Fix product performance grouped JSON build
This commit is contained in:
M_Kececi
@@ -3804,10 +3804,10 @@ SELECT
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avg_stock_180d,
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avg_stock_365d,
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avg_stock_total,
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CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) ELSE 0 END AS stock_turnover_90d,
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CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) ELSE 0 END AS stock_turnover_180d,
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CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) * 4.0 ELSE 0 END AS stock_turnover_90d,
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CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) * 2.0 ELSE 0 END AS stock_turnover_180d,
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CASE WHEN avg_stock_365d > 0 THEN sales_qty_365d / NULLIF(avg_stock_365d,0) ELSE 0 END AS stock_turnover_365d,
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CASE WHEN avg_stock_total > 0 THEN sales_qty_total / NULLIF(avg_stock_total,0) ELSE 0 END AS stock_turnover_total,
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CASE WHEN avg_stock_total > 0 THEN sales_qty_total / NULLIF(avg_stock_total,0) * 360.0 / GREATEST(1, (current_date - DATE '2022-01-01') + 1) ELSE 0 END AS stock_turnover_total,
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has_cost,
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sales_index_90d,
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CASE WHEN NOT has_cost THEN 0 WHEN sales_usd_90d <= 0 THEN 1 ELSE
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@@ -3845,7 +3845,7 @@ SELECT
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CASE WHEN NOT has_cost THEN 0 WHEN sales_usd_90d <= 0 THEN 1 ELSE
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ROUND(
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LEAST(30, GREATEST(gross_margin_cost_90d,0) / 0.40 * 30)
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+ LEAST(20, (CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) ELSE 0 END) / 1.5 * 20)
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+ LEAST(20, (CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) * 4.0 ELSE 0 END) / 4.0 * 20)
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+ LEAST(20, sales_usd_90d / 10000 * 20)
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+ LEAST(15, market_count_90d / 8.0 * 15)
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+ LEAST(15, customer_count_90d / 25.0 * 15),
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@@ -4517,10 +4517,10 @@ SELECT (
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'stock_days_180d', stock_days_180d,
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'stock_days_365d', stock_days_365d,
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'stock_days_total', stock_days_total,
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'stock_turnover_90d', CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) ELSE 0 END,
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'stock_turnover_180d', CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) ELSE 0 END,
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'stock_turnover_90d', CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) * 4.0 ELSE 0 END,
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'stock_turnover_180d', CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) * 2.0 ELSE 0 END,
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'stock_turnover_365d', CASE WHEN avg_stock_365d > 0 THEN sales_qty_365d / NULLIF(avg_stock_365d,0) ELSE 0 END,
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'stock_turnover_total', CASE WHEN avg_stock_total > 0 THEN sales_qty_total / NULLIF(avg_stock_total,0) ELSE 0 END
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'stock_turnover_total', CASE WHEN avg_stock_total > 0 THEN sales_qty_total / NULLIF(avg_stock_total,0) * 360.0 / GREATEST(1, ((SELECT kpi_date FROM LatestKPIDate) - DATE '2022-01-01') + 1) ELSE 0 END
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)
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) AS row_json
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FROM (
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@@ -4643,10 +4643,10 @@ func queryProductPerformanceSQLLeafRows(ctx context.Context, pg *sql.DB, mode st
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query := productPerformanceSQLSourceCTE(mode) + fmt.Sprintf(`
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SELECT to_jsonb(t) || jsonb_build_object(
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'row_key', 'leaf|' || product_code || '|' || color_code || '|' || yaka_kodu || '|' || market_key,
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'stock_turnover_90d', CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) ELSE 0 END,
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'stock_turnover_180d', CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) ELSE 0 END,
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'stock_turnover_90d', CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) * 4.0 ELSE 0 END,
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'stock_turnover_180d', CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) * 2.0 ELSE 0 END,
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'stock_turnover_365d', CASE WHEN avg_stock_365d > 0 THEN sales_qty_365d / NULLIF(avg_stock_365d,0) ELSE 0 END,
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'stock_turnover_total', CASE WHEN avg_stock_total > 0 THEN sales_qty_total / NULLIF(avg_stock_total,0) ELSE 0 END
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'stock_turnover_total', CASE WHEN avg_stock_total > 0 THEN sales_qty_total / NULLIF(avg_stock_total,0) * 360.0 / GREATEST(1, ((SELECT kpi_date FROM LatestKPIDate) - DATE '2022-01-01') + 1) ELSE 0 END
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) AS row_json
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FROM Source t
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%s
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@@ -6000,11 +6000,7 @@ func deriveProductPerformanceGroupMetrics(out map[string]any, groupField string)
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} else if _, ok := out["stock_days_"+suffix]; !ok {
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out["stock_days_"+suffix] = 0
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}
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if turnoverBase > 0 {
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out["stock_turnover_"+suffix] = qty / turnoverBase
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} else {
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out["stock_turnover_"+suffix] = 0
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}
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out["stock_turnover_"+suffix] = productPerformanceAnnualizedStockTurnover(qty, turnoverBase, days)
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if qty > 0 {
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out["avg_price_usd_"+suffix] = sales / qty
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}
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@@ -6111,7 +6107,7 @@ func productPerformancePeriodDays(row map[string]any, suffix string) float64 {
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case "180d":
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return 180
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case "365d":
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return 365
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return 360
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case "total":
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start := parseProductPerformanceDate(stringFromMap(row, "period_start"))
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if start.IsZero() {
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@@ -6130,6 +6126,19 @@ func productPerformancePeriodDays(row map[string]any, suffix string) float64 {
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}
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}
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const productPerformanceStockTurnoverYearDays = 360.0
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func productPerformanceAnnualizedStockTurnover(salesQty, avgStock, periodDays float64) float64 {
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if salesQty <= 0 || avgStock <= 0 {
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return 0
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}
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raw := salesQty / avgStock
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if periodDays <= 0 {
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return raw
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}
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return raw * productPerformanceStockTurnoverYearDays / periodDays
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}
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func parseProductPerformanceDate(value string) time.Time {
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value = strings.TrimSpace(value)
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if value == "" {
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@@ -6206,8 +6215,12 @@ func productPerformanceSalesPeriodScore(row map[string]any, suffix string) float
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salesQty := floatFromMap(row, "sales_qty_"+suffix)
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stockTurnover := floatFromMap(row, "stock_turnover_"+suffix)
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if stockTurnover == 0 {
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if stockQty := floatFromMap(row, "stock_qty"); stockQty > 0 {
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stockTurnover = salesQty / stockQty
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avgStock := floatFromMap(row, "avg_stock_"+suffix)
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if avgStock <= 0 {
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avgStock = floatFromMap(row, "stock_qty")
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}
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if avgStock > 0 {
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stockTurnover = productPerformanceAnnualizedStockTurnover(salesQty, avgStock, productPerformancePeriodDays(row, suffix))
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}
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}
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return productPerformanceProductScore(
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@@ -6267,13 +6280,17 @@ func productPerformanceProductScore(suffix string, salesUSD, salesIndex, margin,
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}
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revenueScore := productPerformanceRevenueScore(suffix, salesUSD, salesIndex, productPerformanceProductRevenueTarget(suffix))
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score := 0.30*productPerformanceMarginComponentScore(margin) +
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0.20*productPerformanceRatioScore(stockTurnover, 1.50) +
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0.20*productPerformanceRatioScore(stockTurnover, productPerformanceStockTurnoverTarget(suffix)) +
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0.20*revenueScore +
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0.15*productPerformanceRatioScore(marketCount, 8) +
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0.15*productPerformanceRatioScore(customerCount, 25)
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return productPerformanceRoundScore(score)
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}
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func productPerformanceStockTurnoverTarget(suffix string) float64 {
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return 4
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}
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func productPerformanceCustomerScore(suffix string, salesUSD, margin, productGroupCount, salesQty float64) float64 {
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if salesUSD <= 0 {
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return 1
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