REF: De-duplicate agg_series

pandas/core/groupby/generic.py

@@ -1686,7 +1686,7 @@ def _insert_inaxis_grouper_inplace(self, result: DataFrame) -> None:
 
     def _wrap_aggregated_output(
         self,
-        output: Mapping[base.OutputKey, Series | np.ndarray],
+        output: Mapping[base.OutputKey, Series | ArrayLike],
     ) -> DataFrame:
         """
         Wraps the output of DataFrameGroupBy aggregations into the expected result.

pandas/core/groupby/groupby.py

@@ -1056,7 +1056,7 @@ def _set_result_index_ordered(
 
         return result
 
-    def _wrap_aggregated_output(self, output: Mapping[base.OutputKey, np.ndarray]):
+    def _wrap_aggregated_output(self, output: Mapping[base.OutputKey, ArrayLike]):
         raise AbstractMethodError(self)
 
     def _wrap_transformed_output(self, output: Mapping[base.OutputKey, ArrayLike]):
@@ -1222,7 +1222,7 @@ def _python_agg_general(self, func, *args, **kwargs):
         f = lambda x: func(x, *args, **kwargs)
 
         # iterate through "columns" ex exclusions to populate output dict
-        output: dict[base.OutputKey, np.ndarray] = {}
+        output: dict[base.OutputKey, ArrayLike] = {}
 
         for idx, obj in enumerate(self._iterate_slices()):
             name = obj.name

pandas/core/groupby/ops.py

@@ -923,7 +923,8 @@ def _cython_operation(
             **kwargs,
         )
 
-    def agg_series(self, obj: Series, func: F):
+    @final
+    def agg_series(self, obj: Series, func: F) -> tuple[ArrayLike, np.ndarray]:
         # Caller is responsible for checking ngroups != 0
         assert self.ngroups != 0
 
@@ -952,8 +953,9 @@ def agg_series(self, obj: Series, func: F):
                 raise
         return self._aggregate_series_pure_python(obj, func)
 
-    @final
-    def _aggregate_series_fast(self, obj: Series, func: F):
+    def _aggregate_series_fast(
+        self, obj: Series, func: F
+    ) -> tuple[ArrayLike, np.ndarray]:
         # At this point we have already checked that
         #  - obj.index is not a MultiIndex
         #  - obj is backed by an ndarray, not ExtensionArray
@@ -1157,18 +1159,14 @@ def groupings(self) -> list[grouper.Grouping]:
             for lvl, name in zip(self.levels, self.names)
         ]
 
-    def agg_series(self, obj: Series, func: F):
-        # Caller is responsible for checking ngroups != 0
-        assert self.ngroups != 0
-        assert len(self.bins) > 0  # otherwise we'd get IndexError in get_result
-
-        if is_extension_array_dtype(obj.dtype):
-            # preempt SeriesBinGrouper from raising TypeError
-            return self._aggregate_series_pure_python(obj, func)
-
-        elif obj.index._has_complex_internals:
-            return self._aggregate_series_pure_python(obj, func)
-
+    def _aggregate_series_fast(
+        self, obj: Series, func: F
+    ) -> tuple[ArrayLike, np.ndarray]:
+        # At this point we have already checked that
+        #  - obj.index is not a MultiIndex
+        #  - obj is backed by an ndarray, not ExtensionArray
+        #  - ngroups != 0
+        #  - len(self.bins) > 0
         grouper = libreduction.SeriesBinGrouper(obj, func, self.bins)
         return grouper.get_result()