ENH: implement EA._putmask

pandas/core/arrays/_mixins.py

@@ -310,7 +310,7 @@ def _wrap_reduction_result(self, axis: int | None, result):
     # ------------------------------------------------------------------------
     # __array_function__ methods
 
-    def putmask(self, mask: np.ndarray, value) -> None:
+    def _putmask(self, mask: npt.NDArray[np.bool_], value) -> None:
         """
         Analogue to np.putmask(self, mask, value)
 

pandas/core/arrays/base.py

@@ -1409,6 +1409,33 @@ def insert(self: ExtensionArrayT, loc: int, item) -> ExtensionArrayT:
 
         return type(self)._concat_same_type([self[:loc], item_arr, self[loc:]])
 
+    def _putmask(self, mask: npt.NDArray[np.bool_], value) -> None:
+        """
+        Analogue to np.putmask(self, mask, value)
+
+        Parameters
+        ----------
+        mask : np.ndarray[bool]
+        value : scalar or listlike
+            If listlike, must be arraylike with same length as self.
+
+        Returns
+        -------
+        None
+
+        Notes
+        -----
+        Unlike np.putmask, we do not repeat listlike values with mismatched length.
+        'value' should either be a scalar or an arraylike with the same length
+        as self.
+        """
+        if is_list_like(value):
+            val = value[mask]
+        else:
+            val = value
+
+        self[mask] = val
+
     def _where(
         self: ExtensionArrayT, mask: npt.NDArray[np.bool_], value
     ) -> ExtensionArrayT:

pandas/core/arrays/interval.py

@@ -36,6 +36,7 @@
     PositionalIndexer,
     ScalarIndexer,
     SequenceIndexer,
+    npt,
 )
 from pandas.compat.numpy import function as nv
 from pandas.util._decorators import Appender
@@ -1482,15 +1483,15 @@ def to_tuples(self, na_tuple=True) -> np.ndarray:
 
     # ---------------------------------------------------------------------
 
-    def putmask(self, mask: np.ndarray, value) -> None:
+    def _putmask(self, mask: npt.NDArray[np.bool_], value) -> None:
         value_left, value_right = self._validate_setitem_value(value)
 
         if isinstance(self._left, np.ndarray):
             np.putmask(self._left, mask, value_left)
             np.putmask(self._right, mask, value_right)
         else:
-            self._left.putmask(mask, value_left)
-            self._right.putmask(mask, value_right)
+            self._left._putmask(mask, value_left)
+            self._right._putmask(mask, value_right)
 
     def insert(self: IntervalArrayT, loc: int, item: Interval) -> IntervalArrayT:
         """

pandas/core/indexes/base.py

@@ -4444,8 +4444,7 @@ def _join_non_unique(
         if isinstance(join_array, np.ndarray):
             np.putmask(join_array, mask, right)
         else:
-            # error: "ExtensionArray" has no attribute "putmask"
-            join_array.putmask(mask, right)  # type: ignore[attr-defined]
+            join_array._putmask(mask, right)
 
         join_index = self._wrap_joined_index(join_array, other)
 
@@ -5051,8 +5050,7 @@ def putmask(self, mask, value) -> Index:
         else:
             # Note: we use the original value here, not converted, as
             #  _validate_fill_value is not idempotent
-            # error: "ExtensionArray" has no attribute "putmask"
-            values.putmask(mask, value)  # type: ignore[attr-defined]
+            values._putmask(mask, value)
 
         return self._shallow_copy(values)
 

pandas/core/internals/blocks.py

@@ -1415,15 +1415,13 @@ def putmask(self, mask, new) -> list[Block]:
 
         new_values = self.values
 
-        if isinstance(new, (np.ndarray, ExtensionArray)) and len(new) == len(mask):
-            new = new[mask]
-
         if mask.ndim == new_values.ndim + 1:
             # TODO(EA2D): unnecessary with 2D EAs
             mask = mask.reshape(new_values.shape)
 
         try:
-            new_values[mask] = new
+            # Caller is responsible for ensuring matching lengths
+            new_values._putmask(mask, new)
         except TypeError:
             if not is_interval_dtype(self.dtype):
                 # Discussion about what we want to support in the general
@@ -1704,7 +1702,7 @@ def putmask(self, mask, new) -> list[Block]:
             return self.coerce_to_target_dtype(new).putmask(mask, new)
 
         arr = self.values
-        arr.T.putmask(mask, new)
+        arr.T._putmask(mask, new)
         return [self]
 
     def where(self, other, cond) -> list[Block]: