REF: eliminate statefulness in FrameApply

pandas/core/apply.py

@@ -1,6 +1,6 @@
 import abc
 import inspect
-from typing import TYPE_CHECKING, Any, Dict, Iterator, Optional, Type, Union
+from typing import TYPE_CHECKING, Any, Dict, Iterator, Tuple, Type, Union
 
 import numpy as np
 
@@ -72,7 +72,9 @@ def series_generator(self) -> Iterator["Series"]:
         pass
 
     @abc.abstractmethod
-    def wrap_results_for_axis(self, results: ResType) -> Union["Series", "DataFrame"]:
+    def wrap_results_for_axis(
+        self, results: ResType, res_index: "Index"
+    ) -> Union["Series", "DataFrame"]:
         pass
 
     # ---------------------------------------------------------------
@@ -112,15 +114,6 @@ def f(x):
 
         self.f = f
 
-        # results
-        self.result = None
-        self._res_index: Optional["Index"] = None
-
-    @property
-    def res_index(self) -> "Index":
-        assert self._res_index is not None
-        return self._res_index
-
     @property
     def res_columns(self) -> "Index":
         return self.result_columns
@@ -313,12 +306,12 @@ def apply_standard(self):
                 return self.obj._constructor_sliced(result, index=labels)
 
         # compute the result using the series generator
-        results = self.apply_series_generator()
+        results, res_index = self.apply_series_generator()
 
         # wrap results
-        return self.wrap_results(results)
+        return self.wrap_results(results, res_index)
 
-    def apply_series_generator(self) -> ResType:
+    def apply_series_generator(self) -> Tuple[ResType, "Index"]:
         series_gen = self.series_generator
         res_index = self.result_index
 
@@ -345,19 +338,20 @@ def apply_series_generator(self) -> ResType:
                 results[i] = self.f(v)
                 keys.append(v.name)
 
-        self._res_index = res_index
-        return results
+        return results, res_index
 
-    def wrap_results(self, results: ResType) -> Union["Series", "DataFrame"]:
+    def wrap_results(
+        self, results: ResType, res_index: "Index"
+    ) -> Union["Series", "DataFrame"]:
 
         # see if we can infer the results
         if len(results) > 0 and 0 in results and is_sequence(results[0]):
 
-            return self.wrap_results_for_axis(results)
+            return self.wrap_results_for_axis(results, res_index)
 
         # dict of scalars
         result = self.obj._constructor_sliced(results)
-        result.index = self.res_index
+        result.index = res_index
 
         return result
 
@@ -380,7 +374,9 @@ def result_index(self) -> "Index":
     def result_columns(self) -> "Index":
         return self.index
 
-    def wrap_results_for_axis(self, results: ResType) -> "DataFrame":
+    def wrap_results_for_axis(
+        self, results: ResType, res_index: "Index"
+    ) -> "DataFrame":
         """ return the results for the rows """
 
         result = self.obj._constructor(data=results)
@@ -389,8 +385,8 @@ def wrap_results_for_axis(self, results: ResType) -> "DataFrame":
             if len(result.index) == len(self.res_columns):
                 result.index = self.res_columns
 
-        if len(result.columns) == len(self.res_index):
-            result.columns = self.res_index
+        if len(result.columns) == len(res_index):
+            result.columns = res_index
 
         return result
 
@@ -418,35 +414,37 @@ def result_index(self) -> "Index":
     def result_columns(self) -> "Index":
         return self.columns
 
-    def wrap_results_for_axis(self, results: ResType) -> Union["Series", "DataFrame"]:
+    def wrap_results_for_axis(
+        self, results: ResType, res_index: "Index"
+    ) -> Union["Series", "DataFrame"]:
         """ return the results for the columns """
         result: Union["Series", "DataFrame"]
 
         # we have requested to expand
         if self.result_type == "expand":
-            result = self.infer_to_same_shape(results)
+            result = self.infer_to_same_shape(results, res_index)
 
         # we have a non-series and don't want inference
         elif not isinstance(results[0], ABCSeries):
             from pandas import Series
 
             result = Series(results)
-            result.index = self.res_index
+            result.index = res_index
 
         # we may want to infer results
         else:
-            result = self.infer_to_same_shape(results)
+            result = self.infer_to_same_shape(results, res_index)
 
         return result
 
-    def infer_to_same_shape(self, results: ResType) -> "DataFrame":
+    def infer_to_same_shape(self, results: ResType, res_index: "Index") -> "DataFrame":
         """ infer the results to the same shape as the input object """
 
         result = self.obj._constructor(data=results)
         result = result.T
 
         # set the index
-        result.index = self.res_index
+        result.index = res_index
 
         # infer dtypes
         result = result.infer_objects()