TYP: stricter typing of return value of to_numpy_dtype_inference helper function (pandas-dev#62284)

Author: jorisvandenbossche

pandas/core/arrays/_utils.py

@@ -15,49 +15,51 @@
 
 if TYPE_CHECKING:
     from pandas._typing import (
-        ArrayLike,
         npt,
     )
 
+    from pandas.core.arrays.base import ExtensionArray
+
 
 def to_numpy_dtype_inference(
-    arr: ArrayLike, dtype: npt.DTypeLike | None, na_value, hasna: bool
-) -> tuple[npt.DTypeLike, Any]:
+    arr: ExtensionArray, dtype: npt.DTypeLike | None, na_value, hasna: bool
+) -> tuple[np.dtype | None, Any]:
+    result_dtype: np.dtype | None
+    inferred_numeric_dtype = False
     if dtype is None and is_numeric_dtype(arr.dtype):
-        dtype_given = False
+        inferred_numeric_dtype = True
         if hasna:
             if arr.dtype.kind == "b":
-                dtype = np.dtype(np.object_)
+                result_dtype = np.dtype(np.object_)
             else:
                 if arr.dtype.kind in "iu":
-                    dtype = np.dtype(np.float64)
+                    result_dtype = np.dtype(np.float64)
                 else:
-                    dtype = arr.dtype.numpy_dtype  # type: ignore[union-attr]
+                    result_dtype = arr.dtype.numpy_dtype  # type: ignore[attr-defined]
                 if na_value is lib.no_default:
                     na_value = np.nan
         else:
-            dtype = arr.dtype.numpy_dtype  # type: ignore[union-attr]
+            result_dtype = arr.dtype.numpy_dtype  # type: ignore[attr-defined]
     elif dtype is not None:
-        dtype = np.dtype(dtype)
-        dtype_given = True
+        result_dtype = np.dtype(dtype)
     else:
-        dtype_given = True
+        result_dtype = None
 
     if na_value is lib.no_default:
-        if dtype is None or not hasna:
+        if result_dtype is None or not hasna:
             na_value = arr.dtype.na_value
-        elif dtype.kind == "f":  # type: ignore[union-attr]
+        elif result_dtype.kind == "f":
             na_value = np.nan
-        elif dtype.kind == "M":  # type: ignore[union-attr]
+        elif result_dtype.kind == "M":
             na_value = np.datetime64("nat")
-        elif dtype.kind == "m":  # type: ignore[union-attr]
+        elif result_dtype.kind == "m":
             na_value = np.timedelta64("nat")
         else:
             na_value = arr.dtype.na_value
 
-    if not dtype_given and hasna:
+    if inferred_numeric_dtype and hasna:
         try:
-            np_can_hold_element(dtype, na_value)  # type: ignore[arg-type]
+            np_can_hold_element(result_dtype, na_value)  # type: ignore[arg-type]
         except LossySetitemError:
-            dtype = np.dtype(np.object_)
-    return dtype, na_value
+            result_dtype = np.dtype(np.object_)
+    return result_dtype, na_value