package pricing

import (
	"context"
	"fmt"
	"time"

	"github.com/sirupsen/logrus"
	"gorm.io/gorm"
)

// OptimizationStrategy represents pricing optimization strategies
type OptimizationStrategy string

const (
	StrategyRevenueMax     OptimizationStrategy = "revenue_maximization"
	StrategyMarketShare    OptimizationStrategy = "market_share"
	StrategyProfitMargin   OptimizationStrategy = "profit_margin"
	StrategyCompetitive    OptimizationStrategy = "competitive"
	StrategyChurnReduction OptimizationStrategy = "churn_reduction"
)

// PricingOptimizationService provides automated pricing optimization
type PricingOptimizationService struct {
	db     *gorm.DB
	logger *logrus.Logger
}

// NewPricingOptimizationService creates a new pricing optimization service
func NewPricingOptimizationService(db *gorm.DB, logger *logrus.Logger) *PricingOptimizationService {
	return &PricingOptimizationService{
		db:     db,
		logger: logger,
	}
}

// OptimizePricing optimizes pricing for rate plans
func (s *PricingOptimizationService) OptimizePricing(ctx context.Context, ratePlanIDs []string, strategy OptimizationStrategy) ([]*OptimizationResult, error) {
	results := make([]*OptimizationResult, 0)

	for _, ratePlanID := range ratePlanIDs {
		result, err := s.optimizeRatePlan(ctx, ratePlanID, strategy)
		if err != nil {
			s.logger.WithError(err).Error("Failed to optimize rate plan", "rate_plan_id", ratePlanID)
			continue
		}
		results = append(results, result)
	}

	return results, nil
}

// optimizeRatePlan optimizes a single rate plan
func (s *PricingOptimizationService) optimizeRatePlan(ctx context.Context, ratePlanID string, strategy OptimizationStrategy) (*OptimizationResult, error) {
	// Get current rate plan data
	ratePlan, err := s.getRatePlan(ctx, ratePlanID)
	if err != nil {
		return nil, err
	}

	// Get historical data
	historicalData, err := s.getHistoricalData(ctx, ratePlanID)
	if err != nil {
		return nil, err
	}

	// Calculate optimal price based on strategy
	optimalPrice := s.calculateOptimalPrice(ratePlan, historicalData, strategy)

	// Calculate expected outcomes
	expectedRevenue, expectedDemand := s.predictOutcomes(ratePlan, optimalPrice, historicalData)

	// Generate reasoning and recommendations
	reasoning, risks, recommendations := s.generateAnalysis(ratePlan, optimalPrice, strategy, historicalData)

	result := &OptimizationResult{
		RatePlanID:      ratePlanID,
		Strategy:        strategy,
		CurrentPrice:    ratePlan.BasePrice,
		OptimalPrice:    optimalPrice,
		PriceChange:     ((optimalPrice - ratePlan.BasePrice) / ratePlan.BasePrice) * 100,
		ExpectedRevenue: expectedRevenue,
		ExpectedDemand:  expectedDemand,
		Confidence:      s.calculateConfidence(historicalData),
		Reasoning:       reasoning,
		Risks:           risks,
		Recommendations: recommendations,
		GeneratedAt:     time.Now(),
	}

	return result, nil
}

// GetPricingMetrics returns pricing performance metrics
func (s *PricingOptimizationService) GetPricingMetrics(ctx context.Context, period string) (*PricingMetrics, error) {
	metrics := &PricingMetrics{
		Period:      period,
		GeneratedAt: time.Now(),
	}

	// Calculate total revenue
	var totalRevenue float64
	s.db.WithContext(ctx).Table("billing_transactions").
		Where("status = ? AND created_at BETWEEN ? AND ?", "completed",
			s.getPeriodStart(period), s.getPeriodEnd(period)).
		Select("COALESCE(SUM(amount), 0)").
		Scan(&totalRevenue)
	metrics.TotalRevenue = totalRevenue

	// Calculate total subscribers
	var totalSubs int64
	s.db.WithContext(ctx).Table("profiles").
		Where("status = ?", "active").
		Count(&totalSubs)
	metrics.TotalSubscribers = totalSubs

	// Calculate ARPU
	if totalSubs > 0 {
		metrics.ARPU = totalRevenue / float64(totalSubs)
	}

	// Calculate churn rate
	metrics.ChurnRate = s.calculateChurnRate(ctx, period)

	// Calculate price elasticity
	metrics.PriceElasticity = s.calculateElasticity(ctx, &RatePlan{})

	// Calculate competitive index
	metrics.CompetitiveIndex = s.calculateCompetitiveIndex(ctx, period)

	// Calculate optimization ROI
	metrics.OptimizationROI = s.calculateOptimizationROI(ctx, period)

	return metrics, nil
}

// ApplyOptimization applies pricing optimization
func (s *PricingOptimizationService) ApplyOptimization(ctx context.Context, result *OptimizationResult) error {
	// Update rate plan price
	err := s.db.WithContext(ctx).Table("rate_plans").
		Where("id = ?", result.RatePlanID).
		Updates(map[string]interface{}{
			"base_price": result.OptimalPrice,
			"updated_at": time.Now(),
		}).Error

	if err != nil {
		return fmt.Errorf("failed to update rate plan: %w", err)
	}

	// Log the optimization
	s.logger.WithFields(logrus.Fields{
		"rate_plan_id":     result.RatePlanID,
		"strategy":         result.Strategy,
		"old_price":        result.CurrentPrice,
		"new_price":        result.OptimalPrice,
		"price_change":     result.PriceChange,
		"expected_revenue": result.ExpectedRevenue,
	}).Info("Pricing optimization applied")

	return nil
}

// getRatePlan retrieves rate plan data
func (s *PricingOptimizationService) getRatePlan(ctx context.Context, ratePlanID string) (*RatePlan, error) {
	var ratePlan RatePlan
	err := s.db.WithContext(ctx).Where("id = ?", ratePlanID).First(&ratePlan).Error
	if err != nil {
		return nil, fmt.Errorf("rate plan not found: %w", err)
	}
	return &ratePlan, nil
}

// getHistoricalData retrieves historical pricing and demand data
func (s *PricingOptimizationService) getHistoricalData(_ context.Context, _ string) ([]HistoricalDataPoint, error) {
	// Get pricing history and subscription data
	var data []HistoricalDataPoint

	// This would query actual historical data
	// For now, return simulated data
	for i := 0; i < 12; i++ { // Last 12 months
		date := time.Now().AddDate(0, -i, 0)
		point := HistoricalDataPoint{
			Date:    date,
			Price:   10.0 + float64(i)*0.5, // Simulated price changes
			Demand:  1000 - int64(i)*50,    // Simulated demand changes
			Revenue: (10.0 + float64(i)*0.5) * float64(1000-int64(i)*50),
		}
		data = append(data, point)
	}

	return data, nil
}

// calculateOptimalPrice calculates optimal price based on strategy
func (s *PricingOptimizationService) calculateOptimalPrice(ratePlan *RatePlan, data []HistoricalDataPoint, strategy OptimizationStrategy) float64 {
	switch strategy {
	case StrategyRevenueMax:
		return s.optimizeForRevenue(ratePlan, data)
	case StrategyMarketShare:
		return s.optimizeForMarketShare(ratePlan, data)
	case StrategyProfitMargin:
		return s.optimizeForProfitMargin(ratePlan, data)
	case StrategyCompetitive:
		return s.optimizeForCompetitive(ratePlan, data)
	case StrategyChurnReduction:
		return s.optimizeForChurnReduction(ratePlan, data)
	default:
		return ratePlan.BasePrice
	}
}