Fix product performance grouped JSON build

svc/queries/product_performance.go

@@ -5229,15 +5229,30 @@ func productPerformanceGroupedRawSnapshotSourceRows(ctx context.Context, pg *sql
 		return nil, nil
 	}
 	if strings.TrimSpace(mode) == "idle" {
+		normalizeProductPerformanceGroupedSourceScores(rows, mode)
 		return productPerformanceIdleSourceRows(rows), nil
 	}
 	if mode == "products" || mode == "product_detail" {
 		rows = mergeProductPerformanceGeneralSnapshotMetrics(ctx, pg, rows)
 		rows = mergeProductPerformanceSalesSpreadKeys(ctx, pg, rows)
 	}
+	normalizeProductPerformanceGroupedSourceScores(rows, mode)
 	return rows, nil
 }
 
+func normalizeProductPerformanceGroupedSourceScores(rows []map[string]any, mode string) {
+	if !shouldCascadeProductPerformanceGroupedScores(mode) {
+		return
+	}
+	for _, row := range rows {
+		deriveProductPerformanceGroupMetrics(row, "")
+		for _, suffix := range productPerformancePeriodSuffixes() {
+			row["performance_score_"+suffix] = productPerformanceSalesPeriodScore(row, suffix)
+		}
+		row["performance_score"] = row["performance_score_90d"]
+	}
+}
+
 func mergeProductPerformanceGeneralSnapshotMetrics(ctx context.Context, pg *sql.DB, rows []map[string]any) []map[string]any {
 	if len(rows) == 0 {
 		return rows
@@ -5518,9 +5533,82 @@ func buildProductPerformanceGroupedSnapshotRows(sourceRows []map[string]any, lev
 
 	out := make([]map[string]any, 0, len(sourceRows))
 	appendProductPerformanceGroupedSnapshotNodes(&out, roots, rootOrder)
+	applyProductPerformanceGroupedChildScoreAverages(out, mode)
 	return out
 }
 
+func applyProductPerformanceGroupedChildScoreAverages(rows []map[string]any, mode string) {
+	if !shouldCascadeProductPerformanceGroupedScores(mode) || len(rows) == 0 {
+		return
+	}
+	byKey := make(map[string]map[string]any, len(rows))
+	children := map[string][]map[string]any{}
+	maxLevel := -1
+	for _, row := range rows {
+		key := stringFromMap(row, "key")
+		if key == "" {
+			continue
+		}
+		byKey[key] = row
+		if level := intFromMap(row, "level"); level > maxLevel {
+			maxLevel = level
+		}
+	}
+	for _, row := range rows {
+		key := stringFromMap(row, "key")
+		parentKey := productPerformanceParentGroupKey(key)
+		if parentKey == "" || byKey[parentKey] == nil {
+			continue
+		}
+		children[parentKey] = append(children[parentKey], row)
+	}
+	for level := maxLevel - 1; level >= 0; level-- {
+		for _, row := range rows {
+			if intFromMap(row, "level") != level {
+				continue
+			}
+			childRows := children[stringFromMap(row, "key")]
+			if len(childRows) == 0 {
+				continue
+			}
+			for _, suffix := range productPerformancePeriodSuffixes() {
+				field := "performance_score_" + suffix
+				if !productPerformanceRowsHaveField(childRows, field) {
+					continue
+				}
+				row[field] = weightedAverageProductPerformanceScoreRows(childRows, field, suffix)
+			}
+			if score, ok := productPerformanceOptionalFloat(row, "performance_score_90d"); ok {
+				row["performance_score"] = score
+			}
+		}
+	}
+}
+
+func shouldCascadeProductPerformanceGroupedScores(mode string) bool {
+	switch strings.TrimSpace(mode) {
+	case "products",
+		"product_detail",
+		"idle",
+		"sales_color_yaka_market_customer",
+		"sales_product_country_segment_market_customer",
+		"sales_market_customer_product",
+		"sales_country_segment_market_customer_product":
+		return true
+	default:
+		return false
+	}
+}
+
+func productPerformanceRowsHaveField(rows []map[string]any, field string) bool {
+	for _, row := range rows {
+		if _, ok := productPerformanceOptionalFloat(row, field); ok {
+			return true
+		}
+	}
+	return false
+}
+
 func (n *productPerformanceGroupedSnapshotNode) add(row map[string]any) {
 	n.Count++
 	if n.Image == nil && stringFromMap(row, "product_code") != "" {