REF: implement _rebox_native

pandas/core/arrays/datetimelike.py

@@ -175,6 +175,14 @@ def _scalar_from_string(self, value: str) -> DTScalarOrNaT:
         """
         raise AbstractMethodError(self)
 
+    @classmethod
+    def _rebox_native(cls, value: int) -> Union[int, np.datetime64, np.timedelta64]:
+        """
+        Box an integer unboxed via _unbox_scalar into the native type for
+        the underlying ndarray.
+        """
+        raise AbstractMethodError(cls)
+
     def _unbox_scalar(self, value: DTScalarOrNaT) -> int:
         """
         Unbox the integer value of a scalar `value`.
@@ -464,7 +472,9 @@ def _ndarray(self) -> np.ndarray:
 
     def _from_backing_data(self: _T, arr: np.ndarray) -> _T:
         # Note: we do not retain `freq`
-        return type(self)._simple_new(arr, dtype=self.dtype)
+        return type(self)._simple_new(  # type: ignore[attr-defined]
+            arr, dtype=self.dtype
+        )
 
     # ------------------------------------------------------------------
 
@@ -717,7 +727,7 @@ def _validate_fill_value(self, fill_value):
 
         Returns
         -------
-        fill_value : np.int64
+        fill_value : np.int64, np.datetime64, or np.timedelta64
 
         Raises
         ------
@@ -732,12 +742,7 @@ def _validate_fill_value(self, fill_value):
         except TypeError as err:
             raise ValueError(msg) from err
         rv = self._unbox(fill_value)
-        if self.dtype.kind == "M":
-            return np.int64(rv).view("M8[ns]")
-        elif self.dtype.kind == "m":
-            return np.int64(rv).view("m8[ns]")
-        else:
-            return rv
+        return self._rebox_native(rv)
 
     def _validate_shift_value(self, fill_value):
         # TODO(2.0): once this deprecation is enforced, use _validate_fill_value

pandas/core/arrays/datetimes.py

@@ -446,6 +446,10 @@ def _generate_range(
     # -----------------------------------------------------------------
     # DatetimeLike Interface
 
+    @classmethod
+    def _rebox_native(cls, value: int) -> np.datetime64:
+        return np.int64(value).view("M8[ns]")
+
     def _unbox_scalar(self, value):
         if not isinstance(value, self._scalar_type) and value is not NaT:
             raise ValueError("'value' should be a Timestamp.")

pandas/core/arrays/period.py

@@ -253,6 +253,10 @@ def _generate_range(cls, start, end, periods, freq, fields):
     # -----------------------------------------------------------------
     # DatetimeLike Interface
 
+    @classmethod
+    def _rebox_native(cls, value: int) -> np.int64:
+        return np.int64(value)
+
     def _unbox_scalar(self, value: Union[Period, NaTType]) -> int:
         if value is NaT:
             return value.value

pandas/core/arrays/timedeltas.py

@@ -271,6 +271,10 @@ def _generate_range(cls, start, end, periods, freq, closed=None):
     # ----------------------------------------------------------------
     # DatetimeLike Interface
 
+    @classmethod
+    def _rebox_native(cls, value: int) -> np.timedelta64:
+        return np.int64(value).view("m8[ns]")
+
     def _unbox_scalar(self, value):
         if not isinstance(value, self._scalar_type) and value is not NaT:
             raise ValueError("'value' should be a Timedelta.")