package warehouse

import (
	"sort"
	"strings"

	"git.mchus.pro/mchus/priceforge/internal/lotmatch"
	"git.mchus.pro/mchus/priceforge/internal/models"
	"gorm.io/gorm"
)

type SnapshotItem struct {
	LotName     string
	Price       float64
	PriceMethod string
	Category    string // Historical snapshot of lot_category
}

type weightedPricePoint struct {
	price  float64
	weight float64
}

// ComputePricelistItemsFromStockLog builds warehouse snapshot items from stock_log.
func ComputePricelistItemsFromStockLog(db *gorm.DB) ([]SnapshotItem, error) {
	type stockRow struct {
		Partnumber string   `gorm:"column:partnumber"`
		Price      float64  `gorm:"column:price"`
		Qty        *float64 `gorm:"column:qty"`
	}

	var rows []stockRow
	if err := db.Table(models.StockLog{}.TableName()).Select("partnumber, price, qty").Where("price > 0").Scan(&rows).Error; err != nil {
		return nil, err
	}

	resolver, err := lotmatch.NewLotResolverFromDB(db)
	if err != nil {
		return nil, err
	}

	grouped := make(map[string][]weightedPricePoint)
	for _, row := range rows {
		pn := strings.TrimSpace(row.Partnumber)
		if pn == "" || row.Price <= 0 {
			continue
		}
		lot, _, err := resolver.Resolve(pn)
		if err != nil || strings.TrimSpace(lot) == "" {
			continue
		}
		weight := 0.0
		if row.Qty != nil && *row.Qty > 0 {
			weight = *row.Qty
		}
		grouped[lot] = append(grouped[lot], weightedPricePoint{price: row.Price, weight: weight})
	}

	items := make([]SnapshotItem, 0, len(grouped))
	for lot, values := range grouped {
		price := weightedAverage(values)
		if price <= 0 {
			continue
		}
		items = append(items, SnapshotItem{LotName: lot, Price: price, PriceMethod: "weighted_avg", Category: ""})
	}

	// Load categories for all lots in a single query
	if len(items) > 0 {
		lotNames := make([]string, 0, len(items))
		lotToIdx := make(map[string]int, len(items))
		for i, item := range items {
			lotToIdx[item.LotName] = i
			lotNames = append(lotNames, item.LotName)
		}

		var categories []struct {
			LotName     string
			LotCategory string
		}
		if err := db.Table("lot").Select("lot_name, lot_category").Where("lot_name IN ?", lotNames).Scan(&categories).Error; err == nil {
			for _, cat := range categories {
				if idx, ok := lotToIdx[cat.LotName]; ok {
					items[idx].Category = cat.LotCategory
				}
			}
		}
		defaultCategory := models.DefaultLotCategoryCode
		missingCategoryLots := make([]string, 0)
		for i := range items {
			if strings.TrimSpace(items[i].Category) == "" {
				items[i].Category = defaultCategory
				missingCategoryLots = append(missingCategoryLots, items[i].LotName)
			}
		}
		if len(missingCategoryLots) > 0 {
			ensureCategoryExists(db, defaultCategory)
			_ = db.Model(&models.Lot{}).
				Where("lot_name IN ?", missingCategoryLots).
				Update("lot_category", defaultCategory).Error
		}
	}

	sort.Slice(items, func(i, j int) bool { return items[i].LotName < items[j].LotName })
	return items, nil
}

func ensureCategoryExists(db *gorm.DB, code string) {
	var count int64
	if err := db.Model(&models.Category{}).Where("code = ?", code).Count(&count).Error; err != nil || count > 0 {
		return
	}
	var maxOrder int
	if err := db.Model(&models.Category{}).Select("COALESCE(MAX(display_order), 0)").Scan(&maxOrder).Error; err != nil {
		return
	}
	_ = db.Create(&models.Category{
		Code:         code,
		Name:         code,
		NameRu:       code,
		DisplayOrder: maxOrder + 1,
	}).Error
}

// LoadLotMetrics returns stock qty and partnumbers for selected lots.
// If latestOnly is true, qty/partnumbers from stock_log are calculated only for latest import date.
func LoadLotMetrics(db *gorm.DB, lotNames []string, latestOnly bool) (map[string]float64, map[string][]string, error) {
	qtyByLot := make(map[string]float64, len(lotNames))
	partnumbersByLot := make(map[string][]string, len(lotNames))
	if len(lotNames) == 0 {
		return qtyByLot, partnumbersByLot, nil
	}

	lotSet := make(map[string]struct{}, len(lotNames))
	for _, lot := range lotNames {
		trimmed := strings.TrimSpace(lot)
		if trimmed == "" {
			continue
		}
		lotSet[trimmed] = struct{}{}
	}

	resolver, err := lotmatch.NewLotResolverFromDB(db)
	if err != nil {
		return nil, nil, err
	}

	seenPN := make(map[string]map[string]struct{}, len(lotSet))
	addPartnumber := func(lotName, partnumber string) {
		lotName = strings.TrimSpace(lotName)
		partnumber = strings.TrimSpace(partnumber)
		if lotName == "" || partnumber == "" {
			return
		}
		if _, ok := lotSet[lotName]; !ok {
			return
		}
		if _, ok := seenPN[lotName]; !ok {
			seenPN[lotName] = map[string]struct{}{}
		}
		key := strings.ToLower(partnumber)
		if _, ok := seenPN[lotName][key]; ok {
			return
		}
		seenPN[lotName][key] = struct{}{}
		partnumbersByLot[lotName] = append(partnumbersByLot[lotName], partnumber)
	}

	var mappingRows []models.LotPartnumber
	if err := db.Select("partnumber, lot_name").Find(&mappingRows).Error; err != nil {
		return nil, nil, err
	}
	for _, row := range mappingRows {
		addPartnumber(row.LotName, row.Partnumber)
	}

	type stockRow struct {
		Partnumber string   `gorm:"column:partnumber"`
		Qty        *float64 `gorm:"column:qty"`
	}
	var stockRows []stockRow
	if latestOnly {
		err = db.Raw(`
			SELECT sl.partnumber, sl.qty
			FROM stock_log sl
			INNER JOIN (SELECT MAX(date) AS max_date FROM stock_log) md ON sl.date = md.max_date
		`).Scan(&stockRows).Error
	} else {
		err = db.Table(models.StockLog{}.TableName()).Select("partnumber, qty").Scan(&stockRows).Error
	}
	if err != nil {
		return nil, nil, err
	}

	for _, row := range stockRows {
		pn := strings.TrimSpace(row.Partnumber)
		if pn == "" {
			continue
		}
		lot, _, err := resolver.Resolve(pn)
		if err != nil {
			continue
		}
		if _, exists := lotSet[lot]; !exists {
			continue
		}
		if row.Qty != nil {
			qtyByLot[lot] += *row.Qty
		}
		addPartnumber(lot, pn)
	}

	for lot := range partnumbersByLot {
		sort.Slice(partnumbersByLot[lot], func(i, j int) bool {
			return strings.ToLower(partnumbersByLot[lot][i]) < strings.ToLower(partnumbersByLot[lot][j])
		})
	}

	return qtyByLot, partnumbersByLot, nil
}

func weightedMedian(values []weightedPricePoint) float64 {
	if len(values) == 0 {
		return 0
	}
	type pair struct {
		price  float64
		weight float64
	}
	items := make([]pair, 0, len(values))
	totalWeight := 0.0
	prices := make([]float64, 0, len(values))
	for _, v := range values {
		if v.price <= 0 {
			continue
		}
		prices = append(prices, v.price)
		if v.weight > 0 {
			items = append(items, pair{price: v.price, weight: v.weight})
			totalWeight += v.weight
		}
	}
	if totalWeight <= 0 {
		return median(prices)
	}
	sort.Slice(items, func(i, j int) bool {
		if items[i].price == items[j].price {
			return items[i].weight < items[j].weight
		}
		return items[i].price < items[j].price
	})
	threshold := totalWeight / 2.0
	acc := 0.0
	for _, it := range items {
		acc += it.weight
		if acc >= threshold {
			return it.price
		}
	}
	return items[len(items)-1].price
}

func median(values []float64) float64 {
	if len(values) == 0 {
		return 0
	}
	cp := append([]float64(nil), values...)
	sort.Float64s(cp)
	n := len(cp)
	if n%2 == 0 {
		return (cp[n/2-1] + cp[n/2]) / 2
	}
	return cp[n/2]
}
func weightedAverage(values []weightedPricePoint) float64 {
	if len(values) == 0 {
		return 0
	}
	sumWeighted := 0.0
	sumWeight := 0.0
	prices := make([]float64, 0, len(values))
	for _, v := range values {
		if v.price <= 0 {
			continue
		}
		prices = append(prices, v.price)
		if v.weight > 0 {
			sumWeighted += v.price * v.weight
			sumWeight += v.weight
		}
	}
	if sumWeight > 0 {
		return sumWeighted / sumWeight
	}
	return median(prices)
}