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20 Commits
Author SHA1 Message Date
M_Kececi 474904481f Fix product performance grouped JSON build 2026-08-18 13:38:32 +03:00
M_Kececi 6eaf0e3ed3 Fix product performance grouped JSON build 2026-08-18 13:23:10 +03:00
M_Kececi 8249761415 Fix product performance grouped JSON build 2026-08-18 13:10:11 +03:00
M_Kececi dbd84f7399 Fix product performance grouped JSON build 2026-08-18 13:04:50 +03:00
M_Kececi 9edc806345 Fix product performance grouped JSON build 2026-08-18 12:45:11 +03:00
M_Kececi 7a7008cc1b Fix product performance grouped JSON build 2026-07-14 00:18:23 +03:00
M_Kececi 3e0253f6be Fix product performance grouped JSON build 2026-07-13 22:43:51 +03:00
M_Kececi b80b5024f4 Fix product performance grouped JSON build 2026-07-13 21:55:17 +03:00
M_Kececi 5eaf8be9e6 Fix product performance grouped JSON build 2026-07-12 16:15:41 +03:00
M_Kececi cc2930caf2 Fix product performance grouped JSON build 2026-07-09 16:41:41 +03:00
M_Kececi 26b4a63c45 Fix product performance grouped JSON build 2026-07-07 23:51:29 +03:00
M_Kececi c6a3d1552e Fix product performance grouped JSON build 2026-07-07 12:59:19 +03:00
M_Kececi 005d2eafac Fix product performance grouped JSON build 2026-07-07 01:21:07 +03:00
M_Kececi 289f204752 Fix product performance grouped JSON build 2026-07-06 18:01:34 +03:00
M_Kececi 1448dab9d7 Fix product performance grouped JSON build 2026-07-06 17:01:39 +03:00
M_Kececi 5d4216d42e Fix product performance grouped JSON build 2026-07-06 16:54:36 +03:00
M_Kececi 3993c363cb Fix product performance grouped JSON build 2026-07-06 01:28:44 +03:00
M_Kececi a0da3f2bed Fix product performance grouped JSON build 2026-07-06 00:53:30 +03:00
M_Kececi 19a42e0551 Merge remote-tracking branch 'origin/master' 2026-07-05 23:43:20 +03:00
M_Kececi 53cdd1a4a1 Fix product performance grouped JSON build 2026-07-05 23:43:17 +03:00
14 changed files with 1804 additions and 533 deletions
+1
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@@ -1,6 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<module type="WEB_MODULE" version="4">
<component name="Go" enabled="true" />
<component name="GoModuleSettings" enabled="true" />
<component name="NewModuleRootManager">
<content url="file://$MODULE_DIR$" />
<orderEntry type="inheritedJdk" />
+21
View File
@@ -227,6 +227,7 @@ InitRoutes — FULL V3 (Method-aware) PERMISSION EDITION
func InitRoutes(pgDB *sql.DB, mssql *sql.DB, ml *mailer.GraphMailer) *mux.Router {
r := mux.NewRouter()
mountUploads(r)
mountSPA(r)
/*
@@ -1517,6 +1518,26 @@ func main() {
}
func mountUploads(r *mux.Router) {
root := strings.TrimSpace(os.Getenv("BLOB_ROOT"))
if root == "" {
return
}
uploadsRoot := filepath.Join(root, "uploads")
if fi, err := os.Stat(uploadsRoot); err != nil || !fi.IsDir() {
return
}
fileServer := http.StripPrefix("/uploads/", http.FileServer(http.Dir(uploadsRoot)))
r.PathPrefix("/uploads/").Handler(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.Method != http.MethodGet && r.Method != http.MethodHead {
http.Error(w, "method not allowed", http.StatusMethodNotAllowed)
return
}
w.Header().Set("Cache-Control", "public, max-age=3600")
fileServer.ServeHTTP(w, r)
})).Methods(http.MethodGet, http.MethodHead, http.MethodOptions)
}
func mountSPA(r *mux.Router) {
r.NotFoundHandler = http.HandlerFunc(spaIndex)
r.HandleFunc("/", spaIndex).Methods(http.MethodGet)
+83 -62
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@@ -1,68 +1,85 @@
package models
type ProductPerformanceRow struct {
KpiDate string `json:"kpi_date"`
ProductCode string `json:"product_code"`
ColorCode string `json:"color_code"`
ColorDescription string `json:"color_description"`
YakaKodu string `json:"yaka_kodu"`
ItemDescription string `json:"item_description"`
Kategori string `json:"kategori"`
Seri string `json:"seri"`
YasGrubu string `json:"yas_grubu"`
AskiliYan string `json:"askili_yan"`
UrunIlkGrubu string `json:"urun_ilk_grubu"`
UrunAnaGrubu string `json:"urun_ana_grubu"`
UrunAltGrubu string `json:"urun_alt_grubu"`
MarketKey string `json:"market_key"`
StockQty float64 `json:"stock_qty"`
SalesQty30 float64 `json:"sales_qty_30d"`
SalesQty90 float64 `json:"sales_qty_90d"`
SalesQty180 float64 `json:"sales_qty_180d"`
SalesQty365 float64 `json:"sales_qty_365d"`
SalesQty730 float64 `json:"sales_qty_730d"`
SalesQtyTotal float64 `json:"sales_qty_total"`
SalesUSD30 float64 `json:"sales_usd_30d"`
SalesUSD90 float64 `json:"sales_usd_90d"`
SalesUSD180 float64 `json:"sales_usd_180d"`
SalesUSD365 float64 `json:"sales_usd_365d"`
SalesUSDTotal float64 `json:"sales_usd_total"`
AvgDailySales90 float64 `json:"avg_daily_sales_90d"`
AvgDailySales180 float64 `json:"avg_daily_sales_180d"`
AvgDailySales365 float64 `json:"avg_daily_sales_365d"`
AvgDailySalesTotal float64 `json:"avg_daily_sales_total"`
StockDays90 float64 `json:"stock_days_90d"`
StockDays180 float64 `json:"stock_days_180d"`
StockDays365 float64 `json:"stock_days_365d"`
StockDaysTotal float64 `json:"stock_days_total"`
StockTurnover90 float64 `json:"stock_turnover_90d"`
StockTurnover180 float64 `json:"stock_turnover_180d"`
StockTurnover365 float64 `json:"stock_turnover_365d"`
StockTurnoverTotal float64 `json:"stock_turnover_total"`
AvgPriceUSD90 float64 `json:"avg_price_usd_90d"`
AvgPriceUSD180 float64 `json:"avg_price_usd_180d"`
CostPriceUSD float64 `json:"cost_price_usd"`
BasePriceUSD float64 `json:"base_price_usd"`
BasePriceTRY float64 `json:"base_price_try"`
GrossProfitUSD90 float64 `json:"gross_profit_usd_90d"`
GrossProfitUSD180 float64 `json:"gross_profit_usd_180d"`
GrossMargin90 float64 `json:"gross_margin_90d"`
GrossMargin180 float64 `json:"gross_margin_180d"`
UnitProfitCost90 float64 `json:"unit_profit_cost_90d"`
UnitProfitCost180 float64 `json:"unit_profit_cost_180d"`
UnitProfitBase90 float64 `json:"unit_profit_base_90d"`
UnitProfitBase180 float64 `json:"unit_profit_base_180d"`
MarketCount90 int `json:"market_count_90d"`
CustomerCount90 int `json:"customer_count_90d"`
SalesIndex90 float64 `json:"sales_index_90d"`
PriceIndex90 float64 `json:"price_index_90d"`
MarginIndex90 float64 `json:"margin_index_90d"`
PerformanceScore float64 `json:"performance_score"`
PerformanceBucket string `json:"performance_bucket"`
Recommendation string `json:"recommendation"`
LastSaleDate string `json:"last_sale_date"`
LastRefNumber string `json:"last_ref_number"`
UpdatedAt string `json:"updated_at"`
KpiDate string `json:"kpi_date"`
ProductCode string `json:"product_code"`
ColorCode string `json:"color_code"`
ColorDescription string `json:"color_description"`
YakaKodu string `json:"yaka_kodu"`
ItemDescription string `json:"item_description"`
Kategori string `json:"kategori"`
Seri string `json:"seri"`
YasGrubu string `json:"yas_grubu"`
AskiliYan string `json:"askili_yan"`
UrunIlkGrubu string `json:"urun_ilk_grubu"`
UrunAnaGrubu string `json:"urun_ana_grubu"`
UrunAltGrubu string `json:"urun_alt_grubu"`
MarketKey string `json:"market_key"`
StockQty float64 `json:"stock_qty"`
SalesQty30 float64 `json:"sales_qty_30d"`
SalesQty90 float64 `json:"sales_qty_90d"`
SalesQty180 float64 `json:"sales_qty_180d"`
SalesQty365 float64 `json:"sales_qty_365d"`
SalesQty730 float64 `json:"sales_qty_730d"`
SalesQtyTotal float64 `json:"sales_qty_total"`
SalesUSD30 float64 `json:"sales_usd_30d"`
SalesUSD90 float64 `json:"sales_usd_90d"`
SalesUSD180 float64 `json:"sales_usd_180d"`
SalesUSD365 float64 `json:"sales_usd_365d"`
SalesUSDTotal float64 `json:"sales_usd_total"`
AvgDailySales90 float64 `json:"avg_daily_sales_90d"`
AvgDailySales180 float64 `json:"avg_daily_sales_180d"`
AvgDailySales365 float64 `json:"avg_daily_sales_365d"`
AvgDailySalesTotal float64 `json:"avg_daily_sales_total"`
AvgStock90 float64 `json:"avg_stock_90d"`
AvgStock180 float64 `json:"avg_stock_180d"`
AvgStock365 float64 `json:"avg_stock_365d"`
AvgStockTotal float64 `json:"avg_stock_total"`
StockDays90 float64 `json:"stock_days_90d"`
StockDays180 float64 `json:"stock_days_180d"`
StockDays365 float64 `json:"stock_days_365d"`
StockDaysTotal float64 `json:"stock_days_total"`
StockTurnover90 float64 `json:"stock_turnover_90d"`
StockTurnover180 float64 `json:"stock_turnover_180d"`
StockTurnover365 float64 `json:"stock_turnover_365d"`
StockTurnoverTotal float64 `json:"stock_turnover_total"`
AvgPriceUSD90 float64 `json:"avg_price_usd_90d"`
AvgPriceUSD180 float64 `json:"avg_price_usd_180d"`
CostPriceUSD float64 `json:"cost_price_usd"`
BasePriceUSD float64 `json:"base_price_usd"`
BasePriceTRY float64 `json:"base_price_try"`
GrossProfitUSD90 float64 `json:"gross_profit_usd_90d"`
GrossProfitUSD180 float64 `json:"gross_profit_usd_180d"`
GrossMargin90 float64 `json:"gross_margin_90d"`
GrossMargin180 float64 `json:"gross_margin_180d"`
UnitProfitCost90 float64 `json:"unit_profit_cost_90d"`
UnitProfitCost180 float64 `json:"unit_profit_cost_180d"`
UnitProfitBase90 float64 `json:"unit_profit_base_90d"`
UnitProfitBase180 float64 `json:"unit_profit_base_180d"`
MarketCount90 int `json:"market_count_90d"`
MarketCount180 int `json:"market_count_180d"`
MarketCount365 int `json:"market_count_365d"`
MarketCountTotal int `json:"market_count_total"`
CustomerCount90 int `json:"customer_count_90d"`
CustomerCount180 int `json:"customer_count_180d"`
CustomerCount365 int `json:"customer_count_365d"`
CustomerCountTotal int `json:"customer_count_total"`
SalesIndex90 float64 `json:"sales_index_90d"`
SalesIndex180 float64 `json:"sales_index_180d"`
SalesIndex365 float64 `json:"sales_index_365d"`
SalesIndexTotal float64 `json:"sales_index_total"`
PriceIndex90 float64 `json:"price_index_90d"`
MarginIndex90 float64 `json:"margin_index_90d"`
PerformanceScore90 float64 `json:"performance_score_90d"`
PerformanceScore180 float64 `json:"performance_score_180d"`
PerformanceScore365 float64 `json:"performance_score_365d"`
PerformanceScoreTotal float64 `json:"performance_score_total"`
PerformanceScore float64 `json:"performance_score"`
PerformanceBucket string `json:"performance_bucket"`
Recommendation string `json:"recommendation"`
LastSaleDate string `json:"last_sale_date"`
LastRefNumber string `json:"last_ref_number"`
UpdatedAt string `json:"updated_at"`
}
type ProductPerformanceSummary struct {
@@ -378,6 +395,10 @@ type ProductPerformanceSalesBreakdownRow struct {
GrossMarginBaseTotal float64 `json:"gross_margin_base_total"`
GrossMarginCostTotal float64 `json:"gross_margin_cost_total"`
StockQty float64 `json:"stock_qty"`
AvgStock90 float64 `json:"avg_stock_90d"`
AvgStock180 float64 `json:"avg_stock_180d"`
AvgStock365 float64 `json:"avg_stock_365d"`
AvgStockTotal float64 `json:"avg_stock_total"`
StockTurnover90 float64 `json:"stock_turnover_90d"`
StockTurnover180 float64 `json:"stock_turnover_180d"`
StockTurnover365 float64 `json:"stock_turnover_365d"`
+843 -226
View File
@@ -481,6 +481,10 @@ CREATE TABLE IF NOT EXISTS mk_product_performance_kpi_daily (
sales_usd_365d NUMERIC(18,4) NOT NULL DEFAULT 0,
avg_daily_sales_90d NUMERIC(18,6) NOT NULL DEFAULT 0,
avg_daily_sales_180d NUMERIC(18,6) NOT NULL DEFAULT 0,
avg_stock_90d NUMERIC(18,6) NOT NULL DEFAULT 0,
avg_stock_180d NUMERIC(18,6) NOT NULL DEFAULT 0,
avg_stock_365d NUMERIC(18,6) NOT NULL DEFAULT 0,
avg_stock_total NUMERIC(18,6) NOT NULL DEFAULT 0,
stock_days_90d NUMERIC(18,6) NOT NULL DEFAULT 0,
stock_days_180d NUMERIC(18,6) NOT NULL DEFAULT 0,
avg_price_usd_90d NUMERIC(18,6) NOT NULL DEFAULT 0,
@@ -497,8 +501,17 @@ CREATE TABLE IF NOT EXISTS mk_product_performance_kpi_daily (
unit_profit_base_90d NUMERIC(18,6) NOT NULL DEFAULT 0,
unit_profit_base_180d NUMERIC(18,6) NOT NULL DEFAULT 0,
market_count_90d INTEGER NOT NULL DEFAULT 0,
market_count_180d INTEGER NOT NULL DEFAULT 0,
market_count_365d INTEGER NOT NULL DEFAULT 0,
market_count_total INTEGER NOT NULL DEFAULT 0,
customer_count_90d INTEGER NOT NULL DEFAULT 0,
customer_count_180d INTEGER NOT NULL DEFAULT 0,
customer_count_365d INTEGER NOT NULL DEFAULT 0,
customer_count_total INTEGER NOT NULL DEFAULT 0,
sales_index_90d NUMERIC(18,6) NOT NULL DEFAULT 0,
sales_index_180d NUMERIC(18,6) NOT NULL DEFAULT 0,
sales_index_365d NUMERIC(18,6) NOT NULL DEFAULT 0,
sales_index_total NUMERIC(18,6) NOT NULL DEFAULT 0,
price_index_90d NUMERIC(18,6) NOT NULL DEFAULT 0,
margin_index_90d NUMERIC(18,6) NOT NULL DEFAULT 0,
performance_score NUMERIC(18,6) NOT NULL DEFAULT 0,
@@ -552,6 +565,10 @@ WHERE btrim(askili_yan) = '-'`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS avg_daily_sales_180d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS avg_daily_sales_365d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS avg_daily_sales_total NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS avg_stock_90d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS avg_stock_180d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS avg_stock_365d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS avg_stock_total NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS stock_days_180d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS stock_days_365d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS stock_days_total NUMERIC(18,6) NOT NULL DEFAULT 0`,
@@ -567,6 +584,15 @@ WHERE btrim(askili_yan) = '-'`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS unit_profit_base_90d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS unit_profit_base_180d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS market_count_90d INTEGER NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS market_count_180d INTEGER NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS market_count_365d INTEGER NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS market_count_total INTEGER NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS customer_count_180d INTEGER NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS customer_count_365d INTEGER NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS customer_count_total INTEGER NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS sales_index_180d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS sales_index_365d NUMERIC(18,6) NOT NULL DEFAULT 0`,
`ALTER TABLE mk_product_performance_kpi_daily ADD COLUMN IF NOT EXISTS sales_index_total NUMERIC(18,6) NOT NULL DEFAULT 0`,
`
CREATE TABLE IF NOT EXISTS mk_product_performance_report_snapshot (
report_key TEXT NOT NULL,
@@ -1072,6 +1098,9 @@ func RebuildProductPerformanceGroupedSnapshots(ctx context.Context, pg *sql.DB)
return 0, err
}
log.Printf("[ProductPerformanceRefresh] grouped snapshot definitions ready count=%d", len(defs))
if err := deleteStaleProductPerformanceGroupedSnapshots(ctx, pg, productPerformanceSnapshotKey("grouped", "product_detail")+":%"); err != nil {
return 0, err
}
total := 0
for i, def := range defs {
started := time.Now()
@@ -1107,41 +1136,33 @@ func RebuildProductPerformanceGroupedSnapshots(ctx context.Context, pg *sql.DB)
return total, nil
}
func deleteStaleProductPerformanceGroupedSnapshots(ctx context.Context, pg *sql.DB, reportKeyLike string) error {
reportKeyLike = strings.TrimSpace(reportKeyLike)
if reportKeyLike == "" {
return nil
}
if _, err := pg.ExecContext(ctx, `DELETE FROM mk_product_performance_grouped_snapshot WHERE report_key LIKE $1`, reportKeyLike); err != nil {
return err
}
if _, err := pg.ExecContext(ctx, `DELETE FROM mk_product_performance_grouped_snapshot_meta WHERE report_key LIKE $1`, reportKeyLike); err != nil {
return err
}
return nil
}
func productPerformanceGroupedSnapshotDefinitions(ctx context.Context, pg *sql.DB) ([]productPerformanceGroupedSnapshotDefinition, error) {
_ = ctx
_ = pg
defs := []productPerformanceGroupedSnapshotDefinition{
{Mode: "products", Levels: []string{"urun_ilk_grubu", "askili_yan", "kategori", "urun_ana_grubu", "urun_alt_grubu", "product_code", "color_yaka", "market_key"}},
{Mode: "products", Levels: []string{"urun_ana_grubu"}},
{Mode: "idle", Levels: []string{"urun_ilk_grubu", "askili_yan", "kategori", "urun_ana_grubu", "urun_alt_grubu", "product_code", "color_yaka"}},
{Mode: "sales_color_yaka_market_customer", Levels: []string{"color_yaka", "urun_ilk_grubu", "askili_yan", "kategori", "urun_ana_grubu", "urun_alt_grubu", "product_code", "country", "market_key", "customer_segment", "customer_code", "customer_name"}},
{Mode: "sales_color_yaka_market_customer", Levels: []string{"urun_ana_grubu", "color_yaka", "market_key", "customer_code", "customer_name", "urun_alt_grubu", "product_code"}},
{Mode: "sales_product_country_segment_market_customer", Levels: []string{"urun_ilk_grubu", "askili_yan", "kategori", "urun_ana_grubu", "urun_alt_grubu", "product_code", "color_yaka", "country", "customer_segment", "market_key", "customer_code", "customer_name"}},
{Mode: "sales_country_segment_market_customer_product", Levels: []string{"country", "customer_segment", "market_key", "customer_code", "customer_name", "urun_ilk_grubu", "askili_yan", "kategori", "urun_ana_grubu", "urun_alt_grubu", "product_code", "color_yaka"}},
{Mode: "order_product_customers", Levels: []string{"urun_ilk_grubu", "askili_yan", "kategori", "urun_ana_grubu", "urun_alt_grubu", "product_code", "color_yaka", "market_key", "customer_code", "customer_name"}},
{Mode: "order_market_details", Levels: []string{"market_key", "customer_code", "customer_name", "urun_ilk_grubu", "askili_yan", "kategori", "urun_ana_grubu", "urun_alt_grubu", "product_code", "color_yaka"}},
}
productRows, ok, err := loadProductPerformanceSnapshotMapRows(ctx, pg, productPerformanceSnapshotKey("products"), 50000)
if err != nil {
return nil, err
}
if ok {
mainGroups := make([]string, 0)
seen := map[string]bool{}
for _, row := range productRows {
mainGroup := productPerformanceGroupedFilterValue(row, "urun_ana_grubu")
if mainGroup == "" || seen[mainGroup] {
continue
}
seen[mainGroup] = true
mainGroups = append(mainGroups, mainGroup)
}
sort.Strings(mainGroups)
for _, mainGroup := range mainGroups {
defs = append(defs, productPerformanceGroupedSnapshotDefinition{
Mode: "product_detail",
Levels: []string{"urun_alt_grubu", "product_code", "color_yaka", "market_key"},
MainGroup: mainGroup,
})
}
}
return defs, nil
}
@@ -1775,11 +1796,15 @@ SELECT
sales_qty_30d, sales_qty_90d, sales_qty_180d, sales_qty_365d, sales_qty_730d, sales_qty_total,
sales_usd_30d, sales_usd_90d, sales_usd_180d, sales_usd_365d, sales_usd_total,
avg_daily_sales_90d, avg_daily_sales_180d, avg_daily_sales_365d, avg_daily_sales_total,
avg_stock_90d, avg_stock_180d, avg_stock_365d, avg_stock_total,
stock_days_90d, stock_days_180d, stock_days_365d, stock_days_total,
stock_turnover_90d, stock_turnover_180d, stock_turnover_365d, stock_turnover_total,
avg_price_usd_90d, avg_price_usd_180d, cost_price_usd, base_price_usd, base_price_try,
gross_profit_usd_90d, gross_profit_usd_180d, gross_margin_90d, gross_margin_180d,
unit_profit_cost_90d, unit_profit_cost_180d, unit_profit_base_90d, unit_profit_base_180d, market_count_90d, customer_count_90d, sales_index_90d,
unit_profit_cost_90d, unit_profit_cost_180d, unit_profit_base_90d, unit_profit_base_180d,
market_count_90d, market_count_180d, market_count_365d, market_count_total,
customer_count_90d, customer_count_180d, customer_count_365d, customer_count_total,
sales_index_90d, sales_index_180d, sales_index_365d, sales_index_total,
price_index_90d, margin_index_90d, performance_score, performance_bucket,
recommendation, COALESCE(to_char(last_sale_date,'YYYY-MM-DD'),''), last_ref_number,
to_char(updated_at,'YYYY-MM-DD HH24:MI:SS')
@@ -1801,11 +1826,15 @@ LIMIT $`+fmt.Sprint(len(args)-1)+` OFFSET $`+fmt.Sprint(len(args)), args...)
&r.SalesQty30, &r.SalesQty90, &r.SalesQty180, &r.SalesQty365, &r.SalesQty730, &r.SalesQtyTotal,
&r.SalesUSD30, &r.SalesUSD90, &r.SalesUSD180, &r.SalesUSD365, &r.SalesUSDTotal,
&r.AvgDailySales90, &r.AvgDailySales180, &r.AvgDailySales365, &r.AvgDailySalesTotal,
&r.AvgStock90, &r.AvgStock180, &r.AvgStock365, &r.AvgStockTotal,
&r.StockDays90, &r.StockDays180, &r.StockDays365, &r.StockDaysTotal,
&r.StockTurnover90, &r.StockTurnover180, &r.StockTurnover365, &r.StockTurnoverTotal,
&r.AvgPriceUSD90, &r.AvgPriceUSD180, &r.CostPriceUSD, &r.BasePriceUSD, &r.BasePriceTRY,
&r.GrossProfitUSD90, &r.GrossProfitUSD180, &r.GrossMargin90, &r.GrossMargin180,
&r.UnitProfitCost90, &r.UnitProfitCost180, &r.UnitProfitBase90, &r.UnitProfitBase180, &r.MarketCount90, &r.CustomerCount90, &r.SalesIndex90,
&r.UnitProfitCost90, &r.UnitProfitCost180, &r.UnitProfitBase90, &r.UnitProfitBase180,
&r.MarketCount90, &r.MarketCount180, &r.MarketCount365, &r.MarketCountTotal,
&r.CustomerCount90, &r.CustomerCount180, &r.CustomerCount365, &r.CustomerCountTotal,
&r.SalesIndex90, &r.SalesIndex180, &r.SalesIndex365, &r.SalesIndexTotal,
&r.PriceIndex90, &r.MarginIndex90, &r.PerformanceScore, &r.PerformanceBucket,
&r.Recommendation, &r.LastSaleDate, &r.LastRefNumber, &r.UpdatedAt,
); err != nil {
@@ -1829,37 +1858,109 @@ LIMIT $`+fmt.Sprint(len(args)-1)+` OFFSET $`+fmt.Sprint(len(args)), args...)
func applyProductPerformanceProductRowScores(rows []models.ProductPerformanceRow) {
avg := productPerformanceProductRowAverages(rows)
for i := range rows {
rows[i].PerformanceScore = productPerformanceProductScore(
rows[i].SalesIndex90 = productPerformanceRelativeIndex(rows[i].SalesUSD90, avg.salesUSD90)
rows[i].SalesIndex180 = productPerformanceRelativeIndex(rows[i].SalesUSD180, avg.salesUSD180)
rows[i].SalesIndex365 = productPerformanceRelativeIndex(rows[i].SalesUSD365, avg.salesUSD365)
rows[i].SalesIndexTotal = productPerformanceRelativeIndex(rows[i].SalesUSDTotal, avg.salesUSDTotal)
margin365 := productPerformanceMarginFromSales(rows[i].SalesUSD365, rows[i].SalesQty365, rows[i].CostPriceUSD)
marginTotal := productPerformanceMarginFromSales(rows[i].SalesUSDTotal, rows[i].SalesQtyTotal, rows[i].CostPriceUSD)
rows[i].PerformanceScore90 = productPerformanceProductScore(
"90d",
rows[i].SalesUSD90,
productPerformanceRelativeIndex(rows[i].SalesUSD90, avg.salesUSD90),
rows[i].SalesIndex90,
rows[i].GrossMargin90,
rows[i].StockTurnover90,
float64(rows[i].MarketCount90),
float64(rows[i].CustomerCount90),
)
rows[i].PerformanceScore180 = productPerformanceProductScore(
"180d",
rows[i].SalesUSD180,
rows[i].SalesIndex180,
rows[i].GrossMargin180,
rows[i].StockTurnover180,
float64(rows[i].MarketCount180),
float64(rows[i].CustomerCount180),
)
rows[i].PerformanceScore365 = productPerformanceProductScore(
"365d",
rows[i].SalesUSD365,
rows[i].SalesIndex365,
margin365,
rows[i].StockTurnover365,
float64(rows[i].MarketCount365),
float64(rows[i].CustomerCount365),
)
rows[i].PerformanceScoreTotal = productPerformanceProductScore(
"total",
rows[i].SalesUSDTotal,
rows[i].SalesIndexTotal,
marginTotal,
rows[i].StockTurnoverTotal,
float64(rows[i].MarketCountTotal),
float64(rows[i].CustomerCountTotal),
productPerformanceProductRowTotalPeriodDays(rows[i]),
)
rows[i].PerformanceScore = rows[i].PerformanceScore90
}
}
type productPerformanceProductRowAverage struct {
salesUSD90 float64
salesUSD90 float64
salesUSD180 float64
salesUSD365 float64
salesUSDTotal float64
}
func productPerformanceProductRowAverages(rows []models.ProductPerformanceRow) productPerformanceProductRowAverage {
var sum90, count90 float64
var sum90, count90, sum180, count180, sum365, count365, sumTotal, countTotal float64
for _, row := range rows {
if row.SalesUSD90 > 0 {
sum90 += row.SalesUSD90
count90++
}
if row.SalesUSD180 > 0 {
sum180 += row.SalesUSD180
count180++
}
if row.SalesUSD365 > 0 {
sum365 += row.SalesUSD365
count365++
}
if row.SalesUSDTotal > 0 {
sumTotal += row.SalesUSDTotal
countTotal++
}
}
out := productPerformanceProductRowAverage{}
if count90 > 0 {
out.salesUSD90 = sum90 / count90
}
if count180 > 0 {
out.salesUSD180 = sum180 / count180
}
if count365 > 0 {
out.salesUSD365 = sum365 / count365
}
if countTotal > 0 {
out.salesUSDTotal = sumTotal / countTotal
}
return out
}
func productPerformanceProductRowTotalPeriodDays(row models.ProductPerformanceRow) float64 {
return productPerformancePeriodDays(map[string]any{"kpi_date": row.KpiDate}, "total")
}
func productPerformanceMarginFromSales(salesUSD, salesQty, unitCost float64) float64 {
if salesUSD <= 0 {
return 0
}
return (salesUSD - (salesQty * unitCost)) / salesUSD
}
func GetProductPerformanceSummary(ctx context.Context, pg *sql.DB) (models.ProductPerformanceSummary, error) {
if err := EnsureProductPerformanceTables(pg); err != nil {
return models.ProductPerformanceSummary{}, err
@@ -2190,7 +2291,7 @@ SELECT
WHEN sales_qty_total > 0 AND stock_qty <= 0 AND sales_index_total >= 1 THEN 'STOKSUZ_TALEP'
WHEN sales_qty_total = 0 AND stock_qty > 0 THEN 'STOK_RISKI'
WHEN gross_margin_total < 0 THEN 'FIYAT_BASKISI'
WHEN sales_index_total >= 1.4 AND gross_margin_total >= 0.25 THEN 'YILDIZ_URUN'
WHEN sales_index_total >= 1.4 AND gross_margin_total >= 0.45 THEN 'YILDIZ_URUN'
WHEN gross_margin_total >= 0.35 AND sales_index_total < 0.8 THEN 'FIYAT_FIRSATI'
ELSE 'TAKIP'
END AS performance_bucket,
@@ -2198,7 +2299,7 @@ SELECT
WHEN sales_qty_total > 0 AND stock_qty <= 0 THEN 'Talep var, stok yok. Uretim/satin alma onceligi ver.'
WHEN sales_qty_total = 0 AND stock_qty > 0 THEN 'Satis yok, stok maliyeti tasiyor. Piyasa/fiyat aksiyonu gerekli.'
WHEN gross_margin_total < 0 THEN 'Ciplak maliyet altinda satis var. Fiyat veya maliyet kontrol edilmeli.'
WHEN sales_index_total >= 1.4 AND gross_margin_total >= 0.25 THEN 'Genel donemde guclu urun. Stok ve fiyat korunmali.'
WHEN sales_index_total >= 1.4 AND gross_margin_total >= 0.45 THEN 'Genel donemde guclu urun. Stok ve fiyat korunmali.'
WHEN gross_margin_total >= 0.35 AND sales_index_total < 0.8 THEN 'Karli ama yavas. Dogru piyasada satis firsati var.'
ELSE 'Izleme ve piyasa bazli aksiyon.'
END AS recommendation,
@@ -3485,6 +3586,19 @@ StockTotalStart AS (
WHERE stock_date <= DATE '2022-01-01'
ORDER BY product_code, color_code, yaka_kodu, stock_date DESC
),
FirstSaleByProduct AS (
SELECT
product_code,
color_code,
yaka_kodu,
MIN(sales_date) FILTER (WHERE sales_date >= current_date - INTERVAL '89 days') AS first_sale_date_90d,
MIN(sales_date) FILTER (WHERE sales_date >= current_date - INTERVAL '179 days') AS first_sale_date_180d,
MIN(sales_date) FILTER (WHERE sales_date >= current_date - INTERVAL '359 days') AS first_sale_date_365d,
MIN(sales_date) FILTER (WHERE sales_date >= DATE '2022-01-01') AS first_sale_date_total
FROM mk_product_performance_sales_daily
WHERE sales_date >= DATE '2022-01-01'
GROUP BY product_code, color_code, yaka_kodu
),
Agg AS (
SELECT
$2::text AS breakdown,
@@ -3587,18 +3701,55 @@ Agg AS (
COALESCE(pd.base_price_usd,0) AS base_price_usd,
COALESCE(pd.cost_price_usd,0) AS cost_price_usd,
COALESCE(st.stock_qty,0) AS stock_qty,
(COALESCE(s90.stock_qty,0) + COALESCE(st.stock_qty,0)) / 2.0 AS avg_stock_90d,
(COALESCE(s180.stock_qty,0) + COALESCE(st.stock_qty,0)) / 2.0 AS avg_stock_180d,
(COALESCE(s365.stock_qty,0) + COALESCE(st.stock_qty,0)) / 2.0 AS avg_stock_365d,
(COALESCE(stotal.stock_qty,0) + COALESCE(st.stock_qty,0)) / 2.0 AS avg_stock_total
(COALESCE(s90.stock_qty, st.stock_qty, 0) + COALESCE(st.stock_qty,0)) / 2.0 AS avg_stock_90d,
(COALESCE(s180.stock_qty, st.stock_qty, 0) + COALESCE(st.stock_qty,0)) / 2.0 AS avg_stock_180d,
(COALESCE(s365.stock_qty, st.stock_qty, 0) + COALESCE(st.stock_qty,0)) / 2.0 AS avg_stock_365d,
(COALESCE(stotal.stock_qty, st.stock_qty, 0) + COALESCE(st.stock_qty,0)) / 2.0 AS avg_stock_total
FROM mk_product_performance_sales_daily s
LEFT JOIN mk_product_performance_price_dim pd ON pd.product_code = s.product_code
LEFT JOIN LatestKPI k ON k.product_code = s.product_code AND k.color_code = s.color_code AND k.yaka_kodu = s.yaka_kodu
LEFT JOIN FirstSaleByProduct fs ON fs.product_code = s.product_code AND fs.color_code = s.color_code AND fs.yaka_kodu = s.yaka_kodu
LEFT JOIN StockAgg st ON st.product_code = s.product_code AND st.color_code = s.color_code AND st.yaka_kodu = s.yaka_kodu
LEFT JOIN Stock90Start s90 ON s90.product_code = s.product_code AND s90.color_code = s.color_code AND s90.yaka_kodu = s.yaka_kodu
LEFT JOIN Stock180Start s180 ON s180.product_code = s.product_code AND s180.color_code = s.color_code AND s180.yaka_kodu = s.yaka_kodu
LEFT JOIN Stock365Start s365 ON s365.product_code = s.product_code AND s365.color_code = s.color_code AND s365.yaka_kodu = s.yaka_kodu
LEFT JOIN StockTotalStart stotal ON stotal.product_code = s.product_code AND stotal.color_code = s.color_code AND stotal.yaka_kodu = s.yaka_kodu
LEFT JOIN LATERAL (
SELECT x.stock_qty
FROM mk_product_performance_stock_daily x
WHERE x.product_code = s.product_code
AND x.color_code = s.color_code
AND x.yaka_kodu = s.yaka_kodu
AND x.stock_date <= COALESCE(fs.first_sale_date_90d, current_date - INTERVAL '89 days')
ORDER BY x.stock_date DESC
LIMIT 1
) s90 ON TRUE
LEFT JOIN LATERAL (
SELECT x.stock_qty
FROM mk_product_performance_stock_daily x
WHERE x.product_code = s.product_code
AND x.color_code = s.color_code
AND x.yaka_kodu = s.yaka_kodu
AND x.stock_date <= COALESCE(fs.first_sale_date_180d, current_date - INTERVAL '179 days')
ORDER BY x.stock_date DESC
LIMIT 1
) s180 ON TRUE
LEFT JOIN LATERAL (
SELECT x.stock_qty
FROM mk_product_performance_stock_daily x
WHERE x.product_code = s.product_code
AND x.color_code = s.color_code
AND x.yaka_kodu = s.yaka_kodu
AND x.stock_date <= COALESCE(fs.first_sale_date_365d, current_date - INTERVAL '359 days')
ORDER BY x.stock_date DESC
LIMIT 1
) s365 ON TRUE
LEFT JOIN LATERAL (
SELECT x.stock_qty
FROM mk_product_performance_stock_daily x
WHERE x.product_code = s.product_code
AND x.color_code = s.color_code
AND x.yaka_kodu = s.yaka_kodu
AND x.stock_date <= COALESCE(fs.first_sale_date_total, DATE '2022-01-01')
ORDER BY x.stock_date DESC
LIMIT 1
) stotal ON TRUE
) s
WHERE sales_date >= DATE '2022-01-01'
AND upper(translate(btrim(COALESCE(urun_ilk_grubu,'')), U&'\0130\015E\011E\00DC\00D6\00C7\0131\015F\011F\00FC\00F6\00E7', 'ISGUOCisguoc')) NOT IN ('MALZEMELI FASON', 'MALZEMESIZ FASON', 'MAZLEMELI FASON', 'MAZEMESIZ FASON', 'DIGER')
@@ -3704,16 +3855,20 @@ SELECT
gross_profit_cost_usd_total,
gross_margin_base_total,
gross_margin_cost_total,
CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) ELSE 0 END AS stock_turnover_90d,
CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) ELSE 0 END AS stock_turnover_180d,
avg_stock_90d,
avg_stock_180d,
avg_stock_365d,
avg_stock_total,
CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) * 4.0 ELSE 0 END AS stock_turnover_90d,
CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) * 2.0 ELSE 0 END AS stock_turnover_180d,
CASE WHEN avg_stock_365d > 0 THEN sales_qty_365d / NULLIF(avg_stock_365d,0) ELSE 0 END AS stock_turnover_365d,
CASE WHEN avg_stock_total > 0 THEN sales_qty_total / NULLIF(avg_stock_total,0) ELSE 0 END AS stock_turnover_total,
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,
has_cost,
sales_index_90d,
CASE WHEN NOT has_cost THEN 0 WHEN sales_usd_90d <= 0 THEN 1 ELSE
ROUND((
LEAST(35, sales_usd_90d / 25000 * 35)
+ LEAST(30, GREATEST(gross_margin_cost_90d,0) / 0.40 * 30)
+ LEAST(30, GREATEST(gross_margin_cost_90d,0) / 0.45 * 30)
+ LEAST(20, product_group_count_90d / 8.0 * 20)
+ LEAST(15, sales_qty_90d / 500 * 15)
)::numeric, 4)
@@ -3721,7 +3876,7 @@ SELECT
CASE WHEN NOT has_cost THEN 0 WHEN sales_usd_180d <= 0 THEN 1 ELSE
ROUND((
LEAST(35, sales_usd_180d / 50000 * 35)
+ LEAST(30, GREATEST(gross_margin_cost_180d,0) / 0.40 * 30)
+ LEAST(30, GREATEST(gross_margin_cost_180d,0) / 0.45 * 30)
+ LEAST(20, product_group_count_180d / 8.0 * 20)
+ LEAST(15, sales_qty_180d / 1000 * 15)
)::numeric, 4)
@@ -3729,7 +3884,7 @@ SELECT
CASE WHEN NOT has_cost THEN 0 WHEN sales_usd_365d <= 0 THEN 1 ELSE
ROUND((
LEAST(35, sales_usd_365d / 100000 * 35)
+ LEAST(30, GREATEST(gross_margin_cost_365d,0) / 0.40 * 30)
+ LEAST(30, GREATEST(gross_margin_cost_365d,0) / 0.45 * 30)
+ LEAST(20, product_group_count_365d / 8.0 * 20)
+ LEAST(15, sales_qty_365d / 2000 * 15)
)::numeric, 4)
@@ -3737,18 +3892,18 @@ SELECT
CASE WHEN NOT has_cost THEN 0 WHEN sales_usd_total <= 0 THEN 1 ELSE
ROUND((
LEAST(35, sales_usd_total / 300000 * 35)
+ LEAST(30, GREATEST(gross_margin_cost_total,0) / 0.40 * 30)
+ LEAST(30, GREATEST(gross_margin_cost_total,0) / 0.45 * 30)
+ LEAST(20, product_group_count_total / 8.0 * 20)
+ LEAST(15, sales_qty_total / 6000 * 15)
)::numeric, 4)
END AS customer_score_total,
CASE WHEN NOT has_cost THEN 0 WHEN sales_usd_90d <= 0 THEN 1 ELSE
ROUND(
LEAST(30, GREATEST(gross_margin_cost_90d,0) / 0.40 * 30)
+ LEAST(20, (CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) ELSE 0 END) / 1.5 * 20)
+ LEAST(20, sales_usd_90d / 10000 * 20)
+ LEAST(15, market_count_90d / 8.0 * 15)
+ LEAST(15, customer_count_90d / 25.0 * 15),
LEAST(30, GREATEST(gross_margin_cost_90d,0) / 0.45 * 30)
+ 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)
+ LEAST(20, sales_usd_90d / 25000 * 20)
+ LEAST(5, market_count_90d / 3.0 * 5)
+ LEAST(25, customer_count_90d / 8.0 * 25),
4
)
END AS performance_score,
@@ -3812,6 +3967,7 @@ LIMIT $1
&r.GrossMarginCost365, &r.CustomerCount365, &r.InvoiceCount365, &r.CustomerCountTotal, &r.InvoiceCountTotal, &r.SalesQtyTotal, &r.SalesUSDTotal,
&r.AvgPriceUSDTotal, &r.BasePriceUSDTotal, &r.CostPriceUSDTotal, &r.GrossProfitBaseTotal,
&r.GrossProfitCostTotal, &r.GrossMarginBaseTotal, &r.GrossMarginCostTotal,
&r.AvgStock90, &r.AvgStock180, &r.AvgStock365, &r.AvgStockTotal,
&r.StockTurnover90, &r.StockTurnover180, &r.StockTurnover365, &r.StockTurnoverTotal, &r.HasCost,
&r.SalesIndex90, &r.CustomerScore90, &r.CustomerScore180, &r.CustomerScore365, &r.CustomerScoreTotal, &r.PerformanceScore,
&r.PerformanceBucket, &r.Recommendation, &r.LastSaleDate,
@@ -3920,6 +4076,7 @@ func ListProductPerformanceGrouped(ctx context.Context, pg *sql.DB, req ProductP
sourceRows = filterProductPerformanceGroupedRows(sourceRows, productPerformanceGroupedEffectiveFilters(req))
out := make([]map[string]any, 0, len(sourceRows))
appendProductPerformanceGroupedRows(&out, sourceRows, levels, 0, 0, []string{"tab:" + req.Mode}, req.ExpandedKeys, req.ExpandThroughLevel)
out = sortProductPerformancePreparedGroupedRows(out, req.SortBy, req.Descending)
if len(out) > 0 || !productPerformanceLiveFallbackEnabled() {
return out, nil
}
@@ -4038,6 +4195,9 @@ func loadProductPerformancePreparedGroupedRows(ctx context.Context, pg *sql.DB,
}
effectiveFilters := productPerformancePreparedGroupedEffectiveFilters(req)
hasFilters := len(effectiveFilters) > 0
if hasFilters {
return nil, false, nil
}
hasManualExpansion := len(req.ExpandedKeys) > 0
query := `
SELECT payload
@@ -4098,7 +4258,6 @@ SELECT EXISTS (
return nil, false, nil
}
}
out = filterProductPerformancePreparedGroupedRows(out, effectiveFilters)
out = filterProductPerformanceGroupedRowsForExpansion(out, req.ExpandedKeys, req.ExpandThroughLevel, req.Limit)
out = sortProductPerformancePreparedGroupedRows(out, req.SortBy, req.Descending)
return out, true, nil
@@ -4257,7 +4416,11 @@ func listProductPerformanceGroupedSQL(ctx context.Context, pg *sql.DB, req Produ
out := make([]map[string]any, 0, 512)
filters := productPerformanceGroupedBaseFilters(req)
err := appendProductPerformanceGroupedSQLRows(ctx, pg, &out, mode, levels, 0, 0, []string{"tab:" + mode}, filters, req.ExpandedKeys, req.ExpandThroughLevel, req.Limit)
return out, true, err
if err != nil {
return out, true, err
}
out = sortProductPerformancePreparedGroupedRows(out, req.SortBy, req.Descending)
return out, true, nil
}
func productPerformanceGroupedBaseFilters(req ProductPerformanceGroupedRequest) []productPerformanceSQLGroupFilter {
@@ -4335,6 +4498,7 @@ func appendProductPerformanceGroupedSQLRows(ctx context.Context, pg *sql.DB, out
row["label"] = value
row["__group"] = true
row[field] = value
deriveProductPerformanceGroupMetrics(row, field)
*out = append(*out, row)
if expandedKeys[key] || level <= expandThroughLevel {
nextFilters := append(append([]productPerformanceSQLGroupFilter{}, filters...), productPerformanceSQLGroupFilter{Field: field, Value: value})
@@ -4360,6 +4524,8 @@ SELECT (
jsonb_build_object(
'group_value', group_value,
'label', group_value,
'period_start', '2022-01-01',
'period_end', COALESCE(to_char((SELECT kpi_date FROM LatestKPIDate),'YYYY-MM-DD'), ''),
'count', row_count,
'recommendation', CASE WHEN recommendation <> '' THEN recommendation ELSE row_count::text || ' satir' END,
'image_product_code', image_product_code,
@@ -4378,6 +4544,10 @@ SELECT (
)
|| jsonb_build_object(
'stock_qty', stock_qty,
'avg_stock_90d', avg_stock_90d,
'avg_stock_180d', avg_stock_180d,
'avg_stock_365d', avg_stock_365d,
'avg_stock_total', avg_stock_total,
'sales_qty_90d', sales_qty_90d,
'sales_qty_180d', sales_qty_180d,
'sales_qty_365d', sales_qty_365d,
@@ -4402,8 +4572,17 @@ SELECT (
'unit_profit_base_90d', unit_profit_base_90d,
'unit_profit_base_180d', unit_profit_base_180d,
'market_count_90d', market_count_90d,
'market_count_180d', market_count_180d,
'market_count_365d', market_count_365d,
'market_count_total', market_count_total,
'customer_count_90d', customer_count_90d,
'customer_count_180d', customer_count_180d,
'customer_count_365d', customer_count_365d,
'customer_count_total', customer_count_total,
'sales_index_90d', sales_index_90d,
'sales_index_180d', sales_index_180d,
'sales_index_365d', sales_index_365d,
'sales_index_total', sales_index_total,
'price_index_90d', price_index_90d,
'margin_index_90d', margin_index_90d,
'performance_score', performance_score,
@@ -4413,10 +4592,10 @@ SELECT (
'stock_days_180d', stock_days_180d,
'stock_days_365d', stock_days_365d,
'stock_days_total', stock_days_total,
'stock_turnover_90d', CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) ELSE 0 END,
'stock_turnover_180d', CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) ELSE 0 END,
'stock_turnover_365d', CASE WHEN avg_stock_365d > 0 THEN sales_qty_365d / NULLIF(avg_stock_365d,0) ELSE 0 END,
'stock_turnover_total', CASE WHEN avg_stock_total > 0 THEN sales_qty_total / NULLIF(avg_stock_total,0) ELSE 0 END
'stock_turnover_90d', stock_turnover_90d,
'stock_turnover_180d', stock_turnover_180d,
'stock_turnover_365d', stock_turnover_365d,
'stock_turnover_total', stock_turnover_total
)
) AS row_json
FROM (
@@ -4481,33 +4660,37 @@ FROM (
CASE WHEN SUM(sales_qty_180d) > 0 THEN SUM(unit_profit_cost_180d * sales_qty_180d) / NULLIF(SUM(sales_qty_180d),0) ELSE 0 END AS unit_profit_cost_180d,
CASE WHEN SUM(sales_qty_90d) > 0 THEN SUM(unit_profit_base_90d * sales_qty_90d) / NULLIF(SUM(sales_qty_90d),0) ELSE 0 END AS unit_profit_base_90d,
CASE WHEN SUM(sales_qty_180d) > 0 THEN SUM(unit_profit_base_180d * sales_qty_180d) / NULLIF(SUM(sales_qty_180d),0) ELSE 0 END AS unit_profit_base_180d,
COUNT(DISTINCT NULLIF(NULLIF(market_key,'STOK'),'')) FILTER (WHERE COALESCE(sales_usd_90d,0) > 0)::integer AS market_count_90d,
COUNT(DISTINCT NULLIF(NULLIF(display_market_key,'STOK'),'')) FILTER (WHERE COALESCE(sales_usd_90d,0) > 0)::integer AS market_count_90d,
COUNT(DISTINCT NULLIF(NULLIF(display_market_key,'STOK'),'')) FILTER (WHERE COALESCE(sales_usd_180d,0) > 0)::integer AS market_count_180d,
COUNT(DISTINCT NULLIF(NULLIF(display_market_key,'STOK'),'')) FILTER (WHERE COALESCE(sales_usd_365d,0) > 0)::integer AS market_count_365d,
COUNT(DISTINCT NULLIF(NULLIF(display_market_key,'STOK'),'')) FILTER (WHERE COALESCE(sales_usd_total,0) > 0)::integer AS market_count_total,
COALESCE(SUM(CASE WHEN COALESCE(sales_usd_90d,0) > 0 THEN customer_count_90d ELSE 0 END),0)::integer AS customer_count_90d,
COALESCE(SUM(CASE WHEN COALESCE(sales_usd_180d,0) > 0 THEN customer_count_180d ELSE 0 END),0)::integer AS customer_count_180d,
COALESCE(SUM(CASE WHEN COALESCE(sales_usd_365d,0) > 0 THEN customer_count_365d ELSE 0 END),0)::integer AS customer_count_365d,
COALESCE(SUM(CASE WHEN COALESCE(sales_usd_total,0) > 0 THEN customer_count_total ELSE 0 END),0)::integer AS customer_count_total,
CASE WHEN SUM(sales_qty_90d) > 0 THEN SUM(sales_index_90d * sales_qty_90d) / NULLIF(SUM(sales_qty_90d),0) ELSE 0 END AS sales_index_90d,
CASE WHEN SUM(sales_qty_180d) > 0 THEN SUM(sales_index_180d * sales_qty_180d) / NULLIF(SUM(sales_qty_180d),0) ELSE 0 END AS sales_index_180d,
CASE WHEN SUM(sales_qty_365d) > 0 THEN SUM(sales_index_365d * sales_qty_365d) / NULLIF(SUM(sales_qty_365d),0) ELSE 0 END AS sales_index_365d,
CASE WHEN SUM(sales_qty_total) > 0 THEN SUM(sales_index_total * sales_qty_total) / NULLIF(SUM(sales_qty_total),0) ELSE 0 END AS sales_index_total,
CASE WHEN SUM(sales_qty_90d) > 0 THEN SUM(price_index_90d * sales_qty_90d) / NULLIF(SUM(sales_qty_90d),0) ELSE 0 END AS price_index_90d,
CASE WHEN SUM(sales_qty_90d) > 0 THEN SUM(margin_index_90d * sales_qty_90d) / NULLIF(SUM(sales_qty_90d),0) ELSE 0 END AS margin_index_90d,
CASE WHEN SUM(sales_qty_90d) > 0 THEN SUM(stock_turnover_90d * sales_qty_90d) / NULLIF(SUM(sales_qty_90d),0) ELSE 0 END AS stock_turnover_90d,
CASE WHEN SUM(sales_qty_180d) > 0 THEN SUM(stock_turnover_180d * sales_qty_180d) / NULLIF(SUM(sales_qty_180d),0) ELSE 0 END AS stock_turnover_180d,
CASE WHEN SUM(sales_qty_365d) > 0 THEN SUM(stock_turnover_365d * sales_qty_365d) / NULLIF(SUM(sales_qty_365d),0) ELSE 0 END AS stock_turnover_365d,
CASE WHEN SUM(sales_qty_total) > 0 THEN SUM(stock_turnover_total * sales_qty_total) / NULLIF(SUM(sales_qty_total),0) ELSE 0 END AS stock_turnover_total,
CASE
WHEN SUM(CASE
WHEN COALESCE(sales_usd_90d,0) > 0 THEN sales_usd_90d
WHEN COALESCE(sales_qty_90d,0) > 0 THEN sales_qty_90d
WHEN COALESCE(stock_qty,0) > 0 AND COALESCE(cost_price_usd,0) > 0 THEN stock_qty * cost_price_usd
WHEN COALESCE(stock_qty,0) > 0 THEN stock_qty
ELSE 1
ELSE 0
END) > 0
THEN SUM(performance_score * CASE
WHEN COALESCE(sales_usd_90d,0) > 0 THEN sales_usd_90d
WHEN COALESCE(sales_qty_90d,0) > 0 THEN sales_qty_90d
WHEN COALESCE(stock_qty,0) > 0 AND COALESCE(cost_price_usd,0) > 0 THEN stock_qty * cost_price_usd
WHEN COALESCE(stock_qty,0) > 0 THEN stock_qty
ELSE 1
ELSE 0
END) / NULLIF(SUM(CASE
WHEN COALESCE(sales_usd_90d,0) > 0 THEN sales_usd_90d
WHEN COALESCE(sales_qty_90d,0) > 0 THEN sales_qty_90d
WHEN COALESCE(stock_qty,0) > 0 AND COALESCE(cost_price_usd,0) > 0 THEN stock_qty * cost_price_usd
WHEN COALESCE(stock_qty,0) > 0 THEN stock_qty
ELSE 1
ELSE 0
END),0)
ELSE 0
ELSE COALESCE(AVG(performance_score),0)
END AS performance_score,
MODE() WITHIN GROUP (ORDER BY performance_bucket) AS performance_bucket,
COALESCE(MODE() WITHIN GROUP (ORDER BY NULLIF(recommendation,'')), '') AS recommendation,
@@ -4515,6 +4698,11 @@ FROM (
FROM (
SELECT
Source.*,
btrim(regexp_replace(COALESCE(Source.market_key,''), '^.*[|]', '')) AS display_market_key,
CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) * 4.0 ELSE 0 END AS stock_turnover_90d,
CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) * 2.0 ELSE 0 END AS stock_turnover_180d,
CASE WHEN avg_stock_365d > 0 THEN sales_qty_365d / NULLIF(avg_stock_365d,0) ELSE 0 END AS stock_turnover_365d,
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 AS stock_turnover_total,
ROW_NUMBER() OVER (
PARTITION BY COALESCE(%s, ''), product_code, color_code, yaka_kodu
ORDER BY performance_score DESC NULLS LAST
@@ -4539,10 +4727,10 @@ func queryProductPerformanceSQLLeafRows(ctx context.Context, pg *sql.DB, mode st
query := productPerformanceSQLSourceCTE(mode) + fmt.Sprintf(`
SELECT to_jsonb(t) || jsonb_build_object(
'row_key', 'leaf|' || product_code || '|' || color_code || '|' || yaka_kodu || '|' || market_key,
'stock_turnover_90d', CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) ELSE 0 END,
'stock_turnover_180d', CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) ELSE 0 END,
'stock_turnover_90d', CASE WHEN avg_stock_90d > 0 THEN sales_qty_90d / NULLIF(avg_stock_90d,0) * 4.0 ELSE 0 END,
'stock_turnover_180d', CASE WHEN avg_stock_180d > 0 THEN sales_qty_180d / NULLIF(avg_stock_180d,0) * 2.0 ELSE 0 END,
'stock_turnover_365d', CASE WHEN avg_stock_365d > 0 THEN sales_qty_365d / NULLIF(avg_stock_365d,0) ELSE 0 END,
'stock_turnover_total', CASE WHEN avg_stock_total > 0 THEN sales_qty_total / NULLIF(avg_stock_total,0) ELSE 0 END
'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
) AS row_json
FROM Source t
%s
@@ -4641,10 +4829,10 @@ Source AS (
urun_alt_grubu,
market_key,
COALESCE(stock_qty,0) AS stock_qty,
(COALESCE((SELECT s.stock_qty FROM Stock90Start s WHERE s.product_code = mk_product_performance_kpi_daily.product_code AND s.color_code = mk_product_performance_kpi_daily.color_code AND s.yaka_kodu = mk_product_performance_kpi_daily.yaka_kodu),0) + COALESCE(stock_qty,0)) / 2.0 AS avg_stock_90d,
(COALESCE((SELECT s.stock_qty FROM Stock180Start s WHERE s.product_code = mk_product_performance_kpi_daily.product_code AND s.color_code = mk_product_performance_kpi_daily.color_code AND s.yaka_kodu = mk_product_performance_kpi_daily.yaka_kodu),0) + COALESCE(stock_qty,0)) / 2.0 AS avg_stock_180d,
(COALESCE((SELECT s.stock_qty FROM Stock365Start s WHERE s.product_code = mk_product_performance_kpi_daily.product_code AND s.color_code = mk_product_performance_kpi_daily.color_code AND s.yaka_kodu = mk_product_performance_kpi_daily.yaka_kodu),0) + COALESCE(stock_qty,0)) / 2.0 AS avg_stock_365d,
(COALESCE((SELECT s.stock_qty FROM StockTotalStart s WHERE s.product_code = mk_product_performance_kpi_daily.product_code AND s.color_code = mk_product_performance_kpi_daily.color_code AND s.yaka_kodu = mk_product_performance_kpi_daily.yaka_kodu),0) + COALESCE(stock_qty,0)) / 2.0 AS avg_stock_total,
COALESCE(NULLIF(avg_stock_90d,0), (COALESCE((SELECT s.stock_qty FROM Stock90Start s WHERE s.product_code = mk_product_performance_kpi_daily.product_code AND s.color_code = mk_product_performance_kpi_daily.color_code AND s.yaka_kodu = mk_product_performance_kpi_daily.yaka_kodu),0) + COALESCE(stock_qty,0)) / 2.0) AS avg_stock_90d,
COALESCE(NULLIF(avg_stock_180d,0), (COALESCE((SELECT s.stock_qty FROM Stock180Start s WHERE s.product_code = mk_product_performance_kpi_daily.product_code AND s.color_code = mk_product_performance_kpi_daily.color_code AND s.yaka_kodu = mk_product_performance_kpi_daily.yaka_kodu),0) + COALESCE(stock_qty,0)) / 2.0) AS avg_stock_180d,
COALESCE(NULLIF(avg_stock_365d,0), (COALESCE((SELECT s.stock_qty FROM Stock365Start s WHERE s.product_code = mk_product_performance_kpi_daily.product_code AND s.color_code = mk_product_performance_kpi_daily.color_code AND s.yaka_kodu = mk_product_performance_kpi_daily.yaka_kodu),0) + COALESCE(stock_qty,0)) / 2.0) AS avg_stock_365d,
COALESCE(NULLIF(avg_stock_total,0), (COALESCE((SELECT s.stock_qty FROM StockTotalStart s WHERE s.product_code = mk_product_performance_kpi_daily.product_code AND s.color_code = mk_product_performance_kpi_daily.color_code AND s.yaka_kodu = mk_product_performance_kpi_daily.yaka_kodu),0) + COALESCE(stock_qty,0)) / 2.0) AS avg_stock_total,
COALESCE(sales_qty_90d,0) AS sales_qty_90d,
COALESCE(sales_qty_180d,0) AS sales_qty_180d,
COALESCE(sales_qty_365d,0) AS sales_qty_365d,
@@ -4671,8 +4859,17 @@ Source AS (
COALESCE(unit_profit_base_90d,0) AS unit_profit_base_90d,
COALESCE(unit_profit_base_180d,0) AS unit_profit_base_180d,
COALESCE(market_count_90d,0) AS market_count_90d,
COALESCE(market_count_180d,0) AS market_count_180d,
COALESCE(market_count_365d,0) AS market_count_365d,
COALESCE(market_count_total,0) AS market_count_total,
COALESCE(customer_count_90d,0) AS customer_count_90d,
COALESCE(customer_count_180d,0) AS customer_count_180d,
COALESCE(customer_count_365d,0) AS customer_count_365d,
COALESCE(customer_count_total,0) AS customer_count_total,
COALESCE(sales_index_90d,0) AS sales_index_90d,
COALESCE(sales_index_180d,0) AS sales_index_180d,
COALESCE(sales_index_365d,0) AS sales_index_365d,
COALESCE(sales_index_total,0) AS sales_index_total,
COALESCE(price_index_90d,0) AS price_index_90d,
COALESCE(margin_index_90d,0) AS margin_index_90d,
COALESCE(performance_score,0) AS performance_score,
@@ -4698,7 +4895,7 @@ func productPerformanceSQLGroupExpr(field string) (string, bool) {
case "color_yaka":
return "concat_ws('/', NULLIF(btrim(COALESCE(color_code,'')), ''), NULLIF(btrim(COALESCE(yaka_kodu,'')), ''))", true
case "market_key":
return "btrim(regexp_replace(COALESCE(market_key,''), '^.*\\|', ''))", true
return "btrim(regexp_replace(COALESCE(market_key,''), '^.*[|]', ''))", true
default:
return "", false
}
@@ -4988,9 +5185,9 @@ func productPerformanceGroupedFilterValue(row map[string]any, field string) stri
}
func productPerformanceGroupedSourceRows(ctx context.Context, pg *sql.DB, mode string, limit int) ([]map[string]any, error) {
if rows, ok, err := productPerformanceGroupedSnapshotRows(ctx, pg, mode, limit); err != nil {
if rows, err := productPerformanceGroupedRawSnapshotSourceRows(ctx, pg, mode, limit); err != nil {
return nil, err
} else if ok {
} else if rows != nil {
return rows, nil
}
@@ -5032,14 +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
@@ -5070,7 +5283,122 @@ func mergeProductPerformanceGeneralSnapshotMetrics(ctx context.Context, pg *sql.
}
}
if value, ok := general["performance_score"]; ok {
row["performance_score_total"] = value
if _, exists := row["performance_score_total"]; !exists {
row["performance_score_total"] = value
}
}
}
return rows
}
func mergeProductPerformanceSalesSpreadKeys(ctx context.Context, pg *sql.DB, rows []map[string]any) []map[string]any {
if len(rows) == 0 {
return rows
}
const query = `
WITH Latest AS (
SELECT COALESCE(
(SELECT MAX(kpi_date) FROM mk_product_performance_kpi_daily),
(SELECT MAX(sales_date) FROM mk_product_performance_sales_daily),
current_date
)::date AS kpi_date
),
Spread AS (
SELECT
s.product_code,
s.color_code,
s.yaka_kodu,
s.market_key,
COALESCE(jsonb_agg(DISTINCT display_market_key) FILTER (
WHERE s.sales_date BETWEEN Latest.kpi_date - INTERVAL '89 days' AND Latest.kpi_date
AND COALESCE(s.sales_usd,0) > 0
AND display_market_key NOT IN ('', 'STOK', '-')
), '[]'::jsonb) AS market_keys_90d,
COALESCE(jsonb_agg(DISTINCT display_market_key) FILTER (
WHERE s.sales_date BETWEEN Latest.kpi_date - INTERVAL '179 days' AND Latest.kpi_date
AND COALESCE(s.sales_usd,0) > 0
AND display_market_key NOT IN ('', 'STOK', '-')
), '[]'::jsonb) AS market_keys_180d,
COALESCE(jsonb_agg(DISTINCT display_market_key) FILTER (
WHERE s.sales_date BETWEEN Latest.kpi_date - INTERVAL '359 days' AND Latest.kpi_date
AND COALESCE(s.sales_usd,0) > 0
AND display_market_key NOT IN ('', 'STOK', '-')
), '[]'::jsonb) AS market_keys_365d,
COALESCE(jsonb_agg(DISTINCT display_market_key) FILTER (
WHERE s.sales_date BETWEEN DATE '2022-01-01' AND Latest.kpi_date
AND COALESCE(s.sales_usd,0) > 0
AND display_market_key NOT IN ('', 'STOK', '-')
), '[]'::jsonb) AS market_keys_total,
COALESCE(jsonb_agg(DISTINCT btrim(s.customer_code)) FILTER (
WHERE s.sales_date BETWEEN Latest.kpi_date - INTERVAL '89 days' AND Latest.kpi_date
AND COALESCE(s.sales_usd,0) > 0
AND btrim(COALESCE(s.customer_code,'')) NOT IN ('', '-')
), '[]'::jsonb) AS customer_keys_90d,
COALESCE(jsonb_agg(DISTINCT btrim(s.customer_code)) FILTER (
WHERE s.sales_date BETWEEN Latest.kpi_date - INTERVAL '179 days' AND Latest.kpi_date
AND COALESCE(s.sales_usd,0) > 0
AND btrim(COALESCE(s.customer_code,'')) NOT IN ('', '-')
), '[]'::jsonb) AS customer_keys_180d,
COALESCE(jsonb_agg(DISTINCT btrim(s.customer_code)) FILTER (
WHERE s.sales_date BETWEEN Latest.kpi_date - INTERVAL '359 days' AND Latest.kpi_date
AND COALESCE(s.sales_usd,0) > 0
AND btrim(COALESCE(s.customer_code,'')) NOT IN ('', '-')
), '[]'::jsonb) AS customer_keys_365d,
COALESCE(jsonb_agg(DISTINCT btrim(s.customer_code)) FILTER (
WHERE s.sales_date BETWEEN DATE '2022-01-01' AND Latest.kpi_date
AND COALESCE(s.sales_usd,0) > 0
AND btrim(COALESCE(s.customer_code,'')) NOT IN ('', '-')
), '[]'::jsonb) AS customer_keys_total
FROM (
SELECT
s.*,
btrim(regexp_replace(COALESCE(s.market_key,''), '^.*[|]', '')) AS display_market_key
FROM mk_product_performance_sales_daily s
) s
CROSS JOIN Latest
WHERE s.sales_date BETWEEN DATE '2022-01-01' AND Latest.kpi_date
AND upper(translate(btrim(COALESCE(s.urun_ilk_grubu,'')), U&'\0130\015E\011E\00DC\00D6\00C7\0131\015F\011F\00FC\00F6\00E7', 'ISGUOCisguoc')) NOT IN ('MALZEMELI FASON', 'MALZEMESIZ FASON', 'MAZLEMELI FASON', 'MAZEMESIZ FASON', 'DIGER')
GROUP BY s.product_code, s.color_code, s.yaka_kodu, s.market_key
)
SELECT jsonb_build_object(
'product_code', product_code,
'color_code', color_code,
'yaka_kodu', yaka_kodu,
'market_key', market_key,
'__market_keys_90d', market_keys_90d,
'__market_keys_180d', market_keys_180d,
'__market_keys_365d', market_keys_365d,
'__market_keys_total', market_keys_total,
'__customer_keys_90d', customer_keys_90d,
'__customer_keys_180d', customer_keys_180d,
'__customer_keys_365d', customer_keys_365d,
'__customer_keys_total', customer_keys_total
)
FROM Spread`
spreadRows, err := queryProductPerformanceJSONRows(ctx, pg, query)
if err != nil {
log.Printf("[ProductPerformanceRefresh] product sales spread keys skipped err=%v", err)
return rows
}
byKey := make(map[string]map[string]any, len(spreadRows))
for _, row := range spreadRows {
key := productPerformanceMapMarketVariantKey(row)
if key != "" {
byKey[key] = row
}
}
for _, row := range rows {
spread := byKey[productPerformanceMapMarketVariantKey(row)]
if spread == nil {
continue
}
for _, suffix := range productPerformancePeriodSuffixes() {
for _, prefix := range []string{"__market_keys_", "__customer_keys_"} {
field := prefix + suffix
if value, ok := spread[field]; ok {
row[field] = value
}
}
}
}
return rows
@@ -5181,23 +5509,21 @@ type productPerformanceGroupedSnapshotAvgState struct {
}
type productPerformanceGroupedSnapshotNode struct {
Key string
Level int
Field string
Value string
Row map[string]any
Count int
Children map[string]*productPerformanceGroupedSnapshotNode
ChildOrder []string
StockMetricSeen map[string]map[string]bool
IdleSeen map[string]bool
Avg map[string]*productPerformanceGroupedSnapshotAvgState
BucketCounts map[string]int
Image map[string]any
Market90Seen map[string]bool
MarketTotalSeen map[string]bool
Customer90Seen map[string]bool
CustomerTotalSeen map[string]bool
Key string
Level int
Field string
Value string
Row map[string]any
Count int
Children map[string]*productPerformanceGroupedSnapshotNode
ChildOrder []string
StockMetricSeen map[string]map[string]bool
IdleSeen map[string]bool
Avg map[string]*productPerformanceGroupedSnapshotAvgState
BucketCounts map[string]int
Image map[string]any
MarketSeen map[string]map[string]bool
CustomerSeen map[string]map[string]bool
}
func buildProductPerformanceGroupedSnapshotRows(sourceRows []map[string]any, levels []string, mode string) []map[string]any {
@@ -5238,9 +5564,89 @@ 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)
}
for _, suffix := range productPerformancePeriodSuffixes() {
field := "stock_turnover_" + suffix
if !productPerformanceRowsHaveField(childRows, field) {
continue
}
row[field] = weightedAverageProductPerformanceRows(childRows, field, "sales_qty_"+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") != "" {
@@ -5253,7 +5659,7 @@ func (n *productPerformanceGroupedSnapshotNode) add(row map[string]any) {
n.BucketCounts[bucket]++
}
for key, value := range row {
if key == "row_key" || key == "key" || isProductPerformanceMarginField(key) {
if key == "row_key" || key == "key" || isProductPerformanceInternalGroupField(key) || isProductPerformanceMarginField(key) {
continue
}
switch {
@@ -5324,34 +5730,36 @@ func (n *productPerformanceGroupedSnapshotNode) addDistinctVariantMetric(row map
func (n *productPerformanceGroupedSnapshotNode) addDistinctSpread(row map[string]any) {
market := displayProductPerformanceMarketName(stringFromMap(row, "market_key"))
if market != "" && market != "STOK" {
if floatFromMap(row, "sales_usd_90d") > 0 {
if n.Market90Seen == nil {
n.Market90Seen = map[string]bool{}
for _, suffix := range productPerformancePeriodSuffixes() {
if floatFromMap(row, "sales_usd_"+suffix) > 0 {
if n.MarketSeen == nil {
n.MarketSeen = map[string]map[string]bool{}
}
if n.MarketSeen[suffix] == nil {
n.MarketSeen[suffix] = map[string]bool{}
}
n.MarketSeen[suffix][market] = true
}
n.Market90Seen[market] = true
}
if floatFromMap(row, "sales_usd_total") > 0 {
if n.MarketTotalSeen == nil {
n.MarketTotalSeen = map[string]bool{}
}
n.MarketTotalSeen[market] = true
}
}
customer := strings.TrimSpace(stringFromMap(row, "customer_code"))
if customer != "" && customer != "-" {
if floatFromMap(row, "sales_usd_90d") > 0 {
if n.Customer90Seen == nil {
n.Customer90Seen = map[string]bool{}
for _, suffix := range productPerformancePeriodSuffixes() {
if floatFromMap(row, "sales_usd_"+suffix) > 0 {
if n.CustomerSeen == nil {
n.CustomerSeen = map[string]map[string]bool{}
}
if n.CustomerSeen[suffix] == nil {
n.CustomerSeen[suffix] = map[string]bool{}
}
n.CustomerSeen[suffix][customer] = true
}
n.Customer90Seen[customer] = true
}
if floatFromMap(row, "sales_usd_total") > 0 {
if n.CustomerTotalSeen == nil {
n.CustomerTotalSeen = map[string]bool{}
}
n.CustomerTotalSeen[customer] = true
}
}
for _, suffix := range productPerformancePeriodSuffixes() {
n.MarketSeen = productPerformanceAddSeenStrings(n.MarketSeen, suffix, productPerformanceStringSliceFromMap(row, "__market_keys_"+suffix))
n.CustomerSeen = productPerformanceAddSeenStrings(n.CustomerSeen, suffix, productPerformanceStringSliceFromMap(row, "__customer_keys_"+suffix))
}
}
func appendProductPerformanceGroupedSnapshotNodes(out *[]map[string]any, nodes map[string]*productPerformanceGroupedSnapshotNode, order []string) {
@@ -5387,7 +5795,7 @@ func (n *productPerformanceGroupedSnapshotNode) snapshotRow() map[string]any {
row[key] = state.Sum / state.Count
}
}
applyProductPerformanceDistinctSpread(row, n.Market90Seen, n.MarketTotalSeen, n.Customer90Seen, n.CustomerTotalSeen)
applyProductPerformanceDistinctSpread(row, n.MarketSeen, n.CustomerSeen)
deriveProductPerformanceGroupMetrics(row, n.Field)
if bucket := n.dominantBucket(); bucket != "" {
row["performance_bucket"] = bucket
@@ -5508,14 +5916,12 @@ func clearProductPerformanceGroupDimensions(row map[string]any, groupField, grou
func aggregateProductPerformanceRows(rows []map[string]any, groupField string) map[string]any {
out := map[string]any{}
market90Seen := map[string]bool{}
marketTotalSeen := map[string]bool{}
customer90Seen := map[string]bool{}
customerTotalSeen := map[string]bool{}
marketSeen := map[string]map[string]bool{}
customerSeen := map[string]map[string]bool{}
for _, row := range rows {
addProductPerformanceDistinctSpread(row, market90Seen, marketTotalSeen, customer90Seen, customerTotalSeen)
addProductPerformanceDistinctSpread(row, marketSeen, customerSeen)
for key, value := range row {
if key == "row_key" || key == "key" {
if key == "row_key" || key == "key" || isProductPerformanceInternalGroupField(key) {
continue
}
if isProductPerformanceMarginField(key) {
@@ -5541,6 +5947,9 @@ func aggregateProductPerformanceRows(rows []map[string]any, groupField string) m
}
for _, row := range rows {
for key := range row {
if isProductPerformanceInternalGroupField(key) {
continue
}
if isProductPerformanceMarginField(key) {
continue
}
@@ -5549,62 +5958,120 @@ func aggregateProductPerformanceRows(rows []map[string]any, groupField string) m
}
}
}
applyProductPerformanceDistinctSpread(out, market90Seen, marketTotalSeen, customer90Seen, customerTotalSeen)
applyProductPerformanceDistinctSpread(out, marketSeen, customerSeen)
deriveProductPerformanceGroupMetrics(out, groupField)
out["performance_bucket"] = dominantProductPerformanceValue(rows, "performance_bucket")
return out
}
func addProductPerformanceDistinctSpread(row map[string]any, market90Seen, marketTotalSeen, customer90Seen, customerTotalSeen map[string]bool) {
func addProductPerformanceDistinctSpread(row map[string]any, marketSeen, customerSeen map[string]map[string]bool) {
market := displayProductPerformanceMarketName(stringFromMap(row, "market_key"))
if market != "" && market != "STOK" {
if floatFromMap(row, "sales_usd_90d") > 0 {
market90Seen[market] = true
}
if floatFromMap(row, "sales_usd_total") > 0 {
marketTotalSeen[market] = true
for _, suffix := range productPerformancePeriodSuffixes() {
if floatFromMap(row, "sales_usd_"+suffix) > 0 {
if marketSeen[suffix] == nil {
marketSeen[suffix] = map[string]bool{}
}
marketSeen[suffix][market] = true
}
}
}
customer := strings.TrimSpace(stringFromMap(row, "customer_code"))
if customer != "" && customer != "-" {
if floatFromMap(row, "sales_usd_90d") > 0 {
customer90Seen[customer] = true
for _, suffix := range productPerformancePeriodSuffixes() {
if floatFromMap(row, "sales_usd_"+suffix) > 0 {
if customerSeen[suffix] == nil {
customerSeen[suffix] = map[string]bool{}
}
customerSeen[suffix][customer] = true
}
}
if floatFromMap(row, "sales_usd_total") > 0 {
customerTotalSeen[customer] = true
}
for _, suffix := range productPerformancePeriodSuffixes() {
marketSeen = productPerformanceAddSeenStrings(marketSeen, suffix, productPerformanceStringSliceFromMap(row, "__market_keys_"+suffix))
customerSeen = productPerformanceAddSeenStrings(customerSeen, suffix, productPerformanceStringSliceFromMap(row, "__customer_keys_"+suffix))
}
}
func applyProductPerformanceDistinctSpread(row map[string]any, marketSeen, customerSeen map[string]map[string]bool) {
for _, suffix := range productPerformancePeriodSuffixes() {
marketField := "market_count_" + suffix
customerField := "customer_count_" + suffix
if seen := marketSeen[suffix]; len(seen) > 0 {
row[marketField] = len(seen)
}
if seen := customerSeen[suffix]; len(seen) > 0 {
row[customerField] = len(seen)
}
if floatFromMap(row, "sales_usd_"+suffix) > 0 && (suffix == "90d" || suffix == "total") {
if intFromMap(row, marketField) == 0 {
row[marketField] = 1
}
if intFromMap(row, customerField) == 0 {
if suffix == "total" {
row[customerField] = maxInt(1, intFromMap(row, "customer_count_90d"))
} else {
row[customerField] = 1
}
}
}
}
}
func applyProductPerformanceDistinctSpread(row map[string]any, market90Seen, marketTotalSeen, customer90Seen, customerTotalSeen map[string]bool) {
if len(market90Seen) > 0 {
row["market_count_90d"] = len(market90Seen)
func productPerformanceAddSeenStrings(seen map[string]map[string]bool, suffix string, values []string) map[string]map[string]bool {
if len(values) == 0 {
return seen
}
if len(marketTotalSeen) > 0 {
row["market_count_total"] = len(marketTotalSeen)
if seen == nil {
seen = map[string]map[string]bool{}
}
if len(customer90Seen) > 0 {
row["customer_count_90d"] = len(customer90Seen)
if seen[suffix] == nil {
seen[suffix] = map[string]bool{}
}
if len(customerTotalSeen) > 0 {
row["customer_count_total"] = len(customerTotalSeen)
}
if floatFromMap(row, "sales_usd_90d") > 0 {
if intFromMap(row, "market_count_90d") == 0 {
row["market_count_90d"] = 1
}
if intFromMap(row, "customer_count_90d") == 0 {
row["customer_count_90d"] = 1
for _, value := range values {
value = strings.TrimSpace(value)
if value == "" || value == "-" {
continue
}
seen[suffix][value] = true
}
if floatFromMap(row, "sales_usd_total") > 0 {
if intFromMap(row, "market_count_total") == 0 {
row["market_count_total"] = maxInt(1, intFromMap(row, "market_count_90d"))
}
if intFromMap(row, "customer_count_total") == 0 {
row["customer_count_total"] = maxInt(1, intFromMap(row, "customer_count_90d"))
}
return seen
}
func productPerformanceStringSliceFromMap(row map[string]any, field string) []string {
value, ok := row[field]
if !ok || value == nil {
return nil
}
switch v := value.(type) {
case []string:
return v
case []any:
out := make([]string, 0, len(v))
for _, item := range v {
text := strings.TrimSpace(fmt.Sprint(item))
if text != "" {
out = append(out, text)
}
}
return out
case string:
text := strings.TrimSpace(v)
if text == "" {
return nil
}
var parsed []string
if strings.HasPrefix(text, "[") && json.Unmarshal([]byte(text), &parsed) == nil {
return parsed
}
return []string{text}
default:
return nil
}
}
func isProductPerformanceInternalGroupField(field string) bool {
return strings.HasPrefix(field, "__")
}
func productPerformanceGroupRecommendation(row map[string]any, groupField string, count int) string {
@@ -5711,18 +6178,55 @@ func productPerformanceMapVariantKey(row map[string]any) string {
func deriveProductPerformanceGroupMetrics(out map[string]any, groupField string) {
normalizeProductPerformanceCostFields(out)
for _, suffix := range []string{"90d", "180d", "365d", "total"} {
isGroup := strings.TrimSpace(groupField) != ""
if isGroup {
out["group_field"] = groupField
}
preservedCustomerScores := map[string]float64{}
preservedProductScores := map[string]float64{}
preservedStockTurnovers := map[string]float64{}
for _, suffix := range productPerformancePeriodSuffixes() {
if score, ok := productPerformanceOptionalFloat(out, "customer_score_"+suffix); ok {
preservedCustomerScores[suffix] = score
}
if score, ok := productPerformanceOptionalFloat(out, "performance_score_"+suffix); ok {
preservedProductScores[suffix] = score
}
if isGroup {
if turnover, ok := productPerformanceOptionalFloat(out, "stock_turnover_"+suffix); ok {
preservedStockTurnovers[suffix] = turnover
}
}
}
if score, ok := productPerformanceOptionalFloat(out, "performance_score"); ok {
if _, exists := preservedProductScores["90d"]; !exists {
preservedProductScores["90d"] = score
}
}
for _, suffix := range productPerformancePeriodSuffixes() {
sales := floatFromMap(out, "sales_usd_"+suffix)
qty := floatFromMap(out, "sales_qty_"+suffix)
stockQty := floatFromMap(out, "stock_qty")
turnoverBase := floatFromMap(out, "avg_stock_"+suffix)
if turnoverBase <= 0 {
if turnoverBase <= 0 && !isGroup {
turnoverBase = stockQty
}
if turnoverBase > 0 {
out["stock_turnover_"+suffix] = qty / turnoverBase
} else {
out["stock_turnover_"+suffix] = 0
days := productPerformancePeriodDays(out, suffix)
avgDaily := floatFromMap(out, "avg_daily_sales_"+suffix)
if days > 0 {
avgDaily = qty / days
out["avg_daily_sales_"+suffix] = avgDaily
}
if avgDaily > 0 && turnoverBase > 0 {
out["stock_days_"+suffix] = turnoverBase / avgDaily
} else if qty <= 0 && stockQty > 0 {
out["stock_days_"+suffix] = 9999
} else if _, ok := out["stock_days_"+suffix]; !ok {
out["stock_days_"+suffix] = 0
}
out["stock_turnover_"+suffix] = productPerformanceAnnualizedStockTurnover(qty, turnoverBase, days)
if turnover, ok := preservedStockTurnovers[suffix]; ok {
out["stock_turnover_"+suffix] = turnover
}
if qty > 0 {
out["avg_price_usd_"+suffix] = sales / qty
@@ -5775,37 +6279,19 @@ func deriveProductPerformanceGroupMetrics(out map[string]any, groupField string)
if _, ok := out["net_stock_after_order"]; ok || orderQty > 0 {
out["net_stock_after_order"] = floatFromMap(out, "stock_qty") - orderQty
}
if _, ok := out["customer_score_90d"]; !ok {
out["customer_score_90d"] = productPerformanceCustomerSalesPeriodScore(rowPeriodMetricMap(out, "90d"))
}
if _, ok := out["customer_score_180d"]; !ok {
out["customer_score_180d"] = productPerformanceCustomerSalesPeriodScore(rowPeriodMetricMap(out, "180d"))
}
if _, ok := out["customer_score_365d"]; !ok {
out["customer_score_365d"] = productPerformanceCustomerSalesPeriodScore(rowPeriodMetricMap(out, "365d"))
}
if _, ok := out["customer_score_total"]; !ok {
out["customer_score_total"] = productPerformanceCustomerSalesPeriodScore(rowPeriodMetricMap(out, "total"))
}
if _, ok := out["performance_score_90d"]; !ok {
out["performance_score_90d"] = productPerformanceSalesPeriodScore(out, "90d")
}
if _, ok := out["performance_score_180d"]; !ok {
out["performance_score_180d"] = productPerformanceSalesPeriodScore(out, "180d")
}
if _, ok := out["performance_score_365d"]; !ok {
out["performance_score_365d"] = productPerformanceSalesPeriodScore(out, "365d")
}
if _, ok := out["performance_score_total"]; !ok {
out["performance_score_total"] = productPerformanceSalesPeriodScore(out, "total")
}
if _, ok := out["performance_score"]; !ok {
if score, exists := productPerformanceOptionalFloat(out, "performance_score_90d"); exists {
out["performance_score"] = score
for _, suffix := range productPerformancePeriodSuffixes() {
if score, ok := preservedCustomerScores[suffix]; ok {
out["customer_score_"+suffix] = score
} else {
out["performance_score"] = productPerformanceGroupScore(out, groupField)
out["customer_score_"+suffix] = productPerformanceCustomerSalesPeriodScore(rowPeriodMetricMap(out, suffix))
}
if score, ok := preservedProductScores[suffix]; ok {
out["performance_score_"+suffix] = score
} else {
out["performance_score_"+suffix] = productPerformanceSalesPeriodScore(out, suffix)
}
}
out["performance_score"] = out["performance_score_90d"]
if floatFromMap(out, "order_qty") > 0 || floatFromMap(out, "order_usd") > 0 {
score := productPerformanceOrderGroupScore(out)
out["performance_score_90d"] = score
@@ -5832,11 +6318,69 @@ func normalizeProductPerformanceCostFields(row map[string]any) {
}
}
normalize("cost_price_usd", "base_price_usd")
for _, suffix := range []string{"90d", "180d", "365d", "total"} {
for _, suffix := range productPerformancePeriodSuffixes() {
normalize("cost_price_usd_"+suffix, "base_price_usd_"+suffix)
}
}
func productPerformancePeriodSuffixes() []string {
return []string{"90d", "180d", "365d", "total"}
}
func productPerformancePeriodDays(row map[string]any, suffix string) float64 {
switch suffix {
case "90d":
return 90
case "180d":
return 180
case "365d":
return 360
case "total":
start := parseProductPerformanceDate(stringFromMap(row, "period_start"))
if start.IsZero() {
start = time.Date(2022, 1, 1, 0, 0, 0, 0, time.UTC)
}
end := parseProductPerformanceDate(stringFromMap(row, "period_end"))
if end.IsZero() {
end = parseProductPerformanceDate(stringFromMap(row, "kpi_date"))
}
if end.IsZero() || end.Before(start) {
return 0
}
return end.Sub(start).Hours()/24 + 1
default:
return 0
}
}
const productPerformanceStockTurnoverYearDays = 360.0
func productPerformanceAnnualizedStockTurnover(salesQty, avgStock, periodDays float64) float64 {
if salesQty <= 0 || avgStock <= 0 {
return 0
}
raw := salesQty / avgStock
if periodDays <= 0 {
return raw
}
return raw * productPerformanceStockTurnoverYearDays / periodDays
}
func parseProductPerformanceDate(value string) time.Time {
value = strings.TrimSpace(value)
if value == "" {
return time.Time{}
}
if len(value) >= len("2006-01-02") {
value = value[:len("2006-01-02")]
}
t, err := time.Parse("2006-01-02", value)
if err != nil {
return time.Time{}
}
return t
}
func productPerformanceOptionalFloat(row map[string]any, field string) (float64, bool) {
value, ok := row[field]
if !ok {
@@ -5898,8 +6442,12 @@ func productPerformanceSalesPeriodScore(row map[string]any, suffix string) float
salesQty := floatFromMap(row, "sales_qty_"+suffix)
stockTurnover := floatFromMap(row, "stock_turnover_"+suffix)
if stockTurnover == 0 {
if stockQty := floatFromMap(row, "stock_qty"); stockQty > 0 {
stockTurnover = salesQty / stockQty
avgStock := floatFromMap(row, "avg_stock_"+suffix)
if avgStock <= 0 && strings.TrimSpace(stringFromMap(row, "group_field")) == "" {
avgStock = floatFromMap(row, "stock_qty")
}
if avgStock > 0 {
stockTurnover = productPerformanceAnnualizedStockTurnover(salesQty, avgStock, productPerformancePeriodDays(row, suffix))
}
}
return productPerformanceProductScore(
@@ -5910,6 +6458,7 @@ func productPerformanceSalesPeriodScore(row map[string]any, suffix string) float
stockTurnover,
productPerformancePeriodCount(row, "market_count", suffix),
productPerformancePeriodCount(row, "customer_count", suffix),
productPerformancePeriodDays(row, suffix),
)
}
@@ -5953,19 +6502,54 @@ func productPerformanceCustomerSalesPeriodScore(row map[string]any) float64 {
return productPerformanceCustomerScore(suffix, salesUSD, margin, productCount, salesQty)
}
func productPerformanceProductScore(suffix string, salesUSD, salesIndex, margin, stockTurnover, marketCount, customerCount float64) float64 {
func productPerformanceProductScore(suffix string, salesUSD, salesIndex, margin, stockTurnover, marketCount, customerCount float64, periodDays ...float64) float64 {
if salesUSD <= 0 {
return 1
}
revenueScore := productPerformanceRevenueScore(suffix, salesUSD, salesIndex, productPerformanceProductRevenueTarget(suffix))
days := productPerformanceScorePeriodDays(suffix, periodDays...)
revenueScore := productPerformanceRevenueScore(suffix, salesUSD, salesIndex, productPerformanceProductRevenueTargetForDays(suffix, days))
score := 0.30*productPerformanceMarginComponentScore(margin) +
0.20*productPerformanceRatioScore(stockTurnover, 1.50) +
0.20*productPerformanceRatioScore(stockTurnover, productPerformanceStockTurnoverTarget(suffix)) +
0.20*revenueScore +
0.15*productPerformanceRatioScore(marketCount, 8) +
0.15*productPerformanceRatioScore(customerCount, 25)
0.05*productPerformanceRatioScore(marketCount, productPerformanceMarketSpreadTarget(suffix)) +
0.25*productPerformanceRatioScore(customerCount, productPerformanceCustomerSpreadTargetForDays(suffix, days))
return productPerformanceRoundScore(score)
}
func productPerformanceStockTurnoverTarget(suffix string) float64 {
return 4
}
func productPerformanceMarketSpreadTarget(suffix string) float64 {
switch suffix {
case "90d":
return 3
case "180d":
return 3
case "365d":
return 6
default:
return 6
}
}
func productPerformanceCustomerSpreadTarget(suffix string) float64 {
return productPerformanceCustomerSpreadTargetForDays(suffix, productPerformanceScorePeriodDays(suffix))
}
func productPerformanceCustomerSpreadTargetForDays(suffix string, periodDays float64) float64 {
switch suffix {
case "90d":
return 8
case "180d":
return 20
case "365d":
return 50
default:
return 20 * productPerformanceTotalPeriodMultiplier(periodDays)
}
}
func productPerformanceCustomerScore(suffix string, salesUSD, margin, productGroupCount, salesQty float64) float64 {
if salesUSD <= 0 {
return 1
@@ -5989,7 +6573,7 @@ func productPerformanceRelativeIndex(value, average float64) float64 {
}
func productPerformanceMarginComponentScore(margin float64) float64 {
return productPerformanceRatioScore(maxFloat(0, margin), 0.40)
return productPerformanceRatioScore(maxFloat(0, margin), 0.45)
}
func productPerformanceRatioScore(value, target float64) float64 {
@@ -6010,18 +6594,49 @@ func productPerformanceRoundScore(score float64) float64 {
}
func productPerformanceProductRevenueTarget(suffix string) float64 {
return productPerformanceProductRevenueTargetForDays(suffix, productPerformanceScorePeriodDays(suffix))
}
func productPerformanceProductRevenueTargetForDays(suffix string, periodDays float64) float64 {
switch suffix {
case "180d":
return 20000
return 50000
case "365d":
return 40000
return 100000
case "total":
return 120000
return 50000 * productPerformanceTotalPeriodMultiplier(periodDays)
default:
return 10000
return 25000
}
}
func productPerformanceScorePeriodDays(suffix string, periodDays ...float64) float64 {
if len(periodDays) > 0 && periodDays[0] > 0 {
return periodDays[0]
}
switch suffix {
case "90d":
return 90
case "180d":
return 180
case "365d":
return 360
case "total":
return productPerformancePeriodDays(map[string]any{
"kpi_date": time.Now().Format("2006-01-02"),
}, "total")
default:
return 0
}
}
func productPerformanceTotalPeriodMultiplier(periodDays float64) float64 {
if periodDays <= 0 {
periodDays = 180
}
return maxFloat(1, periodDays/180.0)
}
func productPerformanceCustomerRevenueTarget(suffix string) float64 {
switch suffix {
case "180d":
@@ -6131,7 +6746,7 @@ func sanitizeProductPerformanceGroupLevels(levels []string) []string {
func defaultProductPerformanceGroupLevels(mode string) []string {
switch mode {
case "sales_color_yaka_market_customer":
return []string{"color_yaka", "urun_ilk_grubu", "askili_yan", "kategori", "urun_ana_grubu", "urun_alt_grubu", "product_code", "country", "market_key", "customer_segment", "customer_code", "customer_name"}
return []string{"urun_ana_grubu", "color_yaka", "market_key", "customer_code", "customer_name", "urun_alt_grubu", "product_code"}
case "product_detail":
return []string{"urun_alt_grubu", "product_code", "color_yaka", "market_key"}
case "idle":
@@ -6172,7 +6787,16 @@ func mapGroupValue(row map[string]any, field string) string {
}
func shouldSumProductPerformanceField(field string) bool {
return strings.HasSuffix(field, "_qty") ||
return strings.HasPrefix(field, "sales_qty_") ||
strings.HasPrefix(field, "sales_usd_") ||
strings.HasPrefix(field, "avg_daily_sales_") ||
strings.HasPrefix(field, "gross_profit_") ||
strings.HasPrefix(field, "invoice_count_") ||
strings.HasPrefix(field, "market_count_") ||
strings.HasPrefix(field, "customer_count_") ||
strings.HasPrefix(field, "product_group_count_") ||
strings.HasPrefix(field, "product_count_") ||
strings.HasSuffix(field, "_qty") ||
strings.HasSuffix(field, "_usd") ||
strings.HasSuffix(field, "_count") ||
strings.HasSuffix(field, "_value_usd") ||
@@ -6189,6 +6813,9 @@ func shouldSumProductPerformanceField(field string) bool {
}
func shouldAverageProductPerformanceField(field string) bool {
if strings.HasPrefix(field, "avg_daily_sales_") {
return false
}
return strings.HasPrefix(field, "avg_") ||
strings.HasPrefix(field, "unit_") ||
strings.HasPrefix(field, "base_price") ||
@@ -6206,6 +6833,9 @@ func productPerformanceMetricWeightField(field string) string {
if productPerformanceUsesCostWeight(field) {
return "__product_cost_weight"
}
if strings.HasPrefix(field, "stock_turnover") {
return "sales_qty_" + productPerformanceScoreSuffix(field)
}
if strings.Contains(field, "_180d") {
return "sales_qty_180d"
}
@@ -6264,23 +6894,10 @@ func productPerformanceScoreSuffix(field string) string {
}
func productPerformanceScoreWeight(row map[string]any, suffix string) float64 {
if weight := floatFromMap(row, "sales_usd_"+suffix); weight > 0 {
return weight
}
if weight := floatFromMap(row, "sales_qty_"+suffix); weight > 0 {
return weight
}
stockQty := floatFromMap(row, "stock_qty")
if stockQty <= 0 {
return 1
}
if cost := floatFromMap(row, "cost_price_usd_"+suffix); cost > 0 {
return stockQty * cost
}
if cost := floatFromMap(row, "cost_price_usd"); cost > 0 {
return stockQty * cost
}
return stockQty
return 0
}
func productPerformanceCostWeight(row map[string]any) float64 {
+94 -25
View File
@@ -486,6 +486,13 @@ SalesAgg AS (
SUM(sales_usd) FILTER (WHERE sales_date >= $1::date - INTERVAL '359 days') AS sales_usd_365d,
SUM(sales_usd) FILTER (WHERE sales_date >= DATE '2022-01-01') AS sales_usd_total,
COUNT(DISTINCT NULLIF(customer_code, '-')) FILTER (WHERE sales_date >= $1::date - INTERVAL '89 days' AND COALESCE(sales_usd, 0) > 0) AS customer_count_90d,
COUNT(DISTINCT NULLIF(customer_code, '-')) FILTER (WHERE sales_date >= $1::date - INTERVAL '179 days' AND COALESCE(sales_usd, 0) > 0) AS customer_count_180d,
COUNT(DISTINCT NULLIF(customer_code, '-')) FILTER (WHERE sales_date >= $1::date - INTERVAL '359 days' AND COALESCE(sales_usd, 0) > 0) AS customer_count_365d,
COUNT(DISTINCT NULLIF(customer_code, '-')) FILTER (WHERE sales_date >= DATE '2022-01-01' AND COALESCE(sales_usd, 0) > 0) AS customer_count_total,
MIN(sales_date) FILTER (WHERE sales_date >= $1::date - INTERVAL '89 days') AS first_sale_date_90d,
MIN(sales_date) FILTER (WHERE sales_date >= $1::date - INTERVAL '179 days') AS first_sale_date_180d,
MIN(sales_date) FILTER (WHERE sales_date >= $1::date - INTERVAL '359 days') AS first_sale_date_365d,
MIN(sales_date) FILTER (WHERE sales_date >= DATE '2022-01-01') AS first_sale_date_total,
MAX(sales_date) AS last_sale_date,
MAX(last_ref_number) AS last_ref_number
FROM mk_product_performance_sales_daily
@@ -500,7 +507,9 @@ Scope AS (
item_description, kategori, seri, yas_grubu, askili_yan, urun_ilk_grubu, urun_ana_grubu, urun_alt_grubu,
sales_qty_30d, sales_qty_90d, sales_qty_180d, sales_qty_365d, sales_qty_730d, sales_qty_total,
sales_usd_30d, sales_usd_90d, sales_usd_180d, sales_usd_365d, sales_usd_total,
customer_count_90d, last_sale_date, last_ref_number
customer_count_90d, customer_count_180d, customer_count_365d, customer_count_total,
first_sale_date_90d, first_sale_date_180d, first_sale_date_365d, first_sale_date_total,
last_sale_date, last_ref_number
FROM SalesAgg
UNION ALL
SELECT
@@ -528,6 +537,13 @@ Scope AS (
0 AS sales_usd_365d,
0 AS sales_usd_total,
0 AS customer_count_90d,
0 AS customer_count_180d,
0 AS customer_count_365d,
0 AS customer_count_total,
NULL::date AS first_sale_date_90d,
NULL::date AS first_sale_date_180d,
NULL::date AS first_sale_date_365d,
NULL::date AS first_sale_date_total,
NULL::date AS last_sale_date,
'' AS last_ref_number
FROM LatestStock ls
@@ -570,10 +586,10 @@ Base AS (
COALESCE(s.sales_qty_180d, 0) / 180.0 AS avg_daily_sales_180d,
COALESCE(s.sales_qty_365d, 0) / 360.0 AS avg_daily_sales_365d,
COALESCE(s.sales_qty_total, 0) / GREATEST(1, ($1::date - DATE '2022-01-01') + 1) AS avg_daily_sales_total,
(COALESCE(s90.stock_qty, 0) + COALESCE(ls.stock_qty, 0)) / 2.0 AS avg_stock_90d,
(COALESCE(s180.stock_qty, 0) + COALESCE(ls.stock_qty, 0)) / 2.0 AS avg_stock_180d,
(COALESCE(s365.stock_qty, 0) + COALESCE(ls.stock_qty, 0)) / 2.0 AS avg_stock_365d,
(COALESCE(stotal.stock_qty, 0) + COALESCE(ls.stock_qty, 0)) / 2.0 AS avg_stock_total,
(COALESCE(s90.stock_qty, ls.stock_qty, 0) + COALESCE(ls.stock_qty, 0)) / 2.0 AS avg_stock_90d,
(COALESCE(s180.stock_qty, ls.stock_qty, 0) + COALESCE(ls.stock_qty, 0)) / 2.0 AS avg_stock_180d,
(COALESCE(s365.stock_qty, ls.stock_qty, 0) + COALESCE(ls.stock_qty, 0)) / 2.0 AS avg_stock_365d,
(COALESCE(stotal.stock_qty, ls.stock_qty, 0) + COALESCE(ls.stock_qty, 0)) / 2.0 AS avg_stock_total,
CASE WHEN COALESCE(s.sales_qty_90d, 0) = 0 THEN 0 ELSE COALESCE(s.sales_usd_90d, 0) / NULLIF(s.sales_qty_90d, 0) END AS avg_price_usd_90d,
CASE WHEN COALESCE(s.sales_qty_180d, 0) = 0 THEN 0 ELSE COALESCE(s.sales_usd_180d, 0) / NULLIF(s.sales_qty_180d, 0) END AS avg_price_usd_180d,
COALESCE(s.sales_usd_90d, 0) - (COALESCE(s.sales_qty_90d, 0) * COALESCE(pd.cost_price_usd, 0)) AS gross_profit_usd_90d,
@@ -590,11 +606,47 @@ Base AS (
CASE WHEN COALESCE(s.sales_qty_180d, 0) = 0 THEN 0 ELSE (COALESCE(s.sales_usd_180d, 0) / NULLIF(s.sales_qty_180d, 0)) - COALESCE(pd.base_price_usd, 0) END AS unit_profit_base_180d
FROM Scope s
LEFT JOIN LatestStock ls ON ls.product_code=s.product_code AND ls.color_code=s.color_code AND ls.yaka_kodu=s.yaka_kodu
LEFT JOIN Stock90Start s90 ON s90.product_code=s.product_code AND s90.color_code=s.color_code AND s90.yaka_kodu=s.yaka_kodu
LEFT JOIN Stock180Start s180 ON s180.product_code=s.product_code AND s180.color_code=s.color_code AND s180.yaka_kodu=s.yaka_kodu
LEFT JOIN Stock365Start s365 ON s365.product_code=s.product_code AND s365.color_code=s.color_code AND s365.yaka_kodu=s.yaka_kodu
LEFT JOIN StockTotalStart stotal ON stotal.product_code=s.product_code AND stotal.color_code=s.color_code AND stotal.yaka_kodu=s.yaka_kodu
LEFT JOIN PriceDim pd ON pd.product_code=s.product_code
LEFT JOIN LATERAL (
SELECT x.stock_qty
FROM mk_product_performance_stock_daily x
WHERE x.product_code=s.product_code
AND x.color_code=s.color_code
AND x.yaka_kodu=s.yaka_kodu
AND x.stock_date <= COALESCE(s.first_sale_date_90d, $1::date - INTERVAL '89 days')
ORDER BY x.stock_date DESC
LIMIT 1
) s90 ON TRUE
LEFT JOIN LATERAL (
SELECT x.stock_qty
FROM mk_product_performance_stock_daily x
WHERE x.product_code=s.product_code
AND x.color_code=s.color_code
AND x.yaka_kodu=s.yaka_kodu
AND x.stock_date <= COALESCE(s.first_sale_date_180d, $1::date - INTERVAL '179 days')
ORDER BY x.stock_date DESC
LIMIT 1
) s180 ON TRUE
LEFT JOIN LATERAL (
SELECT x.stock_qty
FROM mk_product_performance_stock_daily x
WHERE x.product_code=s.product_code
AND x.color_code=s.color_code
AND x.yaka_kodu=s.yaka_kodu
AND x.stock_date <= COALESCE(s.first_sale_date_365d, $1::date - INTERVAL '359 days')
ORDER BY x.stock_date DESC
LIMIT 1
) s365 ON TRUE
LEFT JOIN LATERAL (
SELECT x.stock_qty
FROM mk_product_performance_stock_daily x
WHERE x.product_code=s.product_code
AND x.color_code=s.color_code
AND x.yaka_kodu=s.yaka_kodu
AND x.stock_date <= COALESCE(s.first_sale_date_total, DATE '2022-01-01')
ORDER BY x.stock_date DESC
LIMIT 1
) stotal ON TRUE
WHERE upper(translate(btrim(COALESCE(NULLIF(s.urun_ilk_grubu,''), pd.urun_ilk_grubu, '')), U&'\0130\015E\011E\00DC\00D6\00C7\0131\015F\011F\00FC\00F6\00E7', 'ISGUOCisguoc')) NOT IN ('MALZEMELI FASON', 'MALZEMESIZ FASON', 'MAZLEMELI FASON', 'MAZEMESIZ FASON', 'DIGER')
),
Spread AS (
@@ -602,15 +654,20 @@ Spread AS (
product_code,
color_code,
yaka_kodu,
COUNT(DISTINCT NULLIF(NULLIF(market_key, 'STOK'), '')) AS market_count_90d
COUNT(DISTINCT NULLIF(NULLIF(market_key, 'STOK'), '')) FILTER (WHERE COALESCE(sales_usd_90d, 0) > 0) AS market_count_90d,
COUNT(DISTINCT NULLIF(NULLIF(market_key, 'STOK'), '')) FILTER (WHERE COALESCE(sales_usd_180d, 0) > 0) AS market_count_180d,
COUNT(DISTINCT NULLIF(NULLIF(market_key, 'STOK'), '')) FILTER (WHERE COALESCE(sales_usd_365d, 0) > 0) AS market_count_365d,
COUNT(DISTINCT NULLIF(NULLIF(market_key, 'STOK'), '')) FILTER (WHERE COALESCE(sales_usd_total, 0) > 0) AS market_count_total
FROM SalesAgg
WHERE COALESCE(sales_usd_90d, 0) > 0
GROUP BY product_code, color_code, yaka_kodu
),
Market AS (
SELECT
market_key,
AVG(NULLIF(sales_qty_90d, 0)) AS market_avg_sales_qty_90d,
AVG(NULLIF(sales_qty_180d, 0)) AS market_avg_sales_qty_180d,
AVG(NULLIF(sales_qty_365d, 0)) AS market_avg_sales_qty_365d,
AVG(NULLIF(sales_qty_total, 0)) AS market_avg_sales_qty_total,
AVG(NULLIF(avg_price_usd_90d, 0)) AS market_avg_price_usd_90d,
AVG(NULLIF(gross_margin_90d, 0)) AS market_avg_margin_90d
FROM Base
@@ -620,15 +677,21 @@ Scored AS (
SELECT
b.*,
COALESCE(sp.market_count_90d, 0) AS market_count_90d,
COALESCE(sp.market_count_180d, 0) AS market_count_180d,
COALESCE(sp.market_count_365d, 0) AS market_count_365d,
COALESCE(sp.market_count_total, 0) AS market_count_total,
CASE WHEN b.avg_daily_sales_90d = 0 THEN 0 ELSE b.avg_stock_90d / NULLIF(b.avg_daily_sales_90d, 0) END AS stock_days_90d,
CASE WHEN b.avg_daily_sales_180d = 0 THEN 0 ELSE b.avg_stock_180d / NULLIF(b.avg_daily_sales_180d, 0) END AS stock_days_180d,
CASE WHEN b.avg_daily_sales_365d = 0 THEN 0 ELSE b.avg_stock_365d / NULLIF(b.avg_daily_sales_365d, 0) END AS stock_days_365d,
CASE WHEN b.avg_daily_sales_total = 0 THEN 0 ELSE b.avg_stock_total / NULLIF(b.avg_daily_sales_total, 0) END AS stock_days_total,
CASE WHEN b.avg_stock_90d = 0 THEN 0 ELSE b.sales_qty_90d / NULLIF(b.avg_stock_90d, 0) END AS stock_turnover_90d,
CASE WHEN b.avg_stock_180d = 0 THEN 0 ELSE b.sales_qty_180d / NULLIF(b.avg_stock_180d, 0) END AS stock_turnover_180d,
CASE WHEN b.avg_stock_90d = 0 THEN 0 ELSE b.sales_qty_90d / NULLIF(b.avg_stock_90d, 0) * 4.0 END AS stock_turnover_90d,
CASE WHEN b.avg_stock_180d = 0 THEN 0 ELSE b.sales_qty_180d / NULLIF(b.avg_stock_180d, 0) * 2.0 END AS stock_turnover_180d,
CASE WHEN b.avg_stock_365d = 0 THEN 0 ELSE b.sales_qty_365d / NULLIF(b.avg_stock_365d, 0) END AS stock_turnover_365d,
CASE WHEN b.avg_stock_total = 0 THEN 0 ELSE b.sales_qty_total / NULLIF(b.avg_stock_total, 0) END AS stock_turnover_total,
CASE WHEN b.avg_stock_total = 0 THEN 0 ELSE b.sales_qty_total / NULLIF(b.avg_stock_total, 0) * 360.0 / GREATEST(1, ($1::date - DATE '2022-01-01') + 1) END AS stock_turnover_total,
CASE WHEN COALESCE(m.market_avg_sales_qty_90d, 0) = 0 THEN 0 ELSE b.sales_qty_90d / NULLIF(m.market_avg_sales_qty_90d, 0) END AS sales_index_90d,
CASE WHEN COALESCE(m.market_avg_sales_qty_180d, 0) = 0 THEN 0 ELSE b.sales_qty_180d / NULLIF(m.market_avg_sales_qty_180d, 0) END AS sales_index_180d,
CASE WHEN COALESCE(m.market_avg_sales_qty_365d, 0) = 0 THEN 0 ELSE b.sales_qty_365d / NULLIF(m.market_avg_sales_qty_365d, 0) END AS sales_index_365d,
CASE WHEN COALESCE(m.market_avg_sales_qty_total, 0) = 0 THEN 0 ELSE b.sales_qty_total / NULLIF(m.market_avg_sales_qty_total, 0) END AS sales_index_total,
CASE WHEN COALESCE(m.market_avg_price_usd_90d, 0) = 0 THEN 0 ELSE b.avg_price_usd_90d / NULLIF(m.market_avg_price_usd_90d, 0) END AS price_index_90d,
CASE WHEN COALESCE(m.market_avg_margin_90d, 0) = 0 THEN 0 ELSE b.gross_margin_90d / NULLIF(m.market_avg_margin_90d, 0) END AS margin_index_90d
FROM Base b
@@ -640,11 +703,14 @@ INSERT INTO mk_product_performance_kpi_daily (
kategori, seri, yas_grubu, askili_yan, urun_ilk_grubu, urun_ana_grubu, urun_alt_grubu, market_key, stock_qty,
sales_qty_30d, sales_qty_90d, sales_qty_180d, sales_qty_365d, sales_qty_730d, sales_qty_total,
sales_usd_30d, sales_usd_90d, sales_usd_180d, sales_usd_365d, sales_usd_total, avg_daily_sales_90d, avg_daily_sales_180d, avg_daily_sales_365d, avg_daily_sales_total,
avg_stock_90d, avg_stock_180d, avg_stock_365d, avg_stock_total,
stock_days_90d, stock_days_180d, stock_days_365d, stock_days_total, stock_turnover_90d, stock_turnover_180d, stock_turnover_365d, stock_turnover_total,
avg_price_usd_90d, avg_price_usd_180d, cost_price_usd, base_price_usd, base_price_try,
gross_profit_usd_90d, gross_profit_usd_180d, gross_margin_90d, gross_margin_180d,
unit_profit_cost_90d, unit_profit_cost_180d, unit_profit_base_90d, unit_profit_base_180d, market_count_90d, customer_count_90d,
sales_index_90d, price_index_90d, margin_index_90d, performance_score,
unit_profit_cost_90d, unit_profit_cost_180d, unit_profit_base_90d, unit_profit_base_180d,
market_count_90d, market_count_180d, market_count_365d, market_count_total,
customer_count_90d, customer_count_180d, customer_count_365d, customer_count_total,
sales_index_90d, sales_index_180d, sales_index_365d, sales_index_total, price_index_90d, margin_index_90d, performance_score,
performance_bucket, recommendation, last_sale_date, last_ref_number, updated_at
)
SELECT
@@ -653,22 +719,25 @@ SELECT
kategori, seri, yas_grubu, askili_yan, urun_ilk_grubu, urun_ana_grubu, urun_alt_grubu, market_key, stock_qty,
COALESCE(sales_qty_30d, 0), COALESCE(sales_qty_90d, 0), COALESCE(sales_qty_180d, 0), COALESCE(sales_qty_365d, 0), COALESCE(sales_qty_730d, 0), COALESCE(sales_qty_total, 0),
COALESCE(sales_usd_30d, 0), COALESCE(sales_usd_90d, 0), COALESCE(sales_usd_180d, 0), COALESCE(sales_usd_365d, 0), COALESCE(sales_usd_total, 0), COALESCE(avg_daily_sales_90d, 0), COALESCE(avg_daily_sales_180d, 0), COALESCE(avg_daily_sales_365d, 0), COALESCE(avg_daily_sales_total, 0),
COALESCE(avg_stock_90d, 0), COALESCE(avg_stock_180d, 0), COALESCE(avg_stock_365d, 0), COALESCE(avg_stock_total, 0),
COALESCE(stock_days_90d, 0), COALESCE(stock_days_180d, 0), COALESCE(stock_days_365d, 0), COALESCE(stock_days_total, 0), COALESCE(stock_turnover_90d, 0), COALESCE(stock_turnover_180d, 0), COALESCE(stock_turnover_365d, 0), COALESCE(stock_turnover_total, 0),
COALESCE(avg_price_usd_90d, 0), COALESCE(avg_price_usd_180d, 0), COALESCE(cost_price_usd, 0), COALESCE(base_price_usd, 0), COALESCE(base_price_try, 0),
COALESCE(gross_profit_usd_90d, 0), COALESCE(gross_profit_usd_180d, 0), COALESCE(gross_margin_90d, 0), COALESCE(gross_margin_180d, 0),
COALESCE(unit_profit_cost_90d, 0), COALESCE(unit_profit_cost_180d, 0), COALESCE(unit_profit_base_90d, 0), COALESCE(unit_profit_base_180d, 0), COALESCE(market_count_90d, 0), COALESCE(customer_count_90d, 0),
COALESCE(sales_index_90d, 0), COALESCE(price_index_90d, 0), COALESCE(margin_index_90d, 0),
COALESCE(unit_profit_cost_90d, 0), COALESCE(unit_profit_cost_180d, 0), COALESCE(unit_profit_base_90d, 0), COALESCE(unit_profit_base_180d, 0),
COALESCE(market_count_90d, 0), COALESCE(market_count_180d, 0), COALESCE(market_count_365d, 0), COALESCE(market_count_total, 0),
COALESCE(customer_count_90d, 0), COALESCE(customer_count_180d, 0), COALESCE(customer_count_365d, 0), COALESCE(customer_count_total, 0),
COALESCE(sales_index_90d, 0), COALESCE(sales_index_180d, 0), COALESCE(sales_index_365d, 0), COALESCE(sales_index_total, 0), COALESCE(price_index_90d, 0), COALESCE(margin_index_90d, 0),
CASE WHEN COALESCE(sales_usd_90d, 0) <= 0 THEN 1 ELSE
ROUND(
LEAST(35, COALESCE(sales_index_90d, 0) * 18)
+ LEAST(25, GREATEST(COALESCE(gross_margin_90d, 0), 0) * 50)
+ LEAST(20, COALESCE(customer_count_90d, 0) * 2)
+ LEAST(10, COALESCE(market_count_90d, 0) * 3)
+ CASE WHEN COALESCE(stock_days_90d, 0) BETWEEN 10 AND 90 THEN 10 WHEN COALESCE(stock_days_90d, 0) > 180 THEN -10 ELSE 0 END
LEAST(30, GREATEST(COALESCE(gross_margin_90d, 0), 0) / 0.45 * 30)
+ LEAST(20, COALESCE(stock_turnover_90d, 0) / 4.0 * 20)
+ LEAST(20, COALESCE(sales_usd_90d, 0) / 25000.0 * 20)
+ LEAST(5, COALESCE(market_count_90d, 0) / 3.0 * 5)
+ LEAST(25, COALESCE(customer_count_90d, 0) / 8.0 * 25)
, 4)
END AS performance_score,
CASE
WHEN COALESCE(sales_index_90d,0) >= 1.25 AND COALESCE(gross_margin_90d,0) >= 0.25 THEN 'YILDIZ_URUN'
WHEN COALESCE(sales_index_90d,0) >= 1.25 AND COALESCE(gross_margin_90d,0) >= 0.45 THEN 'YILDIZ_URUN'
WHEN COALESCE(stock_qty,0) <= 0 AND COALESCE(sales_qty_90d,0) > 0 THEN 'STOKSUZ_TALEP'
WHEN COALESCE(stock_days_90d,0) > 180 AND COALESCE(sales_index_90d,0) < 0.75 THEN 'STOK_RISKI'
WHEN COALESCE(price_index_90d,0) > 1.10 AND COALESCE(sales_index_90d,0) < 0.80 THEN 'FIYAT_BASKISI'
@@ -676,7 +745,7 @@ SELECT
ELSE 'TAKIP'
END AS performance_bucket,
CASE
WHEN COALESCE(sales_index_90d,0) >= 1.25 AND COALESCE(gross_margin_90d,0) >= 0.25 THEN 'Piyasa ustu satis ve iyi marj: stok ve fiyat gucu takip edilmeli.'
WHEN COALESCE(sales_index_90d,0) >= 1.25 AND COALESCE(gross_margin_90d,0) >= 0.45 THEN 'Piyasa ustu satis ve iyi marj: stok ve fiyat gucu takip edilmeli.'
WHEN COALESCE(stock_qty,0) <= 0 AND COALESCE(sales_qty_90d,0) > 0 THEN 'Talep var, stok yok: uretim/satin alma planina alinmali.'
WHEN COALESCE(stock_days_90d,0) > 180 AND COALESCE(sales_index_90d,0) < 0.75 THEN 'Stok yuksek, satis piyasa alti: kampanya veya fiyat kontrolu gerekli.'
WHEN COALESCE(price_index_90d,0) > 1.10 AND COALESCE(sales_index_90d,0) < 0.80 THEN 'Fiyat piyasa ustunde ve satis zayif: fiyat revizyonu degerlendirilmeli.'
+143 -23
View File
@@ -51,6 +51,10 @@ type productPerformanceExcelVariant struct {
UrunAnaGrubu string
UrunAltGrubu string
StockQty float64
AvgStock90 float64
AvgStock180 float64
AvgStock365 float64
AvgStockTotal float64
BasePriceUSD float64
CostPriceUSD float64
@@ -188,6 +192,10 @@ func (v *productPerformanceExcelVariant) addProductRow(row models.ProductPerform
v.SalesUSD90 += row.SalesUSD90
v.SalesUSD180 += row.SalesUSD180
v.SalesUSD365 += row.SalesUSD365
v.AvgStock90 = productPerformanceExcelFirstNonZero(v.AvgStock90, row.AvgStock90)
v.AvgStock180 = productPerformanceExcelFirstNonZero(v.AvgStock180, row.AvgStock180)
v.AvgStock365 = productPerformanceExcelFirstNonZero(v.AvgStock365, row.AvgStock365)
v.AvgStockTotal = productPerformanceExcelFirstNonZero(v.AvgStockTotal, row.AvgStockTotal)
v.SalesQtyTotalProduct += row.SalesQtyTotal
v.SalesUSDTotalProduct += row.SalesUSDTotal
v.MarketCount90 = productPerformanceExcelMaxInt(v.MarketCount90, row.MarketCount90)
@@ -407,9 +415,9 @@ func productPerformanceExcelPeriodColumns(label, suffix string, values func(*pro
qty, usd, _, _ := values(v)
return productPerformanceExcelAvgPrice(usd, qty)
}),
numberExcelColumn(label+" Stok Devir Hızı", "number", func(v *productPerformanceExcelVariant) any {
numberExcelColumn(label+" Yıllık Stok Devir", "number", func(v *productPerformanceExcelVariant) any {
qty, _, _, _ := values(v)
return productPerformanceExcelStockTurnover(qty, v.StockQty)
return productPerformanceExcelStockTurnover(qty, productPerformanceExcelAvgStock(v, suffix), productPerformanceExcelPeriodDays(v, suffix))
}),
numberExcelColumn(label+" Taban Maliyet USD", "number", func(v *productPerformanceExcelVariant) any { return v.BasePriceUSD }),
numberExcelColumn(label+" Çıplak Maliyet USD", "number", func(v *productPerformanceExcelVariant) any { return v.CostPriceUSD }),
@@ -439,7 +447,8 @@ func productPerformanceExcelPeriodColumns(label, suffix string, values func(*pro
}),
numberExcelColumn(label+" Ürün Skor", "number", func(v *productPerformanceExcelVariant) any {
qty, usd, markets, customers := values(v)
return productPerformanceExcelProductScore(suffix, usd, productPerformanceExcelStockTurnover(qty, v.StockQty), float64(markets), float64(customers), productPerformanceExcelMargin(usd, qty, v.CostPriceUSD))
days := productPerformanceExcelPeriodDays(v, suffix)
return productPerformanceExcelProductScore(suffix, usd, productPerformanceExcelStockTurnover(qty, productPerformanceExcelAvgStock(v, suffix), days), float64(markets), float64(customers), productPerformanceExcelMargin(usd, qty, v.CostPriceUSD), days)
}),
}
}
@@ -657,13 +666,13 @@ func productPerformanceExcelSortNumber(row *productPerformanceExcelVariant, sort
case "avg_price_usd_total":
return productPerformanceExcelAvgPrice(row.totalUSD(), row.totalQty())
case "stock_turnover_90d":
return productPerformanceExcelStockTurnover(row.SalesQty90, row.StockQty)
return productPerformanceExcelStockTurnover(row.SalesQty90, productPerformanceExcelAvgStock(row, "90d"), productPerformanceExcelPeriodDays(row, "90d"))
case "stock_turnover_180d":
return productPerformanceExcelStockTurnover(row.SalesQty180, row.StockQty)
return productPerformanceExcelStockTurnover(row.SalesQty180, productPerformanceExcelAvgStock(row, "180d"), productPerformanceExcelPeriodDays(row, "180d"))
case "stock_turnover_365d":
return productPerformanceExcelStockTurnover(row.SalesQty365, row.StockQty)
return productPerformanceExcelStockTurnover(row.SalesQty365, productPerformanceExcelAvgStock(row, "365d"), productPerformanceExcelPeriodDays(row, "365d"))
case "stock_turnover_total":
return productPerformanceExcelStockTurnover(row.totalQty(), row.StockQty)
return productPerformanceExcelStockTurnover(row.totalQty(), productPerformanceExcelAvgStock(row, "total"), productPerformanceExcelPeriodDays(row, "total"))
case "base_price_usd":
return row.BasePriceUSD
case "cost_price_usd":
@@ -677,9 +686,11 @@ func productPerformanceExcelSortNumber(row *productPerformanceExcelVariant, sort
case "customer_count_total":
return float64(row.CustomerCountTotal)
case "performance_score", "performance_score_90d":
return productPerformanceExcelProductScore("90d", row.SalesUSD90, productPerformanceExcelStockTurnover(row.SalesQty90, row.StockQty), float64(row.marketCount90()), float64(row.CustomerCount90), productPerformanceExcelMargin(row.SalesUSD90, row.SalesQty90, row.CostPriceUSD))
days := productPerformanceExcelPeriodDays(row, "90d")
return productPerformanceExcelProductScore("90d", row.SalesUSD90, productPerformanceExcelStockTurnover(row.SalesQty90, productPerformanceExcelAvgStock(row, "90d"), days), float64(row.marketCount90()), float64(row.CustomerCount90), productPerformanceExcelMargin(row.SalesUSD90, row.SalesQty90, row.CostPriceUSD), days)
case "performance_score_total":
return productPerformanceExcelProductScore("total", row.totalUSD(), productPerformanceExcelStockTurnover(row.totalQty(), row.StockQty), float64(row.marketCountTotal()), float64(row.CustomerCountTotal), productPerformanceExcelMargin(row.totalUSD(), row.totalQty(), row.CostPriceUSD))
days := productPerformanceExcelPeriodDays(row, "total")
return productPerformanceExcelProductScore("total", row.totalUSD(), productPerformanceExcelStockTurnover(row.totalQty(), productPerformanceExcelAvgStock(row, "total"), days), float64(row.marketCountTotal()), float64(row.CustomerCountTotal), productPerformanceExcelMargin(row.totalUSD(), row.totalQty(), row.CostPriceUSD), days)
default:
return 0
}
@@ -795,7 +806,7 @@ func productPerformanceExcelStatus(row *productPerformanceExcelVariant) string {
return "Stok Riski"
case productPerformanceExcelMargin(row.totalUSD(), row.totalQty(), row.CostPriceUSD) < 0:
return "Fiyat Baskısı"
case productPerformanceExcelProductScore("total", row.totalUSD(), productPerformanceExcelStockTurnover(row.totalQty(), row.StockQty), float64(row.marketCountTotal()), float64(row.CustomerCountTotal), productPerformanceExcelMargin(row.totalUSD(), row.totalQty(), row.CostPriceUSD)) >= 70:
case productPerformanceExcelProductScore("total", row.totalUSD(), productPerformanceExcelStockTurnover(row.totalQty(), productPerformanceExcelAvgStock(row, "total"), productPerformanceExcelPeriodDays(row, "total")), float64(row.marketCountTotal()), float64(row.CustomerCountTotal), productPerformanceExcelMargin(row.totalUSD(), row.totalQty(), row.CostPriceUSD), productPerformanceExcelPeriodDays(row, "total")) >= 70:
return "Yıldız Ürün"
default:
return productPerformanceExcelBucketLabel(row.PerformanceBucket)
@@ -881,11 +892,55 @@ func productPerformanceExcelAvgPrice(salesUSD, qty float64) float64 {
return salesUSD / qty
}
func productPerformanceExcelStockTurnover(salesQty, stockQty float64) float64 {
if stockQty <= 0 {
const productPerformanceExcelStockTurnoverYearDays = 360.0
func productPerformanceExcelAvgStock(row *productPerformanceExcelVariant, suffix string) float64 {
switch suffix {
case "90d":
return productPerformanceExcelFirstNonZero(row.AvgStock90, row.StockQty)
case "180d":
return productPerformanceExcelFirstNonZero(row.AvgStock180, row.StockQty)
case "365d":
return productPerformanceExcelFirstNonZero(row.AvgStock365, row.StockQty)
case "total":
return productPerformanceExcelFirstNonZero(row.AvgStockTotal, row.StockQty)
default:
return row.StockQty
}
}
func productPerformanceExcelPeriodDays(row *productPerformanceExcelVariant, suffix string) float64 {
switch suffix {
case "90d":
return 90
case "180d":
return 180
case "365d":
return 360
case "total":
end, err := time.Parse("2006-01-02", strings.TrimSpace(row.KpiDate))
if err != nil {
return 0
}
start := time.Date(2022, 1, 1, 0, 0, 0, 0, time.UTC)
if end.Before(start) {
return 0
}
return end.Sub(start).Hours()/24 + 1
default:
return 0
}
return salesQty / stockQty
}
func productPerformanceExcelStockTurnover(salesQty, avgStock, periodDays float64) float64 {
if salesQty <= 0 || avgStock <= 0 {
return 0
}
raw := salesQty / avgStock
if periodDays <= 0 {
return raw
}
return raw * productPerformanceExcelStockTurnoverYearDays / periodDays
}
func productPerformanceExcelGrossProfit(salesUSD, qty, unitCost float64) float64 {
@@ -902,37 +957,102 @@ func productPerformanceExcelMargin(salesUSD, qty, unitCost float64) float64 {
return productPerformanceExcelGrossProfit(salesUSD, qty, unitCost) / salesUSD
}
func productPerformanceExcelProductScore(suffix string, salesUSD, stockTurnover, marketCount, customerCount, margin float64) float64 {
func productPerformanceExcelProductScore(suffix string, salesUSD, stockTurnover, marketCount, customerCount, margin float64, periodDays ...float64) float64 {
if salesUSD <= 0 {
return 1
}
revenueScore := productPerformanceExcelRatioScore(salesUSD, productPerformanceExcelProductRevenueTarget(suffix))
days := productPerformanceExcelScorePeriodDays(suffix, periodDays...)
revenueScore := productPerformanceExcelRatioScore(salesUSD, productPerformanceExcelProductRevenueTargetForDays(suffix, days))
score := 0.30*productPerformanceExcelMarginScore(margin) +
0.20*productPerformanceExcelRatioScore(stockTurnover, 1.50) +
0.20*productPerformanceExcelRatioScore(stockTurnover, 4) +
0.20*revenueScore +
0.15*productPerformanceExcelRatioScore(marketCount, 8) +
0.15*productPerformanceExcelRatioScore(customerCount, 25)
0.05*productPerformanceExcelRatioScore(marketCount, productPerformanceExcelMarketSpreadTarget(suffix)) +
0.25*productPerformanceExcelRatioScore(customerCount, productPerformanceExcelCustomerSpreadTargetForDays(suffix, days))
return productPerformanceExcelRoundScore(score)
}
func productPerformanceExcelMarketSpreadTarget(suffix string) float64 {
switch suffix {
case "90d":
return 3
case "180d":
return 3
case "365d":
return 6
default:
return 6
}
}
func productPerformanceExcelCustomerSpreadTarget(suffix string) float64 {
return productPerformanceExcelCustomerSpreadTargetForDays(suffix, productPerformanceExcelScorePeriodDays(suffix))
}
func productPerformanceExcelCustomerSpreadTargetForDays(suffix string, periodDays float64) float64 {
switch suffix {
case "90d":
return 8
case "180d":
return 20
case "365d":
return 50
default:
return 20 * productPerformanceExcelTotalPeriodMultiplier(periodDays)
}
}
func productPerformanceExcelProductRevenueTarget(suffix string) float64 {
return productPerformanceExcelProductRevenueTargetForDays(suffix, productPerformanceExcelScorePeriodDays(suffix))
}
func productPerformanceExcelProductRevenueTargetForDays(suffix string, periodDays float64) float64 {
switch suffix {
case "180d":
return 20000
return 50000
case "365d":
return 40000
return 100000
case "total":
return 120000
return 50000 * productPerformanceExcelTotalPeriodMultiplier(periodDays)
default:
return 10000
return 25000
}
}
func productPerformanceExcelScorePeriodDays(suffix string, periodDays ...float64) float64 {
if len(periodDays) > 0 && periodDays[0] > 0 {
return periodDays[0]
}
switch suffix {
case "90d":
return 90
case "180d":
return 180
case "365d":
return 360
case "total":
start := time.Date(2022, 1, 1, 0, 0, 0, 0, time.UTC)
now := time.Now()
if now.Before(start) {
return 0
}
return now.Sub(start).Hours()/24 + 1
default:
return 0
}
}
func productPerformanceExcelTotalPeriodMultiplier(periodDays float64) float64 {
if periodDays <= 0 {
periodDays = 180
}
return math.Max(1, periodDays/180.0)
}
func productPerformanceExcelMarginScore(margin float64) float64 {
if margin < 0 {
margin = 0
}
return productPerformanceExcelRatioScore(margin, 0.40)
return productPerformanceExcelRatioScore(margin, 0.45)
}
func productPerformanceExcelRatioScore(value, target float64) float64 {
+8
View File
@@ -1427,6 +1427,14 @@ func postProductionProductCostingOnMLSaveHandler(w http.ResponseWriter, r *http.
totalUSD := 0.0
totalEUR := 0.0
for _, r := range req.Detail.Upserts {
// The top header in the detail screen only includes rows marked
// "Maliyete Dahil". Persist that exact business total to the master
// record as well; excluded detail rows must not inflate the cost.
groupName := strings.ToUpper(strings.TrimSpace(r.SAciklama3))
isCMLaborGroup := strings.Contains(groupName, "CM1") || strings.Contains(groupName, "CM2")
if r.MaliyeteDahil != 1 && !isCMLaborGroup {
continue
}
qty := r.LMiktar
if qty < 0 {
qty = 0
+2 -2
View File
@@ -1289,12 +1289,12 @@ function normalizeUploadsPath (storagePath) {
function resolveProductImageUrl (item) {
if (!item || typeof item !== 'object') return ''
const contentUrl = toText(item.content_url || item.ContentURL)
if (contentUrl) return contentUrl.startsWith('/api/') ? contentUrl : contentUrl
const thumbUrl = toText(item.thumb_url || item.thumbUrl)
if (thumbUrl) return thumbUrl
const fullUrl = toText(item.full_url || item.fullUrl)
if (fullUrl) return fullUrl
const contentUrl = toText(item.content_url || item.ContentURL)
if (contentUrl) return contentUrl.startsWith('/api/') ? contentUrl : contentUrl
const uploadsPath = normalizeUploadsPath(item.storage_path || item.storage)
if (uploadsPath) return uploadsPath
const fileName = toText(item.file_name || item.FileName)
+358 -127
View File
@@ -35,6 +35,15 @@
:disable="pageBusy"
class="period-selector bg-white q-px-xs q-py-none"
/>
<q-btn
dense
outline
color="primary"
icon="view_column"
:label="detailColumnsHidden ? 'Detay Kolonları Göster' : 'Detay Kolonları Gizle'"
:disable="pageBusy"
@click="detailColumnsHidden = !detailColumnsHidden"
/>
<q-btn-dropdown
v-model="detailLevelMenuOpen"
split
@@ -90,20 +99,6 @@
</button>
</div>
<div v-if="activeTab === 'product_detail'" class="main-group-bar q-mb-xs">
<button
v-for="option in detailMainGroupOptions"
:key="option.value"
type="button"
:class="['main-group-button', { active: selectedDetailMainGroup === option.value }]"
:disabled="pageBusy"
@click="selectedDetailMainGroup = option.value"
>
<span>{{ option.label }}</span>
<small>{{ formatNumber(option.stock_qty, 0) }} stok</small>
</button>
</div>
<div ref="topScrollbarRef" class="performance-top-scrollbar q-mb-xs">
<div ref="topScrollbarInnerRef" class="performance-top-scrollbar-inner"></div>
</div>
@@ -113,9 +108,14 @@
flat
bordered
row-key="row_key"
class="performance-table sticky-dim-table sticky-dim-7 bg-white"
:class="[
'performance-table',
'sticky-dim-table',
detailColumnsHidden ? 'sticky-dim-4' : 'sticky-dim-7',
'bg-white'
]"
:rows="filteredGeneralRows"
:columns="generalColumns"
:columns="visibleGeneralColumns"
:loading="activeTableLoading"
v-model:pagination="tablePagination.general"
virtual-scroll
@@ -560,6 +560,7 @@
'performance-table',
'product-breakdown-table',
'bg-white',
{ 'compact-detail-columns': detailColumnsHidden },
activeTab === 'product_detail' ? 'product-detail-table' : 'product-summary-table'
]"
:rows="displayProductKpiTableRows"
@@ -1603,6 +1604,7 @@ const loadingNow = ref(0)
const loadingStage = ref('')
const generalRowsLoaded = ref(false)
const detailLevelMenuOpen = ref(false)
const detailColumnsHidden = ref(false)
const topScrollbarRef = ref(null)
const topScrollbarInnerRef = ref(null)
let backendGroupedTimer = null
@@ -1619,7 +1621,7 @@ const lastManualExpandedGroupKey = ref('')
const selectedExpandLevelKeysByTab = reactive({
products: ['urun_ilk_grubu', 'askili_yan', 'kategori'],
product_detail: ['urun_alt_grubu'],
sales_color_yaka_market_customer: ['color_yaka'],
sales_color_yaka_market_customer: ['urun_ana_grubu', 'color_yaka'],
idle: ['urun_ilk_grubu', 'askili_yan', 'kategori'],
sales_product_country_segment_market_customer: ['urun_ilk_grubu', 'askili_yan', 'kategori'],
sales_market_customer_product: ['market_key', 'customer_code', 'customer_name', 'urun_ilk_grubu', 'askili_yan'],
@@ -1675,8 +1677,7 @@ const productPerformanceExcelExportFilterFields = new Set([
])
const performanceTabs = [
{ name: 'products', icon: 'dashboard', label: 'Genel Özet KPI' },
{ name: 'product_detail', icon: 'category', label: 'Detay KPI' },
{ name: 'sales_color_yaka_market_customer', icon: 'palette', label: 'Renk/Yaka > Piyasa > Müşteri' },
{ name: 'sales_color_yaka_market_customer', icon: 'palette', label: 'Ürün Ana Grubu > Renk/Yaka > Piyasa > Müşteri' },
{ name: 'idle', icon: 'warning', label: 'Atıl Stok / Maliyet' },
{ name: 'sales_product_country_segment_market_customer', icon: 'account_tree', label: 'Ürün > Ülke > Segment > Piyasa > Müşteri' },
{ name: 'sales_country_segment_market_customer_product', icon: 'public', label: 'Ülke > Segment > Piyasa > Müşteri > Ürün Satış KPI' },
@@ -1816,10 +1817,10 @@ const columns = [
{ name: 'stock_days_180d', label: '180G Stok Gün', field: row => formatNumber(row.stock_days_180d, 1), align: 'right', sortable: true },
{ name: 'stock_days_365d', label: '360G Stok Gün', field: row => formatNumber(row.stock_days_365d, 1), align: 'right', sortable: true },
{ name: 'stock_days_total', label: 'Genel Stok Gün', field: row => formatNumber(row.stock_days_total, 1), align: 'right', sortable: true },
{ name: 'stock_turnover_90d', label: '90G Stok Devir Hızı', field: row => formatNumber(row.stock_turnover_90d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_180d', label: '180G Stok Devir Hızı', field: row => formatNumber(row.stock_turnover_180d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_365d', label: '360G Stok Devir Hızı', field: row => formatNumber(row.stock_turnover_365d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_total', label: 'Genel Stok Devir Hızı', field: row => formatNumber(row.stock_turnover_total, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_90d', label: '90G Yıllık Stok Devir', field: row => formatNumber(row.stock_turnover_90d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_180d', label: '180G Yıllık Stok Devir', field: row => formatNumber(row.stock_turnover_180d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_365d', label: '360G Yıllık Stok Devir', field: row => formatNumber(row.stock_turnover_365d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_total', label: 'Genel Yıllık Stok Devir', field: row => formatNumber(row.stock_turnover_total, 2), align: 'right', sortable: true },
{ name: 'avg_price_usd_90d', label: '90G Ort. Satış Fiyatı USD', field: row => formatMoney(row.avg_price_usd_90d, 'USD'), align: 'right' },
{ name: 'avg_price_usd_180d', label: '180G Ort. Satış Fiyatı USD', field: row => formatMoney(row.avg_price_usd_180d, 'USD'), align: 'right' },
{ name: 'avg_price_usd_365d', label: '360G Ort. Satış Fiyatı USD', field: row => formatMoney(row.avg_price_usd_365d, 'USD'), align: 'right' },
@@ -1849,7 +1850,6 @@ const columns = [
{ name: 'customer_count_total', label: 'Genel Müşteri', field: row => formatNumber(row.customer_count_total, 0), align: 'right', sortable: true },
{ name: 'sales_index_90d', label: 'Piyasa End.', field: row => formatNumber(row.sales_index_90d, 2), align: 'right', sortable: true },
{ name: 'sales_index_total', label: 'Genel Endeks', field: row => formatNumber(row.sales_index_total, 2), align: 'right', sortable: true },
{ name: 'performance_score', label: 'Skor', field: row => formatNumber(row.performance_score, 2), align: 'right', sortable: true },
{ name: 'performance_bucket', label: 'Durum', field: 'performance_bucket', align: 'left' },
{ name: 'recommendation', label: 'Öneri', field: 'recommendation', align: 'left' }
]
@@ -2024,7 +2024,32 @@ const productColumns = computed(() => orderedMetricColumns(columns.filter(visibl
const productDetailColumns = computed(() => orderedMetricColumns(columns
.filter(col => !['urun_ilk_grubu', 'askili_yan', 'kategori'].includes(col.name))
.filter(visiblePeriodColumn)))
const activeProductColumns = computed(() => activeTab.value === 'product_detail' ? productDetailColumns.value : productColumns.value)
const detailColumnNames = new Set([
'item_description',
'kategori',
'askili_yan',
'urun_ilk_grubu',
'urun_ana_grubu',
'urun_alt_grubu',
'period_start',
'period_end',
'country',
'customer_segment',
'customer_code',
'customer_name',
'first_sale_date',
'last_sale_date',
'last_ref_number'
])
function applyDetailColumnVisibility (sourceColumns) {
if (!detailColumnsHidden.value) return sourceColumns
return sourceColumns.filter(col => !detailColumnNames.has(col.name))
}
const visibleProductColumns = computed(() => applyDetailColumnVisibility(productColumns.value))
const visibleProductDetailColumns = computed(() => applyDetailColumnVisibility(productDetailColumns.value))
const activeProductColumns = computed(() => activeTab.value === 'product_detail' ? visibleProductDetailColumns.value : visibleProductColumns.value)
const generalColumns = [
{ name: 'image', label: 'Foto', field: 'image', align: 'center' },
@@ -2059,13 +2084,15 @@ const generalColumns = [
{ name: 'customer_count_total', label: 'Toplam Müşteri', field: row => formatNumber(row.customer_count_total, 0), align: 'right', sortable: true },
{ name: 'invoice_count_total', label: 'Fatura', field: row => formatNumber(row.invoice_count_total, 0), align: 'right', sortable: true },
{ name: 'sales_index_total', label: 'Genel Endeks', field: row => formatNumber(row.sales_index_total, 2), align: 'right', sortable: true },
{ name: 'performance_score', label: 'Genel Skor', field: row => formatNumber(row.performance_score, 2), align: 'right', sortable: true },
{ name: 'performance_score_total', label: 'Genel Skor', field: row => formatNumber(row.performance_score_total ?? row.performance_score, 2), align: 'right', sortable: true },
{ name: 'performance_bucket', label: 'Durum', field: 'performance_bucket', align: 'left', sortable: true },
{ name: 'first_sale_date', label: 'İlk Satış', field: 'first_sale_date', align: 'left', sortable: true },
{ name: 'last_sale_date', label: 'Son Satış', field: 'last_sale_date', align: 'left', sortable: true },
{ name: 'recommendation', label: 'Öneri', field: 'recommendation', align: 'left' }
]
const visibleGeneralColumns = computed(() => applyDetailColumnVisibility(generalColumns))
const orderAnalysisColumns = [
{ name: 'image', label: 'Foto', field: 'image', align: 'center' },
{ name: 'product_code', label: 'Ürün', field: 'product_code', align: 'left', sortable: true },
@@ -2205,7 +2232,7 @@ const idleColumns = [
{ name: 'idle_cost_usd', label: 'Stok Maliyeti USD', field: 'idle_cost_usd', align: 'right', sortable: true },
{ name: 'sales_qty_90d', label: '90G Satış', field: row => formatNumber(row.sales_qty_90d, 0), align: 'right', sortable: true },
{ name: 'stock_days_90d', label: 'Stok Gün', field: row => formatNumber(row.stock_days_90d, 1), align: 'right', sortable: true },
{ name: 'stock_turnover_90d', label: '90G Stok Devir Hızı', field: row => formatNumber(row.stock_turnover_90d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_90d', label: '90G Yıllık Stok Devir', field: row => formatNumber(row.stock_turnover_90d, 2), align: 'right', sortable: true },
{ name: 'performance_bucket', label: 'Durum', field: 'performance_bucket', align: 'left' },
{ name: 'recommendation', label: 'Öneri', field: 'recommendation', align: 'left' }
]
@@ -2288,13 +2315,13 @@ const salesBreakdownColumns = [
{ name: 'sales_qty_90d', label: '90G Adet', field: row => formatNumber(row.sales_qty_90d, 0), align: 'right', sortable: true },
{ name: 'sales_usd_90d', label: '90G USD', field: 'sales_usd_90d', align: 'right', sortable: true },
{ name: 'avg_price_usd_90d', label: '90G Ort. Satış Fiyatı USD', field: 'avg_price_usd_90d', align: 'right', sortable: true },
{ name: 'stock_turnover_90d', label: '90G Stok Devir Hızı', field: row => formatNumber(row.stock_turnover_90d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_90d', label: '90G Yıllık Stok Devir', field: row => formatNumber(row.stock_turnover_90d, 2), align: 'right', sortable: true },
{ name: 'customer_count_180d', label: '180G Müşteri', field: row => formatNumber(row.customer_count_180d, 0), align: 'right', sortable: true },
{ name: 'invoice_count_180d', label: '180G Fatura', field: row => formatNumber(row.invoice_count_180d, 0), align: 'right', sortable: true },
{ name: 'sales_qty_180d', label: '180G Adet', field: row => formatNumber(row.sales_qty_180d, 0), align: 'right', sortable: true },
{ name: 'sales_usd_180d', label: '180G USD', field: row => formatMoney(row.sales_usd_180d, 'USD'), align: 'right', sortable: true },
{ name: 'avg_price_usd_180d', label: '180G Ort. Satış Fiyatı USD', field: row => formatMoney(row.avg_price_usd_180d, 'USD'), align: 'right', sortable: true },
{ name: 'stock_turnover_180d', label: '180G Stok Devir Hızı', field: row => formatNumber(row.stock_turnover_180d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_180d', label: '180G Yıllık Stok Devir', field: row => formatNumber(row.stock_turnover_180d, 2), align: 'right', sortable: true },
{ name: 'base_price_usd_180d', label: '180G Taban', field: row => formatMoney(row.base_price_usd_180d, 'USD'), align: 'right', sortable: true },
{ name: 'cost_price_usd_180d', label: '180G Çıplak', field: row => formatMoney(row.cost_price_usd_180d, 'USD'), align: 'right', sortable: true },
{ name: 'gross_profit_base_usd_180d', label: '180G Taban K/Z', field: row => formatMoney(row.gross_profit_base_usd_180d, 'USD'), align: 'right', sortable: true },
@@ -2305,7 +2332,7 @@ const salesBreakdownColumns = [
{ name: 'sales_qty_365d', label: '360G Adet', field: row => formatNumber(row.sales_qty_365d, 0), align: 'right', sortable: true },
{ name: 'sales_usd_365d', label: '360G USD', field: row => formatMoney(row.sales_usd_365d, 'USD'), align: 'right', sortable: true },
{ name: 'avg_price_usd_365d', label: '360G Ort. Satış Fiyatı USD', field: row => formatMoney(row.avg_price_usd_365d, 'USD'), align: 'right', sortable: true },
{ name: 'stock_turnover_365d', label: '360G Stok Devir Hızı', field: row => formatNumber(row.stock_turnover_365d, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_365d', label: '360G Yıllık Stok Devir', field: row => formatNumber(row.stock_turnover_365d, 2), align: 'right', sortable: true },
{ name: 'base_price_usd_365d', label: '360G Taban', field: row => formatMoney(row.base_price_usd_365d, 'USD'), align: 'right', sortable: true },
{ name: 'cost_price_usd_365d', label: '360G Çıplak', field: row => formatMoney(row.cost_price_usd_365d, 'USD'), align: 'right', sortable: true },
{ name: 'gross_profit_base_usd_365d', label: '360G Taban K/Z', field: row => formatMoney(row.gross_profit_base_usd_365d, 'USD'), align: 'right', sortable: true },
@@ -2318,7 +2345,7 @@ const salesBreakdownColumns = [
{ name: 'sales_qty_total', label: 'Genel Adet', field: row => formatNumber(row.sales_qty_total, 0), align: 'right', sortable: true },
{ name: 'sales_usd_total', label: 'Genel USD', field: row => formatMoney(row.sales_usd_total, 'USD'), align: 'right', sortable: true },
{ name: 'avg_price_usd_total', label: 'Genel Ort. Satış Fiyatı USD', field: row => formatMoney(row.avg_price_usd_total, 'USD'), align: 'right', sortable: true },
{ name: 'stock_turnover_total', label: 'Genel Stok Devir Hızı', field: row => formatNumber(row.stock_turnover_total, 2), align: 'right', sortable: true },
{ name: 'stock_turnover_total', label: 'Genel Yıllık Stok Devir', field: row => formatNumber(row.stock_turnover_total, 2), align: 'right', sortable: true },
{ name: 'base_price_usd_total', label: 'Genel Taban', field: row => formatMoney(row.base_price_usd_total, 'USD'), align: 'right', sortable: true },
{ name: 'cost_price_usd_total', label: 'Genel Çıplak', field: row => formatMoney(row.cost_price_usd_total, 'USD'), align: 'right', sortable: true },
{ name: 'gross_profit_base_usd_total', label: 'Genel Taban K/Z', field: row => formatMoney(row.gross_profit_base_usd_total, 'USD'), align: 'right', sortable: true },
@@ -2327,7 +2354,6 @@ const salesBreakdownColumns = [
{ name: 'gross_margin_cost_total', label: 'Genel Çıplak Marj', field: row => formatPercent(row.gross_margin_cost_total), align: 'right', sortable: true },
{ name: 'customer_score_total', label: 'Genel Müşteri Skor', field: row => formatNumber(row.customer_score_total, 2), align: 'right', sortable: true },
{ name: 'sales_index_90d', label: 'Endeks', field: row => formatNumber(row.sales_index_90d, 2), align: 'right', sortable: true },
{ name: 'performance_score', label: 'Skor', field: row => formatNumber(row.performance_score, 2), align: 'right', sortable: true },
{ name: 'performance_bucket', label: 'Durum', field: 'performance_bucket', align: 'left', sortable: true },
{ name: 'last_sale_date', label: 'Son Satış', field: 'last_sale_date', align: 'left', sortable: true },
{ name: 'recommendation', label: 'Öneri', field: 'recommendation', align: 'left' }
@@ -2399,7 +2425,6 @@ const metricLabelOverrides = {
gross_margin_cost_365d: '360G Çıplak Marj',
gross_margin_base_total: 'Genel Taban Marj',
gross_margin_cost_total: 'Genel Çıplak Marj',
performance_score: 'Skor',
performance_score_90d: '90G Ürün Skor',
performance_score_180d: '180G Ürün Skor',
performance_score_365d: '360G Ürün Skor',
@@ -2412,10 +2437,10 @@ const metricLabelOverrides = {
customer_count_90d: '90G Tekil Müşteri',
market_count_total: 'Genel Tekil Piyasa',
customer_count_total: 'Genel Tekil Müşteri',
stock_turnover_90d: '90G Stok Devir Hızı',
stock_turnover_180d: '180G Stok Devir Hızı',
stock_turnover_365d: '360G Stok Devir Hızı',
stock_turnover_total: 'Genel Stok Devir Hızı',
stock_turnover_90d: '90G Yıllık Stok Devir',
stock_turnover_180d: '180G Yıllık Stok Devir',
stock_turnover_365d: '360G Yıllık Stok Devir',
stock_turnover_total: 'Genel Yıllık Stok Devir',
sales_index_90d: '90G Endeks',
sales_index_total: 'Genel Endeks',
stock_days_90d: '90G Stok Gün',
@@ -2513,7 +2538,6 @@ function ensureColorYakaColumn (targetColumns) {
].forEach(target => ensureColumns(target, customerPeriodScoreColumns))
;[
generalColumns,
orderAnalysisColumns,
orderGroupColumns,
orderProductCustomerColumns,
@@ -2639,7 +2663,10 @@ const visibleOrderAnalysisColumns = computed(() => {
function performanceCardsForRow (row) {
const source = row || {}
return [
{ key: 'score', label: 'Skor', value: formatNumber(source.performance_score, 2) },
{ key: 'score90', label: '90G Skor', value: formatNumber(source.performance_score_90d ?? source.performance_score, 2) },
{ key: 'score180', label: '180G Skor', value: formatNumber(source.performance_score_180d, 2) },
{ key: 'score360', label: '360G Skor', value: formatNumber(source.performance_score_365d, 2) },
{ key: 'scoreTotal', label: 'Genel Skor', value: formatNumber(source.performance_score_total ?? source.performance_score, 2) },
{ key: 'stock', label: 'Stok', value: formatNumber(source.stock_qty, 0) },
{ key: 'sales90', label: '90G Satış', value: formatNumber(source.sales_qty_90d, 0) },
{ key: 'sales180', label: '180G Satış', value: formatNumber(source.sales_qty_180d, 0) },
@@ -2700,18 +2727,13 @@ const tabGroupLevels = {
{ key: 'market_key', label: 'Piyasa' }
],
sales_color_yaka_market_customer: [
{ key: 'color_yaka', label: 'Renk/Yaka' },
{ key: 'urun_ilk_grubu', label: 'Ürün İlk Grubu' },
{ key: 'askili_yan', label: 'Askılı/Yan' },
{ key: 'kategori', label: 'Kategori' },
{ key: 'urun_ana_grubu', label: 'Ürün Ana Grubu' },
{ key: 'urun_alt_grubu', label: 'Ürün Alt Grubu' },
{ key: 'product_code', label: 'Ürün' },
{ key: 'country', label: 'Ülke' },
{ key: 'color_yaka', label: 'Renk/Yaka' },
{ key: 'market_key', label: 'Piyasa' },
{ key: 'customer_segment', label: 'Segment' },
{ key: 'customer_code', label: 'Müşteri Kodu' },
{ key: 'customer_name', label: 'Müşteri' }
{ key: 'customer_name', label: 'Müşteri' },
{ key: 'urun_alt_grubu', label: 'Ürün Alt Grubu' },
{ key: 'product_code', label: 'Ürün' }
],
idle: [
{ key: 'urun_ilk_grubu', label: 'Ürün İlk Grubu' },
@@ -3052,7 +3074,7 @@ function filterSourceRowsForTab (tabKey, fallbackRows) {
}
function backendGroupedFilterOptionParams (tabKey) {
const columns = columnsForTableKey(tabKey)
const columns = filterColumnsForTableKey(tabKey)
const fields = columns
.map(col => col?.name || '')
.filter(name => backendGroupedFilterFields.has(name))
@@ -3132,7 +3154,7 @@ function backendFilterOptionLabel (name, value) {
function backendGroupedFilterState (tabKey) {
const out = {}
const columns = columnsForTableKey(tabKey)
const columns = filterColumnsForTableKey(tabKey)
for (const col of columns) {
const name = col?.name || ''
if (!isColumnFilterable(name)) continue
@@ -3152,7 +3174,7 @@ function shouldUseBackendGroupedRows (tabKey) {
function tableFilterSource (tableKey) {
if (backendGroupedSupportedTab(tableKey)) {
return { rows: backendGroupedRows.value[tableKey] || [], columns: columnsForTableKey(tableKey) }
return { rows: backendGroupedRows.value[tableKey] || [], columns: filterColumnsForTableKey(tableKey) }
}
if (tableKey === 'general') return { rows: generalRows.value, columns: generalColumns }
if (tableKey === 'markets') return { rows: marketRows.value, columns: marketColumns }
@@ -3162,6 +3184,20 @@ function tableFilterSource (tableKey) {
}
function columnsForTableKey (tabKey) {
if (tabKey === 'products') return visibleProductColumns.value
if (tabKey === 'product_detail') return visibleProductDetailColumns.value
if (tabKey === 'general') return visibleGeneralColumns.value
if (tabKey === 'order_product_customers') return orderProductCustomerColumns
if (tabKey === 'order_market_details') return orderMarketDetailColumns
if (tabKey === 'idle') return idleColumns
if (tabKey === 'markets') return marketColumns
if (tabKey === 'countries') return countryColumns
if (tabKey === 'customers') return customerColumns
if (salesBreakdownTabKeys.includes(tabKey)) return visibleSalesBreakdownColumns.value
return productColumns.value
}
function filterColumnsForTableKey (tabKey) {
if (tabKey === 'products') return productColumns.value
if (tabKey === 'product_detail') return productDetailColumns.value
if (tabKey === 'general') return generalColumns
@@ -3244,6 +3280,9 @@ function compareGroupedBucketsForTable (tableKey, left, right, groupDef) {
function groupedBucketSortValue (sourceRows, sortBy) {
if (!sourceRows?.length) return 0
if (shouldUseDerivedGroupSortValue(sortBy)) {
return sortValueForColumnName(aggregateGroupFields(sourceRows), sortBy)
}
if (sortBy === 'stock_qty') return distinctVariantStockQty(sourceRows)
if (sortBy === 'idle_cost_usd') return distinctVariantStockCost(sourceRows)
if (sortBy === 'base_price_usd' || sortBy === 'cost_price_usd') return weightedAverageProductCost(sourceRows, sortBy)
@@ -3252,6 +3291,10 @@ function groupedBucketSortValue (sourceRows, sortBy) {
return sortValueForColumnName(sourceRows[0], sortBy)
}
function shouldUseDerivedGroupSortValue (sortBy) {
return /^(performance_score|stock_turnover|stock_days|avg_price_usd|unit_profit|gross_profit|gross_margin|market_count|customer_count|sales_index)/i.test(String(sortBy || ''))
}
function sortProductGroupedTableRows (tableRows, sortBy, descending) {
const source = Array.isArray(tableRows) ? tableRows : []
if (backendGroupedSupportedTab(activeTab.value)) return source
@@ -3438,8 +3481,8 @@ function aggregateGroupFields (sourceRows, groupField = '') {
for (const field of fields) {
if (field === 'row_key' || field === 'key') continue
if (/^gross_margin(_base|_cost)?(_|$)/i.test(field)) continue
if (field === 'stock_qty') {
out[field] = distinctVariantStockQty(sourceRows)
if (field === 'stock_qty' || /^avg_stock_/i.test(field)) {
out[field] = distinctVariantNumber(sourceRows, field)
continue
}
if (field === 'idle_cost_usd') {
@@ -3466,15 +3509,18 @@ function aggregateGroupFields (sourceRows, groupField = '') {
}
function shouldSumField (field) {
return /(_qty|_usd|_count|_value_usd|line_count|invoice_count|order_count|product_count|market_count|customer_count|overdue_qty|stock_qty|net_stock_after_order|idle_cost_usd)$/i.test(field)
return /^(sales_qty_|sales_usd_|avg_daily_sales_|gross_profit_|invoice_count_|market_count_|customer_count_|product_group_count_|product_count_)/i.test(field) ||
/(_qty|_usd|_count|_value_usd|line_count|invoice_count|order_count|product_count|market_count|customer_count|overdue_qty|stock_qty|net_stock_after_order|idle_cost_usd)$/i.test(field)
}
function shouldAverageField (field) {
if (/^avg_daily_sales_/i.test(field)) return false
return /^(avg_|unit_|base_price|cost_price|gross_margin|expected_margin|sales_index|performance_score|customer_score|stock_days|stock_turnover)/i.test(field) ||
/(_price_usd|_margin|_index|_days)$/i.test(field)
}
function weightFieldForMetric (field) {
if (field.startsWith('stock_turnover')) return `sales_qty_${countPeriodSuffix(field)}`
if (field.includes('_180d')) return 'sales_qty_180d'
if (field.includes('_365d')) return 'sales_qty_365d'
if (field.includes('_total')) return 'sales_qty_total'
@@ -3485,13 +3531,43 @@ function weightFieldForMetric (field) {
function applyDerivedGroupMetrics (out, sourceRows, groupField = '') {
Object.assign(out, normalizeProductCostFields(out))
const isGroup = Boolean(String(groupField || '').trim())
const preservedCustomerScores = {}
const preservedProductScores = {}
const preservedStockTurnovers = {}
for (const suffix of ['90d', '180d', '365d', 'total']) {
if (Object.prototype.hasOwnProperty.call(out, `customer_score_${suffix}`)) {
preservedCustomerScores[suffix] = Number(out[`customer_score_${suffix}`] || 0)
}
if (Object.prototype.hasOwnProperty.call(out, `performance_score_${suffix}`)) {
preservedProductScores[suffix] = Number(out[`performance_score_${suffix}`] || 0)
}
if (isGroup && Object.prototype.hasOwnProperty.call(out, `stock_turnover_${suffix}`)) {
preservedStockTurnovers[suffix] = Number(out[`stock_turnover_${suffix}`] || 0)
}
}
if (
Object.prototype.hasOwnProperty.call(out, 'performance_score') &&
!Object.prototype.hasOwnProperty.call(preservedProductScores, '90d')
) {
preservedProductScores['90d'] = Number(out.performance_score || 0)
}
for (const suffix of ['90d', '180d', '365d', 'total']) {
const sales = Number(out[`sales_usd_${suffix}`] || 0)
const qty = Number(out[`sales_qty_${suffix}`] || 0)
const stockQty = Number(out.stock_qty || 0)
const avgStock = Number(out[`avg_stock_${suffix}`] || 0)
const turnoverBase = avgStock > 0 ? avgStock : stockQty
out[`stock_turnover_${suffix}`] = turnoverBase > 0 ? qty / turnoverBase : 0
const turnoverBase = avgStock > 0 ? avgStock : (isGroup ? 0 : stockQty)
const days = productPerformancePeriodDays(out, suffix)
const avgDaily = days > 0 ? qty / days : Number(out[`avg_daily_sales_${suffix}`] || 0)
if (days > 0) out[`avg_daily_sales_${suffix}`] = avgDaily
if (avgDaily > 0 && turnoverBase > 0) out[`stock_days_${suffix}`] = turnoverBase / avgDaily
else if (qty <= 0 && stockQty > 0) out[`stock_days_${suffix}`] = 9999
else if (!Object.prototype.hasOwnProperty.call(out, `stock_days_${suffix}`)) out[`stock_days_${suffix}`] = 0
out[`stock_turnover_${suffix}`] = annualizedStockTurnover(qty, turnoverBase, days)
if (Object.prototype.hasOwnProperty.call(preservedStockTurnovers, suffix)) {
out[`stock_turnover_${suffix}`] = preservedStockTurnovers[suffix]
}
if (qty > 0) out[`avg_price_usd_${suffix}`] = sales / qty
const { costPrice, basePrice } = periodCostPair(out, suffix)
out[`base_price_usd_${suffix}`] = basePrice
@@ -3530,19 +3606,33 @@ function applyDerivedGroupMetrics (out, sourceRows, groupField = '') {
if (sourceRows.some(row => row.performance_bucket)) {
out.performance_bucket = dominantValue(sourceRows, 'performance_bucket')
}
if (!Object.prototype.hasOwnProperty.call(out, 'customer_score_90d')) out.customer_score_90d = customerSalesPeriodScore(periodMetricSource(out, '90d'))
if (!Object.prototype.hasOwnProperty.call(out, 'customer_score_180d')) out.customer_score_180d = customerSalesPeriodScore(periodMetricSource(out, '180d'))
if (!Object.prototype.hasOwnProperty.call(out, 'customer_score_365d')) out.customer_score_365d = customerSalesPeriodScore(periodMetricSource(out, '365d'))
if (!Object.prototype.hasOwnProperty.call(out, 'customer_score_total')) out.customer_score_total = customerSalesPeriodScore(periodMetricSource(out, 'total'))
if (!Object.prototype.hasOwnProperty.call(out, 'performance_score_90d')) out.performance_score_90d = productSalesPeriodScore(productPeriodMetricSource(out, '90d'))
if (!Object.prototype.hasOwnProperty.call(out, 'performance_score_180d')) out.performance_score_180d = productSalesPeriodScore(productPeriodMetricSource(out, '180d'))
if (!Object.prototype.hasOwnProperty.call(out, 'performance_score_365d')) out.performance_score_365d = productSalesPeriodScore(productPeriodMetricSource(out, '365d'))
if (!Object.prototype.hasOwnProperty.call(out, 'performance_score_total')) out.performance_score_total = productSalesPeriodScore(productPeriodMetricSource(out, 'total'))
if (!Object.prototype.hasOwnProperty.call(out, 'performance_score')) {
out.performance_score = Object.prototype.hasOwnProperty.call(out, 'performance_score_90d')
? Number(out.performance_score_90d || 0)
: groupPerformanceScore(out, groupField)
for (const suffix of ['90d', '180d', '365d', 'total']) {
out[`customer_score_${suffix}`] = Object.prototype.hasOwnProperty.call(preservedCustomerScores, suffix)
? preservedCustomerScores[suffix]
: customerSalesPeriodScore(periodMetricSource(out, suffix))
out[`performance_score_${suffix}`] = Object.prototype.hasOwnProperty.call(preservedProductScores, suffix)
? preservedProductScores[suffix]
: productSalesPeriodScore(productPeriodMetricSource(out, suffix))
}
out.performance_score = Number(out.performance_score_90d || 0)
}
function productPerformancePeriodDays (row, suffix) {
if (suffix === '90d') return 90
if (suffix === '180d') return 180
if (suffix === '365d') return 360
if (suffix !== 'total') return 0
const start = parseProductPerformanceDate(row?.period_start) || new Date(Date.UTC(2022, 0, 1))
const end = parseProductPerformanceDate(row?.period_end) || parseProductPerformanceDate(row?.kpi_date)
if (!start || !end || end < start) return 0
return Math.floor((end.getTime() - start.getTime()) / 86400000) + 1
}
function parseProductPerformanceDate (value) {
const text = String(value || '').trim().slice(0, 10)
if (!/^\d{4}-\d{2}-\d{2}$/.test(text)) return null
const [year, month, day] = text.split('-').map(Number)
return new Date(Date.UTC(year, month - 1, day))
}
function groupPerformanceScore (row, groupField = '') {
@@ -3557,8 +3647,10 @@ function salesGroupPerformanceScore (row) {
function productSalesPeriodScore (row) {
const suffix = row?.suffix || '90d'
const periodDays = productPerformancePeriodDays(row, suffix)
return productScore100({
suffix,
periodDays,
salesUSD: Number(row?.sales_usd_90d || 0),
salesIndex: Number(row?.sales_index_90d || 0),
margin: Number(row?.gross_margin_cost_90d ?? row?.gross_margin_90d ?? 0),
@@ -3572,6 +3664,9 @@ function productPeriodMetricSource (row, suffix) {
const salesIndex = Number(row?.[`sales_index_${suffix}`] || 0)
const qty = Number(row?.[`sales_qty_${suffix}`] || 0)
const stockQty = Number(row?.stock_qty || 0)
const avgStock = Number(row?.[`avg_stock_${suffix}`] || 0)
const isGroup = Boolean(row?.__group || String(row?.group_field || '').trim())
const turnoverBase = avgStock > 0 ? avgStock : (isGroup ? 0 : stockQty)
const turnoverKey = `stock_turnover_${suffix}`
const hasTurnover = Object.prototype.hasOwnProperty.call(row || {}, turnoverKey)
return {
@@ -3581,7 +3676,7 @@ function productPeriodMetricSource (row, suffix) {
gross_margin_cost_90d: Number(row?.[`gross_margin_cost_${suffix}`] ?? 0),
gross_margin_90d: Number(row?.[`gross_margin_${suffix}`] ?? 0),
sales_qty_90d: qty,
stock_turnover_90d: hasTurnover ? Number(row?.[turnoverKey] || 0) : (stockQty > 0 ? qty / stockQty : 0),
stock_turnover_90d: hasTurnover ? Number(row?.[turnoverKey] || 0) : annualizedStockTurnover(qty, turnoverBase, productPerformancePeriodDays(row, suffix)),
market_count_90d: periodCount(row, 'market_count', suffix),
customer_count_90d: periodCount(row, 'customer_count', suffix),
stock_qty: stockQty
@@ -3623,15 +3718,15 @@ function periodMetricSource (row, suffix) {
}
}
function productScore100 ({ suffix = '90d', salesUSD = 0, margin = 0, stockTurnover = 0, marketCount = 0, customerCount = 0 } = {}) {
function productScore100 ({ suffix = '90d', periodDays = 0, salesUSD = 0, margin = 0, stockTurnover = 0, marketCount = 0, customerCount = 0 } = {}) {
if (Number(salesUSD || 0) <= 0) return 1
const revenue = ratioScore(salesUSD, productRevenueTarget(suffix))
const revenue = ratioScore(salesUSD, productRevenueTarget(suffix, periodDays))
return clampScore(
0.30 * marginScore(margin) +
0.20 * ratioScore(stockTurnover, 1.5) +
0.20 * ratioScore(stockTurnover, stockTurnoverTarget(suffix)) +
0.20 * revenue +
0.15 * ratioScore(marketCount, 8) +
0.15 * ratioScore(customerCount, 25)
0.05 * ratioScore(marketCount, marketSpreadTarget(suffix)) +
0.25 * ratioScore(customerCount, customerSpreadTarget(suffix, periodDays))
)
}
@@ -3653,7 +3748,7 @@ function ratioScore (value, target) {
}
function marginScore (margin) {
return ratioScore(Math.max(0, Number(margin || 0)), 0.40)
return ratioScore(Math.max(0, Number(margin || 0)), 0.45)
}
function clampScore (score) {
@@ -3662,11 +3757,11 @@ function clampScore (score) {
return Math.round(Math.min(100, n) * 10000) / 10000
}
function productRevenueTarget (suffix) {
if (suffix === '180d') return 20000
if (suffix === '365d') return 40000
if (suffix === 'total') return 120000
return 10000
function productRevenueTarget (suffix, periodDays = 0) {
if (suffix === '180d') return 50000
if (suffix === '365d') return 100000
if (suffix === 'total') return 50000 * totalPeriodMultiplier(periodDays)
return 25000
}
function customerRevenueTarget (suffix) {
@@ -3683,6 +3778,43 @@ function customerQtyTarget (suffix) {
return 500
}
const STOCK_TURNOVER_YEAR_DAYS = 360
function annualizedStockTurnover (salesQty, avgStock, periodDays) {
const qty = Number(salesQty || 0)
const stock = Number(avgStock || 0)
const days = Number(periodDays || 0)
if (!Number.isFinite(qty) || !Number.isFinite(stock) || qty <= 0 || stock <= 0) return 0
const raw = qty / stock
return days > 0 ? raw * STOCK_TURNOVER_YEAR_DAYS / days : raw
}
function stockTurnoverTarget () {
return 4
}
function marketSpreadTarget (suffix) {
if (suffix === '90d') return 3
if (suffix === '180d') return 3
if (suffix === '365d') return 6
return 6
}
function customerSpreadTarget (suffix, periodDays = 0) {
if (suffix === '90d') return 8
if (suffix === '180d') return 20
if (suffix === '365d') return 50
return 20 * totalPeriodMultiplier(periodDays)
}
function totalPeriodMultiplier (periodDays = 0) {
let days = Number(periodDays || 0)
if (!Number.isFinite(days) || days <= 0) {
days = productPerformancePeriodDays({ kpi_date: new Date().toISOString().slice(0, 10) }, 'total')
}
return Math.max(1, days / 180)
}
function periodCount (row, prefix, suffix) {
const keyed = Number(row?.[`${prefix}_${suffix}`] || 0)
if (keyed > 0) return keyed
@@ -3716,19 +3848,23 @@ function productVariantStockKey (row) {
}
function distinctVariantStockQty (sourceRows) {
return distinctVariantNumber(sourceRows, 'stock_qty')
}
function distinctVariantNumber (sourceRows, field) {
const seen = new Set()
let total = 0
let keyed = false
for (const row of sourceRows) {
const key = productVariantStockKey(row)
const stockQty = Number(row?.stock_qty || 0)
const value = Number(row?.[field] || 0)
if (!key) continue
keyed = true
if (seen.has(key)) continue
seen.add(key)
total += stockQty
total += value
}
return keyed ? total : sumRows(sourceRows, 'stock_qty')
return keyed ? total : sumRows(sourceRows, field)
}
function distinctVariantStockCost (sourceRows) {
@@ -3784,6 +3920,12 @@ function distinctRevenueMarketCount (sourceRows, suffix, fallbackField) {
const values = new Set()
for (const row of sourceRows) {
if (Number(row?.[salesField] || 0) <= 0) continue
const marketKeys = stringListFromRow(row, `__market_keys_${suffix}`)
for (const key of marketKeys) {
const value = displayMarketName(key)
if (value && value !== 'STOK' && value !== '-') values.add(value)
}
if (marketKeys.length > 0) continue
const value = displayMarketName(row?.market_key)
if (value && value !== 'STOK' && value !== '-') values.add(value)
}
@@ -3798,6 +3940,11 @@ function distinctRevenueCustomerCount (sourceRows, suffix, fallbackField) {
const values = new Set()
for (const row of sourceRows) {
if (Number(row?.[salesField] || 0) <= 0) continue
const customerKeys = stringListFromRow(row, `__customer_keys_${suffix}`)
for (const code of customerKeys) {
if (code && code !== '-') values.add(code)
}
if (customerKeys.length > 0) continue
const code = String(row?.customer_code || '').trim()
if (code && code !== '-') values.add(code)
}
@@ -3807,6 +3954,22 @@ function distinctRevenueCustomerCount (sourceRows, suffix, fallbackField) {
}, 0)
}
function stringListFromRow (row, field) {
const value = row?.[field]
if (Array.isArray(value)) return value.map(item => String(item || '').trim()).filter(Boolean)
const text = String(value || '').trim()
if (!text) return []
if (text.startsWith('[')) {
try {
const parsed = JSON.parse(text)
return Array.isArray(parsed) ? parsed.map(item => String(item || '').trim()).filter(Boolean) : []
} catch {
return []
}
}
return [text]
}
function distinctSummary (sourceRows, field, fallbackField) {
const values = new Set()
for (const row of sourceRows) {
@@ -3879,14 +4042,9 @@ function scoreSuffixForMetric (field) {
}
function scoreWeight (row, suffix) {
const salesUsd = Number(row?.[`sales_usd_${suffix}`] || 0)
if (salesUsd > 0) return salesUsd
const salesQty = Number(row?.[`sales_qty_${suffix}`] || 0)
if (salesQty > 0) return salesQty
const stockQty = Number(row?.stock_qty || 0)
if (stockQty <= 0) return 1
const costPrice = Number(row?.[`cost_price_usd_${suffix}`] || row?.cost_price_usd || 0)
return costPrice > 0 ? stockQty * costPrice : stockQty
return 0
}
function weightedAverageScore (sourceRows, valueField, suffix) {
@@ -4126,10 +4284,10 @@ function withProductMargins (row) {
const out = {
...next,
avg_price_usd_365d: Number(next?.sales_qty_365d || 0) > 0 ? Number(next?.sales_usd_365d || 0) / Number(next?.sales_qty_365d || 0) : 0,
stock_turnover_90d: existingOrStockTurnover(next?.stock_turnover_90d, next?.sales_qty_90d, next?.stock_qty),
stock_turnover_180d: existingOrStockTurnover(next?.stock_turnover_180d, next?.sales_qty_180d, next?.stock_qty),
stock_turnover_365d: existingOrStockTurnover(next?.stock_turnover_365d, next?.sales_qty_365d, next?.stock_qty),
stock_turnover_total: existingOrStockTurnover(next?.stock_turnover_total, next?.sales_qty_total, next?.stock_qty)
stock_turnover_90d: groupedOrExistingStockTurnover(next, '90d', 90),
stock_turnover_180d: groupedOrExistingStockTurnover(next, '180d', 180),
stock_turnover_365d: groupedOrExistingStockTurnover(next, '365d', 360),
stock_turnover_total: groupedOrExistingStockTurnover(next, 'total', productPerformancePeriodDays(next, 'total'))
}
for (const suffix of ['90d', '180d', '365d', 'total']) {
applyPeriodProfitFields(out, suffix)
@@ -4142,7 +4300,7 @@ function withGeneralMargins (row) {
applyPeriodProfitFields(out, 'total')
return {
...out,
stock_turnover_total: existingOrStockTurnover(out?.stock_turnover_total, out?.sales_qty_total, out?.stock_qty)
stock_turnover_total: groupedOrExistingStockTurnover(out, 'total', productPerformancePeriodDays(out, 'total'))
}
}
@@ -4209,15 +4367,27 @@ function applyPeriodProfitFields (row, suffix) {
row[`gross_margin_cost_${suffix}`] = marginFromSalesCost(salesUSD, qty, costPrice)
}
function stockTurnover (salesQty, stockQty) {
const stock = Number(stockQty || 0)
if (stock <= 0) return 0
return Number(salesQty || 0) / stock
function stockTurnover (salesQty, stockQty, periodDays) {
return annualizedStockTurnover(salesQty, stockQty, periodDays)
}
function existingOrStockTurnover (value, salesQty, stockQty) {
function existingOrStockTurnover (value, salesQty, stockQty, periodDays) {
const current = Number(value)
return value !== undefined && value !== null && Number.isFinite(current) ? current : stockTurnover(salesQty, stockQty)
return value !== undefined && value !== null && Number.isFinite(current) ? current : stockTurnover(salesQty, stockQty, periodDays)
}
function groupedOrExistingStockTurnover (row, suffix, periodDays) {
const salesQty = Number(row?.[`sales_qty_${suffix}`] || 0)
const avgStock = Number(row?.[`avg_stock_${suffix}`] || 0)
const stockQty = Number(row?.stock_qty || 0)
if (row?.__group) {
const current = Number(row?.[`stock_turnover_${suffix}`])
if (Number.isFinite(current)) return current
if (avgStock > 0) return stockTurnover(salesQty, avgStock, periodDays)
return 0
}
const stockBase = avgStock > 0 ? avgStock : stockQty
return existingOrStockTurnover(row?.[`stock_turnover_${suffix}`], salesQty, stockBase, periodDays)
}
function filterKey (tableKey, name) {
@@ -5204,7 +5374,7 @@ function productPerformanceExcelExportTableKey () {
function buildProductPerformanceExcelExportFilters () {
const tableKey = productPerformanceExcelExportTableKey()
const out = {}
for (const col of columnsForTableKey(tableKey) || []) {
for (const col of filterColumnsForTableKey(tableKey) || []) {
const name = String(col?.name || '').trim()
if (!productPerformanceExcelExportFilterFields.has(name)) continue
const selected = selectedColumnFilters(tableKey, name)
@@ -5986,95 +6156,95 @@ onBeforeUnmount(() => {
table-layout: fixed;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(-n+10)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(-n+10)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(-n+10)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(-n+10)) {
position: sticky;
z-index: 2;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(-n+10)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(-n+10)) {
z-index: 30;
background: #f8fbff;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table tbody tr:not(.group-row) td:nth-child(-n+10)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table tbody tr:not(.group-row) td:nth-child(-n+10)) {
background: #fff;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(1)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(1)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(1)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(1)) {
left: 0;
width: 190px;
min-width: 190px;
max-width: 190px;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(2)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(2)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(2)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(2)) {
left: 190px;
width: 140px;
min-width: 140px;
max-width: 140px;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(3)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(3)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(3)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(3)) {
left: 330px;
width: 110px;
min-width: 110px;
max-width: 110px;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(4)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(4)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(4)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(4)) {
left: 440px;
width: 150px;
min-width: 150px;
max-width: 150px;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(5)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(5)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(5)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(5)) {
left: 590px;
width: 170px;
min-width: 170px;
max-width: 170px;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(6)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(6)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(6)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(6)) {
left: 760px;
width: 150px;
min-width: 150px;
max-width: 150px;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(7)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(7)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(7)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(7)) {
left: 910px;
width: 130px;
min-width: 130px;
max-width: 130px;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(8)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(8)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(8)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(8)) {
left: 1040px;
width: 90px;
min-width: 90px;
max-width: 90px;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(9)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(9)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(9)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(9)) {
left: 1130px;
width: 80px;
min-width: 80px;
max-width: 80px;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(10)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(10)) {
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(10)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(10)) {
left: 1210px;
width: 130px;
min-width: 130px;
@@ -6082,6 +6252,58 @@ onBeforeUnmount(() => {
box-shadow: 8px 0 10px -10px rgba(17, 24, 39, 0.45);
}
.product-breakdown-table.compact-detail-columns :deep(.q-table) {
min-width: 2450px;
}
.product-breakdown-table.compact-detail-columns :deep(.q-table th:nth-child(-n+4)),
.product-breakdown-table.compact-detail-columns :deep(.q-table td:nth-child(-n+4)) {
position: sticky;
z-index: 2;
}
.product-breakdown-table.compact-detail-columns :deep(.q-table th:nth-child(-n+4)) {
z-index: 30;
background: #f8fbff;
}
.product-breakdown-table.compact-detail-columns :deep(.q-table tbody tr:not(.group-row) td:nth-child(-n+4)) {
background: #fff;
}
.product-breakdown-table.compact-detail-columns :deep(.q-table th:nth-child(1)),
.product-breakdown-table.compact-detail-columns :deep(.q-table td:nth-child(1)) {
left: 0;
width: 86px;
min-width: 86px;
max-width: 86px;
}
.product-breakdown-table.compact-detail-columns :deep(.q-table th:nth-child(2)),
.product-breakdown-table.compact-detail-columns :deep(.q-table td:nth-child(2)) {
left: 86px;
width: 150px;
min-width: 150px;
max-width: 150px;
}
.product-breakdown-table.compact-detail-columns :deep(.q-table th:nth-child(3)),
.product-breakdown-table.compact-detail-columns :deep(.q-table td:nth-child(3)) {
left: 236px;
width: 112px;
min-width: 112px;
max-width: 112px;
}
.product-breakdown-table.compact-detail-columns :deep(.q-table th:nth-child(4)),
.product-breakdown-table.compact-detail-columns :deep(.q-table td:nth-child(4)) {
left: 348px;
width: 132px;
min-width: 132px;
max-width: 132px;
box-shadow: 8px 0 10px -10px rgba(17, 24, 39, 0.45);
}
.product-breakdown-table.product-detail-table :deep(.q-table) {
min-width: 2620px;
}
@@ -6198,10 +6420,14 @@ onBeforeUnmount(() => {
font-variant-numeric: tabular-nums;
}
.product-breakdown-table:not(.product-detail-table) :deep(.q-table th:nth-child(n+11):not(.text-right)),
.product-breakdown-table:not(.product-detail-table) :deep(.q-table td:nth-child(n+11):not(.text-right)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table th:nth-child(n+11):not(.text-right)),
.product-breakdown-table:not(.product-detail-table):not(.compact-detail-columns) :deep(.q-table td:nth-child(n+11):not(.text-right)),
.product-breakdown-table.compact-detail-columns :deep(.q-table th:nth-child(n+5):not(.text-right)),
.product-breakdown-table.compact-detail-columns :deep(.q-table td:nth-child(n+5):not(.text-right)),
.sticky-dim-table.sticky-dim-3 :deep(.q-table th:nth-child(n+4):not(.text-right)),
.sticky-dim-table.sticky-dim-3 :deep(.q-table td:nth-child(n+4):not(.text-right)),
.sticky-dim-table.sticky-dim-4 :deep(.q-table th:nth-child(n+5):not(.text-right)),
.sticky-dim-table.sticky-dim-4 :deep(.q-table td:nth-child(n+5):not(.text-right)),
.sticky-dim-table.sticky-dim-5 :deep(.q-table th:nth-child(n+6):not(.text-right)),
.sticky-dim-table.sticky-dim-5 :deep(.q-table td:nth-child(n+6):not(.text-right)),
.sticky-dim-table.sticky-dim-6 :deep(.q-table th:nth-child(n+7):not(.text-right)),
@@ -6281,6 +6507,8 @@ onBeforeUnmount(() => {
.sticky-dim-table.sticky-dim-3 :deep(.q-table th:nth-child(-n+3)),
.sticky-dim-table.sticky-dim-3 :deep(.q-table td:nth-child(-n+3)),
.sticky-dim-table.sticky-dim-4 :deep(.q-table th:nth-child(-n+4)),
.sticky-dim-table.sticky-dim-4 :deep(.q-table td:nth-child(-n+4)),
.sticky-dim-table.sticky-dim-5 :deep(.q-table th:nth-child(-n+5)),
.sticky-dim-table.sticky-dim-5 :deep(.q-table td:nth-child(-n+5)),
.sticky-dim-table.sticky-dim-6 :deep(.q-table th:nth-child(-n+6)),
@@ -6300,6 +6528,7 @@ onBeforeUnmount(() => {
}
.sticky-dim-table.sticky-dim-3 :deep(.q-table th:nth-child(-n+3)),
.sticky-dim-table.sticky-dim-4 :deep(.q-table th:nth-child(-n+4)),
.sticky-dim-table.sticky-dim-5 :deep(.q-table th:nth-child(-n+5)),
.sticky-dim-table.sticky-dim-6 :deep(.q-table th:nth-child(-n+6)),
.sticky-dim-table.sticky-dim-7 :deep(.q-table th:nth-child(-n+7)),
@@ -6317,6 +6546,8 @@ onBeforeUnmount(() => {
.sticky-dim-table.sticky-dim-3 :deep(.q-table th:nth-child(3)),
.sticky-dim-table.sticky-dim-3 :deep(.q-table td:nth-child(3)),
.sticky-dim-table.sticky-dim-4 :deep(.q-table th:nth-child(4)),
.sticky-dim-table.sticky-dim-4 :deep(.q-table td:nth-child(4)),
.sticky-dim-table.sticky-dim-5 :deep(.q-table th:nth-child(5)),
.sticky-dim-table.sticky-dim-5 :deep(.q-table td:nth-child(5)),
.sticky-dim-table.sticky-dim-6 :deep(.q-table th:nth-child(6)),
+9 -25
View File
@@ -423,7 +423,6 @@ const productImageListByCode = ref({})
const productImageListLoading = ref({})
const productImageFallbackByKey = ref({})
const productImageContentLoading = ref({})
const productImageBlobUrls = ref([])
const productImageListBlockedUntil = ref(0)
const productCardDialog = ref(false)
const productCardData = ref({})
@@ -702,24 +701,13 @@ function clearGalleryQueryIndex() {
async function resolveProductImageUrlForCarousel(item) {
const resolved = resolveProductImageUrl(item)
const contentUrl = String(resolved.contentUrl || '').trim()
if (contentUrl) return contentUrl
const directUrl = String(resolved.fullUrl || resolved.thumbUrl || resolved.publicUrl || '').trim()
if (directUrl) return directUrl
const contentUrl = String(resolved.contentUrl || '').trim()
if (contentUrl) {
try {
const blobRes = await api.get(contentUrl, { baseURL: '', responseType: 'blob' })
const blob = blobRes?.data
if (blob instanceof Blob) {
const objectUrl = URL.createObjectURL(blob)
productImageBlobUrls.value.push(objectUrl)
return objectUrl
}
} catch {
// fall through to public url
}
}
return contentUrl
return ''
}
function getProductImageUrl(code, color, secondColor = '', dim1Id = '', dim3Id = '') {
@@ -769,9 +757,9 @@ async function flushProductImageBatch() {
const list = Array.isArray(item.images) ? item.images : []
const first = list[0] || null
const resolved = resolveProductImageUrl(first)
const url = resolved.thumbUrl || resolved.fullUrl || resolved.publicUrl || resolved.contentUrl || ''
const url = resolved.contentUrl || resolved.thumbUrl || resolved.fullUrl || resolved.publicUrl || ''
productImageCache.value[key] = String(url || '').trim()
productImageFallbackByKey.value[key] = resolved.fullUrl || resolved.publicUrl || resolved.contentUrl || ''
productImageFallbackByKey.value[key] = resolved.thumbUrl || resolved.fullUrl || resolved.publicUrl || ''
if (queued) productImageListByCode.value[queued.listKey] = list
delete productImageLoading.value[key]
}
@@ -860,11 +848,11 @@ async function ensureProductImage(code, color, secondColor = '', dim1Id = '', di
productImageCache.value[key] = String(
preferredCardUrl ||
primaryResolved.fullUrl || primaryResolved.publicUrl || primaryResolved.thumbUrl || primaryResolved.contentUrl ||
secondaryResolved.fullUrl || secondaryResolved.publicUrl || secondaryResolved.thumbUrl || secondaryResolved.contentUrl ||
primaryResolved.contentUrl || primaryResolved.fullUrl || primaryResolved.publicUrl || primaryResolved.thumbUrl ||
secondaryResolved.contentUrl || secondaryResolved.fullUrl || secondaryResolved.publicUrl || secondaryResolved.thumbUrl ||
''
).trim()
productImageFallbackByKey.value[key] = primaryResolved.fullUrl || primaryResolved.publicUrl || primaryResolved.contentUrl || secondaryResolved.fullUrl || secondaryResolved.publicUrl || secondaryResolved.contentUrl || ''
productImageFallbackByKey.value[key] = primaryResolved.fullUrl || primaryResolved.publicUrl || primaryResolved.thumbUrl || secondaryResolved.fullUrl || secondaryResolved.publicUrl || secondaryResolved.thumbUrl || ''
} catch (err) {
console.warn('[ProductStockByAttributes] product image fetch failed', { code, color, err })
productImageCache.value[key] = ''
@@ -1576,10 +1564,6 @@ onUnmounted(() => {
clearTimeout(filterOptionsDebounceTimer)
filterOptionsDebounceTimer = null
}
for (const url of productImageBlobUrls.value) {
try { URL.revokeObjectURL(url) } catch {}
}
productImageBlobUrls.value = []
})
</script>
+9 -25
View File
@@ -390,7 +390,6 @@ const productImageListByCode = ref({})
const productImageListLoading = ref({})
const productImageFallbackByKey = ref({})
const productImageContentLoading = ref({})
const productImageBlobUrls = ref([])
const productImageListBlockedUntil = ref(0)
const productCardDialog = ref(false)
const productCardData = ref({})
@@ -681,24 +680,13 @@ function clearGalleryQueryIndex() {
async function resolveProductImageUrlForCarousel(item) {
const resolved = resolveProductImageUrl(item)
const contentUrl = String(resolved.contentUrl || '').trim()
if (contentUrl) return contentUrl
const directUrl = String(resolved.fullUrl || resolved.thumbUrl || resolved.publicUrl || '').trim()
if (directUrl) return directUrl
const contentUrl = String(resolved.contentUrl || '').trim()
if (contentUrl) {
try {
const blobRes = await api.get(contentUrl, { baseURL: '', responseType: 'blob' })
const blob = blobRes?.data
if (blob instanceof Blob) {
const objectUrl = URL.createObjectURL(blob)
productImageBlobUrls.value.push(objectUrl)
return objectUrl
}
} catch {
// fall through to public url
}
}
return contentUrl
return ''
}
function getProductImageUrl(code, color, secondColor = '', dim1Id = '', dim3Id = '') {
@@ -748,9 +736,9 @@ async function flushProductImageBatch() {
const list = Array.isArray(item.images) ? item.images : []
const first = list[0] || null
const resolved = resolveProductImageUrl(first)
const url = resolved.thumbUrl || resolved.fullUrl || resolved.publicUrl || resolved.contentUrl || ''
const url = resolved.contentUrl || resolved.thumbUrl || resolved.fullUrl || resolved.publicUrl || ''
productImageCache.value[key] = String(url || '').trim()
productImageFallbackByKey.value[key] = resolved.fullUrl || resolved.publicUrl || resolved.contentUrl || ''
productImageFallbackByKey.value[key] = resolved.thumbUrl || resolved.fullUrl || resolved.publicUrl || ''
if (queued) productImageListByCode.value[queued.listKey] = list
delete productImageLoading.value[key]
}
@@ -836,11 +824,11 @@ async function ensureProductImage(code, color, secondColor = '', dim1Id = '', di
const secondaryResolved = resolveProductImageUrl(secondaryItem)
productImageCache.value[key] = String(
preferredCardUrl ||
primaryResolved.fullUrl || primaryResolved.publicUrl || primaryResolved.thumbUrl || primaryResolved.contentUrl ||
secondaryResolved.fullUrl || secondaryResolved.publicUrl || secondaryResolved.thumbUrl || secondaryResolved.contentUrl ||
primaryResolved.contentUrl || primaryResolved.fullUrl || primaryResolved.publicUrl || primaryResolved.thumbUrl ||
secondaryResolved.contentUrl || secondaryResolved.fullUrl || secondaryResolved.publicUrl || secondaryResolved.thumbUrl ||
''
).trim()
productImageFallbackByKey.value[key] = primaryResolved.fullUrl || primaryResolved.publicUrl || primaryResolved.contentUrl || secondaryResolved.fullUrl || secondaryResolved.publicUrl || secondaryResolved.contentUrl || ''
productImageFallbackByKey.value[key] = primaryResolved.fullUrl || primaryResolved.publicUrl || primaryResolved.thumbUrl || secondaryResolved.fullUrl || secondaryResolved.publicUrl || secondaryResolved.thumbUrl || ''
} catch (err) {
console.warn('[ProductStockQuery] product image fetch failed', { code, color, err })
productImageCache.value[key] = ''
@@ -1374,10 +1362,6 @@ function resetForm() {
onUnmounted(() => {
window.removeEventListener('mousemove', onFullscreenMouseMove)
window.removeEventListener('mouseup', onFullscreenMouseUp)
for (const url of productImageBlobUrls.value) {
try { URL.revokeObjectURL(url) } catch {}
}
productImageBlobUrls.value = []
})
onMounted(async () => {
@@ -40,6 +40,14 @@
:loading="loading"
@click="fetchRows"
/>
<q-btn
label="Excel'e Aktar"
icon="download"
color="primary"
outline
:disable="loading || rows.length === 0"
@click="exportVisibleRows"
/>
</div>
</div>
</div>
@@ -141,7 +149,7 @@
</template>
<script setup>
import { computed, onMounted, reactive, ref, watch } from 'vue'
import { computed, nextTick, onMounted, reactive, ref, watch } from 'vue'
import { useRouter } from 'vue-router'
import { usePermission } from 'src/composables/usePermission'
import { get, extractApiErrorDetail } from 'src/services/api'
@@ -186,6 +194,30 @@ const columns = [
]
const columnFilters = reactive({})
const LIST_STATE_STORAGE_KEY = 'bssapp:production-product-costing:has-cost-list-state:v1'
function persistListState () {
try {
sessionStorage.setItem(LIST_STATE_STORAGE_KEY, JSON.stringify({
filters: { search: String(filters.search || '') },
columnFilters: JSON.parse(JSON.stringify(columnFilters)),
pagination: { ...tablePagination.value }
}))
} catch {}
}
function restoreListState () {
try {
const raw = sessionStorage.getItem(LIST_STATE_STORAGE_KEY)
if (!raw) return
const saved = JSON.parse(raw)
filters.search = String(saved?.filters?.search || '')
Object.assign(columnFilters, saved?.columnFilters && typeof saved.columnFilters === 'object' ? saved.columnFilters : {})
if (saved?.pagination && typeof saved.pagination === 'object') {
tablePagination.value = { ...tablePagination.value, ...saved.pagination }
}
} catch {}
}
function getColumnFilter (name) {
if (!columnFilters[name]) {
@@ -293,9 +325,11 @@ function clearAllColumnFilters () {
}
let searchTimer = null
let filterWatchEnabled = false
watch(
() => filters.search,
() => {
if (!filterWatchEnabled) return
clearTimeout(searchTimer)
searchTimer = setTimeout(() => {
fetchRows()
@@ -348,19 +382,66 @@ function clearFilters () {
fetchRows()
}
function escapeExcelCsvCell (value) {
let text = String(value ?? '')
// Prevent spreadsheet applications from evaluating data as a formula.
if (/^[=+\-@]/.test(text)) text = `'${text}`
return `"${text.replace(/"/g, '""')}"`
}
const excelNumericColumns = new Set(['lTutarTL', 'lTutarUSD', 'lTutarEURO'])
function formatExcelCsvCell (col, rawValue, displayValue) {
if (excelNumericColumns.has(col?.name)) {
const numericValue = Number(rawValue)
if (Number.isFinite(numericValue)) return String(numericValue).replace('.', ',')
}
return escapeExcelCsvCell(displayValue)
}
function exportVisibleRows () {
const visibleRows = Array.isArray(rows.value) ? rows.value : []
if (visibleRows.length === 0) return
const exportColumns = columns.filter(col => col.name !== 'open')
const csvLines = [
exportColumns.map(col => escapeExcelCsvCell(col.label)).join(';'),
...visibleRows.map(row => exportColumns.map(col => {
const rawValue = typeof col.field === 'function' ? col.field(row) : row?.[col.field]
const displayValue = typeof col.format === 'function' ? col.format(rawValue, row) : rawValue
return formatExcelCsvCell(col, rawValue, displayValue)
}).join(';'))
]
const blob = new Blob([`\uFEFF${csvLines.join('\r\n')}`], { type: 'text/csv;charset=utf-8;' })
const url = URL.createObjectURL(blob)
const link = document.createElement('a')
link.href = url
link.download = `mevcut_maliyetli_urunler_${new Date().toISOString().slice(0, 10)}.csv`
document.body.appendChild(link)
link.click()
link.remove()
URL.revokeObjectURL(url)
}
function openRow (row) {
const urunKodu = String(row?.UrunKodu || '').trim()
if (!urunKodu) return
persistListState()
router.push({
name: 'production-product-costing-has-cost-history',
query: { urun_kodu: urunKodu }
})
}
onMounted(() => {
onMounted(async () => {
if (!canReadOrder.value) return
fetchRows()
restoreListState()
await nextTick()
filterWatchEnabled = true
await fetchRows()
})
</script>
@@ -1557,8 +1557,15 @@ function ensureBeforeUnloadGuard (enabled) {
return ''
}
}
function shouldIncludeRowInCostingTotal (row) {
// CM1/CM2 are labor-cost groups and always contribute to costing. For all
// other groups the explicit "Maliyete Dahil" selection is authoritative.
return isCMGroupName(row?.sAciklama3) ||
normalizeBooleanFlag(row?.maliyeteDahil ?? row?.maliyete_dahil ?? row?.Maliyete_dahil)
}
const toolbarSummary = computed(() => flatDetailRows.value.reduce((acc, row) => {
if (!row?.maliyeteDahil) return acc
if (!shouldIncludeRowInCostingTotal(row)) return acc
acc.tryTotal += resolveRowTRYTutar(row)
acc.usdTotal += resolveRowUSDTutar(row)
acc.eurTotal += resolveRowEURTutar(row)
@@ -2848,12 +2855,8 @@ function resolveRowUSDTutar (row) {
return Number.isFinite(calc) ? calc : 0
}
function shouldIgnoreGroupMaliyeteDahil (grp) {
return isCMGroupName(grp?.sAciklama3)
}
function shouldIncludeRowInGroupTotal (grp, row) {
return shouldIgnoreGroupMaliyeteDahil(grp) || normalizeBooleanFlag(row?.maliyeteDahil)
function shouldIncludeRowInGroupTotal (_grp, row) {
return shouldIncludeRowInCostingTotal(row)
}
function resolveGroupTRYTutar (grp) {
@@ -3928,10 +3931,14 @@ async function ensureNoCostRequiredRowsFromMappings (mappings) {
const groupName = normalizeGroupName(meta?.groupName || '')
const hammaddeAdi = String(meta?.hammaddeAdi || '').trim()
const effectiveGroupName = groupName || 'TANIMSIZ'
const mtBolumID = (meta?.mtBolumID > 0 ? meta.mtBolumID : mappingMtBolumID) || 0
const metaParcaCandidate = normalizeGroupName((meta?.parcaAdi || '').trim())
// Defensive: if backend/lookup accidentally returns group label (DT/TP/...) as part name, ignore it.
const desiredParcaAdi = normalizeGroupName((metaParcaCandidate && !isKnownGroupName(metaParcaCandidate)) ? metaParcaCandidate : mappingParcaAdi)
// The product-type mapping is authoritative for the required part. A raw
// material type can be required for multiple parts, while its master
// record only carries one default MT section. Using that default here
// incorrectly made an existing recipe row satisfy every mapped part.
const mtBolumID = mappingMtBolumID > 0 ? mappingMtBolumID : (meta?.mtBolumID || 0)
const desiredParcaAdi = mappingMtBolumID > 0
? mappingParcaAdi
: normalizeGroupName(meta?.parcaAdi || mappingParcaAdi)
const anyMatch = flatDetailRows.value.find(r => {
if (normalizeHammaddeNo(r?.nHammaddeTuruNo) !== hNo) return false
@@ -5062,13 +5069,31 @@ async function saveChanges () {
// If we created a new OnML (no-cost), switch to has-cost detail mode.
if (isNoCostDetail.value && newOnMLNo > 0) {
router.replace({
await router.replace({
name: 'production-product-costing-has-cost-detail',
query: {
n_onml_no: String(newOnMLNo),
urun_kodu: String(header?.UrunKodu || productCode.value || '').trim()
}
})
$q.dialog({
title: 'Maliyet Kaydedildi',
message: 'Maliyeti olmayan urunler listesine donup kaldiginiz yerden devam etmek ister misiniz?',
ok: {
label: 'Listeye Don',
color: 'primary',
icon: 'arrow_back'
},
cancel: {
label: 'Bu Sayfada Devam Et',
color: 'grey-7',
flat: true
},
persistent: true
}).onOk(() => {
router.push({ name: 'production-product-costing-no-cost' })
})
return
}
@@ -5078,6 +5103,24 @@ async function saveChanges () {
window.setTimeout(() => {
try { refreshLast10Warnings() } catch {}
}, 1200)
$q.dialog({
title: 'Maliyet Guncellendi',
message: 'Mevcut maliyeti olan urunler listesine donup kaldiginiz yerden devam etmek ister misiniz?',
ok: {
label: 'Listeye Don',
color: 'primary',
icon: 'arrow_back'
},
cancel: {
label: 'Bu Sayfada Devam Et',
color: 'grey-7',
flat: true
},
persistent: true
}).onOk(() => {
router.push({ name: 'production-product-costing-has-cost' })
})
} catch (e) {
// Surface backend message (http.Error text) when available.
const msg = String(
@@ -49,6 +49,14 @@
:loading="loading"
@click="fetchRows"
/>
<q-btn
label="Excel'e Aktar"
icon="download"
color="primary"
outline
:disable="loading || rows.length === 0"
@click="exportVisibleRows"
/>
<div class="npc-missing-count text-caption text-grey-7">
Maliyeti Girilmemis Satir Sayisi: <b>{{ missingCostRowCount }}</b>
</div>
@@ -176,7 +184,7 @@
</template>
<script setup>
import { computed, onMounted, reactive, ref, watch } from 'vue'
import { computed, nextTick, onMounted, reactive, ref, watch } from 'vue'
import { useQuasar } from 'quasar'
import { useRouter } from 'vue-router'
import { usePermission } from 'src/composables/usePermission'
@@ -262,6 +270,34 @@ const columns = [
]
const columnFilters = reactive({})
const LIST_STATE_STORAGE_KEY = 'bssapp:production-product-costing:no-cost-list-state:v1'
function persistListState () {
try {
sessionStorage.setItem(LIST_STATE_STORAGE_KEY, JSON.stringify({
filters: {
search: String(filters.search || ''),
fromDate: String(filters.fromDate || '')
},
columnFilters: JSON.parse(JSON.stringify(columnFilters)),
scrollY: Number(window.scrollY || 0)
}))
} catch {}
}
function restoreListState () {
try {
const raw = sessionStorage.getItem(LIST_STATE_STORAGE_KEY)
if (!raw) return 0
const saved = JSON.parse(raw)
filters.search = String(saved?.filters?.search || '')
filters.fromDate = String(saved?.filters?.fromDate || '2025-06-01')
Object.assign(columnFilters, saved?.columnFilters && typeof saved.columnFilters === 'object' ? saved.columnFilters : {})
return Number(saved?.scrollY || 0)
} catch {
return 0
}
}
function getColumnFilter (name) {
if (!columnFilters[name]) {
@@ -384,9 +420,11 @@ function clearAllColumnFilters () {
}
let searchTimer = null
let filterWatchEnabled = false
watch(
() => filters.search,
() => {
if (!filterWatchEnabled) return
clearTimeout(searchTimer)
searchTimer = setTimeout(() => {
fetchRows()
@@ -397,6 +435,7 @@ watch(
watch(
() => filters.fromDate,
() => {
if (!filterWatchEnabled) return
fetchRows()
}
)
@@ -430,6 +469,49 @@ function clearFilters () {
fetchRows()
}
function escapeExcelCsvCell (value) {
let text = String(value ?? '')
// Prevent spreadsheet applications from evaluating data as a formula.
if (/^[=+\-@]/.test(text)) text = `'${text}`
return `"${text.replace(/"/g, '""')}"`
}
function formatExcelCsvCell (col, rawValue, displayValue) {
if (col?.name === 'lMMiktar_G') {
const numericValue = Number(rawValue)
if (Number.isFinite(numericValue)) return String(numericValue).replace('.', ',')
}
return escapeExcelCsvCell(displayValue)
}
function exportVisibleRows () {
const visibleRows = Array.isArray(rows.value) ? rows.value : []
if (visibleRows.length === 0) {
$q.notify({ type: 'warning', message: 'Excel aktarimi icin ekranda satir bulunamadi.', position: 'top-right' })
return
}
const exportColumns = columns.filter(col => col.name !== 'open')
const csvLines = [
exportColumns.map(col => escapeExcelCsvCell(col.label)).join(';'),
...visibleRows.map(row => exportColumns.map(col => {
const rawValue = typeof col.field === 'function' ? col.field(row) : row?.[col.field]
const displayValue = typeof col.format === 'function' ? col.format(rawValue, row) : rawValue
return formatExcelCsvCell(col, rawValue, displayValue)
}).join(';'))
]
const blob = new Blob([`\uFEFF${csvLines.join('\r\n')}`], { type: 'text/csv;charset=utf-8;' })
const url = URL.createObjectURL(blob)
const link = document.createElement('a')
link.href = url
link.download = `maliyeti_olmayan_urunler_${new Date().toISOString().slice(0, 10)}.csv`
document.body.appendChild(link)
link.click()
link.remove()
URL.revokeObjectURL(url)
}
function openRow (row) {
const productCode = String(row?.sMModelKodu || '').trim()
const recipeCode = String(row?.sKodu || '').trim()
@@ -449,6 +531,8 @@ function openRow (row) {
recipe_code: recipeCode
})
persistListState()
router.push({
name: 'production-product-costing-has-cost-detail',
query: {
@@ -460,9 +544,16 @@ function openRow (row) {
})
}
onMounted(() => {
onMounted(async () => {
if (!canReadOrder.value) return
fetchRows()
const savedScrollY = restoreListState()
await nextTick()
filterWatchEnabled = true
await fetchRows()
if (savedScrollY > 0) {
await nextTick()
window.scrollTo({ top: savedScrollY, behavior: 'auto' })
}
})
</script>