CLN: standardize values coercion in Blocks

pandas/core/internals/blocks.py

@@ -124,14 +124,28 @@ def _simple_new(
     def __init__(self, values, placement, ndim=None):
         self.ndim = self._check_ndim(values, ndim)
         self.mgr_locs = placement
-        self.values = values
+        self.values = self._maybe_coerce_values(values)
 
         if self._validate_ndim and self.ndim and len(self.mgr_locs) != len(self.values):
             raise ValueError(
                 f"Wrong number of items passed {len(self.values)}, "
                 f"placement implies {len(self.mgr_locs)}"
             )
 
+    def _maybe_coerce_values(self, values):
+        """
+        Ensure we have correctly-typed values.
+
+        Parameters
+        ----------
+        values : np.ndarray, ExtensionArray, Index
+
+        Returns
+        -------
+        np.ndarray or ExtensionArray
+        """
+        return values
+
     def _check_ndim(self, values, ndim):
         """
         ndim inference and validation.
@@ -1614,7 +1628,6 @@ def __init__(self, values, placement, ndim=None):
         This will call continue to call __init__ for the other base
         classes mixed in with this Mixin.
         """
-        values = self._maybe_coerce_values(values)
 
         # Placement must be converted to BlockPlacement so that we can check
         # its length
@@ -2109,10 +2122,6 @@ class DatetimeBlock(DatetimeLikeBlockMixin, Block):
     __slots__ = ()
     is_datetime = True
 
-    def __init__(self, values, placement, ndim=None):
-        values = self._maybe_coerce_values(values)
-        super().__init__(values, placement=placement, ndim=ndim)
-
     @property
     def _can_hold_na(self):
         return True
@@ -2366,14 +2375,14 @@ class TimeDeltaBlock(DatetimeLikeBlockMixin, IntBlock):
     is_numeric = False
     fill_value = np.timedelta64("NaT", "ns")
 
-    def __init__(self, values, placement, ndim=None):
+    def _maybe_coerce_values(self, values):
         if values.dtype != TD64NS_DTYPE:
             # e.g. non-nano or int64
             values = TimedeltaArray._from_sequence(values)._data
         if isinstance(values, TimedeltaArray):
             values = values._data
         assert isinstance(values, np.ndarray), type(values)
-        super().__init__(values, placement=placement, ndim=ndim)
+        return values
 
     @property
     def _holder(self):
@@ -2426,11 +2435,10 @@ class ObjectBlock(Block):
     is_object = True
     _can_hold_na = True
 
-    def __init__(self, values, placement=None, ndim=2):
+    def _maybe_coerce_values(self, values):
         if issubclass(values.dtype.type, str):
             values = np.array(values, dtype=object)
-
-        super().__init__(values, ndim=ndim, placement=placement)
+        return values
 
     @property
     def is_bool(self):