REGR: Remove groupby's __getattribute__ for nth (pandas-dev#49676)

doc/source/whatsnew/v1.5.2.rst

@@ -18,6 +18,7 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.plot` preventing :class:`~matplotlib.colors.Colormap` instance
   from being passed using the ``colormap`` argument if Matplotlib 3.6+ is used (:issue:`49374`)
 - Fixed regression in :func:`date_range` returning an invalid set of periods for ``CustomBusinessDay`` frequency and ``start`` date with timezone (:issue:`49441`)
+- Fixed performance regression in groupby operations (:issue:`49676`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/groupby/groupby.py

@@ -984,15 +984,6 @@ def __getattr__(self, attr: str):
             f"'{type(self).__name__}' object has no attribute '{attr}'"
         )
 
-    def __getattribute__(self, attr: str):
-        # Intercept nth to allow both call and index
-        if attr == "nth":
-            return GroupByNthSelector(self)
-        elif attr == "nth_actual":
-            return super().__getattribute__("nth")
-        else:
-            return super().__getattribute__(attr)
-
     @final
     def _op_via_apply(self, name: str, *args, **kwargs):
         """Compute the result of an operation by using GroupBy's apply."""
@@ -2936,13 +2927,10 @@ def bfill(self, limit=None):
         return self._fill("bfill", limit=limit)
 
     @final
+    @property
     @Substitution(name="groupby")
     @Substitution(see_also=_common_see_also)
-    def nth(
-        self,
-        n: PositionalIndexer | tuple,
-        dropna: Literal["any", "all", None] = None,
-    ) -> NDFrameT:
+    def nth(self) -> GroupByNthSelector:
         """
         Take the nth row from each group if n is an int, otherwise a subset of rows.
 
@@ -3030,6 +3018,13 @@ def nth(
         Columns: [A, B]
         Index: []
         """
+        return GroupByNthSelector(self)
+
+    def _nth(
+        self,
+        n: PositionalIndexer | tuple,
+        dropna: Literal["any", "all", None] = None,
+    ) -> NDFrameT:
         if not dropna:
             mask = self._make_mask_from_positional_indexer(n)
 

pandas/core/groupby/indexing.py

@@ -297,7 +297,7 @@ def __call__(
         n: PositionalIndexer | tuple,
         dropna: Literal["any", "all", None] = None,
     ) -> DataFrame | Series:
-        return self.groupby_object.nth_actual(n, dropna)
+        return self.groupby_object._nth(n, dropna)
 
     def __getitem__(self, n: PositionalIndexer | tuple) -> DataFrame | Series:
-        return self.groupby_object.nth_actual(n)
+        return self.groupby_object._nth(n)