scalability framework: refactorings: extract methods

misc/python/materialize/scalability/comparison_outcome.py

@@ -41,6 +41,9 @@ def has_significant_improvements(self) -> bool:
         )
         return len(self.significant_improvements) > 0
 
+    def has_scalability_changes(self) -> bool:
+        return self.has_regressions() or self.has_significant_improvements()
+
     def __str__(self) -> str:
         return f"{len(self.regressions)} regressions, {len(self.significant_improvements)} significant improvements"
 
@@ -60,17 +63,31 @@ def _to_description(self, entries: Sequence[ScalabilityChange]) -> str:
         return "\n".join(f"* {x}" for x in entries)
 
     def merge(self, other: ComparisonOutcome) -> None:
-        self.regressions.extend(other.regressions)
-        self.significant_improvements.extend(other.significant_improvements)
-        self.append_regression_df(other.regression_df)
-        self.append_significant_improvement_df(other.significant_improvement_df)
+        self.append_regressions(
+            other.regressions,
+            other.significant_improvements,
+            other.regression_df,
+            other.significant_improvement_df,
+        )
+
+    def append_regressions(
+        self,
+        regressions: list[Regression],
+        significant_improvements: list[ScalabilityImprovement],
+        regression_df: DfTotalsExtended,
+        significant_improvement_df: DfTotalsExtended,
+    ) -> None:
+        self.regressions.extend(regressions)
+        self.significant_improvements.extend(significant_improvements)
+        self._append_regression_df(regression_df)
+        self._append_significant_improvement_df(significant_improvement_df)
 
-    def append_regression_df(self, regressions_data: DfTotalsExtended) -> None:
+    def _append_regression_df(self, regressions_data: DfTotalsExtended) -> None:
         self.regression_df = concat_df_totals_extended(
             [self.regression_df, regressions_data]
         )
 
-    def append_significant_improvement_df(
+    def _append_significant_improvement_df(
         self, significant_improvements_data: DfTotalsExtended
     ) -> None:
         self.significant_improvement_df = concat_df_totals_extended(

misc/python/materialize/scalability/result_analyzers.py

@@ -60,10 +60,10 @@ def perform_comparison_in_workload(
             workload_name,
             other_endpoint,
         )
-        comparison_outcome.regressions.extend(regressions)
-        comparison_outcome.significant_improvements.extend(improvements)
-        comparison_outcome.append_regression_df(entries_worse_than_threshold)
-        comparison_outcome.append_significant_improvement_df(
-            entries_better_than_threshold
+        comparison_outcome.append_regressions(
+            regressions,
+            improvements,
+            entries_worse_than_threshold,
+            entries_better_than_threshold,
         )
         return comparison_outcome

test/scalability/mzcompose.py

@@ -302,7 +302,7 @@ def report_regression_result(
 
     baseline_desc = endpoint_name_to_description(baseline_endpoint.try_load_version())
 
-    if outcome.has_regressions() or outcome.has_significant_improvements():
+    if outcome.has_scalability_changes():
         print(
             f"{'ERROR' if outcome.has_regressions() else 'INFO'}: "
             f"The following scalability changes were detected "