complex], Type[bool],
-            # Type[object]]]"
             return self.array.to_numpy(  # type: ignore[call-arg]
-                dtype, copy=copy, na_value=na_value, **kwargs  # type: ignore[arg-type]
+                dtype, copy=copy, na_value=na_value, **kwargs
             )
         elif kwargs:
             bad_keys = list(kwargs.keys())[0]